Data and R Code for manuscript titled "Population Dynamics and Harvest Management of Eastern Mallards"

Body mass in overwintering waterfowl is an important fitness attribute as it affects winter survival, timing of spring migration, and subsequent reproductive success. Recent research in Europe and the western United States indicates body mass of mallards (Anas platyrhynchos) has increased from the late 1960s to early 2000s. The underlying mechanism is currently unknown; however, researchers hypothesize that increases are due to a more benign winter climate, increased food availability through natural and artificial flooding, introgression of wild mallard populations by game-farm mallards, or shifting of wintering distributions northward. Further investigation of factors related to winter mallard body mass increases and whether this phenomenon is occurring in other major flyways could increase understanding of intrinsic and extrinsic variables influencing waterfowl fitness. We collected and analyzed mallard body mass data in the Lower Mississippi Alluvial Valley from 1979 to 2021 to determine sources of temporal variation. We measured hunter-harvested mallards from private hunting clubs, public hunting areas, and duck-plucking businesses. Mallard body mass increased by approximately 6% among all age-sex classes from 1979 to 2021. We also compiled weather data (rainfall [cm], weather severity index information [WSI], river gage discharge [cfs] and height [m]) to relate to mallard body mass measurements.

Body mass in overwintering waterfowl is an important fitness attribute as it affects winter survival, timing of spring migration, and subsequent reproductive success. Recent research in Europe and the western United States indicates body mass of mallards (Anas platyrhynchos) has increased from the late 1960s to early 2000s. The underlying mechanism is currently unknown; however, researchers hypothesize that increases are due to a more benign winter climate, increased food availability through natural and artificial flooding, introgression of wild mallard populations by game-farm mallards, or shifting of wintering distributions northward. Further investigation of factors related to winter mallard body mass increases and whether this phenomenon is occurring in other major flyways could increase understanding of intrinsic and extrinsic variables influencing waterfowl fitness. We collected and analyzed mallard body mass data in the Lower Mississippi Alluvial Valley from 1979 to 2021 to determine sources of temporal variation. We measured hunter-harvested mallards from private hunting clubs, public hunting areas, and duck-plucking businesses. Mallard body mass increased by approximately 6% among all age-sex classes from 1979 to 2021. We also compiled weather data (rainfall [cm], weather severity index information [WSI], river gage discharge [cfs] and height [m]) to relate to mallard body mass measurements.

The datasets used in the creation of the predicted Habitat Suitability models includes the CWHR range maps of Californias regularly-occurring vertebrates which were digitized as GIS layers to support the predictions of the CWHR System software. These vector datasets of CWHR range maps are one component of California Wildlife Habitat Relationships (CWHR), a comprehensive information system and predictive model for Californias wildlife. The CWHR System was developed to support habitat conservation and management, land use planning, impact assessment, education, and research involving terrestrial vertebrates in California. CWHR contains information on life history, management status, geographic distribution, and habitat relationships for wildlife species known to occur regularly in California. Range maps represent the maximum, current geographic extent of each species within California. They were originally delineated at a scale of 1:5,000,000 by species-level experts and have gradually been revised at a scale of 1:1,000,000. For more information about CWHR, visit the CWHR webpage (https://www.wildlife.ca.gov/Data/CWHR). The webpage provides links to download CWHR data and user documents such as a look up table of available range maps including species code, species name, and range map revision history; a full set of CWHR GIS data; .pdf files of each range map or species life history accounts; and a User Guide.The models also used the CALFIRE-FRAP compiled "best available" land cover data known as Fveg. This compilation dataset was created as a single data layer, to support the various analyses required for the Forest and Rangeland Assessment, a legislatively mandated function. These data are being updated to support on-going analyses and to prepare for the next FRAP assessment in 2015. An accurate depiction of the spatial distribution of habitat types within California is required for a variety of legislatively-mandated government functions. The California Department of Forestry and Fire Protections CALFIRE Fire and Resource Assessment Program (FRAP), in cooperation with California Department of Fish and Wildlife VegCamp program and extensive use of USDA Forest Service Region 5 Remote Sensing Laboratory (RSL) data, has compiled the "best available" land cover data available for California into a single comprehensive statewide data set. The data span a period from approximately 1990 to 2014. Typically the most current, detailed and consistent data were collected for various regions of the state. Decision rules were developed that controlled which layers were given priority in areas of overlap. Cross-walks were used to compile the various sources into the common classification scheme, the California Wildlife Habitat Relationships (CWHR) system.CWHR range data was used together with the FVEG vegetation maps and CWHR habitat suitability ranks to create Predicted Habitat Suitability maps for species. The Predicted Habitat Suitability maps show the mean habitat suitability score for the species, as defined in CWHR. CWHR defines habitat suitability as NO SUITABILITY (0), LOW (0.33), MEDIUM (0.66), or HIGH (1) for reproduction, cover, and feeding for each species in each habitat stage (habitat type, size, and density combination). The mean is the average of the reproduction, cover, and feeding scores, and can be interpreted as LOW (less than 0.34), MEDIUM (0.34-0.66), and HIGH (greater than 0.66) suitability. Note that habitat suitability ranks were developed based on habitat patch sizes >40 acres in size, and are best interpreted for habitat patches >200 acres in size. The CWHR Predicted Habitat Suitability rasters are named according to the 4 digit alpha-numeric species CWHR ID code. The CWHR Species Lookup Table contains a record for each species including its CWHR ID, scientific name, common name, and range map revision history (available for download at https://www.wildlife.ca.gov/Data/CWHR).

