Video And Visual Surveys Of Spawning In Devils Hole Pupfish By

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VIDEO AND VISUAL SURVEYS OF SPAWNING IN DEVILS HOLE PUPFISH CYPRINODON DIABOLIS by Ambre Leah Chaudoin A Thesis Submitted to the Faculty of THE SCHOOL OF NATURAL RESOURCES AND THE ENVIRONMENT In Partial Fulfillment of the Requirements For the Degree of MASTER OF SCIENCE WITH A MAJOR IN FISHERIES CONSERVATION AND MANAGEMENT In the Graduate College THE UNIVERSITY OF ARIZONA 2014 2 STATEMENT BY AUTHOR This thesis has been submitted in partial fulfillment of requirements for an advanced degree at the University of Arizona and is deposited in the University Library to be made available to borrowers under rules of the Library. Brief quotations from this thesis are allowable without special permission, provided that accurate acknowledgment of source is made. Requests for permission for extended quotation from or reproduction of this manuscript in whole or in part may be granted by the head of the major department or the Dean of Graduate College when in his or her judgment the proposed use of the material is in the interests of scholarship. In all other instances, however, permission must be obtained from the author. SIGNED: ________________________________________ APPROVAL BY THESIS COMMITTEE This thesis has been approved on the date shown below: Scott A. Bonar Associate Professor, Wildlife and Fisheries Science Date William J. Matter Professor, Wildlife and Fisheries Science Date Lee H. Simons Senior Fish Biologist, U.S. Fish and Wildlife Service Date 3 ACKNOWLEDGMENTS I would especially like to thank my major advisor Scott Bonar, and Olin Feuerbacher, who were both integral to this study. Thank you to those who assisted with fieldwork, especially Olin Feuerbacher and Lisa Trestik, who both put in many long hours of labor, as well as Parker Ashbaugh, Laiken Jordhal, Justin Mapula, and Rachel More-Hla; without their help this project would not have been possible. Thanks to the U.S. Fish and Wildlife Service (USFWS), U.S. Geological Survey (USGS), University of Arizona (UA), Nevada Department of Wildlife (NDOW), and National Park Service (NPS) for project funding, consultation, and support. Thanks to Paul Barrett and Lee Simons for providing project oversight, and to Michael Bower, Bailey Gaines, Genne Nelson, Kevin Wilson (NPS), William Matter (UA), Jon Sjoberg (NDOW), and Darrick Weissenfluh (USFWS) for project consultation, review, and advice. Thanks to Mark Borgstrom and Robert Steidl (UA) for statistical advice; Dave Bogner (UA), Steve Hiebert (BOR), and David Ward (AZGFD) for technical advice; Mickey Reed (UA) for his GIS/cartography expertise; Martin Pepper (UA), Greg Sherman (Wiseguys Custom Home Theater, LLC), and Katherine Kent (The Solar Store) for advice and guidance on custom technical systems design; and Cindy Cowen and Carol Yde (UA) for their guidance with administrative procedures. 4 DEDICATION I dedicate this to my dad, Robert Wesley Chaudoin, who is the reason I am where I am today. 5 TABLE OF CONTENTS ACKNOWLEDGMENTS ...................................................................................................3 DEDICATION .....................................................................................................................4 LIST OF TABLES ...............................................................................................................7 LIST OF FIGURES .............................................................................................................8 ABSTRACT .......................................................................................................................10 INTRODUCTION .............................................................................................................12 PRESENT STUDY ............................................................................................................17 APPENDIX A: COMPARISON OF FIXED VIDEOGRAPHY AND VISUAL SURVEYS FOR MONITORING SPAWNING BEHAVIOR OF DEVILS HOLE PUPFISH ...........................................................................................................................22 ABSTRACT ...........................................................................................................23 INTRODUCTION .................................................................................................24 METHODS ............................................................................................................29 Study system ...............................................................................................29 Survey methods ..........................................................................................30 Data analysis. ............................................................................................33 Cost-benefit analysis ..................................................................................35 RESULTS ..............................................................................................................37 DISCUSSION ........................................................................................................40 ACKNOWLEDGMENTS .....................................................................................46 REFERENCES ......................................................................................................52 APPENDIX B: FACTORS ASSOCIATED WITH SPAWNING IN DEVILS HOLE PUPFISH............................................................................................................................59 ABSTRACT ...........................................................................................................60 INTRODUCTION .................................................................................................62 METHODS ............................................................................................................66 Study system ...............................................................................................66 Survey methods ..........................................................................................67 Data analysis. ............................................................................................70 Temporal analysis ..........................................................................70 Earthquake disturbance ..................................................................72 Spatial analysis...............................................................................72 RESULTS ..............................................................................................................74 Temporal analysis ..........................................................................74 Earthquake disturbance ..................................................................76 Spatial analysis...............................................................................77 6 DISCUSSION ........................................................................................................78 ACKNOWLEDGMENTS .....................................................................................92 REFERENCES ....................................................................................................112 7 LIST OF TABLES Table A1. Cost per available data-hour and analyzed data-hour for video and visual surveys of spawning in Devils Hole pupfish in Devils Hole, Nevada, February–December 2010 ................................................................................47 Table B1. Zero-inflated Poisson models ranked by Akaike’s Information Criterion .......91 Table B2. Best-fit zero-inflated Poisson regression model parameter estimates..............92 8 LIST OF FIGURES Figure A1. Schematic for custom camera mounts, overhead view of three above-water cameras, and survey frame at Devils Hole, Nevada .......................................48 Figure A2. View from underwater camera on the shallow shelf at Devils Hole, Nevada, 2010 .................................................................................................49 Figure A3. Solar-powered fixed videography system used to monitor spawning of Devils Hole pupfish .......................................................................................50 Figure A4. Mean monthly daytime spawning (number of events per 5-min sample or survey) of Devils Hole pupfish, as detected by underwater camera, abovewater camera, and visual surveys at Devils Hole, Nevada, 2010 ..................51 Figure B1. Locations of water quality meter, light meter, and survey frame on the shallow shelf at Devils Hole, Nevada .................................................93 Figure B2. Frequency distribution of spawning of Devils Hole pupfish on the shallow shelf at Devils Hole, Nevada ............................................................94 Figure B3. Devils Hole pupfish spawning activity by month, 2010 .................................95 Figure B4. Daily maximum, minimum, and mean water temperature (oC) on the shallow shelf at Devils Hole, Nevada, 2010 ..................................................96 Figure B5. Daily maximum, minimum, and mean dissolved oxygen (mg/L) on the shallow shelf at Devils Hole, Nevada, 2010 ..................................................97 Figure B6. Daily maximum and total daily light intensity (lux) at Devils Hole, Nevada, 2010................................................................................................................98 Figure B7. Mean monthly percent cover of algae/cyanobacteria on the shallow shelf at Devils Hole, Nevada, 2010 ............................................................................99 Figure B8. Spawning in Devils Hole pupfish as a function of dissolved oxygen (mg/L) in Devils Hole, Nevada, 2010. .........................................................100 Figure B9. Spawning in Devils Hole pupfish as a function of loge-transformed total daily light intensity (lux) in Devils Hole, Nevada, 2010 .....................101 Figure B10. Spawning in Devils Hole pupfish as a function of arcsine-transformed mean monthly percent cover algae/cyanobacteria in Devils Hole, Nevada, 2010 ...... ......................................................................................................................102 Figure B11. Spawning in Devils Hole pupfish as a function of dissolved oxygen 9 and diel variation in dissolved oxygen in Devils Hole, Nevada, 2010 ........103 Figure B12. Spawning in Devils Hole pupfish as a function of loge-transformed total daily light intensity (lux) and arcsine-transformed mean monthly percent cover algae/cyanobacteria in Devils Hole, Nevada, 2010...............104 Figure B13. Spawning in Devils Hole pupfish as a function of diel dissolved oxygen variation immediately after seiches and during the rest of the year, Devils Hole, Nevada, 2010.....................................................................................105 Figure B14. Mean spawning before and after seiches in Devils Hole, Nevada, 2010.....106 Figure B15. Spatial variation in spawning of Devils Hole pupfish on the shallow shelf at Devils Hole, Nevada, 2010 ..........................................................................107 Figure B16. Spatial variation by month in spawning of Devils Hole pupfish on the shallow shelf at Devils Hole, Nevada, 2010 ...............................................108 Figure B17. Substrate composition on the shallow shelf at Devils Hole, Nevada, 2010 ...... .......................................................................................................................109 Figure B18. Depth across the shallow shelf at Devils Hole, Nevada, 2010 ....................110 Figure B19. Spatial variation in algal/cyanobacterial cover on the shallow shelf at Devils Hole, Nevada, 2010 ..........................................................................111 10 ABSTRACT The highly endangered Devils Hole pupfish Cyprinodon diabolis exists in a single warm spring, Devils Hole, in Death Valley National Park, California-Nevada. Over the past decade, record-low population size and renewed interest in captive propagation of the species have emphasized information deficits in some aspects of Devils Hole pupfish reproductive ecology. In particular, there is a dearth of information on factors that influence spawning behavior. Furthermore, efficient monitoring of fish behavior in isolated sites such as Devils Hole can be a logistical and costly challenge. Thus, I compared three methods to monitor spawning in Devils Hole pupfish, and investigated environmental factors associated with spawning February–December 2010. A solarpowered video surveillance system that incorporated fixed-position above-water and underwater cameras provided continuous video monitoring of a shallow rock shelf in Devils Hole that the Devils Hole pupfish utilizes for spawning. I used visual surveys to record additional information on temporal and spatial patterns in spawning on the shelf. Dissolved oxygen, temperature, and light intensity datalogging meters recorded environmental data continually from a fixed point on the shelf, and I conducted once or twice monthly algal/cyanobacterial surveys to measure percent cover of key species across the shelf. Water level and precipitation data provided by the National Park Service revealed earthquake-induced seiche and storm-induced flash-flood events. An underwater camera detected significantly more overall and peak-season spawning than an above-water camera. The visual surveys yielded data that contained much more variability and sampling error than data from video methods. Underwater video data revealed a bimodal spawning pattern during 2010, with a primary spawning 11 period in spring and a secondary spawning period in fall. Furthermore, underwater fixed videography was the most cost-efficient of the three methods. Zero-inflated Poisson regression showed greatest spawning activity was associated with the following conditions: dissolved oxygen 2.6–4.8 mg/L, total daily light intensity 133,250–400,300 lux, mean percent cover filamentous algae/cyanobacteria 24–60% and especially 24– 27%, and presence of earthquake disturbance; and among significant interaction effects, more spawning occurred at approximately 2.6 mg/L dissolved oxygen when diel dissolved oxygen variation was low (approximately 0.3–1.6 mg/L); at lower–mid-range monthly mean percent cover filamentous algae/cyanobacteria (approximately 24–32%) when total daily light intensity was lower to mid-range (110,000–330,000 lux); and postearthquake when diel dissolved oxygen variation was low (0.6–1.3 mg/L). Increased spawning occurred after earthquakes on 27 February and 21 October 2010, but not after an earthquake on 4 April 2010 at the peak of the primary spawning period. There was significant spatial variation in spawning; most spawning occurred in the northeast area of the shelf. This study provides new information on the benefits of fixed videography to monitor fish behavior in a freshwater spring, and on factors in spawning of Devils Hole pupfish. Self-contained underwater cameras are affordable and widely available, and are a valuable tool for monitoring remote or sensitive aquatic ecosystems. Dissolved oxygen, diel dissolved oxygen variation, total daily light energy, percent cover filamentous algae/cyanobacteria, earthquake disturbance, and location on the shelf were the strongest predictors of spawning behavior in wild Devils Hole pupfish. These are factors that might be utilized in adaptive management and captive propagation of the species. 