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While genetic variation in any species is potentially shaped by a range of processes, phylogeography and landscape genetics are largely concerned with inferring how environmental conditions and landscape features impact neutral intraspecific diversity. However, even as both disciplines have come to utilize SNP data over the last decades, analytical approaches have remained for the most part focused on either broad-scale inferences of historical processes (phylogeography) or on more localized inferences about environmental and/or landscape features (landscape genetics). Here we demonstrate that an artificial intelligence model-based analytical framework can consider both deeper historical factors and landscape-level processes in an integrated analysis. We implement this framework using data collected from two Brazilian anurans, the Brazilian sibilator frog (Leptodactylus troglodytes) and granular toad (Rhinella granulosa). Our results indicate that historical demographic processes shape most the genetic variation in the sibulator frog, while landscape processes primarily influence variation in the granular toad. The machine learning framework used here allows both historical and landscape processes to be considered equally, rather than requiring researchers to make an a priori decision about which factors are important.

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On a planet experiencing constant human population growth, it is necessary to explore the anthropogenic effects on the genetic diversity of species, and specifically invasive species. Using an analysis that integrates comparative phylogeography, urban landscape genetics, macrogenetics and a systematic review, we explore the worldwide genetic diversity of the human commensal and anthropogenic species Rattus rattus and Rattus norvegicus. Based on metadata obtained considering 35 selected studies related to observed heterozygosity, measured by nuclear molecular markers (microsatellites, Single Nucleotide Polymorphisms-SNPs-, restrictition site-associated DNA sequencing -RAD-Seq-), socioeconomic and mobility anthropogenic factors were used as predictors of genetic diversity of R. rattus and R. norvegicus, using the Gini index, principal component analysis and Random Forest Regression as analysis methodology. Population density was on average the best predictor of genetic diversity in the Rattus species analyzed, indicating that the species respond in a particular way to the characteristics present in urban environments because of a combination of life history characteristics and human-mediated migration and colonization processes. To create better management and control strategies for these rodents and their associated diseases, it is necessary to fill the existing information gap in urban landscape genetics studies with more metadata repositories, with emphasis on tropical and subtropical regions of the world.

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Macrophomina phaseolina causes charcoal rot, which can significantly reduce yield and seed quality of soybean and dry bean resulting from primarily environmental stressors. Although charcoal rot has been recognized as a warm climate-driven disease of increasing concern under global climate change, knowledge regarding population genetics and climatic variables contributing to the genetic diversity of M. phaseolina is limited. This study conducted genome sequencing for 95 M. phaseolina isolates from soybean and dry bean across the continental United States, Puerto Rico, and Colombia. Inference on the population structure using 76,981 single nucleotide polymorphisms (SNPs) revealed that the isolates exhibited a discrete genetic clustering at the continental level and a continuous genetic differentiation regionally. A majority of isolates from the United States (96%) grouped in a clade with a predominantly clonal genetic structure, while 88% of Puerto Rican and Colombian isolates from dry bean were assigned to a separate clade with higher genetic diversity. A redundancy analysis (RDA) was used to estimate the contributions of climate and spatial structure to genomic variation (11,421 unlinked SNPs). Climate significantly contributed to genomic variation at a continental level with temperature seasonality explaining the most variation while precipitation of warmest quarter explaining the most when spatial structure was accounted for. The loci significantly associated with multivariate climate were found closely to the genes related to fungal stress responses, including transmembrane transport, glycoside hydrolase activity and a heat-shock protein, which may mediate climatic adaptation for M. phaseolina. On the contrary, limited genome-wide differentiation among populations by hosts was observed. These findings highlight the importance of population genetics and identify candidate genes of M. phaseolina that can be used to elucidate the molecular mechanisms that underly climatic adaptation to the changing climate.

