fF ~ - ( ~ i4r -I

10 Prehistoric Anthropogenic Impacts to Local and Regional Faunas Are Not Ubiquitous

R Lee Lyman

Abstract Many zooarchaeologists have presented evidence indicating that preshyh i toric forag rs h ad Significant impacts on faunas The evidence has prompted the suggestion that anth ropogenic impacts are ubiqui tous In many times and places humans indeed influenced local faunal communities Research should not however be initia ted with the p reconceived notion that evidence of th il t influence wiIJ be fou nd in every collection of faunal r mains studied Some studies indicate minima l human influence and suggest that fa ilure to find c ishydence of human influence can be the res ult of methOdological artifacts use of data of insufficient (spatiotemporal) resolution and lise of data representing cases in which humans had minimal inJ1uence on faunas Reasons for lack of influence include alci1aeological monitoring perspective and harvest of indishyviduals whose abundance does not influence pI y availability

Ecologically inclined archaeologists or what we might today label thnobiologist ethnobotanists zo archaeologists and the like have long been

interested in the interactions between hLUnan and nonhuman organisms Beginshyning in the 1970s some of th se researchers adopted versions of optimal foraging theory (eg Krebs and Davies 1978 Pyke et al 1977) to assi t with understanding and explaining the interactions (Bayham 1979 Earle and Christenson 1980 Winshyterhalder and Smith 1981) Foraging theory ultimately came to provide a source of mod Is that explicitly relate var iables manifest by predators and thei r prey and the in teractions of the two (Broughton and OConnell 1999) The numerous studies that have to date beel perfom1ed under the guidance of foraging theory

The Archaeology of Anthropogenic Environments edited by Rebecca M Dean enter for Archae oshylogical rnves tigations Occasional Paper No 37 copy 2010 by the Board of Trustees Southern IlIinois University All rights reserved rSBN 978-0-88104-094-4

204

(Stephens an behavioral e( have providE archaeology

By thela prey interact behavioral e(

geograp hic a Jmet ki 1997 et al 1999 Si ers seem to i crage that ill when in the times and pL degree I sug notion that of falmal r n several rease

To date within the z growing (Bu 2003a 2004a as some earl lar instance J

for observec brand t and J Martin and ~ find ings of r growing wei nificant inflt are backed t are studies i found and cases where to me that tl influence on reveal how I such influen

I F

1 might not bE tive of anth

tpacts Are

ating that preshy has prompted any times and search should idence of that tudied Some ue to find evishyrtifacts use of I representing )1S fo r lack of Irvest of indishy

today label middote long been sms B gin-al foragi ng

jerstanding 11980 Winshyde a sou ro I their prey ~ numerous ging theory

for Archaeoshyes Southell1

Pre~storic Anthropogenic Impacts Are Not Ubiquitous I 205

(Stephens and Krebs 1986) are now often grouped und r the banner of human behavioral ecology (Winterhalder and Smith 2000) and while many such studies have provided signi fi cant insights to human behaviors in ethnographic settings archaeology ha it share of the e studi s (Bird and OConnell 2006)

By the last decad of the twentieth century the plethora of research on predatorshyprey interactions perform d by zooarchaeologists under the guidance of human behavioral ecology prompted som researchers to synthesize evidence from large geographic areas (eg Cannon 2000 rayson 2001 Hildebrandt and Jones 2002 Janetski 1997 Kay 1994 Martin and Szuter 1999a 1999b Stiner et al 2000 Stiner et a1 1999 Szuter and Bayham 1989)_ The syntheses presented by thes re earchshyers seem to imply if not by word then by spatiotemporal breadth of their covshyerage that anthropogenic impacts are detectable nearly everywhere and ev ryshywhen in the zooarchaeological record While not denying that hwnans in many times and places likely influenced local and regi nal faunas to a greater or lesser degree I suggest th at we should not go into our research with the preconceived notion that w vill find evidence of that influenc in each and every collection of faunal remains we study We may find what J think of as false signals for any of several reasons What Lhose reasons are is one issue I explore here

To date few studies have failed t find evidence of anthropogenic influences within the zooarcha ological record but the number of such studies is slowly growing (Butler and Campb 11 2004 Byers and Broughton 2004 Lyman 1995 2003a 2004a Lym n and Wolverton 2002 Wolverton 2005) Interestingly whereshyas some early reports that anthropogeni infl uence wa not evident in a particushylar instance met with insistence that prehistoric people were indeed responsib le for observed changes in taxon m ic relative abundances over time (eg H ildeshybrand t and Jones 2002 Jones and Hildebrand t 1995 Laliberte and Ripple 2003 Martin and Szuter 2002) such disagreem nt has no t yet surfaced r garding later fi nding of no significant anthropogenic influence Perhaps this is because of the growing weight of the evidence or because of the recency of the reports of no sigshyni ficant ll1flu nee or because analyses are more sophis ticated theoretically and are backed by large data set Whatever the case given the facts that first th re are studies in which no evidence of an thropogenic influence on faunas has been found and second there is some (perhaps small) d gree of doubt about those ases where evidence of anthropogenic influence is appar ntly lacking it seems

to me that the is ue of why we might not always find evidence of nthr pogenic influenc on prehistoric faunas should be explored Figuring this out may in turn reveal how false signals of anthropogenic influence (or false signals of the lack of such influence) may be created These are the centra l issues I address here

Detecting Anthropogenic Influence on Prehis toric Faunas

To id ntify reasons as to why evidence of anthropogenic influence might not be found the zooarchaeological evidence uSLlally called upon as indIcashytive of anthropogenic influence on prehistoriC faunas mLlst be identified Given

206 I R L Lyman

that the typica l signature evid nce was recognized as such in light of fo raging theory and behavioral ecology I start there The nuances of th method and the eviden e should by now be well known gi en the xlensive pertinent li teralure so I only outline the basics Th pr y-choice model holds tha t human foragers will preferentially exploit the largest prey firs t because these taxa are the most valushyable all else being equal (Ugan 2005) If valuable (large) prey decrease in availabilshyity and thus the frequency at which Lhey are encountered decreases then foragers will turn to progreSSively more kinds of less va lu ble generally smaller preyshyeach individual considered less valuabl than a single larger individual-to mainshylain a constant level of nutrition Thus the ratio of large prey to small p lus large prey will fluctuate over time decreasiJlg (the proportion becomiJlg progpssively smaller than 10) as large prey become less available relative to small prey and increasing (becoming progr sively closer to 10) as large prey become mor availshyable relative to small pr y Typically animal prey ab W1dance me sured as the number of id ntified specimens ( lSF) are re ldered as an index value between oand 10 that xpresses the proportion of large prey relative to small plus large prey Plotting each index value against the temporal midpoint of the time span during which the assemblage of faunal remains on which the value is based was d pusited-whether stra tigraphically radiometrically or cultu rally dClerminedshyin a bivaria te scatterpJot visually reveals what are int rpreted to be changes in prey re turn rates that are in turn interpreted to reflect cha nges in prey avai lability or abundance Interp retation of the atterp lot is sometimes aided by calculating a simple best-fi t r gression li ne through the point scatter in order to highlight temporal trends

The model and analy tica l protocol just described identi fy an empirical manshyitestation of a particular signatu re criterion of anthropogenic influences on (pashyleo)faunas (Grayson 2001) As a result of their selective exploitation ot prey taxa that provided eilher or both low cos ts and high relurns humans with primitive technologies caused changes in fau na l taxonomic richness and cv nness indeshypendent of changes in climate and tech nology Humans therefore had to alter what they were expl iling as a response to a change in the availabili ty of animal prey that they themselves had caused The signatur i that over time large prey decrease in re lative abundance in the zooarchaeological record and small prey increase in relative abundan c as humans adapt to an anthropogenic infl uence on prey availability

The voice of caution requires that if one attributes increasing relative abunshydanc s of small low-value prey taxa to human exp loitation having depressed the availability of1arge high-value prey taxa alternative causes of depression of high-value preymust be disconfirmed Alternative causes can in lude cl anges in technology (eg shift fro m atlatl and dart to bow and arrow) changes in how tecl1l1ology was us gtd (eg h ift from individual h unters t communal hunts) and environmentally or dim tically driven changes in taxonomic abund ances (Gra son and ann on 1999) Disconfirmation of these al ternate causes may not however be as easy as originally thought Recent etluloarchaeological research among foragers indicates that sh ifts in technology may be driven by seasonal

shifts in prey variation in ao es in relati e al anthropogenic cal signatures where the sigr that the halle will demand r

It has aisl scu re a signal ally tallied b )

kinds of resou tortoises shell and fl ing bir In addi tion f( events with dt p ra l un its ar r-mains ty pic ing m ass-kill Dlpech 1998 represented b genic infiuen( correspondin behavioral ch

Finally S

lhey represen of shifls in cal sisten Uy appi lytical spatial environmentlt as a tempora mullipl ites create fa Ise si Cannon 2000 (total popula predation in I

sion in the lat The imn

difficulties m faunas They be evidence I

the remainde problems Th and undersc( genically in fl

light of foraging method and the t inent literature 1at1 foragers will e the most valushyease in availabilshyes then f ragcrs smaller preyshy

idual-to m ainshysmall pl us large 19 progressively small prey nd

orne more availshyneasured as the val ue between mall plus large If the ti me span ue is based was y detcnnin dshy) be chang s in gtreyavailability i by calculating ler to highli ght

empiric 1m anshyluences on (pashyon of prey taxa with primi tive evenne s indeshyIre had to alter bi lity of ani mal time large p rey m d smaU prey ~en i c influence

rela tive abunshyling d pressed f depression of Idu d ~ changes hange in how munal hu nts) ic abundan es luses may not gica 1 res Jarch

~ n by seasonal

Prehistoric Anthropogenic Impacts Are Not Ubiquitous I 207

shift s in prey accessibility and variation in the age of foragers may also create variation in accumulated prey (Lupo and Schmitt 2005) Both can resLllt in changshyes in relative abundances of high- and low-value p rey creating false signatur s of anthropog nically infl uenced faunas Sirmlarly r cent research seeking biologishycal sign tures of climatic changes and means to distinguish the e from instances where the signature has been forged by anthropogenic catLSes highlights the fa L that the challenge of disconfinning limatic environ mental change as the cause will demand multiple lines of vidence (Parmesan 2006)

It has also been suggested that the ki nds o( units used in analysis may obshyscure a signal of resou rce depr ssion For example faunal abundances are usushy

11y tallied by Linnaean taxonomic units but these units may mask various kind of resource depression sllch as if reJatively slow-mov ing prey (eg tu rtle tortoises shellfi sh) are depleted and exploitation of fast-moving prey (eg hares and flying birds) is intensifi ed (Stiner 2001 Stiner et al 2000 tiner et al 1999) In addition foraging models typically include temporal units such s forag ing events with du rat ions of several minutes hours days or weeks These bricf temshyporal un its are invisible in the archaeological record where a collection of p r y remai ns typically represents an unknown number of foraging events (excludshying mass-kill si t s) and a duraLion (of fo rmation) of multiple years (Grayson and Delpech 1998 Lyman 2003b) Rela tiv Iy long-duration temporal units typically represented by a rchaeofaunal as emblages may mask signatures of nth roposhygenic influences or they may create false signatures of thos influences by say correspond ing with und et cted rlimatic phases technological flux or predator behavioral change

Fin ally pabal uni ts in the ecologically based models may be treated as if they represent a predatorS catchm nt area arch eologi al m Lhods for detection of shifts in caLchn tent areas are slowly being developed but thus far are not COnshysistently applied ( annan 2003 Lyman 2003a Munro 2005 Nagaoka 2005) Anashylytical spatial units need not be assumd to repre ent a catchment area Given that environmental va riability has a geographic (habitats vary across space) as e1 a a temporal dimension inclusion in an analysis of fa unal ass mbJages from multiple sites located across en ironmentally het rogeneous areas may ma k or create false signatures of anthropogenic influences (eg Broughton 1994a 1994b

armon 2000 Janetski 1997) importan tly we now know that a metapopulation (total population) of a migratory taxon might be depressed by an thropogenic predation in one area but no t another allsiJ1g what appears to be local d p re shysian in the latter ar a (Bovy 2007)

The immediately preceding several paragraphs identify som ar as wh rp difficulties may res ide when seeki ng (3vidence of anthr pog nlcally influen ed faunas They also reveal reasons why we mayor may not fi nd what appears to be evidence of anthropogenic influence on a prehistoric faunal comm unity In the remainder of this discllssion I present examples of various of these kinds of probl m This ex rcise r veals additional reasons that false signals might app ar and underscores analyti al and in terpreti e difficulties with de tecting anthroposhygenicaJly innuenc~d fau nas

208 I R L Lyman

Faunal Change That Is Not() Anthropogenically Caused

As noted above changes in technology changes in how technology was used and chang s in environment or climate may cause changes in taxoshynomic abundances that fit the prediction of behavioral ec logy that high-value large prey will become less vailable and decrease in relative abundance while low-value small prey be ome more abundant in the zooarchaeological record (Grayson and CaJUlOl1 1999) A grow ing number of studies find a correlation beshytween environmental change and shift in relative abundances of taxa In some cases enviIonmental change caused high-value pr y to decrease in abundance (eg Wolverton 2005) in other cases environmental change caused high-value prey to incre se in availa ilily (eg Byers and Broughton 2004 Byers t al 2005)

I su pect that an instance of the latter will more re d ily catch the allil lysts atshytention than an in tance of the former and resul t in additional deta iled analyses aimed at determination of why the trend i the way thal it is I su pect this beshycause an increilse in high-value prey is the opposite of what b havioral ecology models suggest should b the result of human predation An instance when enshyvir runental change causes high- alue prey to become less availab le over time will ca tch the ana lysts attention but may not result in additional (confirmatory) analyses because its signature is precisely whal many models suggest should reshysult from human predation Whether r not my suspicion is correct it is clear that detailed paleoenvironmental records are required to evaluate whether chang s in rdati ve abundc n es of animal taxa are the resu lt of anthropogenic facto rs or climatic fac tor In some cases a I note below we may not be ab le to determine which set of factors is responsible

Change in technology or how a particul r technology is used has as yet selshydom been documented Remarkably one of the seminal studies to explicitly utilize foraging theory model provided a detailed comparison of faunal change and techshynological change In his (unfortunately unpublished and thus not widely available) doctoral dissertation Frank Bayham (1982) sttldied covariation in the frequency of remains of high- aiue (artiodactyls) and low-value Oeporid) prey and the freshyquency of what he categorized as hunting tools (projectile points flake knives and bifaces) and gathering tools (metates manos and p stIes) When thes fr quencies wer plotted against the 4500-year-duration seven-period stratigraphic sequence at ntana Cave Arizona gathering tool were m st abundant early and hunting tools were most abundant late in time Not only tha t Bayham observed that the relshyative abundance of artiodaclyl remajns increased more or less in correspondence with the increase in relative abundance of hunting tools

To summarize Bayhams (1982) inSights in one graph I used h is artiodactyl index values which are the prop rtion of artiodactyl remains in the combined am pIe of artiodacl y and leporid remains per stratum (Szu ter and Bayham 1989) I als calculated a bun ting-tool index as th proportion of hunting tools (as disshytinguish d by Bayham) in the combined sample of hunting and gathering tools per stratum (Table 10-1) The two set of index alues are pI tted against their stratigraphic provenience in Figure 10-1 The two ets of values are orrelated

Stratum

2

3

4

5

6

7

Nole Oat from

YOl

o

Fig tioc ing em cor

tHy Caused

w technology mges in laxoshyit high-value ndance while logical record orrelation beshytaxa In some in abundance ~d high-value rs et al 2005) analysts atshyiled analyses spect this beshyioral ecology nce w h middot n enshyble over time ~onfinnalory) ~s t should rcshyit is clear that middotther changes ni factors or to de termine

lS as yet selshyJlicitly uti lize nge and techshyely available) he frequency and the freshye knives and e frequencies hie sequence and hunting

d that the relshy-responden e

bull II artiodacty I 1e combined lyham 1989) tools (as d isshythering tools against th ir re cor related

Prehistoric Anthropogenic Impacts Are Not Ubiquitous I 209

TabJe 10-1 Ventana Cave Frequency Data for Leporid and Artiodactyl Faunal Remains and for Gathering Tools and Hunting Tools

Leporid Artiodactyl Artiodactyl Gathering Hunting Hunting-Stra tum NlSP NISP Index Tools Tools Tool Index

1 179 321 642 110 306 736

2 259 371 589 171 296 634

3 125 91 421 286 247 463

4 264 155 370 536 238 307

5 145 62 300 607 138 185

6 177 51 224 266 139 343

7 118 21 151 58 45 437

Note Data from Bayham (1982) IISP is number of identified specimens

Index Values 01 02 03 04 05 06 07 08

1 o you ng bull

2

3

5

6

old 7

hunting-tool index artiodacty I index

Figure 10-1 Artiodactyl index (propor tion of artiodactyl remains among arshytiodactyl plus leporid remains) and hunting-tool index (proportion of lllmtshy

ing tools among hU llting pIllS gathering tools ) across seven strata at Ventana Cave Arizona (data from Bayham 1982) The two sets of index values are correlated (coefficient ofdetermination 2 = 57 P lt 05)

~ ~~shy bull t bull I I I~ ~~ - ~--

tpacts Are

ating that preshy has prompted any times and search should idence of that tudied Some ue to find evishyrtifacts use of I representing )1S fo r lack of Irvest of indishy

today label middote long been sms B gin-al foragi ng

jerstanding 11980 Winshyde a sou ro I their prey ~ numerous ging theory

for Archaeoshyes Southell1

Pre~storic Anthropogenic Impacts Are Not Ubiquitous I 205

(Stephens and Krebs 1986) are now often grouped und r the banner of human behavioral ecology (Winterhalder and Smith 2000) and while many such studies have provided signi fi cant insights to human behaviors in ethnographic settings archaeology ha it share of the e studi s (Bird and OConnell 2006)

By the last decad of the twentieth century the plethora of research on predatorshyprey interactions perform d by zooarchaeologists under the guidance of human behavioral ecology prompted som researchers to synthesize evidence from large geographic areas (eg Cannon 2000 rayson 2001 Hildebrandt and Jones 2002 Janetski 1997 Kay 1994 Martin and Szuter 1999a 1999b Stiner et al 2000 Stiner et a1 1999 Szuter and Bayham 1989)_ The syntheses presented by thes re earchshyers seem to imply if not by word then by spatiotemporal breadth of their covshyerage that anthropogenic impacts are detectable nearly everywhere and ev ryshywhen in the zooarchaeological record While not denying that hwnans in many times and places likely influenced local and regi nal faunas to a greater or lesser degree I suggest th at we should not go into our research with the preconceived notion that w vill find evidence of that influenc in each and every collection of faunal remains we study We may find what J think of as false signals for any of several reasons What Lhose reasons are is one issue I explore here

To date few studies have failed t find evidence of anthropogenic influences within the zooarcha ological record but the number of such studies is slowly growing (Butler and Campb 11 2004 Byers and Broughton 2004 Lyman 1995 2003a 2004a Lym n and Wolverton 2002 Wolverton 2005) Interestingly whereshyas some early reports that anthropogeni infl uence wa not evident in a particushylar instance met with insistence that prehistoric people were indeed responsib le for observed changes in taxon m ic relative abundances over time (eg H ildeshybrand t and Jones 2002 Jones and Hildebrand t 1995 Laliberte and Ripple 2003 Martin and Szuter 2002) such disagreem nt has no t yet surfaced r garding later fi nding of no significant anthropogenic influence Perhaps this is because of the growing weight of the evidence or because of the recency of the reports of no sigshyni ficant ll1flu nee or because analyses are more sophis ticated theoretically and are backed by large data set Whatever the case given the facts that first th re are studies in which no evidence of an thropogenic influence on faunas has been found and second there is some (perhaps small) d gree of doubt about those ases where evidence of anthropogenic influence is appar ntly lacking it seems

to me that the is ue of why we might not always find evidence of nthr pogenic influenc on prehistoric faunas should be explored Figuring this out may in turn reveal how false signals of anthropogenic influence (or false signals of the lack of such influence) may be created These are the centra l issues I address here

Detecting Anthropogenic Influence on Prehis toric Faunas

To id ntify reasons as to why evidence of anthropogenic influence might not be found the zooarchaeological evidence uSLlally called upon as indIcashytive of anthropogenic influence on prehistoriC faunas mLlst be identified Given

206 I R L Lyman

that the typica l signature evid nce was recognized as such in light of fo raging theory and behavioral ecology I start there The nuances of th method and the eviden e should by now be well known gi en the xlensive pertinent li teralure so I only outline the basics Th pr y-choice model holds tha t human foragers will preferentially exploit the largest prey firs t because these taxa are the most valushyable all else being equal (Ugan 2005) If valuable (large) prey decrease in availabilshyity and thus the frequency at which Lhey are encountered decreases then foragers will turn to progreSSively more kinds of less va lu ble generally smaller preyshyeach individual considered less valuabl than a single larger individual-to mainshylain a constant level of nutrition Thus the ratio of large prey to small p lus large prey will fluctuate over time decreasiJlg (the proportion becomiJlg progpssively smaller than 10) as large prey become less available relative to small prey and increasing (becoming progr sively closer to 10) as large prey become mor availshyable relative to small pr y Typically animal prey ab W1dance me sured as the number of id ntified specimens ( lSF) are re ldered as an index value between oand 10 that xpresses the proportion of large prey relative to small plus large prey Plotting each index value against the temporal midpoint of the time span during which the assemblage of faunal remains on which the value is based was d pusited-whether stra tigraphically radiometrically or cultu rally dClerminedshyin a bivaria te scatterpJot visually reveals what are int rpreted to be changes in prey re turn rates that are in turn interpreted to reflect cha nges in prey avai lability or abundance Interp retation of the atterp lot is sometimes aided by calculating a simple best-fi t r gression li ne through the point scatter in order to highlight temporal trends

The model and analy tica l protocol just described identi fy an empirical manshyitestation of a particular signatu re criterion of anthropogenic influences on (pashyleo)faunas (Grayson 2001) As a result of their selective exploitation ot prey taxa that provided eilher or both low cos ts and high relurns humans with primitive technologies caused changes in fau na l taxonomic richness and cv nness indeshypendent of changes in climate and tech nology Humans therefore had to alter what they were expl iling as a response to a change in the availabili ty of animal prey that they themselves had caused The signatur i that over time large prey decrease in re lative abundance in the zooarchaeological record and small prey increase in relative abundan c as humans adapt to an anthropogenic infl uence on prey availability

The voice of caution requires that if one attributes increasing relative abunshydanc s of small low-value prey taxa to human exp loitation having depressed the availability of1arge high-value prey taxa alternative causes of depression of high-value preymust be disconfirmed Alternative causes can in lude cl anges in technology (eg shift fro m atlatl and dart to bow and arrow) changes in how tecl1l1ology was us gtd (eg h ift from individual h unters t communal hunts) and environmentally or dim tically driven changes in taxonomic abund ances (Gra son and ann on 1999) Disconfirmation of these al ternate causes may not however be as easy as originally thought Recent etluloarchaeological research among foragers indicates that sh ifts in technology may be driven by seasonal

shifts in prey variation in ao es in relati e al anthropogenic cal signatures where the sigr that the halle will demand r

It has aisl scu re a signal ally tallied b )

kinds of resou tortoises shell and fl ing bir In addi tion f( events with dt p ra l un its ar r-mains ty pic ing m ass-kill Dlpech 1998 represented b genic infiuen( correspondin behavioral ch

Finally S

lhey represen of shifls in cal sisten Uy appi lytical spatial environmentlt as a tempora mullipl ites create fa Ise si Cannon 2000 (total popula predation in I

sion in the lat The imn

difficulties m faunas They be evidence I

the remainde problems Th and undersc( genically in fl

light of foraging method and the t inent literature 1at1 foragers will e the most valushyease in availabilshyes then f ragcrs smaller preyshy

idual-to m ainshysmall pl us large 19 progressively small prey nd

orne more availshyneasured as the val ue between mall plus large If the ti me span ue is based was y detcnnin dshy) be chang s in gtreyavailability i by calculating ler to highli ght

empiric 1m anshyluences on (pashyon of prey taxa with primi tive evenne s indeshyIre had to alter bi lity of ani mal time large p rey m d smaU prey ~en i c influence

rela tive abunshyling d pressed f depression of Idu d ~ changes hange in how munal hu nts) ic abundan es luses may not gica 1 res Jarch

~ n by seasonal

Prehistoric Anthropogenic Impacts Are Not Ubiquitous I 207

shift s in prey accessibility and variation in the age of foragers may also create variation in accumulated prey (Lupo and Schmitt 2005) Both can resLllt in changshyes in relative abundances of high- and low-value p rey creating false signatur s of anthropog nically infl uenced faunas Sirmlarly r cent research seeking biologishycal sign tures of climatic changes and means to distinguish the e from instances where the signature has been forged by anthropogenic catLSes highlights the fa L that the challenge of disconfinning limatic environ mental change as the cause will demand multiple lines of vidence (Parmesan 2006)

It has also been suggested that the ki nds o( units used in analysis may obshyscure a signal of resou rce depr ssion For example faunal abundances are usushy

11y tallied by Linnaean taxonomic units but these units may mask various kind of resource depression sllch as if reJatively slow-mov ing prey (eg tu rtle tortoises shellfi sh) are depleted and exploitation of fast-moving prey (eg hares and flying birds) is intensifi ed (Stiner 2001 Stiner et al 2000 tiner et al 1999) In addition foraging models typically include temporal units such s forag ing events with du rat ions of several minutes hours days or weeks These bricf temshyporal un its are invisible in the archaeological record where a collection of p r y remai ns typically represents an unknown number of foraging events (excludshying mass-kill si t s) and a duraLion (of fo rmation) of multiple years (Grayson and Delpech 1998 Lyman 2003b) Rela tiv Iy long-duration temporal units typically represented by a rchaeofaunal as emblages may mask signatures of nth roposhygenic influences or they may create false signatures of thos influences by say correspond ing with und et cted rlimatic phases technological flux or predator behavioral change

Fin ally pabal uni ts in the ecologically based models may be treated as if they represent a predatorS catchm nt area arch eologi al m Lhods for detection of shifts in caLchn tent areas are slowly being developed but thus far are not COnshysistently applied ( annan 2003 Lyman 2003a Munro 2005 Nagaoka 2005) Anashylytical spatial units need not be assumd to repre ent a catchment area Given that environmental va riability has a geographic (habitats vary across space) as e1 a a temporal dimension inclusion in an analysis of fa unal ass mbJages from multiple sites located across en ironmentally het rogeneous areas may ma k or create false signatures of anthropogenic influences (eg Broughton 1994a 1994b

armon 2000 Janetski 1997) importan tly we now know that a metapopulation (total population) of a migratory taxon might be depressed by an thropogenic predation in one area but no t another allsiJ1g what appears to be local d p re shysian in the latter ar a (Bovy 2007)

The immediately preceding several paragraphs identify som ar as wh rp difficulties may res ide when seeki ng (3vidence of anthr pog nlcally influen ed faunas They also reveal reasons why we mayor may not fi nd what appears to be evidence of anthropogenic influence on a prehistoric faunal comm unity In the remainder of this discllssion I present examples of various of these kinds of probl m This ex rcise r veals additional reasons that false signals might app ar and underscores analyti al and in terpreti e difficulties with de tecting anthroposhygenicaJly innuenc~d fau nas

