Combining genotype, phenotype, and environmental data to delineate site-adjusted provenance strategies for ecological restoration

Abstract

Despite the importance of climate-adjusted provenancing to mitigate the effects of climate change, climatic considerations alone are insufficient when restoring highly degraded sites. Here we employ a comprehensive landscape genomic approach to assist the restoration of moderately disturbed and highly degraded sites. Relying on genotyping-by-sequencing we identified thousands of single nucleotide polymorphisms in two plant species of special interest for the restoration of iron-rich Amazon Savannas from the Eastern Amazon. We first used a subset of neutral loci to assess genetic structure and determine the genetic neighborhood size, and then combined uni-variate and multivariate methods to identify genotype-environment and genotype-phenotype associations, representing local adaptations. We then mapped adaptive genetic variation and predicted adaptive genotypes for both restoration sites. Whereas local provenances where found optimal to restore the moderately disturbed site, a mixture of genotypes was the most promising strategy to recover a highly degraded mining site, to which local provenances were not adapted. We discuss how our results can help define site-adjusted provenancing strategies and argue that our methods can be more broadly applied to assist other restoration and rehabilitation initiatives.

A comprehensive landscape genomics approach for seed sourcing strategies in landscapes under varying degrees of habitat disturbance

“…In line with the conceptual premise by Lesica and Allendorf (1999), Carvalho et al. (2020) found that observed and predicted genotypes for the highly degraded restoration site did not cluster together in either species, while the opposite was observed for the moderately disturbed site. In the praxis, this result suggests that local provenances are optimal to restore the moderately disturbed site, whereas mixed seed could be the best strategy to revegetate the highly degraded mining site, as local plants are probably no longer adapted to their climate and soil conditions.…”

“…Plant species suitable for restoration of iron‐ore‐exhausted mining areas in Canga ecosystems in Brazil and examined for neutral and adaptive genetic variation by Carvalho et al. (2020): (a) Dioclea apurensis (photo: Daniela Zappi); (b) Mimosa acutistipula var. ferrea (photo: Pedro Viana); (c) Pristine Canga ecosystem (savannas on the top of mountain plateaus surrounded by evergreen forest) (photo: Leonardo Viana) [Colour figure can be viewed at wileyonlinelibrary.com]…”

“…Thus, the most salient aspect of the approach taken by Carvalho et al. (2020) is the assessment of genotype–environmental associations (GEAs) and genotype–phenotype associations (GPAs) to detect putative adaptive loci, map the adaptive variation and assess the most adequate genotypes for each restoration site. Environmental data included climate and soil composition variables and the phenotypic data comprised measures of the specific leaf area and leaf macro‐ and micronutrients, which are key traits related to plant physiology for metalliferous ecosystems.…”

“…The framework proposed by Carvalho et al. (2020) offers a comprehensive perspective to guide provenance delimitation and the optimal seed sourcing strategy upon the degree of habitat disturbance of restoration sites by taking advantage of the information that can be gathered for both neutral and adaptive variation. As the field of restoration genomics grows, there remain several methodological aspects that need to be explored, such as the power and performance of the available spatial modelling methods (GDM, sPCA, gradient forest) depending on the type of genomic and spatial data (linear versus.…”

“…In this context, in this issue of Molecular Ecology Resources , Carvalho et al. (2020) advance the use of landscape genomic tools by developing a comprehensive approach to guide prerestoration provenance decisions across sites with varying environmental and disturbance regimes by considering both neutral and adaptive genetic variation via single nucleotide polymorphisms (SNPs) for two native plants ( Dioclea apurensis and Mimosa acutistipula var. ferrea ) of the Canga ecosystem in Brazil (Figure 1).…”