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This study purposes to examine the distribution of A2A2 alleles in herds of Curraleiro Pé-Duro (CPD) cattle and test association patterns with geographical and municipal development data. Eight CPD herds were selected from the municipalities of Tocantins State, Brazil. The frequency of the A1 and A2 allele was 40.0 and 60.0%, and the frequencies of genotypes A1A1, A1A2, and A2A2 were 20.0, 39.0, and 41.0%, respectively. Correlation estimates supported that the preferred genotype (A2A2) was mostly present in the relatively higher developed mesoregion (West) (P < 0.05). However, genotypic frequencies varied at random according to human population of municipalities and human development index (P > 0.05). The evaluation of the variability of the ß-casein gene polymorphism, coupled with spatially explicit methods (spatial autocorrelation, mantel test, and interpolation procedures), revealed some level of spatial dependency. The results suggest that the production of A2A2 milk in indigenous CPD cattle is feasible. This will depend on the adoption of selection schemes.

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The phylogeography of the American black bear (Ursus americanus) is characterized by isolation into glacial refugia, followed by population expansion and genetic admixture. Anthropogenic activities, including overharvest, habitat loss, and transportation infrastructure, have also influenced their landscape genetic structure. We describe the genetic structure of the American black bear in the American Southwest and northern Mexico and investigate how prehistoric and contemporary forces shaped genetic structure and influenced gene flow. Using a suite of microsatellites and a sample of 550 bears, we identified 14 subpopulations organized hierarchically following the distribution of ecoregions and mountain ranges containing black bear habitat. The pattern of subdivision we observed is more likely a product of postglacial habitat fragmentation during the Pleistocene and Holocene, rather than a consequence of contemporary anthropogenic barriers to movement during the Anthropocene. We used linear mixed-effects models to quantify the relationship between landscape resistance and genetic distance among individuals, which indicated that both isolation by resistance and geographic distance govern gene flow. Gene flow was highest among subpopulations occupying large tracts of contiguous habitat, was reduced among subpopulations in the Madrean Sky Island Archipelago, where montane habitat exists within a lowland matrix of arid lands, and was essentially nonexistent between two isolated subpopulations. We found significant asymmetric gene flow supporting the hypothesis that bears expanded northward from a Pleistocene refugium located in the American Southwest and northern Mexico and that major highways were not yet affecting gene flow. The potential vulnerability of the species to climate change, transportation infrastructure, and the US-Mexico border wall highlights conservation challenges and opportunities for binational collaboration.

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BACKGROUND: Historical and ecological processes shape patterns of genetic diversity in plant species. Colonization to new environments and geographical landscape features determine, amongst other factors, genetic diversity within- and differentiation between-populations. We analyse the genetic diversity and population structure of Calibrachoa heterophylla to infer the influence of abiotic landscape features on the level of gene flow in this coastal species of the South Atlantic Coastal Plain. RESULTS: The C. heterophylla populations located on early-deposited coastal plain regions show higher genetic diversity than those closer to the sea. The genetic differentiation follows a pattern of isolation-by-distance. Landscape features, such as water bodies and wind corridors, and geographical distances equally explain the observed genetic differentiation, whereas the precipitation seasonality exhibits a strong signal for isolation-by-environment in marginal populations. The estimated levels of gene flow suggest that marginal populations had restricted immigration rates enhancing differentiation. CONCLUSIONS: Topographical features related to coastal plain deposition history influence population differentiation in C. heterophylla. Gene flow is mainly restricted to nearby populations and facilitated by wind fields, albeit without any apparent influence of large water bodies. Furthermore, differential rainfall regimes in marginal populations seem to promote genetic differentiation.

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This study was realized to analyze the combinations of climatic, physical, and socio-economic variables on distribution of breeding values for performance characteristics and scrotal circumference of Brangus cattle. Records of 84,703 Brangus animals, born from 2000 to 2010 distributed in 65 farms in Brazil were used. The characteristics analyzed were average daily gain from birth to weaning and from weaning to yearling (WW and YW), visual scores of conformations (WC and YC), muscle score (WM and YM), precocity score (WP and YS), and size score (WS and YS) at weaning and yearling and scrotal circumference (SC) at yearling. Components of (co)variance estimated through the animal model employing methodology to AIREML. Mean estimates of direct heritability obtained for visual scores at weaning (WC 0.16, WM 0.16, WP 0.19, and WS 0.22) were lower than those obtained at yearling (YC 0.28, YM 0.26, YP 0.24, and YS 0.40). WW had heritability greater than YW (0.27 and 0.12) and a heritability of 0.36 obtained for SC. Canonical, discriminant, and cluster analyses were performed in the SAS® 9.4 program. Three clusters of genetic values averages per farm were formed according to climatic, physical, and socio-economic variables. Brangus animals are from states of RS, PR, SP, MG, GO, MG, and MS. The highest breeding values were strongly related to thermal amplitude and municipality area. Spatial distribution of the breeding value of Brangus animals can help in the development of environmental indices, genetic evaluations, and the choice of animals for certain environments.

