Habitat use for many species is directly affected by the climate. Thus climate information was used by ABMI when modeling variation in species abundance throughout Alberta.
Dr. Diana Stralberg (University of Alberta) interpolated existing bioclimate data for Alberta. Climate variables were derived from an interpolation of historical weather station data using the parameter-elevation regressions on independent slopes model (PRISM) method (Daly et al. 2002). Monthly climate normals for the 1961-1990 baseline period were downscaled to a 500-m resolution using the Climate WNA tool. Derived bioclimatic indices were developed from monthly variables according to Wang et al. (2011).
Hamann, A., Wang, T., Spittlehouse, D.L. & Murdock, T.Q. (2013) A comprehensive, high-resolution database of historical and projected climate surfaces for western North America. Bulletin of the American Meteorological Society, 94, 1307–1309.
Daly, C., W.P. Gibson, G.H. Taylor, G.L. Johnson, and P. Pasteris. 2002. A knowledge-based approach to the statistical mapping of climate. Climate Research 22:99-113.
Hijmans, R.J., S.E. Cameron, J.L. Parra, P.G. Jones, and A. Jarvis. 2005. Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology 25:1965-1978.
Wang, T., A. Hamann, D.L. Spittlehouse, and T.Q. Murdock. 2011. ClimateWNA - high-resolution spatial climate data for western North America. Meteorology and Climatology 51:16-29.
- Species & Habitat Raw Data
- Human Footprint Products
- ABMI GitHub
- Advanced Landcover Prediction & Habitat Assessment (ALPHA) Products
- Other Geospatial Land Surface Data
- GIS Data: Biodiversity
- Species-level Data Sets
- Remote Camera Mammal Data
- Rare Species Data
- Data Archive