208 I R L Lyman

Faunal Change That Is Not() Anthropogenically Caused

As noted above changes in technology changes in how technology was used and chang s in environment or climate may cause changes in taxoshynomic abundances that fit the prediction of behavioral ec logy that high-value large prey will become less vailable and decrease in relative abundance while low-value small prey be ome more abundant in the zooarchaeological record (Grayson and CaJUlOl1 1999) A grow ing number of studies find a correlation beshytween environmental change and shift in relative abundances of taxa In some cases enviIonmental change caused high-value pr y to decrease in abundance (eg Wolverton 2005) in other cases environmental change caused high-value prey to incre se in availa ilily (eg Byers and Broughton 2004 Byers t al 2005)

I su pect that an instance of the latter will more re d ily catch the allil lysts atshytention than an in tance of the former and resul t in additional deta iled analyses aimed at determination of why the trend i the way thal it is I su pect this beshycause an increilse in high-value prey is the opposite of what b havioral ecology models suggest should b the result of human predation An instance when enshyvir runental change causes high- alue prey to become less availab le over time will ca tch the ana lysts attention but may not result in additional (confirmatory) analyses because its signature is precisely whal many models suggest should reshysult from human predation Whether r not my suspicion is correct it is clear that detailed paleoenvironmental records are required to evaluate whether chang s in rdati ve abundc n es of animal taxa are the resu lt of anthropogenic facto rs or climatic fac tor In some cases a I note below we may not be ab le to determine which set of factors is responsible

Change in technology or how a particul r technology is used has as yet selshydom been documented Remarkably one of the seminal studies to explicitly utilize foraging theory model provided a detailed comparison of faunal change and techshynological change In his (unfortunately unpublished and thus not widely available) doctoral dissertation Frank Bayham (1982) sttldied covariation in the frequency of remains of high- aiue (artiodactyls) and low-value Oeporid) prey and the freshyquency of what he categorized as hunting tools (projectile points flake knives and bifaces) and gathering tools (metates manos and p stIes) When thes fr quencies wer plotted against the 4500-year-duration seven-period stratigraphic sequence at ntana Cave Arizona gathering tool were m st abundant early and hunting tools were most abundant late in time Not only tha t Bayham observed that the relshyative abundance of artiodaclyl remajns increased more or less in correspondence with the increase in relative abundance of hunting tools

To summarize Bayhams (1982) inSights in one graph I used h is artiodactyl index values which are the prop rtion of artiodactyl remains in the combined am pIe of artiodacl y and leporid remains per stratum (Szu ter and Bayham 1989) I als calculated a bun ting-tool index as th proportion of hunting tools (as disshytinguish d by Bayham) in the combined sample of hunting and gathering tools per stratum (Table 10-1) The two set of index alues are pI tted against their stratigraphic provenience in Figure 10-1 The two ets of values are orrelated

Stratum

2

3

4

5

6

7

Nole Oat from

YOl

o

Fig tioc ing em cor

tHy Caused

w technology mges in laxoshyit high-value ndance while logical record orrelation beshytaxa In some in abundance ~d high-value rs et al 2005) analysts atshyiled analyses spect this beshyioral ecology nce w h middot n enshyble over time ~onfinnalory) ~s t should rcshyit is clear that middotther changes ni factors or to de termine

lS as yet selshyJlicitly uti lize nge and techshyely available) he frequency and the freshye knives and e frequencies hie sequence and hunting

d that the relshy-responden e

bull II artiodacty I 1e combined lyham 1989) tools (as d isshythering tools against th ir re cor related

Prehistoric Anthropogenic Impacts Are Not Ubiquitous I 209

TabJe 10-1 Ventana Cave Frequency Data for Leporid and Artiodactyl Faunal Remains and for Gathering Tools and Hunting Tools

Leporid Artiodactyl Artiodactyl Gathering Hunting Hunting-Stra tum NlSP NISP Index Tools Tools Tool Index

1 179 321 642 110 306 736

2 259 371 589 171 296 634

3 125 91 421 286 247 463

4 264 155 370 536 238 307

5 145 62 300 607 138 185

6 177 51 224 266 139 343

7 118 21 151 58 45 437

Note Data from Bayham (1982) IISP is number of identified specimens

Index Values 01 02 03 04 05 06 07 08

1 o you ng bull

2

3

5

6

old 7

hunting-tool index artiodacty I index

Figure 10-1 Artiodactyl index (propor tion of artiodactyl remains among arshytiodactyl plus leporid remains) and hunting-tool index (proportion of lllmtshy

ing tools among hU llting pIllS gathering tools ) across seven strata at Ventana Cave Arizona (data from Bayham 1982) The two sets of index values are correlated (coefficient ofdetermination 2 = 57 P lt 05)

~ ~~shy bull t bull I I I~ ~~ - ~--

206 I R L Lyman

that the typica l signature evid nce was recognized as such in light of fo raging theory and behavioral ecology I start there The nuances of th method and the eviden e should by now be well known gi en the xlensive pertinent li teralure so I only outline the basics Th pr y-choice model holds tha t human foragers will preferentially exploit the largest prey firs t because these taxa are the most valushyable all else being equal (Ugan 2005) If valuable (large) prey decrease in availabilshyity and thus the frequency at which Lhey are encountered decreases then foragers will turn to progreSSively more kinds of less va lu ble generally smaller preyshyeach individual considered less valuabl than a single larger individual-to mainshylain a constant level of nutrition Thus the ratio of large prey to small p lus large prey will fluctuate over time decreasiJlg (the proportion becomiJlg progpssively smaller than 10) as large prey become less available relative to small prey and increasing (becoming progr sively closer to 10) as large prey become mor availshyable relative to small pr y Typically animal prey ab W1dance me sured as the number of id ntified specimens ( lSF) are re ldered as an index value between oand 10 that xpresses the proportion of large prey relative to small plus large prey Plotting each index value against the temporal midpoint of the time span during which the assemblage of faunal remains on which the value is based was d pusited-whether stra tigraphically radiometrically or cultu rally dClerminedshyin a bivaria te scatterpJot visually reveals what are int rpreted to be changes in prey re turn rates that are in turn interpreted to reflect cha nges in prey avai lability or abundance Interp retation of the atterp lot is sometimes aided by calculating a simple best-fi t r gression li ne through the point scatter in order to highlight temporal trends

The model and analy tica l protocol just described identi fy an empirical manshyitestation of a particular signatu re criterion of anthropogenic influences on (pashyleo)faunas (Grayson 2001) As a result of their selective exploitation ot prey taxa that provided eilher or both low cos ts and high relurns humans with primitive technologies caused changes in fau na l taxonomic richness and cv nness indeshypendent of changes in climate and tech nology Humans therefore had to alter what they were expl iling as a response to a change in the availabili ty of animal prey that they themselves had caused The signatur i that over time large prey decrease in re lative abundance in the zooarchaeological record and small prey increase in relative abundan c as humans adapt to an anthropogenic infl uence on prey availability

The voice of caution requires that if one attributes increasing relative abunshydanc s of small low-value prey taxa to human exp loitation having depressed the availability of1arge high-value prey taxa alternative causes of depression of high-value preymust be disconfirmed Alternative causes can in lude cl anges in technology (eg shift fro m atlatl and dart to bow and arrow) changes in how tecl1l1ology was us gtd (eg h ift from individual h unters t communal hunts) and environmentally or dim tically driven changes in taxonomic abund ances (Gra son and ann on 1999) Disconfirmation of these al ternate causes may not however be as easy as originally thought Recent etluloarchaeological research among foragers indicates that sh ifts in technology may be driven by seasonal

shifts in prey variation in ao es in relati e al anthropogenic cal signatures where the sigr that the halle will demand r

It has aisl scu re a signal ally tallied b )

kinds of resou tortoises shell and fl ing bir In addi tion f( events with dt p ra l un its ar r-mains ty pic ing m ass-kill Dlpech 1998 represented b genic infiuen( correspondin behavioral ch

Finally S

lhey represen of shifls in cal sisten Uy appi lytical spatial environmentlt as a tempora mullipl ites create fa Ise si Cannon 2000 (total popula predation in I

sion in the lat The imn

difficulties m faunas They be evidence I

the remainde problems Th and undersc( genically in fl

light of foraging method and the t inent literature 1at1 foragers will e the most valushyease in availabilshyes then f ragcrs smaller preyshy

idual-to m ainshysmall pl us large 19 progressively small prey nd

orne more availshyneasured as the val ue between mall plus large If the ti me span ue is based was y detcnnin dshy) be chang s in gtreyavailability i by calculating ler to highli ght

empiric 1m anshyluences on (pashyon of prey taxa with primi tive evenne s indeshyIre had to alter bi lity of ani mal time large p rey m d smaU prey ~en i c influence

rela tive abunshyling d pressed f depression of Idu d ~ changes hange in how munal hu nts) ic abundan es luses may not gica 1 res Jarch

~ n by seasonal

Prehistoric Anthropogenic Impacts Are Not Ubiquitous I 207

shift s in prey accessibility and variation in the age of foragers may also create variation in accumulated prey (Lupo and Schmitt 2005) Both can resLllt in changshyes in relative abundances of high- and low-value p rey creating false signatur s of anthropog nically infl uenced faunas Sirmlarly r cent research seeking biologishycal sign tures of climatic changes and means to distinguish the e from instances where the signature has been forged by anthropogenic catLSes highlights the fa L that the challenge of disconfinning limatic environ mental change as the cause will demand multiple lines of vidence (Parmesan 2006)

It has also been suggested that the ki nds o( units used in analysis may obshyscure a signal of resou rce depr ssion For example faunal abundances are usushy

11y tallied by Linnaean taxonomic units but these units may mask various kind of resource depression sllch as if reJatively slow-mov ing prey (eg tu rtle tortoises shellfi sh) are depleted and exploitation of fast-moving prey (eg hares and flying birds) is intensifi ed (Stiner 2001 Stiner et al 2000 tiner et al 1999) In addition foraging models typically include temporal units such s forag ing events with du rat ions of several minutes hours days or weeks These bricf temshyporal un its are invisible in the archaeological record where a collection of p r y remai ns typically represents an unknown number of foraging events (excludshying mass-kill si t s) and a duraLion (of fo rmation) of multiple years (Grayson and Delpech 1998 Lyman 2003b) Rela tiv Iy long-duration temporal units typically represented by a rchaeofaunal as emblages may mask signatures of nth roposhygenic influences or they may create false signatures of thos influences by say correspond ing with und et cted rlimatic phases technological flux or predator behavioral change

Fin ally pabal uni ts in the ecologically based models may be treated as if they represent a predatorS catchm nt area arch eologi al m Lhods for detection of shifts in caLchn tent areas are slowly being developed but thus far are not COnshysistently applied ( annan 2003 Lyman 2003a Munro 2005 Nagaoka 2005) Anashylytical spatial units need not be assumd to repre ent a catchment area Given that environmental va riability has a geographic (habitats vary across space) as e1 a a temporal dimension inclusion in an analysis of fa unal ass mbJages from multiple sites located across en ironmentally het rogeneous areas may ma k or create false signatures of anthropogenic influences (eg Broughton 1994a 1994b

armon 2000 Janetski 1997) importan tly we now know that a metapopulation (total population) of a migratory taxon might be depressed by an thropogenic predation in one area but no t another allsiJ1g what appears to be local d p re shysian in the latter ar a (Bovy 2007)

The immediately preceding several paragraphs identify som ar as wh rp difficulties may res ide when seeki ng (3vidence of anthr pog nlcally influen ed faunas They also reveal reasons why we mayor may not fi nd what appears to be evidence of anthropogenic influence on a prehistoric faunal comm unity In the remainder of this discllssion I present examples of various of these kinds of probl m This ex rcise r veals additional reasons that false signals might app ar and underscores analyti al and in terpreti e difficulties with de tecting anthroposhygenicaJly innuenc~d fau nas

208 I R L Lyman

Faunal Change That Is Not() Anthropogenically Caused

As noted above changes in technology changes in how technology was used and chang s in environment or climate may cause changes in taxoshynomic abundances that fit the prediction of behavioral ec logy that high-value large prey will become less vailable and decrease in relative abundance while low-value small prey be ome more abundant in the zooarchaeological record (Grayson and CaJUlOl1 1999) A grow ing number of studies find a correlation beshytween environmental change and shift in relative abundances of taxa In some cases enviIonmental change caused high-value pr y to decrease in abundance (eg Wolverton 2005) in other cases environmental change caused high-value prey to incre se in availa ilily (eg Byers and Broughton 2004 Byers t al 2005)

I su pect that an instance of the latter will more re d ily catch the allil lysts atshytention than an in tance of the former and resul t in additional deta iled analyses aimed at determination of why the trend i the way thal it is I su pect this beshycause an increilse in high-value prey is the opposite of what b havioral ecology models suggest should b the result of human predation An instance when enshyvir runental change causes high- alue prey to become less availab le over time will ca tch the ana lysts attention but may not result in additional (confirmatory) analyses because its signature is precisely whal many models suggest should reshysult from human predation Whether r not my suspicion is correct it is clear that detailed paleoenvironmental records are required to evaluate whether chang s in rdati ve abundc n es of animal taxa are the resu lt of anthropogenic facto rs or climatic fac tor In some cases a I note below we may not be ab le to determine which set of factors is responsible

Change in technology or how a particul r technology is used has as yet selshydom been documented Remarkably one of the seminal studies to explicitly utilize foraging theory model provided a detailed comparison of faunal change and techshynological change In his (unfortunately unpublished and thus not widely available) doctoral dissertation Frank Bayham (1982) sttldied covariation in the frequency of remains of high- aiue (artiodactyls) and low-value Oeporid) prey and the freshyquency of what he categorized as hunting tools (projectile points flake knives and bifaces) and gathering tools (metates manos and p stIes) When thes fr quencies wer plotted against the 4500-year-duration seven-period stratigraphic sequence at ntana Cave Arizona gathering tool were m st abundant early and hunting tools were most abundant late in time Not only tha t Bayham observed that the relshyative abundance of artiodaclyl remajns increased more or less in correspondence with the increase in relative abundance of hunting tools

To summarize Bayhams (1982) inSights in one graph I used h is artiodactyl index values which are the prop rtion of artiodactyl remains in the combined am pIe of artiodacl y and leporid remains per stratum (Szu ter and Bayham 1989) I als calculated a bun ting-tool index as th proportion of hunting tools (as disshytinguish d by Bayham) in the combined sample of hunting and gathering tools per stratum (Table 10-1) The two set of index alues are pI tted against their stratigraphic provenience in Figure 10-1 The two ets of values are orrelated

Stratum

2

3

4

5

6

7

Nole Oat from

YOl

o

Fig tioc ing em cor

tHy Caused

w technology mges in laxoshyit high-value ndance while logical record orrelation beshytaxa In some in abundance ~d high-value rs et al 2005) analysts atshyiled analyses spect this beshyioral ecology nce w h middot n enshyble over time ~onfinnalory) ~s t should rcshyit is clear that middotther changes ni factors or to de termine

lS as yet selshyJlicitly uti lize nge and techshyely available) he frequency and the freshye knives and e frequencies hie sequence and hunting

d that the relshy-responden e

bull II artiodacty I 1e combined lyham 1989) tools (as d isshythering tools against th ir re cor related

Prehistoric Anthropogenic Impacts Are Not Ubiquitous I 209

TabJe 10-1 Ventana Cave Frequency Data for Leporid and Artiodactyl Faunal Remains and for Gathering Tools and Hunting Tools

Leporid Artiodactyl Artiodactyl Gathering Hunting Hunting-Stra tum NlSP NISP Index Tools Tools Tool Index

1 179 321 642 110 306 736

2 259 371 589 171 296 634

3 125 91 421 286 247 463

4 264 155 370 536 238 307

5 145 62 300 607 138 185

6 177 51 224 266 139 343

7 118 21 151 58 45 437

Note Data from Bayham (1982) IISP is number of identified specimens

Index Values 01 02 03 04 05 06 07 08

1 o you ng bull

2

3

5

6

old 7

hunting-tool index artiodacty I index

Figure 10-1 Artiodactyl index (propor tion of artiodactyl remains among arshytiodactyl plus leporid remains) and hunting-tool index (proportion of lllmtshy

ing tools among hU llting pIllS gathering tools ) across seven strata at Ventana Cave Arizona (data from Bayham 1982) The two sets of index values are correlated (coefficient ofdetermination 2 = 57 P lt 05)

~ ~~shy bull t bull I I I~ ~~ - ~--

light of foraging method and the t inent literature 1at1 foragers will e the most valushyease in availabilshyes then f ragcrs smaller preyshy

idual-to m ainshysmall pl us large 19 progressively small prey nd

orne more availshyneasured as the val ue between mall plus large If the ti me span ue is based was y detcnnin dshy) be chang s in gtreyavailability i by calculating ler to highli ght

empiric 1m anshyluences on (pashyon of prey taxa with primi tive evenne s indeshyIre had to alter bi lity of ani mal time large p rey m d smaU prey ~en i c influence

rela tive abunshyling d pressed f depression of Idu d ~ changes hange in how munal hu nts) ic abundan es luses may not gica 1 res Jarch

~ n by seasonal

Prehistoric Anthropogenic Impacts Are Not Ubiquitous I 207

shift s in prey accessibility and variation in the age of foragers may also create variation in accumulated prey (Lupo and Schmitt 2005) Both can resLllt in changshyes in relative abundances of high- and low-value p rey creating false signatur s of anthropog nically infl uenced faunas Sirmlarly r cent research seeking biologishycal sign tures of climatic changes and means to distinguish the e from instances where the signature has been forged by anthropogenic catLSes highlights the fa L that the challenge of disconfinning limatic environ mental change as the cause will demand multiple lines of vidence (Parmesan 2006)

It has also been suggested that the ki nds o( units used in analysis may obshyscure a signal of resou rce depr ssion For example faunal abundances are usushy

11y tallied by Linnaean taxonomic units but these units may mask various kind of resource depression sllch as if reJatively slow-mov ing prey (eg tu rtle tortoises shellfi sh) are depleted and exploitation of fast-moving prey (eg hares and flying birds) is intensifi ed (Stiner 2001 Stiner et al 2000 tiner et al 1999) In addition foraging models typically include temporal units such s forag ing events with du rat ions of several minutes hours days or weeks These bricf temshyporal un its are invisible in the archaeological record where a collection of p r y remai ns typically represents an unknown number of foraging events (excludshying mass-kill si t s) and a duraLion (of fo rmation) of multiple years (Grayson and Delpech 1998 Lyman 2003b) Rela tiv Iy long-duration temporal units typically represented by a rchaeofaunal as emblages may mask signatures of nth roposhygenic influences or they may create false signatures of thos influences by say correspond ing with und et cted rlimatic phases technological flux or predator behavioral change

Fin ally pabal uni ts in the ecologically based models may be treated as if they represent a predatorS catchm nt area arch eologi al m Lhods for detection of shifts in caLchn tent areas are slowly being developed but thus far are not COnshysistently applied ( annan 2003 Lyman 2003a Munro 2005 Nagaoka 2005) Anashylytical spatial units need not be assumd to repre ent a catchment area Given that environmental va riability has a geographic (habitats vary across space) as e1 a a temporal dimension inclusion in an analysis of fa unal ass mbJages from multiple sites located across en ironmentally het rogeneous areas may ma k or create false signatures of anthropogenic influences (eg Broughton 1994a 1994b

armon 2000 Janetski 1997) importan tly we now know that a metapopulation (total population) of a migratory taxon might be depressed by an thropogenic predation in one area but no t another allsiJ1g what appears to be local d p re shysian in the latter ar a (Bovy 2007)

The immediately preceding several paragraphs identify som ar as wh rp difficulties may res ide when seeki ng (3vidence of anthr pog nlcally influen ed faunas They also reveal reasons why we mayor may not fi nd what appears to be evidence of anthropogenic influence on a prehistoric faunal comm unity In the remainder of this discllssion I present examples of various of these kinds of probl m This ex rcise r veals additional reasons that false signals might app ar and underscores analyti al and in terpreti e difficulties with de tecting anthroposhygenicaJly innuenc~d fau nas

208 I R L Lyman

Faunal Change That Is Not() Anthropogenically Caused

As noted above changes in technology changes in how technology was used and chang s in environment or climate may cause changes in taxoshynomic abundances that fit the prediction of behavioral ec logy that high-value large prey will become less vailable and decrease in relative abundance while low-value small prey be ome more abundant in the zooarchaeological record (Grayson and CaJUlOl1 1999) A grow ing number of studies find a correlation beshytween environmental change and shift in relative abundances of taxa In some cases enviIonmental change caused high-value pr y to decrease in abundance (eg Wolverton 2005) in other cases environmental change caused high-value prey to incre se in availa ilily (eg Byers and Broughton 2004 Byers t al 2005)

I su pect that an instance of the latter will more re d ily catch the allil lysts atshytention than an in tance of the former and resul t in additional deta iled analyses aimed at determination of why the trend i the way thal it is I su pect this beshycause an increilse in high-value prey is the opposite of what b havioral ecology models suggest should b the result of human predation An instance when enshyvir runental change causes high- alue prey to become less availab le over time will ca tch the ana lysts attention but may not result in additional (confirmatory) analyses because its signature is precisely whal many models suggest should reshysult from human predation Whether r not my suspicion is correct it is clear that detailed paleoenvironmental records are required to evaluate whether chang s in rdati ve abundc n es of animal taxa are the resu lt of anthropogenic facto rs or climatic fac tor In some cases a I note below we may not be ab le to determine which set of factors is responsible

Change in technology or how a particul r technology is used has as yet selshydom been documented Remarkably one of the seminal studies to explicitly utilize foraging theory model provided a detailed comparison of faunal change and techshynological change In his (unfortunately unpublished and thus not widely available) doctoral dissertation Frank Bayham (1982) sttldied covariation in the frequency of remains of high- aiue (artiodactyls) and low-value Oeporid) prey and the freshyquency of what he categorized as hunting tools (projectile points flake knives and bifaces) and gathering tools (metates manos and p stIes) When thes fr quencies wer plotted against the 4500-year-duration seven-period stratigraphic sequence at ntana Cave Arizona gathering tool were m st abundant early and hunting tools were most abundant late in time Not only tha t Bayham observed that the relshyative abundance of artiodaclyl remajns increased more or less in correspondence with the increase in relative abundance of hunting tools

To summarize Bayhams (1982) inSights in one graph I used h is artiodactyl index values which are the prop rtion of artiodactyl remains in the combined am pIe of artiodacl y and leporid remains per stratum (Szu ter and Bayham 1989) I als calculated a bun ting-tool index as th proportion of hunting tools (as disshytinguish d by Bayham) in the combined sample of hunting and gathering tools per stratum (Table 10-1) The two set of index alues are pI tted against their stratigraphic provenience in Figure 10-1 The two ets of values are orrelated

Stratum

2

3

4

5

6

7

Nole Oat from

YOl

o

Fig tioc ing em cor

tHy Caused

w technology mges in laxoshyit high-value ndance while logical record orrelation beshytaxa In some in abundance ~d high-value rs et al 2005) analysts atshyiled analyses spect this beshyioral ecology nce w h middot n enshyble over time ~onfinnalory) ~s t should rcshyit is clear that middotther changes ni factors or to de termine

lS as yet selshyJlicitly uti lize nge and techshyely available) he frequency and the freshye knives and e frequencies hie sequence and hunting

d that the relshy-responden e

bull II artiodacty I 1e combined lyham 1989) tools (as d isshythering tools against th ir re cor related

Prehistoric Anthropogenic Impacts Are Not Ubiquitous I 209

TabJe 10-1 Ventana Cave Frequency Data for Leporid and Artiodactyl Faunal Remains and for Gathering Tools and Hunting Tools

Leporid Artiodactyl Artiodactyl Gathering Hunting Hunting-Stra tum NlSP NISP Index Tools Tools Tool Index

1 179 321 642 110 306 736

2 259 371 589 171 296 634

3 125 91 421 286 247 463

4 264 155 370 536 238 307

5 145 62 300 607 138 185

6 177 51 224 266 139 343

7 118 21 151 58 45 437

Note Data from Bayham (1982) IISP is number of identified specimens

Index Values 01 02 03 04 05 06 07 08

1 o you ng bull

2

3

5

6

old 7

hunting-tool index artiodacty I index

Figure 10-1 Artiodactyl index (propor tion of artiodactyl remains among arshytiodactyl plus leporid remains) and hunting-tool index (proportion of lllmtshy

ing tools among hU llting pIllS gathering tools ) across seven strata at Ventana Cave Arizona (data from Bayham 1982) The two sets of index values are correlated (coefficient ofdetermination 2 = 57 P lt 05)

~ ~~shy bull t bull I I I~ ~~ - ~--

208 I R L Lyman

Faunal Change That Is Not() Anthropogenically Caused

As noted above changes in technology changes in how technology was used and chang s in environment or climate may cause changes in taxoshynomic abundances that fit the prediction of behavioral ec logy that high-value large prey will become less vailable and decrease in relative abundance while low-value small prey be ome more abundant in the zooarchaeological record (Grayson and CaJUlOl1 1999) A grow ing number of studies find a correlation beshytween environmental change and shift in relative abundances of taxa In some cases enviIonmental change caused high-value pr y to decrease in abundance (eg Wolverton 2005) in other cases environmental change caused high-value prey to incre se in availa ilily (eg Byers and Broughton 2004 Byers t al 2005)

I su pect that an instance of the latter will more re d ily catch the allil lysts atshytention than an in tance of the former and resul t in additional deta iled analyses aimed at determination of why the trend i the way thal it is I su pect this beshycause an increilse in high-value prey is the opposite of what b havioral ecology models suggest should b the result of human predation An instance when enshyvir runental change causes high- alue prey to become less availab le over time will ca tch the ana lysts attention but may not result in additional (confirmatory) analyses because its signature is precisely whal many models suggest should reshysult from human predation Whether r not my suspicion is correct it is clear that detailed paleoenvironmental records are required to evaluate whether chang s in rdati ve abundc n es of animal taxa are the resu lt of anthropogenic facto rs or climatic fac tor In some cases a I note below we may not be ab le to determine which set of factors is responsible

Change in technology or how a particul r technology is used has as yet selshydom been documented Remarkably one of the seminal studies to explicitly utilize foraging theory model provided a detailed comparison of faunal change and techshynological change In his (unfortunately unpublished and thus not widely available) doctoral dissertation Frank Bayham (1982) sttldied covariation in the frequency of remains of high- aiue (artiodactyls) and low-value Oeporid) prey and the freshyquency of what he categorized as hunting tools (projectile points flake knives and bifaces) and gathering tools (metates manos and p stIes) When thes fr quencies wer plotted against the 4500-year-duration seven-period stratigraphic sequence at ntana Cave Arizona gathering tool were m st abundant early and hunting tools were most abundant late in time Not only tha t Bayham observed that the relshyative abundance of artiodaclyl remajns increased more or less in correspondence with the increase in relative abundance of hunting tools

To summarize Bayhams (1982) inSights in one graph I used h is artiodactyl index values which are the prop rtion of artiodactyl remains in the combined am pIe of artiodacl y and leporid remains per stratum (Szu ter and Bayham 1989) I als calculated a bun ting-tool index as th proportion of hunting tools (as disshytinguish d by Bayham) in the combined sample of hunting and gathering tools per stratum (Table 10-1) The two set of index alues are pI tted against their stratigraphic provenience in Figure 10-1 The two ets of values are orrelated

Stratum

2

3

4

5

6

7

Nole Oat from

YOl

o

Fig tioc ing em cor

tHy Caused

w technology mges in laxoshyit high-value ndance while logical record orrelation beshytaxa In some in abundance ~d high-value rs et al 2005) analysts atshyiled analyses spect this beshyioral ecology nce w h middot n enshyble over time ~onfinnalory) ~s t should rcshyit is clear that middotther changes ni factors or to de termine

lS as yet selshyJlicitly uti lize nge and techshyely available) he frequency and the freshye knives and e frequencies hie sequence and hunting

d that the relshy-responden e

bull II artiodacty I 1e combined lyham 1989) tools (as d isshythering tools against th ir re cor related

