USGS Science at The Wildlife Society 2020 Conference

Table of Contents



Monday 9/28 Sessions 

Sagebrush-steppe landscapes have changed in fundamental ways over the past 100 years.
  • Sagebrush ecosystem (USGS image).

Anthropogenic Subsidies and Wildlife: The Good, the Bad, and the Unintended Consequences of Food and Shelter Subsidies for Wildlife 

Shawn O’Neil and others: Impacts of subsidized ravens on greater sage-grouse populations within sagebrush ecosystems of western North America. 


Long-Term Data Sets for Biodiversity Monitoring, Research, and Management 

John Sauer and others: Biometrics for Complex Long-Term Biodiversity Data Sets: Lessons from the Breeding Bird Survey 

John R. Sauer; William A. Link; James E. Hines–Most of our understanding of changes in avian biodiversity in North America is based on analysis of population change from the North American Breeding Bird Survey (BBS). The BBS provides data at spatial scales ranging from individual survey locations to continental, but analyses at all scales are complicated by the need to accommodate detectability issues during sampling and changes in sampling effort over space and time. Over the years of the survey, a variety of statistical methods have been used to estimate species richness and change in biodiversity from BBS data. In conjunction with studies funded by the United States Environmental Protection Agency, methods for estimating species richness based on capture-recapture heterogeneity models and focusing on local species integrity (i.e., estimating the proportion of a regional species pool that occurs at a site) were developed and used to address a variety of ecological hypotheses. In recent years, focus has shifted to estimating change in biodiversity through “State-of-the-Birds” composite estimates of population change of collections of species. These composite change metrics can be implemented at a variety of geographic scales and can be weighted by species-specific abundance data. Recently developed methods for estimating occupancy along BBS routes also offer alternative estimation procedures that avoid restrictive assumptions of heterogeneity models. These approaches to estimation of biodiversity change, in combination with ever-advancing abilities to fit complex models to BBS data, have made the BBS even more important as a fundamental source of avian data for biodiversity studies. 


Alexa McKerrow and others: USGS Foundational Data Supporting National Assessments 

Alexa J. McKerrow; Abigail L. Benson; Julie S. Prior-Magee; Elizabeth Martin; Annie Simpson; Daniel J. Wieferich–Science Analytics and Synthesis (SAS) Program’s Biodiversity Science activities focus on landscape-level understanding of terrestrial, aquatic, and marine species and ecosystems, through development, maintenance, and integration of a suite of synthesized data systems used to conduct biodiversity assessments at regional to national scales. Our biodiversity data are derived through our partnerships with regional, national, and international biodiversity organizations and are organized according to global standards. Key datasets supported by SAS include terrestrial vertebrate species habitat distribution and fish distribution models, the National Terrestrial Ecosystems Dataset, and the Protected Areas Database of the U.S. (PAD-US). These are central to national conservation assessments, including the National Gap Analysis Project (GAP) and the National Fish Habitat Assessment. In addition, SAS is the U.S. node and major hub of the Global Biodiversity Information Facility (GBIF) as well as for the Ocean Biogeographic Information System (OBIS). Finally, SAS is responsible for Biodiversity Serving Our Nation (BISON), a US-wide species mapping initiative to aggregate occurrence records for species distribution modeling, with an emphasis on species data collected by federal agencies, and invasive species and pollinator datasets. Here we will describe datasets developed by the SAS Program, the partnerships that support this work, and the results of recent national assessments. Specifically, we will describe the nearly 2000 terrestrial and aquatic species models, the breadth and depths of the PAD-US, the recent innovations in the GAP/LANDFIRE National Terrestrial Ecosystems Database, and current statistics about the species occurrence data found in GBIF, BISON, and the OBIS. USGS is well-known for development and maintenance of long-term datasets. Over the past few decades we have been able to expand these assets to include datasets central to improving our understanding of the biodiversity of the U.S. and the biotic components of the critical zone. 



Tuesday 9/29 Sessions 

Polar bear mother and two cubs on the Beaufort Sea ice.

Polar bear mother and two cubs on the Beaufort Sea ice.

(Credit: Steven Amstrup, USGS, Alaska Science Center. Public domain.)

