Honors Thesis Proposal

8/8/2019 Honors Thesis Proposal

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Variation in pocket gopher (Thomomys) digging morphology

as a determining factor in species distribution innortheastern California

Ariel E. Marcy

Objective of research

Pocket gophers (family Geomyidae) are subterranean rodents that use tooth- and claw-

digging to varying degrees to tunnel underground. Western pocket gophers (genus

Thomomys) are distributed throughout the western U.S. Thomomys inhabit a wide variety

of habitats and exhibit huge interspecific morphological variation. Pocket gopher ranges

are determined through competitive exclusion such that two species rarely occupy the same

area.

My objective is to combine species locality and morphology analyses to test

whether variations in the Thomomys digging apparatus can explain why each species gains

competitive dominance in the particular soil and climate conditions of its range.

AIM 1: I hypothesize that morphological variation between the digging apparatus

of the species determines their niche along the tooth-to-claw-digging strategy spectrum. I

will test this using morphometrics quantitative size and shape analyses to describe and

compare gopher skeletal specimens from all five species in NE California.

AIM 2: I predict that these differences contribute to the competitive dominance of

one species over another under certain soil characteristics (e.g. particle size, hardness,

water capacity), many of which vary with climate. I will test this by using Geographic

Information Systems (GIS) to project the latitude and longitude of gopher capture site data

onto maps of soil and climate characteristics across California.


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AIM 3: Use GIS to analyze the smaller subset of morphometrically-described

specimens to directly explore the relationship between individual morphology and the soil

and climate conditions of its habitat. If strong correlations exist, I will use them to propose

a biomechanical explanation of how gopher morphology determines each species

competitive ability under certain soil and climate characteristics. This knowledge could

help explain the current distribution pattern of pocket gophers across California,

understand a species turnover event during the Pleistocene, and predict gopher

distributions under a climate change model.

Introduction

Charles Thaeler laid the groundwork for pocket gopher research in Northeastern California

by investigating the claim that gopher ranges never overlap. Thaeler chose Northeastern

California because five species inhabit this area and of the ten possible pair-wise species

overlap combinations, nine occur. He created a distribution map for NE California through

extensive field observations and sampling (Fig. 1). He determined that Thomomys have

abutting ranges, but species almost never exist sympatrically (Thaeler 1968). The rare

cases of range overlap occur in areas with two radically different soil types. Morphological

differences had not been analyzed thoroughly by Thaelers time but he suggested these as

the main reason for competitive exclusion (Thaeler 1968).

Thaelers hypothesis for exclusion assumes that variations in environmental

characteristics across the NE Californian region alter the outcome of competition. To test

this, my study will combine species locality and morphology analyses to see whether a

biomechanical advantage under particular soil and climate conditions can explain the

geography of range boundaries between competing gopher species. Extensive


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documentation of gopher sensitivity to soil moisture, temperature, and texture supports this

hypothesis (Miller and Gross 1998, Romanach et al 2005). Digging is very energetically

demanding, but the exact cost varies between soil types (Lessa 1990). Furthermore,

metabolic rates of subterranean species working in harder soils vary, demonstrating that

some are more efficient in particular soil types (Luna and Antinuchi 2006).

Recent assessment of gopher morphology has emphasized the dual nature of the

digging apparatus, involving both the forelimbs and the jaw, which are the lever arms for

claw- and tooth-digging respectively (Lessa and Thaeler 1989). Further analysis of the

digging apparatus found that claw-digging tends to restrict animals to friable sandy soils

whereas tooth specializations broaden the potential spectrum of habitable soil textures

(Lessa and Thaeler 1989). The authors conclude that digging specializations contribute to

the realized range of gophers, however, the exact mechanisms are undeveloped.

In a follow-up study, Lessa and Stein conducted linear morphometric and

myological analyses that included two representatives from the genus Thomomys. The

morphometric analysis found only osteological variation between jaw and forelimbs (Lessa

and Stein 1992, Stein 1993). This observation allows me to limit my morphological studies

to skull and forelimb bones, which are much more accessible than myological material.

Their analyses also showed that Thomomys morphology varies from highly specialized for

tooth-digging to slightly favoring claw-digging (Fig. 2).

Despite the large number of morphological studies on pocket gophers, no studies

have focused only on differences within a genus and thus range determination between

species is still poorly understood (E.A. Hadly, personal communication 2009). The

existing literature draws on the larger cross-genera morphological differences to

characterize gophers as more specialized for claw-digging versus tooth-digging


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invaluable information for my project. However, unwarranted generalizations from one

species to its entire genera are common in pocket gopher literature. Despite the spread in

Thomomys digging modes noted in Lessa and Stein 1992, the genus is usually

characterized as tooth-specialized diggers in cross-genera studies, and strangely, Stein

describes them as claw-diggers in Stein 2000.