Prehistoric Anthropogenic Impacts Are Not Ubiquitous I 209

TabJe 10-1 Ventana Cave Frequency Data for Leporid and Artiodactyl Faunal Remains and for Gathering Tools and Hunting Tools

Leporid Artiodactyl Artiodactyl Gathering Hunting Hunting-Stra tum NlSP NISP Index Tools Tools Tool Index

1 179 321 642 110 306 736

2 259 371 589 171 296 634

3 125 91 421 286 247 463

4 264 155 370 536 238 307

5 145 62 300 607 138 185

6 177 51 224 266 139 343

7 118 21 151 58 45 437

Note Data from Bayham (1982) IISP is number of identified specimens

Index Values 01 02 03 04 05 06 07 08

1 o you ng bull

2

3

5

6

old 7

hunting-tool index artiodacty I index

Figure 10-1 Artiodactyl index (propor tion of artiodactyl remains among arshytiodactyl plus leporid remains) and hunting-tool index (proportion of lllmtshy

ing tools among hU llting pIllS gathering tools ) across seven strata at Ventana Cave Arizona (data from Bayham 1982) The two sets of index values are correlated (coefficient ofdetermination 2 = 57 P lt 05)

~ ~~shy bull t bull I I I~ ~~ - ~--

tHy Caused

w technology mges in laxoshyit high-value ndance while logical record orrelation beshytaxa In some in abundance ~d high-value rs et al 2005) analysts atshyiled analyses spect this beshyioral ecology nce w h middot n enshyble over time ~onfinnalory) ~s t should rcshyit is clear that middotther changes ni factors or to de termine

lS as yet selshyJlicitly uti lize nge and techshyely available) he frequency and the freshye knives and e frequencies hie sequence and hunting

d that the relshy-responden e

bull II artiodacty I 1e combined lyham 1989) tools (as d isshythering tools against th ir re cor related

Prehistoric Anthropogenic Impacts Are Not Ubiquitous I 209

TabJe 10-1 Ventana Cave Frequency Data for Leporid and Artiodactyl Faunal Remains and for Gathering Tools and Hunting Tools

Leporid Artiodactyl Artiodactyl Gathering Hunting Hunting-Stra tum NlSP NISP Index Tools Tools Tool Index

1 179 321 642 110 306 736

2 259 371 589 171 296 634

3 125 91 421 286 247 463

4 264 155 370 536 238 307

5 145 62 300 607 138 185

6 177 51 224 266 139 343

7 118 21 151 58 45 437

Note Data from Bayham (1982) IISP is number of identified specimens

Index Values 01 02 03 04 05 06 07 08

1 o you ng bull

2

3

5

6

old 7

hunting-tool index artiodacty I index

Figure 10-1 Artiodactyl index (propor tion of artiodactyl remains among arshytiodactyl plus leporid remains) and hunting-tool index (proportion of lllmtshy

ing tools among hU llting pIllS gathering tools ) across seven strata at Ventana Cave Arizona (data from Bayham 1982) The two sets of index values are correlated (coefficient ofdetermination 2 = 57 P lt 05)

~ ~~shy bull t bull I I I~ ~~ - ~--

It ~ bull4 _ bull

210 I R L Lyman

(co ffiei nt of determination)2 = 57 Plt 05) Bayham (1982 ee lt-l Is Szu t r and Bayham 1989) suggests that the corresponding temporal tr nds in abundances of too l types and fau nal taxarefle t a chang in how the si te was u tili zed spe ifica lshyly the sites role wi thin the s cioeconomic system shift d Initially Ventana Cav was llsed as a base camp arou nd which many fo raging activ ities took place As a result of chlt-l ng s in land use ov r time Ventan Cav gradually w as used less as a base camp and more as a h unting locality Fau na l de ta fro m other sites in the region vary in a cor respond ing manner (Szu ter and Bayham 1989) Thus Ventana Cave provides a unique case in which the ar haeological monitoring perspecti ve of how a socioeconomic sys tem uL-ilizes a landscape cb anges no t because the archaeologisl relocated geographicall y but because prehistoric people altered how they used particular piece of real esta te The ap paren t anthropogen ically caused change in fau na on the landscape was the result of I s middotxtensive hun tshying pressure by which I mean that pressure was perha ps more intensi e but for much briefer periods of tim allowing tl e artiodacty l pOpU lcl lion to remain table or perhaps even rebound a bi t between hunti ng episodes

l3 ayhams (1982) analysis of artifacts likely grew uut or the fact that th faushynal r cord d id not reflect lh predictions of the prey choice model Instead of high-value prey decreasing ove r time their remains increased through the stratishygraphic sequence prompting fi rst a stlld y of tool ab undances (Bayham 1982) and then a study of other faunas in nearby locations (Sz utcr n d Bar ham 1989) Major insigh ts w re gained but failure Lo find the xpectcd signature of mthropogenic resource depression ontribu tcd to w hy those insights wer gained Ther arc oth r examples of explanatory com plexi ties when the faunal record does not beshyhave the w ay it should by whi h 1 mean the faunal record docs not reflect anshythropogeniC infiu nces

Atypical Anthropogenic Changes in Faunas

Al though many stud ies of anthropogenic infl uen ces on paJeofaunas concern h uman foragers it is worth mentioning the in fl uences of food prod ucshyers- horticul turalists and agricultur alists- on fauna because some such in fl ushyences do not presen t the typical signature of depreSSion of high-value prey These are archetypical examples of the demnnd for complex mul ti variate expl an ations because they do not easily fit the traditional m d 1

On the one hand the garden-hunting hypothesis was proposed by Olga Linare c (1976) more than 30 ars ago This hypothesiS holds that anthropogenic floras created by gardening and horticul ture result ill ar tificially in reased animal biomass especially an imal taxa of small body iz The increased availabili ty of small animals is thought to be taken advantage of by the fann ers and is thought Lo show up in the zooarchaeological record as increases in the abu ndanc of remains of small animals (Stahl [2000J presen ts a related ar haeological example) John Speth and Susan S ott (1989) suggested on the oth er hand that in creasing depenshydellCe on cultivated plant foods could Ie d to increased reliance on large animals An increase in the abundance of remains of large an imals in the archaeological

record of farn the hunters fo conomi nlly

known as ani Precisely

faunal record debrandt ane the debale c change in poundal or a h uman debate w ill n vi c ib l diffeD guishcd faur had accum u the taxa in e to explain th point raised th exact oP] demand con whether it v place to l ()o~ nol ogy in ki demands ne in te hnol o~ taxa (eg LI

no an th rop he la tter i

cause of 10 so w eak as evidence 01 readily exp for the absl

In an t

coast I arg ent becausmiddot as the for those same taxon) h ad subseq uen (Eumetopia site forma

Iso Szu ter and abundances of ~ed specifica lshyVent na ave took place As was used less ler sites in the Thus Ventnna g perspective tt because the leople altered ropogenically tensi e huntshyintensive bu t ion to remain

t tha t the faushyel Instead of Igh the stratishyam 1982) and 11989) Mdjor lthr pogenic d There arc d es no t beshyat re tl ct al1shy

palcofaunas ood p roclucshy~ uch in fl ushy_ prey hese gtxplana hons

ed by Olga thropogcnic ased an imal laiability of 5 thought to of remains mple) John sing d PCI1shy

~ge animals haeological

Preh islori Anthropogenic Impacls Are Not Ubiquitous I 211

record of farmers uld result from greater s lcctivity for large game on th part of tIl hunters for any of s vera1 reasons sLlch as in rea ed status from undertaking an ec nomically risky endeavor or the presen e of buffer zones (Hickerson 1965 also known as animal source areas see Pulliam 1988) between sedentary farm ers

Precisely these two possible cau es hav appeared in a recent d bate about a falU1al record created by p rehistoric foragers (Broughton and Bayham 2003 Hilshydebra ndt and M Guire 2002 200 ) Using the words of some of the p articipants the debate center around the que tion Was the (apparently) anthropogenic change in faunal taxonomic abundances driven by human desire for calories or a human desire for p restige (McGui re and Hildebrandt 2005) Resolving the debate w ill no doubt require innovative analyses meant to detect archa oIogically visible di ff ~ r nces between the two possibilities Stahl (2000) for example distinshyguished faunal remains accumulated and deposited by humans from r main s that J ad accumulated na turally and then considered th e ecological predilections o f the t xa in each subsampl (culturally accumulated and natu rally accumulated) to explain the an thropogenic nature of the fauna he studied This highlights the point rais d eaTlier tha t identify ing the cau e of a faunal abundance trend that is th exact opposite of th standard signature of an thropogenic influence willlikeJy demand complex multivariate analyses For example it has been suggested that whether it was a desire for calories or a desire for pr stige may be the incorrect place to look the p rtinent fa una l trends may have resu lted from chang s in techshynology in kind or how it was II cd (Hockett 2005) Confirma tion of this possibility demallds not only detailed study of tools but also determination of whether shifts in technology w re a clt use or a cons qucnce of hifls in the ava ilnbility of prey taxa (eg Lupo and Schm itt 2005)

Instances of No Apparent Anthropogenic Influence

I turn now to instances in which the fa unal record suggests there was nn an th ropogenic influence or at least there was no eviden e of such influence The la tter impl ies that the m agnitude of influence may no t impact a fauna beshycau se of Inw intenSity or tha t the zooarchaeological signal of such influence is so w ak as t be imper middoteptibl- J am awme of two kinds of stu dies in which no evidence of anthropogenic influence was found In one the nbsence of a trend is readily explained b prey ehav ior in the othel~ there is no obvious explanation for the absence of ~ trend in taxonomic abundance and that is cri tical

Tn an arly study of pinniped pmains from the I te Holocene of the Oregon coast I argued th t dep ression of local populations of several taxa was not apparshyent because indices of abundances of p referr d prey did not uniformly decrease as the foraging model suggestd they should (Lyman 1995) Others thought those same data suggested tha t the metapopulation (the total population of a taxon) had indeed bl~en depressed (read depleted) (Jones and Hildebrandt 1995) I subsequently fou nd tha t the abundance of a local popUlation of Steller sea lions (Eumetopias jubatus) did not seem to be depress(d over the 700-yeaJ dllation of site form ation largely because abou t 90 percent of the remains were fro m adult

212 I R L Lyman

males-the demographic cat gory th at could be exploited w iUl0ut major influshyence on the loc 1popuLation given rep roductive behaviors of this taxon (Lyman 2003a) ln this case the reason that no evidence of an thropogenic depression w as fou nd involved vad ti n in the escape behaviors across age-sex classes of the population Adult females and yOWlg of both sexes flee in to the water at lhe fi rs t sign f danger on land w hi le adult bre ding-age ma les defend terrestrial breedshying territories against all com 1S Culling m ostly ad ult males if not excessive would not influen e the ize of the population And con traJY to som who say this r p resents p rehistoric conservation (Alvard 1998) it in fact does not because it did not involve the int n tional exploitation f a certain fraction of th e populashytion such as is usu ally meant by the term conservation (Smith and Wishnie 2000) In tead the lack of anthropogenic infllenc was an epiphen menan (Hu nn 1982) of which age-sex class of p rey animals was exploited which ilself was a function o f prey escape behavior and how availilble t clmology was used

In another study Butler and am pbeU (2004) reviewed zooard1aeological d ta for the southern Northwest Coas t and for the northern Col umbia Plateau environmentally and archaeologically distinct area in the Paci fic Northwest of North America In bo th areas they found no changE in relative abundances oi high-value and low-valu fi sh through time and they found no change in abw1shydances of high- lue mammals (artiodaclyls) relati e to abund ances [low-value mammaL They suggest th t th lalter may be the result of en virolUl1ental change in th C lumbia Plateau but that explanation does not ae aunt for the Northwe t Coast data They also suggesl that the reprodueti e sbmiddotategy and li f cycle of salmshyon me y render these fi sh somewhat imm une to expl itation-related depression They hypo thesize as well thal hu m n populations in both areas may never have been suffi ciently large to significan tly in fl uence fis h and mammal populations Finally But le r and ampbell (2004391) suggest their scale of an lysis may have caused them to not fi nd evidence f resource d p r ssion In my iew the struggle and u ltimate failure they have in fi nding an explanation for the lack of evidence of resource depression highlights two thin gs First pedlap_ we too read ily accept evidence of depression in the form of decreased abwldance of hig -value prey And second we tend to work hard at xplaining the posite of the signature bmiddotend in order to maintain some ersion o f the resource-depression model When there is no trend in taxonomic abundances we may be left wiLh ltl con undrum

False Signals of Anthropogenic Influence

The case of the pinnipeds on the Oregon coast suggests tha t spa tial grain may influence whether or not vidence of anlhmpogenic influence is deshytected A coarse spatial gr in is one in w hich a me tapopulation is under study a fine patial grain is one in w hich an individual local population is under study In the case of the Oregon pinnip ds the oar e spatia l grain sugg sted anthroshypogenic influence whereas a fine spatial grain suggested no anlhropogenic influshyence in the location scrutinized There is an oLher example of how geographic resolu tion grain might influence results that warran ts m n tiol1

Kay (199 10000 years ( or wapiti (Ce abundance 01 small (Figure th e enLire sev popula tions t Yellowstone i When h is dat when the spa less time and som time pe

Considel ern Washingt blages of fau wapiti (mail (Lym an 2004 blage against Further usin~ man 2004a) I the abwldanc seemed at th( dances [ fou middot pgt 9) and fo n ificantly frOl no evidence I

resented If 1middot period in wh period corres 10-4) The sil zer and the son 11 re is t11 abundances c What is the way At pres other potenti

To this f and bivariate the tTadition ing trends wi Calculating c sample size ( non 2000 20( samp le sizes of 5 and an a1 percent of thl

major inpoundlushylXOn (Lyman pression was lasses of the middoter at the firs t ~strial breedshyot excessive )mE who say nol because f the populashyishnie 2000) (Hunn 1982) as a fu nction

middotchaeological lbia Plateau -Iorthwest of undances of nge in abW1shyof low -valu ental change e Northwest yele of salmshydepression

1 never have populations may have th struggle of evidence

adily accept l-value prey he signa lure lOdeJ When lUndrum

that spatial uence is dlshyder stud y a mder s udy ted anthroshy)genic influshygeographic

Prehistoric Anthropogenic Impacts Are Not Ubiquitous I 213

Kay (1994) lumped zooarchaeologi a1 da ta from seven western states and 10000 years of prehistory He found that the abundance of North American elk or wapiti (Cervus elaphus) remains fo r that patiotemporal area relative to the abundance of wapiti in the modern Yellow tone ecosy tern was exceptionally small (Figur 10-2) He then extrapolated from the Yellowstone ecosystem to the enti re seven-state area arguing tha l prehistoric hunters had depleted wapiti pop ulations throughou t the Holocene and th modern abundance of wapiti in ~ 110wst ne is an arti fact of tw entieth-century wild life and park management When his data are eli ided into more spatiotelTlporally limited samples that is when the spatiotemp ral uni ts arc changed to much finer grain units containing less time and less space vidence for depT ssion vanishes in some areas and in some time periods (Lym an 2004a)

Considel~ for example the data fr m Holocene archaeological sites in eastshyern Washington state These data represent 86 spatiotemporally d istinct assemshyblages of faunal remains In an earli r analy is I calculated the proportion of wapiti remains among summed wapiti and de r remains for each assemblage (Lyman 2004a) A bivaria te plo t of th proportion of wapiti remains in an assemshyblage against the ge of the assemblage reveals no obvious trend (Figure 10-3) Fur ther using the lhen standard analy tical techniques in my earlier analysis (Lyshyman 2004a) 1 found no correlation between the deer plus wapi ti samples anL the lt bundance of w pin rem ain per assemblage (r 16 P= 14) Sample size it seemed at the time was not d riving any trend (or lack thereof) in wapiti abw1shydances I fo und no correlation be tween age and proportion of wapiti (r = 006 P gt 9) and found that the slope of the best-fit regression line did not differ sigshynifican tly from zero (Figure 10-3) This prompted me to concl ude that there w as no evidence fo r the d pres ion (depletion) of wapiti over the 10000 years repshyresented If however the wapiti and deer remains are summed by the SOO-year period in which they occur the proportion of wapiti remains for each SOO-year period corresponds very nicely t the anthropogenic depression model (Figur 10-4) The simple best-fit regIe sion line has a slope sign ifjcantly different from zero and the two vari ables are orrelated (I = 489 P = 064) The importan t lesshyson here is thal a trend in taxonomic abundances may be an artifact of how tho e abtlJ1dan es are talli ed This observation demands that we consider the qm tiol1 What is th correct way to tally those abundances or i there a single correct way At present thi question cannot be answered And sadly ther is yet anshyother potential problem here

To this point I have used particular statistical analyses (simple correlation) and bivaria le plots to search for evidence of anthropogenic depression both are the Lradi tional m ans of s arching y t neither is pcuticularly sensitive to detectshying trends when percentag s or proportions ar used as measures of abundan ce Calcula ting a correlation coefficient betvveen relative abundances of taxa and ample size ([ SP) is not the best way to sta tis ti Ily search for tr nds (Canshy

non 2000 2001) This is so becau relative abundance do not r gister wh ther sa mple sizes are 5 or 5000 Statist ically the di fference b tween an absolute ta lly of 5 and an absolu te taUy of 5000 i quite d ifferent from saying each comprises per ent of Lhe total collection (100 and 100000 respectively) The effect of small

214 I R L Lyman

Figure 10-2 Relashytive abundances of North American wa-

Piti and other artioshydactyls in the modern Yellowstone ecosysshytem compared 0 the relative abundances ofwapiti remains and rel1ains of other arshytiodaclyls in archaeoshylogiwl sites in seven western states (data from Kay 1994)

100 -------------------------------~

QJ

80

~

~ 40 ~

20

bull Yellowstone

bull Intermontane West

Wapiti Other Ungulate Taxa

05 ----------------------------

o o o

o

04 0 0

o o

0~ 03 cU C cs

middotn 0 5 0

0 ~ 02 0 0 c 0

0

C DoD~

0

01 0 0

0 0

o 0 0

o ciDa o B 0 o 0 0

0 00 ~~ 0 rn lib 0 0 sect 0 8 0 g rP 00

a 2000 tOOO 6000 8000 10000 Age (radiocarbon years BP)

Figure 10-3 Proportion of wapiti remains among summed wapiti and deer remains in 86 assemblages from eastern Washington state (da ta from Lyman 2004a) The slope of the simple best-fit regres ion line is not sigl1ificantly differshyent from zero and there i no correlation between age and proportion of wapiti

06

05

04 x OJ

U

s ~ 03 11

~ 02

0

01

00 0 0 Of)

f r

s Ii v

samples on accurate ref inventory t the abW1dat bUl sample not be accUJ relatively m sampling er INISP acro sampling er

Use of ur 10-3 an hypothesis 1 no trend ) or there is no t the null hn sam ples tha correl tion ( source of thE

r

10000

ti l11ld dctl om Lyman II tty diffe1shy of wapiti

Preh istoric Anth ropogenic Impacts Are Not Ubiquitous I 215

06

0 05

04

x 000

s I 03 D 2

02

01

0 0 00

0 000

0 0 0 D C Cgt C 0 co Cgt Q Cgt Cgt 0 Cgt 0 c 0 0 co 0 0 c 0 0 Cgt 0 0 0 0 Cgt 0 8 C

Q U) Cgt 8 en 0 U) Cgt 0 co 1 1 0 cr-N~ T 7 ~I r 7 1 l l 1 ~5 0 Cgt 5 0 ltgt 0 0 0 0 c5 sect S

n 0 r ltgt f) 0 0 u 8 n co ~ N rlt) lt-- ~ U lR h tt 00

I

Age (radiocarbon years BP)

Figure 10-4 Proportion of wapiti remaiJls among summed wapiti and deer remains by SOO-year period for 86 assemblages from eas tern Washington state (data from Lyman 2004a) The slope of the simple best-fit regression line is sigllificantly different from zero and the age and proportion of wapiti variables are correlated (1 = 489 P = 064)

samples on corr la tions may simply be due to sampling error ralher than any accurate [-fle lion of abundance Rar phcnom na are particula rl y difficult to in entory they wi ll be ab ent from collections unless the sampleti arc large H th abundances of tie ral rare taxa are not quite equal in the target pop ula tion bu t samples are sm all the true rela tive abundan ces of those rare taxa likely will not be accurately refle ted by small sam ples (Grayson 1984) S )mc taxa v il be relatively more abundant some k ss abundnnt in th sample simply bec use of ampling error Thus a correIalion betvvee the relative abundance of a taxon and

[ Nl P across m ultiple assemblages may be driven by sm all sam ples because of sam pIing error

se of th regression approach to search for sa mplc-size effecls (as in Figshyures 10-3 and 10-4) may lead to commission of a Type I error (rejecting a lru null hypothesis that there is no true trend in relative abundances vhen in fact there is no trend) or com mi ssion of a Type II error (accepting a fa l e nu ll hypothesis that there is no true tren d in abundances when in fact there is a trend) In bo th cases the null hypothesis is th t no trend is presen t bulampling error has produced a mples that a r not representative of the p opu lation Traditionally a signifi cant correlation coeffici nt has been in terpreted a indicating that sample size is the sou rce of the correlation and lh absence of tiign ificant correlation coeffici nt is

2] 6 I K L Lyman

interpreted as indica ting that sampl size is not the source of the correlation As Cannon (2001 185) obser ed the firs t interpr tabon at best rests on an incomplete understanding of the relationship between relative abundances and sample size the second interpret tion pre urnes sample sizes ar sllfficientl y large to warrant confidence but in fact they may be too sma ll In lerm more pertinent to seeking evidence of nthropogenic depression tnle trends in say the relative abundance of wapiti (in Figur s 10-3 and 10-4) that is tr nds that are no t the r sult of sample size may go unddected by correlation analysis because oj onfla tion of those trends with sam pI -size effects

Cannon (2000 2001) suggests using Cochrans t st of linear trends a form of chi- quare analysis that tests for trends among mult iple rank-ordered samples (Zar 19 6562-565) As Cannon (2000332) notes Cochrans test is constructed uch that signifi cant trends will not be fou nd when samples are so small that random error cannot be mled out at a specified confjdence level as the cause of differences in relative abundance between samples Cochrans test seeks trends in relative abundall e in such a way as to mol directly take absolute sample size into account than correlation-based analyses One first calculates a standard chi-square [aostic and then detennines how much of that statistic is the resul t of a linear trend if the latter i sufficiently (s ta tistically significant) large then on condud s that there is indeed linear hend in lh data ind pendent of any effects of sample size

Let us reconsider the wapiti data in FigLlfe 10-3 The overall chi-square stashytisti is la rg and significant (X2 = 46966 P lt 0001 ) uggesting there is a sigshynifi ant association between the frequency of deer remains and the frequency of wapiti remain The chi-square statistic fo r a linear trend is also significant (X2 =

11296 P lt 0001) suggesting there i a significant tem poral trend in the re lative abundance of wapiti remains acr ss the 86 assemblages regard less of the sizes at the a semblages The simple best-fit regression line in Figure 10-3 is of no help in det rmining which d irection the trend is do wapi ti increase over time or deshycrease in abundance relative to the abund nee of deer The chi-square trend stashytistic fails to indicate the dir chon of change Figure 10-4 provides an indication that the trend is for wapiti mains t decrease in abundance

Whatever trends in tax nomi abundances there may be in Figure 10-3 and in Figure 10-4 must for the present be treated as methodological artifacts They could refl ect how remains were tallied how assembl ges were patiotemporally lumped or how they were graphically or statistically detected (see Lyman 2008 for additional d iscussion) Another example will demonstrate that uch methodshyological artifacts are not unusual Chatters (2004~73) found an inverse correlation between the number of sites in eastern Washington state in which bison [Bison bison] number more than 10 percent of the mammalian archaeofauna and date between 1800 and 2400 BP and a curve meant to estimat hwuan population size based on the frequency of radiocarbon dates (Figme 10-5) Although this may well represent a case of anthropogenic depres ion and subsequ nt release of bison populations from predation I perceive two potential methodologi al artifacts First there are only eight archaeologio l sites in the sample so the apshypearance of a correlation bet en human population size and bison avail bility

Fi

may b a fun ters could art in all sites in I during any 0

human popu The ece

of a curve be a pro y for n ters 1995) A may be are tested with a diocarbon re 2000b) Even i b n record n nor the frequ negatively) w man 2004b) 0 1

correlation AE 1 an incomplete nd sample size uge to warrant nent to seeking tive abtmdance

sult of sam ple lation of those

trends a form dered samples is constructed

e so small that as the calise of st seeks lrends )solute sample tes a standard tic is the result nt large then )endent of any

chi-squar slashythere is a sigshye frequency of gnifican t (X2 = in the reI live of the sizes of 3 is of no help er time or dcshyJan~ trend stashybull an ind ication

tgure 10-3 and artifacts They Itiotemporally e Lyman 2008

uch method shyse correla tion h bison [Bi on luna and date ttl popula tion A lthough this quent release e hodological Ie so the apshym a-ailabil ity

Prehist ric Anthropogenic Impacts Are Not Ubiquitous I 217

Number of Si tes Rrtdiocarboll Date Curve o 1 2 3 infrequent freq uent

1000

1200

1400

1600

~

~ 1800 ro ~ ~ 2000 b

lJt 2200

2400

2600

2800

3000

Figure 10-5 CUrle of archaeological radiocarbon ages as a surrogate meashysure of human pOuation size and frequency of site in which bison make up more than 10 percent of the marrzmalian archaeofnuna Redrawn from Chatshyter lt (200473 Figure 53) the radiocarbon age curve has been smoothed

may be a function of the f w sites comp rising the sample To counler th is Chat shyters could argue that th percentage of illl llngulatc remains that represent bison in all sites in eastern Vashington dating between 2001 and 2500 BP is higher than d uring any othe r 500-year period exc pI during the termin al Pleistocene when human populations were undoubtedly small (Lyman 2004b)

The second possible methodologicaJ artifact in Chatterss analysis is his use of a urve based on the frequency of rad iocarbon dates adj u ted for decay as a proxy f r reg ional [human] population size (Chc tL I S 200471 see also Chatshyters 1995) A smoothed version of the urve is shown in Figure 10-5 The curve may be a r asonable estimate of human population size but it h as not be n tes ted with any independent evidence of population size For example the ra shydiocarbon record for the area may b biased in one or more ways (Lyman 2000a 2000b) Even if th sa mple f radiocarbon dates is rcp resentati of the radiocar shybon record neither the frequenc y of radiocarbon d ates per 500-year in rement nor the f r quency of dated archaeological compon nts corTe late~ (positively or negatively) wi th the propor tion of ungulate remains that represent bison (Lyshyman 2004b) or with the N [SP of bison per 500-year increment (Figure 1O-6)lf the

Iso Szu ter and abundances of ~ed specifica lshyVent na ave took place As was used less ler sites in the Thus Ventnna g perspective tt because the leople altered ropogenically tensi e huntshyintensive bu t ion to remain

t tha t the faushyel Instead of Igh the stratishyam 1982) and 11989) Mdjor lthr pogenic d There arc d es no t beshyat re tl ct al1shy

palcofaunas ood p roclucshy~ uch in fl ushy_ prey hese gtxplana hons

ed by Olga thropogcnic ased an imal laiability of 5 thought to of remains mple) John sing d PCI1shy

