How Ecology, Hydrogeology, and Geomorphology

MULTI-FACETED “MUDBUGS”: HOW ECOLOGY, HYDROGEOLOGY, AND

GEOMORPHOLOGY INFLUENCE BURROWING CRAYFISH BIODIVERSITY IN

ALABAMA’S BLACK BELT PRAIRIE

REBECCA ANN BEARDEN

ALEXANDER D. HURYN, COMMITTEE CHAIR JENNIFER G. HOWETH PAIGE F. FERGUSON CARLA L. ATKINSON NATASHA T. DIMOVA GUENTER A. SCHUSTER

A DISSERTATION

Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of Biological Sciences in the Graduate School of The University of Alabama

TUSCALOOSA, ALABAMA

2020

ABSTRACT Aquatic species are facing imperilment at a disproportionate rate compared to terrestrial species and thus higher probabilities of extinction. The southeastern United States has an exceptionally high level of freshwater biodiversity, supporting the majority of the nation’s fish, mussel, and crayfish species. Crayfish research, in particular, is significant to conservation efforts, as nearly half of the crayfish species in the southeastern United States are threatened.

Through their signature burrowing strategy, many crayfish bridge the gap between aquatic and terrestrial communities, especially in floodplain habitats. Floodplains are highly heterogeneous and harbor a high diversity of species, yet our understanding of species-habitat relationships within these complex ecosystems remains incomplete and may hinder conservation.

I studied floodplains in the Bogue Chitto Creek watershed in the Black Belt Prairie region of

Alabama to investigate: 1) activity patterns of primary burrowing crayfish and 2) local and landscape level environmental factors that may affect burrowing crayfish distribution. In Chapter

2, I used motion-triggered digital photography to document activity patterns for two primary burrowing crayfish. I found that out-of-burrow activity was greatest at night and during periods of relatively cool groundwater temperatures and relatively warm air temperatures, which may be linked to thermal regulation. In Chapter 3, I examined relationships between burrowing crayfish presence and species composition and local hydrogeological factors. Results suggested an increased likelihood that crayfish were present at sites with a shallow water table, and that species composition was marginally associated with depth to groundwater and inundation

ii duration. In Chapter 4, I investigated associations between burrowing crayfish presence and species composition and geomorphological factors. I found that crayfish were more likely to be present in areas that were not in the channel migration path, areas near streams with a greater sinuosity, areas with greater floodplain connectivity, and areas with less forested land use.

The combined results of my studies in the Bogue Chitto Creek watershed suggest that projects embracing integrated, multidisciplinary approaches to surface and groundwater hydrology as drivers of biodiversity should be a priority for research related to the conservation of burrowing crayfish populations and communities.

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DEDICATION This dissertation is dedicated to the patient and supportive “Team Crayfish.”

LIST OF ABBREVIATIONS AND SYMBOLS d.f. Degrees of freedom: number of values free to vary after certain restrictions have been placed on the data p Probability associated with the occurrence under the null hypothesis of a value as extreme or more extreme than the observed value r Pearson correlation coefficient ρ Spearman’s rank correlation coefficient < Less than = Equal to

ACKNOWLEDGMENTS I am forever indebted to my advisor, Alex Huryn, for taking me on as a graduate student, encouraging me to tackle burrowing crayfish as a research project, and for helping me stay focused on the basics of burrower biology. Alex’s first research advice was the best I’ve ever received: “Go and sit in your study system, observe what you see, and think hard about what’s going on around you.” I am also grateful to the godfather of Alabama crayfish, Guenter Schuster, for his mentorship and the wealth of crayfish knowledge he has shared over the past five years. I will continue to seek his advice as long as he will allow. I thank Jennifer Howeth, Carla

Atkinson, Paige Ferguson, and Natasha Dimova for their guidance as committee members and for their leadership as women in science. I look forward to future collaborations with all of you. I am grateful to past and present graduate students, Emma Arneson, Nate Sturm, Jacob Dawson, and Zoe Nichols, for providing moral and field support during this project. I especially thank

John Abbott for his guidance regarding laser-triggered photography. Thanks to his direction, the world of astacology now has a nondestructive sampling method for recording burrowing crayfish activity. I thank the University of Alabama Biological Sciences Department for funding the cameras and laser triggers used for Chapter 2 and data loggers used for Chapter 3. I am forever grateful to my co-author, Emily Tompkins, who spent hours not only helping me understand how to run generalized linear mixed models in R but also editing my rough draft chapters to make them publication-quality manuscripts. What I have learned from Emily constitutes an entire graduate course in data analysis.

vi I express gratitude to the Geological Survey of Alabama (GSA) for solely funding the shallow monitoring well supplies for Chapter 3 and for allowing me to utilize the geochemistry lab for sediment analysis for Chapter 3. I especially thank Nick Tew, Pat O’Neil, and Stuart

McGregor for their support of my academic endeavors. I also greatly appreciate the data collection assistance from Daniel West, Parker Nenstiel, Greg Guthrie, Steve Jones, and David

Tidwell and from Jamekia Durrough-Pritchard and Anne Wynn (formerly of GSA). I thank Gary

Hastert of GSA for his invaluable GIS contributions utilized heavily for Chapter 4.

I attribute my love of nature and pursuit of science to my late father, Gary Bearden, who never missed an opportunity to share his knowledge of the natural world, especially via his preferred instruction method—horseback. I thank my sweet mother, Peggy Bearden, who offers daily encouragement for all of my scholastic goals, unwavering love, and attention to detail, which have all proven invaluable during my graduate career. I thank my sister, Rachel Bearden

Yeargan, whose work ethic rivals that of any scientist past or present, for her friendship, sibling support, and high standards. I am grateful to my two nephews, J.B. and Gary, for their indulgence in hours of creek time and to my brother-in-law, Brant Yeargan, for spending time and skills cutting up scores of sediment cores for analysis. I am eternally grateful to my biggest supporter, Chris Weaver, who spent years of his life dedicated to this project. The blood, sweat, and tears were all in the name of science, and I am evermore appreciative of his love, the opportunity to conduct research alongside him, and his tireless efforts in assisting with arduous fieldwork. This project would not have happened without him.

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CONTENTS

ABSTRACT ...... ii

DEDICATION ...... iv

LIST OF ABBREVIATIONS AND SYMBOLS ...... v

ACKNOWLEDGMENTS ...... vi

LIST OF TABLES ...... xi

LIST OF FIGURES ...... xiii

CHAPTER 1: INTRODUCTION TO THE DISSERTATION ...... 1

Introduction ...... 1

Chapter 2: Activity study ...... 2

Chapter 3: Local environmental factors ...... 4

Chapter 4: Landscape-scale environmental factors ...... 5

Literature Cited ...... 6 CHAPTER 2: MOTION-TRIGGERED LASER PHOTOGRAPHY REVEALS FINE- SCALE ACTIVITY PATTERNS IN BURROWING CRAYFISH ...... 9

Abstract ...... 9

Introduction ...... 10

Methods ...... 13

Study area ...... 13

Study organisms ...... 13

Photography ...... 14

Environmental data ...... 15

Data analysis ...... 16

viii Results ...... 18

Lacunicambarus erythrodactylus ...... 18

Procambarus holifieldi ...... 19

Discussion ...... 20

Acknowledgments ...... 25

Literature Cited ...... 25 CHAPTER 3: CRAYFISH CONNECTIONS: LINKING ECOLOGY AND HYDROGEOLOGY IN ALABAMA’S BLACK BELT PRAIRIE USING BURROWING CRAYFISH PRESENCE ...... 39

Abstract ...... 39

Introduction ...... 40

Methods ...... 43

Study site ...... 43

Crayfish presence and collections ...... 44

Environmental variables ...... 44

Statistical analysis ...... 45

Three-zone presence/absence analysis ...... 46

Two-zone presence/absence analysis ...... 47

Species composition by habitat ...... 48

Results ...... 48

Three-zone presence/absence analysis ...... 48

Two-zone presence/absence analysis ...... 49

Crayfish presence and collections and species composition by habitat ...... 49

Discussion ...... 50

Conclusions ...... 55

Acknowledgments ...... 56

ix Literature Cited ...... 56 CHAPTER 4: LANDSCAPE-SCALE ENVIRONMENTAL VARIABLES INFLUENCE WATERSHED-WIDE BURROWING CRAYFISH PRESENCE ...... 70

Abstract ...... 70

Introduction ...... 71

Methods ...... 76

Study site ...... 76

Crayfish presence and collections ...... 76

Landscape variables ...... 77

Statistical analysis ...... 78

Species composition by landscape variables ...... 79

Results ...... 80

Landscape variables ...... 80

Crayfish presence and collections ...... 81

Species composition by landscape variables ...... 82

Discussion ...... 83

Acknowledgments ...... 89

Literature Cited ...... 90

CHAPTER 5: CONCLUSIONS AND FUTURE DIRECTIONS ...... 111

Conclusions ...... 111

Future Directions ...... 114

Literature Cited ...... 116

LIST OF TABLES Table 2.1. Top candidate models ranked by AIC describing variation in Lacunicambarus erythrodactylus activity, Procambarus holifieldi activity, and chimney construction activity for P. holifieldi ...... 30 Appendix 2.1. Habitat characteristics for Site 1 (Lacunicambarus erythrodactylus) and Site 2 (Procambarus holifieldi) ...... 36 Appendix 2.2. Photographs of Lacunicambarus erythrodactylus (left column) and Procambarus holifieldi (right column) displaying emergence behavior (A-B) and chimney construction behavior (C-D) ...... 37 Appendix 2.3. Coefficient estimates for the GLMM (binomial errors, logit link) best explaining variation (lowest AICc value; the “top model”) in out-of-burrow activity for Lacunicambarus erythrodactylus and Procambarus holifieldi, as well as the probability of chimney construction in P. holifieldi ...... 38 Table 3.1. Correlation coefficients between pairs of soil variables measured at each floodplain and intermediate sampling site (N = 50) ...... 61 Table 3.2. Environmental variables measured from January to December of 2017 comparing sites with and without crayfish ...... 62 Table 3.3. Top candidate models ranked by AICc describing variation in crayfish presence in streamside, intermediate, and floodplains zones (top) and in data restricted to intermediate and floodplain zones (bottom) ...... 63 Table 3.4. Crayfish collections by species and sampling site ...... 64 Appendix 3.1. Coefficient estimates for the GLM (binomial errors, logit link) best explaining variation (lowest AICc value; the “top model”) in burrowing crayfish presence ...... 69 Table 4.1. Correlation coefficients between pairs of environmental variables used in this study ...... 96 Table 4.2. Site data including locations and values for landscape variables used in this study ...... 97 Table 4.3. Top candidate models ranked by AICc describing variation in crayfish presence...... 99 Table 4.4. Pearson’s correlation coefficients between pairs of measured local environmental variables and landscape variables calculated for each sampling site (N = 50) during a previous burrowing crayfish presence-absence study (Bearden et al. 2020, unpublished data) ...... 100 Table 4.5. Crayfish collection sites and number collected ...... 101

xi Table 4.6. Spearman’s rank correlations coefficients comparing burrowing crayfish species with MDS axes 1 and 2 ...... 103 Appendix 4.1. Coefficient estimates for the GLM (binomial errors, logit link) best explaining variation (lowest AICc value; the “top model”) in burrowing crayfish presence, as well as the GLMs that included each variable in isolation ...... 109

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LIST OF FIGURES Figure 2.1. Camera and laser-trigger setup used to monitor crayfish activity at each burrow ...... 31 Figure 2.2. Year-round activity for Lacunicambarus erythrodactylus (left column) and Procambarus holifieldi (right column) for emergence and chimney construction behavior with corresponding daylength, groundwater temperature, and precipitation ...... 32 Figure 2.3. Model-estimated relationships (in black) between the probability of a burrow being active and statistically supported environmental predictors and precipitation for Lacunicambarus erythrodactylus (left) and Procambarus holifieldi (right) ...... 33 Figure 2.4. Model-estimated relationships between the probability of chimney construction behavior given that a burrow is active and each predictor variable present in the top model (black points in B, black lines in A, C-E), overlaid on the raw data grouped by time and into equally spaced bins along the x-axis (gray points), for Procambarus holifieldi ...... 34 Figure 2.5. Year-round, chimney-construction activity Procambarus holifieldi with corresponding groundwater depth...... 35 Figure 3.1. Study area with transect locations as black dots ...... 65 Figure 3.2. Model-estimated relationships (in black) between the probability of a crayfish being present and groundwater depth, soil resistance, dominant particle size (two-zone analysis only), and DBH from three-zone (left) and two-zone analyses (right) ...... 66 Figure 3.3. Plots showing the ordination results from NMDS for species composition and abundance as they relate to groundwater depth (A) and inundation duration (B) for each site ...... 67 Figure 3.4. Monthly profiles of groundwater depth and inundation duration at sites where each crayfish species was collected during this study ...... 68 Figure 4.1. Study area in the Bogue Chitto Creek watershed in the Black Belt Prairie physiographic district in Dallas and Perry counties, Alabama, USA ...... 104 Figure 4.2. LiDAR imagery used to determine channel migration status for each sampling site ...... 105 Figure 4.3. Model-estimated relationships (in black) between the probability of a crayfish being present and statistically supported landscape predictors...... 106 Figure 4.4. Plot showing the ordination results from NMDS for species composition and abundance ...... 107 Figure 4.5. Raw data for species-specific responses to distance to nearest stream (A), sinuosity (B), rate of elevation change (C), and forest cover (D) ...... 108

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CHAPTER 1: INTRODUCTION TO THE DISSERTATION Introduction The southeastern United States has an unusually high level of freshwater biodiversity, supporting almost two-thirds of the nation’s fish species, >90 % of the mussel species, and nearly half of the world’s crayfish species (Jenkins et al. 2015, Elkins et al. 2019). Crayfish research, in particular, is a growing field, as nearly half of the crayfish species in the southeastern United States are threatened or endangered (Taylor et al. 2007, Richman et al.

2015). This level of imperilment is especially relevant to the state of Alabama and its 99 described species of crayfish, as some of these are limited to a single drainage and their ecology, behavior, and vulnerability to human disturbance are still poorly understood (Neves 1999,

Warren et al. 2000, Taylor 2002).

Crayfish are a diverse group of invertebrates with unique adaptations for burrowing in benthic and terrestrial habitats, providing a vital link between aquatic and terrestrial environments. Crayfish burrowing can enhance soil mixing, increase soil habitat complexity

(Robertson and Johnson 2004, Welch et al. 2008, Reynolds et al. 2013), increase soil respiration

(Richardson 1983, Stone 1993) and provide habitat for other species (Pintor and Soluk 2006,

Loughman 2010). Their signature burrowing ability has led to classification based on the level of connection between their habitats and surface waters: “primary” burrowers spend most of their time in the burrow, and rarely if ever, use permanent surface waters (Hobbs 1981, Berrill and

Chenoweth 1982, DiStefano et al. 2009); “secondary” burrowers produce relatively simple burrows near, and often in, surface-water habitats (Hobbs 1981); and “tertiary” burrowers

1 construct an even more basic burrow, often a single, blind tunnel in the bottom of a stream or pond which they use primarily for reproduction or avoidance of unfavorable environmental conditions.

Understanding the role of burrowing crayfish in driving a geomorphic interface between subsurface and terrestrial animal communities requires knowledge of their life history, distribution, population status, and ecological interactions (Taylor et al. 2007, Helms et al.

2013a,b). In this dissertation, I examined relationships between burrowing crayfish behavior and biodiversity and environmental correlates in the Mobile River Basin; I targeted floodplains within the Bogue Chitto Creek watershed in the Black Belt Prairie physiographic region to assess these relationships. I addressed five questions: (1) Is out-of-burrow activity triggered by specific environmental cues (Chapter 2)? (2) Is burrowing crayfish site selection driven by local environmental factors? Are there species-specific responses to local environmental variables

(Chapter 3)? (3) Is watershed-wide burrowing crayfish distribution driven by landscape-level environmental factors? Are there species-specific responses to landscape-level environmental variables (Chapter 4)?

Chapter 2: Activity study One factor contributing to the paucity of studies on primary burrower biology is the difficulty researchers face in sampling these species (Williams et al. 1974). Burrowing crayfish collection methods have included excavation (Simon 2004), visual night searches (Hobbs 1981), vernal pool traps (Taylor and Anton 1998), a plunger method (Simon 2001), the Norrocky burrowing crayfish trap (Norrocky 1984), a funnel trap (Hopper and Huryn 2012), and the burrowing crayfish net (Welch and Eversole 2006). Ridge et al. (2008) compared the efficiency and efficacy of excavation, the Norrocky burrowing crayfish trap, and burrowing crayfish mist

2 nets and determined that excavation was the most successful, though the process destroys burrows and restricts opportunities for subsequent sampling (Simon, 2004), leaving room for methodological improvements. Laser-triggered, digital photography is a promising, non- destructive, non-invasive method that has been recently used to study species presence/absence and activity patterns in aquatic systems (e.g., crawfish frogs: Heemeyer and Lannoo 2012,

Heemeyer et al. 2012, Stiles et al. 2017).

The sampling difficulty and resulting small sample size characterizing primary burrower research may also result from a poor understanding of burrower behavior. Collections, for example, may be more efficient if peak activity periods can be identified. Field studies linking year-round burrower behavior to possible environmental cues, however, are sparse. Most studies have revealed seasonal patterns in crayfish activity, but the timing of peak activity may be species-specific (Norrocky 1991, Ridge et al. 2008, Camp et al. 2011).

In Chapter 2, I assessed if burrowing crayfish behavior can be linked to environmental cues using laser-triggered, digital photography. I evaluated fine-scale temporal activity patterns of two primary burrowing crayfish species, Lacunicambarus erythrodactylus (Simon and Morris) and Procambarus holifieldi (Schuster, Taylor and Adams), as a function of emergence time, activity duration, and activity type. I predicted that activity would be primarily nocturnal and would be most prevalent following rainfall events and also predicted that activity would follow a seasonal pattern, with highest activity levels during the spring (when groundwater depth is low and air temperatures are relatively high), and relatively low activity in the summer (due to high groundwater depth) and winter (due to low temperatures).

3 Chapter 3: Local environmental factors Through their use of both aquatic and terrestrial environments in floodplain ecosystems, crayfish are ideal organisms for studies of both local hydrogeological and landscape-level geomorphological processes. Understanding associations between burrowing crayfish and the environmental features of floodplains is particularly valuable because crayfish, through burrowing, play an important role in establishing aquatic-terrestrial connections. While primary burrowers typically use groundwater as their main source of water, secondary and tertiary burrowers may frequent permanent surface water or use water provided by seasonal floodplain pools (Hobbs 1981, Berrill and Chenoweth 1982, DiStefano et al. 2009). Species of crayfish that persist in floodplains holding water during limited periods of the year must burrow deep enough to access shallow groundwater, therefore, burrow presence may indicate a preference for select local surface and subsurface characteristics.

Floodplain studies targeting crayfish have been species-specific and limited in scope.

Laboratory studies have shown that the local distribution of primary burrower Lacunicambarus. erythrodactylus is influenced by water table height (Hobbs 1981), soil type (Grow and Merchant

1980, Loughman et al. 2012, Helms et al. 2013b), floodplain connectivity, and stream bank condition (Helms et al. 2013b). Soil type and soil compaction may also influence occupancy, and population responses to drying and flooding are species-specific (Dorn and Volin 2009, March and Robson 2006, Caine 1978, Taylor 1983, Dorn and Trexler 2007). Because some floodplain habitats harbor a diversity of crayfish in the same local area, a micro-landscape approach that addresses environmental drivers of distribution in a field setting may help determine which environmental factors enhance local biodiversity within floodplains.

In Chapter 3, I assessed if burrowing crayfish presence was linked to local environmental factors and identified possible species-specific responses to the same environmental factors. I

4 evaluated crayfish presence and composition with respect to groundwater depth, inundation duration, soil characteristics, and tree size. I predicted that crayfish would prefer areas with shallower groundwater depth, fine-grained soils, and larger trees, while crayfish composition would show species-specific responses to groundwater depth and soil characteristics.

Chapter 4: Landscape-scale environmental factors Due to diverse habitat requirements for all three burrower types, the spatial distribution of these species within floodplains may also be the result of landscape-level processes creating local habitat patches. While studies have shown that the distribution of burrowing crayfish within floodplains may be affected by fine-scale variables such as soil type, water table height, and stream bank characteristics (Hobbs 1981, Grow and Merchant 1980, Loughman et al. 2012,

Helms et al. 2013b), landscape level studies are sparse and have focused more heavily on stream- dwelling crayfish. Lacking from the literature are studies of landscape-level variables that may influence burrowing crayfish which rely solely on groundwater and seasonal inundation. An approach that incorporates geomorphological components may identify processes that contribute to watershed-wide patterns of burrowing crayfish biodiversity.

In Chapter 4, I used field surveys and geospatial data to determine if select landscape- scale environmental variables affect the distribution of burrowing crayfish in a Black Belt Prairie watershed in the Mobile River Basin in Alabama. I evaluated the presence of burrowing crayfish with respect to channel migration, channel sinuosity, floodplain connectivity, and land use, and assessed if species composition was related to distance to nearest stream, channel sinuosity, floodplain connectivity, or land use. I predicted that burrowers would be distributed in areas previously located in the channel’s migration trajectory, areas near streams with a greater sinuosity, areas with a greater floodplain connection, and areas with predominantly forested

5 areas. In Chapter 5, I summarize by findings of burrowing crayfish behavior, local site selection, and landscape-level distribution in the Bogue Chitto Creek watershed and discuss future research directions.

Literature Cited Berrill, M. and B. Chenoweth. 1982. The burrowing ability of nonburrowing crayfish. American Midland Naturalist 108:199–201. Caine, E. A. 1978. Comparative ecology of epigean and hypogean crayfish (Crustacea: Cambaridae) from northwestern Florida. American Midland Naturalist 99:315–329. Camp, M. A., C. E. Skelton, and C. B. Zehnder. 2011. Population dynamics and life history characteristics of the Ambiguous Crayfish (Cambarus striatus). Freshwater Crayfish 18: 75-81. DiStefano, R. J., D. D. Magoulick, E. M. Imhoff, and E. R. Larson. 2009. Imperiled crayfishes use hyporheic zone during seasonal drying of an intermittent stream. Journal of the North American Benthological Society 28:142–152. Dorn, N. J. and J. C. Trexler. 2007. Crayfish assemblage shifts in a large drought-prone wetland: the roles of hydrology and competition. Freshwater Biology 52:2399–2411. Dorn, N. J., and J. C. Volin. 2009. Resistance of crayfish (Procambarus spp.) populations to wetland drying depends on species and substrate. Journal of the North American Benthological Society 28:766–777. Elkins, D., S. C. Sweat, B. R. Kuhajda, A. L. George, K. S. Hill, and S. J. Wenger. 2019. Illuminating hotspots of imperiled aquatic biodiversity in the southeastern US. Global Ecology and Conservation, 19:1-13. Grow, L. and H. Merchant. 1980. The burrow habitat of the crayfish, Cambarus diogenes diogenes (Girard). American Midland Naturalist 103:231–237. Heemeyer, J. L. and M. J. Lannoo. 2012. Breeding migrations in Crawfish Frogs (Lithobates areolatus): long-distance movements, burrow philopatry, and mortality in a near- threatened species. Copeia 2012:440–450. Heemeyer, J. L., P. J. Williams, and M. J. Lannoo. 2012. Obligate crayfish burrow use and core habitat requirements of crawfish frogs. Journal of Wildlife Management 76:1081-1091. Helms, B. S., W. Budnick, P. Pecora, J. Skipper, E. Kosnicki, J. Feminella, and J. Stoeckel. 2013a. The influence of soil type, congeneric cues, and floodplain connectivity on the local distribution of the devil crayfish (Cambarus diogenes (Girard)). Freshwater Science 32:1333-1344. Helms, B. S., C. Figiel, J. Rivera, J. Stoeckel, G. Stanton, and T. A. Keller. 2013b. Life-history observations, environmental associations, and soil preferences of the Piedmont Blue Burrower (Cambarus [Depressicambarus] harti) Hobbs. Southeastern Naturalist 12:143– 160.