Morphological comparisons within any pocket gopher genera would generate

interesting results to a field lacking such studies. Thomomys is an ideal genus to investigate

sub-genera differences because its species vary across an order of magnitude in size and

they inhabit a wide range of soils and habitats (Stein 2000, Thaeler 1968). Most of the

cross-genera studies described above used linear morphometrics. My approach will

achieve a higher degree of sensitivity by adding geometric morphometric analysis.

My focus on interspecific differences allows me to introduce a unique extension to

gopher ecology. Previous cross-genera studies made observations of the general ecology

for the genera, but extensions are limited because each genus of gophers resides in

different regions of the country. Therefore the populations studied do not interact and

comparisons cannot control for larger variations between ecosystems or for variations

within the genera. I avoid these issues by focusing on all the species within one genus

located specifically in Northeastern California.

If both facets of my study reveal significant results, these will be combined to

propose a biomechanical explanation for the competitive exclusion determining pocket

gopher spatial distributions. Knowledge of why particular gopher species competitively

exclude the others in certain soil types and that of ancient gopher distribution information

could be extended to recreate ancient regional climates. There is evidence of a gopher

replacement event in Northeastern California during the Pleistocene in which one species


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supplanted another from its former range (Blois 2008). We will be able to describe how

climatic conditions might have changed during the Pleistocene, once we understand the

soil and climate conditions these species thrive in.

Furthermore, this knowledge, in conjunction with climate change models, could be

used to predict future gopher distributions under different parameters. Gophers are

ecosystem engineers that create habitats for endangered species, such as the burrowing

owl, reduce invasive grass establishment, and otherwise greatly affect community structure

(Cameron 2000, Cox and Hunt 1994, Eviner and Chapin 2003, Stein 2000). Forming a

deeper understanding of pocket gopher species biomechanics, competitive interactions, and

ecology will generate insights into the past, current, and future Californian ecosystem.

Materials and Methods

First, I will use two types of morphometric analysis, linear and geometric, to

quantify functional differences between the skulls and forelimbs of the five species of

Thomomys pocket gophers from NE California. Second, I will use GIS to overlay museum

specimen locality data on maps of soil and climate. Principal Components Analyses (PCA)

and Geographically Weighted Regression (GWR) can determine whether correlations exist

between the soil, climate, and the spatial distribution patterns exist across the western US,

concentrating in California. Finally, I will analyze the subset of gopher species from NE

California with morphometric data in GIS to determine whether the morphological

differences can be linked to differences in the abiotic characteristics where they occur to

help explain the trends seen across species in the Western US.

1. Analysis of variations in Thomomys digging morphology


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Morphometrics is a quantitative way of comparing shape. Linear morphometrics

(LM) are simple measures of length and width of bones and bony processes (muscle

attachment sites). I will use five forelimb as well as eight cranial and dental standard

measurements previously described for gophers (Fig. 3). My specific predictions for

variations in linear measurements by digging mode are described in Table 1. LM can be

used on ancient bones and will generate absolute measurements appropriate for

quantitative biomechanical studies of gopher lever arms. Often morphometric studies on

species within a genus produce data that can be used to identify ancient bones more

specifically.

Geometric Morphometrics (GM) is a branch of mathematical shape analysis aided

by digital camera and computer software. GM can perform more sophisticated analyses

than LM because linear measurements do not convey information about spatial

relationships between measurement points (Zeldich et al 2004). GM solves this problem by

creating a digital network of points called landmarks that define the shape of the bone of

interest. Landmarks must be discrete points on an organism that are recognizable across all

specimens and can be pinpointed with a computer image of the specimen (Fig. 6). Often,

recognizable areas have functional significance, such as a muscle attachment scar. I can

use the photos I take for LM analyses and ImageJ to perform most GM analyses. The

Hadly lab computer has additional statistical analysis programs for regression, CVA,

MANOVA, and PCA tests.

