Isolation by resistance explains genetic diversity in the Arremon brushfinches of northern Mesoamerica.

Genetic differentiation between and within natural populations is the result of the joint effects of neutral and adaptative processes. In addition, the spatial arrangement of the landscape promotes connectivity or creates barriers to gene flow, directly affecting speciation processes. In this study, we carried out a landscape genomics analysis using NextRAD data from a montane forest specialist bird complex, the Mesoamerican Chestnut-capped/Green-striped Brushfinch of the genus Arremon. Specifically, we examined population genomic structure using different assignment methods and genomic differentiation and diversity, and we tested alternative genetic isolation hypotheses at the individual level (e.g., isolation by barrier, IBB; isolation by environment, IBE; isolation by resistance, IBR). We found well-delimited genomic structuring (K = 5) across Mesoamerican montane forests in the studied group. Individual-level genetic distances among major montane ranges were mainly explained by IBR hypotheses in this sedentary Neotropical taxon. Our results uncover genetic distances/differentiation and patterns of gene flow in allopatric species that support the role of tropical mountains as spatial landscape drivers of biodiversity. IBR clearly supports a pattern of conserved niche-tracking of suitable habitat conditions and topographic complexity throughout glacial-interglacial dynamics.

A comparative phylogenomic analysis of birds reveals heterogeneous differentiation processes among Neotropical savannas.

The main objective of this study was to evaluate biogeographical hypotheses of diversification and connection between isolated savannas north (Amazonian savannas) and south (Cerrado core) of the Amazon River. To achieve this, we used genomic markers (genotyping-by-sequencing) to evaluate the genetic structure, population phylogenetic relationships and historical range shifts of four Neotropical passerines with peri-Atlantic distributions: the narrow-billed woodcreeper (Lepidocolaptes angustirostris), the plain-crested elaenia (Elaenia cristata), the grassland sparrow (Ammodramus humeralis) and the white-banded tanager (Neothraupis fasciata). Population genetic analyses indicated that landscape (e.g., geographic distance, landscape resistance and percentage of tree cover) and climate metrics explained divergence among populations in most species, but without indicating a differential role between current and historical factors. Our results did not fully support the hypothesis that isolated populations in Amazonian savannas have been recently derived from the Cerrado core domain. Intraspecific phylogenies and gene flow analyses supported multiple routes of connection between the Cerrado and Amazonian savannas, rejecting the hypothesis that the Atlantic corridor explains the peri-Atlantic distribution. Our results reveal that the biogeographical history of the region is complex and cannot be explained by simple vicariant models.

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

As most ecosystems around the world are threatened by anthropogenic degradation and climate change, there is an increasing urgency to implement restoration strategies aiming at ensuring ecosystem self-sustainability and resilience. An initial step towards that goal relies on selecting the most suitable seed sources for a successful revegetation, which can be extremely challenging in highly degraded landscapes. The most common seed sourcing strategy is to select local seeds because it is assumed that plants experience strong adaptations to their natal sites. An alternative strategy is the selection of climate-adapted genotypes to future conditions. While considering future climatic projections is important to account for spatial shifts in climate to inform assisted gene flow and translocations, to restore highly degraded landscapes we need a comprehensive approach that first accounts for species adaptations to current at-site environmental conditions. In this issue of Molecular Ecology Resources, Carvalho et al. present a novel landscape genomics framework to identify the most appropriate seed sourcing strategy for moderately and highly degraded sites by integrating genotype, phenotype and environmental data in a spatially explicit context for two native plant species with potential to help restore iron-rich Amazonian savannas. This framework is amenable to be applicable and adapted to a broad range of restoration initiatives, as the dichotomy between focusing on the current or future climatic conditions should depend on the goals and environmental circumstances of each restoration site.

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

Despite the importance of climate-adjusted provenancing to mitigate the effects of environmental change, climatic considerations alone are insufficient when restoring highly degraded sites. Here we propose a comprehensive landscape genomic approach to assist the restoration of moderately disturbed and highly degraded sites. To illustrate it we employ genomic data sets comprising thousands of single nucleotide polymorphisms from two plant species suitable for the restoration of iron-rich Amazonian Savannas. We first use a subset of neutral loci to assess genetic structure and determine the genetic neighbourhood size. We then identify genotype-phenotype-environment associations, map adaptive genetic variation, and predict adaptive genotypes for restoration sites. Whereas local provenances were found optimal to restore a moderately disturbed site, a mixture of genotypes seemed the most promising strategy to recover a highly degraded mining site. 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 initiatives.