~ge animals haeological

Preh islori Anthropogenic Impacls Are Not Ubiquitous I 211

record of farmers uld result from greater s lcctivity for large game on th part of tIl hunters for any of s vera1 reasons sLlch as in rea ed status from undertaking an ec nomically risky endeavor or the presen e of buffer zones (Hickerson 1965 also known as animal source areas see Pulliam 1988) between sedentary farm ers

Precisely these two possible cau es hav appeared in a recent d bate about a falU1al record created by p rehistoric foragers (Broughton and Bayham 2003 Hilshydebra ndt and M Guire 2002 200 ) Using the words of some of the p articipants the debate center around the que tion Was the (apparently) anthropogenic change in faunal taxonomic abundances driven by human desire for calories or a human desire for p restige (McGui re and Hildebrandt 2005) Resolving the debate w ill no doubt require innovative analyses meant to detect archa oIogically visible di ff ~ r nces between the two possibilities Stahl (2000) for example distinshyguished faunal remains accumulated and deposited by humans from r main s that J ad accumulated na turally and then considered th e ecological predilections o f the t xa in each subsampl (culturally accumulated and natu rally accumulated) to explain the an thropogenic nature of the fauna he studied This highlights the point rais d eaTlier tha t identify ing the cau e of a faunal abundance trend that is th exact opposite of th standard signature of an thropogenic influence willlikeJy demand complex multivariate analyses For example it has been suggested that whether it was a desire for calories or a desire for pr stige may be the incorrect place to look the p rtinent fa una l trends may have resu lted from chang s in techshynology in kind or how it was II cd (Hockett 2005) Confirma tion of this possibility demallds not only detailed study of tools but also determination of whether shifts in technology w re a clt use or a cons qucnce of hifls in the ava ilnbility of prey taxa (eg Lupo and Schm itt 2005)

Instances of No Apparent Anthropogenic Influence

I turn now to instances in which the fa unal record suggests there was nn an th ropogenic influence or at least there was no eviden e of such influence The la tter impl ies that the m agnitude of influence may no t impact a fauna beshycau se of Inw intenSity or tha t the zooarchaeological signal of such influence is so w ak as t be imper middoteptibl- J am awme of two kinds of stu dies in which no evidence of anthropogenic influence was found In one the nbsence of a trend is readily explained b prey ehav ior in the othel~ there is no obvious explanation for the absence of ~ trend in taxonomic abundance and that is cri tical

Tn an arly study of pinniped pmains from the I te Holocene of the Oregon coast I argued th t dep ression of local populations of several taxa was not apparshyent because indices of abundances of p referr d prey did not uniformly decrease as the foraging model suggestd they should (Lyman 1995) Others thought those same data suggested tha t the metapopulation (the total population of a taxon) had indeed bl~en depressed (read depleted) (Jones and Hildebrandt 1995) I subsequently fou nd tha t the abundance of a local popUlation of Steller sea lions (Eumetopias jubatus) did not seem to be depress(d over the 700-yeaJ dllation of site form ation largely because abou t 90 percent of the remains were fro m adult

212 I R L Lyman

males-the demographic cat gory th at could be exploited w iUl0ut major influshyence on the loc 1popuLation given rep roductive behaviors of this taxon (Lyman 2003a) ln this case the reason that no evidence of an thropogenic depression w as fou nd involved vad ti n in the escape behaviors across age-sex classes of the population Adult females and yOWlg of both sexes flee in to the water at lhe fi rs t sign f danger on land w hi le adult bre ding-age ma les defend terrestrial breedshying territories against all com 1S Culling m ostly ad ult males if not excessive would not influen e the ize of the population And con traJY to som who say this r p resents p rehistoric conservation (Alvard 1998) it in fact does not because it did not involve the int n tional exploitation f a certain fraction of th e populashytion such as is usu ally meant by the term conservation (Smith and Wishnie 2000) In tead the lack of anthropogenic infllenc was an epiphen menan (Hu nn 1982) of which age-sex class of p rey animals was exploited which ilself was a function o f prey escape behavior and how availilble t clmology was used

In another study Butler and am pbeU (2004) reviewed zooard1aeological d ta for the southern Northwest Coas t and for the northern Col umbia Plateau environmentally and archaeologically distinct area in the Paci fic Northwest of North America In bo th areas they found no changE in relative abundances oi high-value and low-valu fi sh through time and they found no change in abw1shydances of high- lue mammals (artiodaclyls) relati e to abund ances [low-value mammaL They suggest th t th lalter may be the result of en virolUl1ental change in th C lumbia Plateau but that explanation does not ae aunt for the Northwe t Coast data They also suggesl that the reprodueti e sbmiddotategy and li f cycle of salmshyon me y render these fi sh somewhat imm une to expl itation-related depression They hypo thesize as well thal hu m n populations in both areas may never have been suffi ciently large to significan tly in fl uence fis h and mammal populations Finally But le r and ampbell (2004391) suggest their scale of an lysis may have caused them to not fi nd evidence f resource d p r ssion In my iew the struggle and u ltimate failure they have in fi nding an explanation for the lack of evidence of resource depression highlights two thin gs First pedlap_ we too read ily accept evidence of depression in the form of decreased abwldance of hig -value prey And second we tend to work hard at xplaining the posite of the signature bmiddotend in order to maintain some ersion o f the resource-depression model When there is no trend in taxonomic abundances we may be left wiLh ltl con undrum

False Signals of Anthropogenic Influence

The case of the pinnipeds on the Oregon coast suggests tha t spa tial grain may influence whether or not vidence of anlhmpogenic influence is deshytected A coarse spatial gr in is one in w hich a me tapopulation is under study a fine patial grain is one in w hich an individual local population is under study In the case of the Oregon pinnip ds the oar e spatia l grain sugg sted anthroshypogenic influence whereas a fine spatial grain suggested no anlhropogenic influshyence in the location scrutinized There is an oLher example of how geographic resolu tion grain might influence results that warran ts m n tiol1

Kay (199 10000 years ( or wapiti (Ce abundance 01 small (Figure th e enLire sev popula tions t Yellowstone i When h is dat when the spa less time and som time pe

Considel ern Washingt blages of fau wapiti (mail (Lym an 2004 blage against Further usin~ man 2004a) I the abwldanc seemed at th( dances [ fou middot pgt 9) and fo n ificantly frOl no evidence I

resented If 1middot period in wh period corres 10-4) The sil zer and the son 11 re is t11 abundances c What is the way At pres other potenti

To this f and bivariate the tTadition ing trends wi Calculating c sample size ( non 2000 20( samp le sizes of 5 and an a1 percent of thl

major inpoundlushylXOn (Lyman pression was lasses of the middoter at the firs t ~strial breedshyot excessive )mE who say nol because f the populashyishnie 2000) (Hunn 1982) as a fu nction

middotchaeological lbia Plateau -Iorthwest of undances of nge in abW1shyof low -valu ental change e Northwest yele of salmshydepression

1 never have populations may have th struggle of evidence

adily accept l-value prey he signa lure lOdeJ When lUndrum

that spatial uence is dlshyder stud y a mder s udy ted anthroshy)genic influshygeographic

Prehistoric Anthropogenic Impacts Are Not Ubiquitous I 213

Kay (1994) lumped zooarchaeologi a1 da ta from seven western states and 10000 years of prehistory He found that the abundance of North American elk or wapiti (Cervus elaphus) remains fo r that patiotemporal area relative to the abundance of wapiti in the modern Yellow tone ecosy tern was exceptionally small (Figur 10-2) He then extrapolated from the Yellowstone ecosystem to the enti re seven-state area arguing tha l prehistoric hunters had depleted wapiti pop ulations throughou t the Holocene and th modern abundance of wapiti in ~ 110wst ne is an arti fact of tw entieth-century wild life and park management When his data are eli ided into more spatiotelTlporally limited samples that is when the spatiotemp ral uni ts arc changed to much finer grain units containing less time and less space vidence for depT ssion vanishes in some areas and in some time periods (Lym an 2004a)

Considel~ for example the data fr m Holocene archaeological sites in eastshyern Washington state These data represent 86 spatiotemporally d istinct assemshyblages of faunal remains In an earli r analy is I calculated the proportion of wapiti remains among summed wapiti and de r remains for each assemblage (Lyman 2004a) A bivaria te plo t of th proportion of wapiti remains in an assemshyblage against the ge of the assemblage reveals no obvious trend (Figure 10-3) Fur ther using the lhen standard analy tical techniques in my earlier analysis (Lyshyman 2004a) 1 found no correlation between the deer plus wapi ti samples anL the lt bundance of w pin rem ain per assemblage (r 16 P= 14) Sample size it seemed at the time was not d riving any trend (or lack thereof) in wapiti abw1shydances I fo und no correlation be tween age and proportion of wapiti (r = 006 P gt 9) and found that the slope of the best-fit regression line did not differ sigshynifican tly from zero (Figure 10-3) This prompted me to concl ude that there w as no evidence fo r the d pres ion (depletion) of wapiti over the 10000 years repshyresented If however the wapiti and deer remains are summed by the SOO-year period in which they occur the proportion of wapiti remains for each SOO-year period corresponds very nicely t the anthropogenic depression model (Figur 10-4) The simple best-fit regIe sion line has a slope sign ifjcantly different from zero and the two vari ables are orrelated (I = 489 P = 064) The importan t lesshyson here is thal a trend in taxonomic abundances may be an artifact of how tho e abtlJ1dan es are talli ed This observation demands that we consider the qm tiol1 What is th correct way to tally those abundances or i there a single correct way At present thi question cannot be answered And sadly ther is yet anshyother potential problem here

To this point I have used particular statistical analyses (simple correlation) and bivaria le plots to search for evidence of anthropogenic depression both are the Lradi tional m ans of s arching y t neither is pcuticularly sensitive to detectshying trends when percentag s or proportions ar used as measures of abundan ce Calcula ting a correlation coefficient betvveen relative abundances of taxa and ample size ([ SP) is not the best way to sta tis ti Ily search for tr nds (Canshy

non 2000 2001) This is so becau relative abundance do not r gister wh ther sa mple sizes are 5 or 5000 Statist ically the di fference b tween an absolute ta lly of 5 and an absolu te taUy of 5000 i quite d ifferent from saying each comprises per ent of Lhe total collection (100 and 100000 respectively) The effect of small

214 I R L Lyman

Figure 10-2 Relashytive abundances of North American wa-

Piti and other artioshydactyls in the modern Yellowstone ecosysshytem compared 0 the relative abundances ofwapiti remains and rel1ains of other arshytiodaclyls in archaeoshylogiwl sites in seven western states (data from Kay 1994)

100 -------------------------------~

QJ

80

~

~ 40 ~

20

bull Yellowstone

bull Intermontane West

Wapiti Other Ungulate Taxa

05 ----------------------------

o o o

o

04 0 0

o o

0~ 03 cU C cs

middotn 0 5 0

0 ~ 02 0 0 c 0

0

C DoD~

0

01 0 0

0 0

o 0 0

o ciDa o B 0 o 0 0

0 00 ~~ 0 rn lib 0 0 sect 0 8 0 g rP 00

a 2000 tOOO 6000 8000 10000 Age (radiocarbon years BP)

Figure 10-3 Proportion of wapiti remains among summed wapiti and deer remains in 86 assemblages from eastern Washington state (da ta from Lyman 2004a) The slope of the simple best-fit regres ion line is not sigl1ificantly differshyent from zero and there i no correlation between age and proportion of wapiti

06

05

04 x OJ

U

s ~ 03 11

~ 02

0

01

00 0 0 Of)

f r

s Ii v

samples on accurate ref inventory t the abW1dat bUl sample not be accUJ relatively m sampling er INISP acro sampling er

Use of ur 10-3 an hypothesis 1 no trend ) or there is no t the null hn sam ples tha correl tion ( source of thE

r

10000

ti l11ld dctl om Lyman II tty diffe1shy of wapiti

Preh istoric Anth ropogenic Impacts Are Not Ubiquitous I 215

06

0 05

04

x 000

s I 03 D 2

02

01

0 0 00

0 000

0 0 0 D C Cgt C 0 co Cgt Q Cgt Cgt 0 Cgt 0 c 0 0 co 0 0 c 0 0 Cgt 0 0 0 0 Cgt 0 8 C

Q U) Cgt 8 en 0 U) Cgt 0 co 1 1 0 cr-N~ T 7 ~I r 7 1 l l 1 ~5 0 Cgt 5 0 ltgt 0 0 0 0 c5 sect S

n 0 r ltgt f) 0 0 u 8 n co ~ N rlt) lt-- ~ U lR h tt 00

I

Age (radiocarbon years BP)

Figure 10-4 Proportion of wapiti remaiJls among summed wapiti and deer remains by SOO-year period for 86 assemblages from eas tern Washington state (data from Lyman 2004a) The slope of the simple best-fit regression line is sigllificantly different from zero and the age and proportion of wapiti variables are correlated (1 = 489 P = 064)

samples on corr la tions may simply be due to sampling error ralher than any accurate [-fle lion of abundance Rar phcnom na are particula rl y difficult to in entory they wi ll be ab ent from collections unless the sampleti arc large H th abundances of tie ral rare taxa are not quite equal in the target pop ula tion bu t samples are sm all the true rela tive abundan ces of those rare taxa likely will not be accurately refle ted by small sam ples (Grayson 1984) S )mc taxa v il be relatively more abundant some k ss abundnnt in th sample simply bec use of ampling error Thus a correIalion betvvee the relative abundance of a taxon and

[ Nl P across m ultiple assemblages may be driven by sm all sam ples because of sam pIing error

se of th regression approach to search for sa mplc-size effecls (as in Figshyures 10-3 and 10-4) may lead to commission of a Type I error (rejecting a lru null hypothesis that there is no true trend in relative abundances vhen in fact there is no trend) or com mi ssion of a Type II error (accepting a fa l e nu ll hypothesis that there is no true tren d in abundances when in fact there is a trend) In bo th cases the null hypothesis is th t no trend is presen t bulampling error has produced a mples that a r not representative of the p opu lation Traditionally a signifi cant correlation coeffici nt has been in terpreted a indicating that sample size is the sou rce of the correlation and lh absence of tiign ificant correlation coeffici nt is

2] 6 I K L Lyman

interpreted as indica ting that sampl size is not the source of the correlation As Cannon (2001 185) obser ed the firs t interpr tabon at best rests on an incomplete understanding of the relationship between relative abundances and sample size the second interpret tion pre urnes sample sizes ar sllfficientl y large to warrant confidence but in fact they may be too sma ll In lerm more pertinent to seeking evidence of nthropogenic depression tnle trends in say the relative abundance of wapiti (in Figur s 10-3 and 10-4) that is tr nds that are no t the r sult of sample size may go unddected by correlation analysis because oj onfla tion of those trends with sam pI -size effects

Cannon (2000 2001) suggests using Cochrans t st of linear trends a form of chi- quare analysis that tests for trends among mult iple rank-ordered samples (Zar 19 6562-565) As Cannon (2000332) notes Cochrans test is constructed uch that signifi cant trends will not be fou nd when samples are so small that random error cannot be mled out at a specified confjdence level as the cause of differences in relative abundance between samples Cochrans test seeks trends in relative abundall e in such a way as to mol directly take absolute sample size into account than correlation-based analyses One first calculates a standard chi-square [aostic and then detennines how much of that statistic is the resul t of a linear trend if the latter i sufficiently (s ta tistically significant) large then on condud s that there is indeed linear hend in lh data ind pendent of any effects of sample size

Let us reconsider the wapiti data in FigLlfe 10-3 The overall chi-square stashytisti is la rg and significant (X2 = 46966 P lt 0001 ) uggesting there is a sigshynifi ant association between the frequency of deer remains and the frequency of wapiti remain The chi-square statistic fo r a linear trend is also significant (X2 =

11296 P lt 0001) suggesting there i a significant tem poral trend in the re lative abundance of wapiti remains acr ss the 86 assemblages regard less of the sizes at the a semblages The simple best-fit regression line in Figure 10-3 is of no help in det rmining which d irection the trend is do wapi ti increase over time or deshycrease in abundance relative to the abund nee of deer The chi-square trend stashytistic fails to indicate the dir chon of change Figure 10-4 provides an indication that the trend is for wapiti mains t decrease in abundance

Whatever trends in tax nomi abundances there may be in Figure 10-3 and in Figure 10-4 must for the present be treated as methodological artifacts They could refl ect how remains were tallied how assembl ges were patiotemporally lumped or how they were graphically or statistically detected (see Lyman 2008 for additional d iscussion) Another example will demonstrate that uch methodshyological artifacts are not unusual Chatters (2004~73) found an inverse correlation between the number of sites in eastern Washington state in which bison [Bison bison] number more than 10 percent of the mammalian archaeofauna and date between 1800 and 2400 BP and a curve meant to estimat hwuan population size based on the frequency of radiocarbon dates (Figme 10-5) Although this may well represent a case of anthropogenic depres ion and subsequ nt release of bison populations from predation I perceive two potential methodologi al artifacts First there are only eight archaeologio l sites in the sample so the apshypearance of a correlation bet en human population size and bison avail bility

Fi

may b a fun ters could art in all sites in I during any 0

human popu The ece

of a curve be a pro y for n ters 1995) A may be are tested with a diocarbon re 2000b) Even i b n record n nor the frequ negatively) w man 2004b) 0 1

correlation AE 1 an incomplete nd sample size uge to warrant nent to seeking tive abtmdance

sult of sam ple lation of those

trends a form dered samples is constructed

e so small that as the calise of st seeks lrends )solute sample tes a standard tic is the result nt large then )endent of any

chi-squar slashythere is a sigshye frequency of gnifican t (X2 = in the reI live of the sizes of 3 is of no help er time or dcshyJan~ trend stashybull an ind ication

tgure 10-3 and artifacts They Itiotemporally e Lyman 2008

uch method shyse correla tion h bison [Bi on luna and date ttl popula tion A lthough this quent release e hodological Ie so the apshym a-ailabil ity

Prehist ric Anthropogenic Impacts Are Not Ubiquitous I 217

Number of Si tes Rrtdiocarboll Date Curve o 1 2 3 infrequent freq uent

1000

1200

1400

1600

~

~ 1800 ro ~ ~ 2000 b

lJt 2200

2400

2600

2800

3000

Figure 10-5 CUrle of archaeological radiocarbon ages as a surrogate meashysure of human pOuation size and frequency of site in which bison make up more than 10 percent of the marrzmalian archaeofnuna Redrawn from Chatshyter lt (200473 Figure 53) the radiocarbon age curve has been smoothed

may be a function of the f w sites comp rising the sample To counler th is Chat shyters could argue that th percentage of illl llngulatc remains that represent bison in all sites in eastern Vashington dating between 2001 and 2500 BP is higher than d uring any othe r 500-year period exc pI during the termin al Pleistocene when human populations were undoubtedly small (Lyman 2004b)

The second possible methodologicaJ artifact in Chatterss analysis is his use of a urve based on the frequency of rad iocarbon dates adj u ted for decay as a proxy f r reg ional [human] population size (Chc tL I S 200471 see also Chatshyters 1995) A smoothed version of the urve is shown in Figure 10-5 The curve may be a r asonable estimate of human population size but it h as not be n tes ted with any independent evidence of population size For example the ra shydiocarbon record for the area may b biased in one or more ways (Lyman 2000a 2000b) Even if th sa mple f radiocarbon dates is rcp resentati of the radiocar shybon record neither the frequenc y of radiocarbon d ates per 500-year in rement nor the f r quency of dated archaeological compon nts corTe late~ (positively or negatively) wi th the propor tion of ungulate remains that represent bison (Lyshyman 2004b) or with the N [SP of bison per 500-year increment (Figure 1O-6)lf the

212 I R L Lyman

males-the demographic cat gory th at could be exploited w iUl0ut major influshyence on the loc 1popuLation given rep roductive behaviors of this taxon (Lyman 2003a) ln this case the reason that no evidence of an thropogenic depression w as fou nd involved vad ti n in the escape behaviors across age-sex classes of the population Adult females and yOWlg of both sexes flee in to the water at lhe fi rs t sign f danger on land w hi le adult bre ding-age ma les defend terrestrial breedshying territories against all com 1S Culling m ostly ad ult males if not excessive would not influen e the ize of the population And con traJY to som who say this r p resents p rehistoric conservation (Alvard 1998) it in fact does not because it did not involve the int n tional exploitation f a certain fraction of th e populashytion such as is usu ally meant by the term conservation (Smith and Wishnie 2000) In tead the lack of anthropogenic infllenc was an epiphen menan (Hu nn 1982) of which age-sex class of p rey animals was exploited which ilself was a function o f prey escape behavior and how availilble t clmology was used

In another study Butler and am pbeU (2004) reviewed zooard1aeological d ta for the southern Northwest Coas t and for the northern Col umbia Plateau environmentally and archaeologically distinct area in the Paci fic Northwest of North America In bo th areas they found no changE in relative abundances oi high-value and low-valu fi sh through time and they found no change in abw1shydances of high- lue mammals (artiodaclyls) relati e to abund ances [low-value mammaL They suggest th t th lalter may be the result of en virolUl1ental change in th C lumbia Plateau but that explanation does not ae aunt for the Northwe t Coast data They also suggesl that the reprodueti e sbmiddotategy and li f cycle of salmshyon me y render these fi sh somewhat imm une to expl itation-related depression They hypo thesize as well thal hu m n populations in both areas may never have been suffi ciently large to significan tly in fl uence fis h and mammal populations Finally But le r and ampbell (2004391) suggest their scale of an lysis may have caused them to not fi nd evidence f resource d p r ssion In my iew the struggle and u ltimate failure they have in fi nding an explanation for the lack of evidence of resource depression highlights two thin gs First pedlap_ we too read ily accept evidence of depression in the form of decreased abwldance of hig -value prey And second we tend to work hard at xplaining the posite of the signature bmiddotend in order to maintain some ersion o f the resource-depression model When there is no trend in taxonomic abundances we may be left wiLh ltl con undrum

False Signals of Anthropogenic Influence

The case of the pinnipeds on the Oregon coast suggests tha t spa tial grain may influence whether or not vidence of anlhmpogenic influence is deshytected A coarse spatial gr in is one in w hich a me tapopulation is under study a fine patial grain is one in w hich an individual local population is under study In the case of the Oregon pinnip ds the oar e spatia l grain sugg sted anthroshypogenic influence whereas a fine spatial grain suggested no anlhropogenic influshyence in the location scrutinized There is an oLher example of how geographic resolu tion grain might influence results that warran ts m n tiol1

Kay (199 10000 years ( or wapiti (Ce abundance 01 small (Figure th e enLire sev popula tions t Yellowstone i When h is dat when the spa less time and som time pe

Considel ern Washingt blages of fau wapiti (mail (Lym an 2004 blage against Further usin~ man 2004a) I the abwldanc seemed at th( dances [ fou middot pgt 9) and fo n ificantly frOl no evidence I

resented If 1middot period in wh period corres 10-4) The sil zer and the son 11 re is t11 abundances c What is the way At pres other potenti

To this f and bivariate the tTadition ing trends wi Calculating c sample size ( non 2000 20( samp le sizes of 5 and an a1 percent of thl

major inpoundlushylXOn (Lyman pression was lasses of the middoter at the firs t ~strial breedshyot excessive )mE who say nol because f the populashyishnie 2000) (Hunn 1982) as a fu nction

middotchaeological lbia Plateau -Iorthwest of undances of nge in abW1shyof low -valu ental change e Northwest yele of salmshydepression

1 never have populations may have th struggle of evidence

adily accept l-value prey he signa lure lOdeJ When lUndrum

that spatial uence is dlshyder stud y a mder s udy ted anthroshy)genic influshygeographic

Prehistoric Anthropogenic Impacts Are Not Ubiquitous I 213

Kay (1994) lumped zooarchaeologi a1 da ta from seven western states and 10000 years of prehistory He found that the abundance of North American elk or wapiti (Cervus elaphus) remains fo r that patiotemporal area relative to the abundance of wapiti in the modern Yellow tone ecosy tern was exceptionally small (Figur 10-2) He then extrapolated from the Yellowstone ecosystem to the enti re seven-state area arguing tha l prehistoric hunters had depleted wapiti pop ulations throughou t the Holocene and th modern abundance of wapiti in ~ 110wst ne is an arti fact of tw entieth-century wild life and park management When his data are eli ided into more spatiotelTlporally limited samples that is when the spatiotemp ral uni ts arc changed to much finer grain units containing less time and less space vidence for depT ssion vanishes in some areas and in some time periods (Lym an 2004a)

Considel~ for example the data fr m Holocene archaeological sites in eastshyern Washington state These data represent 86 spatiotemporally d istinct assemshyblages of faunal remains In an earli r analy is I calculated the proportion of wapiti remains among summed wapiti and de r remains for each assemblage (Lyman 2004a) A bivaria te plo t of th proportion of wapiti remains in an assemshyblage against the ge of the assemblage reveals no obvious trend (Figure 10-3) Fur ther using the lhen standard analy tical techniques in my earlier analysis (Lyshyman 2004a) 1 found no correlation between the deer plus wapi ti samples anL the lt bundance of w pin rem ain per assemblage (r 16 P= 14) Sample size it seemed at the time was not d riving any trend (or lack thereof) in wapiti abw1shydances I fo und no correlation be tween age and proportion of wapiti (r = 006 P gt 9) and found that the slope of the best-fit regression line did not differ sigshynifican tly from zero (Figure 10-3) This prompted me to concl ude that there w as no evidence fo r the d pres ion (depletion) of wapiti over the 10000 years repshyresented If however the wapiti and deer remains are summed by the SOO-year period in which they occur the proportion of wapiti remains for each SOO-year period corresponds very nicely t the anthropogenic depression model (Figur 10-4) The simple best-fit regIe sion line has a slope sign ifjcantly different from zero and the two vari ables are orrelated (I = 489 P = 064) The importan t lesshyson here is thal a trend in taxonomic abundances may be an artifact of how tho e abtlJ1dan es are talli ed This observation demands that we consider the qm tiol1 What is th correct way to tally those abundances or i there a single correct way At present thi question cannot be answered And sadly ther is yet anshyother potential problem here

To this point I have used particular statistical analyses (simple correlation) and bivaria le plots to search for evidence of anthropogenic depression both are the Lradi tional m ans of s arching y t neither is pcuticularly sensitive to detectshying trends when percentag s or proportions ar used as measures of abundan ce Calcula ting a correlation coefficient betvveen relative abundances of taxa and ample size ([ SP) is not the best way to sta tis ti Ily search for tr nds (Canshy

non 2000 2001) This is so becau relative abundance do not r gister wh ther sa mple sizes are 5 or 5000 Statist ically the di fference b tween an absolute ta lly of 5 and an absolu te taUy of 5000 i quite d ifferent from saying each comprises per ent of Lhe total collection (100 and 100000 respectively) The effect of small

214 I R L Lyman

Figure 10-2 Relashytive abundances of North American wa-

Piti and other artioshydactyls in the modern Yellowstone ecosysshytem compared 0 the relative abundances ofwapiti remains and rel1ains of other arshytiodaclyls in archaeoshylogiwl sites in seven western states (data from Kay 1994)

100 -------------------------------~

QJ

80

~

~ 40 ~

20

bull Yellowstone

bull Intermontane West

Wapiti Other Ungulate Taxa

05 ----------------------------

o o o

o

04 0 0

o o

0~ 03 cU C cs

middotn 0 5 0

0 ~ 02 0 0 c 0

0

C DoD~

0

01 0 0

0 0

o 0 0

o ciDa o B 0 o 0 0

0 00 ~~ 0 rn lib 0 0 sect 0 8 0 g rP 00

a 2000 tOOO 6000 8000 10000 Age (radiocarbon years BP)

Figure 10-3 Proportion of wapiti remains among summed wapiti and deer remains in 86 assemblages from eastern Washington state (da ta from Lyman 2004a) The slope of the simple best-fit regres ion line is not sigl1ificantly differshyent from zero and there i no correlation between age and proportion of wapiti