12 INTRODUCTION Native fishes living in arid and semi-arid regions of North America have experienced unprecedented declines in the past century (Williams et al. 1985; Williams et al. 1989; Minckley and Douglas 1991), with many desert fishes vanishing before much was known about them (Williams et al. 1985). Ever-increasing water demands for urban and agricultural use have greatly diminished desert aquatic ecosystems, including desert springs. Establishment of non-native species and other human-caused habitat alteration and degradation threaten what remain of these ecosystems (Pister 1974; Minckley and Deacon 1991; Shepard 1993; Rinne 2004; Unmack and Minckley 2008). Recent efforts to curb species loss have included habitat conservation and restoration, federal and state regulations on natural resource uses that directly affect threatened and endangered species, and control of pollution and non-native species. Despite these efforts, biologists may be forced to increasingly rely on management tools such as captive breeding programs that can be utilized to create redundant populations, to supplement existing populations, and for research and education (Seal 1986; Rahbek 1993; Philippart 1995; Seddon et al. 2007; Griffiths and Pavajeau 2008). Environmental cues (e.g., water temperature and flow, photoperiod, and substrate type) can induce mating in many wild and captive fishes, making these cues potentially critical for successful captive propagation (e.g., Middaugh 1981; Bromage et al. 1984; Zanuy et al. 1986; Gillet 1991; Lluch-Belda et al. 1991; Hutchings and Myers 1994; Planque and Fredou 1999; Shumway 1999; Heyman et al. 2005; Archdeacon and Bonar 2009; King et al. 2009). Avoiding unnatural selection, through simulation of the natural environment, is an important consideration for captive populations intended as redundant populations 13 or for reintroduction (Williams and Hoffman 2009). There is a relative dearth of information on important aspects of natural history such as spawning behavior for many desert fish species. Limitations in desert fish research associated with harsh desert climate, remoteness of aquatic ecosystems, and enhanced protection status of threatened and endangered fishes likely contribute to this shortage. Implementation of current advanced technologies, such as video cameras and datalogging equipment, has enabled development of methods for aquatic biologists to better achieve minimally intrusive investigation of animal behavior in natural and artificial environments. These methodologies would presumably be equally useful in the study of rare, threatened, and endangered fishes, particularly those living in sensitive environments such as delicate desert springs that are easily impacted by human activities. Devils Hole pupfish Cyprinodon diabolis exemplifies both the difficulties associated with studying threatened and endangered desert species and the importance of simulating natural conditions for captive fishes that normally live in unique or extreme environments. Devils Hole pupfish exists as a single population and the only aquatic vertebrate species within Devils Hole, a geothermal fracture spring (Springer et al. 2008) located within a disjunct portion of Death Valley National Park, California-Nevada. The Devils Hole pupfish endures extreme environmental conditions such as consistently high temperature and low dissolved oxygen, limited food supply, and restricted habitat for feeding and mating. Devils Hole pupfish was first listed as endangered on March 11, 1967, under the Endangered Species Preservation Act of 1966 (U.S. Office of the Federal Register 1967). The population plummeted in the early 1970s after local groundwater pumping for 14 proposed agricultural development lowered water levels, and exposed the primary spawning area (a shallow rock shelf) (Minckley and Deacon 1991; Andersen and Deacon 2001). The ensuing battle to save the species from extinction was elevated to the United States Supreme Court, which ruled water levels within Devils Hole be maintained at or above a designated minimum (Cappaert v. United States 1976). Although this level was lower than historic pre-pumping levels (Andersen and Deacon 2001), the species was spared immediate extinction, and the battle to save this small fish proved instrumental in the formation of the United States Endangered Species Act of 1973 (Pister 1991). The population subsequently rebounded, until the mid-1990s, when it began a precipitous decline that continues today. The population reached an all-time low of 35 individuals Spring 2013 and 65 individuals Fall 2013 (National Park Service, unpublished data; U.S. Fish and Wildlife Service et al. 2013). Studies have implicated multiple factors in the continuing decline of Devils Hole pupfish. These include possible genetic bottlenecks (Martin et al. 2012), shifts in available food species (Minckley and Deacon 1975; Wilson and Blinn 2007), changes in available habitat (Andersen and Deacon 2001; Riggs and Deacon 2002), and changes in abiotic parameters (Wilson and Blinn 2007; Hausner et al. 2012). Despite a plethora of research over the past several decades, the exact mechanism perpetuating this decline remains elusive, and multiple attempts at propagation in the laboratory and artificial refuges have not produced lasting captive populations. In general, there remains a dearth of information on many aspects of the reproductive ecology of this endangered fish, including detailed information on spawning season and factors influencing spawning behavior. 15 Conservation and management of the wild population as well as captive populations may be better informed with increased knowledge of Devils Hole pupfish spawning behavior. However, Devils Hole is located in a remote region of the Mojave Desert, far from research facilities, electrical power, and communications sources. Furthermore, the disturbance of even a single researcher may confound study of Devils Hole pupfish behavior. Here, I show that fixed videography may provide an important means to study this rare fish, with minimal intrusiveness. Also, I show that a suite of environmental factors is associated with Devils Hole pupfish spawning in the wild. My goals were to: 1) compare visual surveys conducted in person from above the water surface, above-water videography, and underwater videography to study temporal trends in spawning behavior in Devils Hole pupfish; 2) assess the environmental factors associated with spawning activity, 3) assess spatial variation in spawning behavior across the single shallow shelf in Devils Hole; and 4) provide monitoring options for other desert spring fishes. This thesis consists of two papers describing the use of visual surveys and standalone above-water and underwater video systems to investigate temporal, spatial, and environmental aspects of spawning Devils Hole pupfish within Devils Hole, Nevada, from January to December 2010. The first paper (Appendix A) analyzes the functionality and cost-effectiveness of three survey methods, and the temporal trends in spawning recorded by each method. The second paper (Appendix B) investigates environmental conditions associated with spawning, and is based on behavioral data recorded with an underwater video camera and environmental data from visual surveys and datalogging meters. In Appendix B, I use underwater video and water level data to 16 describe effects of disturbances on spawning, and use data recorded from visual surveys to describe spatial patterns in spawning. 17 PRESENT STUDY The methods, results, and conclusions of this study are presented in the papers appended to this thesis, and are summarized as follows. My study utilized a single, shallow, submerged rock shelf where most Devils Hole pupfish spawning activity occurs (hereafter referred to as “the shelf”). I used an underwater and above-water videography system comprised of closed circuit television (CCTV) cameras, and visual observations conducted in person from above the water surface to survey Devils Hole pupfish spawning behavior. The camera system was powered with a custom built solar photovoltaic system, and equipped with a digital video recorder that recorded all daytime video from 14 February through 15 December 2010. I conducted visual surveys of Devils Hole pupfish spawning behavior once or twice monthly, consisting of five or six surveys per 24-h period, from 8 January through 5 December 2010. Views among the three methods intersected in an approximate 1.5-m2 area in the northwest section the shelf. This area of intersection was used as the sampling frame for comparing survey methodologies and for all underwater video observations. Video and visual survey samples were standardized to 5-min time frames for all methods to allow comparison of spawning counts recorded by each method. I used Kruskal–Wallis k-sample tests with Monte Carlo estimation of exact Pvalues and Wilcoxon rank-sum multiple comparison procedure for all pairwise comparisons (Bonferroni-adjusted α = 0.0167 [0.05/3 comparisons]) to examine significant differences in overall and within-month spawning counts (number of mating incidents per 5-min sample) among the three methods. I also used a Wilcoxon matchedpairs, signed-ranks test to examine significant differences in overall spawning between 18 the two camera methods while holding all extraneous variables constant. A cost-benefit analysis compared monitoring costs of videography to those of visual surveys. Qualitative aspects of each method were also assessed. A portable datalogging meter recorded dissolved oxygen and temperature data every 30 min from a probe located in the shallower, southeast area of the shelf. A datalogging light meter deployed three to six days per month recorded light intensity data in lux every 15 min from a fixed point approximately 1 m above the water surface. Once or twice monthly, I used a modified Braun-Blanquet/Daubenmire method to monitor percent cover of visually dominant algal/cyanobacterial species across the shelf (Braun– Blanquet 1932; Daubenmire 1959). Water level data provided by the National Park Service recorded information on multiple earthquake-induced seiches and storm-induced flash-floods affecting the shallow spawning shelf. Five-minute video clips were randomly selected by date and time—stratified among months—and analyzed for number of spawning events. Corresponding environmental data were date–time matched with corresponding samples, as detailed in Appendix B. I used zero-inflated Poisson regression to model effects on spawning of the following continuous variables (see Appendix B): dissolved oxygen (mg/L), temperature (oC), diel variation in temperature and dissolved oxygen (daily maximum – minimum values), diel variation in temperature and dissolved oxygen for the previous day, light intensity (lux, log10-transformed), total daily light intensity (lux, loge-transformed), mean monthly percent cover filamentous algae/cyanobacteria (arcsine-transformed), and mean percent cover filamentous algae/cyanobacteria as a daily average (arcsine-transformed); and effects on spawning of the categorical variable presence/absence of earthquake 19 seiches. Various combinations of select interaction effects were also tested during model fit (Table B1). Models were ranked by corrected Akaike’s Information Criterion (AICc), and assessed for significance, fit, and multicollinearity among independent variables. I also performed paired t-tests on data recorded from the underwater video to investigate effects on spawning of each of the three earthquakes that occurred during the study. I performed Kruskal–Wallis k-sample tests and Wilcoxon rank-sum multiple comparisons on data from visual surveys to investigate spatial variation in overall and within-month spawning. All statistical analyses were conducted using SAS Statistical Software (SAS Institute® 9.3, 2011–2013, Cary, North Carolina). Among the three methods, the underwater camera detected significantly more spawning than the above-water camera, and the most within-month spawning activity significantly different from zero. Both the underwater and above-water cameras detected a primary, springtime spawning season that peaked in April. However, the springtime spawning season detected by underwater video was longer than that detected by the above-water camera, and only the underwater camera detected a secondary, smaller fall spawning season. Results from the visual surveys displayed an enormous amount of variability both within a given month and across the year, and no mean monthly spawning observed visually was statistically different from zero, based on univariate analysis. Overall, fixed videography provided more available data at a lower cost than visual surveys. The underwater camera provided the best video clarity and the least monitoring intrusiveness, and was the simplest to use among the three methods. 20 The best-fit zero-inflated Poisson regression model showed significant ( ≤ 0.05) relationships among spawning and dissolved oxygen (P = 0.03), loge-transformed total daily light intensity (P < 0.0001), arcsine-transformed mean monthly percent cover filamentous algae/cyanobacteria (P < 0.0001), and earthquakes (P = 0.0008); and the following interactions: dissolved oxygen*diel dissolved oxygen variation (P = 0.05); loge-transformed total daily light intensity*arcsine-transformed mean monthly percent cover filamentous algae/cyanobacteria (P < 0.0001); and diel dissolved oxygen variation*earthquakes (P = 0.02) (see Table B2 and Figures B8–B13 for parameter estimates and relationship to the dependent variable). Highest spawning counts occurred within 2.6–4.8 mg/L dissolved oxygen; total daily light intensity 133,250–400,300 lux; filamentous algal/cyanobacterial cover of 24–60%, and especially 24–27%; and presence of earthquakes. Among interaction effects, more spawning occurred at approximately 2.6 mg/L when diel dissolved oxygen variation was low (0.3–1.6 mg/L); lower to mid-range monthly mean percent cover filamentous algae/cyanobacteria (24–32%) when total daily light intensity was lower to mid-range (10,000–330,000 lux); and post-earthquake when diel dissolved oxygen variation was low (0.6–1.3 mg/L). Month was a significant predictor of excess zeros (i.e., zeros not related to processes dictating count values) (P = 0.0002). Dissolved oxygen instrumentation failure resulted in 176 missing lines of data in the model dataset, reducing the model-specific sample size to n = 346. Variance inflation factors of <3 indicated no significant multicollinearity among independent variables. The likelihood ratio test showed the model was significant (2 = 264.546, df = 8; P < 0.0001); Pearson’s chi-square goodness-of-fit test showed slight underdispersion, but still good fit to the data (2 = 301.432, df = 335; P = 0.91). 21 There was significantly more spawning ( ≤ 0.06) after (compared to before) two of three earthquakes (27 February 2010 and 21 October 2010). There was no significant effect on spawning of an earthquake that occurred 4 April 2010, at the peak-spawning season. Throughout 2010, the northeast quadrant of the shelf had significantly more spawning (number of events per 5-min survey) than the middle-west, southeast, and southwest quadrants (Kruskal–Wallis k-test: P = 0.0005; and Wilcoxon rank-sum multiple comparison with Bonferroni-adjusted α = 0.003 [0.05/15 comparisons]). No differences in spawning among quadrants by month were observed. Knowledge of environmental conditions that promote reproduction in fishes aids conservation and management efforts. My results provide a basis for further controlled evaluation of environmental conditions associated with spawning in Devils Hole pupfish. Given the continuing decline of the only existing population of Devils Hole pupfish, this information is critical to adaptive management of this highly endangered desert fish. Fixed videography systems, especially an underwater camera, were effective in monitoring Devils Hole pupfish. These video systems are easily adaptable to different environments and study designs, and could prove useful in the study of other sensitive and rare fishes, particularly desert spring species. 22 APPENDIX A: COMPARISON OF FIXED VIDEOGRAPHY AND VISUAL SURVEYS FOR MONITORING SPAWNING BEHAVIOR OF DEVILS HOLE PUPFISH 23 ABSTRACT Efficient monitoring of fish behavior in isolated sites is a costly challenge. The highly endangered Devils Hole pupfish Cyprinodon diabolis lives in a single warm spring of unknown depth within Death Valley National Park, California-Nevada. During the past decade, the Devils Hole pupfish has declined to record-low population size, spurring renewed conservation and recovery efforts. Much is still unknown about the reproductive ecology of this unique desert fish. I investigated spawning in Devils Hole pupfish in Devils Hole, NV, from February through December 2010. I used three methods to collect data on spawning behavior, allowing a comparison of relative efficacy of these methods for monitoring of pupfish behavior. A solar-powered video surveillance system incorporated fixed-position above-water and underwater cameras to provide continuous video monitoring of a shallow rock shelf in Devils Hole that Devils Hole pupfish utilizes for spawning. I conducted visual surveys from above the water surface to record additional data on pupfish behaviors for comparison to fixed videography results. An underwater camera detected significantly more overall and peak-season spawning than an above-water camera, with much less data variability than visual observations. Furthermore, underwater fixed videography proved the most cost-efficient of the three methods. My results provide evidence that low-cost and widely available self-contained underwater cameras are useful in monitoring remote and sensitive aquatic ecosystems. 