2026/06/15 by Melissa D. Starking, Tracy Monegan Rice, Karen Terwilliger +7 · 1 voice
Environmental Science · #Fish Ecology and Management Studies #Conservation, Ecology, Wildlife Education #Species Distribution and Climate Change
paper · doi:10.1111/csp2.70335
openalex publication_date 2026/06/15 · openalex created_date 2026/06/16 · openalex updated_date 2026/07/23
Abstract Through the end of the 21st century, biodiversity is expected to markedly decline around the world due to climate change, habitat loss, and other factors. Thus, there is a growing need for more efficient, effective, and collaborative conservation efforts worldwide. While many global and national threat assessment databases exist, utility at regional and local scales is limited, yet on‐the‐ground conservation is most effectively implemented at these scales. To identify species risk at a regional scale, 14 northeastern United States state fish and wildlife agencies, along with other taxonomic experts across this region, developed the most recent Northeast Regional Species of Greatest Conservation Need (RSGCN) list. Comparing a preliminary list compiled from global and national datasets with the finalized RSGCN list after a three‐part evaluation process conducted by regional and state fish and wildlife agency taxonomic experts, we found the global and national datasets accurately identified only ~55% of RSGCN statuses for the region, highlighting the importance of incorporating local and regional expertise with current data. Identifying the northeastern US RSGCN has resulted in specific, actionable information leading to beneficial conservation outcomes for species and habitats across the region, such as dedicated funding for regional initiatives, data sharing, and coordination among regional, state, and local conservation organizations. Furthermore, our process facilitated regional actions contributing to federal delisting or a listing finding of ‘not warranted’ for four species. The methods described serve as a framework for other regions to identify conservation targets using best available and localized landscape‐ and watershed‐scale information.