06

05

04 x OJ

U

s ~ 03 11

~ 02

0

01

00 0 0 Of)

f r

s Ii v

samples on accurate ref inventory t the abW1dat bUl sample not be accUJ relatively m sampling er INISP acro sampling er

Use of ur 10-3 an hypothesis 1 no trend ) or there is no t the null hn sam ples tha correl tion ( source of thE

r

10000

ti l11ld dctl om Lyman II tty diffe1shy of wapiti

Preh istoric Anth ropogenic Impacts Are Not Ubiquitous I 215

06

0 05

04

x 000

s I 03 D 2

02

01

0 0 00

0 000

0 0 0 D C Cgt C 0 co Cgt Q Cgt Cgt 0 Cgt 0 c 0 0 co 0 0 c 0 0 Cgt 0 0 0 0 Cgt 0 8 C

Q U) Cgt 8 en 0 U) Cgt 0 co 1 1 0 cr-N~ T 7 ~I r 7 1 l l 1 ~5 0 Cgt 5 0 ltgt 0 0 0 0 c5 sect S

n 0 r ltgt f) 0 0 u 8 n co ~ N rlt) lt-- ~ U lR h tt 00

I

Age (radiocarbon years BP)

Figure 10-4 Proportion of wapiti remaiJls among summed wapiti and deer remains by SOO-year period for 86 assemblages from eas tern Washington state (data from Lyman 2004a) The slope of the simple best-fit regression line is sigllificantly different from zero and the age and proportion of wapiti variables are correlated (1 = 489 P = 064)

samples on corr la tions may simply be due to sampling error ralher than any accurate [-fle lion of abundance Rar phcnom na are particula rl y difficult to in entory they wi ll be ab ent from collections unless the sampleti arc large H th abundances of tie ral rare taxa are not quite equal in the target pop ula tion bu t samples are sm all the true rela tive abundan ces of those rare taxa likely will not be accurately refle ted by small sam ples (Grayson 1984) S )mc taxa v il be relatively more abundant some k ss abundnnt in th sample simply bec use of ampling error Thus a correIalion betvvee the relative abundance of a taxon and

[ Nl P across m ultiple assemblages may be driven by sm all sam ples because of sam pIing error

se of th regression approach to search for sa mplc-size effecls (as in Figshyures 10-3 and 10-4) may lead to commission of a Type I error (rejecting a lru null hypothesis that there is no true trend in relative abundances vhen in fact there is no trend) or com mi ssion of a Type II error (accepting a fa l e nu ll hypothesis that there is no true tren d in abundances when in fact there is a trend) In bo th cases the null hypothesis is th t no trend is presen t bulampling error has produced a mples that a r not representative of the p opu lation Traditionally a signifi cant correlation coeffici nt has been in terpreted a indicating that sample size is the sou rce of the correlation and lh absence of tiign ificant correlation coeffici nt is

2] 6 I K L Lyman

interpreted as indica ting that sampl size is not the source of the correlation As Cannon (2001 185) obser ed the firs t interpr tabon at best rests on an incomplete understanding of the relationship between relative abundances and sample size the second interpret tion pre urnes sample sizes ar sllfficientl y large to warrant confidence but in fact they may be too sma ll In lerm more pertinent to seeking evidence of nthropogenic depression tnle trends in say the relative abundance of wapiti (in Figur s 10-3 and 10-4) that is tr nds that are no t the r sult of sample size may go unddected by correlation analysis because oj onfla tion of those trends with sam pI -size effects

Cannon (2000 2001) suggests using Cochrans t st of linear trends a form of chi- quare analysis that tests for trends among mult iple rank-ordered samples (Zar 19 6562-565) As Cannon (2000332) notes Cochrans test is constructed uch that signifi cant trends will not be fou nd when samples are so small that random error cannot be mled out at a specified confjdence level as the cause of differences in relative abundance between samples Cochrans test seeks trends in relative abundall e in such a way as to mol directly take absolute sample size into account than correlation-based analyses One first calculates a standard chi-square [aostic and then detennines how much of that statistic is the resul t of a linear trend if the latter i sufficiently (s ta tistically significant) large then on condud s that there is indeed linear hend in lh data ind pendent of any effects of sample size

Let us reconsider the wapiti data in FigLlfe 10-3 The overall chi-square stashytisti is la rg and significant (X2 = 46966 P lt 0001 ) uggesting there is a sigshynifi ant association between the frequency of deer remains and the frequency of wapiti remain The chi-square statistic fo r a linear trend is also significant (X2 =

11296 P lt 0001) suggesting there i a significant tem poral trend in the re lative abundance of wapiti remains acr ss the 86 assemblages regard less of the sizes at the a semblages The simple best-fit regression line in Figure 10-3 is of no help in det rmining which d irection the trend is do wapi ti increase over time or deshycrease in abundance relative to the abund nee of deer The chi-square trend stashytistic fails to indicate the dir chon of change Figure 10-4 provides an indication that the trend is for wapiti mains t decrease in abundance

Whatever trends in tax nomi abundances there may be in Figure 10-3 and in Figure 10-4 must for the present be treated as methodological artifacts They could refl ect how remains were tallied how assembl ges were patiotemporally lumped or how they were graphically or statistically detected (see Lyman 2008 for additional d iscussion) Another example will demonstrate that uch methodshyological artifacts are not unusual Chatters (2004~73) found an inverse correlation between the number of sites in eastern Washington state in which bison [Bison bison] number more than 10 percent of the mammalian archaeofauna and date between 1800 and 2400 BP and a curve meant to estimat hwuan population size based on the frequency of radiocarbon dates (Figme 10-5) Although this may well represent a case of anthropogenic depres ion and subsequ nt release of bison populations from predation I perceive two potential methodologi al artifacts First there are only eight archaeologio l sites in the sample so the apshypearance of a correlation bet en human population size and bison avail bility

Fi

may b a fun ters could art in all sites in I during any 0

human popu The ece

of a curve be a pro y for n ters 1995) A may be are tested with a diocarbon re 2000b) Even i b n record n nor the frequ negatively) w man 2004b) 0 1

correlation AE 1 an incomplete nd sample size uge to warrant nent to seeking tive abtmdance

sult of sam ple lation of those

trends a form dered samples is constructed

e so small that as the calise of st seeks lrends )solute sample tes a standard tic is the result nt large then )endent of any

chi-squar slashythere is a sigshye frequency of gnifican t (X2 = in the reI live of the sizes of 3 is of no help er time or dcshyJan~ trend stashybull an ind ication

tgure 10-3 and artifacts They Itiotemporally e Lyman 2008

uch method shyse correla tion h bison [Bi on luna and date ttl popula tion A lthough this quent release e hodological Ie so the apshym a-ailabil ity

Prehist ric Anthropogenic Impacts Are Not Ubiquitous I 217

Number of Si tes Rrtdiocarboll Date Curve o 1 2 3 infrequent freq uent

1000

1200

1400

1600

~

~ 1800 ro ~ ~ 2000 b

lJt 2200

2400

2600

2800

3000

Figure 10-5 CUrle of archaeological radiocarbon ages as a surrogate meashysure of human pOuation size and frequency of site in which bison make up more than 10 percent of the marrzmalian archaeofnuna Redrawn from Chatshyter lt (200473 Figure 53) the radiocarbon age curve has been smoothed

may be a function of the f w sites comp rising the sample To counler th is Chat shyters could argue that th percentage of illl llngulatc remains that represent bison in all sites in eastern Vashington dating between 2001 and 2500 BP is higher than d uring any othe r 500-year period exc pI during the termin al Pleistocene when human populations were undoubtedly small (Lyman 2004b)

The second possible methodologicaJ artifact in Chatterss analysis is his use of a urve based on the frequency of rad iocarbon dates adj u ted for decay as a proxy f r reg ional [human] population size (Chc tL I S 200471 see also Chatshyters 1995) A smoothed version of the urve is shown in Figure 10-5 The curve may be a r asonable estimate of human population size but it h as not be n tes ted with any independent evidence of population size For example the ra shydiocarbon record for the area may b biased in one or more ways (Lyman 2000a 2000b) Even if th sa mple f radiocarbon dates is rcp resentati of the radiocar shybon record neither the frequenc y of radiocarbon d ates per 500-year in rement nor the f r quency of dated archaeological compon nts corTe late~ (positively or negatively) wi th the propor tion of ungulate remains that represent bison (Lyshyman 2004b) or with the N [SP of bison per 500-year increment (Figure 1O-6)lf the

major inpoundlushylXOn (Lyman pression was lasses of the middoter at the firs t ~strial breedshyot excessive )mE who say nol because f the populashyishnie 2000) (Hunn 1982) as a fu nction

middotchaeological lbia Plateau -Iorthwest of undances of nge in abW1shyof low -valu ental change e Northwest yele of salmshydepression

1 never have populations may have th struggle of evidence

adily accept l-value prey he signa lure lOdeJ When lUndrum

that spatial uence is dlshyder stud y a mder s udy ted anthroshy)genic influshygeographic

Prehistoric Anthropogenic Impacts Are Not Ubiquitous I 213

Kay (1994) lumped zooarchaeologi a1 da ta from seven western states and 10000 years of prehistory He found that the abundance of North American elk or wapiti (Cervus elaphus) remains fo r that patiotemporal area relative to the abundance of wapiti in the modern Yellow tone ecosy tern was exceptionally small (Figur 10-2) He then extrapolated from the Yellowstone ecosystem to the enti re seven-state area arguing tha l prehistoric hunters had depleted wapiti pop ulations throughou t the Holocene and th modern abundance of wapiti in ~ 110wst ne is an arti fact of tw entieth-century wild life and park management When his data are eli ided into more spatiotelTlporally limited samples that is when the spatiotemp ral uni ts arc changed to much finer grain units containing less time and less space vidence for depT ssion vanishes in some areas and in some time periods (Lym an 2004a)

Considel~ for example the data fr m Holocene archaeological sites in eastshyern Washington state These data represent 86 spatiotemporally d istinct assemshyblages of faunal remains In an earli r analy is I calculated the proportion of wapiti remains among summed wapiti and de r remains for each assemblage (Lyman 2004a) A bivaria te plo t of th proportion of wapiti remains in an assemshyblage against the ge of the assemblage reveals no obvious trend (Figure 10-3) Fur ther using the lhen standard analy tical techniques in my earlier analysis (Lyshyman 2004a) 1 found no correlation between the deer plus wapi ti samples anL the lt bundance of w pin rem ain per assemblage (r 16 P= 14) Sample size it seemed at the time was not d riving any trend (or lack thereof) in wapiti abw1shydances I fo und no correlation be tween age and proportion of wapiti (r = 006 P gt 9) and found that the slope of the best-fit regression line did not differ sigshynifican tly from zero (Figure 10-3) This prompted me to concl ude that there w as no evidence fo r the d pres ion (depletion) of wapiti over the 10000 years repshyresented If however the wapiti and deer remains are summed by the SOO-year period in which they occur the proportion of wapiti remains for each SOO-year period corresponds very nicely t the anthropogenic depression model (Figur 10-4) The simple best-fit regIe sion line has a slope sign ifjcantly different from zero and the two vari ables are orrelated (I = 489 P = 064) The importan t lesshyson here is thal a trend in taxonomic abundances may be an artifact of how tho e abtlJ1dan es are talli ed This observation demands that we consider the qm tiol1 What is th correct way to tally those abundances or i there a single correct way At present thi question cannot be answered And sadly ther is yet anshyother potential problem here

To this point I have used particular statistical analyses (simple correlation) and bivaria le plots to search for evidence of anthropogenic depression both are the Lradi tional m ans of s arching y t neither is pcuticularly sensitive to detectshying trends when percentag s or proportions ar used as measures of abundan ce Calcula ting a correlation coefficient betvveen relative abundances of taxa and ample size ([ SP) is not the best way to sta tis ti Ily search for tr nds (Canshy

non 2000 2001) This is so becau relative abundance do not r gister wh ther sa mple sizes are 5 or 5000 Statist ically the di fference b tween an absolute ta lly of 5 and an absolu te taUy of 5000 i quite d ifferent from saying each comprises per ent of Lhe total collection (100 and 100000 respectively) The effect of small

214 I R L Lyman

Figure 10-2 Relashytive abundances of North American wa-

Piti and other artioshydactyls in the modern Yellowstone ecosysshytem compared 0 the relative abundances ofwapiti remains and rel1ains of other arshytiodaclyls in archaeoshylogiwl sites in seven western states (data from Kay 1994)

100 -------------------------------~

QJ

80

~

~ 40 ~

20

bull Yellowstone

bull Intermontane West

Wapiti Other Ungulate Taxa

05 ----------------------------

o o o

o

04 0 0

o o

0~ 03 cU C cs

middotn 0 5 0

0 ~ 02 0 0 c 0

0

C DoD~

0

01 0 0

0 0

o 0 0

o ciDa o B 0 o 0 0

0 00 ~~ 0 rn lib 0 0 sect 0 8 0 g rP 00

a 2000 tOOO 6000 8000 10000 Age (radiocarbon years BP)

Figure 10-3 Proportion of wapiti remains among summed wapiti and deer remains in 86 assemblages from eastern Washington state (da ta from Lyman 2004a) The slope of the simple best-fit regres ion line is not sigl1ificantly differshyent from zero and there i no correlation between age and proportion of wapiti

06

05

04 x OJ

U

s ~ 03 11

~ 02

0

01

00 0 0 Of)

f r

s Ii v

samples on accurate ref inventory t the abW1dat bUl sample not be accUJ relatively m sampling er INISP acro sampling er

Use of ur 10-3 an hypothesis 1 no trend ) or there is no t the null hn sam ples tha correl tion ( source of thE

r

10000

ti l11ld dctl om Lyman II tty diffe1shy of wapiti

Preh istoric Anth ropogenic Impacts Are Not Ubiquitous I 215

06

0 05

04

x 000

s I 03 D 2

02

01

0 0 00

0 000

0 0 0 D C Cgt C 0 co Cgt Q Cgt Cgt 0 Cgt 0 c 0 0 co 0 0 c 0 0 Cgt 0 0 0 0 Cgt 0 8 C

Q U) Cgt 8 en 0 U) Cgt 0 co 1 1 0 cr-N~ T 7 ~I r 7 1 l l 1 ~5 0 Cgt 5 0 ltgt 0 0 0 0 c5 sect S

n 0 r ltgt f) 0 0 u 8 n co ~ N rlt) lt-- ~ U lR h tt 00

I

Age (radiocarbon years BP)

Figure 10-4 Proportion of wapiti remaiJls among summed wapiti and deer remains by SOO-year period for 86 assemblages from eas tern Washington state (data from Lyman 2004a) The slope of the simple best-fit regression line is sigllificantly different from zero and the age and proportion of wapiti variables are correlated (1 = 489 P = 064)

samples on corr la tions may simply be due to sampling error ralher than any accurate [-fle lion of abundance Rar phcnom na are particula rl y difficult to in entory they wi ll be ab ent from collections unless the sampleti arc large H th abundances of tie ral rare taxa are not quite equal in the target pop ula tion bu t samples are sm all the true rela tive abundan ces of those rare taxa likely will not be accurately refle ted by small sam ples (Grayson 1984) S )mc taxa v il be relatively more abundant some k ss abundnnt in th sample simply bec use of ampling error Thus a correIalion betvvee the relative abundance of a taxon and

[ Nl P across m ultiple assemblages may be driven by sm all sam ples because of sam pIing error

se of th regression approach to search for sa mplc-size effecls (as in Figshyures 10-3 and 10-4) may lead to commission of a Type I error (rejecting a lru null hypothesis that there is no true trend in relative abundances vhen in fact there is no trend) or com mi ssion of a Type II error (accepting a fa l e nu ll hypothesis that there is no true tren d in abundances when in fact there is a trend) In bo th cases the null hypothesis is th t no trend is presen t bulampling error has produced a mples that a r not representative of the p opu lation Traditionally a signifi cant correlation coeffici nt has been in terpreted a indicating that sample size is the sou rce of the correlation and lh absence of tiign ificant correlation coeffici nt is

2] 6 I K L Lyman

interpreted as indica ting that sampl size is not the source of the correlation As Cannon (2001 185) obser ed the firs t interpr tabon at best rests on an incomplete understanding of the relationship between relative abundances and sample size the second interpret tion pre urnes sample sizes ar sllfficientl y large to warrant confidence but in fact they may be too sma ll In lerm more pertinent to seeking evidence of nthropogenic depression tnle trends in say the relative abundance of wapiti (in Figur s 10-3 and 10-4) that is tr nds that are no t the r sult of sample size may go unddected by correlation analysis because oj onfla tion of those trends with sam pI -size effects

Cannon (2000 2001) suggests using Cochrans t st of linear trends a form of chi- quare analysis that tests for trends among mult iple rank-ordered samples (Zar 19 6562-565) As Cannon (2000332) notes Cochrans test is constructed uch that signifi cant trends will not be fou nd when samples are so small that random error cannot be mled out at a specified confjdence level as the cause of differences in relative abundance between samples Cochrans test seeks trends in relative abundall e in such a way as to mol directly take absolute sample size into account than correlation-based analyses One first calculates a standard chi-square [aostic and then detennines how much of that statistic is the resul t of a linear trend if the latter i sufficiently (s ta tistically significant) large then on condud s that there is indeed linear hend in lh data ind pendent of any effects of sample size

Let us reconsider the wapiti data in FigLlfe 10-3 The overall chi-square stashytisti is la rg and significant (X2 = 46966 P lt 0001 ) uggesting there is a sigshynifi ant association between the frequency of deer remains and the frequency of wapiti remain The chi-square statistic fo r a linear trend is also significant (X2 =

11296 P lt 0001) suggesting there i a significant tem poral trend in the re lative abundance of wapiti remains acr ss the 86 assemblages regard less of the sizes at the a semblages The simple best-fit regression line in Figure 10-3 is of no help in det rmining which d irection the trend is do wapi ti increase over time or deshycrease in abundance relative to the abund nee of deer The chi-square trend stashytistic fails to indicate the dir chon of change Figure 10-4 provides an indication that the trend is for wapiti mains t decrease in abundance

Whatever trends in tax nomi abundances there may be in Figure 10-3 and in Figure 10-4 must for the present be treated as methodological artifacts They could refl ect how remains were tallied how assembl ges were patiotemporally lumped or how they were graphically or statistically detected (see Lyman 2008 for additional d iscussion) Another example will demonstrate that uch methodshyological artifacts are not unusual Chatters (2004~73) found an inverse correlation between the number of sites in eastern Washington state in which bison [Bison bison] number more than 10 percent of the mammalian archaeofauna and date between 1800 and 2400 BP and a curve meant to estimat hwuan population size based on the frequency of radiocarbon dates (Figme 10-5) Although this may well represent a case of anthropogenic depres ion and subsequ nt release of bison populations from predation I perceive two potential methodologi al artifacts First there are only eight archaeologio l sites in the sample so the apshypearance of a correlation bet en human population size and bison avail bility

Fi

may b a fun ters could art in all sites in I during any 0

human popu The ece

of a curve be a pro y for n ters 1995) A may be are tested with a diocarbon re 2000b) Even i b n record n nor the frequ negatively) w man 2004b) 0 1

correlation AE 1 an incomplete nd sample size uge to warrant nent to seeking tive abtmdance

sult of sam ple lation of those

trends a form dered samples is constructed

e so small that as the calise of st seeks lrends )solute sample tes a standard tic is the result nt large then )endent of any

chi-squar slashythere is a sigshye frequency of gnifican t (X2 = in the reI live of the sizes of 3 is of no help er time or dcshyJan~ trend stashybull an ind ication

tgure 10-3 and artifacts They Itiotemporally e Lyman 2008

uch method shyse correla tion h bison [Bi on luna and date ttl popula tion A lthough this quent release e hodological Ie so the apshym a-ailabil ity

Prehist ric Anthropogenic Impacts Are Not Ubiquitous I 217

Number of Si tes Rrtdiocarboll Date Curve o 1 2 3 infrequent freq uent

1000

1200

1400

1600

~

~ 1800 ro ~ ~ 2000 b

lJt 2200

2400

2600

2800

3000

Figure 10-5 CUrle of archaeological radiocarbon ages as a surrogate meashysure of human pOuation size and frequency of site in which bison make up more than 10 percent of the marrzmalian archaeofnuna Redrawn from Chatshyter lt (200473 Figure 53) the radiocarbon age curve has been smoothed

may be a function of the f w sites comp rising the sample To counler th is Chat shyters could argue that th percentage of illl llngulatc remains that represent bison in all sites in eastern Vashington dating between 2001 and 2500 BP is higher than d uring any othe r 500-year period exc pI during the termin al Pleistocene when human populations were undoubtedly small (Lyman 2004b)

The second possible methodologicaJ artifact in Chatterss analysis is his use of a urve based on the frequency of rad iocarbon dates adj u ted for decay as a proxy f r reg ional [human] population size (Chc tL I S 200471 see also Chatshyters 1995) A smoothed version of the urve is shown in Figure 10-5 The curve may be a r asonable estimate of human population size but it h as not be n tes ted with any independent evidence of population size For example the ra shydiocarbon record for the area may b biased in one or more ways (Lyman 2000a 2000b) Even if th sa mple f radiocarbon dates is rcp resentati of the radiocar shybon record neither the frequenc y of radiocarbon d ates per 500-year in rement nor the f r quency of dated archaeological compon nts corTe late~ (positively or negatively) wi th the propor tion of ungulate remains that represent bison (Lyshyman 2004b) or with the N [SP of bison per 500-year increment (Figure 1O-6)lf the

214 I R L Lyman

Figure 10-2 Relashytive abundances of North American wa-

Piti and other artioshydactyls in the modern Yellowstone ecosysshytem compared 0 the relative abundances ofwapiti remains and rel1ains of other arshytiodaclyls in archaeoshylogiwl sites in seven western states (data from Kay 1994)

100 -------------------------------~

QJ

80

~

~ 40 ~

20

bull Yellowstone

bull Intermontane West

Wapiti Other Ungulate Taxa

05 ----------------------------

o o o

o

04 0 0

o o

0~ 03 cU C cs

middotn 0 5 0

0 ~ 02 0 0 c 0

0

C DoD~

0

01 0 0

0 0

o 0 0

o ciDa o B 0 o 0 0

0 00 ~~ 0 rn lib 0 0 sect 0 8 0 g rP 00

a 2000 tOOO 6000 8000 10000 Age (radiocarbon years BP)

Figure 10-3 Proportion of wapiti remains among summed wapiti and deer remains in 86 assemblages from eastern Washington state (da ta from Lyman 2004a) The slope of the simple best-fit regres ion line is not sigl1ificantly differshyent from zero and there i no correlation between age and proportion of wapiti

06

05

04 x OJ

U

s ~ 03 11

~ 02

0

01

00 0 0 Of)

f r

s Ii v

samples on accurate ref inventory t the abW1dat bUl sample not be accUJ relatively m sampling er INISP acro sampling er

Use of ur 10-3 an hypothesis 1 no trend ) or there is no t the null hn sam ples tha correl tion ( source of thE

r

10000

ti l11ld dctl om Lyman II tty diffe1shy of wapiti

Preh istoric Anth ropogenic Impacts Are Not Ubiquitous I 215

06

0 05

04

x 000

s I 03 D 2

02

01

0 0 00

0 000

0 0 0 D C Cgt C 0 co Cgt Q Cgt Cgt 0 Cgt 0 c 0 0 co 0 0 c 0 0 Cgt 0 0 0 0 Cgt 0 8 C

Q U) Cgt 8 en 0 U) Cgt 0 co 1 1 0 cr-N~ T 7 ~I r 7 1 l l 1 ~5 0 Cgt 5 0 ltgt 0 0 0 0 c5 sect S

n 0 r ltgt f) 0 0 u 8 n co ~ N rlt) lt-- ~ U lR h tt 00

I

Age (radiocarbon years BP)

Figure 10-4 Proportion of wapiti remaiJls among summed wapiti and deer remains by SOO-year period for 86 assemblages from eas tern Washington state (data from Lyman 2004a) The slope of the simple best-fit regression line is sigllificantly different from zero and the age and proportion of wapiti variables are correlated (1 = 489 P = 064)

samples on corr la tions may simply be due to sampling error ralher than any accurate [-fle lion of abundance Rar phcnom na are particula rl y difficult to in entory they wi ll be ab ent from collections unless the sampleti arc large H th abundances of tie ral rare taxa are not quite equal in the target pop ula tion bu t samples are sm all the true rela tive abundan ces of those rare taxa likely will not be accurately refle ted by small sam ples (Grayson 1984) S )mc taxa v il be relatively more abundant some k ss abundnnt in th sample simply bec use of ampling error Thus a correIalion betvvee the relative abundance of a taxon and

[ Nl P across m ultiple assemblages may be driven by sm all sam ples because of sam pIing error

se of th regression approach to search for sa mplc-size effecls (as in Figshyures 10-3 and 10-4) may lead to commission of a Type I error (rejecting a lru null hypothesis that there is no true trend in relative abundances vhen in fact there is no trend) or com mi ssion of a Type II error (accepting a fa l e nu ll hypothesis that there is no true tren d in abundances when in fact there is a trend) In bo th cases the null hypothesis is th t no trend is presen t bulampling error has produced a mples that a r not representative of the p opu lation Traditionally a signifi cant correlation coeffici nt has been in terpreted a indicating that sample size is the sou rce of the correlation and lh absence of tiign ificant correlation coeffici nt is

2] 6 I K L Lyman

interpreted as indica ting that sampl size is not the source of the correlation As Cannon (2001 185) obser ed the firs t interpr tabon at best rests on an incomplete understanding of the relationship between relative abundances and sample size the second interpret tion pre urnes sample sizes ar sllfficientl y large to warrant confidence but in fact they may be too sma ll In lerm more pertinent to seeking evidence of nthropogenic depression tnle trends in say the relative abundance of wapiti (in Figur s 10-3 and 10-4) that is tr nds that are no t the r sult of sample size may go unddected by correlation analysis because oj onfla tion of those trends with sam pI -size effects

Cannon (2000 2001) suggests using Cochrans t st of linear trends a form of chi- quare analysis that tests for trends among mult iple rank-ordered samples (Zar 19 6562-565) As Cannon (2000332) notes Cochrans test is constructed uch that signifi cant trends will not be fou nd when samples are so small that random error cannot be mled out at a specified confjdence level as the cause of differences in relative abundance between samples Cochrans test seeks trends in relative abundall e in such a way as to mol directly take absolute sample size into account than correlation-based analyses One first calculates a standard chi-square [aostic and then detennines how much of that statistic is the resul t of a linear trend if the latter i sufficiently (s ta tistically significant) large then on condud s that there is indeed linear hend in lh data ind pendent of any effects of sample size

Let us reconsider the wapiti data in FigLlfe 10-3 The overall chi-square stashytisti is la rg and significant (X2 = 46966 P lt 0001 ) uggesting there is a sigshynifi ant association between the frequency of deer remains and the frequency of wapiti remain The chi-square statistic fo r a linear trend is also significant (X2 =

11296 P lt 0001) suggesting there i a significant tem poral trend in the re lative abundance of wapiti remains acr ss the 86 assemblages regard less of the sizes at the a semblages The simple best-fit regression line in Figure 10-3 is of no help in det rmining which d irection the trend is do wapi ti increase over time or deshycrease in abundance relative to the abund nee of deer The chi-square trend stashytistic fails to indicate the dir chon of change Figure 10-4 provides an indication that the trend is for wapiti mains t decrease in abundance

