Evaluating strategies for sustainable intensification of ......rates, and a tile drainage system...

Environmental Research Letters

LETTER bull OPEN ACCESS

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Environ Res Lett 13 (2018) 034031 httpsdoiorg1010881748-9326aaa779

LETTER

Evaluating strategies for sustainable intensification of USagriculture through the Long-Term AgroecosystemResearch network

S Spiegal122 B T Bestelmeyer1 D W Archer2 D J Augustine3 E H Boughton4 R K Boughton45 M ACavigelli6 P E Clark7 J D Derner3 E W Duncan8 C J Hapeman6 R D Harmel9 P Heilman10 M A Holly11D R Huggins12 K King8 P J A Kleinman11 M A Liebig2 M A Locke13 G W McCarty6 N Millar14 S BMirsky6 T B Moorman15 F B Pierson7 J R Rigby13 G P Robertson14 J L Steiner16 T C Strickland17 H MSwain4 B J Wienhold18 J D Wulfhorst1219 M A Yost20 and C L Walthall21

1 United States Department of AgriculturemdashAgricultural Research Service (USDA-ARS) Jornada Experimental Range Las Cruces NMUnited States of America

2 USDA-ARS Northern Great Plains Research Laboratory Mandan ND United States of America3 USDA-ARS Rangeland Resources and Systems Research Unit Fort Collins CO and Cheyenne WY United States of America4 Archbold Biological Station Venus FL United States of America5 University of Florida Range Cattle Research and Education Center Ona FL United States of America6 USDA-ARS Beltsville Agricultural Research Center Beltsville MD United States of America7 USDA-ARS Northwest Watershed Research Center Boise ID United States of America8 USDA-ARS Soil Drainage Research Unit Columbus OH United States of America9 USDA-ARS Texas Gulf Research Partnership Temple TX United States of America10 USDA-ARS Southwest Watershed Research Center Tucson AZ United States of America11 USDA-ARS Pasture Systems and Watershed Management Research Unit State College PA United States of America12 USDA-ARS Northwest Sustainable Agroecosystems Research Unit Pullman WA United States of America13 USDA-ARS National Sedimentation Laboratory Oxford MS United States of America14 Michigan State University WK Kellogg Biological Station and Department of Plant Soil and Microbial Sciences Hickory Corners MI

United States of America15 USDA-ARS National Laboratory for Agriculture and the Environment Ames IA United States of America16 USDA-ARS Grazingland Research Laboratory El Reno OK United States of America17 USDA-ARS Southeast Watershed Research Laboratory Tifton GA United States of America18 USDA-ARS Agroecosystem Management Research Unit Lincoln NE United States of America19 University of Idaho Department of Natural Resources and Society Moscow ID United States of America20 USDA-ARS Cropping Systems and Water Quality Research Unit Columbia MO USA now at Utah State University Logan UT

United States of America21 USDA-ARS Office of National Programs Beltsville MD United States of America22 Author to whom any correspondence should be addressed

OPEN ACCESS

RECEIVED

20 September 2017

REVISED

27 November 2017

ACCEPTED FOR PUBLICATION

15 January 2018

PUBLISHED

7 March 2018

Original content fromthis work may be usedunder the terms of theCreative CommonsAttribution 30 licence

Any further distributionof this work mustmaintain attribution tothe author(s) and thetitle of the work journalcitation and DOI

E-mail sherispiegalarsusdagov

Keywords agroecosystem management sustainable intensification of agriculture social-ecological systems long-term research network

Supplementary material for this article is available online

AbstractSustainable intensification is an emerging model for agriculture designed to reconcile acceleratingglobal demand for agricultural products with long-term environmental stewardship Defined here asincreasing agricultural production while maintaining or improving environmental qualitysustainable intensification hinges upon decision-making by agricultural producers consumers andpolicy-makers The Long-Term Agroecosystem Research (LTAR) network was established to informthese decisions Here we introduce the LTAR Common Experiment through which scientists andpartnering producers in US croplands rangelands and pasturelands are conducting 21 independentbut coordinated experiments Each local effort compares the outcomes of a predominantconventional production system in the region (lsquobusiness as usualrsquo) with a system hypothesized toadvance sustainable intensification (lsquoaspirationalrsquo) Following the logic of a conceptual model ofinteractions between agriculture economics society and the environment we identifiedcommonalities among the 21 experiments in terms of (a) concerns about business-as-usualproduction (b) lsquoaspirational outcomesrsquo motivating research into alternatives (c) strategies forachieving the outcomes (d) practices that support the strategies and (e) relationships between

copy 2018 The Author(s) Published by IOP Publishing Ltd

Environ Res Lett 13 (2018) 034031

practice outreach and adoption Network-wide concerns about business as usual include the costs ofinputs opportunities lost to uniform management approaches and vulnerability to acceleratingenvironmental changes Motivated by environmental economic and societal outcomes scientistsand partnering producers are investigating 15 practices in aspirational treatments to sustainablyintensify agriculture from crop diversification to ecological restoration Collectively the aspirationaltreatments reveal four general strategies for sustainable intensification (1) reducing reliance oninputs through ecological intensification (2) diversifying management to match land and economicpotential (3) building adaptive capacity to accelerating environmental changes and (4) managingagricultural landscapes for multiple ecosystem services Key to understanding the potential of thesepractices and strategies are informational economic and social factorsmdashand trade-offs amongthemmdashthat limit their adoption LTAR is evaluating several actions for overcoming these barriersincluding finding financial mechanisms to make aspirational production systems more profitableresolving uncertainties about trade-offs and building collaborative capacity among agriculturalproducers stakeholders and scientists from a broad range of disciplines

Introduction

The worldrsquos population is expected to increase byroughly two billion during the next thirty yearsand humanity is now facing the monumental chal-lenge of reducing hunger among the poor meetingthe dietary demands of a growing middle class andsustaining environmental quality all in the con-text of an increasingly variable climate (Godfrayet al 2010 Foley et al 2011 Alexandratos and Bruinsma2012) Sustainable intensificationmdashincreasing produc-tion while minimizing or reversing the adverse impactsof agriculturemdashhas emerged as a primary frameworkto meet this challenge (Godfray and Garnett 2014Petersen and Snapp 2015 Rockstrom et al 2016)

In the United States achieving sustainable intensi-fication is hampered by climate change entrenchednorms and market structures and the need fornew information technologies and infrastructure(Reganold et al 2011 Tilman et al 2011 Petersenand Snapp 2015) The US Long-Term Agroecosys-tem Research (LTAR) network was established in2014 to address these obstacles (Robertson et al2008 Walbridge and Shafer 2011 Kleinman et alin preparation) LTARrsquos 18 sites have researched var-ious aspects of sustainable intensification for decadesto over a century and represent a diversity of regionalagroecosystems nationwide (figure 1) These sites arenow embarking on a lsquocommon experimentrsquo encom-passing 21 independent but coordinated experimentslinked by common objectives and measurements (table1) Each local effort compares the outcomes of alocal predominant conventional production system(lsquobusiness as usualrsquo) with the outcomes of an alter-native production system hypothesized to advancesustainable intensification in locally appropriate ways(lsquoaspirationalrsquo)

The LTAR Common Experiment offers anunprecedented opportunity to gain local regional andnational insights into critical issues underlying the

sustainable intensification of US agriculture includ-ing the nature of problems to be solved as well asapproaches and key barriers to solving them As region-specific networked experimentation has recently beenidentified as a priority for sustainable intensificationat a global level (Rockstrom et al 2016 Reynoldset al 2017) experiences from the LTAR CommonExperiment can provide valuable lessons for effortsworldwide To introduce LTARrsquos approach we identifycommon themes that span the Common Experimentincluding concerns about business-as-usual produc-tion the strategies for sustainable intensification underinvestigation the practices that support the strate-gies and the factors that limit producersrsquo adoptionof those practices We also explore options for over-coming barriers to adoption focusing on areas wherethe current research portfolio could be expanded

Methods

The LTAR Common Experiment comprises 21 exper-iments in agricultural lands across the United States(figure 1 table 1) Currently measurements are tai-lored to compare the effects of business-as-usual andaspirational management at the plot field (pasture)and farm (ranch) scales alongside efforts to developopen-access databases (httpsltarnalusdagov) andmodeling to link measurements to inferences at thescales of watersheds regions industries and the nation(Walbridge 2013)

We used two web-based digital survey question-naires visual and tabular summaries of questionnairedata and group discussion about the summaries tosynthesize the multiple dimensions of the CommonExperiment into a common framework (figure 2)

Our synthesis was structured according to aconceptual model that identifies the interactions ofan agricultural production system suitable for a region(eg the business-as-usual or aspirational production