6 Hobbs, H. H., Jr. 1981. The crayfishes of Georgia. Smithsonian Contributions to Zoology. No. 318. Smithsonian Institution, Washington, D.C., USA. Hopper, J. D. and A. D. Huryn. 2012. A new, non-destructive method for sampling burrowing crayfish. Southeastern Naturalist, 11:43-48. Jenkins, C. N., K. S. Van Houtan, S. L. Pimm, and J. O. Sexton. 2015. US protected lands mismatch biodiversity priorities. Proceedings of the National Academy of Sciences of the United States of America 112:5081-5086. Loughman, Z. J. 2010. Ecology of Cambarus dubius (upland burrowing crayfish) in northcentral West Virginia. Southeastern Naturalist 9:217–230. Loughman, Z. J., S. A. Welsh, and T. P. Simon. 2012. Occupancy rates of primary burrowing crayfish in natural and disturbed large river bottomlands. Journal of Crustacean Biology 32:557–564. March, T. S. and B. J. Robson. 2006. Association between burrow densities of two Australian freshwater crayfish (Egnaeus sericatus and Geocharax gracilis: Parastacidae) and four riparian land uses. Aquatic Conservation: Marine and Freshwater Ecosystems 16:181– 191. Neves, R. J. 1999. Conservation and commerce: Management of freshwater mussel (Bivalvia: Unionoidea) resources in the United States. Malacologica 4:461–474. Norrocky, M. J. 1984. Burrowing crayfish trap. Ohio Journal of Science, 84, 65-66. Norrocky, M. J. 1991. Observations on the ecology, reproduction, and growth of the burrowing crayfish Fallicambarus (C.) fodiens in north-central Ohio. American Midland Naturalist, 87:75–86. Pintor, L. M. and D. A. Soluk. 2006. Evaluating the nonconsumptive, positive effects of a predator in the persistence of an endangered species. Biological Conservation 130:584- 591. Reynolds, J., C. Souty-Grosset, and A. Richarson. 2013. Ecological roles of crayfish in freshwater and terrestrial habitats. Freshwater Crayfish 19:197-218. Richardson, A. M. M. 1983. The effects of burrows of a crayfish on the respiration of the surrounding soil. Soil Biology and Biochemistry 15:239–242. Richman, N. I., M. Böhm, S. B. Adams, F. Alvarez, E. A. Bergey, J. J. S. Bunn, Q. Burnham, J. Cordeiro, J. Coughran, K. A. Crandall, K. L. Dawkins, R. J. Distefano, N. E. Doran, L. Edsman, A. G. Eversole, L. Füreder, J. M. Furse, F. Gherardi, P. Hamr, D. M. Holdich, P. Horwitz, K. Johnston, C. M. Jones, J. P. G. Jones, R. L. Jones, T. G. Jones, T. Kawai, S. Lawler, M. López-Mejίa, R. M. Miller, C. Pedraza-Lara, A. M. M. Richardson, M. B. Schultz, G. A. Schuster, P. J. Sibley, C. Souty-Grosset, C. A. Taylor, R. F. Thoma, J. Walls, T. S. Walsh, and B. Collen. 2015. Multiple drivers of decline in the global status of freshwater crayfish (Decapoda: Astacidea). Philosophical Transactions of the Royal Society B: Biological Sciences 370:1–11. Ridge, J., T. P. Simon, D. Karns, and J. Robb. 2008. Comparison of three burrowing crayfish capture methods based on relationships with species morphology, seasonality, and habitat quality. Journal of Crustacean Biology 28:466-472.

7 Robertson, K. M. and D. L. Johnson. 2004. Vertical redistribution of pebbles by crayfish in mollisol catenas of central Illinois. Soil Science 169:776–786. Simon, T. P. 2001. Checklist of the crayfish and freshwater shrimp (Decapoda) of Indiana. Proceedings of the Indiana Academy of Science 110:104-110. Simon, T. P. 2004. Standard Operating Procedures for the Collection and Study of Burrowing Crayfish in Indiana. I. Methods for the Collection of Burrowing Crayfish in Streams and Terrestrial Habitats. Occasional Papers of the Indiana Biological Survey Aquatic Research Center 2:1-18. Stiles, R. M., T. R. Halliday, N. J. Engbrecht, J. W. Swan, and M. J. Lanoo. 2017. Wildlife cameras reveal high resolution activity patterns in threatened crawfish frogs (Lithobates areolatus). Herpetological Conservation and Biology 12:160-170. Stone, E. L. 1993. Soil burrowing and mixing by a crayfish. Soil Science Society of America Journal 57:1096–1099. Taylor, C. A. 2002. Taxonomy and conservation of native crayfish stocks. In Biology of freshwater crayfish, D. M. Holdich (Editor). Blackwell Scientific, Oxford, UK, pp. 236- 257. Taylor, C. A., and T. G. Anton. 1998. Distribution and ecological notes on some of Illinois’ burrowing crayfish. Transactions of the Illinois State Academy of Science 92:137-145. Taylor, C. A., G. A. Schuster, J. E. Cooper, R. J. Di Stefano, A. G. Eversole, P. Hamr, H. H. Hobbs, Jr., H. W. Robison, C. E. Skelton, and R. E. Thomas. 2007. A reassessment of the conservation status of crayfishes of the United States and Canada after 10+ years of increased awareness: Fisheries, 32:372–389. Taylor, R. C. 1983. Drought-induced changes in crayfish populations along a stream continuum. American Midland Naturalist 110:286–298 Warren, Jr., M. L., B. M. Burr, S. J. Walsh, H. L. Bart, Jr., R. C. Cashner, D. A. Etnier, B. J. Freeman, B. R. Kuhajde, R. L. Mayden, H. W. Robison, and W. D. Starnes. 2000. Diversity, distribution, and conservation status of the native freshwater fishes of the southern United States. Fisheries 25:7–31. Welch, S. M. and A. G. Eversole. 2006. Comparison of two burrowing crayfish trapping methods. Southeastern Naturalist 5:27-30. Welch, S. M., J. L Waldron, G. Eversole, and J. C. Simoes. 2008. Seasonal variation and ecological effects of Camp Shelby burrowing crayfish (Fallicambarus gordoni) burrows. American Midland Naturalist 159:378–384. Williams, D. D., N. E. Williams, and H. B. Hynes. 1974. Observations of the life history and burrow construction of the crayfish Cambarus fodiens (Cottle) in a temporary stream in southern Ontario. Canadian Journal of Zoology 52:365-370.

CHAPTER 2: MOTION-TRIGGERED LASER PHOTOGRAPHY REVEALS FINE- SCALE ACTIVITY PATTERNS IN BURROWING CRAYFISH Abstract Burrowing crayfish represent 15% of total crayfish species and 32% of imperiled species.

Few life history studies exist for these species, and more information is needed regarding their ecology, population status, distribution, and biogeography for effective conservation efforts.

Challenges to gaining such information include sampling difficulty and small sample sizes.

Collection efforts may be more efficient if activity patterns can be identified for species of interest. The goal of our study was to assess specific environmental indicators of burrowing crayfish activity patterns. We evaluated activity patterns of two primary burrowing crayfish species, Lacunicambarus erythrodactylus (Simon and Morris) and Procambarus holifieldi

(Schuster, Taylor and Adams) using laser-triggered digital photography for one-year periods in the Bogue Chitto Creek floodplain, Alabama, U.S.A. We predicted that activity would be related to time of day, season, groundwater depth, and precipitation. Activity by L. erythrodactylus covaried significantly with time of day, daylength, groundwater temperature, and relative air temperature, while activity by P. holifieldi covaried with time of day, season, groundwater temperature, and relative air temperature. Additionally, burrow chimney construction by P. holifieldi covaried with daylength, groundwater temperature, relative air temperature, and precipitation. Out-of-burrow activity for both species was greatest at night and during periods of relatively cool groundwater temperatures and relatively warm air temperatures, which may be linked to thermal regulation behavior. The probability of chimney construction by P. holifieldi increased with increasing daylength and decreasing precipitation and was highest during periods

9 of cool groundwater temperatures and air temperatures. A distinct lull in activity from October through March for both species likely was the result of reproductive behaviors such as period of egg production and incubation within burrows. Identifying peak out-of-burrow activity periods for burrowing crayfish will allow collection efforts to be focused on periods of greatest activity, thereby facilitating the study of burrowing crayfish biology.

Introduction The southeastern United States has an unusually high level of freshwater biodiversity, supporting almost 66% of the nation’s fish species, >90 % of the mussel species, and nearly 50% of the world’s crayfish species. More than 25% of mussel and crayfish species are endemic to this region (Jenkins et al. 2015, Elkins et al. 2019). This remarkable biodiversity and endemism, much of which is of conservation concern, warrants the attention of biologists and natural resource managers. Advances in crayfish research, in particular, are needed, as nearly 50% of the species in the southeastern United States are threatened or endangered (Taylor et al. 2007). This level of imperilment is especially relevant for the state of Alabama and its 99 documented species of crayfish, as some of these are limited to a single drainage and their ecology and behavior is still poorly understood (Neves 1999, Warren et al. 2000, Taylor 2002).

Crayfish are uniquely adapted to burrowing into benthic and terrestrial substrata, providing a vital link between aquatic and terrestrial environments. Crayfish burrowing can enhance soil mixing, increase soil habitat complexity (Robertson and Johnson 2004, Welch et al. 2008,

Reynolds et al. 2013), increase soil respiration (Richardson 1983, Stone 1993) and provide habitat for other species (Pintor and Soluk 2006, Loughman 2010). By providing habitat, crayfish burrows may also increase community diversity (Camp et al. 2011). Such effects are most prevalent for “primary” burrowers because they construct extensive subterranean labyrinths

10 that are often distant from surface water habitats (Hobbs 1981, Hasiotis 1993, Welch et al. 2008).

Burrower classification is based on the level of connection between their burrows and surface waters. Primary burrowers – the subjects of this study – spend most of the time in their burrows and rarely, if ever, enter surface waters (Hobbs 1981, Berrill and Chenoweth 1982, DiStefano et al. 2009). In contrast, “secondary” burrowers produce relatively simple burrows near, and often in, surface-water habitats, while “tertiary” burrowers construct even more basic burrows, often a single, blind tunnel in the bottom of a stream or pond used only for reproduction or avoidance of unfavorable environmental conditions (Hobbs 1981). Understanding the role of primary burrowing crayfish in driving a geomorphic interface between subsurface and terrestrial animal communities requires knowledge of their life history, distribution, population status, and ecological interactions (Taylor et al. 2007, Helms et al. 2013a,b). Regardless, primary burrowers remain under-studied (Williams et al. 1974, McGrath 1994, Loughman 2010).

One factor contributing to the paucity of studies of primary burrowing crayfish are difficulties in sampling them (Williams et al. 1974). Sampling methods include excavation

(Simon 2004), visual night searches (Hobbs 1981), vernal pool traps (Taylor and Anton 1998), a plunger method (Simon 2001), the Norrocky burrowing crayfish trap (Norrocky 1984), a funnel trap (Hopper and Huryn 2012), and entanglement nets (Welch and Eversole 2006). Ridge et al.

(2008) compared the efficiency and efficacy of excavation, the Norrocky burrowing crayfish trap, and entanglement nets and determined that excavation was the most successful, though this method destroys burrows and opportunities for subsequent sampling (Simon 2004), leaving room for methodological improvements. Laser-triggered, digital photography is a promising, non- destructive, non-invasive method that has been recently used to study species presence/absence

11 and activity patterns in aquatic systems (e.g., crawfish frogs: Heemeyer and Lannoo 2012,

Heemeyer et al. 2012, Stiles et al. 2017).

The sampling difficulty and resulting small sample size characterizing primary burrower research may also result from an imperfect understanding of their behavior. Collections, for example, may be more efficient if peak activity periods can be identified. Field studies linking year-round burrower behavior to possible environmental cues, however, are sparse. Most studies have revealed seasonal patterns in crayfish activity, but the timing of peak activity may be species-specific (Norrocky 1991, Ridge et al. 2008, Camp et al. 2011).

To assess if burrowing crayfish behavior can be linked to environmental cues, we used laser-triggered, digital photography to evaluate fine-scale temporal activity patterns of two primary burrowing crayfish species, Lacunicambarus erythrodactylus (Simon and Morris) and

Procambarus holifieldi (Schuster, Taylor and Adams). These species were chosen based on the availability of year-round access to study populations in the Bogue Chitto Creek drainage,

Alabama, which is known to harbor six species of primary burrowers (McGregor et al. 2018).

We evaluated the activity patterns of L. erythrodactylus and P. holifieldi as a function of selected environmental variables using laser-triggered, digital photography. Emergence time, activity duration, and activity type were recorded for a 12-month period for a total of 35 individuals of each species. We then compared activity to abiotic environmental variables, including daylength, season, groundwater depth, groundwater temperature, air temperature, and precipitation. We hypothesized that burrower activity would be related to time of day, season, precipitation, and groundwater depth (Helms et al. 2013a,b). We predicted that activity would be primarily nocturnal and would be most prevalent following rainfall events. We also predicted that activity would follow a seasonal pattern, with highest activity levels during the spring (when

12 groundwater depth is low and air temperatures are relatively high), and relatively low activity in the summer (due to high groundwater depth) and winter (due to low temperatures).

Methods Study area This study was conducted in the Bogue Chitto Creek watershed in the Black Belt Prairie region of the Coastal Plain of Alabama. The Black Belt Prairie is a subdistrict of the East Gulf

Coastal Plain Physiographic Province (Sapp and Emplaincourt 1975), covering more than 20,719 square kilometers across Alabama, Mississippi, and Tennessee. The Bogue Chitto Creek watershed contains 10 Hydrologic Unit Code (HUC) 12 subwatersheds containing 97 km of stream length. Bogue Chitto Creek terminates at the Alabama River. Our study area was in the

Lower Bogue Chitto Creek subwatershed. Here the land use is 37% forest, 33% wetlands, and

14% agriculture (USDA NRCS 2016). We chose two intensive monitoring sites on the lower

Bogue Chitto Creek floodplain near Orrville, Alabama. These were ~20 m2 and similar in floodplain, soil, and groundwater characteristics according to the National Resources

Conservation Service’s SSURGO database (Soil Survey Staff 2015, Appendix 2.1). Site 1 contained a population of L. erythrodactylus, while Site 2 contained a population of P. holifieldi.

Study organisms Fourteen species of crayfish are known from the Bogue Chitto Creek watershed

(McGregor et al. 2018), six of which are considered primary burrowers: Creaserinus fodiens

(Cottle), L. erythrodactylus, L. ludovicianus (Faxon), L. dalyae (Glon, Williams & Loughman),

Procambarus hagenianus hagenianus (Faxon), and P. holifieldi. Classified as a primary burrower in most habitats, L. erythrodactylus is a member of the Lacunicambarus diogenes species complex and can be found in Alabama and Mississippi, with populations occurring more

13 generally in low-lying woodland areas near rivers, streams and ponds (Simon and Morris 2014).

Members of this species complex construct complex burrows, often with chimneys at the openings (Tarr 1884, Hobbs and Hart 1959, Grow and Merchant 1980, Grow 1982). Burrows are typically found in clay-based soils and have depths ranging from 15 cm to 5 m, depending on groundwater depth; burrow water is often hypoxic or anoxic (Grow and Merchant 1980).

Procambarus holifieldi is a recently described primary burrower found only in Perry County,

Alabama (Schuster et al. 2015). It was originally discovered in a field within a power line easement (Schuster et al. 2015) with poorly drained, Blackland Prairie soils (Harris 1998).

Schuster et al. (2015) excavated several burrows at this location and found them to be complex in structure with a main channel leading to an opening with a chimney at the surface. Schuster et al. (2015) also noted that the main burrow channel had several side channels that also opened at the surface. No additional life history information is available for this species.

Photography We monitored crayfish activity at Site 1 from March 2017 to March 2018 and at Site 2 from May 2018 to May 2019. At each site, we selected 35 active burrows, as indicated by evidence of recent excavation by crayfish. Each week, five burrows were randomly selected for activity monitoring by placing a motion-sensitive Sabre (Cognysis, Traverse City, MI) laser trigger and Rebel (Canon, Oita, Japan) T5 camera near each burrow (Fig. 2.1). The laser triggers engaged whenever motion was detected at a burrow entrance and a photograph was taken. The triggers were mounted on tripods and waterproofed with plastic bags and rubber bands while the cameras were housed in waterproof plastic food storage containers modified with a PVC pipe cutout to allow for the lens. Each camera housing unit was strapped to a concrete block to deter accidental displacement by wind or wildlife. Triggers were placed directly next to burrow

14 entrances while cameras were placed at distances ensuring a quality photo. Cameras and triggers were used to continuously monitor (i.e., 24 hrs/d) each week’s focal burrows. Following a weekly cycle, cameras and triggers were moved to a different set of five randomly chosen burrows, photos were downloaded, memory cards were downloaded and replaced, and time- stamped images were transferred to a laptop computer for later analysis.

We classified crayfish in each photograph as “active” (crayfish was visible either outside its burrow or at the burrow entrance) or “inactive” (camera was triggered from movement in the environment, not crayfish activity). We considered a crayfish active even if it did not move between consecutive photos. We recorded the type of activity exhibited by the individual in the photograph as either “emergence” (individuals visible outside the burrow or at the burrow entrance) or “chimney construction” (individuals in the process of excavating soil and creating chimneys). For descriptive analyses, we recorded activity start and end times and calculated activity duration. For analysis of environmental covariates of crayfish activity, we collapsed active and inactive data points by hour of the day. A burrow was considered “active” for a given date/hour if a photographed crayfish was active in that time period. A burrow was considered

“inactive” if all photographs were “inactive” or if no photographs were taken (i.e., no triggering of the motion-activated sensor).

Environmental data We recorded environmental data at 1-hour intervals to match the data on crayfish activity.

We measured air temperature and precipitation using an on-site continuous HOBO rain gauge

(Onset, Pocasset, MS). We recorded hourly groundwater depth and groundwater temperature using a HOBO water level logger placed in a shallow monitoring well installed at each of the

15 study sites. We obtained daylength statistics from https://sunrise-sunset.org/us/orrville-al. We assigned seasons based on the meteorological calendar.

Data analysis We used generalized linear mixed effect models (GLMMs) with a binomial error structure (R version 3.5.2, R Core Team, 2018) to evaluate which environmental predictors were correlated with burrowing crayfish activity. We first analyzed environment predictors of crayfish activity, ignoring activity type (chimney construction vs. emergence). Data from L. erythrodactylus and P. holifieldi were analyzed separately, and burrow number was included as a random effect in all models to control for the non-independence of observations made at the same burrow. We considered the following environmental predictors (fixed effects): time (a 24- level factor), daylength, season (a four-level factor), groundwater depth, groundwater temperature, air temperature, and precipitation. All continuous variables were standardized (to a mean of 0 and a standard deviation of 1) prior to analysis to put them on a common scale. Before fitting the GLMMs, we evaluated our predictor variables for multicollinearity. Because air temperature was highly correlated with daylength (r = 0.67, d.f. = 27,425, p = << 0.001 for L. erythrodactylus; r = 0.55, d.f. = 17,028, p = << 0.001 for P. holifieldi), and varied with time of day (visually assessed for both species), we used the residuals from a linear model predicting air temperature by time and daylength (“relative air temperature”) in place of air temperature in our models. Although air temperature was correlated with groundwater depth (r = 0.56, d.f.= 27,425, p = <<0.001) for L. erythrodactylus, residual air temperature was less so (r = 0.23, d.f. = 27,245, p = <<0.001). Groundwater depth and groundwater temperature were also highly correlated with one another when the data for both species was analyzed (r = 0.66, d.f. = 27,425, p = << 0.001 for L. erythrodactylus; r = 0.95, d.f. = 17,028, p = << 0.001 for P. holifieldi); we never included

16 these two predictors in the same model. Because daylength varies with season, we never included these two predictors in the same model.

We first constructed four global models for each crayfish species incorporating time, daylength or season, precipitation, relative air temperature and either groundwater temperature or groundwater depth as linear predictors of crayfish activity. The importance of each environmental variable as a predictor of crayfish activity was assessed by comparing the performance of the most general model to that of simpler candidate models (excluding one or more predictors) using Akaike’s information criterion (AIC, Akaike 1974). We included all possible subsets of the global models in each species’ candidate model set. The model that best explained the variation in the data was the model with the lowest AIC value (Burnham and

Anderson 2002). We disregarded all models greater than a delta AIC of 2 from our top model set if they were more complex versions of a nested model with a lower AIC (sensu Burnham and

Anderson 2002, Richards et al. 2011). There were 64 models in the candidate set for L. erythrodactylus and 64 models in the candidate set for P. holifieldi. We assessed model fit by estimating marginal and conditional R-squared values (Nakagawa and Scheilzeth 2013), by determining if the random effects showed a normal distribution, and by plotting model residuals versus the fitted values and each covariate. During model validation, visual inspection of a plot of the residuals against daylength suggested that a linear relationship between crayfish activity and daylength was inadequate for L. erythrodactylus (Zuur et al. 2012). We ran additional models fitting activity as a quadratic function of daylength (daylength + daylength2); these models outperformed those omitting the quadratic term for daylength (see results).

In a second stage of analysis, we retained only active data points for P. holifieldi and analyzed environmental effects on the probability of observing chimney construction (vs.

17 emergence) behavior. We used an identical approach to that described above: models were binomial GLMMs with a random effect of burrow, the fixed effects included in the global models were identical to the first analysis stage (time, daylength or season, groundwater depth or groundwater temperature, relative air temperature, and precipitation), continuous covariates were standardized, and AIC was used to rank candidate models and evaluate the importance of each predictor on the probability that the behavior was chimney construction, given that the burrow was active. Activity type could not be analyzed in L. erythrodactylus because chimney construction behavior was very rare (< 9% of cases).

Results We analyzed 113,833 digital photos based on 44,555 hours of sampling. A total of

74,919 photos representing 27,605 hours of sampling were analyzed for L. erythrodactylus, while 38,914 photos representing 16,950 hours of sampling were analyzed for P. holifieldi

(Appendix 2.2). The study site for P. holifieldi could not be accessed during portions of

November and December 2018, and January 2019 due to restrictions related to hunting season.

Lacunicambarus erythrodactylus We observed specimens of L. erythrodactylus outside burrows every month of the year except January, with most activity occurring from March to September (Fig. 2.2A,C). Activity bouts lasted 8.8 hours on average (range 5 minutes to 19.4 hours). Only 8.7 % of observations included chimney construction. Bouts of chimney construction lasted from 5 minutes to 9.8 hours, averaging 6.9 hours per bout. Emergence behavior lasted 5 minutes to 19.3 hours in duration, with an average bout length of 8.9 hours.

The best-supported model (i.e., lowest AIC value) indicated that the probability of L. erythrodactylus activity is predicted by the time of day, daylength, groundwater temperature, and

18 relative air temperature (Table 2.1). The probability of out-of-burrow activity was highest from 8 pm to 4 am (Fig. 2.3A). The probability of out-of-burrow activity increased with increasing daylength (β = 1.78, SE = 0.06, p << 0.001; daylength2 β = -0.59, SE = 0.04, p << 0.001; Fig.

2.3C) and decreased with increasing groundwater temperature (β = -0.17, SE = 0.04, p << 0.001;

Fig. 2.3E). The probability of out-of-burrow activity also increased when air temperatures were relatively warm for a given time of year and time of day (β = 1.08, SE = 0.08 p << 0.001; Fig.

2.3G). A more complex model that included precipitation as a predictor of crayfish activity (but was otherwise identical to the top model) fell within Δ2 AIC of the top model (Table 2.1).

Precipitation did not significantly explain variation in crayfish activity, however (β = 0.01, SE =

0.02, p = 0.78; Fig. 2.3I), and this more complex model scored well simply because only 2 AIC units are added to a model’s AIC value for each additional predictor (Burnham and Anderson

2002).

Procambarus holifieldi We observed P. holifieldi outside burrows every month of the year with most activity occurring from March to September (Fig. 2.2B, D). Activity bouts lasted 10.2 hours on average

(range = 4 minutes to 30.7 hours). In contrast to L. erythrodactylus, which showed limited chimney construction activity, chimney construction was observed in 60% of the photos of P. holifieldi activity, while emergence behavior was observed in 40% of the photos. Periods of chimney construction averaged 10.8 hours (range = 5 minutes to 30.7 hours). Bouts of emergence activity averaged 9.3 hours (range = 4 minutes to 29.4 hours).

The best-supported model indicated that out-of-burrow activity by P. holifieldi covaried with the time of day, season, groundwater temperature, and relative air temperature (Table 2.1).

Crayfish showed most out-of-burrow activity from 7 pm to 6 am (Fig. 2.3B). Activity was

19 highest in the fall (β = -0.96, SE = 0.24, p << 0.001; Fig. 2.3D). The probability of out-of-burrow activity increased when groundwater temperatures were relatively cool (β = -0.28, SE = 0.08 p

<< 0.001; Fig. 2.3F) and when air temperatures were relatively warm for a given time of year and time of day (β = 0.16, SE = 0.06, p = 0.004; Fig. 2.3H). As with L. erythrodactylus, a more complex model (identical to the top model except including precipitation) fell within Δ2 AIC units of the top model but was disregarded because precipitation did not significantly covary with activity (β = -0.005, SE = 0.03, p = 0.88; Fig. 2.3J).

