Reevaluation of a classic phylogeographic barrier: new techniques reveal the influence of microgeographic climate variation on population divergence

We evaluated the mtDNA divergence and relationships within Geomys pinetis to assess the status of formerly recognized Geomys taxa. Additionally, we integrated new hypothesis‐based tests in ecological niche models (ENM) to provide greater insight into causes for divergence and potential barriers to gene flow in Southeastern United States (Alabama, Florida, and Georgia). Our DNA sequence dataset confirmed and strongly supported two distinct lineages within G. pinetis occurring east and west of the ARD. Divergence date estimates showed that eastern and western lineages diverged about 1.37 Ma (1.9 Ma–830 ka). Predicted distributions from ENMs were consistent with molecular data and defined each population east and west of the ARD with little overlap. Niche identity and background similarity tests were statistically significant suggesting that ENMs from eastern and western lineages are not identical or more similar than expected based on random localities drawn from the environmental background. ENMs also support the hypothesis that the ARD represents a ribbon of unsuitable climate between more suitable areas where these populations are distributed. The estimated age of divergence between eastern and western lineages of G. pinetis suggests that the divergence was driven by climatic conditions during Pleistocene glacial–interglacial cycles. The ARD at the contact zone of eastern and western lineages of G. pinetis forms a significant barrier promoting microgeographic isolation that helps maintain ecological and genetic divergence.     

生态位模型的理论基础、发展方向与挑战

生态位模型是一个以生态位理论为基础的新兴研究领域.它通过采集研究对象的已知分布点及其相关的环境数据组成训练样本,利用数理统计或机器学习理论分析数据,构建特征函数表示物种在生态位空间的实际生态位.以生态位模型预测物种潜在分布地或计算物种间的生态位重叠等研究,在生态学、生物地理学和进化生物学研究中显得越来越重要.本文从生态位概念出发,详细解析了生态位模型的理论基础、相关的焦点争论、使用时的注意点以及可能的发展方向与面临的挑战,指出模型中要考虑人类活动对物种生态位的影响.希望本文所探讨的本领域最新的争论焦点能引起相关学者的关注与深入思考.     

Evaluating,partitioning, and mapping the spatial autocorrelation component in ecological niche modeling: a new approach based on environmentally equidistant records

Most species data display spatial autocorrelation that can affect ecological niche models (ENMs) accuracy‐statistics, affecting its ability to infer geographic distributions. Here we evaluate whether the spatial autocorrelation underlying species data affects accuracy‐statistics and map the uncertainties due to spatial autocorrelation effects on species range predictions under past and future climate models. As an example, ENMs were fitted to Qualea grandiflora (Vochysiaceae), a widely distributed plant from Brazilian Cerrado. We corrected for spatial autocorrelation in ENMs by selecting sampling sites equidistant in geographical (GEO) and environmental (ENV) spaces. Distributions were modelled using 13 ENMs evaluated by two accuracy‐statistics (TSS and AUC), which were compared with uncorrected ENMs. Null models and the similarity statistics I were used to evaluate the effects of spatial autocorrelation. Moreover, we applied a hierarchical ANOVA to partition and map the uncertainties from the time (across last glacial maximum, pre‐insustrial, and 2080 time periods) and methodological components (ENMs and autocorrelation corrections). The GEO and ENV models had the highest accuracy‐statistics values, although only the ENV model had values higher than expected by chance alone for most of the 13 ENMs. Uncertainties from time component were higher in the core region of the Brazilian Cerrado where Q. grandiflora occurs, whereas methodological components presented higher uncertainties in the extreme northern and southern regions of South America (i.e. outside of Brazilian Cerrado). Our findings show that accounting for autocorrelation in environmental space is more efficient than doing so in geographical space. Methodological uncertainties were concentrated in outside the core region of Q. grandiflora's habitat. Conversely, uncertainty due to time component in the Brazilian Cerrado reveals that ENMs were able to capture climate change effects on Q. grandiflora distributions.     

