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  • Dataset
    Climate Change as a Wildlife Health Threat: A Scoping Review
    (2024-10-17) Greening, Sabrina; Pascarosa, Lucie; Munster, Avery; Gagne, Roderick; Ellis, Julie
    Background: The definition of wildlife health continues to expand with the recognition that health is more than the absence of disease. As climate-associated impacts on wildlife health become inevitable, it is increasingly important to integrate concepts such as vulnerability, adaption, and resilience into wildlife health research, surveillance, and management actions. Here, we performed a scoping review to identify literature from 2008 onwards with a focus on climate change impacts on wildlife health. The literature fed into an AI-based thematic analysis which was used to describe the scope and depth of existing literature and identify key themes and knowledge gaps that are important to consider in future wildlife health frameworks. The themes identified in the analysis were then manually reviewed and refined by interpreting them in context. Results: In total, 2,249 citations were retrieved from the literature search. After applying a set of inclusion/exclusion criteria, a total of 372 papers were retrieved and split into one of two groups: 1) papers focusing on climate-associated impacts on wildlife health and 2) papers focusing on climate-associated impacts on vector distribution. Thematic analyses were performed separately on each group although results from both groups identified aspects of the host as a top theme including immunological response, physiological stress response, and body size for group one and host population density, host-vector-pathogen interactions, and the importance of reservoir host species for group 2. Conclusions: A large number of the papers retrieved in the literature search focused on how climate change impacts the distribution and abundance of host, vector, and pathogen species, remaining disease-centric in their approach. Themes related to potential management actions, with the exception of vector control, were found across only a limited number of papers reflecting some uncertainty on how best to respond and prepare for climate change as a threat to wildlife health.
  • Dataset
    Slaves in Bucks County, Pennsylvania
    (2024) Wright, Robert E.
    The Bucks County Register of Slaves includes the name, occupation, and township of enslavers as well as the name, gender, and age of persons enslaved in Bucks County, Pennsylvania, in the late eighteenth and early nineteenth centuries. Manumission dates, racial status, and other notes are also noted for some of the slaves. This dataset is a part of the Magazine of American Datasets (MEAD). To view more of the collection, visit https://repository.upenn.edu/exhibits/orgunit/mead.
  • Dataset
    Holland Land Company Deed Tables
    (2024-04-01) Krischer, Elana; Nattrass, Christopher; Rockwell, Sara; Ryan, Jacob
    This dataset is a transcription of the Deed Tables from the Holland Land Company Deed Books held at the New York State Archives. The Holland Land Company was a consortium of Dutch Bankers who purchased the preemption right to lands west of the Genesee River in New York from land speculator Robert Morris. The Holland Land Company then extinguished Seneca title to much of the land at the 1797 Treaty of Big Tree, surveyed townships and Seneca reservations between 1798 and 1800, and then sold the land to settlers beginning in 1802. The deeds listed in these tables include land sales between 1802 and 1833. Fields include names of purchasers, month of purchase, day of purchase, year of purchase, township, range, number of acres sold, and purchase money. The original records include the number of the deed that links the purchases to corresponding records as well as the individual lot number within each township and range. This data was left out of our transcription. Corresponding digitized maps of the Holland Land Purchase can be found at the New York State Archives website. https://www.archives.nysed.gov/ This dataset is a part of the Magazine of American Datasets (MEAD). To view more of the collection, visit https://repository.upenn.edu/exhibits/orgunit/mead.
  • Dataset
    Extreme sea level at different global warming levels
    Tebaldi, Claudia
    Tebaldi, C., Ranasinghe, R., Vousdoukas, M. et al. Extreme sea levels at different global warming levels. Nat. Clim. Chang. 11, 746–751 (2021). https://doi.org/10.1038/s41558-021-01127-1 (as shown in Fig. 1 b,d,f and Fig. 2 top panel for 7,283 locations). Global warming levels reached by 2100 causing a present-day 100-year extreme sea level event to become at least an annual event (for central value and low and upper bounds), and extended mean value of the difference between current 100-yr and the 1-yr events. The numbers from 1 to 9 along the 3rd, 4th and 5th columns correspond to the warming levels in the legend of Figure 1: 1.5, 2, 2+, 3, 4, 5, none (The + sign associated with 2 and 5 °C indicates projections that include SEJ-derived estimates of ice-sheet contribution to RSLC.) See also the data in an interactive way at the Perry World House Global Climate Security Atlas
  • Dataset
    Return period (years) in future (2071–2100) for discharge corresponding to a 30-year flood in the past (1971–2000), for CMIP6 under the ssp585 scenario
    Hirabayashi, Yukiko
    Hirabayashi, Y., Tanoue, M., Sasaki, O. et al. Global exposure to flooding from the new CMIP6 climate model projections. Sci Rep 11, 3740 (2021). https://doi.org/10.1038/s41598-021-83279-w (Fig. 1) Projected change in river flood frequency under the ssp585 climate change scenario. Multi-model median return period (years) in future (2071–2100) for discharge corresponding to a 100-year flood in the past (1971–2000), for CMIP6 under the ssp585 (SSP5-RCP8.5) scenario. See also data in an interactive way at the Perry World House Global Climate Security Atlas https://global.upenn.edu/perryworldhouse/global-climate-security-atlas