24 INTRODUCTION Native fishes living in arid and semi-arid regions of North America are among the most imperiled aquatic taxa. Of the over 40 North American freshwater fishes that have gone extinct in the past century, at least 15 have been desert species (Williams et al. 1985; Williams et al. 1989; Minckley and Douglas 1991). Furthermore, over 165 desert fishes are currently federally listed as threatened, endangered, or species of special concern (Williams et al. 1985; Minckley and Douglas 1991). Many desert fishes have vanished before much was known about them (Williams et al. 1985). Ever-increasing water demands for urban and agricultural use have greatly diminished desert aquatic ecosystems. Establishment of exotic species and other human-caused habitat alteration and degradation threaten what remain of these ecosystems (Pister 1974; Minckley and Deacon 1991; Shepard 1993; Rinne 2004; Unmack and Minckley 2008). Though knowledge of desert fishes has increased in the last few decades, data for many species are scarce. Information is often lacking in aspects of basic life history, such as spawning behavior, that can be essential for designing effective conservation and management plans, including captive breeding programs for refuge populations (e.g., Kirschbaum 1975, 1987; Middaugh et al. 1986; Deacon et al. 1995; Philippart 1995; Rakes et al. 1999; Archdeacon and Bonar 2009; Kline and Bonar 2009). Challenges of desert fish research, including harsh climates, remote aquatic systems, and rarity and enhanced protection status of threatened and endangered fishes, likely contribute to this problem. Effective means to study behavior of animals in their natural environment is critical to conservation. New technologies have allowed development of methods to 25 survey terrestrial animals in remote sites with camera traps (Nichols et al. 2011), DNA obtained from hair and scat samples (Foran et al. 1997; Waits and Paetkau 2005; McKelvey et al. 2006), and even drones equipped with imaging equipment (Koh and Wich 2012). Implementation of advanced technologies in aquatic studies presents similar opportunities for aquatic biologists. Whereas traditional techniques such as surface surveys, snorkel surveys, electrofishing, netting, and SCUBA are often expensive, labor intensive, or subject to sampling bias due to gear type (Bonar et al. 2009) and(or) disturbance to fish (Dearden et al. 2010); newer techniques may eliminate some of these problems and allow for increased precision of fisheries data. Advanced technology-driven methods have been used to study behavior of many aquatic animals including mammals, reptiles, invertebrates, and diving birds (Fedak et al. 1996; Marshall 1998; Davis et al. 1999; Ponganis et al. 2000; Jury et al. 2001; Grizzle et al. 2005; Sheehan et al. 2010). Fisheries biologists have increasingly implemented video cameras as a relatively unobtrusive, minimal footprint technique to study fish behavior in both natural and artificial environments. Cameras have been deployed on airplanes, helicopters, and drones; above water positions; and both fixed and mobile underwater platforms. These cameras have been used to study migration, habitat use, spawning behavior, and community interactions (Mueller 1980; Kadri et al. 1996; Norcross and Mueter 1999; Hinch and Rand 2000; Yoklavich et al. 2000; Hetrick et al. 2004; Bailey et al. 2007; Butler and Rowland 2009; Kudo et al. 2012). Underwater videography has proven especially useful for remote or difficult to access aquatic environments, such as deep water (Guennegan and Rannou 1979; Bailey et al. 2007), beneath ice sheets (Mueller et al. 2006), and waters unsafe for personal entry (Cooke and Schreer 2002). 26 Fixed videography further has the advantage of collecting continuous data, thus increasing potential sample size and allowing biologists to obtain a better understanding of fish behavior over time. Fixed videography has helped increase detection while minimizing unnecessary impacts to rare, endangered, and otherwise difficult to detect terrestrial species (Foster and Humphrey 1995; O’Brien et al. 2003; Claridge et al. 2004; Margalida et al. 2006). Fixed videography would presumably be equally useful in the study of rare, threatened, and endangered fishes, particularly those living in sensitive environments such as delicate desert spring ecosystems that are easily impacted by human activities. Monitoring Devils Hole pupfish Cyprinodon diabolis exemplifies the problems associated with studying threatened and endangered desert species. Among the rarest fishes in world, Devils Hole pupfish is endemic to a single, geothermal spring within a disjunct portion of Death Valley National Park, California-Nevada. Said to have the smallest distribution of any known vertebrate species, this tiny cyprinodont persists at the uppermost limits of its physiological tolerance (James 1969; Brown and Feldmeth 1971), as it endures high temperatures, typically 32.8–34.0 oC (Brown and Feldmeth 1971) and sometimes greater than 36 oC (Threloff and Manning 2003); near-hypoxic average dissolved oxygen levels of 2.5–3.0 mg/L (Baugh and Deacon 1983); and limited direct sunlight (Blinn et al. 2000; Wilson and Blinn 2007). Devils Hole pupfish subsists mainly on small invertebrates, diatoms, and algae produced on a 3.5 × 5 m2 rock shelf submerged under 0.3 m of water in the upper reaches of the spring (James 1969; Minckley and Deacon 1975; Wilson and Blinn 2007). This shelf also serves the Devils Hole pupfish’s primary spawning habitat. 27 Devils Hole pupfish was first listed as endangered on March 11, 1967, under the Endangered Species Preservation Act of 1966 (U.S. Office of the Federal Register 1967). The population plummeted in the early 1970s after groundwater pumping for proposed agricultural development lowered the water level and exposed the shelf, depriving the Devils Hole pupfish of its primary spawning and feeding habitat, and threatening its continued survival (Minckley and Deacon 1991; Andersen and Deacon 2001). The ensuing battle to save the species from extinction was elevated all the way to the U.S. Supreme Court, which ruled water levels within Devils Hole be maintained at or above a designated minimum (Cappaert v. United States 1976). Although this level was lower than historic pre-pumping levels (Andersen and Deacon 2001), Devils Hole pupfish was spared extinction, and the struggle to save this one species of tiny desert fish proved instrumental in the formation of the U.S. Endangered Species Act of 1973 (Pister 1991). After 1975, Devils Hole pupfish rebounded to 450–550 individuals during the fall high, and 150–250 individuals during the spring low. These numbers remained relatively constant until the mid-1990s, when the population began declining and reached a then record low of 38 fish in fall 2006. The population increased to the low to mid-100s 2008–2012, only to decline again to a record low of 35 individuals Spring 2013 and 65 individuals Fall 2013 (National Park Service, unpublished data; U.S. Fish and Wildlife Service et al. 2013). Studies have implicated multiple factors in the continuing decline of Devils Hole pupfish. These include possible genetic bottlenecks (Martin et al. 2012), shifts in available food species (Minckley and Deacon 1975; Wilson and Blinn 2007), changes in available habitat (Andersen and Deacon 2001; Riggs and Deacon 2002), and changes in 28 abiotic conditions (Wilson and Blinn 2007; Hausner et al. 2012). Furthermore, multiple attempts at laboratory and refuge propagation have not produced lasting captive populations, for largely unknown reasons. This underscores the fact there is still much unknown about the reproductive ecology of this endangered fish. Basic reproductive information is lacking, in particular, on temporal trends in spawning behavior in the wild. Studies have suggested seasonal trends in mating activity, based on larval abundance and distribution within Devils Hole (James 1969; Gustafson and Deacon 1997; Threloff 2004, cited in Riggs and Deacon 2002; Lyons 2005), egg production and hatch rates of captive individuals (Deacon et al. 1995), gonad characteristics (Minckley and Deacon 1973), and casual observations of spawning within Devils Hole (James 1969; Gustafson and Deacon 1997); however, mating activity has not been intensively studied in such a manner as to provide detailed information on spawning frequency throughout the year. Devils Hole is located in a remote region of the Mojave Desert, far from research facilities, electricity, and communications services. Furthermore, the presence of even a single researcher may confound study of fish behavior. Information on Devils Hole pupfish spawning behavior is critical to adaptive management and conservation of the species. Fixed videography may provide an important means to study this rare fish with minimal intrusiveness. My goals were to 1) compare onsite visual surface surveys, surface videography, and underwater videography for accuracy, precision, and costeffectiveness in investigation of temporal trends in spawning behavior in Devils Hole pupfish; and 2) provide monitoring options for other isolated fishes. 29 METHODS Study system Devils Hole is a geothermal fracture spring (Springer et al. 2008) of unknown maximum depth (>152 m), located within a disjunct portion of Death Valley National Park within Ash Meadows National Wildlife Refuge in the Mojave Desert of Nevada. Devils Hole provides the only known opening to a submerged limestone cavern system, and a direct connection to an extensive carbonate aquifer within the Amargosa Valley groundwater basin. The alkaline water within Devils Hole has an average pH of 7.4 (Riggs et al. 1994), conductivity of 655–723 µS/cm (Gustafson and Deacon 1997), negligible flow, low dissolved oxygen, and geothermally regulated temperatures. Conditions in the deeper reaches of the cavern are fairly constant; at depths of 5.0–37.5 m, temperature is 33.5–33.9 ºC (Plummer et al. 2000), and dissolved oxygen is 2.5–3.0 mg/L to a depth of about 22 m (Baugh and Deacon 1983). However, fluctuations in temperature and dissolved oxygen may occur over the shallow spawning shelf (Baugh and Deacon 1983; Gustafson and Deacon 1997; Threloff and Manning 2003). Direct sunlight is limited much of the year, with the exception of summer when sunlight is intense for a few hours each day (Blinn et al. 2000; Wilson and Blinn 2007). Algae and cyanobacteria within Devils Hole are largely comprised of filamentous cyanobacteria Oscillatoria princeps and Lyngbya limnetica, filamentous green algae Spirogyra spp., and several diatom species (Shepard et al. 2000). Invertebrates include a gastropod Tryonia variegata, amphipod Hyalella sp., flatworm Dugesia dorotocephala, elmid beetle Stenelmis calida, predaceous dytiscid beetle Neoclypeodytes cinctellus, tanypod midge Zavrelimyia sp., and an unidentified species of cyclopoid copepod, ostracod, 30 oligochaete, and water mite, and chironomid, dipteran, hemipteran, and coleopteran insects (Minckley and Deacon 1975; Herbst and Blinn 2003; Wilson and Blinn 2007). A security system equipped with motion-detectors, surveillance cameras, and a fence has been implemented by the U.S. National Park Service to restrict public access to Devils Hole and the immediate surrounding area. Survey methods I used fixed underwater videography, above-water videography, and visual observations taken from above the water surface to survey Devils Hole pupfish spawning behavior from 14 February through 15 December 2010. An underwater closed circuit television (CCTV) black and white camera (Lorex, Indianapolis, Indiana; Model CVC6990) was attached to a custom stainless steel adjustable camera mount and affixed to a preexisting underwater metal structure that supported past National Park Service scientific equipment in Devils Hole. An above-water CCTV color video surveillance camera (ARM Electronics, Roseville, California; Model C600) equipped with a 2.8–12 mm varifocal auto iris lens and weather resistant housing was attached to the extension arm of a custom camera mount (Moosecrafts.com, Tucson, Arizona) constructed of 5-cm diameter square tubular stainless steel (Figure A1). The camera mount was secured to a preexisting post structure extending perpendicular from the east wall of Devils Hole. The extension arm was hinged with a multiple-point locking system for vertical adjustment, also allowing temporary repositioning of the camera to accommodate other research and monitoring activities in Devils Hole. A locking slide-mount on the camera arm enabled horizontal positioning of the camera. A Manfrotto (Manfrotto Supports by Lino 31 Manfrotto + Co., S.p.A., Cassola, Italy) 486 photographic ball head provided rotational adjustment of camera angle and orientation. The above-water camera was positioned approximately 1.2 m above the water to minimize refractive distortion and accommodate accessibility for other research in Devils Hole. The camera lens focal length was adjusted to a 1.5-m2 field of view of the spawning shelf. Views from the underwater and above-water cameras overlapped completely in order to compare monitoring efficacy between the two camera types (Figure A1, A2). All video monitoring was limited to daytime to avoid potential adverse effects of infrared illumination on Devils Hole pupfish and other organisms. Of particular concern was illumination of the spawning shelf to the detriment of larval and juvenile Devils Hole pupfish, known to be more active at night when cannibalizing adults are less active (K. Wilson, National Park Service, personal communication). No electricity, cellular, or Internet services existed at Devils Hole, so a solar power system was designed to power video cameras and associated components (Figure A3, Table A1). It consisted of four 130-W photovoltaic panels (Kyocera Solar, Scottsdale, Arizona) connected to a charge controller (Morningstar Corporation, Newtown, Pennsylvania; Model TriStar TS-60), which provided DC power to a 125-W 12-V DC sine wave inverter (Exceltech, Fort Worth, Texas), and controlled the charging cycles of four deep-cycle batteries (U.S. Battery Manufacturing, Corona, California; Model L-16) during the day and drew power from these batteries at night. Cameras were powered directly with 12-V DC from the load controller. An in-line fuse, installed in the junction box, prevented power overloads from reaching the cameras or Devils Hole in the case of electrical malfunction or lightning strike. The inverter provided 115-V AC to 32 power all other components. Data were recorded on a digital video recorder (DVR: Everfocus Electronics, Duarte, California; Model EDR1640). A live-feed television monitor was used to check camera placement, focus, and system function. The DVR was fully programmable, and set to record continuous daytime footage from the above-water and underwater cameras. Video data from both cameras were stored in the DVR on one-terabyte (1TB) hard-drives (Seagate Technology, Cupertino, California; Model Barracuda 7200.12). Hot-swappable technology, in which hard-drives are easily removed and replaced, enabled monthly transport of video data to the University of Arizona, Tucson campus. Located within the fenced Devils Hole enclosure, the entire power/DVR system was built on a wooden frame with all components weatherproofed and secured beneath the solar panels, which faced south at a 32o angle to the ground. Visual surveys of Devils Hole pupfish spawning were conducted once or twice monthly from 14 February to 5 December 2010. Fish were viewed from a 0.5 × 3.0 m2 temporary metal platform deployed on the shallow shelf. Five or six surveys were conducted over 24 h during each trip. Surveys occurred 1 h before dawn, sunrise, midmorning, mid-afternoon (approximately 1400–1600 h, coinciding with maximum sun exposure on Devils Hole), sunset, and night (3–4 h after dusk). The spawning shelf was divided into six 1.5-m2 quadrants, each surveyed in random order for 5 min. Spawning activity was assessed within only the northwest quadrant, which encompassed the survey frame for all three methods (Figure A1). I used night-vision goggles (Night Optics U.S.A., Huntington Beach, California; Model D-2MV PRO) to conduct low-light (predawn and sunset) and night surveys. To eliminate inter-observer variability, the observer 33 was the same individual for all surveys. Fish were given at least 2.5 h to acclimate and return to normal activity after deployment of the viewing platform. To further minimize disturbance to fish, the observer wore soft-soled neoprene shoes when walking on the survey platform; remained still on the platform for 5 min before surveys to allow fish to reorient; located the person recording data several meters away from the viewing platform; and minimized unnecessary sound and movement of both surveyor and data recorder. Data analysis Spawning was defined as a single event in which two individual fish came together in a “sidling” behavior of swimming side-by-side, generally followed by one or more of the following behaviors: “s-shaping”, “wrapping”, and “jerking” motions between the mating pair (Barlow 1961; Liu 1969; Baugh 1985). Preliminary onsite visual surface surveys indicated sidling behavior generally results in spawning unless interrupted by other males. Therefore, sidling behavior within the sample frame was considered a spawning event. A mating pair that clearly exited and re-entered the sample frame while only sidling was counted as a single event. A mating pair that completed mating, separated, then proceeded to come together to mate again was counted as a separate spawning event. I used a hard-drive reader (Everfocus; Model EPR 100C/110) and associated proprietary software (Everfocus) running on an Apple 2GHz MacBook (Apple, Cupertino, California) to analyze video data. As in the visual surveys, only one person analyzed video data to avoid inter-observer variability. 