2


Figure 1 The Long-Term Agroecosystem Research networkrsquos Common Experiment is being conducted in croplands rangelandspasturelands and grazed croplands across the United States Gray polygons represent estimated regional inference spaces for the 18LTAR sites based on Major Land Resource Areas (USDA-NRCS 2006) and black icons represent the products under investigationin the regions Twenty-one experiments are being conducted by the 18 sites as three sites are each conducting two experiments intwo different agricultural land uses Black icons by Shutterstockcom artists HuHu iconizer K N NadzeyaShanchuk Hein NouwensOleg7799 VKA and VoodooDot

Figure 2 A synthesis framework containing five major elements of the Common Experiment (five boxes) with common themes sharedamong the 21 experiments within each element (lists in boxes)

3

EnvironR

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034031

Table 1 Summary of the 21 experiments in the LTAR Common Experiment lsquoMAP zonersquo refers to general zone of mean annual precipitation in the United States and lsquoLocationrsquo refers to US state and geographic coordinates of a primaryresearch site

Land use Experiment Location

MAP zone (mm)

Local concerns about business-as-usual production Business-as-usual treatment Aspirational treatment Practices under investigation

Crop

land

Central Mississippi River Basin

MO 3927degN 92121degW

900-1500

Agrochemical inefficiencies erosion water quality limited resilience to climate extremes

Cornsoybean rotation with annual aggressive tillage uniform rates of seed and agrochemicals no cover crops

Extended cornsoybeanwheat rotation with annual cover crops and no-till site-specific management of seed fertilizer and pesticides 4R nutrient stewardship

Cover cropsPrecision technologies Tillage management

Cook Agronomy Farm

WA46781degN 117082degW lt 600

Agrochemical inefficiencies erosion water quality nutrient losses from soils suboptimal C storage

3-year winter wheatspring wheatchickpea rotation with reduced tillage and uniform application of macronutrients

Same rotation with no-tillage and precision application of macronutrients

Precision technologies Tillage management

Eastern Corn Belt

OH40031degN 82973degW

900-1500

Water quality limited resilience to climate extremes Land use affecting Lake Erie and the Ohio River Valley

Corn-soybean with rotational tillage (tillage prior to corn) nutrient and pesticide application at agronomic rates and a tile drainage system that flows freely year-round

Introduction of wheat into cornsoybean rotation cover crops precision nutrient management no-till and drainage water management

Drainage managementPrecision technologies Tillage management

Kellogg Biological Station

MI 42405degN 85401degW

900-1500

Suboptimal crop production with seasonal drought Erosion water quality N emissions suboptimal C storage and biodiversity

Cornsoybean rotation conservation tillage with chisel plow nutrient and pest management with commercial crop adviser rates and GMO seeds and seed treatments

Cornsoybeanwheat rotation with winter cover crops Permanent no-till or narrow-row shallow strip tillage On-the-go-variable rate nutrient and pest management

Cover cropsPrecision technologiesTillage management

Lower Chesapeake Bay

MD 39039degN 76918degW

900-1500

Suboptimal crop production with seasonal drought Erosion water quality wetland conservation urban interface Land use affecting Chesapeake Bay

Cornsoybean rotation used for crop fields with surface-applied manures winter cover crop where subsidized Rotational no-till Conventional herbicide and N application Nutrient management plan required

Increase irrigated acreage and convert marginal land into conservation off-set programs Innovative cornsoybeanwheat rotations with high biomass cover crops no-till and precision agriculture (pest nutrients and water)


Lower Mississippi River Basin

MS 34366degN 89519degW

900-1500

Water competition insect weed pathogen pressures erosion suboptimal C storage water quality fish health

Wheatsoybeancotton rotation with no cover crops conventional tillage uniform nutrient application proactive herbicide and insecticide no edge of field buffer and conventional irrigation

Soybeancottonwheat-soybean rotation with cover crops post-harvest or as intercrop reduced tillage precision nutrient application IPM edge of field buffers and innovative irrigation

Cover cropsCrop diversificationIrrigation management

Platte RiverHigh Plains Aquifer (a)

NE40829degN 96667degW

600-899

Crop and forage production are limited by variable rainfall Heterogeneous soils complicate nutrient and water availability to crops

Maizesoybean rotation under rainfed or sprinkler irrigation Fields managed uniformly

Intensification through crop diversification and cover crops Precision irrigation and fertilization to manage spatial variation

Crop diversificationIrrigation managementPrecision technologies

4

EnvironR

esLett13

(2018)034031

Table 1 Continued

Experiment Location

MAP zone (mm)


Texas Gulf (a)

TX3152degN 969degW

600-899

Increasing production costs limited resilience to climate extremes water quality

Corn or haysmall grain rotation no cover crops conventional or conservation tillage traditional rates of inorganic N P

Corn or haysmall grain rotation with multispecies cover crop reduced or no-till poultry litter application and inorganic N and P application based on Haney test

Cover cropsManure managementTillage management

Upper Mississippi River Basin

IA 42172degN 93275degW

600-899

Glyphosate-resistant weeds soil compaction erosion Tile drainage affects runoff and Gulf of Mexico water quality

Cornsoybean rotation with tile drainage No cover crops chisel plow tillage annual N application for corn and glyphosate and insecticide as needed

Rotation of cornwinter camelina cover crop with soybeans overseeded Minimized tillage and fertilizer application Trifluralin and insecticide as needed Camelina oil seed for biofuel

Cover cropsCrop diversification

Pastu

relan

dGra

zed C

ropla

nd

Gulf Atlantic Coastal Plain

GA31457degN 83703degW

900-1500

Water competition insect weed pathogen pressures toxic dust emissions water quality suboptimal utilization of whole farm landscape

Cottoncottonpeanut rotation with ryeryerye cover crop conventional tillage nutrient pest and weed management linear move irrigation On-farm cow-calf production on marginal land andor crop residue with calves sold at weaning

Cottongrasspeanut rotation with rye+winter pea and rye cover crops rotated with a winter carinata cash crop Cow-calf production integrated into all portions of the farm landscape during twelve months of the year Biofuels

Cover cropsCrop diversificationGraze annual crops

NorthernPlains

ND46825degN 100888degW lt 600

Insect weed pathogen pressures limited resilience to climate extremes suboptimal C storage nutrient losses from soils

Spring wheatcornsoybean rotation with no-till or minimum-till no cover crop uniform nutrient application residue removal

Dynamic and adaptive annual crop rotation with no-till cover crops and precisionvariable nutrient and pesticide application Post-harvest livestock grazing of crop residue andor cover crops

Adaptive management planningCover cropsTillage management

Platte River High Plains Aquifer (b)


600-899

Beef cattle production systems limited by amount of pasture when rainfall is low Greenhouse gas emissions

Yearling steers with season-long grazing in dedicated pastures

Livestock grazing crop residue and cover crops Calving date changes Reduced time in feedlot

Grass-fed beef productionGraze annual cropsLivestock-landscape matching

Southern Plains (a)

OK34885degN 98023degW

600-899

Insect weed pathogen pressures erosion suboptimal soil C storage low primary productivity

Beef cattle stockers on continuous ldquograzeoutrdquo wheat with conventional tillage for weed control

4-year rotation of grain-only wheat dual-purpose wheat grazeout wheat canola with stocker grazing on 2 of 4 years of rotation No till IPM

Crop diversificationIntegrated pest managementTillage management

Texas Gulf (b)

TX3152degN 969degW

600-899

Suboptimal forage production water quality soil quality

Beef cattle on grazing oats pasture cultivated with tillage and inorganic fertilizers Hay in winter Separate herds with best pasture grazing

Beef cattle on overseeded multi-species pasture Cattle intentionally rotated through pasture and cultivated paddocks

Cover cropsGraze annual crops Rotational grazing

Upper Chesapeake Bay

PA40861degN 77763degW

900-1500

High input intensity (fertilizer pesticides energy) erosion water quality air pollutionenterprise solvency and profitability

Dairy cattle on pasture with alfalfa and silage corn Imported fertilizers pesticides and fuels Conventional pest management Ineffective application of manure from on-farm CAFO Minimal-management grazing

Dairy cattle on diversified forage rotation with perennial grasses (biofuels) Precision nutrient management Whole-farm integration IPM Energy independence Conservation tillage

Cover cropsGraze annual cropsManure management

5

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034031

Table 1 Continued


MAP zone (mm)


Rang

eland

Archbold Biological Station University of Florida

FL27183degN 81351degW

900-1500

Suboptimal forage production and utilization biodiversity and carbon storage Land use affecting Everglades

Cattle production with long rotation grazing and low-rate N fertilization on improved pastures during wet season Long rotation grazing and Rx burns during dry season on semi-native and native range

Cattle production with intensive rotation and fertilization on improved pastures during wet season Low intensity rotation on semi-native and native range during dry season with patch burning or Rx burning during wetmdashdry transition season

Prescribed burningRotational grazing

Central Plains Experimental Range

CO40842degN 104716degW lt 600

Suboptimal forage production and utilization biodiversity Drought

Stocker production on shortgrass steppe with May-Oct grazing (during the late spring and summer) at moderate stocking rates

Stocker production on shortgrass steppe with collaborative adaptive rangeland management including pulse grazing flexible stocking rate and patch burning options