I will continue to acquire gopher skeletal specimens from the Museum of

Vertebrate Zoology (MVZ) at University of California, Berkeley. Only female specimens

will be used for morphometric studies because their growth ends short after reproductive

maturity, unlike males, whose continued growth could introduce allometric errors related


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to specimens age at capture (J.L. Patton, personal communication 2010). Only

individuals collected from Northeastern counties will be used in order to control for

regional variation across the state. Furthermore, because gopher populations exhibit huge

intraspecific variation, I will break down species and subspecies into 14 geographic groups

after Patton and Smith 1990. I aim to measure at least 25 specimens per geographic group,

which is the precedent from previous morphometric studies in rodents (Anderson et al

2002, Cartini and OHiggins 2004, Zeldich et al 2004, Zelditch and Swiderski 2009).

Because GM organizes landmarks into a matrix of interrelated points, each

specimen can be scaled to the same size, thus removing the variable that usually drives

most of the differences in the linear PCA and can overshadow variation due to shape. A

PCA of GM data creates vectors that indicate the direction of shape change across groups

of species (Fig. 7). Landmarks could then be grouped using osteological or myological

adaptation indicators of digging mode previously described by cross-genera studies of

pocket gopher morphology. Analysis of how these elements vary could then be applied to

describe how the NE Californian Thomomys geographic groups fall with respect to each

other on the claw- and tooth-digging spectrum.

2. Geographic Information System (GIS) analyses of Thomomys species of California

I will use the Geographic Information System (GIS) to test whether range

boundaries of species are correlated with particular soil and climate conditions by

projecting the latitude and longitude of each gopher capture site onto maps of soil and

climate. I will compare species locality data to soil clay, sand, and silt content, water

capacity, clay mineral type, rock strata, temperature, elevation and annual precipitation

maps. I can access precise maps of soil and climate characteristics for the Western US


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from the Natural Resources Conservation Service (NRCS) and United States Geological

Service (USGS).

Gopher locality data for all five species ofThomomys from museums in the western

region of the US can be downloaded from both the Mammal Networked Information

System (MaNIS) and Arctos, a multi-institution museum database. The dataset of gopher

localities will be reduced to just those points with georeferencing error smaller than 3km.

These data will be used to generate maps illustrating patterns observed across the entire

western US concentrating in California but including Oregon and Nevada. This region is

environmentally heterogeneous and will give a large area to observe patterns over.

Results can be analyzed on an individual map basis by graphing the soil or climate

parameter versus species on density histograms and comparing the averages between

geographic groups. These analyses can be done for the entire geographic range or for much

smaller regions. Data can be exported from GIS and the analysis and graphing can be done

in R. All of the results for every climate and soil parameter will be analyzed in a more

powerful Geographically Weighted Regression (GWR). Using the GWR algorithm in GIS

will determine which abiotic parameters are involved in determining gopher ranges and

which are the most important. GWR is particularly useful because it weighs each

parameters importance over the entire range, so the analysis will give maps showing how

the influence of each parameter varies over the landscape.

3. GIS analysis of morphometrically described specimens in NE California

To determine whether the patterns observed at the species level are in fact driven by

morphological differences, I will use GIS to analyze the 14 groups of morphologically

described specimens from NE California. NE California is an ideal study area because of


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the ten possible pair-wise species interactions, nine occur. Analyses used for the

geographic groups above, can be applied to individual linear measurements or trends in

geometric morphometrics. To reduce error in my analyses, I will need to return to the field

notes for each of the specimens I choose to ensure more accurate georeferencing. When

running GIS analyses, it is possible to introduce a buffer zone that takes into account the

relatively large extent gophers inhabit and the error introduced when field researchers take

only a few georeference points for each trapline.

Preliminary and Anticipated Results

I became involved in the Hadly lab the summer after freshman year working as a field

assistant to Jessica Blois, a graduate student in the lab at the time. She was investigating

how climatic change since the last ice age to the present had affected small mammal

populations. When I began working in the lab my sophomore year, I met with Prof. Hadly

to discuss potential projects I could work on. Prof. Hadly suggested Thomomys as an

interesting study species to describe morphologically because there was some debate over

an ancient species found only in the Shasta cave where Jessica had been working. Over the

course of the year, Jessicas results revealed an interesting turnover event in which one

species of gopher pushed another north. These results, my interest in multidisciplinary

studies, and more discussions with Prof. Hadly changed the focus of my project to the

interaction of biomechanics and environment in range determination over space and time.

1. Analysis of variations in Thomomys digging morphology

Using digital calipers, I have completed forelimb measurements for 98 individuals

including all five species. Redundant measuring allowed me to assess whether my


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measurement error was below 5%. I was not able to measure one specific measurement

consistently with calipers so I plan to take digital pictures of my specimens and use ImageJ

to retake them. Using R, a statistical program, I have completed a preliminary PCA

analysis of the five species by the four accurate measurements of their forelimbs (Figs. 4,

5). PCA is a mathematical procedure that transforms a number of possibly correlated

variables into a smaller number of ranked uncorrelated variables called principal

components (Zeldich et al 2004). In morphometrics, the first PC usually describes size and

the succeeding PCs account for shape. The results show separation of species by size and

the correlation of PC2 to the deltoid process suggest that more powerful analyses like

geometric morphometrics will find significant shape differences.

