Affiliation:
1. Department of Forestry and Natural Resources Purdue University West Lafayette Indiana USA
2. Department of Biological Sciences Kangwon National University Chuncheon Korea
3. Department of Biological Sciences Purdue University West Lafayette Indiana USA
4. Department of Biology University of North Carolina Chapel Hill North Carolina USA
Abstract
AbstractBackgroundEcological and genomic attributes of populations can provide two orthologous perspectives on the biological profiles associated with local adaptation. The ability of organisms to track suitable habitats (ecological adaptability) and of populations to shift allele frequencies (adaptive potential) are prerequisite for population sustainability.AimsMany contemporary populations are threatened by habitat loss (ecological vulnerability) and a lack of adaptive potential (evolutionary vulnerability). Technical advances provide new opportunities to address these challenges in biological conservation: Future habitat shifts can be predicted by ecological niche modelling and adaptive genetic diversity can be discerned using genome sequence data. Together, these two approaches illuminate the local adaptation profile and help identify the environmental and genomic conditions that should maximize evolutionary fitness.Materials and MethodsHere, we reviewed the primary literature to identify key studies that utilize both whole‐genome resequencing (WGR) and ecological niche modelling (ENM) in an effort to envisage future research directions that may benefit conservation efforts.ResultsWe identified ways to integrate different approaches, such as ENM‐informed adaptive genomics and adaptive genomics‐informed ENMs, that can be used to delineate and conserve local adaptation profiles.DiscussionIntegrative approaches can identify adaptive characteristics, vulnerable populations subject to environmental changes, and the patterns of local adaptation from geographic and genomic analyses. We discuss future research directions, limitations and their potential solutions with suggestions for collaborative workflows.ConclusionThe integration of WGR and ENM is promising with their continuous advancement. An integrative approach can be used to evaluate eco‐evolutionary attributes, at both organismal and molecular levels, that can be used to help conserve local adaptation profiles.