RESUMO
One key research goal of evolutionary biology is to understand the origin and maintenance of genetic variation. In the Cerrado, the South American savanna located primarily in the Central Brazilian Plateau, many hypotheses have been proposed to explain how landscape features (e.g., geographic distance, river barriers, topographic compartmentalization, and historical climatic fluctuations) have promoted genetic structure by mediating gene flow. Here, we asked whether these landscape features have influenced the genetic structure and differentiation in the lizard species Norops brasiliensis (Squamata: Dactyloidae). To achieve our goal, we used a genetic clustering analysis and estimate an effective migration surface to assess genetic structure in the focal species. Optimized isolation-by-resistance models and a simulation-based approach combined with machine learning (convolutional neural network; CNN) were then used to infer current and historical effects on population genetic structure through 12 unique landscape models. We recovered five geographically distributed populations that are separated by regions of lower-than-expected gene flow. The results of the CNN showed that geographic distance is the sole predictor of genetic variation in N. brasiliensis, and that slope, rivers, and historical climate had no discernible influence on gene flow. Our novel CNN approach was accurate (89.5%) in differentiating each landscape model. CNN and other machine learning approaches are still largely unexplored in landscape genetics studies, representing promising avenues for future research with increasingly accessible genomic datasets.
Assuntos
Fluxo Gênico , Variação Genética , Genética Populacional , Lagartos , Animais , Lagartos/genética , Brasil , Modelos Genéticos , Aprendizado de MáquinaRESUMO
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.
RESUMO
Animal pollination mediates both reproduction and gene flow for the majority of plant species across the globe. However, past functional studies have focused largely on seed production; although useful, this focus on seed set does not provide information regarding species-specific contributions to pollen-mediated gene flow. Here we quantify pollen dispersal for individual pollinator species across more than 690 ha of tropical forest. Specifically, we examine visitation, seed production, and pollen-dispersal ability for the entire pollinator community of a common tropical tree using a series of individual-based pollinator-exclusion experiments followed by molecular-based fractional paternity analyses. We investigate the effects of pollinator body size, plant size (as a proxy of floral display), local plant density, and local plant kinship on seed production and pollen-dispersal distance. Our results show that while large-bodied pollinators set more seeds per visit, small-bodied bees visited flowers more frequently and were responsible for more than 49% of all long-distance (beyond 1 km) pollen-dispersal events. Thus, despite their size, small-bodied bees play a critical role in facilitating long-distance pollen-mediated gene flow. We also found that both plant size and local plant kinship negatively impact pollen dispersal and seed production. By incorporating genetic and trait-based data into the quantification of pollination services, we highlight the diversity in ecological function mediated by pollinators, the influential role that plant and population attributes play in driving service provision, and the unexpected importance of small-bodied pollinators in the recruitment of plant genetic diversity.