Wildlife Health in a Changing Climate: Novel Stressors and Innovative Solutions 

Olivia LeDee: Climate Adaptation: Improving Wildlife Health Outcomes 

Olivia LeDee–Climate change impairs wildlife health, affecting reproduction, growth, and survival, and altering the trajectory of wildlife populations. Although climate change is a complex, heterogeneous threat, resource managers have and will continue to implement strategic interventions to reduce harm to wildlife populations. To increase their adaptive capacity, a surrogate for health, resource managers typically employ reserve design and habitat management strategies. Population and disease management are important, underutilized techniques to improve wildlife health outcomes under climate change. Moreover, empirical evidence for guidance and experimental approaches to such interventions are limited. This presentation will review the current landscape of climate adaptation for wildlife health, provide a checklist for optimal design of interventions, and outline conflicts between climate adaptation and wildlife disease management. 

OFFICE HOURS Wednesday 3 – 4 PM ET 

Tricia Fry and others: Assessing Polar Bear Health in a Changing Climate 

Tricia Fry; Todd Atwood; Colleen Duncan–Polar bears (Ursus maritimus) from Alaska’s southern Beaufort Sea have been sampled annually since 1984, with few exceptions. This effort has provided long-term data on polar bear demography, habitat use, diet and health. Findings from this long-term data set, in conjunction with relevant sea ice and climate data, afforded us the opportunity to explore how climate-mediated environmental stressors may be influencing polar bear health. Specifically, we discuss how the loss of sea ice habitat has modified bear behavior, resulting in biologic and physiologic cascades that may have adverse implications for population health. Our goal with this synthesis is to explore the opportunities and challenges to moving beyond the predominant conceptualization of wildlife health as the absence of disease to one that recognizes health is the outcome of complex interactions between individuals and their environments. We provide a framework for characterizing polar bear health through the interaction of biological, environmental, and social processes that can be used to provide meaningful measures of progress towards conservation goals and objectives. 

OFFICE HOURS Wednesday 3 – 4 PM ET 


Wednesday 9/30 Sessions 

Image: Sage Grouse

Male greater sage grouse in mating display on rocky ground in Modoc County. (Credit: Dave Menke, Fish and Wildlife Service. Public domain.)

Meta-What? Statistical Analysis in the Era of Big Data 

Rebecca Taylor and others: How we combined three quarters of a century of sage-grouse studies into a range-wide demographic meta-analysis 

Rebecca Taylor; Brett Walker; David Naugle–Sage-grouse demography has been studied since the 1930s in a multitude of locales across the species’ range, but most studies have been only a few years long. We conducted a meta-analysis to provide a comprehensive view of sage-grouse demography and broad-based recommendations to enhance population growth. We applied search criteria to obtain 108 demographic rate studies, and we used information from the 50 studies that met our inclusion criteria. When needed, we applied post hoc-corrections to make apparent rate estimates comparable to true rate estimates. We then described the distribution of each demographic rate over space and time with a mean and process variance estimated from a mixed effects model. These distributions allowed us to conduct a life-stage simulation analysis that identified which demographic rates had the largest per-unit effect on population growth and which explained the most variation in population growth. Both are critical because demographic rates that have the highest per-unit impact on population growth are often the rates that vary least in nature and may therefore be less susceptible to management actions. To maximize population growth, management should simultaneously target female survival, chick survival, and nest success. High spatio-temporal variation in demographic rates indicates that while findings from short-term studies are important, they should be viewed with caution because a rate may be low for a few years as a result of natural variation. Our comprehensive meta-analysis has facilitated conservation of mesic habitats within sagebrush landscapes where females raise chicks because we demonstrated the importance of chick survival to population growth. Finally, because our meta-analysis can include mechanistic linkages between a management action (e.g., pinyon juniper removal), a demographic rate (e.g., nest success), and population growth, it has inspired new research on sage-grouse habitat management. 

OFFICE HOURS Thursday 2-3 PM ET 


Robin Russell: Data Synthesis Techniques, Practical Applications in Wildlife: Notes from a Data Slayer 


Thursday 10/1 Sessions 

Spruce-covered mountains surround a dried-up lake.

Spruce-covered mountains surround a dried-up lake (Credit: Dustin Blakey. Public domain.)