We found that the best-supported model for P. holifieldi indicated that daylength, groundwater temperature, relative air temperature, and precipitation were correlated with crayfish chimney construction activity (Table 2.1). The probability of chimney construction activity vs. emergence activity increased with increasing daylength (β = 0.24, SE = 0.09, p =

0.01; Fig. 2.4A). Replacing daylength with the factor "season" did not improve model performance (delta AIC = 1.33) and gave a similar result: chimney construction activity was highest in the summer and fall (Fig. 2.4B). The probability of observing chimney construction activity also increased with decreasing precipitation (β = -0.40, SE = 0.08, p << 0.001; Fig. 2.4E) and decreasing groundwater temperature (β = -0.31, SE = 0.08, p << 0.001; Fig. 2.4C). The probability of observing chimney construction also increased when air temperatures were relatively cool for a given time of year and time of day (β = -0.23, SE = 0.09, p = 0.01, Fig.

2.4D).

Discussion The substantial energy investment required for burrow construction by crayfish indicates the fitness advantage that burrows offer, especially for species of primary burrowers that construct extensive subterranean labyrinths (Reynolds et al. 2013). Out-of-burrow activity may

20 be accompanied by an increased risk of mortality from predation and dehydration, explaining this fitness advantage of sheltering in burrows. Observed out-of-burrow activity (e.g., in this study) thus suggests such activities must be critical for survival and reproduction. Although there is little information on why primary burrowers leave their burrows, given the apparent risks, we suggest that incentives for leaving burrows fall into two general categories: access to food and access to mates. Understanding the relationship between such out-of-burrow activity and possible environmental cues is a crucial first step toward addressing some of the most basic, and largely unanswered, questions concerning burrowing crayfish biology.

The goal of our study was to evaluate if specific environmental cues predicted out-of- burrow activity patterns for two primary burrowing crayfish species. Our results confirmed our prediction that burrower activity would be influenced by time of day. Both L. erythrodactylus and P. holifieldi showed strong diel patterns that were characterized by primarily nocturnal activity. Seasonal patterns of activity, however, were more complex than expected. We predicted that out-of-burrow activity would be highest in the spring when groundwater depths are shallow and air temperatures are relatively high and that activity would be low during the summer (due to deep groundwater depths) and winter (due to low air temperatures). Out-of- burrow activity was lowest during winter for both species and increased with daylength for L. erythrodactylus, but was highest in the fall, not the spring, for P. holifieldi. Following our predictions, activity was positively related to relative air temperature, but the lack of a relationship between precipitation and activity, as previously shown for C. fodiens in Ohio,

U.S.A., by Norrocky (1991), was unanticipated. Groundwater temperature predicted activity better than groundwater depth, although these two variables were highly positively correlated.

21 Contrary to expectations, out-of-burrow activity decreased with increasing groundwater temperature.

Water temperature provides an important cue used to control life history events for aquatic invertebrates (Vannote and Sweeney 1980). In the case of burrowing crayfish—which use both aquatic and terrestrial habitats—this cue may be problematic, however, due to the seasonal lag of peak groundwater temperature compared with air temperature. In our study, for example, groundwater temperatures were lowest during March and April and highest during

November (Fig. 2.2). Rather than showing positive relationships between groundwater temperature and activity, L. erythrodactylus and P. holifieldi both showed negative relationships, with peak out-of-burrow activity during periods of the coolest groundwater temperatures and low levels of out-of-burrow behavior in the late fall when groundwater temperature are relatively high. In contrast, out-of-burrow activity was positively related to relative air temperature, with out-of-burrow activity being more probable during periods of warmer weather. Thus air temperature rather than groundwater temperature may be the more important seasonal cue driving out-of-burrow activity. Although we are unable to explicitly demonstrate a functional link between groundwater temperature, air temperature, and crayfish behavior, our analyses suggest that the observed seasonal pattern of activity may be linked to thermal regulation. Out- of-burrow behavior in the spring may expose crayfish to warm air temperatures at a time when groundwater temperatures are cool (i.e., during April – May). Similarly, out-of-burrow activity, if linked to thermoregulation, would not be expected when groundwater temperatures are relatively high and air temperatures are low (i.e., during November), which is in accordance with our observations. Camp et al. (2011) similarly showed that out-of-burrow activity by the burrowing crayfish Cambarus striatus Hay in Georgia, U.S.A., was greatest during the spring

22 and early summer and proposed that photoperiod or temperature may be the seasonal cues driving activity. We suggest that groundwater and air temperature may interact to drive seasonal activity and that thermal regulation may be a third potential advantage of out-of-burrow behavior, in addition to foraging and mating behaviors.

There were striking differences in the frequency of chimney building activity between species, with P. holifieldi showing this behavior in 60% of the photographs of activity, while L. erythrodactylus was observed building chimneys in only 9% of the photographs. For burrowing crayfish, chimney construction is evidence of active burrow construction, with the chimney being constructed from pellets of soil that are excavated to form the burrow. More than half

(54%) of chimney construction behavior for P. holifieldi occurred from June through November when groundwater depths are at an annual maximum and active burrowing is presumably required to maintain contact with the groundwater supply (Fig. 2.5). Helms (2013b), for example, found that burrowing activity for populations of Cambarus harti Hobbs in Georgia,

U.S.A, increased with receding groundwater levels during summer. If chimney construction activity is influenced by a change in groundwater depth, the differences in the frequency of chimney construction activity by L. erythrodactylus and P. holifieldi may be due to possible differences in water table levels for the different years of sampling. More precipitation fell within the Bogue Chitto watershed during 2017-2018 than 2018-2019 (Fig. 2.2), which may in part explain why the water table at the L. erythrodactylus site ranged from 12 to 119 cm below the surface in 2017-2018, while the water table level at the P. holifieldi site was much deeper and ranged from 42 to 284 cm below the surface in 2018-2019. The environmental data collected during this study is especially useful for future research efforts targeting P. holifieldi, as this is only the second population to be documented. The type locality was cited as having a water table

23 ranging from 15 to 45 cm below the surface from January to April (Harris 1998). Our study showed a much deeper water table range for this species (42 to 284 cm).

One key finding of this study that may help elucidate some of the unknowns regarding burrower biology is when out-of-burrow activity was not observed. The distinct lull in activity from October through March for both L. erythrodactylus and P. holifieldi may reflect individuals devoting time to reproduction. Mating behavior has been shown to influence activity cycles for burrowing crayfish. Camp et al. (2011), for example, captured Form I males of C. striatus during spring and fall. Additionally, life history studies for L. erythrodactylus indicate that mating likely occurs from late fall through winter, when a higher proportion of the population becomes reproductively active (Ortman 1906, Hobbs 1942, Hobbs and Jass 1988, Miller et al. 2014). In

Alabama, females with active glair glands were collected from November through January, and ovigerous females were collected in late February and early March (Miller et al. 2014). It is likely that the lull in activity observed in our study is linked to mating behavior and is presumably due to mated females sequestering in their burrows during egg and juvenile development. Since our models agree that groundwater temperature is a driver for activity for both L. erythrodactylus and P. holifieldi, perhaps primary burrowers are using warmer groundwater temperatures as a more suitable thermal environment for egg and juvenile development.

Primary burrowers comprise 15% of total crayfish species but constitute 32 percent of imperiled crayfish (Welch and Eversole 2006). In Alabama, 17 of the 99 known species are classified as primary burrowers. This study targeted two of these species using laser-triggered, digital photography, a non-invasive, non-destructive survey method that allowed for large sample sizes and repeated monitoring. The capability to collect year-round data for these

24 burrowers was key to identifying seasonal activity cycles for L. erythrodactylus and P. holifieldi.

This method has contributed toward understanding what mechanisms may drive primary burrowing crayfish behavior. Identifying peak activity periods for primary burrowing crayfish will allow scientists and managers to focus collection efforts during the most active periods. If populations can be sampled more effectively, some of the main challenges associated with primary burrowing crayfish research, namely sampling difficulty and small sample size, can potentially be alleviated. Additional behavior studies for these and other primary burrowing crayfish species will help spur the advancement of ecological and life history studies that are vital to conservation efforts for these unique organisms.

Acknowledgments This work was supported by the University of Alabama and the Geological Survey of

Alabama. We thank landowners Chris Weaver and Luis de Hechavaria for the permission to access private property; and Chris Weaver and property manager Lee Mims for assisting with data collection. Dr. John Abbot (Alabama Museum of Natural History, Tuscaloosa, AL) provided useful technical advice concerning camera deployments. This project was conducted in accordance with the Alabama Department of Natural Resources Scientific Collection Permit

Number 2018030883468680. The authors declare no conflict of interest.

Literature Cited Akaike, H. 1974. A new look at the statistical model identification. Institute of Electrical and Electronics Engineers Transactions on Automatic Control, 19:716–723. Berrill, M. and B. Chenoweth. 1982. The burrowing ability of nonburrowing crayfish. American Midland Naturalist, 108:199–201. Burnham, K. P. and D. R. Anderson. 2002. Model selection and multimodel inference: A practical information-theoretic approach (2nd ed.). Springer, New York, NY, USA. Camp, M. A., C. E. Skelton, and C. B. Zehnder. 2011. Population dynamics and life history characteristics of the Ambiguous Crayfish (Cambarus striatus). Freshwater Crayfish 18:75-81.

25 DiStefano, R. J., D. D. Magoulick, E. M. Imhoff, and E. R. Larson. 2009. Imperiled crayfishes use hyporheic zone during seasonal drying of an intermittent stream. Journal of the North American Benthological Society 28:142–152. Elkins, D., S. C. Sweat, B. R. Kuhajda, A. L. George, K. S. Hill, and S. J. Wenger. 2019. Illuminating hotspots of imperiled aquatic biodiversity in the southeastern US. Global Ecology and Conservation, 19:1-13. Glon, M. G., R. F. Thoma, C. A. Taylor, M. Daly, and J. V. Freudenstein. 2018. Molecular phylogenetic analysis of the devil crayfish group, with elevation of Lacunicambarus Hobbs, 1969 to generic rank and a redescription of the devil crayfish, Lacunicambarus diogenes (Girard, 1852) comb. nov. (Decapoda: Astacoidea: Cambaridae). Journal of Crustacean Biology 38:600-615. Grow, L. 1981. Burrowing behavior in the crayfish, Cambarus diogenes (Girard). Animal Behavior 29:351-356. Grow, L. 1982. Burrowing/soil-texture relationships in the crayfish, Cambarus diogenes diogenes Girard (Decapoda, Astacidae). Crustaceana 42:150–157. Grow, L. and H. Merchant. 1980. The burrow habitat of the crayfish, Cambarus diogenes diogenes (Girard). American Midland Naturalist 103:231–237. Harris, M. C. 1998. Soil Survey of Perry County, Alabama, U.S. Department of Agriculture, Washington, D.C., USA. Hasiotis, S. T. 1993. Evaluation of the burrowing behavior of stream and pond dwelling species of Orconectes in the Front Range of Boulder, Colorado USA: their ethological and geological implications. Freshwater Crayfish 9:399–406. Heemeyer, J. L. and M. J. Lannoo. 2012. Breeding migrations in Crawfish Frogs (Lithobates areolatus): long-distance movements, burrow philopatry, and mortality in a near threatened species. Copeia 2012:440–450. Heemeyer, J. L., P. J. Williams, and M. J. Lannoo, M. J. 2012. Obligate crayfish burrow use and core habitat requirements of crawfish frogs. Journal of Wildlife Management 76: 10811091. Helms, B. S., W. Budnick, P. Pecora, J. Skipper, E. Kosnicki, J. Feminella, and J. Stoeckel. 2013a. The influence of soil type, congeneric cues, and floodplain connectivity on the local distribution of the devil crayfish (Cambarus diogenes (Girard)). Freshwater Science 32:1333-1344. Helms, B. S., C. Figiel, J. Rivera, J. Stoeckel, G. Stanton, and T. A. Keller. 2013b. Life-history observations, environmental associations, and soil preferences of the Piedmont Blue Burrower (Cambarus [Depressicambarus] harti) Hobbs. Southeastern Naturalist 12:143– 160. Hobbs, H. H., Jr. 1942. The Crayfishes of Florida. University of Florida Biological Publications, Biological Science Series 3. Gainesville, FL, USA. Hobbs, H. H., Jr. 1981. The crayfishes of Georgia. Smithsonian Contributions to Zoology. No. 318. Smithsonian Institution, Washington, D.C., USA.

26 Hobbs, H. H., Jr. and G. W. Hart. 1959. Freshwater decapod crustaceans of the Apalachicola drainage system in Florida, South Alabama, and Georgia. Bulletin of Florida State Museum 4:145–192. Hobbs, H. H., III and J. P. Jass. 1988. The crayfishes and shrimp of Wisconsin. Miscellaneous Publications of the Milwaukee Public Museum 5:2. Hopper, J. D. and A. D. Huryn. 2012. A new, non-destructive method for sampling burrowing crayfish. Southeastern Naturalist 11:43-48. Jenkins, C. N., K. S. Van Houtan, S. L. Pimm, and J. O. Sexton. 2015. US protected lands mismatch biodiversity priorities. Proceedings of the National Academy of Sciences of the United States of America 112:5081-5086. Loughman, Z. J. 2010. Ecology of Cambarus dubius (upland burrowing crayfish) in northcentral West Virginia. Southeastern Naturalist 9:217–230. Maloney, K. M. and T. P. Simon. 2015. Occupancy, activity, and relationships to watershed factors in predicting burrow fidelity in the digger crayfish Fallicambarus fodiens (Cottle, 1863). Journal of Crustacean Biology 35:177-184. McGrath, C. 1994. Status survey for the Greensboro burrowing crayfish. Proceedings of the Annual Conference/Southeastern Association of Fish and Wildlife Agencies 48:343-349. McGregor, S. W., G. A. Schuster, C. A. Taylor, R. A. Bearden, and E. A. Wynn. 2018. An updated report on the distribution and conservation status of the Alabama crayfish fauna. Geological Survey of Alabama Open-file report 1801. University of Alabama Press, Tuscaloosa, AL, USA. Miller, J. M., B. B. Niraula, E. G. Reategui-Zirena, and P. M. Stewart. 2014. Life history and physical observations of primary burrowing crayfish (Decopoda: Cambaridae) Cambarus (Lacunicambarus) diogenes and Cambarus (Tubericambarus) polychromatus. Journal of Crustacean Biology 34:15-24. Monroe, W. H. 1941. Notes on deposits of Selma and Ripley age in Alabama. Alabama Geological Survey Bulletin 48. University of Alabama Press, Tuscaloosa, AL, USA. Nakagawa S. and H. A. Schielzeth. 2013. A general and simple method for obtaining R2 from generalized linear mixed-effects models. Methods in Ecology and Evolution 4:133-142. Neves, R. J. 1999. Conservation and commerce: Management of freshwater mussel (Bivalvia:Unionoidea) resources in the United States. Malacologica 4:461–474. Norrocky, M. J. 1984. Burrowing crayfish trap. Ohio Journal of Science 84:65-66. Norrocky, M. J. 1991. Observations on the ecology, reproduction, and growth of the burrowing crayfish Fallicambarus (C.) fodiens in north-central Ohio. American Midland Naturalist 87:75–86. Ortmann, A. E. 1906. The crawfishes of the State of Pennsylvania. Memoirs of the Carnegie Museum of Natural History 2:480-486. Pflieger, W. L. 1996. The Crayfishes of Missouri. Missouri Department of Conservation, Jefferson City, MO, USA.

27 Pintor, L. M. and D. A. Soluk, D. A. 2006. Evaluating the nonconsumptive, positive effects of a predator in the persistence of an endangered species. Biological Conservation 130:584- 591. R Core Team. 2018. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. Reynolds, J., C. Souty-Grosset, and A. Richardson. 2013. Ecological roles of crayfish in freshwater and terrestrial habitats. Freshwater Crayfish 19:197-218. Richards, S. A., M. J. Whittingham, and P. A. Stephens. 2011. Model selection and model averaging in behavioral ecology: the utility of the IT-AIC framework. Behavioral Ecology and Sociobiology 65:77-89. Richardson, A. M. M. 1983. The effects of burrows of a crayfish on the respiration of the surrounding soil. Soil Biology and Biochemistry 15:239–242. Ridge, J., T. P. Simon, D. Karns, and J. Robb. 2008. Comparison of three burrowing crayfish capture methods based on relationships with species morphology, seasonality, and habitat quality. Journal of Crustacean Biology 28:466-472. Robertson, K. M. and D. L. Johnson. 2004. Vertical redistribution of pebbles by crayfish in mollisol catenas of central Illinois. Soil Science 169:776–786. Sapp, C. D. and J. Emplaincourt. 1975. Physiographic regions of Alabama: Geological Survey of Alabama Special Map 168. University of Alabama Press, Tuscaloosa, AL, USA. Schuster, G. A, C. A. Taylor, and S. B. Adams. 2015. Procambarus (Girardiella) holifieldi, a new species of crayfish (Decapoda: Cambaridae) from Alabama with a revision of the Hagenianus Group in the subgenus Girardiella. Zootaxa 4021:001–032. Simon, T. P. 2001. Checklist of the crayfish and freshwater shrimp (Decapoda) of Indiana. Proceedings of the Indiana Academy of Science 110:104-110. Simon, T. P. 2004. Standard Operating Procedures for the Collection and Study of Burrowing Crayfish in Indiana. I. Methods for the Collection of Burrowing Crayfish in Streams and Terrestrial Habitats. Miscellaneous Papers of the Indiana Biological Survey Aquatic Research Center Number 3. Simon, T. P. and C. C. Morris. 2014. Cambarus (Lacunicambarus) erythrodactylus, a new species of crayfish (Decapoda: Cambaridae) of the Cambarus diogenes complex from Alabama and Mississippi, U.S.A. Proceedings of the Biological Society of Washington 127:572-584. Soil Survey Staff. Natural Resources Conservation Service. United States Department of Agriculture. Soil Survey Geographic (SSURGO) Database. https://sdmdataaccess.sc.egov.usda.gov. Accessed on 15 August 2015. Stiles, R. M., T. R. Halliday, N. J. Engbrecht, J. W. Swan, and M. J. Lanoo. 2017. Wildlife cameras reveal high resolution activity patterns in threatened crawfish frogs (Lithobates areolatus). Herpetological Conservation and Biology 12:160-170. Stone, E. L. 1993. Soil burrowing and mixing by a crayfish. Soil Science Society of America Journal 57:1096–1099.

28 Tarr, R. S. 1884. Habits of the burrowing crayfishes in the United States. Nature 30L:127–128. Taylor, C. A. 2002. Taxonomy and conservation of native crayfish stocks. Pages 236-237 in D. M. Holdich (editor). Biology of freshwater crayfish. Blackwell Science Ltd., Oxford, UK. Taylor, C. A. and T. G. Anton. 1998. Distribution and ecological notes on some of Illinois’ burrowing crayfish. Transactions of the Illinois State Academy of Science 92:137-145. Taylor, C. A., G. A. Schuster, J. E. Cooper, R. J. Di Stefano, A. G. Eversole, P. Hamr, H. H. Hobbs, Jr., H. W. Robison, C. E. Skelton, and R. E. Thomas. 2007. A reassessment of the conservation status of crayfishes of the United States and Canada after 10+ years of increased awareness: Fisheries, 32:372–389. U.S. Department of Agriculture Natural Resources Conservation Service. 2016. National Land Cover Dataset. National Geospatial Center of Excellence. http://datagateway.nrcs.usda.gov/GDGOrder.aspx. Accessed on 1 December 2019. Vannote, R. L. and B. W. Sweeney. 1980. Geographic analysis of thermal equilibria: a conceptual model for evaluating the effect of natural and modified thermal regimes on aquatic insect communities. The American Naturalist 115:667-695. Warren, Jr., M. L., B. M. Burr, S. J. Walsh, H. L. Bart, Jr., R. C. Cashner, D. A. Etnier, B. J. Freeman, B. R. Kuhajde, R. L. Mayden, H. W. Robison, and W. D. Starnes. 2000. Diversity, distribution, and conservation status of the native freshwater fishes of the southern United States. Fisheries 25:7–31. Welch, S. M. and A. G. Eversole. 2006. Comparison of two burrowing crayfish trapping methods. Southeastern Naturalist 5:27-30. Welch, S. M., J. L. Waldron, G. Eversole, and J. C. Simoes. 2008. Seasonal variation and ecological effects of Camp Shelby burrowing crayfish (Fallicambarus gordoni) burrows. American Midland Naturalist 159:378–384. Williams, D. D., N. E. Williams, and H. B. Hynes. 1974. Observations of the life history and burrow construction of the crayfish Cambarus fodiens (Cottle) in a temporary stream in southern Ontario. Canadian Journal of Zoology 52:365-370. Zuur, A., E. N. Ieno, N. J. Walker, A. A. Savaliev, and G. M. Smith. 2012. Mixed Effects Models and Extensions in Ecology with R. Springer, New York, NY.

29 Table 2.1. Top candidate models ranked by AIC describing variation in Lacunicambarus erythrodactylus activity, Procambarus holifieldi activity, and chimney construction activity for P. holifieldi. K = the number of parameters, ΔAIC = the difference in AIC value for each model, relative to the top model, wi = Akaike’s model weight. All models included burrow as a random effect. Only models falling within Δ2 AIC are included.

Model K AIC ΔAIC wi Lacunicambarus erythrodactylus activity time + daylength + daylength2 + groundwater temp + relative air temp 29 9,906.29 0 0.69 time + daylength + daylength2 + groundwater temp + relative air temp + precip 30 9,908.22 1.93 0.26 Procambarus holifieldi activity time + season + groundwater temp + relative air temp 30 10,953.4 0 0.68 time + season + groundwater temp + relative air temp + precip 31 10,955.4 1.98 0.25 Procambarus holifieldi chimney construction daylength + groundwater temp + relative air temp + precip 6 2,430.64 0 0.52 season + groundwater temp + relative air temp + precip 8 2,431.97 1.33 0.27

Figure 2.1. Camera and laser-trigger setup used to monitor crayfish activity at each burrow.

Figure 2.2. Year-round activity for Lacunicambarus. erythrodactylus (left column) and Procambarus holifieldi (right column) for emergence and chimney construction behavior with corresponding daylength, groundwater temperature, and precipitation.

Figure 2.3. Model-estimated relationships (in black) between the probability of a burrow being active and statistically supported environmental predictors and precipitation for Lacunicambarus erythrodactylus (left) and Procambarus holifieldi (right). Predicted relationships (in black) and 95% confidence intervals (CIs) were calculated holding all other predictors at their mean value or baseline level (time = 00h). The raw data are grouped by time and equally spaced bins along the x-axis and included as gray points +/- 95% confidence interval.

Figure 2.4. Model-estimated relationships between the probability of chimney construction behavior given that a burrow is active and each predictor variable present in the top model (black points in B, black lines in A, C-E), overlaid on the raw data grouped by time and into equally spaced bins along the x-axis (gray points), for Procambarus holifieldi.

Figure 2.5. Year-round, chimney-construction activity Procambarus holifieldi with corresponding groundwater depth.

35 Appendix 2.1. Habitat characteristics for Site 1 (Lacunicambarus erythrodactylus) and Site 2 (Procambarus holifieldi).

Annual Available water minimum storage of soil depth to Flood Site 150 cm deep water table Soil drainage class Soil type frequency 1 24.8 cm 30 cm Somewhat poorly drained Loam Frequent1 2 25.8 cm 15 cm Poorly drained Loam Frequent

1"Frequent" means that flooding is likely to occur often under normal weather conditions. The chance of flooding is more than 50 percent in any year but is less than 50 percent in all months in any year. Soil Survey Staff. Natural Resources Conservation Service. United States Department of Agriculture. Soil Survey Geographic (SSURGO) Database. https://sdmdataaccess.sc.egov.usda.gov. Accessed on 15 August 2018.

36 Appendix 2.2. Photographs of Lacunicambarus erythrodactylus (left column) and Procambarus holifieldi (right column) displaying emergence behavior (A-B) and chimney construction behavior (C-D)

Appendix 2.3. Coefficient estimates for the GLMM (binomial errors, logit link) best explaining variation (lowest AICc value; the “top model”) in out-of-burrow activity for Lacunicambarus erythrodactylus and Procambarus holifieldi, as well as the probability of chimney construction in P. holifieldi. Time: a 24-level factor; Daylength: continuous; Season: a 4-level factor; Groundwater temperature: continuous; Relative air temperature: continuous; Precipitation: continuous. The variance for the random effects associated with each model are also presented.