34 Residual analysis showed non-normality and heteroscedasticity, so I ran nonparametric analyses to compare survey methods. I took stratified random samples, in which 5-min video clips were randomly chosen by date and time, approximately evenly stratified among months. Five-min video clips (samples) were chosen independently from underwater and above-water video data and analyzed for number of mating incidents per sample. Spawning (number of events/5-min clip) among video samples was compared to spawning recorded during 5-min surveys (samples) from the visual surveys. I used Kruskal–Wallis k-sample tests with Monte Carlo estimation of exact P-values and Wilcoxon rank-sum multiple comparison procedure for all pairwise comparisons (Bonferroni-adjusted α = 0.0167 [0.05/3 comparisons]) to investigate differences in both overall (underwater camera n = 323; above-water camera n = 236; visual surveys n = 46) and within month spawning counts among the three methods. I also compared overall spawning between just the two camera methods while holding all extraneous variables constant. I compared paired-samples of above and underwater 5-min clips recorded at the same time and location. I used a Wilcoxon matched-pairs, signed-ranks test to compare the above-water camera video samples to an additional 236 date–time matched underwater camera video samples. The order in which samples were viewed was randomized to avoid viewer bias. As the camera system was powered off during visual surveys to accommodate system maintenance and research activities in Devils Hole, matched data were not available for the visual surveys. For biological inference of nonparametric tests, means are reported (see Results and Figures) rather than rank-sum scores. Qualitative aspects of each method were also recorded including fish response to person or equipment, video clarity and fish detectability, 35 relative intrusiveness or “footprint”, and overall ease and functionality. I used SAS Statistical Software, (SAS Institute® 9.3, 2011–2013, Cary, North Carolina) to conduct all statistical analyses. Cost-benefit analysis I compared the cost (US$) of fixed videography vs. visual surveys to monitor the entire spawning shelf (roughly 9 m2 viewable area) over 1 yr. For each method, I itemized equipment, transportation, lodging, and salary costs to calculate total cost per available data-hour and cost per hour of data sampled. Transportation costs included round-trip travel between the University of Arizona, Tucson and Ash Meadows National Wildlife Refuge, Nevada, and were standardized to $0.445 per mile, per University of Arizona Financial Service Office 2013 reimbursement rates for privately owned vehicles. Fixed videography included one night of lodging once monthly for system maintenance and data retrieval; visual surveys included one night of lodging twice monthly. An additional trip to deploy the video system included two nights lodging plus transportation. Lodging was estimated at $60 per night local standard rate; actual lodging rates varied. Estimated costs for salary factored in time for travel, surveying, equipment deployment, and system maintenance for two research technicians, and video data viewing for one technician. Hourly pay was estimated at $10/h, per U.S. Office of Personnel Management General Schedule 1 (GS-1) pay rates. Salary hours included only those directly required for daytime fieldwork and data acquisition; and excluded night surveys, other environmental monitoring, and post-video viewing analyses or interpretation. Analysis standardizations included 1) a four-camera design for a fixed 36 videography system that collected continuous daytime video data (average 12-h day); 2) a sample size of 300 5-min video clips analyzed per camera (n = 1,200); 3) a total sample size of 432 5-min observations (three surveys per day, of each of six 1.5-m2 quadrants, twice-monthly) collected and analyzed for the visual survey method; and 4) a 1-yr study duration. Miscellaneous costs such as data sheets, writing implements, and personal gear were excluded from analyses. Costs are average values based on the standardizations of methods used in this study. 37 RESULTS With the exception of two spawning incidents, visual surveys detected spawning activity during daylight hours only. Predawn, dusk, and night samples were thus excluded from the analysis, keeping the visual survey time frame consistent with camera survey time frames. Overall differences in spawning among the three methods were observed (2 = 14.392, df = 2; P = 0.001). The underwater camera detected significantly more overall spawning activity throughout the year than the above-water camera (P = 0.005); neither camera detected significantly more overall spawning than the visual surveys. Within month differences in spawning were observed for March (2 = 7.455, df = 2; P = 0.02), April (2 = 7.797, df = 2; P = 0.02), and December (2 = 9.030, df = 2; P = 0.055). The underwater camera detected significantly more within month spawning activity in April (P = 0.03) and March (P = 0.04) than the above-water camera. Visual surveys detected more spawning than the underwater camera (P = 0.02) and the abovewater camera (P = 0.007) in December (Figure A4). Holding all extraneous variables constant by comparing date–time matched samples, the underwater camera detected significantly more overall spawning activity throughout the year than the above-water camera (S = 143.5, df = 235; P < 0.0001). All three methods detected spawning in April; the two camera methods display April as the main spawning peak. Both the underwater camera and visual surveys detected additional spawning activity October–November. Further, the visual surveys captured spawning activity in July and December. However, results from visual surveys displayed an enormous amount of variability across the year, as well as within month sampling error, and no mean monthly spawning counts observed using this method could 38 be considered statistically different from zero. The video camera system remained fully operational for most of the study, with two exceptions. There was a gap in video data July 14–31, when the DVR exceeded maximum operational temperature and automatically powered off. Summertime air temperatures at Devils Hole often exceeded 43–46 oC, and enclosed power equipment subsequently reached temperatures above ambient. Overheating was resolved by replacing the initial plastic DVR housing (Pelican Products, Torrance, California) with a larger, custom built aluminum housing fitted with two solar-powered ventilation fans. One fan was mounted into the base of the solar system stand directly beneath the DVR and drew in cooler air from beneath. The other fan was placed at the back of the aluminum housing to remove hot air. Elevating the DVR off the housing floor also increased air circulation and minimized DVR contact with surfaces. These changes to the DVR setup successfully increased air circulation and prevented further overheating. The camera system also experienced failure December 15-31, when number of cloudy days exceeded solar system power reserves. Though they presented a larger initial cost, the camera systems were more costeffective than the visual surveys (Table A1). Videography methods standardized to four cameras that captured simultaneous views of the entire spawning shelf over the duration of 1 yr provided a total of 17,520 available data-hours. Average costs were $16,656 equipment, lodging, and transportation and $6,200 labor, yielding an average cost of $1.31 per available data-hour; and $220 per analyzed data-hour (n = 1,200 5-min video clips). The onsite visual survey method standardized to a one-year, whole-shelf study design provided 36 available data-hours. Average costs were $12,419 lodging and 39 transportation and $9,360 labor, yielding a total cost of $605 per both available and analyzed data-hour (n = 432 5-min video clips). 40 DISCUSSION Videography often has advantages over other more traditional methods of monitoring fishes. Above-water video monitoring was more accurate than on-board human observers to determine catch composition in the Alaskan Pacific halibut Hippoglossus stenolepsis long-line fishery (Ames et al. 2007); baited underwater video improved estimates over those of underwater visual censuses in assessing relative abundance of snapper P. auratus in and around a marine reserve (Willis et al. 2000); and fixed underwater videography was more effective than angling, netting, and above-water visual surveys in determining fish community assemblage in a discharge canal near Lake Erie (Cooke and Schreer 2002). Fixed videography, particularly the underwater camera, similarly proved most effective in monitoring Devils Hole pupfish spawning behavior. The underwater camera detected more overall spawning events than the abovewater camera, and the highest number of monthly spawning events among the three methods. Furthermore, it recorded the most footage available for analysis of all methods, allowing increased sample size and thus increased precision of results. Spawning detection and sample size for the above-water camera was limited by the poor quality of available video, likely introducing both survey bias and sampling error, respectively. The sample size of the visual surveys was limited by time, cost, and general logistical difficulties in traveling to and conducting research at the remote and highly protected Devils Hole. Potential survey bias was evidenced by drastic change in fish behavior and abundance on the shelf upon initial deployment of the viewing platform, and by subsequent alterations in fish activities in the presence of the surveyor. Although increased sampling effort might increase precision of visual surveys, it would still not 41 account for effects of human disturbance on fish behavior, and might even introduce further bias into the results. My study may have included observer bias; however, because the same person viewed spawning behavior for both visual surveys and video data, any bias was likely constant. Spawning occurred primarily in spring, peaking in April, which was consistent with previous casual observations (James 1969; Gustafson and Deacon 1997). Further, both the underwater camera and visual surveys detected previously undocumented fall (October–November) spawning. Visual survey results of sporadic spawning throughout much of the year corroborate previous observations of multi-seasonal mating activity (Miller 1948, 1961; James 1969; La Rivers 1994) and year-round presence of larvae on the shelf (James 1969; Lyons 2005). However, the amount of variability in the visual survey results and some lack of consistency between these results and those of the camera methods cast doubt on the ability of visual surveys to accurately assess seasonal trends in spawning. Data from the underwater camera suggest some of the spawning activity in summer and winter detected during visual surveys may be overrepresented, and an artifact of small sample size. Only two to six 5-min visual surveys were conducted per month, compared with continuous recording and subsequent large sample sizes available from the cameras. Therefore, a single survey with increased spawning would have dramatic effects on mean spawning (average number of events/5-min) documented by visual surveys compared to the spawning documented by the cameras. Disturbance may be responsible for the short spikes in spawning activity detected during visual surveys. Past studies have suggested effects of disturbance on Devils Hole pupfish. For example, Lyons (2005) suggested potential impacts on available habitat for 42 larval Devils Hole pupfish, which utilize interstitial spaces, following earthquake and flash flood events that redistribute substrate on the shelf. Recent quantification of the effects of disturbance on spawning activity includes statistically significant increases in spawning for multiple days after seiches in Devils Hole (Chaudoin et al., in review). Based on this evidence of the influence of natural disturbance on Devils Hole pupfish, the spike in spawning during February was likely attributable to surveys commencing the day immediately following an overnight 8.8 magnitude earthquake centered off the coast of central Chile (26 February 2010, 2235 hours PST / 27 February 2010, 0635 hours UTC) which created a seiche that removed the majority of algae/cyanobacteria from the shelf. Though increases in spawning observed during July and December visual surveys are not readily attributable to a known cause, they may be results of less drastic disturbances. Both the above-water (13.2 × 10.4 × 33.0 cm3 including housing) and underwater (10.2 × 2.8 cm2) cameras were minimally intrusive and did not seem to affect fish behavior. The underwater camera was especially convenient because it was small and placement did not interfere with access to the shelf for other research. The above-water camera, however, had to be moved each time physical access to the shelf was required, and then returned to its position. The underwater camera was manually cleared of encrusting and filamentous cyanobacteria and algal growth on and around the lens once or twice monthly. The camera was placed far enough from the substrate and surrounding structures that cyanobacterial/algal encrustation was generally minimal, and obstruction was never severe enough to fully inhibit views of spawning activity. The above-water camera, however, presented several impediments to monitoring Devils Hole pupfish behavior. Surface glare and floating mats of precipitated calcium carbonate were often 43 present on the water surface and frequently obstructed views of fish. These calcium mats additionally caused overexposure of the video footage, further decreasing above-water video quality. With the above-water camera was placed approximately 1.2 m above the water surface, pupfish, only 2.5 cm total length on average, were minute in the abovewater camera view, and discerning specific behaviors was generally difficult. The access platform used February–August for visual surveys disturbed the water and shelf substrate. Fish would immediately scatter and relocate to a second, deeper shelf for several minutes to an hour after deployment of the access platform. The access platform used September–December did not touch the water, and disturbed fish less, though altered behavior was still noted. Regardless, the 2.5-h post-platform-deployment acclimation period was sufficient for fish to resume normal activity. The number of cameras deployed, particularly underwater cameras, was limited by strict permitting regulations imposed on research conducted in the highly protected Devils Hole ecosystem. The survey frame, selected as an area of moderate to high fish activity based on preliminary surveys, comprised approximately one-sixth of the spawning shelf. Ideally, more than one underwater camera would have been incorporated into the study design, allowing a larger overall view of the shelf and more thorough comparison of methods to detect spawning. Fixed videography was more cost-effective than visual surveys for data capture. Although initial equipment investment was high, fixed videography yielded more datahours per dollar. Fixed videography also required fewer research technician hours, thus reduced salary over that of visual surveys. Also noteworthy is the fact that increasing sampling effort will lower the cost per analyzed data-hour for fixed videography but not 44 visual surveys. Adjustable video playback is another useful and potentially cost-effective feature of fixed videography. Though not incorporated into salary costs in the costbenefit analysis, fast-forwarding features can further increase time-efficiency in data analysis. For example, I was generally able to watch video at 1.5–2.0 times normal viewing rate. Furthermore, data accuracy may be enhanced through video replay, and archived data can be re-analyzed for alternate applications. Videography also provides exceptional educational opportunities. Video footage from this project was regularly displayed at the USFWS Ash Meadows National Wildlife Refuge Visitor Center. Video from the remotely deployed cameras provided visitors with close-up views of the Devils Hole pupfish that would have been impossible otherwise because visitors cannot approach the water surface of Devils Hole. This technology provides opportunities for public viewing of organisms in other remote aquatic sites, such as other isolated springs, deep ocean, or high mountain water bodies. Such viewing enhances public knowledge and associated conservation benefits. Recent advancements in fixed videography are making this method even more attractive for fish researchers and educators. Due to near-constant pupfish activity in the relatively small sampling area, motion detection software was not an option when analyzing video data. However, for environments with lower fish densities, such software could further streamline video analysis. Modern DVRs are increasingly adaptable to the needs of the end-user. Fully programmable DVRs allow researchers to set sampling schedules and video quality and resolution, thus providing options for power usage and sampling schemes. Most DVRs can now accommodate 16–32 cameras, increasing sampling area at minimal additional cost. “Hot-swappable” data drives have 45 enabled rapid transfer of huge amounts of data, replacing the need for slow and inefficient transfer to CDs, DVDs, and USB flash drives. DVR compression technologies are also rapidly improving. The MPEG-4 compression that was standard at the time of the field portion of my study has been replaced by H.264 compression, yielding much sharper, clearer images. Camera technologies are constantly improving, as well; camera resolutions continue to increase as costs drop, providing much better image quality at affordable prices. Cameras may be purchased with various lengths of DC and coaxial cable to suit most research situations, and one can easily splice cables to achieve custom lengths. Overall, the fixed videography camera system, particularly the underwater camera, outperformed the visual surveys in cost-effectiveness, data quantity, and data quality. Furthermore, fixed videography minimized monitoring intrusiveness, and after initial setup, was simpler to conduct than visual surveys. Fixed videography systems are easily adaptable to different environments and study designs, and could prove useful in the study of other sensitive and rare species, particularly desert spring fishes. The underwater camera successfully provided data to further knowledge of spawning behavior in Devils Hole pupfish. Amidst ongoing population decline, any such information is critical. 