The National Fish, Wildlife, and Plants Climate Adaptation Network? Advancing Understanding of Climate Change Impacts and Adaptation 

Laura Thompson: Can We See It Coming? Advances in Vulnerability Assessment for Wildlife 


The Rusty Blackbird- Recent Research to Fuel Conservation Strategies 

Jay Wright and others: A Full-Annual Cycle Model to Understand Factors Limiting Rusty Blackbird Populations in Eastern versus Western Flyways 

Clark S. Rushing; Luke L. Powell; Steven M. Matsuoka–The Rusty Blackbird has lost 90% of its global population since 1970 and is projected to lose another 50% in the next 19 years. Since 2005, researchers with the International Rusty Blackbird Working Group (Working Group, have collaborated on a variety of breeding and wintering studies to understand the species’ resource requirements and limiting factors. This collective effort has filled major information gaps on Rusty Blackbird ecology and natural history requirements; however, identifying the causes of its steep decline has remained elusive. In this study we used an integrated population model (IPM) to (1) assess the past contributions of fecundity and age-specific seasonal survival probabilities to Rusty Blackbird population growth in eastern versus western flyway populations of Rusty Blackbirds and (2) project future patterns in population growth in each flyway over a 20-year period under scenarios of current vital rates and realistic increases in vital rates. We analyzed a combination of breeding and winter data on Rusty Blackbirds collected from standardized surveys of abundance (Breeding Bird Survey and Christmas Bird Count) and demographic studies (mark-resighting, summer and winter telemetry, and nest monitoring) conducted by Working Group members from 2005-2015. We used the IPM to estimate past population growth, vital rates (fecundity, age-specific seasonal survival), and the contributions of vital rates to population growth in western versus eastern flyways, the former linking breeding and wintering data between Alaska and Mississippi, the latter New England and South Carolina/Georgia. We then used the IPM to project future annual population growth over 20 years into the future under scenarios where recent rates of fecundity and age-specific seasonal survival were continued versus proportionally increased in the future. We present our preliminary findings on the key vital rates influencing past declines and the magnitude vital rates must be increased to recover populations. 



Sarah Sonsthagen and others: Genes on the Landscape: Population Genomics of Rusty Blackbirds 

Sarah Sonsthagen; Robert Wilson; Luke Powell; Steven Matsuoka; James Johnson; Dean Demarest–Spatial organization of suitable habitat across the landscape plays an important part in how populations maintain genomic (i.e. movement of genes) and landscape (i.e. ability of an individual to move across the landscape) connectivity. Here we analyzed reduced representation genomic (ddRAD) and mitochondrial (mt) DNA sequence data from rusty blackbirds (n=205) sampled across their breeding distribution to assess genomic connectivity and identify markers that may be useful to evaluate migratory connectivity. Spatial genomic structure was analyzed using methods that reflect different temporal scales: 1) principal components analysis to identify major trends in the distribution of genomic variation; 2) maximum likelihood clustering analyses to test for the presence of multiple genomic groupings; 3) shared co-ancestry analyses to assess contemporary relationships; and 4) effective migration surfaces to identify regions that deviate from a null model of isolation by distance. Rusty blackbirds are structured across locales (pairwise mtDNA Ф<sub>ST</sub>=-0.046-0.677; ddRAD Ф<sub>ST</sub>=0.002-0.082) with strong demographic breaks between eastern (Newfoundland and New England/Canadian Maritimes) and other sites in Canada and Alaska. The following sampled locales clustered together: 1) southcentral and interior Alaska (with subtle structure detected for southcentral sites), 2) central Canada (Alberta and Manitoba), 3) Ontario, 4) New England and Canadian Maritimes, and 5) Newfoundland. We identified loci (n=1880) with elevated levels of genomic structure (Ф<sub>ST</sub>>0.1) that will be useful in assigning non-breeding individuals to putative breeding regions to elucidate migratory connectivity. Patterns of genetic structure were concordant across marker types indicating that dispersal tendencies are likely similar between sexes. Observed genomic structure across the breeding distribution indicates that effective dispersal is restricted. Evaluating migratory connectivity will provide insight on whether geographic partitioning in the genomic structure is attributable to behavioral or physical barriers to dispersal, and aid full annual cycle conservation efforts targeting this declining species. 



Friday 10/2 Workshop 

Group of Pacific walruses resting on beach, Alaska

Pacific walruses resting on the beach of the eastern shore of the Chukchi Sea (Credit: Elizabeth Powers, U.S. Geological Survey. Public domain.).