L. erythrodactylus P. holifieldi P. holifieldi p(activity) p(activity) p (chimney construction | active) Fixed effects Estimate [Standard P Estimate P Estimate [Standard P Error] [Standard Error] Error] Intercept -1.64 [0.16] *** -0.96 [0.24] *** 0.12 [0.33] Time 1 -0.07 [0.12] -0.01 [0.13] not in top model Time 2 -0.18 [0.12] -0.17 [0.13] not in top model Time 3 -0.33 [0.12] ** -0.17 [0.13] not in top model Time 4 -0.49 [0.13] *** -0.21 [0.13] . not in top model Time 5 -1.11 [0.14] *** -0.34 [0.13] ** not in top model Time 6 -2.28 [0.20] *** -0.83 [0.14] *** not in top model Time 7 -3.05 [0.26] *** -1.50 [0.17] *** not in top model Time 8 -3.97 [0.39 *** -1.90 [0.19] *** not in top model Time 9 -4.35 [0.46] *** -2.32 [0.22] *** not in top model Time 10 -4.98 [0.59] *** -2.25 [0.21] *** not in top model Time 11 -4.79 [0.51] *** -2.58 [0.24] *** not in top model Time 12 -5.06 [0.59] *** -2.52 [0.23] *** not in top model Time 13 -3.63 [0.32] *** -2.70 [0.25] *** not in top model Time 14 -3.94 [0.33] *** -2.86 [0.27] *** not in top model Time 15 -3.89 [0.32] *** -2.85 [0.27] *** not in top model Time 16 -3.55 [0.31] *** -2.69 [0.25] *** not in top model Time 17 -3.58 [0.32] *** -2.81 [0.26] *** not in top model Time 18 -2.58 [0.21] *** -1.87 [0.18] *** not in top model Time 19 -1.43 [0.15] *** -0.93 [0.14] *** not in top model Time 20 -0.72 [0.13] *** -0.45 [0.13] *** not in top model Time 21 -0.14 [0.12] -0.21 [0.13] not in top model Time 22 -0.04 [0.12] -0.14 [0.13] not in top model Time 23 -0.03 [0.12] -0.01 [0.13] not in top model Daylength 1.78 [0.06] *** not in top model 0.24 [0.07] *** Daylength2 -0.59 [0.04] *** not in top model not in top model Season spring not in top model -0.42 [0.19] * not in top model Season summer not in top model -0.41 [0.09] *** not in top model Season winter not in top model -1.37 [0.22] *** not in top model Groundwater temperature -0.17 [0.04] *** -0.28 [0.08] *** -0.31 [0.08] *** Relative air temperature 1.08 [0.08] *** 0.16 [0.06] ** -0.23 [0.09] ** Precipitation not in top model not in top model -0.40 [0.08] ***

Random effects Variance Variance Variance Burrow 0.62 1.28 3.09

R2m1 0.33 0.11 0.06 R2c1 0.36 0.22 0.47 N cases 27,427 17,030

P: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 1Marginal R2 (R2m), and conditional R2 (R2c) were calculated as in Nakagawa S., & Schielzeth, H. A. (2013). A general and simple method for obtaining R2 from generalized linear mixed-effects models. Methods in Ecology and Evolution 4: 133-142.

CHAPTER 3: CRAYFISH CONNECTIONS: LINKING ECOLOGY AND HYDROGEOLOGY IN ALABAMA’S BLACK BELT PRAIRIE USING BURROWING CRAYFISH PRESENCE Abstract Floodplain ecosystems host a diversity of lotic, lentic, and ephemeral waterbodies, as well as accessible shallow groundwater, features that may be critical habitat for both aquatic and terrestrial species. Floodplain ecosystems are highly heterogeneous and harbor a high diversity of species, yet our understanding of species-habitat relationships within these complex ecosystems remains incomplete and may hinder conservation efforts. Understanding associations between burrowing crayfish and the environmental features of floodplains is particularly valuable because crayfish, through burrowing, play an important role in establishing aquatic- terrestrial connections. Species of crayfish that persist in floodplains holding water during limited periods of the year must burrow deep enough to access shallow groundwater, therefore, burrow presence may indicate a preference for select surface and subsurface characteristics. The primary goal of our study was to assess if burrowing crayfish presence was linked to local environmental factors. Our secondary goal was to determine possible species-specific responses to the same environmental factors. We evaluated crayfish presence (signaled by active burrows) and composition with respect to groundwater depth, inundation duration, soil characteristics, and tree size. We predicted that crayfish presence would be related to groundwater depth, soil characteristics, and tree size, while species composition would be related to groundwater depth and soil characteristics. We monitored the presence of active burrows from January to December of 2017 and then collected crayfish in March and April of 2018 in the Bogue Chitto Creek

39 watershed in Dallas County, Alabama. We found that groundwater depth was the primary driver of burrowing crayfish presence in our system. Crayfish were more likely to be present in areas with relatively shallow groundwater depths (ranging from 35-180 cm). We also found a marginal association between species composition and groundwater depth and inundation duration.

Identifying local landscape factors associated with burrowing crayfish will allow researchers to determine drivers of local biodiversity in floodplains and provide a better understanding of how ecology and hydrogeology can be used to create effective management plans for areas that benefit a host of species.

Introduction Floodplain ecosystems harbor a diversity of species that rely on diverse and dynamic hydrological connectivity for habitat creation and nutrient exchange (Tockner et al. 1999, Górski et al. 2013). The physical landscape of an intact floodplain may include lotic, lentic, and ephemeral waterbodies, in addition to accessible shallow groundwater (Ward et al. 1999,

Tockner and Stanford 2002). The high physio-chemical heterogeneity of floodplains provides complex, unique habitats supporting aquatic and terrestrial fauna (Ward 1998, Thomaz et al.

2007), but species-habitat associations within these complex systems remain poorly understood for many taxa. Here we examine local environmental associations using burrowing crayfish, a group which provides a unique link between aquatic and terrestrial habitats.

The wide variety of habitats within floodplains support three categories of burrowing crayfish: primary burrowers (spend the majority of their time in a burrow; rarely enter permanent surface water), secondary burrowers (burrow into shorelines of surface waters; frequent permanent surface waters), and tertiary burrowers (burrow into open water; Hobbs 1981, Berrill and Chenoweth 1982, DiStefano et al. 2009). Although tertiary burrowers typically burrow only

40 for reproduction or avoidance of unfavorable environmental conditions, primary and secondary burrowers spend considerably more time constructing and maintaining their burrows, relying more heavily on a fossorial existence to complete their life cycles. All three types of burrowing crayfish use aquatic and terrestrial habitats to fulfill life history requirements, providing a unique link between the two.

Tertiary burrowers in stream systems have been the subject of most crayfish research.

These crayfish can have strong effects on freshwater communities via trophic interactions (e.g. as keystone species) or non-trophic interactions (e.g. through ecosystem engineering), and direct and indirect influence of tertiary burrowers has been implicated in the distribution and abundance of sediment, detritus, algae, macrophytes, and macroinvertebrates in stream systems

(Creed 1994, Lodge et al. 1994, Charlebois and Lamberti 1996, Nystrom et al. 2001, Creed and

Reed 2004, Usio and Townsend 2004). Tertiary burrowers may also host annelid

(Brachiobdellida) and arthropod (Ostracoda) ectosymbionts and thereby affect the distribution of other species in both aquatic and terrestrial communities (Alderman and Polglase 1988). The role of tertiary burrowers in floodplain habitats, which hold water only during certain seasons, is far less understood.

Primary and secondary burrowers also affect their environment via increasing soil mixing, soil habitat complexity (Robertson and Johnson 2004, Welch et al. 2008), soil respiration (Richardson 1983, Stone 1993), and by creating habitat for other species (Pintor and

Soluk 2006, Loughman 2010). More research is needed regarding the habitat needs and biogeography of primary and secondary burrowers. Crayfish species that persist in intermittently wetted floodplain habitats must burrow deep enough to access the groundwater during periods of drying (Grow and Merchant 1980). As a result of this life history requirement, the spatial

41 distribution of crayfish burrows within floodplains may indicate a preference for select surface and subsurface characteristics.

Floodplain studies targeting crayfish have been species-specific and limited in scope.

Studies have shown that primary burrower Lacunicambarus erythrodactylus Simon and Morris

2015 occupies locations with a shallow water table, fine-grained soils, and high floodplain connectivity (Grow and Merchant 1980, Hobbs 1981, Helms et al. 2013), and forest age was found to also influence presence of primary burrower Creaserinus fodiens Cottle 1863

(Loughman et al. 2012). Soil composition and soil compaction may also affect occupancy, and population responses to drying and flooding are species-specific (Caine 1978, Taylor 1983,

March and Robson 2006, Dorn and Trexler 2007, Dorn and Volin 2009). Site-specific factors such as aboveground and belowground structures may also influence local distribution, with laboratory studies noting a tendency for some species to burrow against pipes and glass beakers

(Grow 1981, Stoeckel et al. 2011) and field observations documenting burrows between roots and rocks (Hobbs 1981). Floodplain habitats can harbor a diversity of crayfish in the same local area, therefore a microlandscape approach addressing environmental drivers of crayfish distribution in a field setting may help elucidate which environmental factors enhance local biodiversity within floodplains.

The primary objective of our study was to use field surveys to determine if microlandscape components affect the local presence of burrowing crayfish in a Black Belt

Prairie stream floodplain in Alabama, a state known as the most biodiverse region in the world for freshwater crayfishes (Neves 1999, Warren et al. 2000, Taylor 2002). We evaluated the presence of active burrows from January to December of 2017 in a 0.6 km2 area with respect to average annual groundwater depth and soil resistance, inundation duration (number of days

42 inundated during the study period), average tree size, dominant grain size of soil, dominant grain size coefficient of variation, soil moisture, and soil organic matter. We hypothesized that burrower presence would be related to the environmental variables of groundwater depth, soil characteristics, and tree size. We predicted that burrowers would be distributed in areas with a shallow water table, predominantly fine-grained soils such as silt/clay, and more mature timber stands.

The secondary objective of our study was to determine if crayfish species composition varied with the environmental parameters used in our primary analysis. We evaluated the species composition of crayfish collected in March and April of 2018 in relation to groundwater depth, inundation duration, soil characteristics, and tree size. We hypothesized that species composition would be related to groundwater depth and soil characteristics. Because population responses to drying and flooding have shown species-specific responses (Caine 1978, Taylor 1983, March and Robson 2006, Dorn and Trexler 2007, Dorn and Volin 2009), we predicted species-specific responses to groundwater depth and soil type.

Methods Study site Our study area was the Bogue Chitto Creek watershed in the Black Belt Prairie region of the Coastal Plain of Alabama. The Black Belt Prairie is a subdistrict of the East Gulf Coastal

Plain Physiographic Province (Sapp and Emplaincourt 1975), representing more than 20,719 km2 across Alabama, Mississippi, and Tennessee. In Alabama, the Black Belt represents a total land area of approximately 11,136 km2 (Monroe 1941). Located in the Black Belt, the Bogue Chitto

Creek watershed comprises 10 Hydrologic Unit Code (HUC) 12 subwatersheds covering 941 km2 in Dallas and Perry counties and terminates at the Alabama River. Our study was conducted in the Lower Bogue Chitto Creek subwatershed which has land cover comprising 37% forest,

43 33% wetlands, and 14% agriculture (USDA NRCS 2016). Previous surveys for crayfish in

Bogue Chitto Creek indicated the presence of 14 crayfish species (McGregor et al. 2018).

We used ArcGIS software to delineate 100 stream sections (each 100 m in length) of a 10-km reach of Bogue Chitto Creek in Dallas County, Alabama. From these 100 sections, we randomly chose 25 as locations for the placement of sampling transects on the adjacent floodplain (Fig.

3.1). At each chosen section, we placed a 60-m long, 1-m wide transect perpendicular to the stream bank (Fig. 3.1). We divided each transect into three zones for data collection and analysis: a streamside zone (0–20 m), an intermediate zone (21–40 m), and a floodplain zone (41–60 m).

Crayfish presence and collections To determine crayfish presence at each sampling site (zone within transect) during each month of the study (Jan.–Dec. 2017), we identified active burrows based on signals of use: the presence of fresh mud at chimneys and a lack of debris or spider webs covering the burrow entrance. Because burrowing crayfish can have multiple burrow entrances, we did not count the number of entrances at each site but simply recorded presence/absence, which was not species- specific. To evaluate the possibility that species composition varies with our environmental variables, we collected crayfish in each occupied zone by either hand digging or setting minnow traps during high water periods over seven consecutive nights. Captured crayfish were preserved and taken to the Geological Survey of Alabama for species identification.

Environmental variables We collected data on groundwater depth, soil resistance, tree diameter at breast height

(DBH), and inundation duration in all three zones within each transect. Soil moisture, soil organic matter, dominant grain size, and dominant grain size coefficient of variation were measured only for the intermediate zone and the floodplain zone due to landowner restrictions.

44 We sampled groundwater depth monthly using a water level sounder in the intermediate and floodplain zones within each transect from a shallow monitoring well that we installed using procedures recommended by the USDA-NRCS (Sprecher 2008). Due to landowner restrictions, we were unable to install a well in the streamside zone, but we used the depth to permanent surface water from a benchmark in the streamside zone as the data point for this zone, recording it monthly with laser land surveying equipment. In order to determine inundation duration, we used digital elevation model (DEM) data and continuous water level data from HOBO (Onset,

Pocasset, Massachusetts) loggers set to record water depth every 30 minutes at select sites throughout the study area. We calculated inundation duration for each zone within each transect as the number of days during the year that the zone was inundated based on elevation and water level data. We used an impact penetrometer to determine average soil resistance within each zone over the 12-month period (Herrick and Jones 2002). We recorded tree size once using a

DBH tape in a 1 m2 quadrat randomly placed in each of the three zones within each transect. In

October of 2017, we procured a 1-m deep core from each intermediate and floodplain zone for lab analysis of soil moisture, soil organic matter, dominant grain size, and grain size coefficient of variation (Wentworth 1922, ASTM 1993, Brady and Weil 2007, ASTM 2019).

Statistical analysis The presence of burrows did not vary across the year, so data within each site were collapsed to site-level (one measurement of crayfish presence/absence for each site). Annual means of groundwater depth and soil resistance were used as predictors of crayfish presence, along with a yearly sum of inundation days, and one-time measurements of average DBH, dominant grain size of soil, dominant grain size coefficient of variation, soil moisture, and soil organic matter. We used generalized linear mixed effect models (GLMMs) with a binomial error

45 structure (R version 3.5.2/2018, R Core Team, Vienna, Austria) to evaluate which environmental predictors influence burrowing crayfish presence in our study area using a model selection approach (Burnham and Anderson 2002). The importance of each environmental variable as a predictor of crayfish presence was assessed by comparing the performance of the most general model to that of simpler candidate models (excluding one or more predictors) using Akaike’s information criterion (AICc; Akaike 1974). The model that best explained the variation in the data was the model with the lowest AICc value (Burnham and Anderson 2002).

Three-zone presence/absence analysis

We first analyzed environmental effects on the probability that burrowing crayfish are present at a given sampling site (zone within transect) using data from all three zones. Transect was included as a random effect in all models to control for the non-independence of observations made at the same location. We considered the following environmental predictors

(fixed effects): groundwater depth (a 3-level factor; shallow: 35-180 cm; moderate: 181-250 cm; deep: 251-390 cm), inundation duration (number of days inundated), soil resistance (N), and

DBH (cm). Because of landowner restrictions, we were unable to procure a soil core from the streamside zone, therefore soil resistance was the only measured soil characteristic in the three- zone analysis. All continuous variables were standardized (to a mean of 0 and a standard deviation of 1) to put them on a common scale. Before fitting the GLMMs, we evaluated our predictor variables for multicollinearity. Because groundwater depth and inundation duration were highly correlated with one another (r = -0.42, d.f. = 73, p << 0.001) we never included these two predictors in the same candidate model. Also, because the distance from each sampling site to the stream was highly correlated with groundwater depth (r = -0.44. d.f. = 73, p << 0.001) and soil resistance (r = 0.60, d.f. = 73, p << 0.001), it was not included in any of the models.

46 We constructed two global models incorporating groundwater depth or inundation duration, soil resistance, and DBH as linear predictors of crayfish activity. There was a total of

12 models in the candidate set. We used AICc values to rank our models and disregarded all models greater than a delta AICc of 2 from our top model set if they were more complex versions of a nested model with a lower AICc (sensu Burnham and Anderson 2002, Richards et al. 2011).

Two-zone presence/absence analysis

In a second stage of analysis, we restricted the data to the intermediate and floodplain zones to evaluate the importance of the full suite of environmental parameters as predictors of burrowing crayfish presence/absence. We used an approach similar to that described above

(models were binomial GLMMs with a random effect of transect). In addition to groundwater depth, inundation duration, soil resistance, and DBH, the two-zone analysis considered soil moisture (%), soil organic matter (%), dominant grain size (mm), and dominant grain size coefficient of variation. Because some of the soil variables were highly correlated with one another (Table 3.1), we included only one soil variable at a time in each candidate model.

Continuous covariates were standardized, and AICc was used to rank candidate models and evaluate the importance of each environmental variable on crayfish presence. There were 36 models in the candidate model set. Several candidate models gave warnings of singularity when they were fit, indicating that transect level variance was approaching zero. This suggested that our analysis might be better performed using generalized linear models (GLMs with binomial errors and a logit link function) omitting the random effect of transect, and we repeated our model selection using GLMs (all methods as described above).

47 Species composition by habitat

To assess species-specific habitat associations, we first described patterns of species composition and abundance across sites using ordination plots and data on the number of individuals of each species collected at each site. Ordination plots were generated using non- metric multidimensional scaling (NMDS). The crayfish abundance dataset included only sites in which crayfish were captured and identified to species. We square-root transformed the abundance data and then calculated a dissimilarity matrix using the Bray-Curtis similarity measure and then generated ordination plots using NMDS. To evaluate associations between patterns of species composition and abundance and our environmental variables, we constructed three Euclidean distance matrices summarizing site-level variation in environmental conditions using: 1) water variables (groundwater depth and inundation duration); 2) soil variables (soil resistance, dominant grain size, dominant grain size coefficient of variation, soil moisture, and soil organic matter); and 3) DBH. We then evaluated the correlations between each environmental distance matrix (water, soil, DBH) and the crayfish dissimilarity matrix using

Mantel tests based on the Spearman’s rank correlation.

Results Three-zone presence/absence analysis Summary values of each environmental variable measured at sites with and without crayfish are summarized in Table 3.2. For the three-zone analysis, the best-supported GLMM

(lowest AICc) indicated that the probability of a crayfish being present in a site is influenced by groundwater depth and soil resistance (Table 3.3; Appendix 3.1). The probability of observing active burrows was much higher at sampling sites with shallow groundwater depth (35-180 cm deep; β = 5.10, SE = 2.28, p = 0.03) or moderate groundwater depth (181-250 cm deep; β = 1.43,

SE = 1.33, p = 0.28) versus at sites with a deep groundwater depth (Fig. 3.2A). The probability

48 of burrowing crayfish being present was greater at sites with an increased level of soil resistance

(β = 0.69, SE = 0.52, p = 0.19; Fig. 3.2C), although a model excluding soil resistance performed nearly as well (Table 3.3). Three other candidate models fell within Δ2 AIC of the top model

(Table 3.3). One included only groundwater depth, one included groundwater depth and DBH, and one was identical to the top model but included DBH. DBH did not explain variation in crayfish presence/absence (DBH: β = 0.34, SE = 0.53, p = 0.31; Fig. 3.2E).

Two-zone presence/absence analysis For the two-zone analysis, the best approximating GLMM and GLM indicated that the probability of observing active burrows at a site is influenced by groundwater depth and dominant grain size (Table 3.3, Appendix 3.1). The probability that burrowing crayfish are present was much higher in zones with a shallow groundwater depth (35-180 cm deep; β = 3.88,

SE = 1.15, p << 0.001) and slightly higher in zones with moderate groundwater depth (181-250 cm deep; β = 0.23, SE = 0.86, p = 0.79) versus at sites with a deep groundwater depth (Fig.

3.2B). The probability that crayfish are present also increased with declining dominant grain size

(β = -0.77, SE = 0.46, p = 0.09; Fig. 3.2D), an effect that received weak statistical support. Two models fell within Δ2 AIC of the top model (Table 3.3). One featured only groundwater depth and one was identical to the top model but included DBH. DBH did not explain variation in crayfish presence (β = 0.27, SE = 0.34, p = 0.42; Fig. 3.2F).

Crayfish presence and collections and species composition by habitat We did not find active crayfish burrows (crayfish “present”) in any of the 25 streamside zones, but they were present in 9 of the 25 intermediate zones and in 13 of the 25 floodplain zones. In March and April of 2018, we collected six species of crayfish from 22 sites in four intermediate zones and 10 floodplain zones (Table 3.4).

49 Ordination results showed no evidence of clustering regarding community composition and abundance. Two axes were used with a stress value of 0.07, indicating a good fit (R2=1).

Mantel tests revealed a marginal association between species composition and water variables (r

= 0.20, p = 0.09, Fig. 3.3A,B) but no association between species composition and soil variables

(r = -0.15, p = 0.79) or DBH (r = -0.08, p = 0.66). Sites at which Cambarus striatus Hay 1902,

Lacunicambarus dalyae Glon, Williams and Loughman 2019, and Procambarus lophotus Hobbs and Walton 1960 occurred and at which Creaserinus fodiens Cottle 1863 and Lacunicambarus erythrodactylus Simon and Morris 2015 co-exist were somewhat distinct and dissimilar from each other. These groupings generally corresponded to water variables. Three crayfish species were captured at sites with relatively shallow water tables: Cambarus striatus, a secondary burrower (four sites, 54.61–136.78 cm groundwater depth, 7–23 d of inundation),

Lacunicambarus dalyae, a primary burrower (two sites, 54.61–109.73 cm groundwater depth, 1–

11 d of inundation) and Lacunicambarus erythrodactylus, a primary burrower (two sites, 51.18–

109.73 cm groundwater depth, 1 d of inundation). Two other species were captured at sites with a relatively deep water table: Creaserinus fodiens a primary burrower (four sites, 106.43–262.13 cm, 2–26 d of inundation) and Procambarus marthae Hobbs 1975, a tertiary burrower (seven sites, 106.43–262.13 cm, 2–10 d of inundation). The last species occupied sites characterized by a variety of groundwater depths: Procambarus lophotus, a tertiary burrower (seven sites, 54.61–

262.13 cm, 3–11 d of inundation).

Discussion Our results partially confirmed our hypothesis that the distribution of burrowing crayfish is influenced by environmental cues such as groundwater depth, soil characteristics, and tree size. Because studies have shown that burrowing crayfish occupy sites with a shallow water

50 table, fine-grained soils, and belowground structure (Grow and Merchant 1980, Hobbs 1981,

Loughman et al. 2012, Helms et al. 2013), we predicted that crayfish would be distributed in areas with a shallow water table, predominantly fine-grained soils such as silt and clay, and more mature timber stands. While we did find that active burrows were located at sites with a shallow groundwater depth and relatively small dominant grain size (a marginal effect), DBH did not predict where crayfish would be present. Soil resistance also influenced burrowing crayfish presence, although the relationship received only weak statistical support. Nearly 50% of the variation in crayfish presence is explained by the environmental predictors in our top models for the three-zone and two-zone analyses (R2 = 0.43, 0.49 respectively). We found that groundwater depth was a significant driving factor for the presence of active burrows in both three- and two- zone analyses. Burrowing crayfish are often associated with a shallow water table (Hobbs 1981,

Helms et al. 2013), but this study was the first to use field experiments to document the influence of groundwater depth on the local distribution of this group.

One of our key findings is the documentation that burrowing crayfish can indicate the presence of shallow groundwater. Traditionally, biological indicators of shallow groundwater presence have all been plant species (Meinzer 1927); crayfish might represent the first animal species to do so. The possibility that different species may indicate the presence of groundwater depths falling within certain ranges dictated by their (species-specific) life history requirements is worthy of future research efforts. To expand on the marginal association we found between species composition and abundance and water-related characteristics of a site (inundation frequency and groundwater depth), our review of the monthly variability of groundwater levels and inundation duration associated with each species offered additional insight into potential species-specific habitat partitioning (Fig. 3.4A-F). Seasonal profiles of groundwater depth varied

51 among sites occupied by different burrowing species, and these differences were not explained by burrower type. L. erythrodactylus and L. dalyae, primary burrowers, were associated with a relatively shallow groundwater depth (average 75.27 and 82.17 cm, respectively cm); C. striatus, a secondary burrower, with an intermediate groundwater depth (average 103.06 cm); and C. fodiens, a primary burrower, P. lophotus, and P. marthae, tertiary burrowers, with a deeper groundwater depth (average 173.89, 165.88, and 182.39 cm respectively). Our data suggest that, although some species prefer areas with relatively shallow groundwater levels (possibly due to the reduced cost of burrow excavation), others might accept the cost of excavating long burrows to reach relatively deep groundwater levels during periods of drying because they require other habitat components associated with a deep water table. Those requirements may include access to seasonal floodplain pools, often found in conjunction with deeper groundwater levels.