46 ACKNOWLEDGMENTS The U.S. Fish and Wildlife Service (USFWS), U.S. Geological Survey (USGS), University of Arizona (UA), Nevada Department of Wildlife (NDOW), and National Park Service (NPS) provided funding and support for this study. Paul Barrett and Lee Simons (USFWS) provided project oversight. Olin G. Feuerbacher, Scott A. Bonar, and Paul J. Barrett will be co-authors on this paper when submitted for publication. We thank Michael Bower, Bailey Gaines, Genne Nelson, Kevin Wilson (NPS), William Matter (UA), Jon Sjoberg (NDOW), and Darrick Weissenfluh (USFWS) for project consultation, review, and advice. We thank those who assisted with fieldwork, especially Parker Ashbaugh, Laiken Jordhal, Justin Mapula, Rachel More-Hla, and Lisa Trestik (UA). Thanks to Cindy Cowen and Carol Yde (UA) for their guidance with administrative procedures; Robert Steidl (UA) for statistical advice; Dave Bogner (UA), Steve Hiebert (BOR), and David Ward (AZGFD) for technical advice; and Martin Pepper (UA) and Greg Sherman (Wiseguys Custom Home Theater, LLC), and Katherine Kent (The Solar Store) for advice and guidance on custom technical systems design. All research was conducted in accordance with University of Arizona Institutional Animal Care and Use Committee protocol #09-115. Any use of trade names is for descriptive purposes only and does not imply endorsement by the U.S. Government. 47 Table A1. Estimated costs (US$) for an underwater and above-water four-camera fixed videography system and visual surveys for a 1-yr fish behavior study at Devils Hole, Nevada. Visual survey data-hours reflect those gathered within the time and logistical constraints of this study. Costs are average values based on standardization of methods used in this study. Four-camera fixed videography system components Lodging Transportation Solar panels 130-W 12-V DC Lumber for solar array Cables 38-m DC and 115-m RG-59 copper braid coaxial cable DVR NTSC 16-channel MPEG-4 Charge controller 12, 24, 48-V DC AC/DC power inverter 125-W 12-V DC sine wave Above-water camera US$ 840 5,947 2,900 150 150 1,100 200 225 *884 Visual surveys Lodging Transportation Twice-monthly surveys US$ 1,440 10,979 9,360 (468 h per person) NTSC 1/3” Color CCD 2.8-12 mm F1.4 lens, qty. 4 Above-water camera weather resistant housing, qty. 4 Above-water camera arms, parts and labor, qty. 4 Underwater camera *52 *1,240 400 NTSC 1/3” black/white CCD 3.6 mm F2.0 wide angle lens Underwater camera arm parts Batteries 6-V DC 353 amp-hour, qty. 4 Miscellaneous hardware Computer 2.0-GHz Intel Core 2 Duo laptop Hard-drive reader Hard-drives 1-TB 3.5” Serial ATA, qty. 12 Television monitor Monthly video collection and system maintenance 80 1,376 200 1,100 150 960 30 4,320 (216 h per person) Construction and deployment (44 h per person) Video viewing (100 h) Total collected data-hours Total analyzed data-hours Total equipment, lodging, and transportation cost Total labor cost Total cost per collected data-hour Total cost per analyzed data-hour *Cost for four-camera above-water videography system. 880 1,000 17,520 h 100 h 36 h 36 h $15,808/*$17,504 $6,200 $1.26/*$1.35 $220 $12,419 $9,360 $605 $605 48 Figure A1. (a) Schematic for above-water custom camera mounts and (b) overhead view of Devils Hole with three above-water cameras visible, the top-most one was the camera used in this study. The arrow marks the underwater camera location. Each of the three above-water stainless steel camera mounts attached to pre-existing metal post structures extending perpendicular from the east wall of Devils Hole. Cameras were vertically adjustable via a hinge in the camera arm, horizontally adjustable via a camera mount that could slide along the camera arm, and rotationally adjustable via a ball head to which the camera was affixed. Survey area on the shelf is marked where the underwater camera view, the top-most above-water camera view, and the visual survey quadrant used for this study all overlap. Approximate survey area was encompassed within coordinates (1.6 m West [W], 5.6 m North [N]), (2.7 m W, 5.6 m N), (1.41 m W, 4.1 m N), and (2.32 m W, 4.1 m N), based on National Park Service coordinate system. 49 Figure A2. View from underwater camera on the shallow shelf at Devils Hole, Nevada, 2010. Devils Hole pupfish are visible in both foreground and background. 50 Figure A3. Solar-powered fixed videography system used to monitor Devils Hole pupfish spawning activity. Solar power system was comprised of (a,c) four 130-W photovoltaic panels mounted on a custom frame that housed (b,c) four deep-cycle batteries, a charge controller, an AC/DC power inverter, a digital video recorder for data storage, and a television monitor. (c) 12-V DC and RG-59 copper braid coaxial cable connected each underwater and above-water camera to the power system and digital video recorder located approximately 15 m above at ground level. Solid lines represent AC/DC power cable and dashed lines represent coaxial cable. Actual system accommodated two additional cameras, not included in this study. (a) (b) (c) 51 Figure A4. Mean monthly number of daytime spawning events per 5-min survey in Devils Hole pupfish, as detected by underwater camera, above-water camera, and visual surveys, Devils Hole, Nevada, 2010. Per month, n = 18–36 for underwater camera surveys, n = 20–24 for above-water camera surveys, and n = 2–6 for visual surveys. Means with letters in common were not significantly different at the Bonferroni-adjusted α = 0.0167 (0.05/3 comparisons) level. Error bars are ± 1 SE. 52 REFERENCES Ames, R. T., B. M. Leaman, and K. L. Ames. 2007. Evaluation of video technology for monitoring of multispecies longline catches. North American Journal of Fisheries Management 27:955–964. Andersen, M. E., and J. E. Deacon. 2001. Population size of Devils Hole pupfish (Cyprinodon diabolis) correlates with water level. 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Millar, and R. C. Babcock. 2000. Detection of spatial variability in relative density of fishes: comparison of visual census, angling, and baited underwater video. Marine Ecology Progress Series 198:249–260. Wilson, K. P., and D. W. Blinn. 2007. Food web structure, energetics, and importance of allochthonous carbon in a desert cavernous limnocrene: Devils Hole, Nevada. Western North American Naturalist 67:185–198. Yoklavich, M., H. G. Greene, G. M. Cailliet, D. E. Sullivan, R. N. Lea, and M. S. Love. 2000. Habitat associations of deep-water rockfishes in a submarine canyon: an example of a natural refuge. Fishery Bulletin 98:625–641. 59 APPENDIX B: FACTORS ASSOCIATED WITH SPAWNING IN DEVILS HOLE PUPFISH 60 ABSTRACT Population decline to record lows and renewed interest in captive propagation of the endangered Devils Hole pupfish Cyprinodon diabolis has highlighted information deficits in some aspects of the species’ reproductive ecology. I conducted a monitoring study from February to December 2010 to investigate environmental factors associated with spawning activity in Devils Hole pupfish in Devils Hole, Death Valley National Park, Nevada. A fixed underwater camera provided continuous monitoring of a portion of a shallow, submerged rock shelf used for spawning. Dissolved oxygen, temperature, and light intensity datalogging meters continuously recorded environmental data from a fixed point on the shelf, and I conducted once or twice monthly algal/cyanobacterial surveys to measure percent cover of key species across the shelf. Water level and precipitation data provided by the National Park Service recorded earthquake and storminduced flash-flood disturbances. Visual surveys conducted at the water surface from January to December 2010 provided additional information on spatial preferences in spawning. Zero-inflated Poisson regression showed greatest spawning activity was associated with the following conditions: dissolved oxygen 2.6–4.8 mg/L, total daily light intensity 133,250–400,300 lux, mean percent cover filamentous algae/cyanobacteria 24– 60% and especially 24–27%, and presence of earthquake disturbance in the form of seiches. Among significant interaction effects, more spawning occurred at approximately 2.6 mg/L dissolved oxygen when diel dissolved oxygen variation was low (approximately 0.3–1.6 mg/L); at lower to mid-range monthly mean percent cover filamentous algae/cyanobacteria (approximately 24–32%) when total daily light intensity was lower to mid-range (110,000–330,000 lux); and post-earthquake when diel dissolved oxygen 61 variation was low (0.6–1.3 mg/L). Increases in spawning activity occurred after earthquakes on 27 February and 21 October 2010; however, an earthquake during the peak spawning period (4 April 2010) was not associated with increased spawning activity. There was significant spatial variation in spawning, with most spawning activity occurring over the northeast area of the shelf. My study provides new information on spawning in Devils Hole pupfish in Devils Hole, Nevada, including: temporal and spatial patterns, associated environmental factors, and effects of mechanical disturbance. Dissolved oxygen, diel dissolved oxygen variation, total daily light energy, percent cover filamentous algae/cyanobacteria, earthquake disturbance, and location on the shelf are the strongest predictors of spawning behavior in Devils Hole pupfish within Devils Hole. These factors in spawning might be utilized in adaptive management of the wild population, captive propagation to produce reserve populations, and efforts aimed at the recovery of the species. 62 INTRODUCTION Unprecedented species extinction rates, largely linked to global human colonization and population growth, increasingly threaten biodiversity (Pimm et al. 1995; Vitousek et al. 1997; Sala et al. 2000; Thomas et al. 2004). Recent efforts to curb species loss have included habitat conservation and restoration, federal and state regulations restricting natural resource uses that directly affect threatened and endangered species, and pollution and non-native species control. Familiarity with the environmental requirements of all life stages of a particular species allows biologists to tailor conservation efforts to meet species needs (e.g., Crouse et al. 1987; Schlosser 1991; Clarkson and Childs 2000). In addition to field-based conservation efforts, biologists are increasingly forced to rely on management tools such as captive breeding to create reserve populations, supplement existing populations, and provide individuals for research and education (Seal 1986; Rahbek 1993; Philippart 1995; Seddon et al. 2007; Griffiths and Pavajeau 2008). A successful captive breeding program also requires knowledge of the environmental requirements of each life stage of the organism. Conservation of wild populations can often be achieved through manipulation and management of environmental conditions. For example, floodplain management has promoted the conservation of several fish species at the confluence of the Sacramento and American rivers, California (Sommer et al. 2001; Feyrer et al. 2006). Elsewhere, stream restorations incorporating key physical habitat characteristics have led to increased salmonid spawning and recruitment (e.g., Crispin et al. 1993). In other scenarios, however, environmental degradation is so complete that restoration, let alone management, of natural conditions is not possible, as in the case of recruitment failure of 63 razorback sucker Xyrauchen texanus in the lower Colorado River basin (Minckley 1983), which must now be reared in a hatchery setting (Minckley et al. 1991; Mueller 1995). Captive breeding programs for razorback sucker have shown success (Tordoff and Redig 2001; Butchart et al. 2006; Griffiths and Pavajeau 2008), but not without limitations. Difficulties include the ability of small captive populations to maintain genetic diversity, domestication selection, and low survival due to lack of necessary environmental requirements (Philippart 1995; Snyder et al. 1996; Fraser 2008). Alteration of natural conditions associated with mating can affect production and recruitment in animal populations. Identification of mating cues among species is thus necessary for maintenance of wild and captive populations. Environmentally regulated mating induction is a phenomenon recognized in various animals (Bronson 1985; Crews and Moore 1986; Richmond and Hunter 1990). Many fishes, in particular, are known to rely on environmental cues to commence spawning (e.g., Middaugh 1981; Lluch-Belda et al. 1991; Hutchings and Myers 1994; Planque and Fredou 1999; Shumway 1999; Heyman et al. 2005). Environmental cues may also induce spawning in captive stocks. Temperature, flow regimes, and photoperiod are among some of the most-studied inducers of spawning in captive fishes (Bromage et al. 1984; Middaugh et al. 1986; Zanuy et al. 1986; Gillet 1991; Archdeacon and Bonar 2009; King et al. 2009; Kline and Bonar 2009). The availability of preferred substrate is also important for spawning of many fishes (Rakes et al. 1999). Understanding factors that trigger spawning may be of particular concern for rare, endangered fishes that normally live in unique or extreme environments. Devils Hole pupfish exists as a single population and the only aquatic vertebrate within Devils Hole, a 64 geothermal fracture spring (Springer et al. 2008) located within a disjunct portion of Death Valley National Park, California-Nevada. A submerged rock shelf supports the majority of Devils Hole pupfish foraging and spawning activities (James 1969; Minckley and Deacon 1975; Wilson and Blinn 2007). This tiny cyprinodont endures conditions normally lethal to most other fishes. Devils Hole’s high temperatures, typically 32.8– 34.0oC (Brown and Feldmeth 1971) and sometimes reaching greater than 36oC (Threloff and Manning 2003), near-hypoxic average dissolved oxygen levels of 2.5–3.0 mg/L (Baugh and Deacon 1983), and limited direct sunlight (Blinn et al. 2000; Wilson and Blinn 2007) may push the fish to the limits of its physiological tolerance (James 1969; Brown and Feldmeth 1971; Minckley and Deacon 1975). Devils Hole pupfish has been the focus of much research and conservation over the past several decades. As of Spring 2013, the population in Devils Hole fell to an estimated 35 individuals left in the wild, further emphasizing the critical need to identify limiting factors of the wild population and methods to breed the fish in captivity (National Park Service, unpublished data; U.S. Fish and Wildlife Service et al. 2013). A plethora of research has provided increased knowledge of the species and its environment; however, there remains a dearth of information on many aspects of its reproductive ecology. Population size has been associated with annual trends in primary productivity, sunlight intensity and duration (Deacon and Deacon 1979), and long-term water levels in Devils Hole (Andersen and Deacon 2001). Past studies have documented springtime spawning and recruitment (James 1969; Minckley and Deacon 1973; Deacon et al. 1995; Gustafson and Deacon 1997; Riggs and Deacon 2002), although some casual observations have indicated a broader and more varied pattern (James 1969, Riggs and 65 Deacon 2002). Factors that may influence spawning, egg production, and recruitment in Devils Hole include invertebrate food abundance, extremes in dissolved oxygen, water, and air temperatures (Lyons 2005), changes in water level, primary production, and population size (Chernoff 1985). Also unknown is how disturbance from sporadic flash flood and seismic events might affect the population, either positively (e.g., induce spawning) or negatively (e.g., remove eggs and larvae from the shallow rock shelf on which Devils Hole pupfish spawn) (Riggs and Deacon 2002; Lyons 2005). Spatial preferences of adults (James 1969) and larvae (Gustafson and Deacon 1997; Lyons 2005) on the shelf may also be associated with environmental conditions within Devils Hole. However, temporal and spatial patterns in spawning across the shelf have not been comprehensively studied. Knowledge of factors that induce spawning of Devils Hole pupfish would aid conservation and management of both the wild population and any future captive populations of Devils Hole pupfish. Goals of my study were to 1) assess on a temporal scale the environmental factors associated with spawning in Devils Hole pupfish; and 2) assess spatial patterns in spawning activity across the shelf in Devils Hole. 66 METHODS Study system Devils Hole is a disjunct portion of Death Valley National Park within Ash Meadows National Wildlife Refuge in the Mojave Desert of Nevada. It is a geothermal fracture spring of unknown maximum depth (>152 m), contained within a limestone cavern in a tectonic collapse depression estimated to have opened to the surface approximately 60,000 years ago (Riggs and Deacon 2002). Devils Hole is directly connected to an extensive carbonate aquifer within the Amargosa Valley groundwater basin, and has negligible flow and stable water chemistry. The pH at Devils Hole is relatively constant and averages 7.4 (Riggs et al. 1994), and conductivity is 655–723 µS/cm depending on time of year (Gustafson and Deacon 1997). At depths of 5.0–37.5 m, temperature is 33.5–33.9 oC (Plummer et al. 2000), and dissolved oxygen is 2.5–3.0 mg/L to a depth of 22 m (Baugh and Deacon 1983). Despite these relatively constant conditions at depth, diel and seasonal fluctuations in temperature, dissolved oxygen, solar radiation, and primary productivity occur over a 3.5 × 5.0 m2 rock shelf that is submerged at about 0.3 m depth, covers approximately half of the opening to Devils Hole, and supports the majority of Devils Hole pupfish foraging and spawning activities (James 1969; Minckley and Deacon 1975; Wilson and Blinn 2007). Temperature fluctuation is influenced by diel and seasonal changes in air temperature, direct sunlight on the water surface, and precipitation (Threloff and Manning 2003). Maximum dissolved oxygen and diel variation in dissolved oxygen occur May–July (e.g., Blinn et al. 2000; Bernot and Wilson 2012), coinciding with increases in solar radiation, primary productivity, and algal/cyanobacterial biomass (Riggs and Deacon 2002; Wilson and Blinn 2007). 