Adaptive management planningPrescribed burningRotational grazing

Great Basin

ID 4321degN 11675degW lt 600

Cheatgrass invasion of sagebrush bunchgrass rangeland altered grass-fire cycle

Inflexible grazing use policies on public lands Traditional cheatgrass treatments

Management of public lands is adaptive to fire-cheatgrass cycle Novel sagebrush-steppe restoration

Adaptive management planningRangeland restoration

Jornada Experimental Range

NM32029degN 10659degW lt 600

Shrub dominance perennial grass loss drought increasing aridity Localized overgrazing can accelerate grass and soil losses Options for localagriculture are diminishing

Cow-calf productionwith British breeds (Anguscrossbreds) and grain finishing inwestern OK and TX

More options for agricultural production on rangelands including cow-calf production with heritage Raramuri Criollo cattle with grass-finishing cross-breeding and ropingcattle options Brush managementand range seeding

Grass-fed beef productionLivestock-landscape matchingRangeland restoration

Southern Plains (b)


600-899

Suboptimal forage production and utilization on native tall grass prairie

Conventional cow-calf production Treatment on native tall grass prairie with continuous grazing

Cow-calf production with livestock size matched to environment and rotational grazing Treatment on native tall grass prairie

Adaptive management planningLivestock-landscape matchingRotational grazing

Walnut Gulch Experimental Watershed

AZ31711degN 110064degW lt 600

Long term expansion of velvet mesquite and associated loss of NPP perennial grasses and biodiversity with accelerated erosion

Velvet mesquite allowed to increase to its natural limits

Velvet mesquite treated with aerially-applied herbicides Rangeland restoration

6


Natural capital tourism

Consumer choice behavior peer network amp perceptions

Management effects

ENVIRONMENT

ECONOMY

PRODUCTION SYSTEM

Profitability

Ecological feedbacks

SOCIETY

Rural opportunity

Human health non-commodity

ecosystem services

PRODUCERS

Decisions inputs

management

GOVERNMENTPOLICY

Assistance incentives regulations

Politics

PERTURBATIONSWeather extremes invasive species amp disease outbreaks

global market shifts

SCIENCE SUPPORTInformation

Supplydemand

Stakeholder participation

Figure 3 Conceptual model of interactions among agriculture environment economy and society (cf Fox et al 2009 Lescourretet al 2015 DeClerck et al 2016 Moraine et al 2017) used to frame our questionnaires and synthesize the multiple dimensions of theLTAR Common Experiment into a common framework (figure 2) The model centers on agricultural producers and their decision-making about selecting a production system (ie suite of management strategies and practices) suitable for a given agricultural regionFeedback loops mediated by profitability environmental effects societal factors and policies can reinforce the status quo or promptproducers to adopt an alternative production system External shocks (drivers and perturbations that are unaffected by feedbacks)can tip the entire system into alternative states (Walker and Meyers 2004) For decision-making producers integrate knowledge ofprofit potential government policies and social interactions along with science-based information from universities extension andproducer organizations (Rodriguez et al 2008 Lubell et al 2014) The nature quality and availability of scientific information are inturn influenced through participatory science with producers and other stakeholders (Neef and Neubert 2011) With their integratedinsights producers select the parts of the agricultural land mosaic under their management to be used for production or for otherfunctions such as wildlife habitat or watershed management These site-level management decisions affect environmental conditions atthe farmranch and landscape levels which feed back to the production system (and ultimately profitability) via for example long-termchanges in soil quality or pollinator biodiversity (Swain et al 2013 Brown and Havstad 2016 Rockstrom et al 2016) Environmentalconditions produced by agricultural decisions also affect human health (eg dust emissions) and the production of non-commodityecosystem services (eg waste treatment scenic beauty) The environment influences the economy through opportunities for eco-andagro-tourism (Nickerson et al 2001) and natural capital stocks of natural resources that yield ecosystem goods and services now andinto the future (Costanza and Daly 1992) The production system affects the economy through the balance of supply and demand ofagricultural commodities In turn the economy including its transportation agricultural infrastructures and pricing for agriculturalinputs affects the chances that producers will turn a profit (Chandra and Thompson 2000) The health of the local economy also affectsthe local rural community because lack of opportunities can lead to poverty impermanence and eventual outmigration (Ratcliffeet al 2016 Parry and Skaggs 2014 Cohen et al 2015) Perceptions of peers in the community and trends in consumer choice behaviorcan affect producersrsquo management planning as well as their economic bottom lines Societies influence government policies at all levelsthrough the political process Although the power of rural communities to shape policy varies (Lichter and Brown 2011) agriculturaland environmental policies directly affect producers via price supports regulations and compensation for non-commodity ecosystemservices (Reganold et al 2011)

system) with the environment economy societygovernment policy and science support (figure 3)The model focuses on how these interactions affectproducersrsquo decisions to adopt (or maintain) business-as-usual or aspirational production systems

Survey design and data collectionWe designed a survey to develop a network-wideperspective on the Common Experiment using theconceptual model (figure 3) as an organizing frame-work Given the relatively small size of the network acomprehensive census approach (ie surveying all net-work sites) was possible (Salant and Dillman 1994)The survey included two questionnaires administeredby the two lead authors on behalf of the networkScientists from all 18 LTAR sites reviewed their pub-lished studies (httpsdatanalusdagovpublicationsltar) and site-based knowledge to develop one response

per experiment for each of the questionnaires Pri-mary respondents from each site are also authors ofthis article

Through the lsquoCoordination Questionnairersquo (sup-plement 1 available at stacksioporgERL13034031mmedia) administered November 2015mdashOctober2016 scientists described their study designs theirconcerns about the business-as-usual production sys-tems they are evaluating and hypotheses about howtheir aspirational systems can address those concernsQuestions about concerns and hypotheses were open-ended but structured by ecosystem service categories(de Groot et al 2010) to elicit responses in termsof relationships between the focal production sys-tem and other components of the conceptual model(figure 3) provisioning services corresponded withthe economy regulating and supporting services withthe environment and cultural services with society

7


Twenty-two concerns about business as usualwere coded from the qualitative responses to theCoordination Questionnaire and presence (1) orabsence (0) of each concern for each experimentwas tabulated (supplement 2) In October 2016 wegenerated an ordination of the experiments basedon the tabulated data Surprisingly experiments dis-similar in land use and geography clustered inordination space (supplement 3) revealing that con-cerns about business-as-usual production transcendedland use and geography We used the classificationof business-as-usual concerns to design a secondquestionnaire focused on aspirational outcomes thatdirectly address those concerns With the secondquestionnaire we sought to gain precision on theaspirational outcomes described qualitatively throughthe Coordination Questionnaire and to identifypotential barriers to those outcomes Accordinglythe lsquoAspirations Questionnairersquo (supplement 3) usedclosed-ended responses to provide clear links betweenbusiness-as-usual concerns aspirations and barriersBecause they proved uninformative ecosystem ser-vice categories used in the Coordination Questionnairewere omitted from the second questionnaire and syn-thesis

The Aspirations Questionnaire was administeredJanuarymdashFebruary 2017 In a multiple-choice ques-tion respondents selected from among 23 lsquoaspirationaloutcomesrsquo coded from qualitative responses to theCoordination Questionnaire (supplement 4) Theoutcomes were specific objectives of aspirational pro-duction approaches which if met would help achievethe primary goal of sustainable intensification Thenthrough a multi-part question scientists listed the threemain practices in their aspirational treatments and foreach practice rated its level of existing outreach byCooperative Extension and other groups (1 = noneto minimal 5 = extensive) rated its current level ofadoption by producers (same scale) and provided ashort response explaining discrepancies between thetwo ratings Respondents were encouraged to framediscrepancies in terms of relationships between theproduction system and other components in the con-ceptual model (figure 3) This question elicited 61unique practice entries two to three per experiment(supplement 5) Adoption was rated less than or equalto outreach for 58 of the 61 practice entries Shortresponses were given for 47 of the 58 entries 31 casesin which adoption was rated lower than outreach and16 cases in which the two ratings were equal Due tothe instructions given in the questionnaire and thenature of the responses we considered all 47 shortresponses to be explanations for why practice adoptionlags behind outreach Nineteen reasons for the lag werecoded from the 47 explanations and presence (1) orabsence (0) of each reason was tabulated for the 47practice entries (supplement 5) Next fifteen practiceswere coded from the 61 practice entries Each practicecode was assigned one rating for outreach and one for

adoption by averaging ratings across practice entrieswith the code (supplement 5 and 6) Presence (1) orabsence (0) of the 19 reasons that adoption lags behindoutreach were tabulated for each practice code

Coding and tabulation of qualitative survey datawere performed using basic descriptive and thematiccoding methods per Saldana (2016)