Life History Traits and Niche Instability Impact Accuracy and Temporal Transferability for Historically Calibrated Distribution Models of North American Birds

A primary assumption of environmental niche models (ENMs) is that models are both accurate and transferable across geography or time; however, recent work has shown that models may be accurate but not highly transferable. While some of this is due to modeling technique, individual species ecologies may also underlie this phenomenon. Life history traits certainly influence the accuracy of predictive ENMs, but their impact on model transferability is less understood. This study investigated how life history traits influence the predictive accuracy and transferability of ENMs using historically calibrated models for birds. In this study I used historical occurrence and climate data (1950-1990s) to build models for a sample of birds, and then projected them forward to the ‘future’ (1960-1990s). The models were then validated against models generated from occurrence data at that ‘future’ time. Internal and external validation metrics, as well as metrics assessing transferability, and Generalized Linear Models were used to identify life history traits that were significant predictors of accuracy and transferability. This study found that the predictive ability of ENMs differs with regard to life history characteristics such as range, migration, and habitat, and that the rarity versus commonness of a species affects the predicted stability and overlap and hence the transferability of projected models. Projected ENMs with both high accuracy and transferability scores, still sometimes suffered from over- or under- predicted species ranges. Life history traits certainly influenced the accuracy of predictive ENMs for birds, but while aspects of geographic range impact model transferability, the mechanisms underlying this are less understood.     

Geographic distribution,evolution, and disease importance of species within the Neotropical Anopheles albitarsis Group (Diptera,Culicidae)

The Anopheles albitarsis group of mosquitoes comprises eight recognized species and one mitochondrial lineage. Our knowledge of malaria vectorial importance and the distribution and evolution of these taxa is incomplete. We constructed ecological niche models (ENMs) for these taxa and used hypothesized phylogenetic relationships and ENMs to investigate environmental and ecological divergence associated with speciation events. Two major clades were identified, one north (Clade 1) and one south (Clade 2) of the Amazon River that likely is or was a barrier to mosquito movement. Clade 1 species occur more often in higher average temperature locations than Clade 2 species, and taxon splits within Clade 1 corresponded with a greater divergence of variables related to precipitation than was the case within Clade 2. Comparison of the ecological profiles of sympatric species and sister species support the idea that phylogenetic proximity is related to ecological similarity. Anopheles albitarsis I, An. janconnae, and An. marajoara ENMs had the highest percentage of their predicted suitable habitat overlapping distribution models of Plasmodium falciparum and P. vivax, and warrant additional studies of the transmission potential of these species. Phylogenetic proximity may be related to malaria vectorial importance within the Albitarsis Group.     

Ecological Niche Models using MaxEnt in Google Earth Engine: Evaluation,guidelines and recommendations

Google Earth Engine (GEE) has revolutionized geospatial analyses by fast-processing formerly demanding analyses from multiple research areas. Recently, maximum entropy (MaxEnt), the most commonly used method in ecological niche models (ENMs), was integrated into GEE. This integration can significantly enhance modeling efficiency and encourage multidisciplinary approaches of ENMs, but an evaluation assessment of MaxEnt in GEE is lacking. Herein, we present the first MaxEnt models in GEE, as well as its first statistical and spatial evaluation. We also identify the limitations of the approach, providing guidelines and recommendations for its easier applicability in GEE.We tested MaxEnt in GEE using 11 case studies. For each case, we used species of different taxa (insects, amphibians, reptiles, birds and mammals) distributed across global and regional extents. Each species occupied habitats with distinct environmental characteristics (nine terrestrial and two marine species) and within divergent ecoregions across five continents. The models were performed in GEE and Maxent software, and both approaches were contrasted for their model discrimination performance (assessed by eight evaluation metrics) and spatial consistency (correlation analyses and two measures of niche overlap/equivalency).MaxEnt in GEE allows setting several parameters, but important analyses and outputs are unavailable, such as automatic selection of background data, model replicates, and analyses of variable importance (concretely, jackknife analyses and response curves). GEE provided MaxEnt models with high discrimination performance (area under the curve mean between all species models of 0.90) and with spatial equivalency in relation to Maxent software outputs (Hellinger's I mean between all species models >0.90).Our work demonstrates the first application and assessment of MaxEnt in GEE at global and regional scales. We conclude that the GEE modeling method provides ENMs with high performance and reliable spatial predictions, comparable to the widely used Maxent software. We also acknowledge important limitations that should be integrated into GEE in the future, particularly those related to the assessment of variable importance. We expect that our guidelines, recommendations and potential solutions to surpass the identified limitations could help researchers easily apply MaxEnt in GEE across different research fields.     