67 Dominant macro algae/cyanobacteria within Devils Hole include filamentous cyanobacteria Oscillatoria princeps and Lyngbya limnetica, filamentous green algae Spirogyra spp., and several species of diatom (Shepard et al. 2000). Meioscopic and macroscopic invertebrates include the gastropod Tryonia variegata, amphipod Hyalella sp., flatworm Dugesia dorotocephala, elmid beetle Stenelmis calida, predaceous dytiscid beetle Neoclypeodytes cinctellus, and tanypod midge Zavrelimyia sp., an unidentified species of a cyclopoid copepod, ostracod, oligochaete, and water mite, and several other chironomid, dipteran, hemipteran, and coleopteran insects (Minckley and Deacon 1975; Herbst and Blinn 2003; Wilson and Blinn 2007). Public access to Devils Hole is restricted by a fence and security system implemented by the U.S. National Park Service. Survey methods I used underwater videography and a suite of environmental monitoring techniques to investigate temporal trends in Devils Hole pupfish spawning and associated environmental conditions, 14 February–15 December 2010. A black and white closed circuit television (CCTV) underwater camera (Lorex, Indianapolis, Indiana; Model CVC6990) recorded continuous daytime footage of approximately 1.5 m2 of the northwest area of the shelf, determined by preliminary observations as a location of intermediate spawning activity. The camera and digital video recording equipment were powered by a custom-built photovoltaic solar system (Chaudoin et al., in review). An Orion 3-Star RDO portable datalogging meter (NIST traceable, certified ISO 9001compliant; Thermo Scientific, Waltham, Massachusetts) recorded dissolved oxygen and temperature data every 30 min from a probe located at the southeast area of the shelf. 68 This location was chosen 1) to distance the probe from the deep pool, to facilitate measurements representative of shelf conditions while minimizing exposure to the regulating effects of the deeper cavern water, and 2) as one of only a few locations allowed under equipment placement restrictions at Devils Hole. A SPER 850008 datalogging light meter (NIST traceable; SPER Scientific, Scottsdale, Arizona) deployed three to six days per month recorded light intensity data every 15 min from a fixed point approximately 1 m above the water surface in the middle-east section of the shelf. This location was chosen as an area that adequately represented light conditions over the shelf. Once or twice monthly, a modified Braun-Blanquet/Daubenmire method (Braun– Blanquet 1932; Daubenmire 1959) was used to monitor percent cover of visually dominant algal/cyanobacterial species, using a 0.6 × 0.4-m2 PVC-pipe quadrat subdivided by 0.1 × 0.1-m2 squares to survey the entire shelf excepting the area directly beneath the 0.5 × 3.0-m2 viewing platform. Dominant algae Spirogyra spp., cyanobacteria Oscillatoria/Lyngbya spp., unidentified mixed-species encrusting, or bare space was recorded for each square and assigned a median percent cover value based on a standard index of 0–5% = 2.5%, 5–25% = 12.5%, 25–75% = 50%, and 75–100% = 87.5%. Changes ≥ 0.006 m in water level recorded every 15 min indicated disturbance within Devils Hole (National Park Service, unpublished data). Additional precipitation data from an onsite National Park Service weather station plus notes by Park Service biologists specified whether disturbance originated from a seismic event or a storminduced flash flood. Water level data were recorded with a Campbell CR10 datalogger (Campbell Scientific, Logan, Utah), an Enhanced Measurement Process PS-9104E pressure sensor (Instrumentation Northwest, Kirkland, Washington), and a Druck 1830 69 pressure sensor (GE Measurement and Control, Fremont, California); and a secondary system consisting of a Stevens GS-98 datalogger and a Stevens Type A Model 71 continuous chart recorder (Stevens Water Monitoring Systems, Portland, Oregon). To investigate potential relationships between spatial variation in spawning across the shelf, I divided the shelf into six 1.5-m2 quadrants (Figure B1), and measured substrate, depth, and percent algal/cyanobacterial cover in each. I surveyed substrate twice using a modified Braun-Blanquet/Daubenmire method (Braun–Blanquet 1932; Daubenmire 1959) and a 0.6 × 0.4-m2 PVC-pipe quadrat subdivided by 0.1 × 0.1-m squares to survey the entire shelf excepting the area directly beneath the 0.5 × 3.0-m2 viewing platform. I characterized substrate according to modified Wentworth classification of grain size (Cummins 1962). Twenty-six depth measurements (4 equidistant points per quadrant) yielded a rough estimate of average depth across the shelf. I used algal/cyanobacterial censuses to investigate within month differences in percent cover among quadrants. I conducted visual surveys from 8 January to 5 December 2010 to investigate spatial variation in Devils Hole pupfish spawning on the shallow shelf. Fish were viewed from a 0.5 × 3.0-m2 metal viewing platform deployed on the shallow shelf. Fish were given at least 2.5 h to acclimate and return to normal activity after deployment of the viewing platform. Five to six surveys were conducted during a 24-h period, once to twice per month. Surveys occurred 1 h before dawn, sunrise, midmorning, midafternoon (approximately 1400–1600 hours, coinciding with maximum sun exposure on Devils Hole), sunset, and night (3–4 h after dusk). The spawning shelf was divided into six 1.5m2 quadrants to aid visual monitoring. Each quadrant was monitored in random order for 70 5 min, and total spawning events per 5 min were recorded. Low light (predawn and sunset) and night surveys were conducted using night-vision goggles (Night Optics U.S.A., Huntington Beach, California; Model D-2MV PRO). Data analysis Spawning was defined as a single event in which two individual fish came together in a “sidling” behavior of swimming side-by-side, generally followed by one or more of the following behaviors: “s-shaping”, “wrapping”, and “jerking” motions between the mating pair (Barlow 1961; Liu 1969; Baugh 1985). Preliminary visual surveys indicated sidling behavior generally results in spawning unless there is interruption by other males. Therefore, sidling behavior within the sample frame was considered a spawning event. A mating pair that clearly exited and re-entered the sample frame while only sidling was counted as a single event. A mating pair that completed mating, separated, then proceeded to come together to mate again was counted as a separate spawning event. Temporal analysis A total of 522 video clips were randomly sampled by date and time, stratified by month, analyzed for number mating incidents per sample, and date–time matched with corresponding environmental data. Temperature and dissolved oxygen data points (recorded at 30-min intervals) were matched to within 15 min, and light intensity data points (recorded at 15-min intervals) were matched to within 7.5 min. Light intensity values for spawning events that occurred between light surveys were interpolated from the closest proximal recorded date–time values by averaging closest values on either side. 71 For example, if there was a 15-d gap between light surveys, spawning events that took place in the 5 d following the preceding light survey were matched with mean light timevalues from that survey; spawning incidents occurring in the 5 d prior to the later light survey were matched with mean light time-values from that survey; and those falling in the central 5 d between surveys were matched with the average of the mean time-values from each survey. Light measurements were totaled over each 24-h day (0000–2359 hours) to obtain total daily light intensity (lux), which served as an index of light energy input to the system for that day. Total percent cover filamentous algae/cyanobacteria across the shelf was represented by both mean cover per month and a daily average throughout the year. Algal abundance was punctuated by periods of sudden reduction due to disturbance-caused removal. Earthquake seiche and/or storm-induced flash flood disturbance was counted as presence/absence, with presence indicated for 72 h after a given event. The dataset showed a left-skewed distribution with many zeros (Figure B2), thus I used zero-inflated Poisson (ZIP) regression models (e.g., Lambert 1992; Martin et al. 2005) to test for effects on spawning of the following continuous environmental variables (as described above): dissolved oxygen (mg/L), temperature (oC), diel temperature variation (24-h daily maximum – minimum [oC]), diel dissolved oxygen variation (24-h daily maximum – minimum [mg/L]), diel temperature and dissolved oxygen variation for the previous day, light intensity (lux, log10-transformed), total daily light intensity (lux, loge-transformed), mean monthly percent cover filamentous algae/cyanobacteria (arcsinetransformed), and mean daily percent cover filamentous algae/cyanobacteria (arcsinetransformed); and effects on spawning of the categorical variable presence/absence of 72 disturbance events. I tested several full and reduced models that included main, additive, and interaction effects, and ranked them by lowest corrected Akaike’s Information Criterion (AICc). I then calculated the difference in AICc between each competing model and the most plausible model (∆iAICc) and Akaike weight of each model (wiAICc) as a measure of model probability (Anderson 2008). Variance inflation factor (VIF) analysis assessed potential multicollinearity among independent variables. Likelihood ratio and Pearson’s chi-square goodness-of-fit tests assessed model significance and fit, respectively. Earthquake disturbance I used paired t-tests to investigate before and after effects on spawning of each earthquake that created a seiche in Devils Hole. Time-randomized video samples from 72 h before and 72 h after each event were added to those from the temporal analysis that happened to occur within these time frames, bringing total sample size for each earthquake event to n = 14–16 matched pairs of 5-min video clips. Spatial analysis I used Kruskal–Wallis k-sample tests with Monte Carlo estimation of exact Pvalues and Wilcoxon rank-sum multiple comparison procedure for all pairwise comparisons (Bonferroni-adjusted α = 0.003 [0.05/15 comparisons]) to investigate spatial variation in both overall and within month spawning (number of events per 5-min survey). Spawning data were obtained from visual surveys; predawn, sunset, and night surveys were eliminated from the analysis due to almost no spawning activity during these times. For biological inference of nonparametric tests, I report means rather than rank- 73 sum scores. I conducted all statistical analyses using SAS Statistical Software (SAS Institute® 9.3, 2011–2013, Cary, North Carolina). 74 RESULTS Temporal analysis Each Devils Hole pupfish mating pair swam across a large area of the shelf during courtship, often extending beyond the 1.5-m2 survey area. Visual surveys showed mating occurred above the substrate rather than within or under algae/cyanobacteria, which was generally present as a close-fitting, contoured mat along the shelf substrate. Spawning showed a bimodal pattern, with the majority of spawning occurring late February to late May, peaking late March through April, and lesser frequency of spawning in October and November (Figure B3). Mean daily temperature 11 January–21 December 2010 in the southern portion of the shelf where the probe was stationed was 33.2 oC with an overall range of 32.4–34.6 oC, and diel variation in temperature was slightly greater in summer compared to the rest of the year (Figure B4). Daily mean dissolved oxygen was 3.0 mg/L with an overall range of 0.4–10.2 mg/L; dissolved oxygen showed greater diel variation in late spring through late summer compared to the rest of the year, and generally fluctuated more than temperature (Figure B5). Maximum daily light intensity ranged from approximately 4,600 lux in the winter under indirect sunlight to 97,800 lux in July under direct sunlight, and total daily light intensity was likewise at a maximum in July (Figure B6). The most dominant algal/cyanobacterial taxon was the filamentous cyanobacteria Oscillatoria/Lyngbya spp., which was present year-round but most abundant in late spring to mid-summer (Figure B7). The green algae Spirogyra spp. appeared to a much lesser extent in mid to late summer. A bright-green cobbleencrusting biofilm present to a small extent during winter and less in spring and fall appeared to be a mix of early colonizers comprised of diatoms and cyanobacteria that 75 occurred mainly after seiches and following seasonal die-off of larger species. A flashflood occurred 22 December 2010, soon after the study ended on 15 December 2010, and was thus not included in the analysis. Three separate earthquake disturbances created seiches in Devils Hole: 1) 26 February 2010 2235 hours PST / 27 February 2010 0635 hours UTC, 8.8 magnitude, centered off the coast of central Chile; 2) 4 April 2010 1540 hours PST / 2240 hours UTC, 7.2 magnitude, centered just south of Guadalupe Victoria, Baja, California; and 3) 21 October 2010 1053 hours PST / 1753 hours UTC, 6.7 magnitude, centered in the Gulf of California (National Park Service, unpublished data). Eighty-five models were fit, wiAICc ranged 0.00–0.28 (Table B1). The best-fit model: loge(λi) = – 102.642 + 0.875(b) + 0.502(d) + 8.097(h) + 141.167(i) + 2.552(k) – 0.253(b*d) – 11.365(h*i) – 1.849(d*k), loge{[P(y = 0)]/[P(y > 0)]} = – 2.530 + 0.378(l); where λi = the rate (#/5 min) at which spawning events are expected to occur; b = Dissolved oxygen (mg/L); d = Diel dissolved oxygen variation (max – min [mg/L]); h = Loge(Total daily light intensity[lux]); i = Arcsin(Mean monthly % cover filamentous algae/cyanobacteria); k = Earthquake disturbance (presence/absence); l = Month (as a predictor of excess zeros); {[P(y = 0)]/[P(y > 0)]} = the odds of obtaining an excess zero value; showed significant ( ≤ 0.05) relationships between spawning and dissolved oxygen (P = 0.03), loge-transformed total daily light intensity (P < 0.0001), arcsine-transformed mean monthly percent cover filamentous algae/cyanobacteria (P < 0.0001), earthquakes (P = 0.0008), and the following interactions: dissolved oxygen*diel dissolved oxygen 76 variation (P = 0.05), loge-transformed total daily light intensity*arcsine-transformed mean monthly percent cover filamentous algae/cyanobacteria (P < 0.0001), and diel dissolved oxygen variation*earthquakes (P = 0.02) (Table B2). Most spawning occurred within 2.6–4.8 mg/L dissolved oxygen, total daily light intensity133,250–400,300 lux, filamentous algal/cyanobacterial cover 24–60% and especially 24–27%, and presence of earthquakes; and among interaction effects, more spawning occurred at 2.6 mg/L dissolved oxygen when diel dissolved oxygen variation was low (0.3–1.6 mg/L), lower to mid-range monthly mean percent cover filamentous algae/cyanobacteria (24–32%) when total daily light intensity was lower to mid-range (110,000–330,000 lux), and postearthquake when diel dissolved oxygen variation was low (0.6–1.3 mg/L) (Figures B8– 13). In the logistic part of the model, which predicts zeros generated by processes other than those attributable to the count values, month was a significant predictor of excess zeros (P = 0.0002). Dissolved oxygen instrumentation failure resulted in 176 missing lines of data in the model dataset, reducing the model-specific sample size to n = 346. Variance inflation factors of <3 indicated no significant multicollinearity among independent variables. Likelihood ratio test showed the model was significant (2 = 264.546, df = 8; P < 0.0001); Pearson’s chi-square goodness-of-fit test showed slight underdispersion, but still good fit to the data (2 = 301.432, df = 335; P = 0.91). Earthquake disturbance There was significantly more spawning ( ≤ 0.06) after the 27 February 2010 earthquake (mean [number of events per 5 min] = 1.06; SE = 0.32) compared to before (mean = 0.31; SE = 0.15), and significantly more spawning after the 21 October 2010 earthquake (mean = 0.57; SE = 0.27) compared to before (mean = 0.00) (Figure B14, 77 paired t-test: t = -2.02, df = 15; P = 0.06; and t = -2.10, df = 13; P = 0.06, respectively). There was no significant difference in spawning before (mean = 2.07; SE = 0.50) and after (mean = 2.00; SE = 0.62) the 4 April 2010 earthquake, during peak spawning season. Spatial analysis The northeast quadrant of the spawning shelf had significantly more overall spawning (mean [number of events per 5-min survey] = 0.65; SE = 0.18) than the middlewest (mean = 0.12; SE = 0.05), southeast (mean = 0.08; SE = 0.04), and southwest (mean = 0.02; SE = 0.02) quadrants (Figure B15, Kruskal–Wallis k-test: 2 = 19.099, df = 5; P = 0.0005 and Wilcoxon rank-sum multiple comparison with Bonferroni-adjusted α = 0.003 [0.05/15 comparisons]). No differences in spawning among quadrants within a given month were observed (Figure B16). Substrate on the shelf contained a mix of bedrock, boulder, cobble, pebble/gravel, and sand/silt. The northern quadrants of the shelf were comprised of mostly bedrock; the southern areas of the shelf contained more cobble, pebble/gravel, and some sand/silt (Figure B17). Depth across the shelf varied, with the northwest quadrant deepest at mean depth 67.3 cm, and the southwest quadrant shallowest at mean depth 25.7 cm (Figure B18). Filamentous algal/cyanobacterial cover did not vary much among quadrants within a given month (Figure B19). 