The gap between research and its implementation is an impediment to conservation of the environment. Translating science into actionable management and policy requires effective communication and collaboration among scientists, practitioners, and policy-makers. Ecologists routinely rely on spatial data to describe wildlife distributions; however, habitat definitions vary by species, and data sources often differ from those used by land managers. Finding commonalities in the language and data used to plan for industrial activities and wildlife conservation may help address the research-implementation gap for threatened species like woodland caribou. We built resource selection functions for caribou using Alberta Vegetation Index (AVI) habitat data, which is employed by the Alberta forest industry for landbase planning. Our goal was to bridge the research-implementation gap by providing the forest industry with tools to facilitate planning for caribou conservation within their jurisdiction. In contrast to previous studies that highlighted shortcomings in AVI data for predicting wildlife habitat use, we found that resource selection function models that combined AVI data with complementary covariates validated well to predict caribou habitat use. We suggest that by using a data source familiar to land managers, ecologists can facilitate the bridging of the research-implementation gap without compromising the quality of ecological modeling.