Synthesis processIn FebruarymdashAugust 2017 co-authors analyzed iter-ative versions of tabular and graphical summariesof survey results via in-person and virtual meetingsGraphics were created using data available in sup-plementary materials with the ggplot package in Rversion 325 (Wickham 2009 R Core DevelopmentTeam 2015)

We identified common concerns about business-as-usual production by categorizing the 22 concernsused in the ordination into broader themes (supple-ment 2)The23aspirational outcomeswere categorizedinto themes (supplement 4) corresponding with theconceptual model (figure 3) and primary goals forLTAR and sustainable agriculture (National ResearchCouncil 2010 Kleinman et al in review)

The 15 practice codes (hereafter lsquopracticesrsquo) werecategorized into practice types (supplement 5) perUSDA-NRCS conservationpractice standards (USDA-NRCS 2017) and LTAR site publications Practicesapplied mainly to lands used for crops andor forageswere categorized as lsquocropland managementrsquo practicesPractices applied mostly to lands grazed by live-stock were categorized as lsquograzingland managementrsquopractices Practices applied less directly to land andmore directly to management of the overall microe-conomics of the farm or ranch operation werecategorizedas lsquoenterprisemanagementrsquo practices (sensuLowrance et al 1986)

We identified general strategies for sustainableintensification that emerged from the 21 aspirationaltreatments by assimilating the intentions of the 15practices the aspirational outcomes motivating LTARresearch and general literature cited in this paper

To identify common reasons that adoption lagsbehind outreach we categorized the reasons presentfor six or more practices into broader themes We alsoanalyzed how ratings and reasons varied with practicetype (supplement 5)

Results

Our synthesis revealed that scientists across the LTARnetwork share common concerns about business-as-usual production which resolved into three broadthemes (figure 2) In response to those concerns sci-entists are motivated by aspirational outcomes in theenvironment economy and society (figure 2) withsocietal outcomes currently emphasized less overall(figure 4)

8


Figure 4 Scientists selected from among 23 lsquoaspirational outcomesrsquo in a multiple-choice question in the Aspirations QuestionnaireBars represent frequency of selections across all experiments (supplement 4) Outcomes were categorized into themes correspondingwith figure 3 and goals documented for LTAR and sustainable agriculture

Four general strategies for sustainable intensifica-tion emerged across the aspirational treatments (figure2) Most of the 15 practices are multifunctional in thatthey contribute to each strategy

The 15 practices that support the strategies splitevenly into three practice types (figure 2) but the typesdid not sort perfectly with the Common Experimentrsquosthree agricultural land uses For instance tillage man-agement a lsquocropland managementrsquo practice is underinvestigation in both pasturelandsgrazed croplandsand croplands (table 1)

Overall the scientists perceived adoption laggingbehind outreach for all practices except adaptive man-agement planning and adoption generally increasingwith outreach (figure 5)

Reasons that adoption lags behind outreach whichwere present for six or more practices resolved intobroad themes of costs information deficits and socialnorms (figure 2 figure 6)

Cropland management practices were generallyrated highly for outreach (figure 5) and additionalcosts were regularly invoked to describe why adop-tion trails outreach (figure 6) Enterprise managementpractices were rated variably for outreach and adoption(figure 5) Again reasons related to costs were used toexplain discrepancies between the two ratings (figure6) Three of the five grazingland management practiceswere rated relatively low for outreach and adoption(figure 5) with social norms and information deficitsinvoked to explain the ratings (figure 6) Althoughnot captured graphically trade-offs among economicsocial and environmental outcomes of practice imple-mentation were also frequently mentioned during the

synthesis process as important influences on practiceadoption (also see Rodriguez et al 2008 Lubell et al2011)

Discussion

Network-wide concerns about business-as-usualproduction1 Costs of inputsThe economic and environmental costs of the fertiliz-ers fossil fuels and infrastructure in business-as-usualagricultural production are well documented for theUnited States and other countries (eg Matson et al1997 Tilman et al 2002) These costs are primaryconcerns for scientists across the network

Through the survey scientists in croplands andpasturelands conveyed concerns about soil erosionand water quality resulting from agronomic inputsespecially as management in LTAR regions affects sev-eral water bodies of national significance includingthe Florida Everglades Chesapeake Bay Lake Eriethe Mississippi River and the Columbia River Basin(figure 1 table 1) Significant economic costs werealso noted Since 2012 for instance for five com-modities under wide investigation in the CommonExperimentmdashcorn soybeans wheat cotton andpeanutsmdashfertilizerpurchases represented18ndash42ofoperating costs (USDA-ERS 2017)

LTARrsquos rangeland scientists expressed concernsabout suboptimal forage production suboptimal for-age utilization by beef cattle or both (table 1)Supplemental feeding represents on average 20 of

9


Figure 5 Rating for adoption plotted against rating for outreach (1 = none to minimal 5 = extensive) for 15 practices in the aspirationaltreatments Values represent the average of ratings submitted via the Aspirations Questionnaire (see methods supplement 5) Summarystatistics by practice and practice type are available in supplement 6

Figure 6 Reasons that adoption lags behind outreach for practices in the aspirational treatments Reasons shown here were presentfor at least six of the 15 practices coded via the Aspirations Questionnaire (see methods supplement 5) Broader themes identifiedthrough the synthesis process (figure 2) are noted in the brackets Black boxes demonstrate patterns revealed by evaluating the reasonsby practice type

the total operating costs for cow-calf operations in therangelands of the western United States (USDA-ERS2017) Increased feed input costs due to suboptimalforage production or consumption can present signif-icant economic hardships for ranchers (Holechek andHerbel 1986)

2Costsof specialization concentrationanduniformland managementScientists network-wide expressed concerns about howbusiness as usual seeks to overcome the inherent bio-physical and socioeconomic variability of agriculturallands instead of capitalizing on that variability to

10


produce diverse suites of agricultural products andother ecosystem services

During the past century US farming systemshave become increasingly specialized such that thenumber of commodities produced per operation hasdeclined and concentrated such that fewer farms areproducing the nationrsquos overall supply (Dimitri et al2005 Hendrickson et al 2008) LTARrsquos croplandand pastureland scientists expressed concern that thedecoupling of crop and livestock production has ledto broken nutrient cycles and missed opportunities forportfolio diversification (Sharpley et al 2016 Liebig etal 2017) Further they acknowledged that the tendencytoward uniform agronomic management at the fieldscale has come at a cost of flexible location-specificmanagement resulting in negative impacts to waterand air resources soil health and even profit

LTARrsquos rangeland scientists appreciate that ranch-ers have always needed to adjust their management tocope with the intrinsic climatic variability of range-lands however concern was expressed about trendstoward uniform styles of range and ranch man-agement Scientists from central Florida noted thatfixed burning schedules can lead to suboptimal for-age production and reductions in biodiversity in theirregion (Boughton et al 2013) In the Central Plainsmaintaining set stocking rates and pasture rest sched-ules based on calendarsmdashwithout adaptively changingplans based on current forage conditions and weatherpredictionsmdashmay reduce opportunities for match-ing forage availability with animal demand (Dernerand Augustine 2016) Further business as usual haschampioned livestock breeds that provide a uniformproduct for the beef supply chain but those breedscan fail to capitalize on variable pasture resources inthe American Southwest and Southern Plains espe-cially during drought (Anderson et al 2015 Scasta et al2016) Across all rangeland systems it was acknowl-edged that a mismatch of livestock type or managementstyle with the inherent heterogeneity of the landscapecan result in undesirable effects on production vegeta-tion soils and biodiversity3 Vulnerability to accelerating environmentalchangesAfter decades of achievements in overcoming tem-porally variable threats to production producers inLTAR regions and across the world are facing rapidlyaccelerating changes in climate pest and disease pat-terns (Lin 2011 Lipper et al 2014 Marshall et al2014) Drought flooding and record high tempera-tures have increased in frequency and intensity andreductions in global maize and wheat yields havealready been attributed to these climatic changes(Lobell et al 2011) Simultaneously pest weed andpathogen resistance can exacerbate vulnerability tomounting climatic variability LTAR scientists acrossthe network expressed concern about the vulnerabil-ity of business-as-usual production systems to theseaccelerating environmental changes