78 DISCUSSION Environmental cues in spawning of fishes in both natural and captive settings include temperature, dissolved oxygen, photoperiod, flow patterns, salinity, and availability of preferred substrate (e.g., Carlson and Herman 1978; Bromage et al. 1984; Middaugh 1981; Middaugh et al. 1986; Planque and Fredou 1999; Robillard and Marsden 2001; King et al. 2009). Though perhaps less-studied, desert fishes also display spawning preferences linked to several of these parameters (e.g., Mueller 1984; Vives and Minckley 1990; Rakes et al. 1999). Desert warm and hot springs provide geothermally regulated temperatures, relatively constant flow rates, and abundant yearround sunlight to maintain stable conditions relative to non-spring systems. Fishes living in these ecosystems display preferences for spawning associated with subtle changes in environmental conditions. Saratoga Springs pupfish C. nevadensis nevadensis spawned more and produced more eggs per spawn at constant temperatures within the range of 24– 32 oC and when temperatures fluctuated between 32–28 oC and 36–28 oC among test ranges of 18–39 oC in aquaria (Shrode and Gerking 1977). Hybrid Devils Hole pupfish C. diabolis × C. n. mionectes produced more eggs during constant 28 oC and fluctuation of 28–23 oC among test ranges within 24–34 oC in aquaria (Feuerbacher et al., in review). Hybrid Devils Hole pupfish also showed preference for spawning and egg deposition in yarn mops that structurally mimicked filamentous or branching algal/cyanobacterial species over spawning on gravel or bare tiles; and they showed increased spawning activity after water changes without temperature change in oxygen saturated water, indicating possible direct effects of mechanical disturbance (O. G. Feuerbacher, personal communication). Desert pupfish C. macularius (Barlow 1961) and Cuatro Cienegas 79 pupfish C. bifasciatus (Ludlow et al. 2001) spawned more on rocks than on sand in both aquaria and in the field. Past studies have indicated seasonal factors in spawning and recruitment in Devils Hole pupfish. Population size has been positively correlated with primary productivity with a one-month lag time in population increase, and with sunlight intensity and duration with a two-month lag time in population increase (Deacon and Deacon 1979). Larval abundance was greatest from March to April, following decline of invertebrate food species, and prior to periods of increased fluctuations in dissolved oxygen and water, air, and substrate interstitial temperatures (Lyons 2005). Minckley and Deacon (1973) found larger ovaries, larger ova, and greater number of ova within adult fish collected during May 1968 compared to October of the same year. Adult fish collected in spring 1990 produced five times more eggs when placed in a laboratory setting than those collected fall of the previous year (Deacon et al. 1995). Captive fish held in aquaria also preferred to spawn in artificial grass than in gravel (Deacon et al. 1995). These studies plus casual field observations of spawning (James 1969; Gustafson and Deacon 1997) indicated a spring spawning season, though the year-round presence of larvae on the shelf (James 1969; Lyons 2005; National Park Service, unpublished data) and casual observations of spawning (Miller 1948, 1961; James 1969; La Rivers 1994) also suggested the potential of year-round spawning and recruitment. My findings on the temporal and spatial patterns in spawning of Devils Hole pupfish both corroborate and expound upon earlier findings. More spawning occurred at lower to mid-range conditions of dissolved oxygen, total daily light intensity, mean monthly percent cover filamentous algae/cyanobacteria, 80 presence of earthquakes, and interactions of dissolved oxygen*diel dissolved oxygen variation, total daily light intensity* mean monthly percent cover filamentous algae/cyanobacteria, and diel dissolved oxygen variation*earthquakes. There was a positive relationship between spawning and month as a predictor of excess zeros, indicating an increased probability of obtaining an excess zero (not related to processes dictating count values) as the year progressed. Each of the three continuous variables that showed main effects on spawning, as well as diel variation in dissolved oxygen which was significant among interaction variables, generally displayed lowest values in winter and highest values in summer. In summer, dissolved oxygen frequently spiked from a mean baseline of 2.5–3.0 mg/L up to 6.0–10.0 mg/L (~28–140% saturation) for 2 to 3 h during mid-afternoon when direct sunlight was most intense on the shelf and abundant algal/cyanobacterial cover was present. Dissolved oxygen would subsequently return to its near-hypoxic baseline almost immediately after sunlight moved off the shelf. Dissolved oxygen frequently fell to 1.0–2.0 mg/L during night and early morning, likely due to algal/cyanobacterial and/or microbial respiration. However, values below 1.0 mg/L were infrequent, and a 0.35 mg/L low recorded 19 November 2010 2131 h PST was an exception rather than the norm, possibly resulting from seasonal algal/cyanobacterial decay or nighttime respiration of temporary growth surrounding the probe sensor. Optimal dissolved oxygen values (2.6–4.8 mg/L) and diel dissolved oxygen variation (0.3–1.6 mg/L) were frequently recorded during spring and fall spawning periods. However, these values also occurred during winter when spawning was minimal to absent. Among interaction effects, more spawning occurred at 2.6 mg/L dissolved oxygen when diel dissolved oxygen variation was low (0.3–1.6 mg/L). Effects 81 of hypoxia on fishes are well known; however, even fluctuations in dissolved oxygen regardless of hypoxia can trigger molecular-level stress responses in fishes (Marcon and Filho 1999; Ross et al. 2001). Similarly, extremes in dissolved oxygen in Devils Hole may stress Devils Hole pupfish and limit high-energy activities during periods of hypoxia and supersaturation. Such stress may also explain why diel dissolved oxygen variation which did not show a significant main effect on spawning was part of a significant interaction effect on spawning, with increased spawning during days of less dissolved oxygen variation. Photoperiod triggers spawning in many fishes (e.g., Bromage et al. 1984). I found similar association between spawning in Devils Hole pupfish and total daily light intensity, which I used as an indicator of light energy within Devils Hole. The optimal total daily light intensity range identified by the model (133,250–400,300 lux) might represent a range associated with the other optimal conditions identified in this study, which collectively trigger spawning induction. Intense direct sunlight exposure above 400,300 lux could expose fish to stressful levels of ultraviolet radiation or microtemperature increases. Average diel temperature variation of 0.7 oC during the summer, while not significantly related to spawning activity in the best-fit model, may still introduce a level of stress that affects such activities on the shelf. In all models tested, spawning activity was highly associated with mean monthly percent cover of filamentous algae/cyanobacteria, which had an overall range of 24–69%, with most spawning taking place within lower to intermediate cover ranges 24–60%, and especially 24–27%. However, daily mean cover across the shelf ranging 7–74% (lows reflect brief periods of greatly diminished cover due to seiches) was not significant in 82 most models tested. The significance of monthly means rather than daily means in filamentous algal/cyanobacterial cover may indicate a broader pattern of pupfish response to cover over a longer time frame, rather than a specific point-in-time effect of cover. For example, spawning trends associated with monthly changes in cover may indicate both positive and negative impacts of algae/cyanobacteria on Devils Hole pupfish. Positive impacts may include provision as a primary food source, as substrate for forage species such as diatoms and micro/macro invertebrates (which were not included in the model due to restrictions on destructive sampling within Devils Hole), and as substrate for adhesive egg deposition. Optimal algal/cyanobacterial cover may also affect optimal ranges of other significant variables (e.g., dissolved oxygen and diel dissolved oxygen variation). Negative effects of overabundant algal/cyanobacterial cover, as occurs in summer, may include increased spikes in dissolved oxygen, which may stress fish, and increased interstitial anoxia/hypoxia contributing to higher levels of toxic gases such as hydrogen sulfide (Lyons [2005] noted increased low-level H2S from summer samples compared to those taken at other times of the year). Some members of the cyanobacterial generas Lyngbya and Oscillatoria are known to possess chemical compounds toxic to fishes (Teneva et al. 2003; Malbrouck and Kestemont 2006). Spawning was associated with optimal ranges in significant predictors, rather than possessing simple linear association with predictors, potentially indicative of evolutionary-derived physiological and behavioral response to increases in and/or optimal ranges of conditions necessary for commencement of spawning activities. Spawning increased following earthquakes that produced seiches in Devils Hole, specifically in late February and in October, but not when spawning was at its peak in 83 early April. Spawning activity before the April earthquake was likely already at maximum, and probably could not increase much further. Disturbance events such as flash floods caused by rainstorms and seiches caused by seismic events redistribute substrate and reduce algal/cyanobacterial abundance on the shelf. However, daily mean percent cover algae/cyanobacteria was not a significant predictor of spawning activity. The absence of association between spawning and punctuated changes in cover, combined with lack of significant increase in diel dissolved oxygen variation after earthquakes (Chaudoin, unpublished data), suggests potential direct effects of mechanical disturbance on spawning. Although disturbance is associated with increased spawning during all but at the very peak of the spawning season, disturbance may pose other risks to Devils Hole pupfish. Inopportunely timed disturbance could remove eggs and/or larvae from the shelf during the critical spring spawning period, or it could remove already scarce fall/winter algae/cyanobacteria that may not regrow until the following spring, further limiting food sources. A significant effect of multiple interactions of environmental variables suggests a suite of conditions influences spawning of Devils Hole pupfish in the wild. Particularly, the negative relationships between spawning and dissolved oxygen*diel dissolved oxygen variation, and diel dissolved oxygen variation*earthquakes, further corroborates the aforementioned concept of dissolved oxygen spikes presenting potentially suboptimal or stressful conditions for fish. The best-fit model showed no significant effects of water temperature or diel water temperature variation on spawning, suggesting several possibilities: 1) the generally minor diel and seasonal changes in temperature occurring within Devils Hole 84 did not affect spawning; 2) temperature meters, accurate to ±0.3 oC, did not fully detect microtemperature fluctuations; or 3) the model could not detect such small changes in temperature in a meaningful way. Maximum water temperatures generally occurred midafternoon in the summer when air temperature and light intensity were at a maximum; minimum water temperature occurred during a winter storm that likely induced a flash flood in late December and lowered water temperature from 33.4 oC at 1150 hours PST, to 28.2 oC at 1220 hours PST. Water temperature returned to 33.0-33.3 oC by 1350–1420 hours PST. This event occurred after termination of spawning surveys and was not incorporated into the regression model. However, given the effects of earthquakes on spawning activity, flash floods that bring cold, oxygenated, nutrient-enhanced water onto the shelf could have similar or greater effects on spawning, especially during non-peak spawning periods. Zero-inflated mixture models are increasingly employed for longitudinal count data with many zeros. More commonly employed in econometrics, social sciences, and health sciences research, they are increasingly recognized as a useful tool in wildlife, fisheries, and other ecological research (Martin et al. 2005; Arab et al. 2008; Wenger and Freeman 2008). Zero-inflated Poisson regression proved useful in this study, as Devils Hole pupfish spawning activity was infrequent (mean detected spawning frequency = 0.06 events/min). Other types of multiple regression models tested showed poor fit (e.g., zero-inflated negative binomial [ZINB]; Poisson; negative binomial; simple linear; and a two-model approach where data was subdivided into presence/absence versus positive count—the former was analyzed using logistic regression, the latter using Poisson and negative binomial regression). Zero-inflated negative binomial models fit best after ZIP 85 models, but they were very underdispersed. The best-fit ZIP model from this observational study provides a good starting point to further explore the effects of significant variables on spawning in a controlled experimental setting. The use of visual surveys incurred a small sample size and greater variability and variance than the use of fixed videography (Chaudoin et al., in review). However, while the underwater camera surveyed only the northwest area of the shelf, visual surveys collected information on spawning across the entire shelf throughout the year. The spatial patterns in spawning activity I found are opposite larval distributions found by Gustafson and Deacon (1997) and Lyons (2005), who recorded more larvae over the south and middle rather than the north areas of the shelf. My results corroborate casual observations by Gustafson and Deacon (1997) of spawning activity over middle and north areas of the shelf; however, they saw most spawning in the middle-west area followed by the northwest and northeast areas, whereas I saw most spawning in the northeast area, followed by the northwest then middle-east areas. Gustafson and Deacon (1997) implicate diel dissolved oxygen variation across the shelf in the spatial variation of larval abundance, with larvae seeming to prefer areas of higher dissolved oxygen variation. If greater dissolved oxygen variation does create physiological stress in adult fish, the decreased dissolved oxygen variation approaching the deep pool could explain the increased spawning I saw in the middle and north areas of the shelf. Diel temperature variation across the shelf, particularly April–September, has a similar pattern of greater variation over the southern portion of the shelf farthest from the deep pool (Threloff and Manning 2003). Though not significant in the temporal model of spawning, temperatures 86 approaching or exceeding energetic maxima for spawning activity could further induce stress and drive spatial preferences in spawning. During 2010, physical substrate was distributed along a gradient from the south areas of the shelf, which contained mostly sand, gravel/pebble, and cobble, to the north areas, which contained mostly bedrock. Considering the preference of some pupfishes for spawning on cobble as opposed to sand, this substrate gradient presents a potential preference of Devils Hole pupfish to spawn over larger substrate found in the northern areas of the shelf, and might be explored further in a controlled experimental setting. Algal/cyanobacterial cover was generally consistent across the shelf within a given time period, so it was not possible to discern any effect of cover on spatial variation in spawning based on field observations. Variability in depth across the shelf also did not indicate a specific preference for deeper or shallower areas; rather, proximity to the mitigating effects of the deep pool on fluctuations in temperature and dissolved oxygen may be an indirect factor in spatial variation. I noted incidental observations of several spawning events on the very edge of the shelf at the shelf–deep pool boundary, a few spawning events on the convexly sloped west wall beyond the shelf over the deep pool, a few spawning events on a stationary underwater metal structure at the northeast area of the shelf, and one spawning event on the second shelf at about 5 m depth. In June through September, air temperatures frequently reached ≥45 oC/113 oF, which exceeded maximum rated operable temperatures of dissolved oxygen/temperature meters and resulted in some missing environmental data during this time. An automatic fish-feeder in operation since 2006 was located at the far northeast edge of the shelf, within approximately 0.3–1.5 m of the camera field of view and also proximal to areas 87 containing the most spawning activity, presenting a potential confounding factor. Due to strict regulations limiting research equipment within the highly protected Devils Hole environment, I was allowed a single underwater camera providing a subsample of spawning activity on the shelf. A three or four camera design and additional environmental data loggers covering greater shelf area would have allowed more thorough statistical modeling of environmental factors in spawning in Devils Hole pupfish. Visual surveys were instead relied upon for investigation of spatial variation in spawning. These surveys had high sampling error and variability throughout the year, and results were not always consistent with those of the underwater camera (Chaudoin et al., in review). Finally, my results reflect 2010 environmental conditions; environmental conditions and subsequent pupfish behavior could vary year to year. Based on my results, actions to promote spawning in the wild might include one or more of several measures, which would require further action-specific assessment for benefit and safety to Devils Hole pupfish and the Devils Hole ecosystem. These measures include: 1) Aerate the water to 2.6–4.8 mg/L dissolved oxygen, with consideration to resulting pH increase and care not to aerate too quickly or over-aerate, as the pH of Devils Hole water increases rapidly to levels above pH 9 upon aeration, which would cause great stress to fish (O. G. Feuerbacher, personal communication). 