Combining Bayesian genetic clustering and ecological niche modeling: Insights into wolf intraspecific genetic structure

Genetic structure and climate niche differentiation among populations of Leopardus geoffroyi

Geoffroy's cat (Leopardus geoffroyi) is a small-sized felid native to South America. Given the species' distribution covering a wide variety of habitats, and the presence of high levels of anthropization in part of its range, it is possible that genetically differentiated groups exist and that they occupy different climatic niches. We assessed patterns of contemporary genetic diversity and structure in the species across most of its range, characterizing each inferred genetic group based on ecological niche models. We genotyped 11 microsatellites for 142 samples covering most of Geoffroy's cat distribution, and investigated patterns of genetic structure and diversity, applying spatial and nonspatial Bayesian clustering methods and a spatial principal component analysis. We created ecological niche models for each genetic cluster, evaluating whether these clusters occupy different climatic spaces and display differences in the suitability of different values of the climatic variables analyzed. We identified two genetic clusters, one in the north-northeast and the other in the south-southwest of the species' distribution. These clusters showed moderate FST values between them and differences in dispersal/genetic diversity. We found isolation-by-distance patterns globally and within each cluster. We observed lower expected heterozygosity compared with other studies and a north-south gradient in allelic richness. The southern cluster showed lower genetic variability and a more restricted climatic niche suggesting that this group is more vulnerable to the effects of the current context of climate change. Individuals from the southern genetic cluster are under different pressures, likely a product of the particularly dry habitat they occupy. Climatic variables associated with habitat suitability suggest the southern cluster has affinity for the arid and semiarid conditions present in its distribution. Conservation measures should consider the genetic structure observed and differences in climatic spaces to maintain the evolutionary potential of the species.

Spatial and temporal patterns in the population genomics of the European cockchafer Melolontha melolontha in the Alpine region

The European cockchafer Melolontha melolontha is an agricultural pest in many European countries. Populations have a synchronized 3 or 4 years life cycle, leading to temporally isolated populations. Despite the economic importance and availability of comprehensive historical as well as current records on cockchafer occurrence, population genomic analyses of M. melolontha are missing. For example, the effects of geographic separation caused by the mountainous terrain of the Alps and of temporal isolation on the genomic structure of M. melolontha still remain unknown. To address this gap, we genotyped 475 M. melolontha adults collected during 3 years from 35 sites in a central Alpine region. Subsequent population structure analyses discriminated two main genetic clusters, i.e., the South Tyrol cluster including collections located southeast of the Alpine mountain range, and a northwestern alpine cluster with all the other collections, reflecting distinct evolutionary history and geographic barriers. The "passo di Resia" linking South and North Tyrol represented a regional contact zone of the two genetic clusters, highlighting genomic differentiation between the collections from the northern and southern regions. Although the collections from northwestern Italy were assigned to the northwestern alpine genetic cluster, they displayed evidence of admixture with the South Tyrolean genetic cluster, suggesting shared ancestry. A linear mixed model confirmed that both geographic distance and, to a lower extent, also temporal isolation had a significant effect on the genetic distance among M. melolontha populations. These effects may be attributed to limited dispersal capacity and reproductive isolation resulting from synchronized and non-synchronized swarming flights, respectively. This study contributes to the understanding of the phylogeography of an organism that is recognized as an agricultural problem and provides significant information on the population genomics of insect species with prolonged temporally shifted and locally synchronized life cycles.

Unravelling plant diversification: Intraspecific genetic differentiation in hybridizing Anacyclus species in the western Mediterranean Basin

PREMISE

The interfertile species Anacyclus clavatus, A. homogamos, and A. valentinus represent a plant complex coexisting in large anthropic areas of the western Mediterranean Basin with phenotypically mixed populations exhibiting a great floral variation. The goal of this study was to estimate the genetic identity of each species, to infer the role of hybridization in the observed phenotypic diversity, and to explore the effect of climate on the geographic distribution of species and genetic clusters.

METHODS

We used eight nuclear microsatellites to genotype 585 individuals from 31 populations of three Anacyclus species for population genetic analyses by using clustering algorithms based on Bayesian models and ordination methods. In addition, we used ecological niche models and niche overlap analyses for both the species and genetic clusters. We used an expanded data set, including 721 individuals from 129 populations for ecological niche models of the genetic clusters.

RESULTS

We found a clear correspondence between species and genetic clusters, except for A. clavatus that included up to three genetic clusters. We detected individuals with admixed genetic ancestry in A. clavatus and in mixed populations. Ecological niche models predicted similar distributions for species and genetic clusters. For the two specific genetic clusters of A. clavatus, ecological niche models predicted remarkably different areas.

CONCLUSIONS

Gene flow between Anacyclus species likely explains phenotypic diversity in contact areas. In addition, we suggest that introgression could be involved in the origin of one of the two A. clavatus genetic clusters, which also showed ecological differentiation.

