Improved prediction of Canada lynx distribution through regional model transferability and data efficiency
Item Metadata
Dublin Core
Title
Improved prediction of Canada lynx distribution through regional model transferability and data efficiency
Description
The application of species distribution models (SDMs) to areas outside of where a model was created allows informed decisions across large spatial scales, yet transferability remains a challenge in ecological modeling. We examined how regional variation in animal-environment relationships influenced model transferability for Canada lynx (Lynx canadensis), with an additional conservation aim of modeling lynx habitat across the northwestern United States. Simultaneously, we explored the effect of sample size from GPS data on SDM model performance and transferability. We used data from three geographically distinct Canada lynx populations in Washington (n = 17 individuals), Montana (n = 66), and Wyoming (n = 10) from 1996 to 2015. We assessed regional variation in lynx-environment relationships between these three populations using principal components analysis (PCA). We used ensemble modeling to develop SDMs for each population and all populations combined and assessed model prediction and transferability for each model scenario using withheld data and an extensive independent dataset (n = 650). Finally, we examined GPS data efficiency by testing models created with sample sizes of 5%–100% of the original datasets. PCA results indicated some differences in environmental characteristics between populations; models created from individual populations showed differential transferability based on the populations' similarity in PCA space. Despite population differences, a single model created from all populations performed as well, or better, than each individual population. Model performance was mostly insensitive to GPS sample size, with a plateau in predictive ability reached at ~30% of the total GPS dataset when initial sample size was large. Based on these results, we generated well-validated spatial predictions of Canada lynx distribution across a large portion of the species' southern range, with precipitation and temperature the primary environmental predictors in the model. We also demonstrated substantial redundancy in our large GPS dataset, with predictive performance insensitive to sample sizes above 30% of the original.
Bibliographic Citation
Olson, L. E., N. Bjornlie, G. Hanvey, J. D. Holbrook, J. S. Ivan, S. Jackson, B. Kertson, T. King, M. Lucid, D. Murray, R. Naney, J. Rohrer, A. Scully, D. Thornton, Z. Walker, and J. R. Squires. 2021. Improved prediction of Canada lynx distribution through regional model transferability and data efficiency. Ecology and Evolution 11:1667–1690. https://doi.org/10.1002/ece3.7157
Creator
Olson, Lucretia E.
Bjornlie, Nichole
Hanvey, Gary
Holbrook, Joseph D.
Ivan, Jacob S.
Jackson, Scott
Kertson, Brian
King, Travis
Lucid, Michael
Murray, Dennis
Naney, Robert
Rohrer, John
Scully, Arthur
Thornton, Daniel
Walker, Zachary
Squires, John R.
Subject
Canada lynx
Generalizability
GPS telemetry data
Local adaptation
Niche similarity
Regional variation
Sample size
Species distribution model
Transferability
Extent
24 pages
Date Created
2021-01-24
Rights
Type
Article
Format
application/pdf
Language
English
Is Part Of
Ecology and Evolution
Collection
Citation
Olson, Lucretia E. et al., “Improved prediction of Canada lynx distribution through regional model transferability and data efficiency,” CPW Digital Collections, accessed April 25, 2024, https://cpw.cvlcollections.org/items/show/233.