Mapping the Potential Risk of Mycetoma Infection in Sudan and South Sudan Using Ecological Niche Modeling

In 2013, the World Health Organization (WHO) recognized mycetoma as one of the neglected tropical conditions due to the efforts of the mycetoma consortium. This same consortium formulated knowledge gaps that require further research. One of these gaps was that very few data are available on the epidemiology and transmission cycle of the causative agents. Previous work suggested a soil-borne or Acacia thorn-prick-mediated origin of mycetoma infections, but no studies have investigated effects of soil type and Acacia geographic distribution on mycetoma case distributions. Here, we map risk of mycetoma infection across Sudan and South Sudan using ecological niche modeling (ENM). For this study, records of mycetoma cases were obtained from the scientific literature and GIDEON; Acacia records were obtained from the Global Biodiversity Information Facility. We developed ENMs based on digital GIS data layers summarizing soil characteristics, land-surface temperature, and greenness indices to provide a rich picture of environmental variation across Sudan and South Sudan. ENMs were calibrated in known endemic districts and transferred countrywide; model results suggested that risk is greatest in an east-west belt across central Sudan. Visualizing ENMs in environmental dimensions, mycetoma occurs under diverse environmental conditions. We compared niches of mycetoma and Acacia trees, and could not reject the null hypothesis of niche similarity. This study revealed contributions of different environmental factors to mycetoma infection risk, identified suitable environments and regions for transmission, signaled a potential mycetoma-Acacia association, and provided steps towards a robust risk map for the disease.     

Impacts of engineered nanomaterials on microbial community structure and function in natural and engineered ecosystems

In natural and engineered environments, microorganisms often exist as complex communities, which are key to the health of ecosystems and the success of bioprocesses in various engineering applications. With the rapid development of nanotechnology in recent years, engineered nanomaterials (ENMs) have been considered one type of emerging contaminants that pose great potential risks to the proper function of microbial communities in natural and engineered ecosystems. The impacts of ENMs on microorganisms have attracted increasing research attentions; however, most studies focused on the antimicrobial activities of ENMs at single cell and population level. Elucidating the influence of ENMs on microbial communities represents a critical step toward a comprehensive understanding of the ecotoxicity of ENMs. In this mini-review, we summarize and discuss recent research work on the impacts of ENMs on microbial communities in natural and engineered ecosystems, with an emphasis on their influences on the community structure and function. We also highlight several important research topics which may be of great interest to the research community.     

Colonization from divergent ancestors: glaciation signatures on contemporary patterns of genomic variation in Collared Pikas (Ochotona collaris)

Identifying the genetic structure of a species and the factors that drive it is an important first step in modern population management, in part because populations evolving from separate ancestral sources may possess potentially different characteristics. This is especially true for climate‐sensitive species such as pikas, where the delimitation of distinct genetic units and the characterization of population responses to contemporary and historical environmental pressures are of particular interest. We combined a restriction site‐associated DNA sequencing (RADSeq) data set containing 4156 single nucleotide polymorphisms with ecological niche models (ENMs) of present and past habitat suitability to characterize population composition and evaluate the effects of historical range shifts, contemporary climates and landscape factors on gene flow in Collared Pikas, which are found in Alaska and adjacent regions of northwestern Canada and are the lesser‐studied of North America's two pika species. The results suggest that contemporary environmental factors contribute little to current population connectivity. Instead, genetic diversity is strongly shaped by the presence of three ancestral lineages isolated during the Pleistocene (~148 and 52 kya). Based on ENMs and genetic data, populations originating from a northern refugium experienced longer‐term stability, whereas both southern lineages underwent population expansion – contradicting the southern stability and northern expansion patterns seen in many other taxa. Current populations are comparable with respect to generally low diversity within populations and little‐to‐no recent admixture. The predominance of divergent histories structuring populations implies that if we are to understand and manage pika populations, we must specifically assess and accurately account for the forces underlying genetic similarity.     