Evaluation of the Minimum Sampling Design for Population Genomic and Microsatellite Studies: An Analysis Based on Wild Maize.

Massive parallel sequencing (MPS) is revolutionizing the field of molecular ecology by allowing us to understand better the evolutionary history of populations and species, and to detect genomic regions that could be under selection. However, the economic and computational resources needed generate a tradeoff between the amount of loci that can be obtained and the number of populations or individuals that can be sequenced. In this work, we analyzed and compared two simulated genomic datasets fitting a hierarchical structure, two extensive empirical genomic datasets, and a dataset comprising microsatellite information. For all datasets, we generated different subsampling designs by changing the number of loci, individuals, populations, and individuals per population to test for deviations in classic population genetics parameters (H S , F IS , F ST ). For the empirical datasets we also analyzed the effect of sampling design on landscape genetic tests (isolation by distance and environment, central abundance hypothesis). We also tested the effect of sampling a different number of populations in the detection of outlier SNPs. We found that the microsatellite dataset is very sensitive to the number of individuals sampled when obtaining summary statistics. F IS was particularly sensitive to a low sampling of individuals in the simulated, genomic, and microsatellite datasets. For the empirical and simulated genomic datasets, we found that as long as many populations are sampled, few individuals and loci are needed. For the empirical datasets, we found that increasing the number of populations sampled was important in obtaining precise landscape genetic estimates. Finally, we corroborated that outlier tests are sensitive to the number of populations sampled. We conclude by proposing different sampling designs depending on the objectives.

Hybridization and introgression between Helicoverpa armigera and H. zea: an adaptational bridge.

BACKGROUND: Invasion of organisms into new ecosystems is increasingly common, due to the global trade in commodities. One of the most complex post-invasion scenarios occurs when an invasive species is related to a native pest, and even more so when they can hybridize and produce fertile progeny. The global pest Helicoverpa armigera was first detected in Brazil in 2013 and generated a wave of speculations about the possibility of hybridization with the native sister taxon Helicoverpa zea. In the present study, we used genome-wide single nucleotide polymorphisms from field-collected individuals to estimate hybridization between H. armigera and H. zea in different Brazilian agricultural landscapes. RESULTS: The frequency of hybridization varied from 15 to 30% depending on the statistical analyses. These methods showed more congruence in estimating that hybrids contained approximately 10% mixed ancestry (i.e. introgression) from either species. Hybridization also varied considerably depending on the geographic locations where the sample was collected, forming a 'mosaic' hybrid zone where introgression may be facilitated by environmental and landscape variables. Both landscape composition and bioclimatic variables indicated that maize and soybean cropland are the main factors responsible for high levels of introgression in agricultural landscapes. The impact of multiple H. armigera incursions is reflected in the structured and inbred pattern of genetic diversity. CONCLUSIONS: Our data showed that the landscape composition and bioclimatic variables influence the introgression rate between H. armigera and H. zea in agricultural areas. Continuous monitoring of the hybridization process in the field is necessary, since agricultural expansion, climatic fluctuations, changing composition of crop species and varieties, and dynamic planting seasons are some factors in South America that could cause a sudden alteration in the introgression rate between Helicoverpa species. Introgression between invasive and native pests can dramatically impact the evolution of host ranges and resistance management.

Habitat Loss Does Not Always Entail Negative Genetic Consequences.

Although habitat loss has large, consistently negative effects on biodiversity, its genetic consequences are not yet fully understood. This is because measuring the genetic consequences of habitat loss requires accounting for major methodological limitations like the confounding effect of habitat fragmentation, historical processes underpinning genetic differentiation, time-lags between the onset of disturbances and genetic outcomes, and the need for large numbers of samples, genetic markers, and replicated landscapes to ensure sufficient statistical power. In this paper we overcame all these challenges to assess the genetic consequences of extreme habitat loss driven by mining in two herbs endemic to Amazonian savannas. Relying on genotyping-by-sequencing of hundreds of individuals collected across two mining landscapes, we identified thousands of neutral and independent single-nucleotide polymorphisms (SNPs) in each species and used these to evaluate population structure, genetic diversity, and gene flow. Since open-pit mining in our study region rarely involves habitat fragmentation, we were able to assess the independent effect of habitat loss. We also accounted for the underlying population structure when assessing landscape effects on genetic diversity and gene flow, examined the sensitivity of our analyses to the resolution of spatial data, and used annual species and cross-year analyses to minimize and quantify possible time-lag effects. We found that both species are remarkably resilient, as genetic diversity and gene flow patterns were unaffected by habitat loss. Whereas historical habitat amount was found to influence inbreeding; heterozygosity and inbreeding were not affected by habitat loss in either species, and gene flow was mainly influenced by geographic distance, pre-mining land cover, and local climate. Our study demonstrates that it is not possible to generalize about the genetic consequences of habitat loss, and implies that future conservation efforts need to consider species-specific genetic information.