Whatever trends in tax nomi abundances there may be in Figure 10-3 and in Figure 10-4 must for the present be treated as methodological artifacts They could refl ect how remains were tallied how assembl ges were patiotemporally lumped or how they were graphically or statistically detected (see Lyman 2008 for additional d iscussion) Another example will demonstrate that uch methodshyological artifacts are not unusual Chatters (2004~73) found an inverse correlation between the number of sites in eastern Washington state in which bison [Bison bison] number more than 10 percent of the mammalian archaeofauna and date between 1800 and 2400 BP and a curve meant to estimat hwuan population size based on the frequency of radiocarbon dates (Figme 10-5) Although this may well represent a case of anthropogenic depres ion and subsequ nt release of bison populations from predation I perceive two potential methodologi al artifacts First there are only eight archaeologio l sites in the sample so the apshypearance of a correlation bet en human population size and bison avail bility

Fi

may b a fun ters could art in all sites in I during any 0

human popu The ece

of a curve be a pro y for n ters 1995) A may be are tested with a diocarbon re 2000b) Even i b n record n nor the frequ negatively) w man 2004b) 0 1

correlation AE 1 an incomplete nd sample size uge to warrant nent to seeking tive abtmdance

sult of sam ple lation of those

trends a form dered samples is constructed

e so small that as the calise of st seeks lrends )solute sample tes a standard tic is the result nt large then )endent of any

chi-squar slashythere is a sigshye frequency of gnifican t (X2 = in the reI live of the sizes of 3 is of no help er time or dcshyJan~ trend stashybull an ind ication

tgure 10-3 and artifacts They Itiotemporally e Lyman 2008

uch method shyse correla tion h bison [Bi on luna and date ttl popula tion A lthough this quent release e hodological Ie so the apshym a-ailabil ity

Prehist ric Anthropogenic Impacts Are Not Ubiquitous I 217

Number of Si tes Rrtdiocarboll Date Curve o 1 2 3 infrequent freq uent

1000

1200

1400

1600

~

~ 1800 ro ~ ~ 2000 b

lJt 2200

2400

2600

2800

3000

Figure 10-5 CUrle of archaeological radiocarbon ages as a surrogate meashysure of human pOuation size and frequency of site in which bison make up more than 10 percent of the marrzmalian archaeofnuna Redrawn from Chatshyter lt (200473 Figure 53) the radiocarbon age curve has been smoothed

may be a function of the f w sites comp rising the sample To counler th is Chat shyters could argue that th percentage of illl llngulatc remains that represent bison in all sites in eastern Vashington dating between 2001 and 2500 BP is higher than d uring any othe r 500-year period exc pI during the termin al Pleistocene when human populations were undoubtedly small (Lyman 2004b)

The second possible methodologicaJ artifact in Chatterss analysis is his use of a urve based on the frequency of rad iocarbon dates adj u ted for decay as a proxy f r reg ional [human] population size (Chc tL I S 200471 see also Chatshyters 1995) A smoothed version of the urve is shown in Figure 10-5 The curve may be a r asonable estimate of human population size but it h as not be n tes ted with any independent evidence of population size For example the ra shydiocarbon record for the area may b biased in one or more ways (Lyman 2000a 2000b) Even if th sa mple f radiocarbon dates is rcp resentati of the radiocar shybon record neither the frequenc y of radiocarbon d ates per 500-year in rement nor the f r quency of dated archaeological compon nts corTe late~ (positively or negatively) wi th the propor tion of ungulate remains that represent bison (Lyshyman 2004b) or with the N [SP of bison per 500-year increment (Figure 1O-6)lf the

r

10000

ti l11ld dctl om Lyman II tty diffe1shy of wapiti

Preh istoric Anth ropogenic Impacts Are Not Ubiquitous I 215

06

0 05

04

x 000

s I 03 D 2

02

01

0 0 00

0 000

0 0 0 D C Cgt C 0 co Cgt Q Cgt Cgt 0 Cgt 0 c 0 0 co 0 0 c 0 0 Cgt 0 0 0 0 Cgt 0 8 C

Q U) Cgt 8 en 0 U) Cgt 0 co 1 1 0 cr-N~ T 7 ~I r 7 1 l l 1 ~5 0 Cgt 5 0 ltgt 0 0 0 0 c5 sect S

n 0 r ltgt f) 0 0 u 8 n co ~ N rlt) lt-- ~ U lR h tt 00

I

Age (radiocarbon years BP)

Figure 10-4 Proportion of wapiti remaiJls among summed wapiti and deer remains by SOO-year period for 86 assemblages from eas tern Washington state (data from Lyman 2004a) The slope of the simple best-fit regression line is sigllificantly different from zero and the age and proportion of wapiti variables are correlated (1 = 489 P = 064)

samples on corr la tions may simply be due to sampling error ralher than any accurate [-fle lion of abundance Rar phcnom na are particula rl y difficult to in entory they wi ll be ab ent from collections unless the sampleti arc large H th abundances of tie ral rare taxa are not quite equal in the target pop ula tion bu t samples are sm all the true rela tive abundan ces of those rare taxa likely will not be accurately refle ted by small sam ples (Grayson 1984) S )mc taxa v il be relatively more abundant some k ss abundnnt in th sample simply bec use of ampling error Thus a correIalion betvvee the relative abundance of a taxon and

[ Nl P across m ultiple assemblages may be driven by sm all sam ples because of sam pIing error

se of th regression approach to search for sa mplc-size effecls (as in Figshyures 10-3 and 10-4) may lead to commission of a Type I error (rejecting a lru null hypothesis that there is no true trend in relative abundances vhen in fact there is no trend) or com mi ssion of a Type II error (accepting a fa l e nu ll hypothesis that there is no true tren d in abundances when in fact there is a trend) In bo th cases the null hypothesis is th t no trend is presen t bulampling error has produced a mples that a r not representative of the p opu lation Traditionally a signifi cant correlation coeffici nt has been in terpreted a indicating that sample size is the sou rce of the correlation and lh absence of tiign ificant correlation coeffici nt is

2] 6 I K L Lyman

interpreted as indica ting that sampl size is not the source of the correlation As Cannon (2001 185) obser ed the firs t interpr tabon at best rests on an incomplete understanding of the relationship between relative abundances and sample size the second interpret tion pre urnes sample sizes ar sllfficientl y large to warrant confidence but in fact they may be too sma ll In lerm more pertinent to seeking evidence of nthropogenic depression tnle trends in say the relative abundance of wapiti (in Figur s 10-3 and 10-4) that is tr nds that are no t the r sult of sample size may go unddected by correlation analysis because oj onfla tion of those trends with sam pI -size effects

Cannon (2000 2001) suggests using Cochrans t st of linear trends a form of chi- quare analysis that tests for trends among mult iple rank-ordered samples (Zar 19 6562-565) As Cannon (2000332) notes Cochrans test is constructed uch that signifi cant trends will not be fou nd when samples are so small that random error cannot be mled out at a specified confjdence level as the cause of differences in relative abundance between samples Cochrans test seeks trends in relative abundall e in such a way as to mol directly take absolute sample size into account than correlation-based analyses One first calculates a standard chi-square [aostic and then detennines how much of that statistic is the resul t of a linear trend if the latter i sufficiently (s ta tistically significant) large then on condud s that there is indeed linear hend in lh data ind pendent of any effects of sample size

Let us reconsider the wapiti data in FigLlfe 10-3 The overall chi-square stashytisti is la rg and significant (X2 = 46966 P lt 0001 ) uggesting there is a sigshynifi ant association between the frequency of deer remains and the frequency of wapiti remain The chi-square statistic fo r a linear trend is also significant (X2 =

11296 P lt 0001) suggesting there i a significant tem poral trend in the re lative abundance of wapiti remains acr ss the 86 assemblages regard less of the sizes at the a semblages The simple best-fit regression line in Figure 10-3 is of no help in det rmining which d irection the trend is do wapi ti increase over time or deshycrease in abundance relative to the abund nee of deer The chi-square trend stashytistic fails to indicate the dir chon of change Figure 10-4 provides an indication that the trend is for wapiti mains t decrease in abundance

Whatever trends in tax nomi abundances there may be in Figure 10-3 and in Figure 10-4 must for the present be treated as methodological artifacts They could refl ect how remains were tallied how assembl ges were patiotemporally lumped or how they were graphically or statistically detected (see Lyman 2008 for additional d iscussion) Another example will demonstrate that uch methodshyological artifacts are not unusual Chatters (2004~73) found an inverse correlation between the number of sites in eastern Washington state in which bison [Bison bison] number more than 10 percent of the mammalian archaeofauna and date between 1800 and 2400 BP and a curve meant to estimat hwuan population size based on the frequency of radiocarbon dates (Figme 10-5) Although this may well represent a case of anthropogenic depres ion and subsequ nt release of bison populations from predation I perceive two potential methodologi al artifacts First there are only eight archaeologio l sites in the sample so the apshypearance of a correlation bet en human population size and bison avail bility

Fi

may b a fun ters could art in all sites in I during any 0

human popu The ece

of a curve be a pro y for n ters 1995) A may be are tested with a diocarbon re 2000b) Even i b n record n nor the frequ negatively) w man 2004b) 0 1

correlation AE 1 an incomplete nd sample size uge to warrant nent to seeking tive abtmdance

sult of sam ple lation of those

trends a form dered samples is constructed

e so small that as the calise of st seeks lrends )solute sample tes a standard tic is the result nt large then )endent of any

chi-squar slashythere is a sigshye frequency of gnifican t (X2 = in the reI live of the sizes of 3 is of no help er time or dcshyJan~ trend stashybull an ind ication

tgure 10-3 and artifacts They Itiotemporally e Lyman 2008

uch method shyse correla tion h bison [Bi on luna and date ttl popula tion A lthough this quent release e hodological Ie so the apshym a-ailabil ity

Prehist ric Anthropogenic Impacts Are Not Ubiquitous I 217

Number of Si tes Rrtdiocarboll Date Curve o 1 2 3 infrequent freq uent

1000

1200

1400

1600

~

~ 1800 ro ~ ~ 2000 b

lJt 2200

2400

2600

2800

3000

Figure 10-5 CUrle of archaeological radiocarbon ages as a surrogate meashysure of human pOuation size and frequency of site in which bison make up more than 10 percent of the marrzmalian archaeofnuna Redrawn from Chatshyter lt (200473 Figure 53) the radiocarbon age curve has been smoothed

may be a function of the f w sites comp rising the sample To counler th is Chat shyters could argue that th percentage of illl llngulatc remains that represent bison in all sites in eastern Vashington dating between 2001 and 2500 BP is higher than d uring any othe r 500-year period exc pI during the termin al Pleistocene when human populations were undoubtedly small (Lyman 2004b)

The second possible methodologicaJ artifact in Chatterss analysis is his use of a urve based on the frequency of rad iocarbon dates adj u ted for decay as a proxy f r reg ional [human] population size (Chc tL I S 200471 see also Chatshyters 1995) A smoothed version of the urve is shown in Figure 10-5 The curve may be a r asonable estimate of human population size but it h as not be n tes ted with any independent evidence of population size For example the ra shydiocarbon record for the area may b biased in one or more ways (Lyman 2000a 2000b) Even if th sa mple f radiocarbon dates is rcp resentati of the radiocar shybon record neither the frequenc y of radiocarbon d ates per 500-year in rement nor the f r quency of dated archaeological compon nts corTe late~ (positively or negatively) wi th the propor tion of ungulate remains that represent bison (Lyshyman 2004b) or with the N [SP of bison per 500-year increment (Figure 1O-6)lf the

2] 6 I K L Lyman

interpreted as indica ting that sampl size is not the source of the correlation As Cannon (2001 185) obser ed the firs t interpr tabon at best rests on an incomplete understanding of the relationship between relative abundances and sample size the second interpret tion pre urnes sample sizes ar sllfficientl y large to warrant confidence but in fact they may be too sma ll In lerm more pertinent to seeking evidence of nthropogenic depression tnle trends in say the relative abundance of wapiti (in Figur s 10-3 and 10-4) that is tr nds that are no t the r sult of sample size may go unddected by correlation analysis because oj onfla tion of those trends with sam pI -size effects

Cannon (2000 2001) suggests using Cochrans t st of linear trends a form of chi- quare analysis that tests for trends among mult iple rank-ordered samples (Zar 19 6562-565) As Cannon (2000332) notes Cochrans test is constructed uch that signifi cant trends will not be fou nd when samples are so small that random error cannot be mled out at a specified confjdence level as the cause of differences in relative abundance between samples Cochrans test seeks trends in relative abundall e in such a way as to mol directly take absolute sample size into account than correlation-based analyses One first calculates a standard chi-square [aostic and then detennines how much of that statistic is the resul t of a linear trend if the latter i sufficiently (s ta tistically significant) large then on condud s that there is indeed linear hend in lh data ind pendent of any effects of sample size

Let us reconsider the wapiti data in FigLlfe 10-3 The overall chi-square stashytisti is la rg and significant (X2 = 46966 P lt 0001 ) uggesting there is a sigshynifi ant association between the frequency of deer remains and the frequency of wapiti remain The chi-square statistic fo r a linear trend is also significant (X2 =

11296 P lt 0001) suggesting there i a significant tem poral trend in the re lative abundance of wapiti remains acr ss the 86 assemblages regard less of the sizes at the a semblages The simple best-fit regression line in Figure 10-3 is of no help in det rmining which d irection the trend is do wapi ti increase over time or deshycrease in abundance relative to the abund nee of deer The chi-square trend stashytistic fails to indicate the dir chon of change Figure 10-4 provides an indication that the trend is for wapiti mains t decrease in abundance

Whatever trends in tax nomi abundances there may be in Figure 10-3 and in Figure 10-4 must for the present be treated as methodological artifacts They could refl ect how remains were tallied how assembl ges were patiotemporally lumped or how they were graphically or statistically detected (see Lyman 2008 for additional d iscussion) Another example will demonstrate that uch methodshyological artifacts are not unusual Chatters (2004~73) found an inverse correlation between the number of sites in eastern Washington state in which bison [Bison bison] number more than 10 percent of the mammalian archaeofauna and date between 1800 and 2400 BP and a curve meant to estimat hwuan population size based on the frequency of radiocarbon dates (Figme 10-5) Although this may well represent a case of anthropogenic depres ion and subsequ nt release of bison populations from predation I perceive two potential methodologi al artifacts First there are only eight archaeologio l sites in the sample so the apshypearance of a correlation bet en human population size and bison avail bility

Fi

may b a fun ters could art in all sites in I during any 0

human popu The ece

of a curve be a pro y for n ters 1995) A may be are tested with a diocarbon re 2000b) Even i b n record n nor the frequ negatively) w man 2004b) 0 1

correlation AE 1 an incomplete nd sample size uge to warrant nent to seeking tive abtmdance

sult of sam ple lation of those

trends a form dered samples is constructed

e so small that as the calise of st seeks lrends )solute sample tes a standard tic is the result nt large then )endent of any

chi-squar slashythere is a sigshye frequency of gnifican t (X2 = in the reI live of the sizes of 3 is of no help er time or dcshyJan~ trend stashybull an ind ication

tgure 10-3 and artifacts They Itiotemporally e Lyman 2008

uch method shyse correla tion h bison [Bi on luna and date ttl popula tion A lthough this quent release e hodological Ie so the apshym a-ailabil ity

Prehist ric Anthropogenic Impacts Are Not Ubiquitous I 217

Number of Si tes Rrtdiocarboll Date Curve o 1 2 3 infrequent freq uent

1000

1200

1400

1600

~

~ 1800 ro ~ ~ 2000 b

lJt 2200

2400

2600

2800

3000

Figure 10-5 CUrle of archaeological radiocarbon ages as a surrogate meashysure of human pOuation size and frequency of site in which bison make up more than 10 percent of the marrzmalian archaeofnuna Redrawn from Chatshyter lt (200473 Figure 53) the radiocarbon age curve has been smoothed

may be a function of the f w sites comp rising the sample To counler th is Chat shyters could argue that th percentage of illl llngulatc remains that represent bison in all sites in eastern Vashington dating between 2001 and 2500 BP is higher than d uring any othe r 500-year period exc pI during the termin al Pleistocene when human populations were undoubtedly small (Lyman 2004b)

The second possible methodologicaJ artifact in Chatterss analysis is his use of a urve based on the frequency of rad iocarbon dates adj u ted for decay as a proxy f r reg ional [human] population size (Chc tL I S 200471 see also Chatshyters 1995) A smoothed version of the urve is shown in Figure 10-5 The curve may be a r asonable estimate of human population size but it h as not be n tes ted with any independent evidence of population size For example the ra shydiocarbon record for the area may b biased in one or more ways (Lyman 2000a 2000b) Even if th sa mple f radiocarbon dates is rcp resentati of the radiocar shybon record neither the frequenc y of radiocarbon d ates per 500-year in rement nor the f r quency of dated archaeological compon nts corTe late~ (positively or negatively) wi th the propor tion of ungulate remains that represent bison (Lyshyman 2004b) or with the N [SP of bison per 500-year increment (Figure 1O-6)lf the

correlation AE 1 an incomplete nd sample size uge to warrant nent to seeking tive abtmdance

sult of sam ple lation of those

trends a form dered samples is constructed

e so small that as the calise of st seeks lrends )solute sample tes a standard tic is the result nt large then )endent of any

chi-squar slashythere is a sigshye frequency of gnifican t (X2 = in the reI live of the sizes of 3 is of no help er time or dcshyJan~ trend stashybull an ind ication

tgure 10-3 and artifacts They Itiotemporally e Lyman 2008

uch method shyse correla tion h bison [Bi on luna and date ttl popula tion A lthough this quent release e hodological Ie so the apshym a-ailabil ity

Prehist ric Anthropogenic Impacts Are Not Ubiquitous I 217

Number of Si tes Rrtdiocarboll Date Curve o 1 2 3 infrequent freq uent

1000

1200

1400

1600

~

~ 1800 ro ~ ~ 2000 b

lJt 2200

2400

2600

2800

3000

Figure 10-5 CUrle of archaeological radiocarbon ages as a surrogate meashysure of human pOuation size and frequency of site in which bison make up more than 10 percent of the marrzmalian archaeofnuna Redrawn from Chatshyter lt (200473 Figure 53) the radiocarbon age curve has been smoothed

may be a function of the f w sites comp rising the sample To counler th is Chat shyters could argue that th percentage of illl llngulatc remains that represent bison in all sites in eastern Vashington dating between 2001 and 2500 BP is higher than d uring any othe r 500-year period exc pI during the termin al Pleistocene when human populations were undoubtedly small (Lyman 2004b)

The second possible methodologicaJ artifact in Chatterss analysis is his use of a urve based on the frequency of rad iocarbon dates adj u ted for decay as a proxy f r reg ional [human] population size (Chc tL I S 200471 see also Chatshyters 1995) A smoothed version of the urve is shown in Figure 10-5 The curve may be a r asonable estimate of human population size but it h as not be n tes ted with any independent evidence of population size For example the ra shydiocarbon record for the area may b biased in one or more ways (Lyman 2000a 2000b) Even if th sa mple f radiocarbon dates is rcp resentati of the radiocar shybon record neither the frequenc y of radiocarbon d ates per 500-year in rement nor the f r quency of dated archaeological compon nts corTe late~ (positively or negatively) wi th the propor tion of ungulate remains that represent bison (Lyshyman 2004b) or with the N [SP of bison per 500-year increment (Figure 1O-6)lf the

x

L

o frcguency of da tes bull frequency of dated 116

x NISP of bi on

21( I R L Lyman

Normed hequen ies 00 02 0 4 06 08 10

0-500

501-1 000

1000-J 500

1501-2000

2001-2500

2501-3000

~ 3001-3500

~ 3501-4000

~ 4001-4500

~ 4501-5000 c 0 5001-5500

D til 5501-6000 u 9 6001-65000 til 6501-7000 ~ 7001-7500

~ 7501-8000

8001-8 00

8501 -9000

9001-9500

9501-10000

10001-10500 ~--------------~----------------~

Figure 10-6 Frequency of radiocarbon age~ radiocarbon-dated sites and ESP of bison per 500-year increment in eastern Washington state Data

from Lyman (2000b 2004b)

frequency of radiocarbon dates is in fact d irectly correlated w ith human populashyI ion size the lack of correlation over the entire Holoc ne suggests Ihat there is no regular relationship between the size of the hu man popUlat ion and the local availabi lity of bison

As indicated in f igure 10-6 ther doe eem to be a strong inverse rela shytionsh ip between bison [SP and frequen ies of dated sites and bison NISP and frequencies of radi carbon date between 3000 and r oo BP more or les w hen Chatters sugg sts th two are inversely rela ted The remOlinder of th graph however seems to im ply that th is inverse rela tions] ip may be more apparent than real In other tim spans bison rsp and f-r quenci s f de ted sites and of rad io arbon dates both decrease (after 1000 BP) r bo th inocase ( l500 to LOOO BP 6000 to 5000 DP 9500 to 8500 B P) If the inverse relationship of the two v rishyabIes hown in Figure 10-5 is re I it is irtually unique among lhe available data I worry therefore Lhat the re lationship is a simple function of which portion of the en ti re time span shown in Figure 10-6 appears in Figure 10-5

Jam not conclusions ~ te rn-tine whell is the problerr )ted a metho tive in ter st j

prehist ric an

Oi

Th zooa rchaeolo interactions fa u as were r self might po are organi m 1

landsc)pe ha aging theoryshyof those influ people ami a fe w years un h ardly straigl monplace but

The poir been disClLSS

chc nge (Parrr hand def cli methodologic the variables ers I suggest tion methods termines lhe nvironm nt Kid well 2001 Lhe requisite

Attribut detected tren predation Tc evidence mu ence is sllspe influences ot evidence Thl e Limin ale ilia and so on I h ones tha t COt

10

-oX

es

ted site and n state Data

nan p opulashythat there is nd the Ie cal

nvCrs relashyn NIS P and r less when the grapt

~e apparent lites and of 500 to 1000 Ie two v~ishyiIable data portion of

Prehistoric Anthrop genic Impacts Are Not Ubiquitolls I 219

I am not arguing here thil t Chatters (or anyone eLc ) has presented incorrect conclusions wha t I am arguing is that we simply cannot at the present lime dshytermin wheth r he (o r anyone else) is corr ct or n t Th ource of this d iffi culty is the problem of not knowing wh n we have analytically produced a trend (creshyated a methodologica l artifact) rather than simply detected a trend f interpreshytive interest And this is the heart of the point I wish to make about identifying preh istoric an thropogerucally influ enced fawlas

Discussion and Conclusion

There is no doubt that models based ( n foraging theory and used by zooarchaeologlsts have prov ided a wealth of unique ins ight to pr dato r- p rey int ractions One of those insights has been lhat an thropogenically influ nced faunas were rath r commonplace on prehistoric landscapes A cynic such as myshyself might p oint o ut that we should have suspected as much g iven that humans arc organisms that util ize plants rind animals and thus wi ll when present on the landscape ha ve cologi al int111en es on other organi sms (eg tahl 2008) Forshyaging theory-based models have indicated some of the empi ri cal manifes tations of those infl uences But in reases in our knowlc ge abou t foraging practices of people and about aspects of the zooarchaeological record both have in the past few years under cored that detecti ng lIch things as human-depressed faunas is hard ly straightforward etection has jf anything b come not only more comshymonplace but also mu ch more challenging ana lytically to validate

The point 1 wish to make here can b reduced to two va riables tha t hJve been difi Cllsscd jn t11 literature on modern anth ropogenic Ily induced dim te change (Pcumiddotll1esan 2006) Those variables are detection and attribution C n the one hand detection oncerns d iscerning evid n e o( a true hmiddotend (one th at is not a methudological arti fact) in the va riables of in terest ill the cases I have discuss li the v riables are relative abum lanc 5 of animal taxa exploited by human foragshye rs 1sugges t we need more actua li stic fi de lity stu dies to det rmin which de t cshytion methods arl most valid in par ticular s ttings A fid Iity tudy is one that d J _

termines the degret to which a collection of faunal remains accurately refl cts the environment fro m which the collecti n derives (eg Behrensm yer et al 2000 Kid well 200 1) Ethnoarchaeologis ts and neotaphonomists could easily provide the requisite informa tion here (eg Lyman and Lyman 20m)

Attribution on the oth r hand concerns as igning the orred cause to the detected trend in the cases I have discussed the cause should be anthropogenic predation To build robust arguments of attribution I suggest multiple li nes of evidence must be brought to bear in any case in w hicJl an lt nthropog ni influ shyence is uspectcd Because it ma y create a tautology to argue for anth ropogen ic influ ences other caus s of fauna l change should b eliminated wi th independent e idence Thus floral or geological evidence for a lack of eh nge in climate could

liminate tha t cause ana lysis of tech nology could elimina t( thal potential cause and so on 1 have presented examples of what se m to be d tection of false trends ones that could be methodological artifacts I hav also noted that (~ vcn when

220 I R L Lyman

trends in faunal abw d ances seem to reOect what is happ ning on the I ndscape it is another matter to build a strong ase that th tr nd is related to human pre shydation- that is to bu ild a strongly warrll1ted attribu li on

Finally the cases r have reviewed tend to confirm my suspicion that wl1(11 a trend in taxonomi abundances is found that is the opposite of lhilt predicted by mod [s delied from foraging theory- wh n abundances of high-value prey increase 0 er time-analysis in rease in omplexity until ~h fauna l record can be aligned with a revised model This in its lf is not bad T worry however that it migh t indicale that we are bit too complacent when shifts in taxonomic abunshydances malch lhe modeled signature of decreased bundances of high- Cllue prey We do not rigorously explore other possibl causes f r the hanges in taxonomic abundances The ubiquity of anthropogeni ally influcnced faunas in the zooarshychaeological record may thus be marc apparent than r~ cd We need to intensify scrutiny of that record for such e iden e but we also ne d [0 rigorously evalu shyMe any indication o f ClnLfuopogcnically influenced faunas s those faunas ome to play a more prominent role in modern COllSl[valion biology laquo(g Lyman 2006 Stahl 2008) we will wan l to make SLIfe lhat our idel tifka tions of them arc valid else we risk making management de i ions on th basis of inac mat inferences

Acknowledgments

My sincere thanks to two anonymous revi wcrs who in a conlext having nothing to do with this chapter insisled tha l l [earn about Cochran s test fOf linear trends

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Chatters Jam 1995 Pc

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l latea u lI1 unitie and Iar

Earle Ti moth 1980 M(

York Grayson Don

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demieI 2001 Th

ofWora Grayson Don

1999 H tl

the landscape 0 human pre-

ion tha t when that predicted gh- alue prey 1a1 r cord can however tha t onomic abUllshygh-value prey in taxonon ic in the zooarshy

-d to intensify rously evalushy~ faunas come Lyman 2006 1em are valid ~ inferences

in a con texl och ran s tes t

y AlIlh ropollJSf

tion rite Ki va

Venlana Cnve ona St) tc Untshy

peclive edited J Socie ty 13wshy

sea rch 14143shy

Ity SheJ rw nlcr

Prehistoric Anthropogenic Impacts Are Not Ubiquitous I 221

Decline at the Mina rd Site Washington State U A Journal of Archaeological Science 341087- 1097

Brough ton Jack M 19940 Decl ines in Mam ma lian Foraging Efficiency D uring the Late H olocene San

Franci (o Bay Cali forni Joumal of Anthropological Archaeology 13 71-40l 1994b La te Holocene ResOllrce Intensification in the Sa ramento Valley ali fornia

The Vertebrate middot vidence Journal of Archaeological Science 21 501 -514 Brough ton Jack M a nd Frank E Bayham

2003 Showing Off Foraging Models and the Ascendance of Large-Game lIunting in the Ca lifornia Middle Archaic American Antiquity 68783-789

