This dataset contains data from an ongoing trapping effort beginning in 2019 targeting alligator snapping turtles (Macrochelys temminckii) in the Atchafalaya Basin of south-central Louisiana.

This dataset contains initial data from head-started alligator snapping turtles released by Louisiana Department of Wildlife and Fisheries (LDWF) from November 2015 to October 2016. In addition, it contains data from a five-day trapping effort at each of seven release sites by the United States Geological Survey (USGS) from late June to early October 2018. Trapping was completed using hoop nets of three sizes. We recaptured eight head-started alligator snapping turtles as well as four individuals native to the creek.

This dataset includes results from an ongoing annual trapping effort targeting aquatic turtles at two urban ponds in Lafayette, Louisiana. This project began in 2009 and consists of five days of active and passive trapping each May. This project is ongoing with plans to continue in May of 2025.

This dataset includes results from an ongoing annual trapping effort targeting aquatic turtles at two urban ponds in Lafayette, Louisiana. This project began in 2009 and consists of five days of active and passive trapping each May. This project is ongoing with plans to continue in May of 2025.

These data represent the results of trapping efforts for native northwestern pond turtles (Actinemys marmorata) and non-native red-eared sliders (Trachemys scripta elegans) in wetlands and irrigation canals in agricultural regions of the Sacramento Valley in 2018 and the Sacramento-San Joaquin River Delta in 2019. In addition to detection data for these two turtle species, the dataset includes habitat data from each trapped site and data on the capture rate of fish, frogs, and tadpoles at each site.

The American alligator (Alligator mississippiensis) is a species of ecological and economic importance in the southeastern United States. Within South Carolina, alligators are subject to private and public harvest programs, as well as nuisance removal. These management activities can have different impacts across alligator size classes that may not be apparent through widely-used monitoring techniques such as nightlight surveys. We synthesized multiple datasets within an integrated population model (IPM) to estimate size class-specific survival and abundance estimates, that would not be estimable through separate, non-integrated modeling frameworks. The IPM framework included a multistate mark-recapture-recovery model that used mark-recapture-recovery data from the Tom Yawkey Wildlife Center and growth transition probabilities that were estimated outside of the IPM framework. The IPM also included a state-space count model, which used nightlight survey counts of alligtaors from two survey routes: 1) Great Pee Dee and Waccamaw Rivers; and 2) South Santee Rivers. The IPM modeling framework also used mean clutch size data from the Tom Yawkey Wildlife Center and public and private harvest data within the state model. Lastly, we evaluated the effects of capture effort on capture probability, as well as the effects of water temperature and relative water level on count detection probability, and provide all covariate datasets. Our IPM framework determined that size class-specific survival rates were relatively high for all non-hatchling size classes, and abundance trends differed between the two nightlight survey sites.

This dataset includes processed satellite tracking data collected from green turtles between July 2002 and October 2020 in the Gulf of Mexico. Tracks were located along the west coast of Florida from the Florida Keys to the Gulf Islands National Seashore. Output from the state-space model (SSM) described in Lamont et al. (2023) is included, as are inter-nesting and foraging centroids calculated using kernel density estimates and minimum convex polygons.

This dataset contains all input parameters required to perform integrated step selection analysis (iSSA) to quantify marine turtle habitat selection relative to marine protected areas throughout coastal Florida and the Gulf of Mexico. The iSSA is a flexible approach to compare the environmental attributes of observed steps (the linear segment connecting two consecutive observed positions of an animal) against a group of alternative steps taken from the same starting location. Information contained in the dataset includes original PIT (passively induced transponder, a unique identifier for each turtle), step ID, step length and log of the step length, turning angle and cosine of turning angle, start and end date time of each step, protected status of location of each step ID (unprotected, multi-use or no-take, water depth (in meters), and chlorophyll concentration (in mg/m3).

These data are from joint visual encounter and environmental DNA (eDNA) surveys conducted for northwestern pond turtles (Actinemys marmorata) in streams on privately-owned timberlands in northern California.

This data set contains sensitive biological resource data for reptiles and amphibians in coastal Louisiana. Vector polygons represent reptile and amphibian habitats, with nest density values by habitat zone and parish or management unit. Species-specific abundance, seasonality, status, life history, and source information are stored in relational data tables (described below) designed to be used in conjunction with this spatial data layer.This data set comprises a portion of the Environmental Sensitivity Index (ESI) data for Louisiana. ESI data characterize the marine and coastal environments and wildlife by their sensitivity to spilled oil. The ESI data include information for three main components: shoreline habitats, sensitive biological resources, and human-use resources.