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Ecological niche models (ENMs) have classically operated under the simplifying assumptions that there are no barriers to gene flow, species are genetically homogeneous (i.e., no population-specific local adaptation), and all individuals share the same niche. Yet, these assumptions are violated for most broadly distributed species. Here, we incorporate genetic data from the widespread riparian tree species narrowleaf cottonwood (Populus angustifolia) to examine whether including intraspecific genetic variation can alter model performance and predictions of climate change impacts. We found that (1) P. angustifolia is differentiated into six genetic groups across its range from México to Canada and (2) different populations occupy distinct climate niches representing unique ecotypes. Comparing model discriminatory power, (3) all genetically informed ecological niche models (gENMs) outperformed the standard species-level ENM (3-14% increase in AUC; 1-23% increase in pROC). Furthermore, (4) gENMs predicted large differences among ecotypes in both the direction and magnitude of responses to climate change and (5) revealed evidence of niche divergence, particularly for the Eastern Rocky Mountain ecotype. (6) Models also predicted progressively increasing fragmentation and decreasing overlap between ecotypes. Contact zones are often hotspots of diversity that are critical for supporting species' capacity to respond to present and future climate change, thus predicted reductions in connectivity among ecotypes is of conservation concern. We further examined the generality of our findings by comparing our model developed for a higher elevation Rocky Mountain species with a related desert riparian cottonwood, P. fremontii. Together our results suggest that incorporating intraspecific genetic information can improve model performance by addressing this important source of variance. gENMs bring an evolutionary perspective to niche modeling and provide a truly "adaptive management" approach to support conservation genetic management of species facing global change.

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Biogeographic barriers such as rivers have been shown to shape spatial patterns of biodiversity in the Amazon basin, yet relatively little is known about the distribution of genetic variation across continuous rainforest. Here, we characterize the genetic structure of the brilliant-thighed poison frog (Allobates femoralis) across an 880-km-long transect along the Purus-Madeira interfluve south of the Amazon river, based on 64 individuals genotyped at 7609 single-nucleotide polymorphism (SNP) loci. A population tree and clustering analyses revealed 4 distinct genetic groups, one of which was strongly divergent. These genetic groups were concomitant with femoral spot coloration differences, which was intermediate within a zone of admixture between two of the groups. The location of these genetic groups did not consistently correspond to current ecological transitions between major forest types. A multimodel approach to quantify the relative influence of isolation-by-geographic distance (IBD) and isolation-by-environmental resistance (IBR) nevertheless revealed that, in addition to a strong signal of IBD, spatial genetic differentiation was explained by IBR primarily linked to dry season intensity (r2 = 8.4%) and canopy cover (r2 = 6.4%). We show significant phylogenetic divergence in the absence of obvious biogeographical barriers and that finer-scaled measures of genetic structure are associated with environmental variables also known to predict the density of A. femoralis.

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The populations of Humboldtiana durangoensis have experienced a drastic reduction in the effective population size; in addition, the species is threatened by anthropogenic activities. For the aforementioned, landscape genetics will serve as a tool to define the potential evolutionarily significant units (ESU) for this species. To complete our objective, we evaluated the effect of cover vegetation and climate on the functional connectivity of the species from the last glacial maximum (LGM) to the present as well as the effect of climate on shell shape. Partial Mantel tests, distance-based redundance analysis and a Bayesian framework were used to evaluate connectivity. On the other hand, geometric morphometrics, phylogenetic principal component analysis and redundancy analysis were used for the analysis of shell shape. Our results suggest that the suitable areas have been decreasing since the LGM; also, vegetation cover rather than climate has influenced the genetic connectivity among land snail populations, although temperature had a high influence on shell shape in this species. In conclusion, vegetation cover was the main factor that determined the functional connectivity for the land snail; however, local selective pressures led to different phenotypes in shell shape that allowed us to postulate that each one of the previously defined genetic groups must be considered as a different ESU.