Ecological niche models reveal divergent habitat use of Pallas's cat in the Eurasian cold steppes

Identifying the association between the patterns of niche occupation and phylogenetic relationships among sister clades and assisting conservation planning implications are of the most important applications of species distribution models (SDMs). However, most studies have been carried out regardless of within taxon genetic differentiation and the potential of local adaptation occurring within the species level. The Pallas's cat (Otocolobus manul) is a less-studied species with unknown biogeography and phylogenetic structure across a widespread yet isolated range from the Caucasus to eastern China. In the current study, by considering a previously proposed genetic structure and based on a cluster analysis on climatic variables, we supposed three clades for this species, including O. m. manul, O. m. ferrugineus, and O. m. nigripectus. We developed SDM for each clade separately and compared it with a general distribution model of the species to determine whether the hypothesized taxonomic resolution affects the predicted ecological niche of the within-species structures. We assessed the effect of climate change on the future distribution of the species to detect the most sensitive clades to global warming scenarios. Our results showed that for all clades' models, the AUC and TSS were greater than the general model. Access to the preferred prey of the Pallas's cat, that is, pika, had a significant effect on the distribution of O. m. manul and O. m. ferrugineus, whereas the most influential variable affecting O. m. nigripectus habitat suitability was terrain slope. Based on our future projections, we found that future climate change likely threatens the clades O. m. ferrugineus and O. m. nigripectus more than O. m. manul, findings that were hidden in the general model. Our results highlight the proficiency of SDMs in recognizing within-taxon habitat use of widespread species and the necessity of this procedure for implementing effective conservation planning of these species.

Modeling of the Potential Geographical Distribution of Three Fritillaria Species Under Climate Change

Fritillaria species, a well-known Chinese traditional medicine for more than 2,000 years, have become rare resources due to excessive harvesting. In order to balance the economical requirement and ecological protection of Fritillaria species, it is necessary to determine (1) the important environmental variables that were responsible for the spatial distribution, (2) distribution change in response to climate change in the future, (3) ecological niche overlap between various Fritillaria species, and (4) the correlation between spatial distribution and phylogenies as well. In this study, the areas with potential ecological suitability for Fritillaria cirrhosa, Fritillaria unibracteata, and Fritillaria przewalskii were predicted using MaxEnt based on the current occurrence records and bioclimatic variables. The result indicated that precipitation and elevation were the most important environmental variables for the three species. Moreover, the current suitable habitats of F. cirrhosa, F. unibracteata, and F. przewalskii encompassed 681,951, 481,607, and 349,199 km2, respectively. Under the scenario of the highest concentration of greenhouse gas emission (SSP585), the whole suitable habitats of F. cirrhosa and F. przewalskii reach the maximum from 2021 to 2100, while those of F. unibracteata reach the maximum from 2021 to 2100 under the scenario of moderate emission (SSP370) from 2021 to 2100. The MaxEnt data were also used to predict the ecological niche overlap, and thus high overlap occurring among three Fritillaria species was observed. The niche overlap of three Fritillaria species was related to the phylogenetic analysis despite the non-significance (P > 0.05), indicating that spatial distribution was one of the factors that contributed to the speciation diversification. Additionally, we predicted species-specific habitats to decrease habitat competition. Overall, the information obtained in this study provided new insight into the potential distribution and ecological niche of three species for the conservation and management in the future.

A hierarchical Bayesian Beta regression approach to study the effects of geographical genetic structure and spatial autocorrelation on species distribution range shifts

Global climate change (GCC) may be causing distribution range shifts in many organisms worldwide. Multiple efforts are currently focused on the development of models to better predict distribution range shifts due to GCC. We addressed this issue by including intraspecific genetic structure and spatial autocorrelation (SAC) of data in distribution range models. Both factors reflect the joint effect of ecoevolutionary processes on the geographical heterogeneity of populations. We used a collection of 301 georeferenced accessions of the annual plant Arabidopsis thaliana in its Iberian Peninsula range, where the species shows strong geographical genetic structure. We developed spatial and nonspatial hierarchical Bayesian models (HBMs) to depict current and future distribution ranges for the four genetic clusters detected. We also compared the performance of HBMs with Maxent (a presence-only model). Maxent and nonspatial HBMs presented some shortcomings, such as the loss of accessions with high genetic admixture in the case of Maxent and the presence of residual SAC for both. As spatial HBMs removed residual SAC, these models showed higher accuracy than nonspatial HBMs and handled the spatial effect on model outcomes. The ease of modelling and the consistency among model outputs for each genetic cluster was conditioned by the sparseness of the populations across the distribution range. Our HBMs enrich the toolbox of software available to evaluate GCC-induced distribution range shifts by considering both genetic heterogeneity and SAC, two inherent properties of any organism that should not be overlooked.