Spatial priorities for climate-change refugia in British Columbia (Version 2.1)

Overview This dataset provides spatial priorities for climate-informed conservation and restoration planning across British Columbia. The products integrate multiple indicators of macrorefugia and microrefugia using the Core Area Zonation (CAZ) algorithm in Zonation. Macrorefugia represent relatively large areas with the potential to maintain suitable climatic conditions or species habitat as climate changes. Microrefugia represent locations where fine-scale topographic, hydrologic, ecological, or disturbance-related conditions may locally buffer ecosystems from regional climate change. The resulting spatial prioritizations are intended to support climate-informed land stewardship and protected-area planning. They can be used to identify areas with high potential to support biodiversity persistence under climate change, evaluate existing conservation networks, and distinguish areas where conservation versus restoration may be appropriate. Analyses were conducted at 1-km spatial resolution in the NAD 1983 BC Albers projection. Ranked Zonation priorities range from 0 (lowest priority) to 1 (highest priority). Land relationship acknowledgement We respectfully acknowledge that we live and work across diverse unceded territories and treaty lands and pay our respects to the First Nations, Inuit and Métis ancestors of these places. We honour our connections to these lands and waters and reaffirm our relationships with one another. Methods 1. Macrorefugia Macrorefugia priorities incorporated both climate-based and species-specific indicators. Climate-type macrorefugia were represented by forward and backward climate velocity for an ensemble of eight CMIP6 global climate models under SSP2-4.5. Climate-velocity values were transformed so that higher values represented greater refugia potential. Species-specific macrorefugia represented areas with relatively high potential to retain suitable climatic habitat through time. Separate Zonation scenarios were developed for: rare species in British Columbia (833 Red-listed, Blue-listed, and SARA Schedule 1 species), grouped by major taxonomic group; 142 climate-sensitive bird species; and 10 dominant tree species in British Columbia. Species-specific macrorefugia inputs were based on indices ranging from 0 to 1, with higher values indicating greater macrorefugia potential. Taxon-specific Zonation outputs were subsequently combined with forward and backward climate-type velocity in an overall macrorefugia CAZ scenario. Inputs were equally weighted. Separate analyses were conducted for the 2050s (2041–2070) and 2080s (2071–2100) under SSP2-4.5. 2. Microrefugia A separate CAZ scenario combined six indicators of microrefugia: topodiversity; cool slopes, glaciers, and wetlands; topographically mediated fire refugia; thermal refugia; drought refugia; and old-growth forest. Inputs were transformed to a common interpretation in which higher values indicated greater microrefugia potential. Binary indicators were assigned values of 0 or 1, while continuous or categorical products were rescaled or reclassified as described in Table 1. The six microrefugia indicators were equally weighted in the CAZ analysis. Microrefugia were treated as temporally static and therefore used for both future periods. 3. Combined macrorefugia and microrefugia priorities The macrorefugia and microrefugia Zonation outputs were combined in a final CAZ scenario, with equal weighting of the two components. Separate combined prioritizations were produced for the 2050s and 2080s. 4. Conservation and restoration priorities A post hoc human-footprint mask derived from the British Columbia cumulative-effects dataset was applied to the combined Zonation outputs. Areas of low human footprint were classified as candidates for area-based conservation, whereas areas of high human footprint were classified as candidates for restoration or other management actions. These products should therefore be interpreted as relative spatial priorities under the assumptions and inputs of the prioritization framework, rather than as prescriptive designations of areas that should necessarily be protected or restored. Table 1. Spatial inputs used to identify macrorefugia and microrefugia Refugia class Input Resolution Processing for Zonation Source Macrorefugia Forward and backward climate velocity, 8-GCM ensemble, CMIP6, SSP2-4.5 1 km Values were rescaled by adding a constant and taking the inverse so that higher values represented greater refugia potential. Carroll (2023); Carroll et al. (2015) Macrorefugia Bird macrorefugia based on backward velocity (142 species), 3-GCM ensemble, CMIP5, RCP 4.5 1 km Existing 0–100 macrorefugia-index values were used. Raymundo et al. (2025); Bateman et al. (2020) Macrorefugia Rare-species macrorefugia based on forward and backward velocity (833 species), 3-GCM ensemble, CMIP6, SSP2-4.5 1 km Existing 0–100 macrorefugia-index values were used. Stolar et al. (2026); Raymundo et al. (2026) Macrorefugia Dominant tree-species macrorefugia based on forward and backward velocity (10 species in BC), 13-GCM ensemble, CMIP6, SSP2-4.5 1 km Existing 0–100 macrorefugia-index values were used. Campbell et al. (2025) Microrefugia Topodiversity 1 km Existing categorical values were rescaled so that higher values represented greater microrefugia potential: class 2 = 0, class 3 = 0.5, class 4 = 1. Kehm (2026) Microrefugia Cool slopes, glaciers, and wetlands 1 km Reclassified to binary presence/absence (0/1). Kehm (2023) Microrefugia Fire refugia (Fire_Refugia_Topography.tif) 1 km, resampled from 90 m Existing 0–1 values were used. Kuntzemann et al. (2025a,b) Microrefugia Thermal refugia (lm_slope_LST_Tmax.tif) 1 km Thermal sensitivity was reclassified to binary values (0/1); values