Broughton Jack M and James F O Conn II 199 On Evolutiona ry Ecology Selectionist Archaeology and Behavio ra l Archaeolshy

ogy American AntiquitH 64153-165 Butler Virginia L and Sara h K Campbell

2004 Resource Intens iHca tion and Resou rce Depression in the Pacific orlhwest of or th America A Znoa rchaeological Review Journal of World Prehistory 1R327shy405

Byer David A an d Jack M Broughton 2004 1ioloc~ne Envir nmental Change Artiodactyl Abundances and Hum an H unlshy

ing Strategies in the Greal Basin American Antiquity 69 235- 2)5 By rs DClvid A Craig S Smith and Jack M Broughton

2005 Holocene Ar tioclacty l Population Histories and Large Came Hunting in the Wyomi ng Basin USA Jou 11Iai of Archaeological Science 321 21-142

C nnOI1 Mich ael D 2000 Large Mnnmal Relative bundance in Pithousc and Pli ebio P riod Archaeoshy

faw1as from ou thweslern New Mexico Rc ouree Depression Among the Mi mbresshyMogollon Joumal oj Anthropological ArciUlcology 1931 7-347

2001 Archaeofau nal Relative Abu ndc nce Sample Size and Statis tical M th ods Jourllil l of Arclll1cological Science 28185--1 95

2003 A Model of en trcll Place Forager Prey Choice and an Ap plication to Fa unal Rema ins from the Mim bres Valley New Mexico Journal of Anthropological Archaeolshyogy 221 - 25

Chatters James c 1995 Popula tion Growth Clima tic ooling a nd the Development of ollector Stratshy

eg iee on the Sou thern Pla leau Western No rth Am rica Journal of World Preliiston 9341-400

2004 Th Influence 01 I-he Bow and Arrow on Village Formation on the Colu mb ia Plateau In Complex Iilliller-Gatherers [ voill tion IIlld Or~all ization of Prehistoric - VIIshy

mUil itics on till Plateau of NortlLUcstlYll North America ed it d by William C Prenti ss Clnd Ia n Kuijt pp 67- 83 Unive rsity of Utah Press Salt Lake City

Earle Timot hy K and Andrew L Christenson (editors) 1980 Modeling Change in PrPililtforic Suls isJence poundco nomi( lt A ademic Pres ew

York Grlt1 yson Dona ld K

1984 Quantitative Zooarrhar gy Topics in the Analysis of Arci1lleolos ical Faunas Aca shyemic Pr ss Orlan do 1loridlt1

200 I The lt rchaeoJog i 11 Reco rd of rIuman Impacts on Animal Populations Jou rnal of World Preilistory 1 ~1-68

ril yson Donald K and Michael D Ca nnon 1999 H uman Paleoecology and Foraging Theory in the reat Bas in In Models or

222 I R L Lyman

the Millennium [he Current Slllu~ of Great Bnsin Anthropological Research edited by Charlotte Beck pp 111-15 1 ni ersily of Utah Press Sd it Lake C ity

Grayson Donald K a nd Franlto isc Delpech 1998 Changing Diet Bread th in the Early pper Palaeol il hie of Southwestern FrJ nce

Jo urnal of Archaeological Science 25 111 9- 11 29 Hickerson Ila roid

1965 The Virgi ni a Deer al d Intertriba l Buffer Zones in the ppe Missi sippi Valley In Man Culturc and A Ii lnals The Role of Animals in HlInan Ecological Adjusfmcllts edi t db Anthony Leeds and Andr w P Vayda pp 43-tlS Publicati on 78 Amerishycan Association for the Advancemen t of Science Washington DC

H il ciebra nd l William R and Terry L JOnES 2002 Oepl lion of Prehis toric Pinniped Popu lations Along the alifomia a nd Orshy

egon Coasts Were Humans the Cause In Wilderness and Political Ecology J1lo riginnl Influences and the Original ~Iatc of Na ture editeJ by C ha rl s E Kay nd Randy T Simmons p p 72- 110 niverity of Utah Press Sa lt Lake middotity

H ildebrandt William R and Kell y R McGuire 2002 he As e ndance of Hu nting During the C lifornia M iddle Archaic An Evolushy

tionary Perspective American Alltiq uity 6721J - 256 2003 Large-Game Hunti ng Cender-l ifferen tia ted W rk Organization and lhl

Role of Evolutiona ry Ecology in ali forni a nd relt Basin Preh islo ry A Reply to Broughton and Bayham American Antiquity 68790-792

Hockett Bryan 2005 Midd le and LaleHolocene I lunting in the Greal Bas in A Critical Rev iew of the

Deba te and Fulu re Prospects American Antiquity 70713-731 H unn Eugene S

1982 Mobility as a Factor Limiting Resource Use in the Columbia Plateau of North A me rica In Resource Ma nagers North American and Australian Hun ter-Gatherers edshyted by Nancy M Wil lia ms and Eugene S I lunn pp 17 3 AAAS SeJ cled Symposhysi um No 67 Westview Press Boulder Colorado

Jan lsk i Joel 1997 Fremont Hunting and Resource Intensificat ioll in the Eltlstc rn Gr a t Basin Jourshy

nal ofArchaeological Science 241075- 1088 Jones Te rry L and Willia m R H ildebrandt

1995 Reasserti ng a Prehi toric Tragedy of the Com mons Reply to Lym an Journal of Anthropological Archaeology 147R-98

Kay Charles E 1994 Aboriginal Overkill Th Role o f Native Am eri cans in Structuring Weste rn

Ecosystems Human Nature 5359-398 Kidwdl Susan M

2001 Preservation of SpeCies Abundance in the Fossil Record Science 294 l091shy1094

Krtbs John R and Nicholas B Davie 1978 Behavioll ral Ecology J1 n Evolutionary Approach Blackwell Sde nce Oxford UX

LaJiberte Andrea and Will iam J Ripple 2003 Wil dl ife EnCow1ters by Lewis and lark A Spatia l Analys is of Interactions Beshy

tw een alive Americans and Wild life BioSciel1Ce 53994- lO03 Linilrcs Olga F

1976 Garden Hunting in the American Tropics Human Ecology 433 1-349 Lu pa Karen D and Dave N Schm itt

2005 ma ll Prey Hunting Teclu1010gy and Zo a rchaeological M asu res of Taxonomshy

ic DivE Forest

Lyman R Le 1995 01

AI eric 2000a Bl

chrono 2000b R

west AI 2003a Pi

and No --Jorth

200J b T~ Foragil

20011lt1 Al logica l

2004b L Easten

2006 Pc 1511 - 1

2008 Q Lyman R Le

2003 L( tions 0

archaeo l yman R Lc

2002 Tl States

McGuire Kel 200~ Rt

Durint Martin Paul

1999a M Sink I Hart F

1999b Vv 1336-lt

2002 G to Cc

MlU1fO Nata 2005 Z

sity in 45(Sul

Nagaoka Lis 200 D

Zealar Pa rmesan C

2006 pound view oj

10

-oX

es

ted site and n state Data

nan p opulashythat there is nd the Ie cal

nvCrs relashyn NIS P and r less when the grapt

~e apparent lites and of 500 to 1000 Ie two v~ishyiIable data portion of

Prehistoric Anthrop genic Impacts Are Not Ubiquitolls I 219

I am not arguing here thil t Chatters (or anyone eLc ) has presented incorrect conclusions wha t I am arguing is that we simply cannot at the present lime dshytermin wheth r he (o r anyone else) is corr ct or n t Th ource of this d iffi culty is the problem of not knowing wh n we have analytically produced a trend (creshyated a methodologica l artifact) rather than simply detected a trend f interpreshytive interest And this is the heart of the point I wish to make about identifying preh istoric an thropogerucally influ enced fawlas

Discussion and Conclusion

There is no doubt that models based ( n foraging theory and used by zooarchaeologlsts have prov ided a wealth of unique ins ight to pr dato r- p rey int ractions One of those insights has been lhat an thropogenically influ nced faunas were rath r commonplace on prehistoric landscapes A cynic such as myshyself might p oint o ut that we should have suspected as much g iven that humans arc organisms that util ize plants rind animals and thus wi ll when present on the landscape ha ve cologi al int111en es on other organi sms (eg tahl 2008) Forshyaging theory-based models have indicated some of the empi ri cal manifes tations of those infl uences But in reases in our knowlc ge abou t foraging practices of people and about aspects of the zooarchaeological record both have in the past few years under cored that detecti ng lIch things as human-depressed faunas is hard ly straightforward etection has jf anything b come not only more comshymonplace but also mu ch more challenging ana lytically to validate

The point 1 wish to make here can b reduced to two va riables tha t hJve been difi Cllsscd jn t11 literature on modern anth ropogenic Ily induced dim te change (Pcumiddotll1esan 2006) Those variables are detection and attribution C n the one hand detection oncerns d iscerning evid n e o( a true hmiddotend (one th at is not a methudological arti fact) in the va riables of in terest ill the cases I have discuss li the v riables are relative abum lanc 5 of animal taxa exploited by human foragshye rs 1sugges t we need more actua li stic fi de lity stu dies to det rmin which de t cshytion methods arl most valid in par ticular s ttings A fid Iity tudy is one that d J _

termines the degret to which a collection of faunal remains accurately refl cts the environment fro m which the collecti n derives (eg Behrensm yer et al 2000 Kid well 200 1) Ethnoarchaeologis ts and neotaphonomists could easily provide the requisite informa tion here (eg Lyman and Lyman 20m)

Attribution on the oth r hand concerns as igning the orred cause to the detected trend in the cases I have discussed the cause should be anthropogenic predation To build robust arguments of attribution I suggest multiple li nes of evidence must be brought to bear in any case in w hicJl an lt nthropog ni influ shyence is uspectcd Because it ma y create a tautology to argue for anth ropogen ic influ ences other caus s of fauna l change should b eliminated wi th independent e idence Thus floral or geological evidence for a lack of eh nge in climate could

liminate tha t cause ana lysis of tech nology could elimina t( thal potential cause and so on 1 have presented examples of what se m to be d tection of false trends ones that could be methodological artifacts I hav also noted that (~ vcn when

220 I R L Lyman

trends in faunal abw d ances seem to reOect what is happ ning on the I ndscape it is another matter to build a strong ase that th tr nd is related to human pre shydation- that is to bu ild a strongly warrll1ted attribu li on

Finally the cases r have reviewed tend to confirm my suspicion that wl1(11 a trend in taxonomi abundances is found that is the opposite of lhilt predicted by mod [s delied from foraging theory- wh n abundances of high-value prey increase 0 er time-analysis in rease in omplexity until ~h fauna l record can be aligned with a revised model This in its lf is not bad T worry however that it migh t indicale that we are bit too complacent when shifts in taxonomic abunshydances malch lhe modeled signature of decreased bundances of high- Cllue prey We do not rigorously explore other possibl causes f r the hanges in taxonomic abundances The ubiquity of anthropogeni ally influcnced faunas in the zooarshychaeological record may thus be marc apparent than r~ cd We need to intensify scrutiny of that record for such e iden e but we also ne d [0 rigorously evalu shyMe any indication o f ClnLfuopogcnically influenced faunas s those faunas ome to play a more prominent role in modern COllSl[valion biology laquo(g Lyman 2006 Stahl 2008) we will wan l to make SLIfe lhat our idel tifka tions of them arc valid else we risk making management de i ions on th basis of inac mat inferences

Acknowledgments

My sincere thanks to two anonymous revi wcrs who in a conlext having nothing to do with this chapter insisled tha l l [earn about Cochran s test fOf linear trends

References

Alvard Michael S 1998 Evolutionary Ecology and Resource Conservation Evolutlonanf Anthropology

762-74 Bayham Frank E

1979 Factors In flu ncing the ArchJic Palt rn of Animal Exploitation The Kiva 44219- 235

1982 A Diachronic Analy is of Prehistoric Animal Exploitation at Ventana Cave Unpublished PhD disserlation Depa rlm ent of Anthropology Arizona Sta te Unishyver ity Tempe

Behrensmeyer Anna K Susan M Kid we ll and lobert A Castaldo 2000 Taphonomy and PaJ obiology In Deep Time Paleobiologys Perspective ed ited

by Douglas It Erw in and Scott L Wing pp 103~147 PaJconlo logicltJ l ociety Lawshyrence Kansa5

Bird Douglas W and James F QCcmne ll 2006 Behavioral Ecology and Archaeology Journal of Arclmcological Research 14 143shy

188 Bovy Kristine M

2007 labal Human Impacts or Cli mat Change Explaining the Sooty Shea rwater

Dedil 341 01

Broughton J 1994a r

Franc 1994b l

The V Broughton J

2003 S in the

Brough ton J 1999 C

ogy A Butler Virgil

2004 R of NO 405

Byprs David 2004 II

iog I I

Byers David 2005 H

Wyom Cannon Mic

2000 L faw1as Mogol

2001 A Journal

2003 A Rerna il ogy 22

Chatters Jam 1995 Pc

egies 0

9341--1 2004 n

l latea u lI1 unitie and Iar

Earle Ti moth 1980 M(

York Grayson Don

1984 Q~I

demieI 2001 Th

ofWora Grayson Don

1999 H tl

the landscape 0 human pre-

ion tha t when that predicted gh- alue prey 1a1 r cord can however tha t onomic abUllshygh-value prey in taxonon ic in the zooarshy

-d to intensify rously evalushy~ faunas come Lyman 2006 1em are valid ~ inferences

in a con texl och ran s tes t

y AlIlh ropollJSf

tion rite Ki va

Venlana Cnve ona St) tc Untshy

peclive edited J Socie ty 13wshy

sea rch 14143shy

Ity SheJ rw nlcr

Prehistoric Anthropogenic Impacts Are Not Ubiquitous I 221

Decline at the Mina rd Site Washington State U A Journal of Archaeological Science 341087- 1097

Brough ton Jack M 19940 Decl ines in Mam ma lian Foraging Efficiency D uring the Late H olocene San

Franci (o Bay Cali forni Joumal of Anthropological Archaeology 13 71-40l 1994b La te Holocene ResOllrce Intensification in the Sa ramento Valley ali fornia

The Vertebrate middot vidence Journal of Archaeological Science 21 501 -514 Brough ton Jack M a nd Frank E Bayham

2003 Showing Off Foraging Models and the Ascendance of Large-Game lIunting in the Ca lifornia Middle Archaic American Antiquity 68783-789

Broughton Jack M and James F O Conn II 199 On Evolutiona ry Ecology Selectionist Archaeology and Behavio ra l Archaeolshy

ogy American AntiquitH 64153-165 Butler Virginia L and Sara h K Campbell

2004 Resource Intens iHca tion and Resou rce Depression in the Pacific orlhwest of or th America A Znoa rchaeological Review Journal of World Prehistory 1R327shy405

Byer David A an d Jack M Broughton 2004 1ioloc~ne Envir nmental Change Artiodactyl Abundances and Hum an H unlshy

ing Strategies in the Greal Basin American Antiquity 69 235- 2)5 By rs DClvid A Craig S Smith and Jack M Broughton

2005 Holocene Ar tioclacty l Population Histories and Large Came Hunting in the Wyomi ng Basin USA Jou 11Iai of Archaeological Science 321 21-142

C nnOI1 Mich ael D 2000 Large Mnnmal Relative bundance in Pithousc and Pli ebio P riod Archaeoshy

faw1as from ou thweslern New Mexico Rc ouree Depression Among the Mi mbresshyMogollon Joumal oj Anthropological ArciUlcology 1931 7-347

2001 Archaeofau nal Relative Abu ndc nce Sample Size and Statis tical M th ods Jourllil l of Arclll1cological Science 28185--1 95

2003 A Model of en trcll Place Forager Prey Choice and an Ap plication to Fa unal Rema ins from the Mim bres Valley New Mexico Journal of Anthropological Archaeolshyogy 221 - 25

Chatters James c 1995 Popula tion Growth Clima tic ooling a nd the Development of ollector Stratshy

eg iee on the Sou thern Pla leau Western No rth Am rica Journal of World Preliiston 9341-400

2004 Th Influence 01 I-he Bow and Arrow on Village Formation on the Colu mb ia Plateau In Complex Iilliller-Gatherers [ voill tion IIlld Or~all ization of Prehistoric - VIIshy

mUil itics on till Plateau of NortlLUcstlYll North America ed it d by William C Prenti ss Clnd Ia n Kuijt pp 67- 83 Unive rsity of Utah Press Salt Lake City

Earle Timot hy K and Andrew L Christenson (editors) 1980 Modeling Change in PrPililtforic Suls isJence poundco nomi( lt A ademic Pres ew

York Grlt1 yson Dona ld K

1984 Quantitative Zooarrhar gy Topics in the Analysis of Arci1lleolos ical Faunas Aca shyemic Pr ss Orlan do 1loridlt1

200 I The lt rchaeoJog i 11 Reco rd of rIuman Impacts on Animal Populations Jou rnal of World Preilistory 1 ~1-68

ril yson Donald K and Michael D Ca nnon 1999 H uman Paleoecology and Foraging Theory in the reat Bas in In Models or

222 I R L Lyman

the Millennium [he Current Slllu~ of Great Bnsin Anthropological Research edited by Charlotte Beck pp 111-15 1 ni ersily of Utah Press Sd it Lake C ity

Grayson Donald K a nd Franlto isc Delpech 1998 Changing Diet Bread th in the Early pper Palaeol il hie of Southwestern FrJ nce

Jo urnal of Archaeological Science 25 111 9- 11 29 Hickerson Ila roid

1965 The Virgi ni a Deer al d Intertriba l Buffer Zones in the ppe Missi sippi Valley In Man Culturc and A Ii lnals The Role of Animals in HlInan Ecological Adjusfmcllts edi t db Anthony Leeds and Andr w P Vayda pp 43-tlS Publicati on 78 Amerishycan Association for the Advancemen t of Science Washington DC

H il ciebra nd l William R and Terry L JOnES 2002 Oepl lion of Prehis toric Pinniped Popu lations Along the alifomia a nd Orshy

egon Coasts Were Humans the Cause In Wilderness and Political Ecology J1lo riginnl Influences and the Original ~Iatc of Na ture editeJ by C ha rl s E Kay nd Randy T Simmons p p 72- 110 niverity of Utah Press Sa lt Lake middotity

H ildebrandt William R and Kell y R McGuire 2002 he As e ndance of Hu nting During the C lifornia M iddle Archaic An Evolushy

tionary Perspective American Alltiq uity 6721J - 256 2003 Large-Game Hunti ng Cender-l ifferen tia ted W rk Organization and lhl

Role of Evolutiona ry Ecology in ali forni a nd relt Basin Preh islo ry A Reply to Broughton and Bayham American Antiquity 68790-792

Hockett Bryan 2005 Midd le and LaleHolocene I lunting in the Greal Bas in A Critical Rev iew of the

Deba te and Fulu re Prospects American Antiquity 70713-731 H unn Eugene S

1982 Mobility as a Factor Limiting Resource Use in the Columbia Plateau of North A me rica In Resource Ma nagers North American and Australian Hun ter-Gatherers edshyted by Nancy M Wil lia ms and Eugene S I lunn pp 17 3 AAAS SeJ cled Symposhysi um No 67 Westview Press Boulder Colorado

Jan lsk i Joel 1997 Fremont Hunting and Resource Intensificat ioll in the Eltlstc rn Gr a t Basin Jourshy

nal ofArchaeological Science 241075- 1088 Jones Te rry L and Willia m R H ildebrandt

1995 Reasserti ng a Prehi toric Tragedy of the Com mons Reply to Lym an Journal of Anthropological Archaeology 147R-98

Kay Charles E 1994 Aboriginal Overkill Th Role o f Native Am eri cans in Structuring Weste rn

Ecosystems Human Nature 5359-398 Kidwdl Susan M

2001 Preservation of SpeCies Abundance in the Fossil Record Science 294 l091shy1094

Krtbs John R and Nicholas B Davie 1978 Behavioll ral Ecology J1 n Evolutionary Approach Blackwell Sde nce Oxford UX

LaJiberte Andrea and Will iam J Ripple 2003 Wil dl ife EnCow1ters by Lewis and lark A Spatia l Analys is of Interactions Beshy

tw een alive Americans and Wild life BioSciel1Ce 53994- lO03 Linilrcs Olga F

1976 Garden Hunting in the American Tropics Human Ecology 433 1-349 Lu pa Karen D and Dave N Schm itt

2005 ma ll Prey Hunting Teclu1010gy and Zo a rchaeological M asu res of Taxonomshy

ic DivE Forest

Lyman R Le 1995 01

AI eric 2000a Bl

chrono 2000b R

west AI 2003a Pi

and No --Jorth

200J b T~ Foragil

20011lt1 Al logica l

2004b L Easten

2006 Pc 1511 - 1

2008 Q Lyman R Le

2003 L( tions 0

archaeo l yman R Lc

2002 Tl States

McGuire Kel 200~ Rt

Durint Martin Paul

1999a M Sink I Hart F

1999b Vv 1336-lt

2002 G to Cc

MlU1fO Nata 2005 Z

sity in 45(Sul

Nagaoka Lis 200 D

Zealar Pa rmesan C

2006 pound view oj

220 I R L Lyman

trends in faunal abw d ances seem to reOect what is happ ning on the I ndscape it is another matter to build a strong ase that th tr nd is related to human pre shydation- that is to bu ild a strongly warrll1ted attribu li on

Finally the cases r have reviewed tend to confirm my suspicion that wl1(11 a trend in taxonomi abundances is found that is the opposite of lhilt predicted by mod [s delied from foraging theory- wh n abundances of high-value prey increase 0 er time-analysis in rease in omplexity until ~h fauna l record can be aligned with a revised model This in its lf is not bad T worry however that it migh t indicale that we are bit too complacent when shifts in taxonomic abunshydances malch lhe modeled signature of decreased bundances of high- Cllue prey We do not rigorously explore other possibl causes f r the hanges in taxonomic abundances The ubiquity of anthropogeni ally influcnced faunas in the zooarshychaeological record may thus be marc apparent than r~ cd We need to intensify scrutiny of that record for such e iden e but we also ne d [0 rigorously evalu shyMe any indication o f ClnLfuopogcnically influenced faunas s those faunas ome to play a more prominent role in modern COllSl[valion biology laquo(g Lyman 2006 Stahl 2008) we will wan l to make SLIfe lhat our idel tifka tions of them arc valid else we risk making management de i ions on th basis of inac mat inferences

Acknowledgments

My sincere thanks to two anonymous revi wcrs who in a conlext having nothing to do with this chapter insisled tha l l [earn about Cochran s test fOf linear trends

References

Alvard Michael S 1998 Evolutionary Ecology and Resource Conservation Evolutlonanf Anthropology

762-74 Bayham Frank E

1979 Factors In flu ncing the ArchJic Palt rn of Animal Exploitation The Kiva 44219- 235

1982 A Diachronic Analy is of Prehistoric Animal Exploitation at Ventana Cave Unpublished PhD disserlation Depa rlm ent of Anthropology Arizona Sta te Unishyver ity Tempe

Behrensmeyer Anna K Susan M Kid we ll and lobert A Castaldo 2000 Taphonomy and PaJ obiology In Deep Time Paleobiologys Perspective ed ited

by Douglas It Erw in and Scott L Wing pp 103~147 PaJconlo logicltJ l ociety Lawshyrence Kansa5

Bird Douglas W and James F QCcmne ll 2006 Behavioral Ecology and Archaeology Journal of Arclmcological Research 14 143shy

188 Bovy Kristine M

2007 labal Human Impacts or Cli mat Change Explaining the Sooty Shea rwater

Dedil 341 01

Broughton J 1994a r

Franc 1994b l

The V Broughton J

2003 S in the

Brough ton J 1999 C

ogy A Butler Virgil

2004 R of NO 405

Byprs David 2004 II

iog I I

Byers David 2005 H

Wyom Cannon Mic

2000 L faw1as Mogol

2001 A Journal

2003 A Rerna il ogy 22

Chatters Jam 1995 Pc

egies 0

9341--1 2004 n

l latea u lI1 unitie and Iar

Earle Ti moth 1980 M(

York Grayson Don

1984 Q~I

demieI 2001 Th

ofWora Grayson Don

1999 H tl

the landscape 0 human pre-

ion tha t when that predicted gh- alue prey 1a1 r cord can however tha t onomic abUllshygh-value prey in taxonon ic in the zooarshy

-d to intensify rously evalushy~ faunas come Lyman 2006 1em are valid ~ inferences

in a con texl och ran s tes t

y AlIlh ropollJSf

tion rite Ki va

Venlana Cnve ona St) tc Untshy

peclive edited J Socie ty 13wshy

sea rch 14143shy

Ity SheJ rw nlcr

Prehistoric Anthropogenic Impacts Are Not Ubiquitous I 221

Decline at the Mina rd Site Washington State U A Journal of Archaeological Science 341087- 1097

Brough ton Jack M 19940 Decl ines in Mam ma lian Foraging Efficiency D uring the Late H olocene San

Franci (o Bay Cali forni Joumal of Anthropological Archaeology 13 71-40l 1994b La te Holocene ResOllrce Intensification in the Sa ramento Valley ali fornia

The Vertebrate middot vidence Journal of Archaeological Science 21 501 -514 Brough ton Jack M a nd Frank E Bayham

2003 Showing Off Foraging Models and the Ascendance of Large-Game lIunting in the Ca lifornia Middle Archaic American Antiquity 68783-789

Broughton Jack M and James F O Conn II 199 On Evolutiona ry Ecology Selectionist Archaeology and Behavio ra l Archaeolshy

ogy American AntiquitH 64153-165 Butler Virginia L and Sara h K Campbell

2004 Resource Intens iHca tion and Resou rce Depression in the Pacific orlhwest of or th America A Znoa rchaeological Review Journal of World Prehistory 1R327shy405

Byer David A an d Jack M Broughton 2004 1ioloc~ne Envir nmental Change Artiodactyl Abundances and Hum an H unlshy

ing Strategies in the Greal Basin American Antiquity 69 235- 2)5 By rs DClvid A Craig S Smith and Jack M Broughton

2005 Holocene Ar tioclacty l Population Histories and Large Came Hunting in the Wyomi ng Basin USA Jou 11Iai of Archaeological Science 321 21-142

C nnOI1 Mich ael D 2000 Large Mnnmal Relative bundance in Pithousc and Pli ebio P riod Archaeoshy

faw1as from ou thweslern New Mexico Rc ouree Depression Among the Mi mbresshyMogollon Joumal oj Anthropological ArciUlcology 1931 7-347

2001 Archaeofau nal Relative Abu ndc nce Sample Size and Statis tical M th ods Jourllil l of Arclll1cological Science 28185--1 95

2003 A Model of en trcll Place Forager Prey Choice and an Ap plication to Fa unal Rema ins from the Mim bres Valley New Mexico Journal of Anthropological Archaeolshyogy 221 - 25

Chatters James c 1995 Popula tion Growth Clima tic ooling a nd the Development of ollector Stratshy

eg iee on the Sou thern Pla leau Western No rth Am rica Journal of World Preliiston 9341-400

2004 Th Influence 01 I-he Bow and Arrow on Village Formation on the Colu mb ia Plateau In Complex Iilliller-Gatherers [ voill tion IIlld Or~all ization of Prehistoric - VIIshy

mUil itics on till Plateau of NortlLUcstlYll North America ed it d by William C Prenti ss Clnd Ia n Kuijt pp 67- 83 Unive rsity of Utah Press Salt Lake City

Earle Timot hy K and Andrew L Christenson (editors) 1980 Modeling Change in PrPililtforic Suls isJence poundco nomi( lt A ademic Pres ew