Influence of late Quaternary climate change on present patterns of genetic variation in valley oak,Quercus lobata Née

Phylogeography and ecological niche models (ENMs) suggest that late Quaternary glacial cycles have played a prominent role in shaping present population genetic structure and diversity, but have not applied quantitative methods to dissect the relative contribution of past and present climate vs. other forces. We integrate multilocus phylogeography, climate‐based ENMs and multivariate statistical approaches to infer the effects of late Quaternary climate change on contemporary genetic variation of valley oak (Quercus lobata Née). ENMs indicated that valley oak maintained a stable distribution with local migration from the last interglacial period (~120 ka) to the Last Glacial Maximum (~21 ka, LGM) to the present compared with large‐scale range shifts for an eastern North American white oak (Quercus alba L.). Coast Range and Sierra Nevada foothill populations diverged in the late Pleistocene before the LGM [104 ka (28–1622)] and have occupied somewhat distinct climate niches, according to ENMs and coalescent analyses of divergence time. In accordance with neutral expectations for stable populations, nuclear microsatellite diversity positively correlated with niche stability from the LGM to present. Most strikingly, nuclear and chloroplast microsatellite variation significantly correlated with LGM climate, even after controlling for associations with geographic location and present climate using partial redundancy analyses. Variance partitioning showed that LGM climate uniquely explains a similar proportion of genetic variance as present climate (16% vs. 11–18%), and together, past and present climate explains more than geography (19%). Climate can influence local expansion–contraction dynamics, flowering phenology and thus gene flow, and/or impose selective pressures. These results highlight the lingering effect of past climate on genetic variation in species with stable distributions.     

Ecological niche models in phylogeographic studies: applications,advances and precautions

The increased availability of spatial data and methodological developments in species distribution modelling has lead to concurrent advances in phylogeography, broadening the scope of questions studied, as well as providing unprecedented insights. Given the species‐specific nature of the information provided by ecological niche models (ENMs), whether it is on the environmental tolerances of species or their estimated distribution, today or in the past, it is perhaps not surprising that ENMs have rapidly become a common tool in phylogeographic analysis. Such information is essential to phylogeographic tests that provide important biological insights. Here, we provide an overview of the different applications of ENMs in phylogeographic studies, detailing specific studies and highlighting general limitations and challenges with each application. Given that the full potential of integrating ENMs into phylogeographic cannot be realized unless the ENMs themselves are carefully applied, we provide a summary of best practices with using ENMs. Lastly, we describe some recent advances in how quantitative information from ENMs can be integrated into genetic analyses, illustrating their potential use (and key concerns with such implementations), as well as promising areas for future development.     

Niche shift versus niche conservatism? Climatic characteristics of the native and invasive ranges of the Mediterranean house gecko (Hemidactylus turcicus)