General strategies supported by 15 practices toachieve aspirational outcomesIn response to their concerns about business-as-usualproduction LTAR scientists are working with farm-ers ranchers and other agricultural stakeholders toevaluate alternatives Collectively the 21 aspirationaltreatments (table 1) reveal four general strategiesdesigned to achieve the networkrsquos aspirations (figure 4)to advance sustainable intensification Practices underinvestigation are multifunctional in that they supportmultiple strategies1 Reducing reliance on inputs through ecologicalintensificationAll of LTARrsquos aspirational treatments are exploringecological intensification bolstering internal processesmechanisms and functions that directly or indirectlycontribute to agricultural production to reduce relianceonexternal inputs (RobertsonandSwinton2005Bom-marco et al 2013) Production can be ecologicallyintensified by enhancing soil fertility pollination bio-controls genetic diversity and nutrient cycling (Power2010 Rockstrom et al 2016) and most of the 15practices under investigation are designed to pro-mote such processes and functions Broad networkinterest in ecological intensification is reflected in auniversal commitment to maintaining and enhanc-ing soil quality and health (figure 4 Doran 2002Govers et al 2017)2 Diversifying management to match land and eco-nomic potentialMost network locations are working to increase agri-cultural production and profitability (figure 4) anddiversifying management is a prevalent strategy forachieving these outcomes sustainably Tailoring man-agement to match the spatial heterogeneity of soils andtemporal variability of rainfall is under wide investi-gation with crop diversification livestock-landscapematching precision management and adaptive man-agement as examples of practices supporting theapproach (Herrick et al 2013 Derner and Augustine2016) Further several practices promote the integra-tion of enterprises within and between regions forsynergistic exchanges of resources (eg graze annualcrops manure management)mdashan approach increas-ingly recognized for its potential to advance sustainableintensification in the United States (Steiner and Fran-zluebbers 2009 Fedoroff et al 2010 Liebig et al 2017)3 Building adaptive capacity to accelerating environ-mental changesLTAR was conceived in part to help farmers andranchers adapt to increasing variability in climate andrelated challenges associated with pests diseases andinvasive species (Walbridge and Shafer 2011) and thisemphasis was reflected in the survey All 15 practicesserve to build adaptive capacity in some manner Withan eye toward minimizing adverse impacts of agri-culture on climate change most experiments are alsocomparing greenhouse gas dynamics of their business-as-usual and aspirational treatments

11


4 Managing agricultural landscapes for multipleecosystem servicesThe ability to sustainably intensify agriculture dependslargelyonthenon-commodity ecosystemservicesavail-able for agricultural use now and into the future(Power 2010 DeClerck et al 2016) Two general mod-els have emerged for sustaining necessary ecosystemservices while increasing productivity in agriculturallandscapes (Fischer et al 2008 Phalan et al 2011)One model lsquoland sparingrsquo calls for designating someparcels for more intensive agricultural use while settingaside others as reserves for biodiversity maintenanceand other related services The other lsquoland sharingrsquoemphasizes managing landscapes for both conserva-tion and production outcomes allowing for expansionof less intensive agricultural land uses depending onthe situation (sensu Godfray and Garnett 2014) Asthe multifunctionality of agricultural lands is implicitin the agroecosystem concept (Altieri 2002) most ofLTARrsquos aspirational systems are best described as lsquolandsharingrsquo strategies overall the focus is less on regionalland use planning and more on addressing how prac-tices and overall management can protect and enhanceecosystem services on farms and ranches and the landsthat surround them

Overcoming barriers to adoptionmdashnew directionsfor sustainability researchGiven the potential of the practices in the CommonExperiment to advance strategies for sustainable inten-sification it is important to ask why their adoption lagsbehind outreach (figure 5) LTAR scientists explainedthe lag as a function of costs information deficitsand social norms (sensu figure 3) with the relativeinfluence of these factors differing between practicetypes (figure 6) Trade-offs among environmental eco-nomic and social impacts of the practices were alsoidentified as key issues influencing practice adoptionThe development of strategies to overcome barriersto adoption of new practices constitutes a primarychallenge for LTAR and other sustainability scienceinstitutions1 CostsLTAR scientists generally consider cropland manage-ment practices to be widely promoted (figure 5) butlagging in adoption due to added costs (figure 6)Cover crops provide an instructive example Inter-mittent cover crops can increase nutrient retentionbetween cash crops thereby lowering economic (andenvironmental) costs of fertilizers (Doran and Smith1991 Meisinger et al 1991 Snapp et al 2005) How-ever extra labor seed and equipment requirementscan increase costs by 2ndash4 (Schnitkey et al 2016)Therefore savings in fertilizer may be negated byadded costs for management Arguably past researchidentifying certain benefits of cover crops has war-ranted extensive outreach about the practice howevernew knowledge about how to reduce costs for covercrop management is needed now

Similarly LTARrsquos enterprise management prac-tices are increasingly recognized for certain benefits forsustainable intensification (Tilman et al 2002 Liebiget al 2017) but barriers to their adoption include costsrelated to regional processing and marketing (figure6) Products from all of LTARrsquos aspirational systemscan be considered lsquosustainablersquo lsquogreen or lsquonaturalrsquobut a mismatch between niche products and exist-ing processing and marketing mechanisms can preventproducers from achieving acceptable profits (Johnsonet al 2012) Producer cooperatives may help overcomethis barrier by filling processing gaps and advancingmarketing opportunities though economies of scale(Gwin 2009) Depending on LTAR research resultsproducers adopting aspirational production systemsmay consider collectively marketing the potential oftheir products to sustain a variety of ecosystem servicesIn addition many major food companies and non-governmental organizations are working to developlinkages with producers to improve agricultural sus-tainability (eg Maia de Souza et al 2017 Thomson et al2017) LTAR may facilitate coordination of marketingcooperatives and corporate-NGO-producer partner-ships with added benefits of strengthening ties amongstakeholders and expanding networked experimentalresearch into the food system beyond farm and ranchgates (Macfadyen et al 2015)

While our synthesis suggests that added costsare primary considerations for producers consider-ing adoption of cropland and enterprise managementpractices net income from all agricultural productionis generally low compared with other US professions(Fayer 2014) Accordingly added costs and financialrisks are key considerations for all producers (Tanakaet al 2011) Monetary assistance and incentives canhelp mitigate risks of adopting new practices (figure3 Tanaka et al 2011 Boll et al 2015) Nonethelessas exemplified by producers canceling USDA Con-servation Reserve Program contracts when the priceof corn increases (Kleinman et al in preparation)assistance and incentives for conservation-orientedpractices are not yet consistently attractive or effectiveThese mechanisms may be improved by quantifyingthe monetary value of ecosystem services providedby business-as-usual versus aspirational management(Robertson and Swinton 2005 Brown and Havs-tad 2016) Such an accounting may help to ensureenvironmental economic and social equity amongregions of the United States as the nation transitionsto a new paradigm of sustainable intensification (Looset al 2014 Robinson et al 2015) Further equity withinregions could be better understood through such anaccounting Most agricultural production takes placein rural areas yet all Americansmdashurban and ruralmdashconsume the multiple ecosystem services provided byrural agricultural lands and the farmers and ranchersthat tend them(Huntsinger andOviedo2014)Decadesof out-migration have resulted in lt20 of the USpopulation residing in rural areas (Ratcliffe et al 2016

12


Cohenet al2015)Asaconsequence citieshave increas-ingly become the centers of wealth while rural areashave remained relatively impoverished (USDA-ERS2015) In addition compared with urban areas ruralareas are at greater risk for economic losses due toclimate change (Hsiang et al 2017) In light of thesedisparities the flow of benefits from rural to urbanareas should be quantified and ways to adequatelycompensate rural producers for food productionand other ecosystem services should be considered(sensu Gutman 2007)2 Information deficitsInformation deficits were frequently mentioned byLTAR scientists explaining the low outreach andadoption of grazingland management practices underinvestigation (figures 5 and 6 supplement 5) Theseobservations might suggest that more basic researchabout potential benefits of these practices is neededbefore they can be widely recommended through out-reach For example three experiments are evaluatingthe use of beef cattle that are postulated to be well-adapted to their local environments through smallerbody sizes earlier calving dates or heritage genet-ics (table 1) While this approach is hypothesized tolower supplemental feed costs in the Southwest (Estellet al 2012) and reduce enteric methane productionin the pasturelands of the Great Plains (Neel et al2016) profitability may be compromised because thecurrent beef cattle industry favors large and uniformbody size at predictable times of the year (Scasta et al2016) Such predictions about trade-offs between envi-ronmental quality and profitability are plausible butas they have not yet been confirmed more basicresearch is needed including in the area of ecosystemservice provision

As discussed above policy mechanisms to incen-tivizeadoptionof aspirationalmanagement approachesmay be improved through ecosystem service valuationbut the accurate assessment of these values repre-sents a critical information deficit Spatially-explicitmodels that estimate service provision under differentscenarios (eg Integrated Valuation of Ecosystem Ser-vices and Tradeoffs lsquoInVESTrsquo Artificial Intelligencefor Ecosystem Services lsquoARIESrsquo) could be especiallyuseful for comparing the effects of management underaspirational versus business-as-usual paradigms as landuses and water availability change into the futureScenario modeling could improve understanding oftrade-offs among environmental economic and socialeffects of management under the two managementscenarios (Nelson et al 2009)mdashknowledge identifiedas critical during our synthesis process Further suchscenario modeling holds promise for extrapolatingCommon Experiment measurements to broader scalesof agricultural organization However for such pre-dictions to inform incentivization policies effectivelyit will be imperative to quantify the uncertainty aris-ing from extrapolating measurements across spatialand temporal scales and ecosystem service recipients