Fundamentals of Structured Decision Making 

Organizers: Michael Runge, Sarah Converse, James Lyonns, Katrina Alger, Sarah Nells, and Ashley Fortune Isham 


Contributed Oral Presentations (On-Demand) 

Human Dimensions 

Rebecca Taylor and others: Propensity Score Matching for Confounded Data: Help for Detecting a Human Impact on Wildlife 

Rebecca L. Taylor; Chadwick V. Jay; William S. Beatty; Anthony S. Fischbach–We introduce propensity score-based matching methods as a technique to account for confounded data when estimating a single human impact on a wildlife population. We use potential effect of ships on walrus behavior as a concrete example, where concern is that ship exposure may cause walruses to spend more time swimming and less time foraging or resting. Walrus exposure to ships is confounded by environmental covariates which may influence apparent ship effects. For example, walruses are ~20% more likely to be ship-exposed when resting on land instead of ice, and their response to disturbance may differ between substrates. Propensity score-based matching methods can help overcome such confounding because interest lies in the effect of the single “treatment” variable, ship exposure, and environmental covariates simply create nuisance effects. A propensity score model is a type of treatment model that determines the propensity for a unit to be treated based on confounding covariates. This equates to regressing confounders (environmental covariates) on the treatment (ship exposure) rather than the outcome (walrus behavior). The propensity score is thus the probability a walrus falls into the ship-exposed category based on the confounders. Walruses are then matched to each other based on their propensity to be ship-exposed. If matching is ideal, the exposure effect is simply the difference between behavior of ship-exposed walruses and unexposed walruses. If matching is less than ideal, a standard outcome model (a regression of ship exposure and environmental covariates on walrus behavior) is applied to the matched data to further reduce bias in the estimated effect. We compare estimates of the ship exposure effect from propensity score-based matching, outcome modeling, and the two methods combined. Propensity score-based matching methods apply to other human impact to wildlife studies where interest lies in isolating the human impact. 



Herpetofauna I 

Abby Lawson and others: Accounting for Multiple Uncertainties to Evaluate Population Viability of the Alligator Snapping Turtle for the Species Status Assessment 


GIS & Remote Sensing 

Josephine Horton and others: Continuous Monitoring of the United States Using All Available Landsat Data, the Release of the U.S. Geological Survey’s Next Generation Products: LCMAP 

Josephine Horton; Christopher Barber; Ryan Reker; Jesslyn Brown; George Xian; Roger Auch–The U.S. Geological Survey (USGS) has implemented a new approach to mapping and monitoring national land cover as part of the Land Change Monitoring, Assessment, and Projection (LCMAP) initiative. This new approach leverages technological advances in computing, the application of state-of-the-art time series algorithms, and the organization of the U.S. Landsat archive into tiled Analysis Ready Data (ARD). Through this approach, LCMAP can provide information on land cover and land change with greater efficiency, frequency, and consistency than previously possible. The LCMAP implementation of the Continuous Change Detection and Classification (CCDC) algorithm analyzes all available clear Landsat observations on a per-pixel basis to develop harmonic time series models. Attributes of these time series models are used as inputs to classify land cover and produce a suite of ten annual land cover and land surface change products for a 33-year record (1985 through 2017) across the conterminous United States. These products can be utilized by the wildlife and natural resources communities to assist in various conservation and management projects. The time series approach enables the monitoring of annual land cover class conversions and detection of disturbances, including more subtle conditional landscape changes, while also mitigating typical challenges associated with land cover mapping efforts such as cloud cover or phenological cycles. A separate collection of 25,000 validation sites across the United States was utilized to provide quantitative measures of accuracy and consistency of the LCMAP land cover and change products. Collectively, LCMAP enables the USGS to better support the land change science community’s need for more frequent land cover information and provides a new science foundation for decisions, assessments, and projections. This presentation will introduce the LCMAP initiative, Version 1 products, and highlight applications of the products for land change assessments and land cover projections. 



