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Factors affecting the recovery of Mexican wolves in the Southwest United States

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Mendeley Data2024-05-15 更新2024-06-27 收录
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https://datadryad.org/stash/dataset/doi:10.5061/dryad.2280gb5z8
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# Factors affecting the recovery of Mexican wolves in the Southwest United States --- The data provided are on Mexican Wolves (*Canis lupus baileyi*) from 1998–2019 in Arizona and New Mexico, USA following the reintroduction in 1998. The data are from annual monitoring efforts of the population. ## Description of the data and file structure The data are provided in a .csv format and include a table with a row for each year in the study (1998-2019) and 9 columns. The columns are: * Year = the year for which the data apply * Population = the population count based on end-of-year surveys * Pup recruitment = a count of the number of pups recruited into the population based on surveys * Captive release = the number of animals that were captively reared that were released into the population * Translocation = the number of animals that had previously been removed during management removal events that were translocated and released into the population in a given year * Illegal killing = the number of known illegal killing events * Other mortality = the number of natural deaths, vehicle deaths, and other legal killing deaths not accounted for in other mortality sources in a given year * Unknown mortality = the number of wolves with known deaths from unknown causes * Management removal = the number of wolves that were removed by management either to later be translocated (could be in the same year or in later years) or that were permanently removed from the population ## Sharing/Access information Data was derived from the following source: * [https://www.fws.gov/media/mexican-wolf-2019-annual-progress-report](https://www.fws.gov/media/mexican-wolf-2019-annual-progress-report) ## Code/Software These data were analyzed for the manuscript Breck et al. entitled "Factors affecting recovery of Mexican wolves in southwestern USA". The analyses were conducted in program R (version 4.2.2) using a custom coded Bayesian hierarchical model. The code is available through Zenodo: [https://doi.org/10.5281/zenodo.8140794](https://doi.org/10.5281/zenodo.8140794)
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2023-07-26
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