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Service Description: Habitat suitability models were created for 85 pest species that negatively impact tree species across the USA and Canada. Each model was produced as an ensemble of species distribution models that associated the occurrence of pest species with climate factors, topographical characteristics, host tree abundance, and, for non-native pest species, a dispersal metric capturing their spatiotemporal spread from their origin site in North America. Pest species occurrences from 1991-2025 were gathered from multiple online sources, including the USDA Forest Service, Forest Inventory and Analysis program; USDA Forest Service Forest, Insect and Disease Survey database; Global Biodiversity Information Facility; Canadian Forest Service Forest Invasive Alien Species; and numerous regional surveys. This data publication includes raster and image files of current projected distributions (1991-2020) of 85 pest species, as well as projected distributions that incorporate future climate scenarios (2070-2100) corresponding to high and low greenhouse gas emissions and future tree distribution scenarios in which trees do or do not migrate in response to future climate change. Each map is presented as both a probability surface (ranging from 0 to 1000) and a binary classification (0 and 1).
Ecosystems/USFS_ForestPestDistributions_NorthAmerica
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Copyright Text: This project was funded by the USDA Forest Service, Northern Research Station.
Author Information:
Hannah L. Clipp
USDA Forest Service, Northern Research Station (former ORISE postdoctoral researcher)
https://orcid.org/0000-0002-8555-7398
Anantha M. Prasad
USDA Forest Service, Northern Research Station (former employee)
https://orcid.org/0000-0002-4645-6260
Matthew P. Peters
USDA Forest Service, Northern Research Station
https://orcid.org/0000-0002-4793-0075
Stephen N. Matthews
USDA Forest Service, Northern Research Station
https://orcid.org/0000-0001-9175-7778
Andrew V. Gougherty
USDA Forest Service, Northern Research Station
https://orcid.org/0000-0002-3905-8539
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