Wind Energy Impacts on Wildlife 

Group of Pronghorn stand in Wyoming

(Credit: Tom Koerner, FWS. )

Megan Milligan and others: Effects of Wind Energy Development on Pronghorn Habitat Selection 

Megan C. Milligan; Aaron N. Johnston; Jeffrey L. Beck; Kurt T. Smith; Kaitlyn L. Taylor; Embere Hall; Lee Knox; Teal Cufaude; Cody Wallace; Geneva Chong; Matthew J. Kauffman–In the face of climate change, wind energy represents an important alternative to high and increasing energy demands, but it has been criticized for disrupting wildlife populations. While bird and bat fatalities due to collisions are the most visible and measurable negative impact of wind energy development, little is known about the effects on other terrestrial species, including large ungulates. Behavioral adjustments, such as altered habitat selection, are a primary way that long-lived species cope with novel disturbances. We evaluated effects of wind energy development on pronghorn (Antilocapra americana) space use and habitat selection. Using data from GPS-collared female pronghorn in the Shirley Basin of south-central Wyoming, USA, we tested four hypothetical effects of wind turbines on pronghorn summer and winter space use: 1) displacement away from wind turbines, 2) expansion of home ranges, 3) avoidance behavior within home ranges, or 4) sustained avoidance behavior within home ranges. We monitored 156 individuals over 4 summers (2010, 2011, 2018 and 2019) and 225 individuals over 5 winters (2010, 2010/11, 2011/12, 2018/19 and 2019/20) and used resource selection functions to evaluate selection relative to turbines after controlling for other habitat factors, such as snow depth. We found that in most years pronghorn were not displaced after turbine construction and that turbines were not related to an expansion of home ranges, although the effect of turbines on both habitat selection and size of winter home ranges varied by year. Within home ranges, we found that some pronghorn avoided wind turbines whereas others selected habitat closer to turbines, and selection for both turbines and other habitat variables was highly variable, which translated to no population-level patterns in either season. Highly variable habitat selection and movement of pronghorn, both among individuals and across years, may make effects of wind-energy development difficult to detect. 



Game Bird – Ecology and Management 

Robert Wilson and others: Comparative Genomic Structure Within Alaskan Galliforms 

Robert Wilson; Sarah Sonsthagen; Sandra Talbot–In Alaska, resident avian species such as ptarmigan and grouse possess unique ecological traits and likely corresponding genomic variation, allowing them to thrive year-round in Arctic and sub-Arctic ecosystems. Specialization to synergistic effects of thermal and day-light regimes typified by the Arctic may have resulted in narrow response windows in resident species, potentially rendering them more (or differentially) impacted than migratory species to environmental change. We collected reduced representation genomic (ddRAD) data for ptarmigan (rock, willow, white-tailed) and grouse species (spruce, ruff, and sharp-tailed) sampled along a latitudinal gradient (60-70°N) within Alaska. Our goals were to examine levels of genomic diversity and gene flow, and simultaneously identify loci in that may signal local adaptation to Arctic environments. Genomic diversity within Alaskan galliforms is arrayed differentially: weak to no genetic structure in rock ptarmigan (Φ<sub>ST</sub> = 0.012; 0.009 within subspecies) and sharp-tailed grouse (Φ<sub>ST</sub> = 0.012); isolation by distance in willow (Φ<sub>ST</sub> = 0.023) and white-tailed (Φ<sub>ST</sub> = 0.021) ptarmigan; and northern and southern clusters in spruce (Φ<sub>ST</sub> = 0.036) and ruff (Φ<sub>ST</sub> = 0.042) grouse. Patterns of genomic diversity coincide with physiogeographic features (e.g., mountain ranges) and highlight the importance of these environmental and ecological barriers shaping how genomic diversity is arrayed across the landscape. Lack of concordance in spatial patterns of genetic variation among certain species, and the presence of species-specific patterns, however, indicate that species behavior (movement, breeding, etc.) and habitat affinities still play key roles in driving the contrasting patterns of genomic structure among Alaska gallids. These findings highlight the importance of considering disparities in species’ life history traits when evaluating the influence of topographic features on the distribution of genomic diversity across the landscape in comparative analyses. 



Herpetofauna III 

David Pilliod and others: Saving the Last Frogs in the Desert: Ecohydrological Complexity of Drought Mitigation 