This U.S. Geological Survey (USGS) data release represents tabular and geospatial data for the creation and application of a Bayesian network model that predicts Black Skimmer (Rynchops niger) and Gull-billed Tern (Gelochelidon nilotica) on bare ground sites across the U.S. portion of the Gulf of Mexico. Management plans with clear priorities can help to achieve Black Skimmer and Gull-billed Tern population targets (number of breeding pairs) because conservation and restoration opportunities can be limited and costly. These species form breeding colonies on bare ground sites, where the number of breeding pairs may be influenced by numerous site conditions such as site area, soil texture, and topography; island area, shrub area, and elevation; predators, and human disturbances. These data were used to develop a Bayesian network model that uses site conditions to predict Black Skimmer and Gull-billed Tern nest counts as a proxy for breeding pairs. We used the model and 2005-2015 bird survey data to estimate total nests and nest deficits for Gulf Coast Joint Venture Initiative Areas (IA) under existing conditions and simulated scenarios that presumed managers changed site conditions. We selected a best scenario for each IA based on its ability to simultaneously achieve both species targets for the least perceived effort. We used the best scenario to prioritize sites for management until the simulations suggested both species targets might be met. We then repeated the simulations while excluding sites that had attributes that limited their management application.

This U.S. Geological Survey (USGS) data release represents tabular and geospatial data for the creation and application of a Bayesian network model that predicts Black Skimmer (Rynchops niger) and Gull-billed Tern (Gelochelidon nilotica) on bare ground sites across the U.S. portion of the Gulf of Mexico. Management plans with clear priorities can help to achieve Black Skimmer and Gull-billed Tern population targets (number of breeding pairs) because conservation and restoration opportunities can be limited and costly. These species form breeding colonies on bare ground sites, where the number of breeding pairs may be influenced by numerous site conditions such as site area, soil texture, and topography; island area, shrub area, and elevation; predators, and human disturbances. These data were used to develop a Bayesian network model that uses site conditions to predict Black Skimmer and Gull-billed Tern nest counts as a proxy for breeding pairs. We used the model and 2005-2015 bird survey data to estimate total nests and nest deficits for Gulf Coast Joint Venture Initiative Areas (IA) under existing conditions and simulated scenarios that presumed managers changed site conditions. We selected a best scenario for each IA based on its ability to simultaneously achieve both species targets for the least perceived effort. We used the best scenario to prioritize sites for management until the simulations suggested both species targets might be met. We then repeated the simulations while excluding sites that had attributes that limited their management application.

These data and code were collected to support the development of a modeling framework that integrates local daily weather conditions and land cover with individual energetics and morphology to simulate mallard (Anas platyrhynchos) and northern pintail (Anas acuta) migration across the Northern Hemisphere.The simulated birds move across a discretized landscape of 20 by 20 mile nodes. Provided data and code allow for a model to simulate avian migration from September 1st, 2019, through December 31st, 2020. There are 6 zip files included in this data release. 1. MigrationModel_2023.zip contains the model code used to simulate bird movement. It requires the files NodeSpecificData_2019.txt and ENV_MAT.csv to function. 2. NodeSpecificData_2019.zip contains static landscape information for the terrestrial Northern Hemisphere. For each node, the file has information regarding land cover types and areas, forage quality and availability, and capability as breeding range. 3. ENV_MAT.zip contains daily averages for temperature, weather severity index, air density, snow depth, windspeed, and wind direction for each node throughout the study period. 4. mallardtelemetrydata.zip contains satellite telemetry data for mallards that were tagged in Louisiana in the winter of 2019/2020. These data were used to validate the model by comparing to simulated mallard movement. 5. N_ABUND_ALL.zip contains example output from the migration model. It has expected abundance of mallards and pintails in each node on each day of simulation. 6. BCTable_full.zip contains simulated predictions for the distribution of excess energy availability (represented as body condition) across all mallards and pintails in the Northern Hemisphere on each day of simulation.

These data are in two tables relating to fall age ratios (number of juvenile birds : total birds aged) of Black Brant (Branta bernicla nigricans) staging in Izembek Lagoon, Alaska, since 1963. The first table is observation data for the age classes of Black Brant during surveys, and associated survey characteristics. The second table contains model-based estimates of age ratios by year along with Standard Error (SE), and 95% Bayesian credible intervals around estimates.

These data are in two tables relating to fall age ratios (number of juvenile birds : total birds aged) of Black Brant (Branta bernicla nigricans) staging in Izembek Lagoon, Alaska, since 1963. The first table is observation data for the age classes of Black Brant during surveys, and associated survey characteristics. The second table contains model-based estimates of age ratios by year along with Standard Error (SE), and 95% Bayesian credible intervals around estimates.

This dataset consists of three tables relating to (1) detections of adult McKay's Buntings from line transect with distance estimation surveys on St. Matthew and Hall islands in Alaska between May 30 and June 29, 2003 and June 6 and 11, 2018, (2) environmental covariates associated with detections of adult McKay's Buntings in less than or equal to 250-m long contiguous transect segments, and (3) environmental covariates used to predict McKay's Bunting population size in less than or equal to 300 x 300-m pixels across the study area in each year, and to estimate population change between years.