A comparison of genetic and genomic approaches to represent evolutionary potential in conservation planning. (November 2020)

• Record Type: Journal Article
• Authors: Nielsen, Erica S.; Beger, Maria; Henriques, Romina; von der Heyden, Sophie
• Is Part Of: Biological conservation. Volume 251(2020)
• Publication Date: 2020-11
• Subjects: Evolutionary potential -- Spatial conservation planning -- Conservation genomics -- Genetic diversity -- Marxan -- Surrogacy; Conservation of natural resources -- Periodicals; Nature conservation -- Periodicals; Ecology -- Periodicals; Environment -- Periodicals; Environmental Pollution -- Periodicals; Electronic journals; 333.9516
• DOI: 10.1016/j.biocon.2020.108770
• Languages: English
• ISSNs: 0006-3207

Abstract

Abstract: Emerging global change stressors have underlined the importance of informing conservation decisions with molecular diversity, particularly including intraspecific adaptive or evolutionary potential across species and populations. Population-level evolutionary potential is best captured by genomic approaches, yet these data types mostly remain limited to model organisms. In contrast, traditional genetic data are broadly available. The relevance of genomic metrics, and how they differ from genetic metrics in the context of spatial conservation practices, remains unknown. This provides an opportunity to consider the relative contribution and impact of genomic compared to genetic metrics in their efficiency of selecting conservation areas of evolutionary importance. Here, we provide a guideline to include metrics of genetic and genomic variation into spatial planning analyses for multiple conservation objectives, and empirically explore how spatial prioritizations change when including different types of molecular information across multiple species. Specifically, we compare conservation solutions of scenarios including either an increase in molecular information (i.e. either a single locus; mtDNA, or several thousand loci; SNPs), or an increase in species included. We find that including less molecular information from many species leads to similar outcomes to including more molecular information from fewer species. Our work suggests that multi-species genetic data may be a cost- and time-effective surrogate for genomic data in spatial planning. Highlights: Different molecular metrics should be used to meet specific conservation objectives. Single-species molecular data are inefficient at capturing multi-species evolutionary potential. Genetic data may be a potential surrogate of genomic data within conservation planning.