2. GIS analyses of Thomomys species across California

With the help of Hadly lab technician, Lily Li, and Branner GIS specialist, Patricia

Carbajales, I have completed substantial analyses of soil clay content and species locality

(Figs. 8-10). Using data from NRCS soil surveys of the United States, we grouped the soil

survey units into bins of 0-20%, 20-40%, and >40% clay content as suggested by visiting

physical soil properties specialist, Professor Oliver Chadwick (Figs. 8, 9). Overlaying

species locality data over the maps appeared to indicate that the claw-digging subgenera

Thomomys species tracked the regions with lower clay content whereas the tooth-digging

subgenera Megascapheus species tracked regions with higher clay content (Figs. 8, 9).

Density histograms of species from small geographic regions showed that they are indeed

sorting by clay content (Fig. 12).

Unexplained portions of the map, however, include the Northeast corner of

California, where a subgenus Thomomys species, T. mazama, inhabits a region of high soil


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clay content. I hope to continue investigating how soil characteristics interact with climatic

factors to produce these types of results.

3. GIS analysis of morphometrically described specimens in NE California

I have found preliminary results using the linear morphometric data points for the

forelimbs of 30 female individuals with less than 3km georeferencing error. Correlations

between soil clay content and forelimb measurements were all positively correlated with p

values less than 0.01. All of my predictions for this relationship were met except for

humerus length, which increased (Table 1, Fig. 13). I had expected this to decrease due to

increased forces experienced by the forearm while digging (Stein 2000). However, it may

have increased as a result of size conferring an advantage in hard soils. Ulna length also

increased with a correlation greater than that of olecranon length, which also suggests size

playing a role.

These results did not break the points down by species, so some of the results, such

as increased ulna and humerus length, could be related to the species inhabiting harder

soils, emphasizing tooth-digging over claw-digging. To investigate these trends by species,

I will need to gather a larger sample size for each group, which will be accomplished for

the 14 geographic groups of 25 individuals from NE California. Importantly, these results

show that correlations between soil type and species from part 2 are seen also among

individuals, which supports a biomechanical explanation for range determination as

opposed to shared characteristics of a species.

The preliminary results seem promising, however, much more data needs to be

collected and analyzed more thoroughly before conclusions can be made.


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Appendix

Fig. 1: Distribution map of Thomomys genus pocket gophers, for reference, top border is Oregon,

right border is Nevada (from Thaeler 1968)

Fig. 2: PCA illustrating how genera and two species of Thomomys spread on axes of size and

claw- or tooth-digging traits (from Lessa and Stein 1992)


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Fig. 3: Measurements for morphometric analysis (from Lessa and Stein 1992)

Table 1: Linear morphometrics measurements, abbreviations, grouped by forelimb andskull measurements, Hypotheses given for morphology changes in harder soil. Preliminary

results available for forelimb measurements (n=30).Measurement Abbr. Claw-digging Preliminary Results

Humerus

length

HUML Decreased (higher forces experienced

in arms)*

Increased (cor 0.59, p


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Fig. 4: PCA of my preliminary linear measurements. PC1 is correlated with size.

Fig. 5: Scatter plot of P21 versus deltoid width shows that PC2 is moderately correlated to

variation in the deltoid process.


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Fig. 6: Landmarks for a South American subterranean rodent, Ctenomys torquatus skull (From

Fernandes et al 2007)

Fig. 7: PCA results of landmark-based GM of a rodent cranium (From Zelditch and Swiderski

2009)


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Fig. 8: Illustrator-generated image of Fig. 1 over the soil clay content map of California

Fig. 9: GIS-generated map of species point localities over California region clay content,demonstrating more robustly the patterns of subgenera tracking with low and high % clay


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Fig. 10: GIS-generated map of NE California and the proposed 14 geographic groups formorphometric analysis (part 1) and GIS analysis of morphometrically described

individuals (part 3)


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Fig. 11: Topographic map of NE California groups with Mount Shasta study area

highlighted

Fig. 12: Density histogram of 3 species near Mount Shasta showing separation by % clay


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Fig. 13: Scatter plot showing correlation (0.59, p


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