(Hein et al 2006) With its significant spatial coverageand long-term trajectory LTAR is in a unique posi-tion to partner with the modeling community to tacklethese issues and even help to improve existing modelsSynergistically such modeling could help to unify howscientists across LTAR conceptualize ecosystem ser-vice flows which could result in improved aspirationaltreatments as the Common Experiment evolves

For any new information produced throughmodeling or other research efforts effectively com-municating that information will be key to advancingsustainable intensification LTAR is poised to inte-grate voices from multiple disciplines to craft effectivecommunication strategies for multiple sectors of agri-cultural stakeholdersForproducers trustworthinessofthe source communicating information is paramount(Lubell et al 2014) and accordingly LTAR is build-ing on the strong tradition of the USDA AgriculturalResearch Service and other agricultural research orga-nizations to conduct research in a participatory mannerto maintain transparency and credibility Increasinglythroughemergingcitizen science andopen science plat-forms producers and other stakeholders can engagein research directly thereby expanding the interactiverelationships between science support and producers(figure 3 Newman et al 2012 Herrick et al 2013)In addition the USDA Climate Hubs are key part-ners for disseminating research results with trustedconnections with Cooperative Extension at land-grantuniversities andaproventrack recordofproviding toolsto help agricultural operations adapt to environmen-tal changes (Elias et al 2017) To communicate withagricultural consumers at large LTAR and other sus-tainability science institutions might consider locallyappropriate innovative technologiesmdashsuch as soft-ware applications or lsquoappsrsquo (Pitt et al 2011) andinteractive displays inpublic spaces (Antle et al2011)mdashthat may improve overall agricultural literacy andultimately inform consumer choices a primary influ-ence on producer decision-making (figure 3)3 Social normsImportantly even if research reveals that LTARrsquosaspirational systems are optimal for production prof-itability and environmental quality social norms couldprevent their widespread adoption (figure 3) Forinstance even if LTAR research demonstrates thatusing new livestock types can increase profitability andreduce impact to a given environment longstandingnorms tied to producer experiences and traditional useof particular breeds and sizes may prevail and ulti-mately prevent widespread adoption of the new types(Didier and Brunson 2004 Rodriguez et al 2008)Extending the Common Experiment questionnairesto producers could help illuminate how social normsand other factors such as social networks influenceadoption of practices under investigation (Lubell et al2013) Further social networking technologies mayhelp improve understanding of the interaction betweenpublic opinion and adoption of new practices and

13


approaches (eg Barry 2014) Overall understandingthe influence of social factors on practice adoptionand sustainable intensification will require increasedtwo-way collaboration and coordination among pro-ducers agricultural stakeholders and scientists from adiversity of disciplines (Lubell et al 2013)

Conclusion

The common experiment of the LTAR networkseeks to produce new knowledge of agroecosystemfunctions and to understand how aspirational produc-tion systems may advance sustainable intensificationin different regions of the United States Networkinteractions can make research and discovery moreefficientmdashseveral common themes emerge among the21 local experiments and working groups focusedon these themes are likely to speed progress towardgenerally-applicable strategies and solutions (Carpen-ter et al 2009) Because the nature of sustainabilitychallenges and innovations will evolve over timeand because our understanding of agroecosystemswill also evolve with new technologies models anddecision support tools such efforts require long-term research investments Importantly investmenttoward adding new sites to the network will alsobe needed to fill gaps in our knowledge of regionalagroecosystems

One of the most important and least researchedchallenges for LTAR and other sustainability sci-ence networks is understanding how to overcomebarriers to adoption of new practices Partnershipsamong producers policymakers industry and sci-entists should be strengthened to ensure that themerits of promising approaches are widely understoodThese partnerships should also help LTAR researchersdesign approaches and communication strategies thatare matched to local contexts and that accountfor the complex relationships between ecologyeconomics and society US LTAR and other long-term agroecosystem research networks will proveinvaluable in our collective understanding of thesecomplexities

Acknowledgments

We are grateful to all participants in the Long-TermAgroecosystem Research network who are work-ing together to evaluate strategies for sustainableintensification We thank Kris M Havstad for hisvisionary leadership of the LTAR Common Experi-ment JDD and DJA were supported by USDA ARFIgrant no 2012-38415-20328 and DRH and JDW weresupported through USDA NIFA Award no 2011-68002-30191 Discussions with Nicholas P Webb andcomments from Stephen K Hamilton and two anony-mous reviewers led to significant improvements in themanuscript

ORCID iDs

S Spiegal httpsorcidorg0000-0002-5489-9512B T Bestelmeyer httpsorcidorg0000-0001-5060-9955G P Robertson httpsorcidorg0000-0001-9771-9895

References

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Anderson D M Estell R E Gonzalez A L Cibils A F and Torell L A2015 Criollo cattle heritage genetics for arid landscapesRangelands 37 62ndash7

Antle A N et al 2011 Balancing act enabling public engagementwith sustainability issues through a multi-touch tabletopcollaborative game IFIP Conference on Human-ComputerInteraction ed P Campos et al (Lisbon Springer)pp 194ndash211

Barry S J 2014 Using social media to discover public valuesinterests and perceptions about cattle grazing on park landsEnviron Manage 53 454ndash64

Boll J Steenhuis T S Brooks E S Kurkalova L A Rittenburg R ASquires A L Vellidis G Easton Z M and Wulfhorst J D 2015Featured collection introduction synthesis and analysis ofconservation effects assessment projects for improved waterquality J Am Water Resour Assoc 51 302ndash4

Bommarco R Kleijn D and Potts S G 2013 Ecologicalintensification harnessing ecosystem services for food securityTrends Ecol Evol 28 230ndash8

Boughton E H Bohlen P J and Steele C 2013 Season of fire andnutrient enrichment affect plant community dynamics insubtropical semi-natural grasslands released from agricultureBiol Conserv 158 239ndash47

Brown J R and Havstad K M 2016 Using ecological site informationto improve landscape management for ecosystem servicesRangelands 38 318ndash21

Carpenter S R et al 2009 Accelerate synthesis in ecology andenvironmental sciences BioScience 59 699ndash701

Chandra A and Thompson E 2000 Does public infrastructure affecteconomic activity Evidence from the rural interstate highwaysystem Reg Sci Urban Econ 30 457ndash90

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Costanza R and Daly H E 1992 Natural capital and sustainabledevelopment Conserv Biol 6 37ndash46

DeClerck F et al 2016 Agricultural ecosystems and their servicesthe vanguard of sustainability Curr Opin Environ Sustain23 92ndash9

de Groot R S Alkemade R Braat L Hein L and Willemen L 2010Challenges in integrating the concept of ecosystem servicesand values in landscape planning management and decisionmaking Ecol Complexity 7 260ndash72

Derner J D and Augustine D J 2016 Adaptive management fordrought on rangelands Rangelands 38 211ndash5

Didier E A and Brunson M W 2004 Adoption of rangemanagement innovations by Utah ranchers Rangeland EcolManage 57 330ndash6

Dimitri C Effland A B and Conklin N C 2005 The 20th CenturyTransformation of US Agriculture and Farm Policy(Washington DC United States Department ofAgriculturemdashEconomic Research Service)

Doran J W 2002 Soil health and global sustainability translatingscience into practice Agric Ecosyst Environ 88 119ndash27

14


Doran J W et al 1991 Role of Cover Crops in Nitrogen CyclingProceedings of the Soil and Water Conservation SocietyInternational Conference ed W L Hargrove (Ankeny IA Soiland Water Conservation Society) pp 85ndash90

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Estell R E Havstad K M Cibils A F Fredrickson E L Anderson DM Schrader T S and James D K 2012 Increasing shrub use bylivestock in a world with less grass Rangeland Ecol Manage 65553ndash62

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Fedoroff N V et al 2010 Radically rethinking agriculture for the 21stcentury Science 327 833ndash4

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Foley J A et al 2011 Solutions for a cultivated planet Nature 478337ndash42

Fox W E et al 2009 An integrated social economic and ecologicconceptual (ISEEC) framework for considering rangelandsustainability Soc Nat Resour 22 593ndash606

Godfray H C J Beddington J R Crute I R Haddad L Lawrence DMuir J F Pretty J Robinson S Thomas S M and Toulmin C2010 Food security the challenge of feeding 9 billion peopleScience 327 812ndash8

Godfray H C J and Garnett T 2014 Food security and sustainableintensification Phil Trans R Soc B 369 20120273

Govers G Merckx R van Wesemael B and Oost K V 2017 Soilconservation in the 21st century why we need smartagricultural intensification Soil 3 45ndash59

Gutman P 2007 Ecosystem services Foundations for a newruralndashurban compact Ecol Econ 62 383ndash7

Gwin L 2009 Scaling-up sustainable livestock productioninnovation and challenges for grass-fed beef in the USJ Sustain Agric 33 189ndash209

Hein L Van Koppen K de Groot R S and Van Ierland E C 2006Spatial scales stakeholders and the valuation of ecosystemservices Ecol Econ 57 209ndash28