York Grlt1 yson Dona ld K

1984 Quantitative Zooarrhar gy Topics in the Analysis of Arci1lleolos ical Faunas Aca shyemic Pr ss Orlan do 1loridlt1

200 I The lt rchaeoJog i 11 Reco rd of rIuman Impacts on Animal Populations Jou rnal of World Preilistory 1 ~1-68

ril yson Donald K and Michael D Ca nnon 1999 H uman Paleoecology and Foraging Theory in the reat Bas in In Models or

222 I R L Lyman

the Millennium [he Current Slllu~ of Great Bnsin Anthropological Research edited by Charlotte Beck pp 111-15 1 ni ersily of Utah Press Sd it Lake C ity

Grayson Donald K a nd Franlto isc Delpech 1998 Changing Diet Bread th in the Early pper Palaeol il hie of Southwestern FrJ nce

Jo urnal of Archaeological Science 25 111 9- 11 29 Hickerson Ila roid

1965 The Virgi ni a Deer al d Intertriba l Buffer Zones in the ppe Missi sippi Valley In Man Culturc and A Ii lnals The Role of Animals in HlInan Ecological Adjusfmcllts edi t db Anthony Leeds and Andr w P Vayda pp 43-tlS Publicati on 78 Amerishycan Association for the Advancemen t of Science Washington DC

H il ciebra nd l William R and Terry L JOnES 2002 Oepl lion of Prehis toric Pinniped Popu lations Along the alifomia a nd Orshy

egon Coasts Were Humans the Cause In Wilderness and Political Ecology J1lo riginnl Influences and the Original ~Iatc of Na ture editeJ by C ha rl s E Kay nd Randy T Simmons p p 72- 110 niverity of Utah Press Sa lt Lake middotity

H ildebrandt William R and Kell y R McGuire 2002 he As e ndance of Hu nting During the C lifornia M iddle Archaic An Evolushy

tionary Perspective American Alltiq uity 6721J - 256 2003 Large-Game Hunti ng Cender-l ifferen tia ted W rk Organization and lhl

Role of Evolutiona ry Ecology in ali forni a nd relt Basin Preh islo ry A Reply to Broughton and Bayham American Antiquity 68790-792

Hockett Bryan 2005 Midd le and LaleHolocene I lunting in the Greal Bas in A Critical Rev iew of the

Deba te and Fulu re Prospects American Antiquity 70713-731 H unn Eugene S

1982 Mobility as a Factor Limiting Resource Use in the Columbia Plateau of North A me rica In Resource Ma nagers North American and Australian Hun ter-Gatherers edshyted by Nancy M Wil lia ms and Eugene S I lunn pp 17 3 AAAS SeJ cled Symposhysi um No 67 Westview Press Boulder Colorado

Jan lsk i Joel 1997 Fremont Hunting and Resource Intensificat ioll in the Eltlstc rn Gr a t Basin Jourshy

nal ofArchaeological Science 241075- 1088 Jones Te rry L and Willia m R H ildebrandt

1995 Reasserti ng a Prehi toric Tragedy of the Com mons Reply to Lym an Journal of Anthropological Archaeology 147R-98

Kay Charles E 1994 Aboriginal Overkill Th Role o f Native Am eri cans in Structuring Weste rn

Ecosystems Human Nature 5359-398 Kidwdl Susan M

2001 Preservation of SpeCies Abundance in the Fossil Record Science 294 l091shy1094

Krtbs John R and Nicholas B Davie 1978 Behavioll ral Ecology J1 n Evolutionary Approach Blackwell Sde nce Oxford UX

LaJiberte Andrea and Will iam J Ripple 2003 Wil dl ife EnCow1ters by Lewis and lark A Spatia l Analys is of Interactions Beshy

tw een alive Americans and Wild life BioSciel1Ce 53994- lO03 Linilrcs Olga F

1976 Garden Hunting in the American Tropics Human Ecology 433 1-349 Lu pa Karen D and Dave N Schm itt

2005 ma ll Prey Hunting Teclu1010gy and Zo a rchaeological M asu res of Taxonomshy

ic DivE Forest

Lyman R Le 1995 01

AI eric 2000a Bl

chrono 2000b R

west AI 2003a Pi

and No --Jorth

200J b T~ Foragil

20011lt1 Al logica l

2004b L Easten

2006 Pc 1511 - 1

2008 Q Lyman R Le

2003 L( tions 0

archaeo l yman R Lc

2002 Tl States

McGuire Kel 200~ Rt

Durint Martin Paul

1999a M Sink I Hart F

1999b Vv 1336-lt

2002 G to Cc

MlU1fO Nata 2005 Z

sity in 45(Sul

Nagaoka Lis 200 D

Zealar Pa rmesan C

2006 pound view oj

the landscape 0 human pre-

ion tha t when that predicted gh- alue prey 1a1 r cord can however tha t onomic abUllshygh-value prey in taxonon ic in the zooarshy

-d to intensify rously evalushy~ faunas come Lyman 2006 1em are valid ~ inferences

in a con texl och ran s tes t

y AlIlh ropollJSf

tion rite Ki va

Venlana Cnve ona St) tc Untshy

peclive edited J Socie ty 13wshy

sea rch 14143shy

Ity SheJ rw nlcr

Prehistoric Anthropogenic Impacts Are Not Ubiquitous I 221

Decline at the Mina rd Site Washington State U A Journal of Archaeological Science 341087- 1097

Brough ton Jack M 19940 Decl ines in Mam ma lian Foraging Efficiency D uring the Late H olocene San

Franci (o Bay Cali forni Joumal of Anthropological Archaeology 13 71-40l 1994b La te Holocene ResOllrce Intensification in the Sa ramento Valley ali fornia

The Vertebrate middot vidence Journal of Archaeological Science 21 501 -514 Brough ton Jack M a nd Frank E Bayham

2003 Showing Off Foraging Models and the Ascendance of Large-Game lIunting in the Ca lifornia Middle Archaic American Antiquity 68783-789

Broughton Jack M and James F O Conn II 199 On Evolutiona ry Ecology Selectionist Archaeology and Behavio ra l Archaeolshy

ogy American AntiquitH 64153-165 Butler Virginia L and Sara h K Campbell

2004 Resource Intens iHca tion and Resou rce Depression in the Pacific orlhwest of or th America A Znoa rchaeological Review Journal of World Prehistory 1R327shy405

Byer David A an d Jack M Broughton 2004 1ioloc~ne Envir nmental Change Artiodactyl Abundances and Hum an H unlshy

ing Strategies in the Greal Basin American Antiquity 69 235- 2)5 By rs DClvid A Craig S Smith and Jack M Broughton

2005 Holocene Ar tioclacty l Population Histories and Large Came Hunting in the Wyomi ng Basin USA Jou 11Iai of Archaeological Science 321 21-142

C nnOI1 Mich ael D 2000 Large Mnnmal Relative bundance in Pithousc and Pli ebio P riod Archaeoshy

faw1as from ou thweslern New Mexico Rc ouree Depression Among the Mi mbresshyMogollon Joumal oj Anthropological ArciUlcology 1931 7-347

2001 Archaeofau nal Relative Abu ndc nce Sample Size and Statis tical M th ods Jourllil l of Arclll1cological Science 28185--1 95

2003 A Model of en trcll Place Forager Prey Choice and an Ap plication to Fa unal Rema ins from the Mim bres Valley New Mexico Journal of Anthropological Archaeolshyogy 221 - 25

Chatters James c 1995 Popula tion Growth Clima tic ooling a nd the Development of ollector Stratshy

eg iee on the Sou thern Pla leau Western No rth Am rica Journal of World Preliiston 9341-400

2004 Th Influence 01 I-he Bow and Arrow on Village Formation on the Colu mb ia Plateau In Complex Iilliller-Gatherers [ voill tion IIlld Or~all ization of Prehistoric - VIIshy

mUil itics on till Plateau of NortlLUcstlYll North America ed it d by William C Prenti ss Clnd Ia n Kuijt pp 67- 83 Unive rsity of Utah Press Salt Lake City

Earle Timot hy K and Andrew L Christenson (editors) 1980 Modeling Change in PrPililtforic Suls isJence poundco nomi( lt A ademic Pres ew

York Grlt1 yson Dona ld K

1984 Quantitative Zooarrhar gy Topics in the Analysis of Arci1lleolos ical Faunas Aca shyemic Pr ss Orlan do 1loridlt1

200 I The lt rchaeoJog i 11 Reco rd of rIuman Impacts on Animal Populations Jou rnal of World Preilistory 1 ~1-68

ril yson Donald K and Michael D Ca nnon 1999 H uman Paleoecology and Foraging Theory in the reat Bas in In Models or

222 I R L Lyman

the Millennium [he Current Slllu~ of Great Bnsin Anthropological Research edited by Charlotte Beck pp 111-15 1 ni ersily of Utah Press Sd it Lake C ity

Grayson Donald K a nd Franlto isc Delpech 1998 Changing Diet Bread th in the Early pper Palaeol il hie of Southwestern FrJ nce

Jo urnal of Archaeological Science 25 111 9- 11 29 Hickerson Ila roid

1965 The Virgi ni a Deer al d Intertriba l Buffer Zones in the ppe Missi sippi Valley In Man Culturc and A Ii lnals The Role of Animals in HlInan Ecological Adjusfmcllts edi t db Anthony Leeds and Andr w P Vayda pp 43-tlS Publicati on 78 Amerishycan Association for the Advancemen t of Science Washington DC

H il ciebra nd l William R and Terry L JOnES 2002 Oepl lion of Prehis toric Pinniped Popu lations Along the alifomia a nd Orshy

egon Coasts Were Humans the Cause In Wilderness and Political Ecology J1lo riginnl Influences and the Original ~Iatc of Na ture editeJ by C ha rl s E Kay nd Randy T Simmons p p 72- 110 niverity of Utah Press Sa lt Lake middotity

H ildebrandt William R and Kell y R McGuire 2002 he As e ndance of Hu nting During the C lifornia M iddle Archaic An Evolushy

tionary Perspective American Alltiq uity 6721J - 256 2003 Large-Game Hunti ng Cender-l ifferen tia ted W rk Organization and lhl

Role of Evolutiona ry Ecology in ali forni a nd relt Basin Preh islo ry A Reply to Broughton and Bayham American Antiquity 68790-792

Hockett Bryan 2005 Midd le and LaleHolocene I lunting in the Greal Bas in A Critical Rev iew of the

Deba te and Fulu re Prospects American Antiquity 70713-731 H unn Eugene S

1982 Mobility as a Factor Limiting Resource Use in the Columbia Plateau of North A me rica In Resource Ma nagers North American and Australian Hun ter-Gatherers edshyted by Nancy M Wil lia ms and Eugene S I lunn pp 17 3 AAAS SeJ cled Symposhysi um No 67 Westview Press Boulder Colorado

Jan lsk i Joel 1997 Fremont Hunting and Resource Intensificat ioll in the Eltlstc rn Gr a t Basin Jourshy

nal ofArchaeological Science 241075- 1088 Jones Te rry L and Willia m R H ildebrandt

1995 Reasserti ng a Prehi toric Tragedy of the Com mons Reply to Lym an Journal of Anthropological Archaeology 147R-98

Kay Charles E 1994 Aboriginal Overkill Th Role o f Native Am eri cans in Structuring Weste rn

Ecosystems Human Nature 5359-398 Kidwdl Susan M

2001 Preservation of SpeCies Abundance in the Fossil Record Science 294 l091shy1094

Krtbs John R and Nicholas B Davie 1978 Behavioll ral Ecology J1 n Evolutionary Approach Blackwell Sde nce Oxford UX

LaJiberte Andrea and Will iam J Ripple 2003 Wil dl ife EnCow1ters by Lewis and lark A Spatia l Analys is of Interactions Beshy

tw een alive Americans and Wild life BioSciel1Ce 53994- lO03 Linilrcs Olga F

1976 Garden Hunting in the American Tropics Human Ecology 433 1-349 Lu pa Karen D and Dave N Schm itt

2005 ma ll Prey Hunting Teclu1010gy and Zo a rchaeological M asu res of Taxonomshy

ic DivE Forest

Lyman R Le 1995 01

AI eric 2000a Bl

chrono 2000b R

west AI 2003a Pi

and No --Jorth

200J b T~ Foragil

20011lt1 Al logica l

2004b L Easten

2006 Pc 1511 - 1

2008 Q Lyman R Le

2003 L( tions 0

archaeo l yman R Lc

2002 Tl States

McGuire Kel 200~ Rt

Durint Martin Paul

1999a M Sink I Hart F

1999b Vv 1336-lt

2002 G to Cc

MlU1fO Nata 2005 Z

sity in 45(Sul

Nagaoka Lis 200 D

Zealar Pa rmesan C

2006 pound view oj

222 I R L Lyman

the Millennium [he Current Slllu~ of Great Bnsin Anthropological Research edited by Charlotte Beck pp 111-15 1 ni ersily of Utah Press Sd it Lake C ity

Grayson Donald K a nd Franlto isc Delpech 1998 Changing Diet Bread th in the Early pper Palaeol il hie of Southwestern FrJ nce

Jo urnal of Archaeological Science 25 111 9- 11 29 Hickerson Ila roid

1965 The Virgi ni a Deer al d Intertriba l Buffer Zones in the ppe Missi sippi Valley In Man Culturc and A Ii lnals The Role of Animals in HlInan Ecological Adjusfmcllts edi t db Anthony Leeds and Andr w P Vayda pp 43-tlS Publicati on 78 Amerishycan Association for the Advancemen t of Science Washington DC

H il ciebra nd l William R and Terry L JOnES 2002 Oepl lion of Prehis toric Pinniped Popu lations Along the alifomia a nd Orshy

egon Coasts Were Humans the Cause In Wilderness and Political Ecology J1lo riginnl Influences and the Original ~Iatc of Na ture editeJ by C ha rl s E Kay nd Randy T Simmons p p 72- 110 niverity of Utah Press Sa lt Lake middotity

H ildebrandt William R and Kell y R McGuire 2002 he As e ndance of Hu nting During the C lifornia M iddle Archaic An Evolushy

tionary Perspective American Alltiq uity 6721J - 256 2003 Large-Game Hunti ng Cender-l ifferen tia ted W rk Organization and lhl

Role of Evolutiona ry Ecology in ali forni a nd relt Basin Preh islo ry A Reply to Broughton and Bayham American Antiquity 68790-792

Hockett Bryan 2005 Midd le and LaleHolocene I lunting in the Greal Bas in A Critical Rev iew of the

Deba te and Fulu re Prospects American Antiquity 70713-731 H unn Eugene S

1982 Mobility as a Factor Limiting Resource Use in the Columbia Plateau of North A me rica In Resource Ma nagers North American and Australian Hun ter-Gatherers edshyted by Nancy M Wil lia ms and Eugene S I lunn pp 17 3 AAAS SeJ cled Symposhysi um No 67 Westview Press Boulder Colorado

Jan lsk i Joel 1997 Fremont Hunting and Resource Intensificat ioll in the Eltlstc rn Gr a t Basin Jourshy

nal ofArchaeological Science 241075- 1088 Jones Te rry L and Willia m R H ildebrandt

1995 Reasserti ng a Prehi toric Tragedy of the Com mons Reply to Lym an Journal of Anthropological Archaeology 147R-98

Kay Charles E 1994 Aboriginal Overkill Th Role o f Native Am eri cans in Structuring Weste rn

Ecosystems Human Nature 5359-398 Kidwdl Susan M

2001 Preservation of SpeCies Abundance in the Fossil Record Science 294 l091shy1094

Krtbs John R and Nicholas B Davie 1978 Behavioll ral Ecology J1 n Evolutionary Approach Blackwell Sde nce Oxford UX

LaJiberte Andrea and Will iam J Ripple 2003 Wil dl ife EnCow1ters by Lewis and lark A Spatia l Analys is of Interactions Beshy

tw een alive Americans and Wild life BioSciel1Ce 53994- lO03 Linilrcs Olga F

1976 Garden Hunting in the American Tropics Human Ecology 433 1-349 Lu pa Karen D and Dave N Schm itt

2005 ma ll Prey Hunting Teclu1010gy and Zo a rchaeological M asu res of Taxonomshy

ic DivE Forest

Lyman R Le 1995 01

AI eric 2000a Bl

chrono 2000b R

west AI 2003a Pi

and No --Jorth

200J b T~ Foragil

20011lt1 Al logica l

2004b L Easten

2006 Pc 1511 - 1

2008 Q Lyman R Le

2003 L( tions 0

archaeo l yman R Lc

2002 Tl States

McGuire Kel 200~ Rt

Durint Martin Paul

1999a M Sink I Hart F

1999b Vv 1336-lt

2002 G to Cc

MlU1fO Nata 2005 Z

sity in 45(Sul

Nagaoka Lis 200 D

Zealar Pa rmesan C

2006 pound view oj

Ircll edited by

estern France

issi ppi Valley 1 Adjustll1 lllts on 78 AmEJ ishy

ornia and OrshyJgy Aboriginal and Rand y T

lie An Evolushy

bon and the ry A Reply to

Review of the

teal of North -Gilillerels dshyecled Symposhy

~at Basin JO IIr shy

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ne 294 1091-shy

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teracti ons Beshy

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ofTaxonom-

Pr histor i Anthropogenic Impacts Are Nol Ubiquitous j 223

ic Diversity and Abu ndance Ethnoarchaeological Evidence fro m Central Afri can Forest Foragers journal of Anthropological Archaeology 24335-353

Lyman R Lee 1995 On the Evol ution of Marine Mammal Hunti ng on the West COnst oi North

America _journal of Antl1mpoiogiCllI Archaeology 1445-77

2000a Building Cultura l 0 1ronology in Eastern Washing ton The In fl uence of eoshychronology Index Fossils and Rad iocarbon Dating Geoarchaeology 15609--1148

2000b Radiocarbon Da ting in as t m Washington and in Western Washington I ollhshywest Anthropological IZcsearrh Notes 341-] 6

2003a Pinniped Behavior Fo raging Theory and the Depression of Metapopulat ions and Nond pression of a L cal Populat ion on the Southern orthw st Coast of North America Journal of Anthropological Archaeology 22376-388

2003b The Influence of Time Averaging and Space Averaging on the Application of Foraging Theory in Zooarchaeology journal of Archaeological Science 30595- 610

2004a Aboriginal Overkill in the Inte rmounta in West of North America Zooarcl1a toshylogical Tests and Iln plications Human Nllture 15 169-208

2004b Late-Q uaternary Diminution and Abundance of Prehistoric Bison (Biso1 sp) in Eastern Washington _ ta te SA Quaternary Research 6276- 85

2006 Paleozoology in the enjce of Conse rvJtion Biology Evollil ionary Anthropology 15 11- 19

2008 Quantitative Pnleozoology CJmbridge University Presgt Cambridge Lyman R Lee and R Jay Lyman

2003 Lessons (rom Temporal Variation in the Mammalian Faunas from Two olJecshyti ons of Owl Pellets in ol urnbi a County Washington International Tournai of Osteoshyarchaeology 13150- 156

Lyman R Lee and Steve Wolverton 2002 The Latc Prchistoric- Early Historic Ga me Sink in the orthwestern United

States Conservation Biologlj 1673-85 McGuire Kelly R and William R Hildehrandt

2005 Re-Thinking Creat Basin foragers Prestige Hunting and Costly SignJling During the iddl Mehaie PerioJ Amllicall Arltiqll ity 70 695-712

MCl rtin Pau l S and Christ-inc R Szuter 1999a Megafauna ( f the Columbia Basin 1800--1840 Lewis and Clark in a Game

Sink In Norilwcs t Lmlds ortilwest Peoples edited by Dale D Goble and Pau l W H -rt pp [88- 204 niversity of Washington [ rl55 Seat tle

1999b War Zones and Game Sinks in Lewis and Clarks West Con ervati(1II Biology 1336--15

2002 Gnme Parks Before and After Lewis and Clark Rep ly to Lyman anJ Wolvershyton Conservation Biology 16244--247

Munro Natal ie D 2005 ZOOJf haeologica l Measures of HunLing Pressure and Occupation Intenshy

sity in the Natufian Implications for Agricultu rJl Origins Current Antl lOpology 45(Supp l) S5--S33

agaoka lisa 2005 Declining Foraging Eflj cicncy and Moa Ca rcass Exploitation in Southern I W

Ztal and journal of Archaeological Sciel1ce 32 132R--1338 Pa rmesan CamiJIe

2006 Ecological and Evolutionary Responses to Recen t Climate Change Aml unl Reshyview of Ecology Evolutiol1 and Sy5leznll tics 37637- 669

224 I 1lt L Lyrriil1

Pullia m H ROlll d 1988 Sources Sinks and Iopulation Regulation Allwrirnll Nat ll mlisI 132652-661

Pykt Graham I-I H Ronald r ull iam and Ert L 0 1arnov 1977 O ptima l Foraging A d ectiv Review of Theory and Tests Quarlerly Review of

Biology 52137- ] 54 Smith Eri c Alden and M~rk Wishnie

2000 ( on erv a tion and Subsistence in SmJll-Scale Societies A1IIHlai Review of l shythropology 29493--524

Speth John D and llSln L colt 1989 Ho rticultu re m d Large-Mam mal Hunting The Role of Resource Dep letion

dnd the Constrain ts of Time nnd Labor In fa rll1 ers as Il llll as Tile Im plications of jtdshyenliSIIl edited by Susan Kent pp 71- 79 Cam br idge niversi ty Press Cambrid ge

Stah l Peter W 2000 Archaeofauna l Accumulation h -gmented Forests i1 nd Anthropogenic L ndshy

scape Mos ics in the Tropical Lowlands of Prehispanic Ecuador Latill Allleriwn AIIshyliqll ihJ J 1241-257

2008 The Contributions f Zooarchaeology to [listo rical Ecology in the Neotropics QlIllten wry Internrll ivna I180S - 16

St ephens Davi d IN and John R Krebs 1986 Foraging Theory lrinceton nive rsity Prpss Pri nceton lew Jersey

Stiner M ry C 2001 Thirty Years o n the Broad Spectrum Revolution l nd Pltl leolithic Demograshy

phy Prace liirIgs ~f II le Natiolal Academy of Sciences 986993- 6996 Stiner Mary a talie D M u nro and rodd A Surovell

2000 The Tortoise and the Hd re Small-Gam e Use the Broad -Spectrum Revolution and Paleoli th ic Demog raphy Current Anthropology 4139- 73

Stine r Mary c l a tal ie D Munro Todd A Surovell Ettan Tchernov and O fer Bar-Yos f 1999 Pa leolith ic Pop ulatio n Crowth Pu lses Eviden ed by Small Anim al Exploitashy

tion Science 283 190- 194 Szute r hristine R and fran k E Bayh In

1989 Sedenlis m a nd Prehis tor ic Animal Procurement Among Desert Hort icu ltura lshyists ot the N orth American Sou thwes t In Farmers IS HLlI ltfrs The Implicatiolls of Sedshyenism ed ited by Susa n Ken t pp 80- 9 Ca mbridge Un iversity Press Cambri dge

Uga n Andrew 2005 Does Si ze Matter Body Size Mass Coli cting imd Their [mplica t i on~ for Unshy

ders tand ing Preh istoric F ra ging Behavior Amcrica l1 Alll iqldty 7075-~9 Wi nt rhalder Bruce and Er ic Alden Smith

2000 Analy zi ng A dn plive Slra teg ie~ Human Behavioral Fcology at rwenty-five Fvollilionary w thropology 951- 72

Winterhaldc l~ Bruce and Eric Alden Smith (ed itors) 1981 Hunter-Gatherer FO rll8ing Stralegie Ethnographic and Archeological Analyses

University of Chicago Press Chicago Wulverton Steve

2005 The Effects o f the H ypsitherma I on Prehistori ( ForJg ing EffiCiency in Missouri American Antiquity 709J- l06

Zar Jerrold H 1996 Biostatistical Analysis 3rd cd Prentice J la ll Upper SJddle Rive r ew J rsey

11

(

1

1 Ricks Stanf Lo argu middot tha lo be C0l1str

lhat the rna bu t also of more [argul of con truc the built n

The Arcwca og logica l Invest Ill inois Univel

224 I 1lt L Lyrriil1

Pullia m H ROlll d 1988 Sources Sinks and Iopulation Regulation Allwrirnll Nat ll mlisI 132652-661

Pykt Graham I-I H Ronald r ull iam and Ert L 0 1arnov 1977 O ptima l Foraging A d ectiv Review of Theory and Tests Quarlerly Review of

Biology 52137- ] 54 Smith Eri c Alden and M~rk Wishnie

2000 ( on erv a tion and Subsistence in SmJll-Scale Societies A1IIHlai Review of l shythropology 29493--524

Speth John D and llSln L colt 1989 Ho rticultu re m d Large-Mam mal Hunting The Role of Resource Dep letion

dnd the Constrain ts of Time nnd Labor In fa rll1 ers as Il llll as Tile Im plications of jtdshyenliSIIl edited by Susan Kent pp 71- 79 Cam br idge niversi ty Press Cambrid ge

Stah l Peter W 2000 Archaeofauna l Accumulation h -gmented Forests i1 nd Anthropogenic L ndshy

scape Mos ics in the Tropical Lowlands of Prehispanic Ecuador Latill Allleriwn AIIshyliqll ihJ J 1241-257

2008 The Contributions f Zooarchaeology to [listo rical Ecology in the Neotropics QlIllten wry Internrll ivna I180S - 16

St ephens Davi d IN and John R Krebs 1986 Foraging Theory lrinceton nive rsity Prpss Pri nceton lew Jersey

Stiner M ry C 2001 Thirty Years o n the Broad Spectrum Revolution l nd Pltl leolithic Demograshy

phy Prace liirIgs ~f II le Natiolal Academy of Sciences 986993- 6996 Stiner Mary a talie D M u nro and rodd A Surovell

2000 The Tortoise and the Hd re Small-Gam e Use the Broad -Spectrum Revolution and Paleoli th ic Demog raphy Current Anthropology 4139- 73

Stine r Mary c l a tal ie D Munro Todd A Surovell Ettan Tchernov and O fer Bar-Yos f 1999 Pa leolith ic Pop ulatio n Crowth Pu lses Eviden ed by Small Anim al Exploitashy

tion Science 283 190- 194 Szute r hristine R and fran k E Bayh In

1989 Sedenlis m a nd Prehis tor ic Animal Procurement Among Desert Hort icu ltura lshyists ot the N orth American Sou thwes t In Farmers IS HLlI ltfrs The Implicatiolls of Sedshyenism ed ited by Susa n Ken t pp 80- 9 Ca mbridge Un iversity Press Cambri dge

Uga n Andrew 2005 Does Si ze Matter Body Size Mass Coli cting imd Their [mplica t i on~ for Unshy

ders tand ing Preh istoric F ra ging Behavior Amcrica l1 Alll iqldty 7075-~9 Wi nt rhalder Bruce and Er ic Alden Smith

2000 Analy zi ng A dn plive Slra teg ie~ Human Behavioral Fcology at rwenty-five Fvollilionary w thropology 951- 72

Winterhaldc l~ Bruce and Eric Alden Smith (ed itors) 1981 Hunter-Gatherer FO rll8ing Stralegie Ethnographic and Archeological Analyses

University of Chicago Press Chicago Wulverton Steve

2005 The Effects o f the H ypsitherma I on Prehistori ( ForJg ing EffiCiency in Missouri American Antiquity 709J- l06

Zar Jerrold H 1996 Biostatistical Analysis 3rd cd Prentice J la ll Upper SJddle Rive r ew J rsey

11

(

1

1 Ricks Stanf Lo argu middot tha lo be C0l1str

lhat the rna bu t also of more [argul of con truc the built n

The Arcwca og logica l Invest Ill inois Univel