David S. Pilliod; Mark B. Hausner; Rick D. Scherer–Droughts that are so severe or long that they tip ecological systems beyond their natural range of variability are increasingly common as a result of climate change. Drought mitigation actions often attempt to alter the ecohydrology of a site. The objectives of this study were to examine the effectiveness of drought mitigation actions that aimed to reduce stream incision, increase surface water, improve riparian habitat, and increase populations of the Columbia spotted frog (Rana luteiventris) that had declined precipitously during multiple drought cycles in a semi-arid valley in central Nevada, USA. We assessed drought and mitigation responses using the Standardized Precipitation Evapotranspiration Index (SPEI) and Normalized Difference Vegetation Index (NDVI) derived from a 30-year time series of satellite imagery and gridded weather data. We then used a before-after analysis of a 23-year mark-recapture dataset to evaluate the effects of drought mitigation on the probability of survival and recruitment rates in frog populations. Preliminary results suggest that drought, as measured by SPEI in the summer, was detectable in our study meadows using NDVI as a response variable. Then, after accounting for interannual variation in precipitation, we found that NDVI increased significantly from before to after drought mitigation actions indicating that the management actions influenced the hydrology and vegetation of the meadows. Frog survival generally increased with NDVI, but habitat manipulation had an even stronger effect than NDVI where new ponds were excavated. Frog recruitment rates increased in years with higher NDVI, but responses to mitigation actions were more variable. We conclude that it is possible to mitigate some of negative effects of ecological drought through habitat manipulation, but also illustrate the ecohydrological complexity of drought mitigation given the inherent spatial and temporal variability in ecological systems. 



Ecology and Conservation of Bears 

Todd Atwood and Anthony Pagano: Integrating Old and New Technologies to Investigate Polar Bear Energetics 

Todd Atwood; Anthony Pagano–Since the late 1950’s, transmitter tags have been an important tool for understanding wildlife spatial ecology. Advances in tag technology, like the launching of the Argos satellite system in the 1970’s and development of the global positioning system (GPS) in the 1990’s, have made the collection of data more efficient while also improving the precision of point locations. Recent technological advances provide opportunities to create accessorized tags that allow for the simultaneous collection of spatial and behavioral data that, when integrated with other data, allow biologists to develop a more nuanced understanding of how animals interact with their environment. Here, we discuss the development and application of a tag and sensor platform to investigate the behavioral and physiological responses of polar bears (Ursus maritimus) to changes in sea ice habitat. We used GPS satellite collars with tri-axial accelerometers, conductivity sensors, and video cameras to measure the location, behavior, and energy expenditure of adult female polar bears from Alaska’s southern Beaufort Sea. We calibrated accelerometer and conductivity data collected from collars with behaviors observed from video-recorded captive polar bears and with video from camera collars deployed on free-ranging polar bears on sea ice and on land. Analyses suggested a strong ability to discriminate common polar bear behaviors using a combination of accelerometer and conductivity sensor data. This approach provides a method to quantify polar bear behavior and energetics in order to evaluate the impacts of further declines in Arctic sea ice. 



Posters (On-Demand) 


Research and Teaching Opportunities with a Large-Scale Salamander Collaboration Network (SPARCnet) 

Kristine L. Grayson; Caitlin Fisher-Reid; Louise Mead; Hannah Coovert; Raisa Hernández Pacheco; Jennifer Sevin; Sean Sterrett; Chris Sutherland; David Muñoz; David Miller; Evan Grant–Understanding wildlife responses to climate change has never been more urgent. For species with wide geographic ranges, there can be substantial variation in population processes and the effects from environmental change. Terrestrial salamanders in the genus Plethodon are often used in ecological studies as a key component of forest ecosystems, where lungless respiration through their skin and high abundance serves as a commonly used indicator of forest health. The eastern red-backed salamander (P. cinereus) is the most widespread and commonly studied species, yet most studies focus on local population dynamics. Understanding larger scale spatiotemporal patterns in population dynamics in relation to climate requires expanding beyond studies at single institutions. The Salamander Population and Adaptation Research Collaboration Network (SPARCnet) was founded in 2013 by researchers at Pennsylvania State University and the USGS Northeast Amphibian and Research Monitoring Initiative (NEARMI). It has since grown to include collaborators at 19 institutions and 8 education organizations. SPARCnet aims to provide a consistent framework for understanding population trends in P. cinereus, while delivering education opportunities for students. Researchers, educators, and citizen scientists apply the same cover-board plot study design and sampling methods across the range of the salamander in eastern and north-central North America. Most participants mark the salamanders they find, and thus have long-term spatial-capture-recapture data, along with basic population demographic data. Educators at these institutions are also developing course-based research modules available as open education resources for collaborative teaching. This network serves as an important model for bringing field research to students and building robust population data for species with wide geographic ranges. 

OFFICE HOURS: Wednesday 12-12:30 PM and 4-4:40 PM ET 

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