Hendrickson J R Liebig M A and Sassenrath G F 2008Environment and integrated agricultural systems RenewableAgric Food Syst 23 304ndash13

Herrick J E et al 2013 The global land-potential knowledge system(LandPKS) supporting evidence-based site-specific land useand management through cloud computing mobileapplications and crowdsourcing J Soil Water Conserv 685Andash12A

Holechek J L and Herbel C H 1986 Supplementing range livestockRangelands 8 29ndash33

Hsiang S et al 2017 Estimating economic damage from climatechange in the United States Science 356 1362ndash9

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Kleinman P J A et al Advancing sustainable intensification ofUS agriculture through long-term research J Environ Qual inpreparation

Lescourret F et al 2015 A socialndashecological approach to managingmultiple agro-ecosystem services Curr Opin EnvironSustain 14 68ndash75

Liebig M A et al 2017 Aligning land use with land potential the roleof integrated agriculture Agric Environ Lett 2 1ndash5

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Lin B B 2011 Resilience in agriculture through crop diversificationadaptive management for environmental change BioScience 61183ndash93

Lipper L et al 2014 Climate-smart agriculture for food security NatClim Change 4 1068ndash72

Lobell D B Schlenker W and Costa-Roberts J 2011 Climate trendsand global crop production since 1980 Science 333 616ndash20

Loos J Abson D J Chappell M J Hanspach J Mikulcak F Tichit Mand Fischer J 2014 Putting meaning back into sustainableintensification Front Ecol Environ 12 356ndash61

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Lubell M Hillis V and Hoffman M 2011 Innovation cooperationand the perceived benefits and costs of sustainable agriculturepractices Ecol Soc 16 23

Lubell M N Cutts B B Roche L M Hamilton M Derner J DKachergis E and Tate K W 2013 Conservation programparticipation and adaptive rangeland decision-makingRangeland Ecol Manage 66 609ndash20

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Macfadyen S et al 2015 The role of food retailers in improvingresilience in global food supply Glob Food Secur 7 1ndash8

Maia de Souza D Petre R Jackson F Hadarits M Pogue S CarlyleC N Bork E and McAllister T 2017 A review of sustainabilityenhancements in the beef value chain state-of-the-art andrecommendations for future improvements Animals 7 26

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Meisinger J J Hargrove W L Mikkelsen R L Williams J R andBenson V W 1991 Effects of cover crops on groundwaterquality Proc Soil Water Conserv Soc Int Conf 57ndash68(Ankeny IA Soil Water Conservation Society)

Moraine M Duru M and Therond O 2017 A social-ecologicalframework for analyzing and designing integratedcropndashlivestock systems from farm to territory levels RenewableAgric Food Syst 32 43ndash56

National Research Council 2010 Toward Sustainable AgriculturalSystems in the 21st Century (Washington DC The NationalAcademies Press)

Neef A and Neubert D 2011 Stakeholder participation inagricultural research Agric Human Values 28 179ndash94

Neel J P S Turner K E Gowda P H and Steiner J L 2016 Effect offrame size and season on enteric methane and carbon dioxideemissions in Angus brood cows grazing native tallgrass prairieJ Anim Sci 94 293

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Newman G Wiggins A Crall A Graham E Newman S andCrowston K 2012 The future of citizen science emergingtechnologies and shifting paradigms Front Ecol Environ 10298ndash304

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Petersen B and Snapp S 2015 What is sustainable intensificationViews from experts Land Use Policy 46 1ndash10

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15


Power A G 2010 Ecosystem services and agriculture tradeoffs andsynergies Phil Trans R Soc Biol Sci 365 2959ndash71

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Reganold J P et al 2011 Transforming US agriculture Science 332670ndash1

Reynolds M P et al 2017 Improving global integration of cropresearch Science 357 359ndash60

Robertson G P et al 2008 Long-term agricultural research aresearch education and extension imperative BioScience 58640ndash5

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Robinson L W Ericksen P J Chesterman S and Worden J S 2015Sustainable intensification in drylands what resilience andvulnerability can tell us Agric Syst 135 133ndash40

Rockstrom J et al 2016 Sustainable intensification of agriculture forhuman prosperity and global sustainability Ambio 46 1ndash14

Rodriguez J M Molnar J J Fazio R A Sydnor E and Lowe M J 2008Barriers to adoption of sustainable agriculture practiceschange agent perspectives Renewable Agric Food Syst 2460ndash71

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Salant P and Dillman D 1994 How to Conduct Your Own Survey(New York Wiley)

Scasta J D Lalman D L and Henderson L 2016 Drought mitigationfor grazing operations matching the animal to theenvironment Rangelands 38 204ndash10

Schnitkey G Coppess J and Paulson N 2016 Costs and Benefits ofCover Crops An Example with Cereal Rye Farmdoc Daily vol 6(Urbana IL Department of Agricultural and ConsumerEconomics University of Illinois) (httpfarmdocdailyillinoisedu201607costs-and-benefits-of-cover-crops-examplehtml) (Accessed 16 September 2017)

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Snapp S S Swinton S M Labarta R Mutch D Black J R Leep RNyiraneza J and OrsquoNeil K 2005 Evaluating cover crops forbenefits costs and performance within cropping system nichesAgro J 97 322ndash32

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Swain H M Boughton E H Bohlen P J and Lollis L O 2013Trade-offs among ecosystem services and disservices on aFlorida ranch Rangelands 35 75ndash87

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Walbridge M 2013 The Long-Term Agroecosystem Networkstarting local going national Agric Res 61 2ndash3

Walbridge M R and Shafer S R 2011 A long-term agro-ecosystemresearch (LTAR) network for agriculture Proceedings of theFourth Interagency Conference in the Watersheds ObservingStudying and Managing Change (Fairbanks AK USGeological Survey) pp 1ndash7

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16

Environ Res Lett 13 (2018) 034031 httpsdoiorg1010881748-9326aaa779

LETTER

Evaluating strategies for sustainable intensification of USagriculture through the Long-Term AgroecosystemResearch network

S Spiegal122 B T Bestelmeyer1 D W Archer2 D J Augustine3 E H Boughton4 R K Boughton45 M ACavigelli6 P E Clark7 J D Derner3 E W Duncan8 C J Hapeman6 R D Harmel9 P Heilman10 M A Holly11D R Huggins12 K King8 P J A Kleinman11 M A Liebig2 M A Locke13 G W McCarty6 N Millar14 S BMirsky6 T B Moorman15 F B Pierson7 J R Rigby13 G P Robertson14 J L Steiner16 T C Strickland17 H MSwain4 B J Wienhold18 J D Wulfhorst1219 M A Yost20 and C L Walthall21

1 United States Department of AgriculturemdashAgricultural Research Service (USDA-ARS) Jornada Experimental Range Las Cruces NMUnited States of America

2 USDA-ARS Northern Great Plains Research Laboratory Mandan ND United States of America3 USDA-ARS Rangeland Resources and Systems Research Unit Fort Collins CO and Cheyenne WY United States of America4 Archbold Biological Station Venus FL United States of America5 University of Florida Range Cattle Research and Education Center Ona FL United States of America6 USDA-ARS Beltsville Agricultural Research Center Beltsville MD United States of America7 USDA-ARS Northwest Watershed Research Center Boise ID United States of America8 USDA-ARS Soil Drainage Research Unit Columbus OH United States of America9 USDA-ARS Texas Gulf Research Partnership Temple TX United States of America10 USDA-ARS Southwest Watershed Research Center Tucson AZ United States of America11 USDA-ARS Pasture Systems and Watershed Management Research Unit State College PA United States of America12 USDA-ARS Northwest Sustainable Agroecosystems Research Unit Pullman WA United States of America13 USDA-ARS National Sedimentation Laboratory Oxford MS United States of America14 Michigan State University WK Kellogg Biological Station and Department of Plant Soil and Microbial Sciences Hickory Corners MI

United States of America15 USDA-ARS National Laboratory for Agriculture and the Environment Ames IA United States of America16 USDA-ARS Grazingland Research Laboratory El Reno OK United States of America17 USDA-ARS Southeast Watershed Research Laboratory Tifton GA United States of America18 USDA-ARS Agroecosystem Management Research Unit Lincoln NE United States of America19 University of Idaho Department of Natural Resources and Society Moscow ID United States of America20 USDA-ARS Cropping Systems and Water Quality Research Unit Columbia MO USA now at Utah State University Logan UT

United States of America21 USDA-ARS Office of National Programs Beltsville MD United States of America22 Author to whom any correspondence should be addressed

OPEN ACCESS

RECEIVED

20 September 2017

REVISED

27 November 2017

ACCEPTED FOR PUBLICATION

15 January 2018

PUBLISHED

7 March 2018

Original content fromthis work may be usedunder the terms of theCreative CommonsAttribution 30 licence

Any further distributionof this work mustmaintain attribution tothe author(s) and thetitle of the work journalcitation and DOI