Interestingly, not all species associated with relatively deep groundwater sites fall into the same burrower type. Laboratory studies assessing species-specific responses to varying water levels have been limited (Stoeckel et al. 2011), and this study provides the first field data regarding groundwater level associations for burrowing crayfish.

We analyzed the presence of active crayfish burrows as a function of site-specific inundation frequency to evaluate whether burrowing crayfish are associated with areas that retain water during longer periods. A positive correlation between inundation frequency and groundwater depth suggests that areas with a high inundation frequency also feature deep groundwater. Areas with a high clay content or high organic matter content near the surface are more likely to capture and hold water at the surface following precipitation or flood events

(Fetter 2001). Consequently, those properties may prevent the transmission of water downward and result in a much deeper water table during seasons with a low inundation frequency. Because

52 increased depth to water is associated with a low probability of finding an active burrow at a site, we expected crayfish to be found at sites with relatively low inundation frequencies. However, our species-specific analysis revealed that certain species are found at sites with higher inundation durations, likely due to the presence of floodplain pools. Some species living in seasonal wetlands require a lengthy period of exposure to open water for mating, egg development, rearing of young, and terrestrial predator avoidance (Hobbs 1981, Taylor and

Schuster 2004, Loughman and Simon 2011, Barnett et al. 2017). Floodplain pools are typically shallow, feature a medley of organic matter and leaf detritus, and allow light to penetrate to the bottom, promoting the establishment of various plant and animal food sources for crayfish including amphipods, isopods, coleopterans, hemipterans, odonates, annelid worms, and amphibians. These habitats also offer reproductive rewards in the form of additional mate choices and may harbor multiple species of crayfish. As floodplain pools dry, crayfish must burrow deeper to remain in contact with groundwater, however the temporarily moist soil afforded by the pool may make digging easier and possibly lessen the cost of excavating a relatively deep burrow.

The floodplain pool advantage may also help explain the observation that some crayfish species employ life history and burrowing strategies that do not fall distinctly into the traditional burrower classification system. The classification of primary, secondary, and tertiary burrowers is based, in part, on the degree to which they use permanent surface waters; thus, primary burrowers are expected to occupy different geographic locations from secondary and tertiary burrowers, and typically primary burrowers are found in dense colonies often consisting of only one or two species (Guenter Schuster, retired Eastern Kentucky University, pers. comm., 2020).

Our data suggest floodplain habitats facilitate the coexistence of all three burrower types,

53 potentially because the seasonal dynamics of floodplain pools satisfy a diverse set of requirements. In addition to the differences in the seasonal profiles of groundwater depth at sites occupied by different species classified as primary burrowers, we also noted partitioning regarding inundation duration (Fig. 3.4). Primary burrower L. erythrodactylus was found at sites with a relatively short inundation duration (maximum 1 d), while primary burrowers C. fodiens and L. dalyae were at sites with a much greater inundation duration (maximum 26 and 9 d, respectively). In addition to providing ecological associations for underrepresented primary burrowers, our study will expand research efforts for tertiary burrowers that persist at sites with no connection to permanent surface water, fostering an increased understanding of habitat needs for species traditionally viewed as stream dwellers (Creed 1994, Lodge et al. 1994, Charlebois and Lamberti 1996, Nystrom et al. 2001, Creed and Reed 2004, Usio and Townsend 2004). For conservation purposes, the current burrower classification system could possibly be expanded to include a group of species that rely on seasonal, shallow floodplain pools, persist in habitats with deeper groundwater levels, and have no connection to permanent surface water. This reinforces the need for additional, local species-specific habitat studies.

In conjunction with groundwater levels and inundation duration, we found that soil characteristics also affect the distribution of burrowing crayfish in floodplains of the Bogue

Chitto Creek watershed. Our three- and two-zone presence/absence analyses showed that soil characteristics are related to the probability of detecting active burrows at a site. Crayfish were more likely to be found in areas with an increased level of soil resistance and smaller dominant grain size, likely due to the material’s suitability for burrow stability. Other studies have suggested that burrowing crayfish prefer a specific soil type, typically fine-grained clay soils

(Grow and Merchant 1980, Loughman et al. 2012), and loamy floodplain soils (Helms et al.

54 2013). The lack of active burrows in streamside zones may be due to landscape level factors such as periodic flooding that creates areas of coarse sediment content, namely sand, near stream edges. While we did not analyze soil samples from the streamside zone due to landowner restrictions, we did note larger grain sizes (mostly coarse sand) and recorded reduced soil resistance in streamside zones. For sites where crayfish were captured, community composition was unrelated to soil characteristics.

Site-specific factors such as the presence of aboveground and belowground structures may also influence local distribution. In lab experiments, Stoeckel et al. (2011) found that

Cambarus striatus constructed vertical burrows directly against above-water structures such as the inner chamber screening/pvc pipe and Grow (1981) noted that L. erythrodactylus preferred burrowing against the sides of glass beakers. Hobbs (1981) recorded similar activity in the field, observing C. striatus burrowing between roots and rocks. Based on these observations. we predicted that crayfish would be found in conjunction with larger, older trees (and consequently larger roots), but the addition of DBH to our top models did not explain variation in crayfish presence, possibly due to the relative homogeneity of forest stand age in our study area. We also did not find any species-specific patterns relative to tree size.

Conclusions Identifying areas that offer a mosaic of accessible groundwater depths and inundation durations may help provide critical habitat for several species of burrowing crayfish.

Establishing what thresholds are preferred by certain species will not only increase opportunities for effective study of burrower ecology, but also aid in species conservation plans. Such information can be coalesced into a management plan that factors in the negative impact of flooding or drought on other aquatic organisms (Townsend et al. 1997).

55 In floodplain systems, crayfish are found primarily in areas with shallow and moderate groundwater depths, suggesting that conservation of these areas will benefit not only crayfish but other aquatic and terrestrial species which rely on shallow groundwater and floodplain pools, thereby enhancing biodiversity. The strong relationship between crayfish presence and groundwater depth provides the opportunity for these species to become possible indicators of shallow groundwater presence. This will be increasingly more important in the context of how climate change might influence local species diversity. Water quantity both above and below ground will be an issue that continues to receive attention for both ecological and economic impacts. A better understanding of the ecology and hydrogeology interactions in floodplains will add priority to projects that target multidisciplinary approaches to water and species conservation.

Acknowledgments We thank Clay Mangum, hydrologist with Weyerhaeuser, for property access and field assistance; Guenter Schuster, retired professor, Eastern Kentucky University, for assistance with crayfish identification; and Greg Pierce, Parker Nenstiel, and Daniel West of the Geological

Survey of Alabama for field assistance. This project was conducted in accordance with the

Alabama Department of Natural Resources Scientific Collection Permit Number

2018030883468680.

Literature Cited Akaike, H. 1974. A new look at the statistical model identification. IEEE Transactions on Automatic Control 19:716–723. Alderman, D. J. and J. L. Polglase. 1988. Pathogens, parasites and commensals. Pages 167–212 in D. M. Holdich and R. S. Lowery (editors). Freshwater crayfish: biology, management and exploitation. Croom Helm (Chapman and Hall), London, UK.

56 American Society for Testing and Materials (ASTM). 1993. ASTM D 2974-87: Standard test methods for moisture, ash, and organic matter of peat and other organic soils. Annual Book of ASTM Standards, Philadelphia, Pennsylvania. American Society for Testing and Materials (ASTM) International. 2019. D6913/D6913M-17: Standard Test Methods for Particle-Size Distribution (Gradation) of Soils Using Sieve Analysis. ASTM International, West Conshohocken, Pennsylvania. Barnett, Z. C., S. B. Adams, and R. L. Rosamond. 2017. Habitat use and life history of the vernal crayfish, Procambarus viaeviridis (Faxon, 1914), a secondary burrowing crayfish in Mississippi, USA. Journal of Crustacean Biology 37:544-555. Berrill, M. and B. Chenoweth. 1982. The burrowing ability of nonburrowing crayfish. American Midland Naturalist 108: 199–201. Brady, N. C. and R. R. Weil. 2007. The Nature and Properties of Soils. 14th Edition. Prentice Hall, New York, New York, 980 pp. Burnham, K. P. and D. R. Anderson. 2002. Model selection and multimodel inference: a practical information-theoretic approach. 2nd Edition. Springer, New York, New York. Caine, E. A. 1978. Comparative ecology of epigean and hypogean crayfish (Crustacea: Cambaridae) from northwestern Florida. American Midland Naturalist 99:315–329. Charlebois, P. M. and G. A. Lamberti. 1996. Invading crayfish in a Michigan stream: direct and indirect effects on periphyton and macroinvertebrates. Journal of the North American Benthological Society 15:551-563. Creed, R. P. 1994. Direct and indirect effects of crayfish grazing in a stream community. Ecology 75:2091-2103. Creed, R. P. and J. M. Reed. 2004. Ecosystem engineering by crayfish in a headwater stream community. Journal of the North American Benthological Society 23: 224-236. DiStefano, R. J., D. D. Magoulick, E. M. Imhoff, and E. R. Larson. 2009. Imperiled crayfishes use hyporheic zone during seasonal drying of an intermittent stream. Journal of the North American Benthological Society 28:142–152. Dorn, N. J. and J. C. Trexler. 2007. Crayfish assemblage shifts in a large drought-prone wetland: the roles of hydrology and competition. Freshwater Biology 52:2399–2411. Dorn, N. J. and J. C. Volin. 2009. Resistance of crayfish (Procambarus spp.) populations to wetland drying depends on species and substrate. Journal of the North American Benthological Society 28:766–777. Fetter, C. W. 2001. Applied hydrogeology, 4th edition. Prentice-Hall, Inc., Upper Saddle River, New Jersey. Girard, C. 1852. A revision of the North American Astaci, with observations on their habits and geographical distribution. Proceedings of the Academy of Natural Sciences, Philadelphia 6: 87-91. Górski K., A. D. Buijse, H. V. Winter, J. J. De Leeuw, T. J. Compton, D. A. Vekhov, D. V. Zolotarev, J. A. J. Verreth, and L. A. J. Nagelkerke. 2013. Geomorphology and flooding

57 shape fish distribution in a large-scale temperate floodplain. River Research and Applications 29: 1226–1236. Grow, L. 1981. Burrowing behavior in the crayfish, Cambarus diogenes (Girard). Animal Behavior 29:351-356. Grow, L. and H. Merchant. 1980. The burrow habitat of the crayfish, Cambarus diogenes diogenes (Girard). American Midland Naturalist 103:231–237. Guiasu, R. C. 2009. Conservation, status, and diversity of the crayfishes of the genus Cambarus Erichson, 1846 (Decapoda, Cambaridae). Crustaceana 82: 721–742. Helms, B. S., W. Budnick, P. Pecora, J. Skipper, E. Kosnicki, J. Feminella, and J. Stoeckel. 2013. The influence of soil type, congeneric cues, and floodplain connectivity on the local distribution of the devil crayfish (Cambarus diogenes (Girard)). Freshwater Science 32:1333-1344. Herrick, J. E. and T. L. Jones. 2002. A dynamic cone penetrometer for measuring soil penetration resistance. Soil Science Society of America Journal 66:1320–1324. Hobbs, H. H. 1981. The crayfishes of Georgia. Smithsonian Contributions to Zoology. No. 318. Smithsonian Institution, Washington, D.C. Lindeman, R. L. 1942. The trophic-dynamic aspect of ecology. Ecology 23:399-418. Lodge, D. M., M. W. Kershner, J. E. Aloi, and A. P. Covich. 1994. Effects of an omnivorous crayfish (Orconectes rusticus) on a freshwater littoral food web. Ecology 75:1265-1281 Loughman, Z. J. 2010. Ecology of Cambarus dubius (upland burrowing crayfish) in northcentral West Virginia. Southeastern Naturalist 9:217–230. Loughman, Z. J. and T. P. Simon. 2011. Zoogeography, taxonomy, and conservation of West Virginia’s Ohio River floodplain crayfishes (Decapoda, Cambaridae). ZooKeys 74:1-78. Loughman, Z. J., S. A. Welsh, and T. P. Simon. 2012. Occupancy rates of primary burrowing crayfish in natural and disturbed large river bottomlands. Journal of Crustacean Biology 32:557–564. March, T. S. and B. J. Robson. 2006. Association between burrow densities of two Australian freshwater crayfish (Egnaeus sericatus and Geocharax gracilis: Parastacidae) and four riparian land uses. Aquatic Conservation: Marine and Freshwater Ecosystems 16:181– 191. McGregor, S. W., G. A. Schuster, C. A. Taylor, R. A. Bearden, and E. A. Wynn. 2018. An updated report on the distribution and conservation status of the Alabama crayfish fauna. Open file report 1801, Geological Survey of Alabama, Tuscaloosa, Alabama. Meinzer, O. E. 1927. Plants as indicators of ground water. Water-Supply Paper 577. United States Geological Survey. United States Government Printing Office, Washington, D.C. Monroe, W. H. 1941. Notes on deposits of Selma and Ripley age in Alabama. Alabama Geological Survey Bulletin 48, Tuscaloosa, Alabama. Neves, R. J., 1999. Conservation and commerce: Management of freshwater mussel (Bivalvia: Unionoidea) resources in the United States: Malacologica 4:461–474.

58 Nystrom, P., O. Svensson, B. Lardner, C. Bronmark, and G. Wilhelm. 2001. The influence of multiple introduced predators on a littoral pond community. Ecology 82:1023-1039. Paine, R. T. 1966. Food web complexity and species diversity. American Naturalist 100:65-75. Pintor, L. M. and D. A. Soluk. 2006. Evaluating the nonconsumptive, positive effects of a predator in the persistence of an endangered species. Biological Conservation 130:584- 591. Platt, J. R. 1964. Strong Inference. Science 146:347-353. R Core Team. 2018. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. Rhoden, C. M., C. A. Taylor, and W. E. Peterman. 2016. Highway to heaven? Roadsides as preferred habitat for two narrowly endemic crayfish. Freshwater Science 35:974-983. Richards, S. A., M. J. Whittingham, and P. A. Stephens. 2011. Model selection and model averaging in behavioral ecology: the utility of the IT-AIC framework. Behavioral Ecology and Sociobiology 65:77-89. Richardson, A. M. M. 1983. The effects of burrows of a crayfish on the respiration of the surrounding soil. Soil Biology and Biochemistry 15:239–242. Robertson, K. M. and D. L. Johnson. 2004. Vertical redistribution of pebbles by crayfish in mollisol catenas of central Illinois. Soil Science 169:776–786. Sapp, C. D. and J. Emplaincourt. 1975. Physiographic regions of Alabama: Geological Survey of Alabama Special Map 168, Tuscaloosa, Alabama. Skelton, C. E. 2010. History, status, and conservation of Georgia crayfishes. Southeastern Naturalist 9:127–138. Smith, J. B., G. A. Schuster, C. A. Taylor, E. A. Wynn, and S. W. McGregor. 2011. A preliminary report on distribution and conservation status of the Alabama crayfish fauna. Open-file Report 1102, Geological Survey of Alabama, Tuscaloosa, Alabama. Sprecher, S. W. 2008. Installing monitoring wells in soils (Version 1.0). National Soil Survey Center, Natural Resources Conservation Service, USDA, Lincoln, Nebraska. Stoeckel, J. A., B. S. Helms, and E. Cash. 2011. Evaluation of a crayfish burrowing chamber design with simulated groundwater flow. Journal of Crustacean Biology 31:50–58. Stone, E. L. 1993. Soil burrowing and mixing by a crayfish. Soil Science Society of America Journal 57:1096–1099. Taylor, C. A. 2002. Taxonomy and conservation of native crayfish stocks. Pages 236-237 in D. M. Holdich (editor). Biology of freshwater crayfish. Blackwell Science Ltd., Oxford, UK. Taylor, C. A. and G. A. Schuster. 2004. Crayfishes of Kentucky. Illinois Natural History Survey Bulletin 28:1-219. Taylor, C. A., G. A. Schuster, J. E. Cooper, R. J. Di Stefano, A. G. Eversole, P. Hamr, H. H. Hobbs, Jr., H. W. Robison, C. E. Skelton, and R. E. Thomas. 2007. A reassessment of the conservation status of crayfishes of the United States and Canada after 10+ years of increased awareness: Fisheries, 32:372–389.

59 Taylor, R. C. 1983. Drought-induced changes in crayfish populations along a stream continuum. American Midland Naturalist 110:286–298 Thomaz, S. M., L. M. Bini, and R. L. Bozelli. 2007. Floods increase similarity among aquatic habitats in river-floodplain systems. Hydrobiologia 579:1–13 Tockner K., D. Pennetzdorfer, N. Reiner, F. Schiemer, and J. V. Ward. 1999. Hydrological connectivity, and the exchange of organic matter and nutrients in a dynamic river– floodplain system (Danube, Austria). Freshwater Biology 41:521–535. Tockner K. and J. A. Stanford. 2002. Riverine flood plains: present state and future trends. Environmental Conservation 29: 308–330. Townsend, C. R. and M. R. Scarbrook. 1997. The intermediate disturbance hypothesis, refugia, and biodiversity in streams. Limnology and Oceanography 42:938-949. U.S. Department of Agriculture Natural Resources Conservation Service. 2016. National Land Cover Dataset, National Geospatial Center of Excellence, http://datagateway.nrcs.usda.gov/GDGOrder.aspx, accessed 5/30/2020. Usio, N. and C. R. Townsend. 2004. Roles of crayfish: consequences of predation and bioturbation for stream invertebrates. Ecology 85:807-822. Ward, J. V. 1998. Riverine landscapes: biodiversity patterns, disturbance regimes, and aquatic conservation. Biological Conservation 83:269–278. Ward, J. V., K. Tockner, and F. Schiemer. 1999. Biodiversity of floodplain river ecosystems: ecotones and connectivity. Regulated Rivers: Research and Management 15:125–139. Warren, Jr., M. L., B. M. Burr, S. J. Walsh, H. L. Bart, Jr., R. C. Cashner, D. A. Etnier, B. J. Freeman, B. R. Kuhajde, R. L. Mayden, H. W. Robison, and W. D. Starnes. 2000. Diversity, distribution, and conservation status of the native freshwater fishes of the southern United States. Fisheries 25:7–31. Welch, S. M., J. L. Waldron, G. Eversole, and J. C. Simoes. 2008. Seasonal variation and ecological effects of Camp Shelby burrowing crayfish (Fallicambarus gordoni) burrows. American Midland Naturalist 159:378–384. Wentworth, C. K. 1922. A scale of grade and class terms for clastic sediments. Journal of Geology 30:377-392.

60 Table 3.1. Correlation coefficients between pairs of soil variables measured at each floodplain and intermediate sampling site (N = 50). Coefficients with significant p values (<0.05) are in bold.

Dominant Coefficient of Moisture Organic Resistance grain size variation matter Dominant -0.09 -0.10 0.03 -0.01 grain size Coefficient of -0.09 -0.11 0.06 -0.14 variation Moisture -0.10 -0.11 0.43 0.25 Organic matter -0.03 0.06 0.43 0.63 Resistance -0.01 -0.14 0.25 0.63

61 Table 3.2. Environmental variables measured from January to December of 2017 comparing sites with and without crayfish. Groundwater depth and soil resistance are based on annual mean values.

Crayfish present Crayfish absent Min Max Mean Min Max Mean Groundwater depth (cm) 35.64 342.27 160.08 142.14 608.46 303.19 Inundation duration 1 26 5.82 1 11 2.77 (days) DBH (cm) 0 173.50 25.81 0 125 14.00 Soil resistance (N) 150.27 565.13 347.53 94.73 574.93 289.44 Soil moisture (%) 2.70 30.76 15.35 1.78 23.89 12.35 Soil organic matter (%) 0.95 7.67 4.67 2.09 9.85 4.65 Dominant particle size 0.04 0.50 0.07 0.04 0.50 0.07 (mm) Dominant particle size 0.61 2.24 1.32 0.66 2.24 1.29 coefficient of variation

62 Table 3.3. Top candidate models ranked by AICc describing variation in crayfish presence in streamside, intermediate, and floodplains zones (top) and in data restricted to intermediate and floodplain zones (bottom). K = the number of parameters, ΔAICc = the difference in AICc value for each model, relative to the top model, wi = Akaike’s model weight. All models included transect as a random effect. Only models falling within Δ2 AICc are included.

Model K AICc ΔAICc wi Streamside, intermediate, and floodplain zone groundwater depth + soil resistance 5 71.09 0 0.31 groundwater depth 4 71.14 0.06 0.30 groundwater depth + DBH 5 71.48 0.39 0.25 groundwater depth + soil resistance + DBH 6 72.58 1.49 0.15 Intermediate and floodplain zone groundwater depth + dominant grain size 4 54.61 0 0.23 groundwater depth 3 55.55 0.94 0.15 groundwater depth + dominant grain size + DBH 5 56.45 1.83 0.09

63 Table 3.4. Crayfish collections by species and sampling site. Crayfish were collected by either hand digging or setting minnow traps during high water periods over seven consecutive nights. Only sites where crayfish were successfully captured are shown.

Crayfish species1 Cambarus Creaserinus Lacunicambarus Lacunicambarus Procambarus Procambarus Site striatus (s) fodiens (p) erythrodactylus daylae (p) lophotus (t) marthae (t) (p) 2 0 0 0 0 0 0 3 0 0 1 0 0 0 6 0 0 2 1 0 0 12 0 0 0 0 0 1 18 0 0 0 0 0 0 20 0 0 0 0 0 0 21 0 0 0 0 0 0 24 3 0 0 0 0 0 27 3 0 0 0 0 0 30 0 0 0 0 11 0 32 0 0 0 0 0 0 35 0 4 0 0 0 0 47 0 1 0 0 0 5 48 0 1 0 0 3 2 51 0 1 0 0 4 2 53 0 0 0 0 10 1 60 0 0 0 0 18 1 62 0 0 0 0 0 0 65 1 0 0 0 16 5 68 0 0 0 0 0 0 69 0 0 0 0 0 0 75 2 0 0 1 17 0 1p: primary burrower; s: secondary burrower; t: tertiary burrower

Figure 3.1. Study area with transect locations as black dots. Transect layout delineating streamside, intermediate, and floodplain zones is shown in the map inset.

Figure 3.2. Model-estimated relationships (in black) between the probability of a crayfish being present and groundwater depth, soil resistance, dominant particle size (two-zone analysis only), and DBH from three-zone (left) and two-zone analyses (right). Predicted relationships (black points in A and B, black lines in C-F) and 95% CIs were calculated holding all other predictors at their mean value and groundwater depth at the “moderate” level. The raw data are binned by equally spaced bins along the x-axis and included as gray points +/- 95% CI.

Figure 3.3. Plots showing the ordination results from NMDS for species composition and abundance as they relate to groundwater depth (A) and inundation duration (B) for each site. Species locations are shown in blue dots, site locations in blank circles.

Figure 3.4. Monthly profiles of groundwater depth and inundation duration at sites where each crayfish species was collected during this study.

Appendix 3.1. Coefficient estimates for the GLM (binomial errors, logit link) best explaining variation (lowest AICc value; the “top model”) in burrowing crayfish presence. Groundwater depth: a 3-level factor; Soil resistance: continuous; Dominant particle size: continuous. The variance for the random effects associated with the generalized linear mixed models is also presented.