Isolation by instability: Historical climate change shapes population structure and genomic divergence of treefrogs in the Neotropical Cerrado savanna.

Although the impact of Pleistocene glacial cycles on the diversification of the tropical biota was once dismissed, increasing evidence suggests that Pleistocene climatic fluctuations greatly affected the distribution and population divergence of tropical organisms. Landscape genomic analyses coupled with paleoclimatic distribution models provide a powerful way to understand the consequences of past climate changes on the present-day tropical biota. Using genome-wide SNP data and mitochondrial DNA, combined with projections of the species distribution across the late Quaternary until the present, we evaluate the effect of paleoclimatic shifts on the genetic structure and population differentiation of Hypsiboas lundii, a treefrog endemic to the South American Cerrado savanna. Our results show a recent and strong genetic divergence in H. lundii across the Cerrado landscape, yielding four genetic clusters that do not seem congruent with any current physical barrier to gene flow. Isolation by distance (IBD) explains some of the population differentiation, but we also find strong support for past climate changes promoting range shifts and structuring populations even in the presence of IBD. Post-Pleistocene population persistence in four main areas of historical stable climate in the Cerrado seems to have played a major role establishing the present genetic structure of this treefrog. This pattern is consistent with a model of reduced gene flow in areas with high climatic instability promoting isolation of populations, defined here as "isolation by instability," highlighting the effects of Pleistocene climatic fluctuations structuring populations in tropical savannas.

Landscape genomics provides evidence of climate-associated genetic variation in Mexican populations of Quercus rugosa.

Local adaptation is a critical evolutionary process that allows plants to grow better in their local compared to non-native habitat and results in species-wide geographic patterns of adaptive genetic variation. For forest tree species with a long generation time, this spatial genetic heterogeneity can shape the ability of trees to respond to rapid climate change. Here, we identify genomic variation that may confer local environmental adaptations and then predict the extent of adaptive mismatch under future climate as a tool for forest restoration or management of the widely distributed high-elevation oak species Quercus rugosa in Mexico. Using genotyping by sequencing, we identified 5,354 single nucleotide polymorphisms (SNPs) genotyped from 103 individuals across 17 sites in the Trans-Mexican Volcanic Belt, and, after controlling for neutral genetic structure, we detected 74 F ST outlier SNPs and 97 SNPs associated with climate variation. Then, we deployed a nonlinear multivariate model, Gradient Forests, to map turnover in allele frequencies along environmental gradients and predict areas most sensitive to climate change. We found that spatial patterns of genetic variation were most strongly associated with precipitation seasonality and geographic distance. We identified regions of contemporary genetic and climatic similarities and predicted regions where future populations of Q. rugosa might be at risk due to high expected rate of climate change. Our findings provide preliminary details for future management strategies of Q. rugosa in Mexico and also illustrate how a landscape genomic approach can provide a useful tool for conservation and resource management strategies.

Contrasting Patterns of Gene Flow for Amazonian Snakes That Actively Forage and Those That Wait in Ambush.

Knowledge of genetic structure, geographic distance and environmental heterogeneity can be used to identify environmental features and natural history traits that influence dispersal and gene flow. Foraging mode is a trait that might predict dispersal capacity in snakes, because actively foragers typically have greater movement rates than ambush predators. Here, we test the hypothesis that 2 actively foraging snakes have higher levels of gene flow than 2 ambush predators. We evaluated these 4 co-distributed species of snakes in the Brazilian Amazon. Snakes were sampled along an 880 km transect from the central to the southwest of the Amazon basin, which covered a mosaic of vegetation types and seasonal differences in climate. We analyzed thousands of single nucleotide polymorphisms to compare patterns of neutral gene flow based on isolation by geographic distance (IBD) and environmental resistance (IBR). We show that IBD and IBR were only evident in ambush predators, implying lower levels of dispersal than the active foragers. Therefore, gene flow was high enough in the active foragers analyzed here to prevent any build-up of spatial genotypic structure with respect to geographic distance and environmental heterogeneity.