E-mail sherispiegalarsusdagov

Keywords agroecosystem management sustainable intensification of agriculture social-ecological systems long-term research network

Supplementary material for this article is available online

AbstractSustainable intensification is an emerging model for agriculture designed to reconcile acceleratingglobal demand for agricultural products with long-term environmental stewardship Defined here asincreasing agricultural production while maintaining or improving environmental qualitysustainable intensification hinges upon decision-making by agricultural producers consumers andpolicy-makers The Long-Term Agroecosystem Research (LTAR) network was established to informthese decisions Here we introduce the LTAR Common Experiment through which scientists andpartnering producers in US croplands rangelands and pasturelands are conducting 21 independentbut coordinated experiments Each local effort compares the outcomes of a predominantconventional production system in the region (lsquobusiness as usualrsquo) with a system hypothesized toadvance sustainable intensification (lsquoaspirationalrsquo) Following the logic of a conceptual model ofinteractions between agriculture economics society and the environment we identifiedcommonalities among the 21 experiments in terms of (a) concerns about business-as-usualproduction (b) lsquoaspirational outcomesrsquo motivating research into alternatives (c) strategies forachieving the outcomes (d) practices that support the strategies and (e) relationships between

copy 2018 The Author(s) Published by IOP Publishing Ltd



Introduction





Methods




2




3

EnvironR

esLett13(2018)

034031



MAP zone (mm)


Crop

land



900-1500





Cook Agronomy Farm






Eastern Corn Belt


900-1500







900-1500







900-1500







900-1500







600-899





4

EnvironR

esLett13

(2018)034031

Table 1 Continued

Experiment Location

MAP zone (mm)


Texas Gulf (a)

TX3152degN 969degW

600-899







600-899





Pastu

relan

dGra

zed C

ropla

nd



900-1500





NorthernPlains








600-899





Southern Plains (a)


600-899





Texas Gulf (b)

TX3152degN 969degW

600-899







900-1500





5

EnvironR

esLett13(2018)

034031

Table 1 Continued


MAP zone (mm)


Rang

eland



900-1500











Great Basin












Southern Plains (b)


600-899










6




Management effects

ENVIRONMENT

ECONOMY

PRODUCTION SYSTEM

Profitability


SOCIETY

Rural opportunity


ecosystem services

PRODUCERS

Decisions inputs

management

GOVERNMENTPOLICY


Politics




Supplydemand







7











Results


8









Discussion




9






10






11






12






13



Conclusion



Acknowledgments


ORCID iDs


References




















14


















































15
































16



Introduction





Methods




2




3

EnvironR

esLett13(2018)

034031



MAP zone (mm)


Crop

land



900-1500





Cook Agronomy Farm






Eastern Corn Belt


900-1500







900-1500







900-1500







900-1500







600-899





4

EnvironR

esLett13

(2018)034031

Table 1 Continued

Experiment Location

MAP zone (mm)


Texas Gulf (a)

TX3152degN 969degW

600-899







600-899





Pastu

relan

dGra

zed C

ropla

nd



900-1500





NorthernPlains








600-899





Southern Plains (a)


600-899





Texas Gulf (b)

TX3152degN 969degW

600-899







900-1500





5

EnvironR

esLett13(2018)

034031

Table 1 Continued


MAP zone (mm)


Rang

eland



900-1500











Great Basin












Southern Plains (b)


600-899










6




Management effects

ENVIRONMENT

ECONOMY

PRODUCTION SYSTEM

Profitability


SOCIETY

Rural opportunity


ecosystem services

PRODUCERS

Decisions inputs

management

GOVERNMENTPOLICY


Politics




Supplydemand







7











Results


8









Discussion




9






10






11






12






13



Conclusion



Acknowledgments


ORCID iDs


References




















14


















































15
































16




3

EnvironR

esLett13(2018)

034031



MAP zone (mm)


Crop

land



900-1500





Cook Agronomy Farm






Eastern Corn Belt


900-1500







900-1500







900-1500







900-1500







600-899





4

EnvironR

esLett13

(2018)034031

Table 1 Continued

Experiment Location

MAP zone (mm)


Texas Gulf (a)

TX3152degN 969degW

600-899







600-899





Pastu

relan

dGra

zed C

ropla

nd



900-1500





NorthernPlains








600-899





Southern Plains (a)


600-899





Texas Gulf (b)

TX3152degN 969degW

600-899







900-1500





5

EnvironR

esLett13(2018)

034031

Table 1 Continued


MAP zone (mm)


Rang

eland



900-1500











Great Basin












Southern Plains (b)


600-899










6




Management effects

ENVIRONMENT

ECONOMY

PRODUCTION SYSTEM

Profitability


SOCIETY

Rural opportunity


ecosystem services

PRODUCERS

Decisions inputs

management

GOVERNMENTPOLICY


Politics




Supplydemand







7











Results


8









Discussion




9






10






11






12






13



Conclusion



Acknowledgments


ORCID iDs


References




















14


















































15
































16

EnvironR

esLett13(2018)

034031



MAP zone (mm)


Crop

land



900-1500





Cook Agronomy Farm






Eastern Corn Belt


900-1500







900-1500







900-1500







900-1500







600-899





4

EnvironR

esLett13

(2018)034031

Table 1 Continued

Experiment Location

MAP zone (mm)


Texas Gulf (a)

TX3152degN 969degW

600-899







600-899





Pastu

relan

dGra

zed C

ropla

nd



900-1500





NorthernPlains








600-899





Southern Plains (a)


600-899





Texas Gulf (b)

TX3152degN 969degW

600-899







900-1500





5

EnvironR

esLett13(2018)

034031

Table 1 Continued


MAP zone (mm)


Rang

eland



900-1500











Great Basin












Southern Plains (b)


600-899










6




Management effects

ENVIRONMENT

ECONOMY

PRODUCTION SYSTEM

Profitability


SOCIETY

Rural opportunity


ecosystem services

PRODUCERS

Decisions inputs

management

GOVERNMENTPOLICY


Politics




Supplydemand







7











Results


8









Discussion




9






10






11






12






13



Conclusion



Acknowledgments


ORCID iDs


References




















14


















































15
































16

EnvironR

esLett13

(2018)034031

Table 1 Continued

Experiment Location

MAP zone (mm)


Texas Gulf (a)

TX3152degN 969degW

600-899







600-899





Pastu

relan

dGra

zed C

ropla

nd



900-1500





NorthernPlains








600-899





Southern Plains (a)


600-899





Texas Gulf (b)

TX3152degN 969degW

600-899







900-1500





5

EnvironR

esLett13(2018)

034031

Table 1 Continued


MAP zone (mm)


Rang

eland



900-1500











Great Basin












Southern Plains (b)


600-899










6




Management effects

ENVIRONMENT

ECONOMY

PRODUCTION SYSTEM

Profitability


SOCIETY

Rural opportunity


ecosystem services

PRODUCERS

Decisions inputs

management

GOVERNMENTPOLICY


Politics




Supplydemand







7











Results


8









Discussion




9






10






11






12






13



Conclusion



Acknowledgments


ORCID iDs


References




















14


















































15
































16

EnvironR

esLett13(2018)

034031

Table 1 Continued


MAP zone (mm)


Rang

eland



900-1500











Great Basin












Southern Plains (b)


600-899










6




Management effects

ENVIRONMENT

ECONOMY

PRODUCTION SYSTEM

Profitability


SOCIETY

Rural opportunity


ecosystem services

PRODUCERS

Decisions inputs

management

GOVERNMENTPOLICY


Politics




Supplydemand







7











Results


8









Discussion




9






10






11






12






13



Conclusion



Acknowledgments


ORCID iDs


References




















14


















































15
































16




Management effects

ENVIRONMENT

ECONOMY

PRODUCTION SYSTEM

Profitability


SOCIETY

Rural opportunity


ecosystem services

PRODUCERS

Decisions inputs

management

GOVERNMENTPOLICY


Politics




Supplydemand







7











Results


8









Discussion




9






10






11






12






13



Conclusion



Acknowledgments


ORCID iDs


References




















14


















































15
































16











Results


8









Discussion




9






10






11






12






13



Conclusion



Acknowledgments


ORCID iDs


References




















14


















































15
































16









Discussion




9






10






11






12






13



Conclusion



Acknowledgments


ORCID iDs


References




















14


















































15
































16






10






11






12






13



Conclusion



Acknowledgments


ORCID iDs


References




















14


















































15
































16






11






12






13



Conclusion



Acknowledgments


ORCID iDs


References




















14


















































15
































16






12






13



Conclusion



Acknowledgments


ORCID iDs


References




















14


















































15
































16






13



Conclusion



Acknowledgments


ORCID iDs


References




















14


















































15
































16



Conclusion



Acknowledgments


ORCID iDs


References




















14


















































15
































16


















































15
































16
































16

Evaluating strategies for sustainable intensification of ......rates, and a tile drainage system...

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Transcript of Evaluating strategies for sustainable intensification of ......rates, and a tile drainage system...