Streamside, Intermediate Intermediate intermediate and floodplain and floodplain and floodplain zones zones zones p(presence) p(presence) p(presence) Fixed effects Estimate P Estimate P Estimate P [Standard [Standard [Standard Error] Error] Error] Intercept -3.11 [1.36] * -1.45 [0.53] ** -1.45 [0.53] ** Groundwater depth 1.43 [1.33] 0.28 0.23 [0.86] 0.79 0.24 [0.86] 0.79 moderate Groundwater depth 5.10 [2.28] * 3.88 [1.15] *** 3.88 [1.15] *** shallow Soil resistance 0.69 [0.52] 0.19 not in top not in top model model Dominant particle not in top -0.77 [0.46] 0.09 -0.77 [0.46] 0.09 size model

Random effects Variance Variance Transect 2.03 0

R2m1 0.43 0.45 0.49 R2c1 0.60 0.45 N cases 75 50 50

CHAPTER 4: LANDSCAPE-SCALE ENVIRONMENTAL VARIABLES INFLUENCE WATERSHED-WIDE BURROWING CRAYFISH PRESENCE Abstract Aquatic species are facing imperilment at a disproportionate rate when compared to terrestrial species and are falling victim to rapid rates of extinction. Recent evidence has documented the importance of large-scale ecosystem processes which can predict patterns of biodiversity and species distributions through their influence on the suitability of local habitats over short and long time scales. Connecting landscape-level processes to local habitat requirements is especially important for conservation of imperiled species. Through their use of both aquatic and terrestrial environments in floodplain ecosystems, crayfish are excellent organisms for studies of geomorphological processes. Studies of landscape-level variables that may influence burrowing crayfish which rely solely on groundwater and seasonal inundation are lacking. The primary objective of our study was to use field surveys and geospatial data to determine if select landscape-scale environmental variables affect the distribution of burrowing crayfish in a Black Belt Prairie watershed in the Mobile River Basin in Alabama. We evaluated the presence of burrowing crayfish with respect to channel migration, channel sinuosity, floodplain connectivity, and land use. We also assessed if distance to nearest stream, channel sinuosity, floodplain connectivity, and land use were related to burrowing crayfish composition and abundance. We predicted that burrowers would be distributed in areas within a stream channel’s migration path, areas near streams with a greater sinuosity, areas with greater floodplain connectivity, and predominantly forested areas; and that species composition and

70 abundance would be associated with distance to nearest stream, channel sinuosity, floodplain connectivity, and land use. We found that channel migration, channel sinuosity, floodplain connectivity, and land use were the primary drivers of burrowing crayfish presence in our system. Crayfish were more likely to be present in areas that were not in the channel migration path, areas near streams with a greater sinuosity, areas with greater floodplain connectivity, and areas with less forested land use. Additionally, we did not see any association between crayfish species composition and abundance and landscape-level variables. Identifying landscape-scale factors associated with burrowing crayfish distribution will allow researchers to determine drivers of watershed-wide biodiversity and provide a better understanding of how ecology and geomorphology can be integrated to create effective management plans for watersheds that harbor a suite of species.

Introduction Freshwater species are experiencing a disproportionately high rate of imperilment compared to terrestrial and marine species (Dudgeon et al. 2006, Richman et al. 2015, Reid et al.

2019). Freshwater population sizes have declined by 83%, compared to 38 and 36% for terrestrial and marine species (Collen et al. 2009, WWF 2018). Although factors threatening the persistence of aquatic species are often population-specific, habitat destruction and/or modification has been causally linked to population declines and extinction events in many aquatic species (Jelks et al. 2008, Reid et al. 2019). To mitigate population declines and better inform recovery plans, aquatic resource managers have historically sought to define critical habitat requirements for rare species and then manage those habitats and choose relocation sites in accordance with those requirements (Griffith et al. 1989, Foin et al. 1998). Historically, this process has only taken local conditions into account and not considered large-scale ecosystem

71 processes which can predict patterns of biodiversity and species distributions through their influence on the suitability of local habitats over short and long time scales (Naiman et al. 1992,

Reeves at al. 1995, Schlosser and Angermeier 1995, Wiley et al. 1997). Recent studies emphasize the value of taking a landscape-level approach to management, one that incorporates an understanding of how dynamic processes will influence habitat persistence and connectivity

(Freeman et al. 2003, Labbe and Fausch 2000, Tissot et al. 2017).

Floodplain ecosystems host a mosaic of lotic, lentic, ephemeral, and semi-aquatic water bodies with dynamic hydrological connections that provide complex, diverse habitats for a variety of plant and animal species (Ward 1998, Thomaz et al. 2007). Floodplains experience intermittent inundation and drought (flood pulses), creating a lateral exchange of water, nutrients and organisms between the main stream channel and the connected floodplain (Junk et al. 1989).

During each flood pulse, a moving littoral zone traverses the floodplain, accelerating the decomposition of organic matter and facilitating high levels of secondary production (Bayley

1991). Flood pulses improve habitat diversity by providing travel routes to spawning grounds, access to food resources and refugia during periods of drying (Tockner et al. 1999a, Górski et al.

2013). Within and between floodplains, variation in geomorphology, anthropogenic land use, and stream characteristics can influence the frequency and spatial extent of flood pulses (Górski et al. 2013, Miranda 2005, Schramm and Eggleton 2006), affecting patterns of lateral hydrologic connectivity, habitat heterogeneity, and, potentially, patterns of species distributions. Evaluating the distribution patterns of floodplain species at the landscape scale can improve our understanding of how geomorphology, anthropogenic land use, and stream characteristics influence local and regional biodiversity.

72 Geomorphological factors such as channel migration, channel sinuosity, floodplain connectivity, and land use influence floodplain spatial heterogeneity (Benda et al. 2003, 2004); and heterogeneity, in turn, positively associates with in-stream biodiversity (Ward and Stanford

1995, Bellmore and Baxter 2014, Greene and Knox 2014). Floodplains with high levels of spatial heterogeneity are usually found in connection with unregulated, laterally mobile stream channels (Appling et al. 2014, Hughes 1997, Schwendel et al. 2015), whereas less heterogeneous floodplains (featuring decreased overbank flows and decreased lateral channel migration) result from channel straightening or other types of flow regulation and from anthropogenic land use

(e.g., for agriculture). (Brown et al. 2018, Florsheim and Mount 2002, Smith et al. 1989, Ward and Stanford 1995). Patterns of biodiversity follow spatial habitat heterogeneity: stream segments with a higher sinuosity, lower slope, greater active channel width, and more complex channels (i.e. more off-channel habitats) exhibit distinct aquatic invertebrate community composition and higher species richness, when compared to confined segments (Bellmore and

Baxter 2014). Invertebrate, fish, and amphibian assemblages covary with levels of floodplain connectivity with patterns of fish and benthic macroinvertebrates richness being greater in areas with high connectivity and amphibian richness peaking in areas with low connectivity. (Shields et al. 1994, Tockner et al. 1999b, Ward et al. 1999, Amoros and Bornette 2002).

Connecting landscape-level processes to the distribution patterns of floodplain residents is particularly relevant for the conservation of imperiled freshwater species. The southeastern

United States is an exceptionally biodiverse region for freshwater species, sustaining almost two- thirds of the nation’s fish species, > 90 % of the mussel species, and almost half of the world’s crayfish species (Jenkins et al. 2015, Elkins et al. 2019). Many crayfish species, in particular, are endemic to single drainages within this region (Jenkins et al. 2015, Elkins et al. 2019), and nearly

73 half are threatened or endangered (Taylor et al. 2007). Despite the urgent need for conservation action, the ecology and behavior of crayfish are still poorly understood (Neves 1999, Warren et al. 2000, Taylor 2002).

Crayfish use both aquatic and terrestrial environments in floodplain ecosystems, making them excellent subjects for studies seeking to understand how geomorphological processes and features influence distribution patterns. Burrowing crayfish connect aquatic communities to surface and subsurface terrestrial communities. While primary burrowers typically use groundwater as their main source of water, secondary and tertiary burrowers may frequent permanent surface water or use water provided by seasonal floodplain pools (Hobbs 1981, Berrill and Chenoweth 1982, DiStefano et al. 2009, Loughman et al. 2012). The distribution of burrowing crayfish within floodplains may follow that of required or preferred habitat characteristics, including fine-grained soils, a shallow water table, and a decreased stream bank angle (Hobbs 1981, Grow and Merchant 1980, Loughman et al. 2012, Helms et al. 2013,

Bearden et al. unpublished). Due to the different habitat requirements of primary, secondary, and tertiary burrowers, the spatial distribution of these species within floodplains may be the result of landscape-level processes creating and influencing the persistence of required habitats on the local scale. Enhanced lateral channel migration may result in increased sediment and water retention (Choné and Biron 2016), more sinuous channels could create more heterogeneous soil conditions (Valenza et al. 2020), and areas with a relatively high floodplain connectivity are more likely to feature a shallower water table (Fetter 2001). The spatial distribution of agricultural and other land uses may account for changes in burrowing crayfish community composition, with some species found more frequently in areas with increased disturbance and secondary succession (Rhoden et al. 2016) and others occupying mature forests (Loughman et al.

74 2012). Landscape-level studies of burrowing crayfish populations are sparse and have focused on stream-dwelling crayfish. Climate, geology, latitude, stream characteristics, soils, elevation, precipitation, and temperature are considered major factors affecting the distribution of crayfish found in streams (France 1992, Dyer et al. 2013, Nolen et al. 2014). Whether, and how, these same factors influence crayfish populations within floodplain systems is unknown.

We used watershed-wide field surveys and geospatial data to evaluate the influence of landscape-scale environmental variables on the distribution of burrowing crayfish in a Black Belt

Prairie watershed in the Mobile River Basin in Alabama, a region known for its exceptional freshwater crayfish biodiversity (Neves 1999, Taylor 2002, Warren et al. 2000, McGregor et al.

2018). We evaluated the presence of burrowing crayfish from surveys conducted during the spring of 2019 in the Bogue Chitto Creek watershed with respect to channel migration, channel sinuosity, flood frequency, and land use type. We hypothesized that burrower presence-absence would be related to channel migration, channel sinuosity, floodplain connectivity, flood frequency, and land use. We predicted that burrowers would be found in areas within a stream channel’s migration path, areas near streams with a greater sinuosity, areas with greater floodplain connectivity, and predominantly forested areas. We are the first to examine landscape- scale habitat influences on the presence-absence of burrowing crayfish.

The second objective of our study was to determine if landscape-scale environmental variables were related to burrowing crayfish species composition and abundance. Because habitat preferences with respect to the distance to the nearest stream, local soil and groundwater conditions, and land use characteristics may be species-specific (Welch and Eversole 2006,

Helms et al. 2013, Loughman et al. 2012, Bearden, unpublished data), we expected patterns of community composition and abundance to covary with our environmental variables. To test this

75 idea, we evaluated the composition and abundance of crayfish collected from active burrows in the spring of 2019 in relation to the distance to the nearest stream, channel sinuosity, floodplain connectivity, and land use type.

Methods Study site This study was conducted in the Bogue Chitto Creek watershed in the Black Belt physiographic district of the East Gulf Coastal Plain physiographic section (Sapp and

Emplaincourt, 1975) in Dallas and Perry counties, Alabama. This watershed covers 941.46 km2 and contains 10 Hydrologic Unit Code 12 subwatersheds delineating 97 km of stream length.

Bogue Chitto Creek watershed features greater topographic relief in the headwater reaches with elevations peaking at approximately 153.92 m above mean sea level and then gradually decreasing as it flows southeast, where the stream drains forests and agricultural areas in addition to developed and undeveloped areas. Bogue Chitto Creek watershed terminates at the Alabama

River at an elevation of approximately 24.08 m above mean sea level. Fourteen species of stream-dwelling and burrowing crayfish are known from the Bogue Chitto Creek watershed, two of which are listed as being of high conservation concern in Alabama (Procambarus hagenianus hagenianus Faxon 1884 and Procambarus marthae Hobbs 1975) and one endemic species,

Procambarus holifieldi Schuster, Taylor & Adams 2015, that has been given a provisional priority high conservation concern status (McGregor et al. 2018).

Crayfish presence and collections We used ArcGIS (ESRI, Redlands, CA, USA) software to select 80 random locations

(GPS coordinates) throughout the Bogue Chitto Creek watershed in Perry and Dallas counties,

Alabama. From these 80 locations, we chose 54 as burrowing crayfish sampling sites based on

76 accessibility (Fig. 4.1). A sampling site was defined as the 3,600 m2 circle centered on each pair of GPS coordinates. Presence-absence and species collection data were recorded in March-May of 2019 for each sampling site. Because burrowing crayfish can have multiple burrow entrances, we did not record the number of entrances but considered each connected group of entrances a cluster for species collection. Connectivity was established by assessing tunnel morphology during burrow excavation. At each sampling site, all burrow clusters were excavated by hand for a total of 30 minutes per person per cluster. Burrowing crayfish were considered present at a site if a collection was made and absent if no collection was made. In order to determine species- habitat associations, captured crayfish were preserved in ethanol and transported to the

Geological Survey of Alabama for species identification.

Landscape variables We used ArcGIS (ESRI, Redlands, CA, USA) to link presence-absence and species composition and abundance to landscape variables capturing elements of channel migration, channel sinuosity, floodplain connectivity, and land use. Channel migration was defined as a dichotomous variable capturing whether or not a channel had migrated over a site and was determined from LiDAR data by locating previous and current stream channels and then assessing if the sampling point fell within the channel’s migration path (Fig. 4.2). Distance to nearest stream was calculated in ArcMap using the USGS National Hydrography Dataset (NHD;

USGS 2016) by measuring the distance from each sampling site to the nearest flow line. The

NHD was also used to assess channel sinuosity by calculating the ratio of stream channel length to straight line distance for each 2,500 m stream section nearest each sampling site using the sampling site’s perpendicular location to the stream as the center (Rosgen 1996). Floodplain connectivity was estimated as the average rate of change in elevation (meters above sea level)

77 per meter of distance between each sampling site and the nearest stream. A small change in elevation over a large spatial distance thus results in a small number for floodplain connectivity

(feet per meter) and represents a high floodplain connectivity. Elevations were obtained from a

10-m digital elevation model (DEM) data. The USDA NRCS National Land Cover Database with enhanced cropland data (USDA NRCS 2016) was analyzed in a GIS environment to determine the spatial distribution of land cover for the top three land use categories (agriculture, forest, and wetland) within a 1,000-m radius for each sampling site. The area (km2) covered by agriculture, forest, and wetland was used to calculate percentages for each. To assess if channel migration, channel sinuosity, rate of elevation change, and land use are related to local environmental factors shown to affect burrowing crayfish presence-absence at the local scale

(Bearden et al. 2020 unpublished data), we calculated Pearson’s correlation coefficients for each pair of variables.

Statistical analysis We used generalized linear models (GLMs) with a binomial error structure (R version

4.0.1, R Core Team, 2020) to evaluate which environmental variables influence burrowing crayfish presence-absence in our study area. We considered the following: channel migration (a two-level factor: 1 or 0), distance to nearest stream, channel sinuosity, rate of elevation change, and % agriculture, % forest, and % wetland. All continuous variables were standardized (to a mean of 0 and a standard deviation of 1) prior to analysis to put them on a common scale. Before fitting the GLMs, we evaluated our predictor variables for multicollinearity. Because certain land use category variables (% agriculture, % forest, and % wetland) were highly correlated with one another (Table 4.1), we never included more than one land use category variable in each model.

78 We also did not include distance to nearest stream as a variable in our GLMs because it was moderately correlated with channel migration (r = -0.41, d.f. = 52, p = 0.002).

We first constructed three most-general models including channel migration, channel sinuosity, rate of elevation change, and one land use variable (% agriculture, % forest, or % wetland) as linear predictors of the presence of active crayfish burrows. The importance of each environmental variable as a predictor of active burrow presence-absence was assessed by comparing the performance of the most general model to that of simpler candidate models

(excluding one or more predictors) using Akaike’s information criterion corrected for a relatively small sample size (AICc; Akaike 1974). We included all possible subsets of the three most- general models in the candidate model set. The model that best explained the variation in the data was the model with the lowest AICc value (Burnham and Anderson 2002). We disregarded all models greater than a delta AICc of 2 from our top model set if they were more complex versions of a nested model with a lower AICc (sensu Burnham and Anderson 2002, Richards et al. 2011). There was a total of 32 models in the candidate set.

Species composition by landscape variables To assess whether sites with similar crayfish species assemblages also have similar environmental characteristics, we first described the major pattern of species composition and abundance across occupied sites using an ordination plot. We chose non-metric multidimensional scaling (NMDS) as an ordination technique to reduce the dimensions (2 axes) of our species abundance data to describe major patterns in species composition across sites (McCune and

Grace, 2002). A dissimilarity matrix was constructed from the species abundance data using the

Bray-Curtis similarity measure (Borcard et al. 2011). We assessed the ability of the ordination to account for variation in the original abundance data by evaluating the stress and by performing

79 post-hoc regressions of the distances between sampling sites along each ordination axis by the distances between sampling sites in the original abundance dataset. Stress is an inverse measure of fit to the data with lower stress values indicating a better fit (McCune and Grace 2002).

Regressions provided a measure of the variance in the original abundance data explained by each of the two axes of the ordination (i.e. an R2 value). We performed an exploratory analysis of the correlations between each ordination axis and the abundance data for each species to assess the contribution of each species to the two ordination axes. We used Spearman’s rank correlation coefficients and focused on larger correlations (ρ>0.04) to help us determine biologically relevant relationships. We did not perform statistical tests for the significance of these correlations because ordination scores violate the assumption of independence (McCune and

Grace, 2002).

To assess potential associations between patterns of species composition and abundance across sites and continuous landscape variables, we performed Mantel tests using Spearman’s rank correlation. We first constructed Euclidean distance matrices describing differences between sites according to 1) distance to nearest stream, 2) channel sinuosity, 3) rate of elevation change, and then 4) land use variables (% agriculture, forest, and wetland). Next, we used Mantel tests to evaluate associations between each pair of matrices, comparing distances between sites in terms of environmental characteristics with differences between sites in terms of species composition (calculated using the Bray Curtis dissimilarity measure).

Results Landscape variables Landscape variables for each site are listed in Table 4.2. The best approximating GLM indicated that the probability that burrowing crayfish are present at a site is influenced by channel migration, channel sinuosity, rate of elevation change, and % forest (Table 4.3,

80 Appendix 4.1). The probability that crayfish were present was much greater at sampling sites that were not in the migration path of a stream channel (β = -3.52, SE = 1.76, p = 0.04; Fig. 4.3A).

The probability that crayfish were present also increased with stream sinuosity (β = 4.64 SE =

2.14, p = 0.03; Fig. 4.3B) and decreased with forest cover (β = -3.79 SE = 1.94, p = 0.05; Fig.

4.3D). The probability that crayfish are present also increased when rate of elevation change is low (β = -1.72, SE = 0.99, p = 0.08; Fig. 4.3C), an effect that received weak statistical support because a candidate model excluding rate of elevation change performed nearly as well (Table

4.3). We also determined that local groundwater depth was moderately correlated with channel migration and strongly correlated with specific land use variables (% forest and % wetland); local inundation was moderately correlated with channel migration and floodplain connectivity; and local soil resistance was strongly correlated with channel sinuosity and moderately correlated with channel migration, floodplain connectivity, % forest, and % wetland. (Table 4.4).

Crayfish presence and collections We collected 10 species of crayfish from 44 of the 54 sampling sites (Table 4.5). The majority of sites hosted only one or two species (~56%: 1 species; ~30%: 2 species). Four species were relatively common (Creaserinus fodiens Cottle 1863, Cambarus striatus Hay 1902,

Procambarus lophotus Hobbs and Walton 1960, and Procambarus marthae Hobbs 1975, all found at > 8 sites) and the remaining six species were infrequently encountered (Procambarus holifieldi Schuster, Taylor and Adams 2015, Procambarus. hagenianus hagenianus Faxon 1884,

Procambarus clarkii Girard 1852, Lacunicambarus ludovicianus Faxon 1884, Lacunicambarus dalyae Glon, Williams and Loughman 2019, Hobbseus prominens Hobbs 1966, all found at only

1-3 sites).

81 Species composition by landscape variables Because our data included a number of relatively rare species (one individual found at only one site), the NMDS model did not converge when all species were included. Therefore, we excluded four sites from the data (15, 35, 41, and 42). Each of these four sites hosted only one species (L. dalyae, L. ludovicianus, or P. clarkii) and these three species were found only at these four sites (never overlapping with any other crayfish species). The ordination analysis thus focused on patterns of species composition drawn from burrowers encountered more frequently.

Ordination results showed no evidence of clustering regarding community composition and abundance (Fig. 4.4). Two axes were used with a stress value of 0.06, indicating a good fit (R2 =

1). Our assessment of the usefulness of the two-dimensional NMDS ordination using a post-hoc regression of distances between sampling sites in the ordination of species abundances with distances between sampling sites in the original abundance dataset revealed that ordination axes were orthogonal, with axis 1 (R2 = 0.32) capturing slightly more of the variance in the original abundance data than axis 2 (R2 = 0.22).

Our correlation analysis using Spearman’s rank correlation coefficients determined that five species had strong relationships (ρ > 0.4) with one of the two NMDS ordination axes (Table

4.6). Axis 1 was positively correlated with the abundance of C. striatus (ρ = 0.67) and negatively correlated with the abundance of C. fodiens (ρ = -0.53). Axis 2 was positively correlated with the abundance of P. lophotus (ρ = 0.43) and negatively correlated with the abundance of P. holifieldi

(ρ = -0.46) and P. marthae (ρ = -0.44). The remaining species displayed weaker correlations with ordination axes and were often rarely encountered. P. h. hagenianus was only seen at a couple of sites (one shared with C. striatus) and was positively correlated with axis 1 (ρ = 0.39). H. prominens was also encountered at only two sites (one with C. fodiens and P. lophotus) and those were positively correlated with axis 2 (ρ = 0.33).

82 Our species-habitat analysis showed that crayfish composition and abundance were not related to landscape variables. Mantel tests showed no association between species composition and distance to nearest stream (r = -0.04, p = 0.68), channel sinuosity (r = 0.005, p = 0.43), rate of elevation change (r = 0.01, p = 0.42), or land use characteristics (r = -0.01, p = 0.56).

Discussion This study was the first to use geospatial data to document the influence of geomorphological factors on floodplains a landscape scale for a suite of burrowing crayfish species. Our results partially supported our hypothesis that burrowers would be distributed in areas within a channel migration path, areas near streams with a greater sinuosity, areas with a greater floodplain connection, and predominantly forested areas. While we did find that burrowing crayfish presence-absence was associated with greater channel sinuosity and greater floodplain connectivity, we did not predict a negative relationship with channel migration or with forested areas. We also did not find any significant associations between community composition and landscape-scale environmental variables.

The significant finding of this study is that while remotely sensed geomorphological factors can be used to predict burrowing crayfish presence, they cannot be used to predict individual species distributions or how those distributions will change. The lack of association of species composition and abundance with any landscape-level variables suggests that studies of local-scale environmental variables may be better suited for determining species-habitat associations for burrowing crayfish. Although Dyer et al. (2013) and Nolen et al. (2014) were able to link stream-dwelling crayfish species-specific responses to coarse-scale environmental variables (elevation, temperature, geology, land use, stream order), they found that the importance of various local- and landscape-scale variables was species and spatial scale

83 dependent, with finer grained data producing more accurate distribution models and predictions.

This emphasizes the value of collection efforts and mapping efforts that establish small-scale changes in habitat characteristics.

Although we found that channel migration is moderately correlated with shallow groundwater, we did not find that sites in the path of a migrating stream channel were more likely to harbor burrowing crayfish on a landscape scale. Enhanced lateral channel migration can result in cutoff meanders that develop oxbow lakes or seasonally filled depressions which enhance floodplain habitat diversity and increase sediment and water retention (Choné and Biron

2016). They could be important factors for burrowing crayfish site selection. In a previous study conducted in the same watershed but at the local scale, we determined that burrowing crayfish were more likely to be present in areas with shallow groundwater, however we also did not find crayfish present in areas that were 0-20 m from the stream (Bearden et al. 2020, unpublished data). The lack of crayfish in areas adjacent to the stream agrees with the findings of this study.

Of the sites where crayfish were found (n = 43), 21% were within a migration path, while 79% were outside of the migration path (Table 4.4). Contrary to our predictions, the environment created by channel migration may be too dynamic and possibly too disruptive to promote burrowing crayfish biodiversity. Burrowing crayfish need access to shallow groundwater and also the environmental stability found farther away from the stream channel. Though distance to nearest stream was not included in our presence analysis due to collinearity with channel migration, our raw data shows that of the total sites with crayfish present (n=43), 93% were greater than 20 m from the nearest stream (Fig. 4.5A). The location of burrowing crayfish farther from streams in the floodplain agrees with habitat studies of primary burrower Distocambarus crockeri Hobbs and Carlson 1983, a species found to be positively associated with a seasonally

84 accessible water table and distance to nearest stream in South Carolina, USA (Welch and

Eversole 2006).

