Climate matching with the climatchR R package
Climate matching is a method for understanding species distributions and ranges and may be used as part of horizon scanning. Horizon scanning is the process of examining potential risk of invasion of new invasive species. Preventing new invasive species invasion requires less time and resources than attempting to control and remove established invasive species. Horizon scanning allows resource managers at the U.S. Fish and Wildlife Service to identify new potential invasive species and create measures to prevent their invasion. Often resource managers use similarities in the climates of both current distributions of species and possible invasive species to determine new possible invasive species using horizon scanning and other risk assessment techniques. Current climate matching methods are labor-intensive because it requires handpicked data and heavy data manipulation. However, climate matching could be completed in a relatively inexpensive and quick way by automating the process.
R package creation supports cutting edge science
This project aims to automate and make these methods accessible to more researchers that currently don’t have the resources to perform the current methods. To do this, researchers created a new R package called climatchR. ClimatchR is a model that allows researchers to examine many potential invasive species all at once. Models require inputs (data) that go through many processes and formulas to create different outputs. ClimatchR requires four different inputs including a list of species, Global Administrative Areas (governmental boundaries), CHELSA climate data, and Global Biodiversity Information Facility data (species location).
Using the input data and the methods outlined in Erickson et al. 2022, researchers can provide possible locations the eastern rosella (Platycercus eximius) could establish in the contiguous United States. After the model is complete you receive an output such as a heat map of climatch scores that shows where the selected species could establish if it is introduced. Climatch scores range from 0 to 10 and the higher the value the more likely that species is to invade that geographic area. A climatch score of 6 means, that species has a high potential for invasion in that geographic area (U.S. Fish and Wildlife Service 2020, Burner et al. 2023).
This project is ongoing and collaborates with the Natural Resource Ecology Laboratory, the USGS Fort Collins Science Center, the USGS Pacific Islands Ecosystem Research Center, the USGS Wetlands and Aquatic Research Center and Colorado State University.
Work Cited
Burner, R. C., Daniel, W. M., Engelstad, P. S., Churchill, C. J., & Erickson, R. A. (2023) BioLake: A first assessment of lake temperature-derived bioclimatic predictors for aquatic invasive species. ECOSPHERE. 14(7) 1 – 15. https://doi.org/10.1002/ecs2.4616
Erickson, R. A., Engelstad, P. C., Jarnevich, C.S., Sofaer, H. R., & Daniel, W.M. (2022). Climate matching with the climatchR R package. Environmental Modelling and Software. 157. 1 - 7 https://doi.org/10.1016/j.envsoft.2022.105510
U.S. Fish and Wildlife Service. 2020. Standard Operating Procedures: How to Prepare an “Ecological Risk Screening Summary”. Washington, DC: U.S. Fish and Wildlife Service. https://www.fws.gov/media/standard-operating-procedures-how-prepare-eco…
Climate matching is a method for understanding species distributions and ranges and may be used as part of horizon scanning. Horizon scanning is the process of examining potential risk of invasion of new invasive species. Preventing new invasive species invasion requires less time and resources than attempting to control and remove established invasive species. Horizon scanning allows resource managers at the U.S. Fish and Wildlife Service to identify new potential invasive species and create measures to prevent their invasion. Often resource managers use similarities in the climates of both current distributions of species and possible invasive species to determine new possible invasive species using horizon scanning and other risk assessment techniques. Current climate matching methods are labor-intensive because it requires handpicked data and heavy data manipulation. However, climate matching could be completed in a relatively inexpensive and quick way by automating the process.
R package creation supports cutting edge science
This project aims to automate and make these methods accessible to more researchers that currently don’t have the resources to perform the current methods. To do this, researchers created a new R package called climatchR. ClimatchR is a model that allows researchers to examine many potential invasive species all at once. Models require inputs (data) that go through many processes and formulas to create different outputs. ClimatchR requires four different inputs including a list of species, Global Administrative Areas (governmental boundaries), CHELSA climate data, and Global Biodiversity Information Facility data (species location).
Using the input data and the methods outlined in Erickson et al. 2022, researchers can provide possible locations the eastern rosella (Platycercus eximius) could establish in the contiguous United States. After the model is complete you receive an output such as a heat map of climatch scores that shows where the selected species could establish if it is introduced. Climatch scores range from 0 to 10 and the higher the value the more likely that species is to invade that geographic area. A climatch score of 6 means, that species has a high potential for invasion in that geographic area (U.S. Fish and Wildlife Service 2020, Burner et al. 2023).
This project is ongoing and collaborates with the Natural Resource Ecology Laboratory, the USGS Fort Collins Science Center, the USGS Pacific Islands Ecosystem Research Center, the USGS Wetlands and Aquatic Research Center and Colorado State University.
Work Cited
Burner, R. C., Daniel, W. M., Engelstad, P. S., Churchill, C. J., & Erickson, R. A. (2023) BioLake: A first assessment of lake temperature-derived bioclimatic predictors for aquatic invasive species. ECOSPHERE. 14(7) 1 – 15. https://doi.org/10.1002/ecs2.4616
Erickson, R. A., Engelstad, P. C., Jarnevich, C.S., Sofaer, H. R., & Daniel, W.M. (2022). Climate matching with the climatchR R package. Environmental Modelling and Software. 157. 1 - 7 https://doi.org/10.1016/j.envsoft.2022.105510
U.S. Fish and Wildlife Service. 2020. Standard Operating Procedures: How to Prepare an “Ecological Risk Screening Summary”. Washington, DC: U.S. Fish and Wildlife Service. https://www.fws.gov/media/standard-operating-procedures-how-prepare-eco…