Landscape Genomic Conservation Assessment of a Narrow-Endemic and a Widespread Morning Glory From Amazonian Savannas

Abstract

Although genetic diversity ultimately determines the ability of organisms to adapt to environmental changes, conservation assessments like the widely used International Union for Conservation of Nature (IUCN) Red List Criteria do not explicitly consider genetic information. Including a genetic dimension into the IUCN Red List Criteria would greatly enhance conservation efforts, because the demographic parameters traditionally considered are poor predictors of the evolutionary resilience of natural populations to global change. Here we perform the first genomic assessment of genetic diversity, gene flow, and patterns of local adaptation in tropical plant species belonging to different IUCN Red List Categories. Employing RAD-sequencing we identified tens of thousands of single-nucleotide polymorphisms in an endangered narrow-endemic and a least concern widespread morning glory (Convolvulaceae) from Amazonian savannas, a highly threatened and under-protected tropical ecosystem. Our results reveal greater genetic diversity and less spatial genetic structure in the endangered species. Whereas terrain roughness affected gene flow in both species, forested and mining areas were found to hinder gene flow in the endangered plant. Finally we implemented environmental association tests and genome scans for selection, and identified a higher proportion of candidate adaptive loci in the widespread species. These mainly contained genes related to pathogen resistance and physiological adaptations to life in nutrient-limited environments. Our study emphasizes that IUCN Red List Criteria do not always prioritize species with low genetic diversity or whose genetic variation is being affected by habitat loss and fragmentation, and calls for the inclusion of genetic information into conservation assessments. More generally, our study exemplifies how landscape genomic tools can be employed to assess the status, threats and adaptive responses of imperiled biodiversity.

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

“…S1). Our results thus suggest that local climate constitutes an important environmental filter driving local adaptation, as found in other species from Canga environments (Lanes et al, 2018) and temperate climates (Pluess et al, 2016;Pais et al, 2017). In M. acutistipula, Serra Norte populations showed associations with higher SLA, suggesting climatic or soil conditions in Serra Norte are more favorable to plant growth (He et al, 2018).…”

Peer Review #1 of "Everything you always wanted to know about gene flow in tropical landscapes (but were afraid to ask) (v0.2)"

“…The surveyed studies often had overlapping objectives, which comprised assessing contemporary and historical effects of climate on gene flow (Trénel et al, 2008; Ramírez- Barahona & Eguiarte, 2014); predicting gene flow with habitat suitability models (Poelchau & Hamrick, 2012;Guarnizo & Cannatella, 2013;Paz et al, 2015); assessing landscape and climatic effects on gene flow (Hohnen et al, 2016;Lanes et al, 2018); identifying dispersal routes (Andraca-Gómez et al, 2015;Cleary, Waits & Finegan, 2017;Thatte et al, 2018) and barriers to gene flow (Robertson, Duryea & Zamudio, 2009;Boff et al, 2014;Oliveira et al, 2017); and evaluating the impact of habitat fragmentation on gene flow (Balkenhol et al, 2013;Joshi et al, 2013;de Campos Telles et al, 2014;Carvalho et al, 2015;Ruiz-Lopez et al, 2015).…”

Habitat loss does not always entail negative genetic consequences

“…However, the fact that recent land cover did not explain relatedness patterns in either species in Serra Norte, strongly suggests that gene flow has been maintained across mines. In contrast, land cover in existence two decades ago was found to explain gene flow in a perennial narrow endemic morning glory occurring in Serra Norte (Lanes et al, 2018), indicating that our methods should be sufficient to detect an effect of mining should there be one, although differences in reproductive systems and dispersal modes could also underlie these different results (Aguilar et al, 2008;Vranckx et al, 2012). Additionally, our findings were unaffected by the resolution of spatial data and were supported by an independent barrier analysis, so they strongly indicate that gene flow in our two annual herbs is unaffected by habitat loss driven by mining.…”

“…By so doing we were able to evaluate the permeability to gene flow of each land cover class; and test whether habitat loss driven by mining hindered gene flow across our replicated landscapes. Additional variables found to be important predictors of gene flow in other plants (Dyer, 2016;Lanes et al, 2018) were modeled along with land cover, including geographic distance, elevation (DEM retrieved from the USGS Earth Explorer), terrain roughness (generated from the DEM using the Terrain Analysis plug-in from QGIS), and bioclimatic variables (retrieved from WorldClim). To select a set of orthogonal variables explaining most climatic variation across our study area, we first ran separate principal component analyses (PCA) for each species using the extracted values from all 19 WorldClim bioclimatic layers plus elevation (scaled) (Fig.…”