In addition to channel migration, we also found that channel sinuosity predicted crayfish presence-absence, with crayfish being more likely to be present in areas influenced by streams with a higher sinuosity. Typically, sinuosity increases as channel gradient and dominant sediment particle size decrease (Rogsen 1996). The decreased channel gradient may facilitate deposition of smaller particle sizes in local patches (Valenza et al. 2020), agreeing with our finding that sinuosity is positively correlated with local soil conditions. Burrowing crayfish studies have shown that species prefer finer-grained sediments such clay soils (Grow and

Merchant 1980, Loughman et al. 2012) and loamy floodplain soils (Helms et al. 2013), and our previous study found that burrowing crayfish prefer areas with increased soil resistance (Bearden et al. 2020, unpublished data). More sinuous channels also reflect a decreased anthropogenic influence (i.e., channelization), which may also have benefits for burrowing crayfish presence.

We also found that crayfish were more likely to be present in areas with a lower rate of elevation change, i.e. greater floodplain connectivity. Areas with high connectivity have a shallow water table and experience longer periods of inundation locally due to decreased runoff

(Galay 1983, Amoros and Bornette 2002). An accessible water table has been shown to be a habitat requirement for many species of burrowing crayfish, especially those that construct burrows with no connection to open water (Hobbs 1981, Grow and Merchant 1980, Loughman et al. 2012, Helms et al. 2013). Crayfish presence-absence and species-composition vary with groundwater depth and inundation duration (Bearden, unpublished data, 2020). In addition to featuring shallow groundwater, these sites may be critical for certain species because of the presence of floodplain pools which provide habitat for mating, egg development, and predator

85 avoidance (Hobbs 1981, Taylor and Schuster 2004, Loughman and Simon 2011, Barnett et al.

2017).

Contrary to our predictions, we found that crayfish were more likely to be found in areas with a lower percentage of forested land use. This relationship with sites containing little to no canopy cover may be the result of local site selection favoring an absence of large tree roots that may hinder burrow construction. These open sites in our study area were predominantly disturbed sites in the form of agricultural fields or roadside ditches. Though we did not find any species-associations with land use, other studies have shown that tolerance for disturbance may be species-specific. Rhoden et al. (2016) found Creaserinus harpi Hobbs and Robison 1985 and

Procambarus reimeri Hobbs 1979 more frequently in areas with increased land use disturbance and secondary succession (roadside ditches) in Arkansas, USA, while Loughman et al. (2012) found that C. fodiens was more likely to be found in mature forests in West Virginia, USA.

The increased likelihood of finding burrowers in more open areas may also be the “ghost of land use past” (Harding et al. 1998). This watershed was previously open tall grass prairie prior to settlement in 1817 and featured characteristically alkaline soils at lower elevations with large amounts of montmorillonite clay known to shrink and swell with soil moisture fluctuations

(Wilson 1981). Early landscape descriptions include Mohr’s (1901) record of cedar glades, post oak associations, canebrakes, and open, tall grass prairies and Harper’s (1913) notes regarding the numerous natural treeless areas. After the advent of agriculture, fire exclusion, erosion, and development changed the vegetative composition. Canebrakes could only be found near stream banks; other native prairie vegetation was limited to cultivated field borders (Mohr 1878); and erosion removed soil material during peak cotton production (1850-1920; Dixon and Nash

1968). Today the watershed remains predominantly agricultural with most areas classified as

86 either “pasture/hay” or “cultivated crops” (USDA NRCS 2016). Small remnants of prairie remain, and the ecological importance of prairie ecosystems has been recognized in Alabama’s

State Wildlife Action Plan with Black Belt prairies being listed as “critically imperiled”

(ADCNR 2015). Currently, two members of the Hagenianus species group (P. h. hagenianus and P. holifieldi), which live in this watershed, appear to be endemic to prairie regions.

Procambarus h. hagenianus is found only in the Black Belt prairie of Alabama and Mississippi while P. holifieldi is restricted to the Bogue Chitto Creek watershed in Alabama (McGregor et al.

2018). It is unknown how advances in agriculture will affect survival of these rare species.

Although pesticide use is currently widespread for row crop production and could be deleterious for aquatic organisms, toxicity studies for burrowing crayfish are lacking. Most farmers do practice conservation tillage that has improved soil conditions benefitting species using floodplain habitats (personal observation), but more research is needed regarding how best management practices aimed at grassland restoration and reducing erosion and runoff can benefit crayfish populations. Additionally, power line and road right-of-ways that must be maintained regularly may also serve to help protect these species.

Of the 10 crayfish species collected, only three were found to inhabit sites without co- occurrence (L. dalyae, L. ludovicianus, and P. clarkii). The remaining species were found in various combinations with one site (13) providing habitat for members of all three types of burrowers (primary, secondary, and tertiary). Based on the correlations with our NMDS axes, our crayfish composition data was best described by one gradient discriminating sites with a high abundance of secondary burrower C. striatus from sites with a high abundance of primary burrower C. fodiens (axis 1) and a second gradient positioning sites with a high abundance of tertiary burrower P. lophotus far from sites with a high abundance of primary burrower P.

87 holifieldi and tertiary burrower P. marthae. The lack of distinct clusters regarding community composition mirrored that of our previous study of local burrower presence (Bearden et al. 2020, unpublished data). Of the total number of sites with crayfish present in this study, 35% (n=15) had members of more than one burrowing type captured at them. Noteworthy crayfish collections during this study include the first watershed record of H. prominens, a species of high conservation concern in Alabama (McGregor et al. 2018), and additional locations for P. holifieldi, a species previously known from only the type locality.

In addition to providing a link between aquatic and terrestrial communities locally, our study suggests that burrowing crayfish distribution watershed-wide also indicates the connection between large-scale geomorphological processes and local hydrogeological factors. Our research shows that the influence of geomorphological processes extends beyond the known habitat creation for permanent surface water communities (Shields et al. 1994, Tockner et al. 1999b,

Ward et al. 1999, Amoros and Bornette 2002, Bellmore and Baxter 2014) to also impact aquatic species that rely solely on shallow groundwater and seasonal pools, adding another call to action for protecting natural floodplains and unaltered stream channels. Even small anthropogenic alterations to stream channels and floodplains can significantly reduce floodplain spatial heterogeneity (Wohl and Iskin 2019), i.e. through lowering groundwater levels in the adjacent floodplain (Galay 1983, Amoros and Bornette 2002), and floodplain management focused on ecosystem restoration should incorporate geomorphological processes driving floodplain spatial heterogeneity (Ward and Stanford 1995, Florsheim and Mount 2002, Wohl and Iskin 2019). Our study reveals that those same processes also drive burrowing crayfish biodiversity and that a better understanding of these dynamic systems is vital for protecting species of concern. Because our study successfully demonstrated that geospatial data can be used to predict burrowing

88 crayfish presence, management plans benefitting multiple burrowing crayfish can now be created more efficiently using landscape-level variables that do not require costly field measurements.

However, species-specific conservation plans for burrowers still require analysis of local environmental variables.

The observed high level of crayfish biodiversity watershed-wide also warrants additional research regarding the impacts of water quantity on local and landscape-level hydrogeological and geomorphological processes. Studies of the impacts of low-flow or instream flow on biodiversity are gaining traction due in part to increased demands on water resources (Papadaki et al. 2020, Abdi and Yasi 2015, Acreman and Dunbar 2004), but none have incorporated species that rely on floodplain ecosystems. More frequent or prolonged precipitation and drought events could augment or impede changes in channel migration, channel sinuosity, and floodplain connectivity, affecting preferred local hydrogeological factors and potentially shifting crayfish distributions. An increase in anthropogenic land modification may also affect habitat suitability and availability. Assessing which landscape level variables are affecting both water quantity and species distributions in the face of drought, flooding, and population growth will help inform both water policy and species conservation efforts.

Acknowledgments We thank Guenter Schuster, retired professor, Eastern Kentucky University, for assistance with crayfish identification; Emma Arneson of the University of Alabama, Parker

Nenstiel and Daniel West of the Geological Survey of Alabama, and Jamekia Durrough-

Pritchard and Anne Wynn, formerly of GSA, for field assistance. This project was conducted in accordance with the Alabama Department of Natural Resources Scientific Collection Permit

Number 2018030883468680.

89 Literature Cited Abdi, R. and M. Yasi. 2015. Evaluation of environmental flow requirements using eco- hydrologic-hydraulic methods in perennial rivers. Water Science and Technology 72:354- 363. Acreman, M. and M. J. Dunbar. 2004. Defining environmental river flow requirements - a review. Hydrology and Earth System Sciences 8:861-876. Akaike, H. 1974. A new look at the statistical model identification. Institute of Electrical and Electronics Engineers Transactions on Automatic Control 19:716–723. Alabama Department of Conservation and Natural Resources (ADCNR) 2015. Alabama wildlife action plan. ADCNR Division of Wildlife and Freshwater Fisheries. Montgomery, AL, USA. 503 p. Aller, L., T. Bennett, J. Lehr, and R. Petty. 2002. Drastic: a standardized system for evaluating ground water pollution potential using hydrogeologic settings. U.S. Environmental Protection Agency. Washington, D.C., EPA/600/2-85/018. Amoros, C. and G. Bornette. 2002. Connectivity and biocomplexity in waterbodies of riverine floodplains. Freshwater Biology 47:761–776. Appling, A. P., E. S. Bernhardt, and J. A. Stanford. 2014. Floodplain biogeochemical mosaics: a multidimensional view of alluvial soils. Journal of Geophysical Research: Biogeosciences 119:1538-1553. Barnett, Z. C., S. B. Adams, and R. L. Rosamond. 2017. Habitat use and life history of the vernal crayfish, Procambarus viaeviridis (Faxon, 1914), a secondary burrowing crayfish in Mississippi, USA. Journal of Crustacean Biology 37:544-555. Bayley, P. B. 1991. The flood pulse advantage and the restoration of river-floodplain systems. Regulated Rivers: Research and Management 6:75-86. Bellmore, J. R. and C. V. Baxter. 2014. Effects of geomorphic process domains on river ecosystems: A comparison of floodplain and confined valley segments. River Research and Applications 30:617-630. Benda, L., N. L. Poff, D. Miller, T. Dunne, G. Reeves, G. Pess, and M. Pollock. 2004. The network dynamics hypothesis: How channel networks structure riverine habitats. BioScience 54:413-427. Benda, L., C. Veldhuisen, and J. Black. 2003. Debris flows as agents of morphological heterogeneity at low-order confluences, Olympic Mountains, Washington. Geological Society of America Bulletin 115:1110–1121. Berrill, M. and B. Chenoweth 1982. The burrowing ability of nonburrowing crayfish. American Midland Naturalist 108:199–201. Borcard, D., F. Gillet, and P. Legendre. 2011. Numerical Ecology with R, Use R, Springer Science + Business Media, LLC. New York, NY, USA Brown, A. G., L. Lespez, D. A., Sear, J. J. Macaire, P. Houben, K. Klimek, R. E. Brazier, K. Van Oost, and B. Pears. 2018. Natural vs anthropogenic streams in Europe: history, ecology

90 and implications for restoration, river rewilding, and riverine ecosystem services. Earth Science Reviews 180:185-205. Burnham, K. P. and D. R. Anderson. 2002. Model selection and multimodel inference: A practical information-theoretic approach (2nd ed.). Springer, New York, NY, USA. Choné, G. and P. M. Biron. 2016. Assessing the relationship between river mobility and habitat. River Research and Applications 32:528-539. Collen, B., Loh, J., Whitmee, S., McRae, L., Amin, R. & Baillie, J. E. M. 2009. Monitoring change in vertebrate abundance: the Living Planet Index. Conservation Biology 23:317– 327. DiStefano, R. J., D. D. Magoulick, E. M. Imhoff, and E. R. Larson. 2009. Imperiled crayfishes use hyporheic zone during seasonal drying of an intermittent stream. Journal of the North American Benthological Society 28:142–152. Dixon, J. B. and V. E. Nash. 1968. Chemical, mineralogical, and engineering properties of Alabama and Mississippi Black Belt soils. United States Department of Agriculture. Auburn University, Auburn, Alabama. Southern Cooperative Series No. 130. 69 p. Dudgeon, D., Arthington, A. H., Gessner, M. O., Kawabata, Z.-I., Knowler, D. J., L´evˆeque, C., Naiman, R. J., Prieur-Richard, A.-H., Soto, D., Stiassny, M. L. J. & Sullivan, C. A. 2006. Freshwater biodiversity: importance, threats, status and conservation challenges. Biological Reviews 81: 163–182. Dyer, J. J., S. K. Brewer, T. A. Worthington, and E. A. Bergey. 2013. The influence of coarse- scale environmental features on current and predicted future distributions of narrow- range endemic crayfish populations. Freshwater Biology 58:1071–1088. Elkins, D., S. C. Sweat, B. R. Kuhajda, A. L. George, K. S. Hill, and S. J. Wenger. 2019. Illuminating hotspots of imperiled aquatic biodiversity in the southeastern US. Global Ecology and Conservation 19:1-13. Fetter, C. W. 2001. Applied Hydrogeology, 4th ed. Prentice-Hall, Inc., Upper Saddle River, New Jersey, 598 p. Florsheim, J. L. and J. F. Mount. 2002. Restoration of floodplain topography by sand-splay complex formation in response to intentional levee breaches, Lower Cosumnes River, California. Geomorphology 44:67–94. Foin, T. C., S. P. D. Riley, A. L. Pawley, D. R. Ayres, T. M. Carlsen, P. J. Hodum, and P. V. Switzer. 1998. Improving recovery planning for threatened and endangered species. BioScience 48:177–184. France R. 1992. The North American latitudinal gradient in species richness and geographic range of freshwater crayfish and amphipods. The American Naturalist 139:342–354. Freeman, M. C., C. M. Pringle, E. A. Greathouse, and B. J. Freeman. 2003. Ecosystem- level consequences of migratory faunal depletion caused by dams. American Fisheries Society Symposium 35:255–266. Galay, V. J. 1983. Causes of riverbed degradation. Water Resources Research 19:1057–1090.

91 Górski K., A. D. Buijse, H. V. Winter, J. J. De Leeuw, T. J. Compton, D. A. Vekhov, D. V. Zolotarev, J. A. J. Verreth, and L. A. J. Nagelkerke. 2013. Geomorphology and flooding shape fish distribution in a large-scale temperate floodplain. River Research and Applications 29:1226–1236. Greene, S. L. and J. C. Knox. 2014. Coupling legacy geomorphic surface facies to riparian vegetation: Assessing Red Cedar invasion along the Missouri River downstream of Gavins Point Dam, South Dakota. Geomorphology 204:277–286. Griffith, B., J. M. Scott, J. W. Carpenter, and C. Reed. 1989. Translocation as a species conservation tool: status and strategy. Science 245:477–480. Grow, L. and H. Merchant. 1980. The burrow habitat of the crayfish, Cambarus diogenes diogenes (Girard). American Midland Naturalist 103:231–237. Harding, J. S., E. F. Benfield, P. V. Bolstad, G. S. Helfman, and E. B. D. Jones, III. 1998. Stream biodiversity: the ghost of land use past. Proceedings of the National Academy of Sciences of the United States of America 95:14843-14847. Harper, R. 1913. Economic botany in Alabama. Geological Survey of Alabama. University of Alabama. 357 p. Helms, B. S., W. Budnick, P. Pecora, J. Skipper, E. Kosnicki, J. Feminella, and J. Stoeckel. 2013. The influence of soil type, congeneric cues, and floodplain connectivity on the local distribution of the devil crayfish (Cambarus diogenes (Girard)). Freshwater Science 32:1333-1344. Hobbs, H. H., Jr. 1981. The crayfishes of Georgia. Smithsonian Contributions to Zoology. No. 318. Smithsonian Institution, Washington, D.C., USA. Hughes, F. M. R. 1997. Floodplain biogeomorphology. Progress in Physical Geography 21:501- 529. Jelks, H. L., S. J. Walsh, N. M. Burkhead, S. Contreras-Balderas, E. Diaz-Pardo, D. A. Hendrickson, J. Lyons, N. E. Mandrak, F. McCormick, J. S. Nelson, S. P. Platania, B. A. Porter, C. B. Renaud, J. J. Schmitter-Soto, E. B. Taylor, and M. L. Warren, Jr. 2008. Conservation status of imperiled North American freshwater and diadromous fishes. Fisheries 33:373–407. Jenkins, C. N., K. S. Van Houtan, S. L. Pimm, and J. O. Sexton. 2015. US protected lands mismatch biodiversity priorities. Proceedings of the National Academy of Sciences of the United States of America 112: 5081-5086. Junk, J. J., P. B. Bayley, and R. E. Sparks. 1989. The flood pulse concept in river-floodplain systems. p. 110-127. In: D. P. Dodge (ed.) Proceedings of the International Large River Symposium. Canadian Special Publication of Fisheries and Aquatic Sciences 106. Labbe, T. R. and K. D. Fausch. 2000. Dynamics of intermittent stream habitat regulate persistence of a threatened fish at multiple scales. Ecological Applications 10:1774-1791. Loughman, Z. J. and T. P. Simon. 2011. Zoogeography, taxonomy, and conservation of West Virginia’s Ohio River floodplain crayfishes (Decapoda, Cambaridae). ZooKeys 74:1-78.

92 Loughman, Z. J., S. A. Welsh, and T. P. Simon. 2012. Occupancy rates of primary burrowing crayfish in natural and disturbed large river bottomlands. Journal of Crustacean Biology 32:557–564. McCune, B. and J. B. Grace. 2002. Analysis of Ecological Communities, 2nd ed. MjM Software Design, Gleneden Beach, Oregon. McGregor, S. W., G. A. Schuster, C. A. Taylor, R. A. Bearden, and E. A. Wynn. 2018. An updated report on the distribution and conservation status of the Alabama crayfish fauna. Open file report 1801, Geological Survey of Alabama, Tuscaloosa, AL. Miranda, L. E. 2005. Fish assemblages in oxbow lakes relative to connectivity with the Mississippi River. Transactions of the American Fisheries Society 134:1480–1489. Mohr, Charles. 1878. The forests of Alabama, and their products. In Handbook of Alabama; a complete index to the state. Saffold Berney (editor) Mobile Register print. ___1901. Plant life of Alabama, Alabama edition. The Brown Printing Co., Montgomery, Alabama. Naiman, R. J., T. J. Beechie, L. E. Benda, D. R. Berg, P. A. Bisson, L. H. MacDonald, M. D. O’Connor, P. L. Olson, and E. A. Steel. 1992. Fundamental elements of ecologically healthy watersheds in the Pacific Northwest coastal ecoregion, p. 127–188. In: R. J. Naiman, (ed.). Watershed management: balancing sustainability and environmental change. Springer-Verlag, New York, New York, USA. Neves, R. J. 1999. Conservation and commerce: Management of freshwater mussel (Bivalvia: Unionoidea) resources in the United States. Malacologica 4:461–474. Nolen, M. S., D. D. Magoulick, R. J. Distefano, E. M. Imhoff, and B. K. Wagner. 2014. Predicting probability of occurrence and factors affecting distribution and abundance of three Ozark endemic crayfish species at multiple spatial scales. Freshwater Biology 59:2374–2389. Osborne, W. E., M. W. Szabo, C. W. Copeland, Jr., and T. L. Neathery. 1989. Geologic map of Alabama: Alabama Geological Survey Special Map 221, scale 1:500,000. Papadaki, C., K. Soulis, V. Bellos, L. Ntoanidis, and E. Dimitriou. 2020. Estimation of a Suitable Range of Discharges for the Development of Instream Flow Recommendations. Environmental Processes-An International Journal 7:703-721. R Core Team. 2020. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. Reeves, G. H., L. E. Benda, K. M. Burnett, P. A. Bisson, and J. R. Sedell. 1995. A disturbance- based ecosystem approach to maintaining and restoring freshwater habitats of evolutionarily significant units of anadromous salmonids in the Pacific Northwest. American Fisheries Society Symposium 17:360–370. Reid, A. J., A. K. Carlson, I. F. Creed, E. J. Eliason, P A. Gell, P. T. J. Johnson, K. A. Kidd, T. J. MacCormack, J. D. Olden, S. J. Ormerod, J. P. Smol, W. W. Taylor, K. Tockner, J. C. Vermaire, D. Dudgeon, and S. J. Cooke. 2019. Emerging threats and persistent conservation challenges for freshwater biodiversity. Biological Reviews 94:849-873.

93 Rhoden, C.M., C. A. Taylor, and W. E. Peterman. 2016. Highway to heaven? Roadsides as preferred habitat for two narrowly endemic crayfish. Freshwater Science 35:974-983. Ricciardi, A. and J. B. Rasmussen. 1999. Extinction rates of North American freshwater fauna. Conservation Biology 13: 1220–1222. Richards, S. A., M. J. Whittingham, and P. A. Stephens. 2011. Model selection and model averaging in behavioral ecology: the utility of the IT-AIC framework. Behavioral Ecology and Sociobiology 65:77-89. Richman, N. I., M. Böhm, S. B. Adams, F. Alvarez, E. A. Bergey, J. J. S. Bunn, Q. Burnham, J. Cordeiro, J. Coughran, K. A. Crandall, K. L. Dawkins, R. J. Distefano, N. E. Doran, L. Edsman, A. G. Eversole, L. Füreder, J. M. Furse, F. Gherardi, P. Hamr, D. M. Holdich, P. Horwitz, K. Johnston, C. M. Jones, J. P. G. Jones, R. L. Jones, T. G. Jones, T. Kawai, S. Lawler, M. López-Mejίa, R. M. Miller, C. Pedraza-Lara, A. M. M. Richardson, M. B. Schultz, G. A. Schuster, P. J. Sibley, C. Souty-Grosset, C. A. Taylor, R. F. Thoma, J. Walls, T. S. Walsh, and B. Collen. 2015. Multiple drivers of decline in the global status of freshwater crayfish (Decapoda: Astacidea). Philosophical Transactions of the Royal Society B: Biological Sciences 370:1–11. Rosgen, D. 1996. Applied River Morphology Second Edition. Wildland Hydrology, Pagosa Springs, CO. Sapp, C. D. and J. Emplaincourt. 1975. Physiographic regions of Alabama: Geological Survey of Alabama Special Map 168. University of Alabama Press, Tuscaloosa, AL, USA. Schlosser, I. J. and P. L. Angermeier. 1995. Spatial variation in demographic processes in lotic fishes: conceptual models, empirical evidence, and implications for conservation. American Fisheries Society Symposium 17:360–370. Schramm, H. L., Jr. and M. A. Eggleton. 2006. Applicability of the flood‐pulse concept in a temperate floodplain river ecosystem: thermal and temporal components. River Research and Applications 22:543-553. Schwendel, A. C., A. P. Nicholas, R. E. Aalto, G. H. S. Smith, and S. Buckley. 2015. Interaction between meander dynamics and floodplain heterogeneity in a large tropical sandbed river: the Rio Beni, Bolivian Amazon. Earth Surface Processes and Landforms 40:2026-2040. Shields, F. D., S. S. Knight, And C. M. Cooper. 1994. Effects of channel incision on base flow stream habitats and fishes. Environmental Management 18:43–57. Smith, N. D., T. A. Cross, J. P. Dufficy, and S. R. Clough. 1989. Anatomy of an avulsion. Sedimentology 36:1-23. Soil Survey Staff. 2016. The Gridded Soil Survey Geographic (gSSURGO) Database for Alabama. United States Department of Agriculture, Natural Resources Conservation Service. Available online at https://gdg.sc.egov.usda.gov/. November 16, 2015 (FY2016 official release). Taylor, C. A. 2002. Taxonomy and conservation of native crayfish stocks. In D. M. Holdich (Ed.), Biology of freshwater crayfish (pp. 236-257). Blackwell Scientific, Oxford, UK.