2) Provide small scale shaded areas May–August, when total daily light intensity is above optimal range. This may aid in reducing direct negative effects of light intensity, as well as indirect effects such as dissolved oxygen spikes, on pupfish spawning. Provide artificial light November–January, when total daily light may fall below optimal levels. 88 3) Introduce artificial macro algae/cyanobacteria replicas during times of extremely low algal cover (winter/after disturbance), to bring cover into an optimal range for spawning. Perform localized reductions in algae/cyanobacteria during June–July peaks in algal/cyanobacterial abundance, to lower cover into optimal range for spawning and decrease diel dissolved oxygen variation. However, reductions to both light and algal/cyanobacterial cover should be approached with caution, considering evidence that Devils Hole is an energy-limited system (Wilson and Blinn 2007). During the course of this study, I observed small scale, localized removal of algae/cyanobacteria from the shelf due to natural senescence and/or disturbances. Male pupfish subsequently defend these resulting bare spaces. These observations, combined with my results, suggest that any management-associated reduction in algae/cyanobacteria/light might be limited to just a few small areas (e.g., approximately 5–15 cm in diameter). This would allow potential increase in spawning activity, without compromising food sources or other potential positive effects of high algal/cyanobacterial cover. 4) For purposes captive propagation, focus wild egg collection after disturbance events and during late February–May, particularly late March–April and October–November. 5) Focus field management of spawning activity and egg collection to areas of higher spawning activity, particularly the northeast, northwest, and middle-east areas of the shelf, respectively. For initial captive propagation efforts, consideration might be given to dissolved oxygen, light intensity, algal/cyanobacterial cover, and disturbance regimes incorporating natural levels I observed to promote breeding. Devils Hole pupfish spawning seems to be stimulated by a change in conditions— either by progression into optimal ranges of 89 dissolved oxygen, algal/cyanobacterial cover, and light intensity; or by extreme disturbance such as earthquake-induced seiches. Consideration should be given to controlled progression into optimal levels for the variables significantly related to spawning, rather than maintaining static conditions. Upon successful establishment of captive Devils Hole pupfish stock, controlled laboratory experimentation could further isolate individual predictor variable effects and associated mechanisms in promoting spawning activity. After initial success in breeding this notoriously difficult to breed species, Devils Hole seasonal environmental regimes might be applied to captive stock, as fishes bred under more natural conditions may also experience reduced domestic selection, in which unnatural conditions eliminate those selective pressures that maintain population viability in the wild. Minimizing domestic selection is an important consideration for captive and refuge populations intended as reserve populations or for reintroduction (Williams and Hoffman 2009). Knowledge of environmental conditions that promote reproduction in fishes aids conservation and management efforts. Results from this observational field study provide a basis for initial captive propagation attempts and further controlled evaluation of environmental conditions associated with spawning in Devils Hole pupfish. Given the continuing decline in numbers of the only existing population of Devils Hole pupfish, this information is critical to adaptive management of this highly endangered desert fish. 90 ACKNOWLEDGMENTS The U.S. Fish and Wildlife Service (USFWS), U.S. Geological Survey (USGS), University of Arizona (UA), Nevada Department of Wildlife (NDOW), and National Park Service (NPS) provided funding and support for this study. Paul Barrett and Lee Simons (USFWS) provided project oversight. Olin G. Feuerbacher, Scott A. Bonar, and Paul J. Barrett will be co-authors on this paper when submitted for publication. We thank Michael Bower, Bailey Gaines, Genne Nelson, Kevin Wilson (NPS), William Matter (UA), Jon Sjoberg (NDOW), and Darrick Weissenfluh (USFWS) for project consultation, review, and advice. We thank those who assisted with fieldwork, especially Parker Ashbaugh, Laiken Jordhal, Justin Mapula, Rachel More-Hla, and Lisa Trestik (UA). Thanks to Cindy Cowen and Carol Yde (UA) for their guidance with administrative procedures. We thank Mark Borgstrom and Robert Steidl for statistical advice; Mickey Reed (UA) for his GIS/cartography expertise; Dave Bogner (UA), Steve Hiebert (BOR), and David Ward (AZGFD) for their technical advice; and Martin Pepper (UA), Greg Sherman (Wiseguys Custom Home Theater, LLC), and Katherine Kent (The Solar Store) for advice and guidance on custom technical systems design. All research was conducted in accordance with University of Arizona Institutional Animal Care and Use Committee protocol #09-115. Any use of trade names is for descriptive purposes only and does not imply endorsement by the U.S. Government. 91 Table B1. Zero-inflated Poisson model selection results (∆iAICc = difference in corrected Akaike’s information criterion) for those models with corrected Akaike weights (wiAICc) ≥ 0.00. Modela ∆iAICc wiAICc b + d + h + i + k + (b*d) + (h*i) + (d*k); l 0.28 0.00 b + d + h + i + k + (b*d) + (h*i) + (b*k) + (d*k); l 0.17 1.07 b + d + h + i + k + (b*d) + (h*i) + (d*k) + (h*k); l 0.12 1.77 a + b + d + h + i + k + (b*d) + (h*i) + (a*k) + (b*k) + (d*k); l 0.08 2.43 b + d + h + i + k + (b*d) + (h*i) + (d*k) + (h*k) + (i*k); l 0.08 2.44 a + d + h + i + k + (a*d) + (h*i); l 0.05 3.35 a + d + h + i + k + (b*d) + (h*i) + (d*k); l 0.05 3.56 b + d + g + h + i + k + (b*d) + (g*i) + (h*i) + (d*k) + (h*k) + (i*k); l 0.03 4.22 a + b + d + h + i + k + (a*b) + (a*d) + (b*d) + (h*i) + (d*k); l 0.03 4.63 b + d + h + i + k + (h*i); l 0.02 5.22 d + g + h + i + k + (h*i); l 0.02 5.63 a + d + h + i + k + (h*i); l 0.01 6.02 c + d + g + h + i + k + (h*i); l 0.01 6.09 d + h + i + k + (h*i); l 0.01 6.12 a + b + d + h + i + k + (h*i); l 0.01 7.33 a + b + c + d + h + i + k + (h*i); l 0.01 7.47 a Dependent variable: Number of spawning events per 5-minute sample Independent variables: a = Temperature (oC) b = Dissolved oxygen (mg/L) c = Diel temperature variation (max – min [oC)]) d = Diel dissolved oxygen variation (max – min [mg/L]) g = Log10(Light intensity [lux]) h = Loge(Total daily light intensity [lux]) i = Arcsin(Mean monthly % cover filamentous algae/cyanobacteria) k = Earthquakes (presence/absence) l = Month (as a predictor of excess zeros) 92 Table B2. Statistical results for effects of environmental variables on spawning in Devils Hole pupfish (number of events per 5-min sample), from best-fit zero-inflated Poisson model. Significant P-values are in bold, and corresponding relationships are specified for significant predictor variables. ß0.0 and ß0.1 represent the intercept and predictor variable for the logistic regression portion of the model that predicts excess zeros. Parametera Estimate SE P-value -102.642 16.379 ß0 < 0.0001 0.875 0.403 ß1 0.03 0.502 0.413 0.22 ß2 8.097 1.266 ß3 < 0.0001 141.167 26.092 ß4 < 0.0001 2.552 0.758 ß5 0.0008 -0.253 0.132 ß6 0.05 -11.365 2.024 ß7 < 0.0001 -1.849 0.810 ß8 0.02 -2.530 0.704 ß0.0 0.0003 0.378 0.101 ß0.1 0.0002 a Parameters: ßo = Poisson model intercept ß1 = Dissolved oxygen (mg/L) ß2 = Diel dissolved oxygen variation (max – min [mg/L]) ß3 = Loge(Total daily light intensity [lux]) ß4 = Arcsin(Mean monthly % cover filamentous algae/cyanobacteria) ß5 = Earthquakes (presence/absence) ß6 = Dissolved oxygen*Diel dissolved oxygen variation ß7 = Loge(Total daily light intensity [lux])*Arcsin(Mean monthly % cover filamentous algae/cyanobacteria) ß8 = Diel dissolved oxygen variation*Earthquakes ß0.0 = Logistic model intercept ß0.1 = Month (as a predictor of excess zeros) 93 Figure B1. Quadrant demarcation of the shallow shelf at Devils Hole, Nevada showing meter coordinates used for visual spawning, depth, algal/cyanobacterial, and substrate surveys, based on National Park Service coordinate system. Actual survey quadrants begin approximately 0.25 m east and west of the central line to accommodate the presence of the viewing platform. The southernmost section of the shelf was excluded from the surveys. marks the location of the light meter;  marks the location of the temperature/dissolved oxygen probe. 94 Figure B2. Frequency distribution of spawning in Devils Hole pupfish (number of spawning events per 5-min underwater video clip, n = 522) on the shallow shelf at Devils Hole, Nevada, February–December 2010. 500 Number of samples 400 300 200 100 0 0 1 2 3 4 5 6 Count (# of spawning events per sample) 7 8 95 Figure B3. Devils Hole pupfish spawning (number of events per 5-min sample) by month, 2010, recorded on daytime underwater video footage of the shallow shelf in Devils Hole, Nevada. Month intervals on the x-axis are delineated to actual date scale. n = 522 5-min samples. 96 Figure B4. Daily maximum, minimum, and mean water temperature (oC) in the water column above the shallow shelf at Devils Hole, Nevada, 2010. Thermo Orion 3Star Portable RDO datalogging meter recorded temperatures to ±0.3 oC-accuracy every 30 min. Dissolved oxygen/temperature optical probe was deployed above the substrate in approximately 26.5-cm deep water. Data gaps represent missing data due to instrumentation failure. 97 Figure B5. Daily maximum, minimum, and mean dissolved oxygen (mg/L) in the water column above the shallow shelf at Devils Hole, Nevada, 2010. Thermo Orion 3Star Portable RDO datalogging meter recorded dissolved oxygen to ±0.1 mg/L-accuracy every 30 min. Dissolved oxygen/temperature optical probe was deployed above the substrate at approximately 26.5 cm depth. Data gaps represent missing data due to instrument failure. 98 Figure B6. Daily maximum light intensity (lux, y1-axis) and total daily light intensity (lux, y2-axis) at the water surface of the shallow shelf at Devils Hole, Nevada, 2010. A SPER 850008 Datalogging Light Meter recorded light every 15 min three to six days per month at coordinate point (0 m West, 4.1 m North) and approximately one meter above the water surface in the middle-east area of the shelf. 99 Figure B7. Mean monthly percent cover of benthic algae/cyanobacteria on the shallow shelf at Devils Hole, Nevada, 2010. Cover was surveyed once or twice monthly using a modified Braun-Blanquet/Daubenmire method (Braun–Blanquet 1932; Daubenmire 1959). 100 Figure B8. Spawning in Devils Hole pupfish (number of events per 5-min sample) as a function of dissolved oxygen (mg/L) on the shallow shelf at Devils Hole, Nevada, February–December 2010. Data was recorded on continuous daytime underwater video footage of the northwest area of the shelf. Thermo Orion 3Star Portable RDO datalogging meter recorded dissolved oxygen to accuracy ±0.1 mg/L every 30 min. Dissolved oxygen/temperature optical probe was deployed above the substrate at approximately 26.5 cm depth. 101 Figure B9. Spawning in Devils Hole pupfish (number of events per 5-min sample) as a function of loge-transformed total daily light intensity (daily sum of light [lux] readings) on the shallow shelf at Devils Hole, Nevada, February–December 2010. Corresponding untransformed light intensity values are shown in parentheses. Most spawning occurred during days with total light intensity 133,250–400,300 lux. Data was recorded on continuous daytime underwater video footage of the northwest area of the shelf. Light intensity was recorded every 15 min three to six days per month at coordinate point (0 m West, 4.1 m North) and approximately 1 m above the water surface in the middle-east area of the shelf. 102 Figure B10. Spawning in Devils Hole pupfish (number of events per 5-min sample) as a function of arcsine-transformed mean monthly proportion algal/cyanobacterial cover on the shallow shelf at Devils Hole, Nevada, February–December 2010. Corresponding untransformed percent cover values are stated in parentheses. Most spawning occurred during 24–60%, and especially 24–27% cover. Data was recorded on continuous daytime underwater video footage of the northwest area of the shallow shelf. Algal/cyanobacterial cover surveys were conducted once or twice monthly. 103 Figure B11. Spawning in Devils Hole pupfish (number of events per 5-min sample) as a function of x = dissolved oxygen (DO [mg/L]) and y = diel DO (daily max – min [mg/L]) on the shallow shelf at Devils Hole, Nevada, February–December 2010. DO was measured every 30 min; diel DO variation was calculated from daily maximum – minimum DO values. Data was recorded on continuous daytime underwater video footage of the northwest area of the shallow shelf. 104 Figure B12. Spawning in Devils Hole pupfish (number of events per 5-min sample) as a function of x = loge-transformed total daily light intensity (lux) and y = arcsinetransformed mean monthly percent cover filamentous algae/cyanobacteria on the shallow shelf at Devils Hole, Nevada, February–December 2010. Data was recorded on continuous daytime underwater video footage of the northwest area of the shelf. 105 Figure B13. Spawning in Devils Hole pupfish (number of events per 5-min sample) as a function of diel dissolved oxygen (DO) variation (max – min [mg/L]) 72 h after earthquakes and during no earthquake activity in Devils Hole, Nevada, February– December 2010. Data was recorded on continuous daytime underwater video footage of the northwest area of the shelf. 106 Figure B14. Mean spawning in Devils Hole pupfish (number of events per 5-min sample) ±1 SE 72 h before and after earthquake-induced seiches on the shallow shelf at Devils Hole, Nevada, 2010. Data was obtained from random sampling of continuous daytime underwater video footage of the northwest portion of the shelf. 107 Figure B15. Spatial differences in mean spawning in Devils Hole pupfish (number of events per 5-min survey) ±1 SE across the shallow shelf at Devils Hole, Nevada, January–December 2010. NE = northeast, NW = northwest, ME = middle-east, MW = middle-west, SE = south east, and SW = south west. Means with letters in common were not significantly different at the  = 0.05 level. 108 Figure B16. Spatial variation in spawning of Devils Hole pupfish across the shallow shelf at Devils Hole, Nevada. Visual surveys were conducted from just above the water surface three to six times per month, January–December 2010. 109 Figure B17. Mean percent substrate ±1 SE across the shallow shelf at Devils Hole, Nevada, 2010. NE = northeast, NW = northwest, ME = middle-east, MW = middle-west, SE = south east, and SW = south west. Substrate was surveyed using modified BraunBlanquet/Daubenmire method (Braun–Blanquet 1932; Daubenmire 1959) and characterized according to modified Wentworth classification of grain size (Cummins 1962). 110 Figure B18. Mean depth ±1 SE across the shallow shelf at Devils Hole, Nevada, 2010. NE = northeast, NW = northwest, ME = middle-east, MW = middle-west, SE = south east, and SW = south west. 111 Figure B19. 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