94 Taylor, C. A., and G. A. Schuster. 2004. Crayfishes of Kentucky. Illinois Natural History Survey Bulletin 28:1-219. Taylor, C. A., G. A. Schuster, J. E. Cooper, R. J. Di Stefano, A. G. Eversole, P. Hamr, H. H. Hobbs, Jr., H. W. Robison, C. E. Skelton, and R. E. Thomas. 2007. A reassessment of the conservation status of crayfishes of the United States and Canada after 10+ years of increased awareness: Fisheries, 32:372–389. Thomaz S. M., L. M. Bini, and R. L. Bozelli. 2007. Floods increase similarity among aquatic habitats in river-floodplain systems. Hydrobiologia 579:1–13 Tissot, L., V. Bret, H. Capra, P. Baran, and V. Gouraud. 2017. Main potential drivers of trout population dynamics in bypassed stream sections. Ecology of Freshwater Fish 26:336- 346. Tockner K., D. Pennetzdorfer, N. Reiner, F. Schiemer, and J. V. Ward. 1999a. Hydrological connectivity, and the exchange of organic matter and nutrients in a dynamic river– floodplain system (Danube, Austria). Freshwater Biology 41:521–535. Tockner, K., F. Schiemer, C. Baumgartner, G. Kum, E. Weigand, I. Zweimuller, and J. V. Ward. 1999b. The Danube restoration project: species diversity patterns across connectivity gradients in the floodplain system. Regulated Rivers: Research and Management 15:245– 258. Tockner, K. and J. A. Stanford. 2002. Riverine flood plains: present state and future trends. Environmental Conservation 29: 308–330. U.S. Department of Agriculture Natural Resources Conservation Service. 2016. National Land Cover Dataset, National Geospatial Center of Excellence, http://datagateway.nrcs.usda.gov/GDGOrder.aspx, accessed 5/30/2020. U. S. Geological Survey. 2016. USGS National Hydrography Dataset (NHD) downloadable data collection—National Geospatial Data Asset (NGDA) National Hydrography Dataset (NHD): Rolla, Missouri, and Denver, Colorado. USGS National Geospatial Technical Operations Center (NGTOC) http://nhd.usgs.gov, accessed 5/30/20. Valenza, J. M., D. A. Edmonds, T. Hwang, and S. Roy. 2020. Downstream changes in river avulsion style are related to channel morphology. Nature Communications 11:2116. Ward, J. V. 1998. Riverine landscapes: biodiversity patterns, disturbance regimes, and aquatic conservation. Biological Conservation 83:269–278. Ward, J. V. and J. A. Stanford. 1995. Ecological connectivity in alluvial river ecosystems and its disruption by flow regulation. River Research and Applications 11:105-119. Ward, J. V., K. Tockner, and F. Schiemer. 1999. Biodiversity of floodplain river ecosystems: ecotones and connectivity. Regulated Rivers: Research and Management 15:125–139. Warren, Jr., M. L., B. M. Burr, S. J. Walsh, H. L. Bart, Jr., R. C. Cashner, D. A. Etnier, B. J. Freeman, B. R. Kuhajde, R. L. Mayden, H. W. Robison, and W. D. Starnes. 2000. Diversity, distribution, and conservation status of the native freshwater fishes of the southern United States. Fisheries 25:7–31.

95 Welch, S. M. and A. G. Eversole. 2006. The occurrence of primary burrowing crayfish in terrestrial habitat. Biological Conservation 130:458-464. Wiley, M. J., S. L. Kohler, and P. W. Seelbach. 1997. Reconciling landscape and local views of aquatic communities: lessons from Michigan trout streams. Freshwater Biology 37:133– 148. Wilson, T. H. 1981. Natural history of the Black Belt prairie. Journal of the Alabama Academy of Science. 52:10-19. Wohl, E. and E. Iskin. 2019. Patterns of floodplain spatial heterogeneity in the Southern Rockies, USA. Geophysical Research Letters 46:5864-5870. World Wide Fund. 2018. Living Planet Report 2018: Aiming Higher (Eds M. Grooten and R. E. A. Almond). WWF International, Gland, Switzerland.

96 Table 4.1. Correlation coefficients between pairs of environmental variables used in this study. Coefficients with significant p values (<0.05) are in bold.

Distance Channel Channel Relative Agriculture Forest Wetland to stream migration sinuosity slope Distance to -0.41 -0.10 -0.26 0.11 -0.17 0.02 stream Channel -0.41 0.08 0.27 -0.30 0.39 0.09 migration Channel -0.10 0.08 0.00 -0.11 -0.14 0.29 sinuosity Relative -0.26 0.27 0.00 -0.31 0.56 -0.10 slope Agriculture 0.11 -0.30 -0.11 -0.31 -0.64 -0.65 Forest -0.17 0.39 -0.14 0.56 -0.64 -0.09 Wetland 0.02 0.09 0.29 -0.10 -0.65 -0.09

97 Table 4.2. Site data including locations and values for landscape variables used in this study.

Site Latitude Longitude Channel Channel Rate of Agriculture Forest Wetland migration sinuosity elevation (%) (%) (%) change 1 32.4146 -87.2964 0 1.05 0.01 40.22 17.00 33.00 2 32.4996 -87.3723 0 1.26 0.00 71.49 13.68 4.02 3 32.5587 -87.2981 0 1.14 0.01 71.26 10.08 5.00 4 32.501 -87.3477 0 1.01 0.03 51.65 6.42 7.93 5 32.4363 -87.2940 0 1.04 0.02 63.34 21.50 1.06 6 32.2917 -87.3461 1 1.15 -0.05 66.16 12.53 14.43 7 32.2022 -87.2046 0 1.12 0.01 37.58 14.67 41.16 8 32.2522 -87.2364 0 1.13 0.03 5.99 28.76 54.87 9 32.3534 -87.3381 0 1.02 0.01 49.68 22.23 13.52 10 32.5331 -87.3886 0 1.01 0.01 19.64 52.81 19.18 11 32.3661 -87.2466 0 1.13 0.01 71.54 7.77 14.46 12 32.4391 -87.3458 0 1.10 0.00 43.00 29.26 25.42 13 32.2372 -87.2934 1 1.18 0.00 14.18 45.02 29.41 14 32.3459 -87.1816 0 1.01 0.00 6.73 35.43 55.29 15 32.4448 -87.4113 0 1.01 0.00 8.95 35.15 47.17 16 32.4685 -87.5070 0 1.04 0.03 5.43 40.22 36.55 17 32.4499 -87.4644 0 1.11 0.00 71.45 7.33 17.56 18 32.5722 -87.3921 1 1.03 0.00 36.62 18.12 37.97 19 32.4398 -87.3590 0 1.06 0.01 37.27 16.04 37.87 20 32.4468 -87.3535 0 1.18 0.01 79.89 3.24 8.95 21 32.4474 -87.2974 1 1.22 0.01 44.90 8.13 39.92 22 32.3858 -87.2544 0 1.09 0.02 23.67 11.35 59.24 23 32.4387 -87.3797 0 1.52 0.00 10.19 18.63 54.54 24 32.4709 -87.2293 0 1.11 0.02 26.51 59.36 7.65 25 32.3079 -87.2838 0 1.19 0.05 75.62 6.76 10.54 26 32.4028 -87.2477 0 1.07 0.01 29.01 26.08 38.49 27 32.5277 -87.2812 0 1.08 0.01 50.74 34.05 4.96 28 32.3217 -87.3483 1 1.52 0.02 88.04 1.75 2.04 29 32.4666 -87.3306 0 1.15 0.00 76.27 2.89 6.85 30 32.3236 -87.3328 0 1.06 0.01 76.22 14.65 3.85 31 32.4163 -87.3354 0 1.43 0.01 6.59 45.33 40.86 32 32.5557 -87.3226 0 1.09 0.02 70.46 13.31 10.75 33 32.6313 -87.3912 0 1.23 0.03 36.39 15.15 43.66 34 32.2857 -87.3055 0 1.95 0.05 43.52 24.60 22.53 35 32.3046 -87.3274 1 1.90 0.11 5.19 3.14 86.02 36 32.5720 -87.3042 0 1.06 0.02 83.31 6.43 0.49 37 32.2750 -87.2817 1 1.11 0.09 69.31 17.01 5.65 38 32.4607 -87.2556 0 1.05 0.02 27.94 16.71 47.75 39 32.5308 -87.3284 0 1.23 0.02 16.92 2.12 23.74

98 Site Latitude Longitude Channel Channel Rate of Agriculture Forest Wetland migration sinuosity elevation (%) (%) (%) change 40 32.3480 -87.3124 0 1.47 0.03 11.01 21.18 65.32 41 32.3449 -87.3131 1 1.34 0.01 18.39 54.40 14.38 42 32.3264 -87.3012 0 1.42 0.00 4.04 46.26 38.20 43 32.3150 -87.2914 1 1.13 0.00 6.34 27.38 60.87 44 32.2502 -87.2716 1 1.28 0.08 4.21 45.29 45.95 45 32.2396 -87.2705 1 1.02 0.08 0.00 42.74 55.50 46 32.2304 -87.2787 1 1.07 0.00 2.00 26.47 69.44 47 32.2296 -87.2777 0 1.01 0.01 0.00 45.71 48.98 48 32.2264 -87.2763 1 1.05 0.01 0.00 43.23 46.67 49 32.2413 -87.2696 1 1.01 0.40 0.00 97.74 0.00 50 32.2407 -87.2700 1 1.01 0.12 0.00 100.00 0.00 51 32.2277 -87.2597 0 1.09 0.16 11.40 39.43 37.81 52 32.6358 -87.3391 0 1.03 0.05 12.08 64.04 4.94 53 32.5419 -87.3553 1 1.08 0.02 35.54 43.76 5.40 54 32.5480 -87.3670 1 1.11 0.02 19.26 55.15 23.56

99 Table 4.3. Top candidate models ranked by AICc describing variation in crayfish presence. K = the number of parameters, ΔAICc = the difference in AICc value for each model, relative to the top model, wi = Akaike’s model weight. Only models falling within Δ2 AICc are included.

Model K AICc ΔAICc wi Channel migration + channel sinuosity + rate of elevation change + forest 5 26.54 0 0.515 Channel migration + channel sinuosity + forest 4 28.08 1.54 0.239

100 Table 4.4. Pearson’s correlation coefficients between pairs of measured local environmental variables and landscape variables calculated for each sampling site (N = 50) during a previous burrowing crayfish presence-absence study (Bearden et al. 2020, unpublished data). Coefficients with significant p values (<0.05) are in bold.

Groundwater Inundation Soil depth days resistance Channel migration -0.30 0.21 -0.21 Channel sinuosity 0.11 -0.05 0.50 Rate of elevation change 0.10 -0.27 -0.48 Forest (%) -0.56 0.03 -0.35 Wetland %) 0.56 -0.03 0.35

101 Table 4.5. Crayfish collection sites and number collected. All collections were made by hand excavation from March to May of 2019.

Site Cambarus1 Creaserinus Hobbseus Lacunicambarus Lacunicambarus Procambarus Procambarus Procambarus Procambarus Procambarus striatus (s) fodiens (p) prominens daylae (p) ludovicianus (p) clarkii (s) hagenianus holifieldi (p) lophotus (t) marthae (t) (t) hagenianus (p) 1 0 5 0 0 0 0 0 0 0 0 2 3 0 0 0 0 0 0 0 0 3 3 3 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 2 0 0 5 0 4 0 0 0 0 0 0 0 0 6 0 0 0 0 0 0 0 0 1 2 7 0 12 0 0 0 0 0 0 0 0 8 4 0 0 0 0 0 0 0 0 0 9 1 0 0 0 0 0 2 0 0 0 10 2 0 0 0 0 0 0 0 0 0 11 0 3 0 0 0 0 0 0 1 1 12 0 3 0 0 0 0 0 0 7 0 13 1 4 0 0 0 0 0 0 3 3 14 0 8 1 0 0 0 0 0 7 0 15 0 0 0 0 0 4 0 0 0 0 16 2 0 0 0 0 0 0 0 1 0 17 1 0 0 0 0 0 0 0 0 1 18 4 2 0 0 0 0 0 0 0 0 19 0 0 0 0 0 0 0 0 3 0 20 0 0 0 0 0 0 1 0 0 0 21 0 1 0 0 0 0 0 0 0 1 22 0 2 0 0 0 0 0 0 0 0 23 0 2 0 0 0 0 0 0 3 1 24 0 0 0 0 0 0 0 0 1 0

102 Site Cambarus1 Creaserinus Hobbseus Lacunicambarus Lacunicambarus Procambarus Procambarus Procambarus Procambarus Procambarus striatus (s) fodiens (p) prominens daylae (p) ludovicianus (p) clarkii (s) hagenianus holifieldi (p) lophotus (t) marthae (t) (t) hagenianus (p) 25 0 0 0 0 0 0 0 0 4 0 26 0 5 0 0 0 0 0 0 0 0 27 0 1 0 0 0 0 0 0 0 0 28 0 7 0 0 0 0 0 0 0 0 29 0 0 0 0 0 0 0 0 1 2 30 0 2 0 0 0 0 0 0 1 0 31 0 0 0 0 0 0 0 0 1 0 32 0 0 1 0 0 0 0 0 0 0 33 0 1 0 0 0 0 0 3 0 0 34 0 1 0 0 0 0 0 0 0 1 35 0 0 0 1 0 0 0 0 0 0 36 0 1 0 0 0 0 0 0 0 0 37 0 1 0 0 0 0 0 0 3 2 38 0 2 0 0 0 0 0 0 0 0 39 0 1 0 0 0 0 0 0 0 1 40 0 0 0 0 0 0 0 1 0 0 41 0 0 0 1 0 0 0 0 0 0 42 0 0 0 0 1 0 0 0 0 0 43 0 1 0 0 0 0 0 0 0 0 1p: primary burrower; s: secondary burrower; t: tertiary burrower

103 Table 4.6. Spearman’s rank correlations coefficients comparing burrowing crayfish species with MDS axes 1 and 2.

ρ (sign of correlation)

Species MDS1 MDS2 C. striatus 0.67 (+) 0.06 (+) C. fodiens 0.53 (-) 0.04 (+) H. prominens 0.11 (-) 0.33 (+) P. h. hagenianus 0.39 (+) 0.32 (-) P. holifieldi 0.37 (-) 0.46 (-) P. lophotus 0.23 (+) 0.43 (+) P. marthae 0.31 (+) 0.44 (-) The strength (ρ) of the correlation and the direction (+ or -) are shown, and all correlations with an ρ > 0.4 are highlighted in bold.

104

Figure 4.1. Study area in the Bogue Chitto Creek watershed in the Black Belt Prairie physiographic district in Dallas and Perry counties, Alabama, USA.

105

Figure 4.2. LiDAR imagery used to determine channel migration status for each sampling site. For example, Sampling site 6 is located in the migration path of a stream channel.

106

Figure 4.3. Model-estimated relationships (in black) between the probability of a crayfish being present and statistically supported landscape predictors. Predicted relationships (black points in A, black lines in B-D) and 95% confidence intervals (CIs) were calculated holding all other predictors at their mean value or baseline level (migration = 1). The raw data are grouped by equally spaced bins along the x-axis and included as gray points +/- 95% CI.

107

Figure 4.4. Plot showing the ordination results from NMDS for species composition and abundance. Species locations are shown in blue circles, site locations in orange circles.

108

Figure 4.5. Raw data for species-specific responses to distance to nearest stream (A), sinuosity (B), rate of elevation change (C), and forest cover (D).

109 Appendix 4.1. Coefficient estimates for the GLM (binomial errors, logit link) best explaining variation (lowest AICc value; the “top model”) in burrowing crayfish presence, as well as the GLMs that included each variable in isolation. Channel migration: a 2-level factor (0 or 1); Channel sinuosity: continuous; Rate of elevation change: continuous; Forest: continuous.

Probability of presence Fixed effects Estimate P [Standard Error] Intercept 5.94 [2.41] * Channel migration1 -3.51 [1.76] * Channel sinuosity 4.64 [2.14] * Rate of elevation -1.72 [0.99] . change Forest -3.79 [1.94] . R2 0.81

Intercept 2.42 [0.60] *** Channel migration1 -2.31 [0.77] ** R2 0.27

Intercept 1.90 [0.58] ** Channel sinuosity 1.80 {1.04] . R2 0.16

Intercept 1.47 [0.39] *** Rate of elevation -1.77 [0.67] ** change R2 0.32

Intercept 2.13 [0.59] *** Forest -2.22 [0.71] ** R2 0.52

N cases 53 P: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

110

CHAPTER 5: CONCLUSIONS AND FUTURE DIRECTIONS Conclusions My dissertation provides novel information regarding the activity patterns of two primary burrowing crayfish as well as much-needed local and landscape scale habitat associations for a suite of burrowing crayfish. I determined peak activity periods for primary burrowing crayfish that will help make collection efforts more productive, and I report local habitat associations that may influence burrowing crayfish site selection as well as the landscape-level variables that may influence burrowing crayfish distribution watershed-wide. Below, I review the primary conclusions of my research, though a more detailed summary can be found in each chapter of this dissertation. Following a synopsis of conclusions for each dissertation chapter, I discuss future research avenues.

In Chapter 2, I established the relationship between environmental cues and out-of- burrow activity patterns in two primary burrowing crayfish species. Both L. erythrodactylus and

P. holifieldi showed strong diel patterns that were characterized by primarily nocturnal activity.

Activity was lowest during winter for both species, and increased with daylength in L. erythrodactylus, but was highest in the fall, not the spring, in P. holifieldi. Groundwater temperature predicted activity better than water depth (these two variables were highly positively correlated), and contrary to expectations, out-of-burrow activity decreased with increasing groundwater temperature. Although we are unable to explicitly demonstrate a functional link between groundwater temperature, air temperature and crayfish behavior, our analyses suggest that the observed seasonal pattern of activity may be linked to thermal regulation. Out-of-burrow

111 behavior in the spring, for example, may expose crayfish to warm air temperatures at a time when groundwater temperatures are cool (e.g., during April – May). We further suggest that groundwater and temperature may interact to drive seasonal activity and that thermal regulation may be a potential advantage of out-of-burrow behavior, in addition to foraging and mating behaviors. A distinct lull in activity from October through March for both L. erythrodactylus and

P. holifieldi may reflect individuals devoting time to reproduction, presumably due to mated females sequestering in their burrows during egg and juvenile development. Since our models agree that water temperature is a driver for activity for both L. erythrodactylus and P. holifieldi, perhaps primary burrowers are using warmer temperatures as a more suitable thermal environment for egg and juvenile development. Identifying peak activity periods for primary burrowing crayfish will allow scientists and managers to focus collection efforts during the most active periods. If populations can be sampled more effectively, some of the main challenges associated with primary burrowing crayfish research, namely sampling difficulty and small sample size, can potentially be alleviated.

In Chapter 3, I documented that crayfish are more likely to be distributed in areas with a shallow water table and that different species may indicate the presence of groundwater depths falling within certain ranges dictated by their (species-specific) life history requirements.

Burrowing crayfish are often associated with a shallow water table (Hobbs 1981; Helms et al.

2013), but this study was the first to use field experiments to quantify the influence of groundwater depth on a local scale for multiple species. The possibility that burrowing crayfish could serve as indicators of shallow groundwater presence and that some crayfish species may employ life history and burrowing strategies that represent variations in the traditional burrower classification system are two key findings of this research. Additionally, my data suggests that

112 floodplain habitats facilitate the coexistence of all three burrower types at the same locations, potentially because of the seasonal dynamics of floodplain pools. This reinforces the need for additional, local species-specific habitat studies. Identifying areas that offer a mosaic of groundwater depths and inundation durations may help provide critical habitat for several species of burrowing crayfish.

In Chapter 4, my research showed that burrowing crayfish presence was influenced by landscape-level variables. Presence was positively associated with channel sinuosity and floodplain connectivity but negatively associated with channel migration and forested areas.

Contrary to my predictions, the environment created by channel migration may be too dynamic and possibly too disruptive to promote burrowing crayfish biodiversity. The location of crayfish at relatively long distances from stream channels may be the result of a need for increased soil and sediment stability. A decreased channel gradient driving increased channel sinuosity may create deposition of smaller particle sizes in local patches (Valenza et al. 2020), creating preferred habitat for burrowing crayfish in the form of heterogeneous sediment deposition. The association with areas containing little to no forest canopy cover may be the result of habitat selection favoring an absence of large tree roots that could hinder burrow construction.

Alternatively, distribution may be an artefact of an historical association with open, prairie habitats. The location of burrowing crayfish in areas with a low floodplain surface gradient also suggests a possible concurrent habitat need for a more intensely connected floodplain habitats, requiring conditions favorable for a shallow water table and long periods of inundation due to decreased runoff potential.

My research shows that the influence of geomorphological processes for aquatic species that rely solely on shallow groundwater and floodplain pools and supports a call to action for

113 policies protecting natural floodplains and unaltered stream channels. My study reveals that those same processes also drive burrowing crayfish biodiversity and that a better understanding of these dynamic systems is vital for protecting species of concern.

Future Directions Understanding the relationship between out-of-burrow crayfish activity and environmental cues driving such behavior is a crucial first step toward addressing some of the most basic, and largely unanswered, questions concerning burrowing crayfish biology. While my research suggests that water temperature could be an abiotic cue for reproductive activities, more studies are needed to determine if this potential relationship is one that is unique to either of the crayfish species chosen for my studies. At minimum, additional laboratory studies are needed to confirm relationships between water temperature and reproductive strategies.

Identifying floodplains that offer a diverse mosaics of groundwater depths and inundation durations may help provide critical habitat for several species of burrowing crayfish as well as other aquatic and terrestrial species which rely on shallow groundwater and floodplain pools, thereby enhancing biodiversity. Establishing what regime is preferred by certain species will not only increase opportunities for effective study of burrower ecology, but also aid in species conservation plans. Such information can be coalesced into a management plan that factors in the effects of flooding or drought on other aquatic organisms (Townsend et al. 1997). The strong relationship between crayfish presence and groundwater depth provides the opportunity for these species to become possible indicators of shallow groundwater presence. The identification of such relationships and their development into environmental indicators will be increasingly more important in the context of how climate change might influence local species diversity. Water quantity and access, both above and below ground, will be an issue that continues to receive

114 attention due to both significant ecological and economic impacts. A better understanding of the ecology and hydrogeology interactions in floodplains will add priority to projects that target multidisciplinary approaches to water and species conservation.

In addition to providing a link between aquatic and terrestrial communities locally, my studies suggest that burrowing crayfish presence signals the connections between large-scale geomorphological processes and local hydrogeological factors. My research has shown that the influence of geomorphological processes extends beyond habitat creation for stream communities to affect aquatic species that rely solely on shallow groundwater and floodplain pools, adding another call to action for protecting natural floodplains and unaltered stream channels. Even small anthropogenic alterations to stream channels and floodplains can significantly reduce floodplain spatial heterogeneity (Wohl and Iskin 2019), and floodplain management focused on ecosystem restoration should incorporate geomorphological processes driving floodplain spatial heterogeneity (Ward and Stanford 1995, Florsheim and Mount 2002,

Wohl and Iskin 2019). My studies reveal that these same processes also drive burrowing crayfish biodiversity and that a better understanding of these dynamic systems is vital for protecting species of concern.

At the landscape level, the possibility that the association of burrowing crayfish with more open areas could be the “ghost of land use past” warrants additional research at a larger scale. While current populations of crayfish in my study area appear to persist given the current land use, it is unknown how advances in agriculture could affect their survival. Though pesticide use is currently widespread for row crop production and could be deleterious for aquatic organisms, most farmers do practice conservation tillage that has improved soil conditions that could benefit species using floodplain habitats. Toxicity studies for burrowing crayfish are

115 lacking, and more research is needed regarding how best management practices aimed at grassland restoration and reducing erosion and runoff can benefit crayfish populations.

The observed high level of crayfish biodiversity watershed-wide also warrants additional research regarding the impacts of water quantity on local and landscape-level hydrogeological and geomorphological processes. Studies of the impacts of low-flow or instream flow on biodiversity are gaining traction due in part to increased demands on water resources, but none have incorporated species that use floodplain ecosystems. Because the majority of streams in the southeastern United States are sustained during baseflow by shallow groundwater, understanding groundwater-surface water dynamics via surface and subsurface interactions will become increasingly more important. Increased precipitation and flood events and changes in land use could potentially shift crayfish distributions if floodplains are significantly altered. Assessing which landscape level variables are affecting both water quantity and crayfish distributions in the face of drought, flooding, and population growth will help inform both water policy and species conservation efforts.

Literature Cited Florsheim, J. L. and J. F. Mount. 2002. Restoration of floodplain topography by sand-splay complex formation in response to intentional levee breaches, Lower Cosumnes River, California. Geomorphology 44:67–94. Helms, B. S., W. Budnick, P. Pecora, J. Skipper, E. Kosnicki, J. Feminella, and J. Stoeckel. 2013. The influence of soil type, congeneric cues, and floodplain connectivity on the local distribution of the devil crayfish (Cambarus diogenes (Girard)). Freshwater Science 32:1333-1344. Hobbs, H. H. 1981. The crayfishes of Georgia. Smithsonian Contributions to Zoology. No. 318. Smithsonian Institution, Washington, D.C. Townsend, C. R. and M. R. Scarbrook. 1997. The intermediate disturbance hypothesis, refugia, and biodiversity in streams. Limnology and Oceanography 42:938-949. Valenza, J. M., D. A. Edmonds, T. Hwang, and S. Roy. 2020. Downstream changes in river avulsion style are related to channel morphology. Nature Communications 11:2116.

116 Ward, J. V. and J. A. Stanford. 1995. Ecological connectivity in alluvial river ecosystems and its disruption by flow regulation. River Research and Applications 11:105-119. Wohl, E. and E. Iskin. 2019. Patterns of floodplain spatial heterogeneity in the Southern Rockies, USA. Geophysical Research Letters 46:5864-5870.

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