Aim The use of ecological niche models (ENMs) to predict potential distributions of species is steadily increasing. A necessary assumption is that climatic niches are conservative, but recent findings of niche shifts during biological invasion indicate that this assumption is not always valid. Selection of predictor variables may be one reason for the observed shifts. In this paper we assess differences in climatic niches in the native and invaded ranges of the Mediterranean house gecko (Hemidactylus turcicus) in terms of commonly applied climate variables in ENMs. We analyse which variables are more conserved versus relaxed (i.e. subject to niche shift). Furthermore, we study the predictive power of different sets of climate variables. Location The Mediterranean region and North America. Methods We developed models using Maxent and various subsets of variables out of 19 bioclimatic layers including: (1) two subsets comprising almost all variables excluding only highly collinear ones; (2) two subsets with minimalistic variable sets of water availability and energy measures; (3) two subsets focused on temperature‐related parameters; (4) two subsets with precipitation‐related parameters; and (5) one subset comprising variables combining temperature and precipitation characteristics. Occurrence data from the native Mediterranean range were used to predict the potential introduced range in North America and vice versa. Degrees of niche similarity and conservatism were assessed using both Schoener's index and Hellinger distances. The significance of the results was tested using null models. Results The degree of niche similarity and conservatism varied greatly among the predictors and variable sets applied. Shifts observed in some variables could be attributed to active habitat selection while others apparently reflected background effects. Main conclusions The study was based on comprehensive occurrence data from all regions where Hemidactylus turcicus is present in Europe and North America, providing a robust foundation. Our results clearly indicate that the degree of conservatism of niches in H. turcicus largely varies among predictors and variable sets applied. Therefore, the extent of niche conservatism of variables applied should always be tested in ENMs. This has an important impact on studies of biological invasion, impacts of climate change and niche evolution.     

Ecological niche modeling re‐examined: A case study with the Darwin's fox

Many previous studies have attempted to assess ecological niche modeling performance using receiver operating characteristic (ROC) approaches, even though diverse problems with this metric have been pointed out in the literature. We explored different evaluation metrics based on independent testing data using the Darwin's Fox (Lycalopex fulvipes) as a detailed case in point. Six ecological niche models (ENMs; generalized linear models, boosted regression trees, Maxent, GARP, multivariable kernel density estimation, and NicheA) were explored and tested using six evaluation metrics (partial ROC, Akaike information criterion, omission rate, cumulative binomial probability), including two novel metrics to quantify model extrapolation versus interpolation (E‐space index I) and extent of extrapolation versus Jaccard similarity (E‐space index II). Different ENMs showed diverse and mixed performance, depending on the evaluation metric used. Because ENMs performed differently according to the evaluation metric employed, model selection should be based on the data available, assumptions necessary, and the particular research question. The typical ROC AUC evaluation approach should be discontinued when only presence data are available, and evaluations in environmental dimensions should be adopted as part of the toolkit of ENM researchers. Our results suggest that selecting Maxent ENM based solely on previous reports of its performance is a questionable practice. Instead, model comparisons, including diverse algorithms and parameterizations, should be the sine qua non for every study using ecological niche modeling. ENM evaluations should be developed using metrics that assess desired model characteristics instead of single measurement of fit between model and data. The metrics proposed herein that assess model performance in environmental space (i.e., E‐space indices I and II) may complement current methods for ENM evaluation.     

Habitat differentiation among three Nigeria–Cameroon chimpanzee (Pan troglodytes ellioti) populations

Ecological niche models (ENMs) are often used to predict species distribution patterns from datasets that describe abiotic and biotic factors at coarse spatial scales. Ground‐truthing ENMs provide important information about how these factors relate to species‐specific requirements at a scale that is biologically relevant for the species. Chimpanzees are territorial and have a predominantly frugivorous diet. The spatial and temporal variation in fruit availability for different chimpanzee populations is thus crucial, but rarely depicted in ENMs. The genetic and geographic distinction within Nigeria–Cameroon chimpanzee (Pan troglodytes ellioti) populations represents a unique opportunity to understand fine scale species‐relevant ecological variation in relation to ENMs. In Cameroon, P. t. ellioti is composed of two genetically distinct populations that occupy different niches: rainforests in western Cameroon and forest–woodland–savanna mosaic (ecotone) in central Cameroon. We investigated habitat variation at three representative sites using chimpanzee‐relevant environmental variables, including fruit availability, to assess how these variables distinguish these niches from one another. Contrary to the assumption of most ENM studies that intact forest is essential for the survival of chimpanzees, we hypothesized that the ecotone and human‐modified habitats in Cameroon have sufficient resources to sustain large chimpanzee populations. Rainfall, and the diversity, density, and size of trees were higher at the rainforest. The ecotone had a higher density of terrestrial herbs and lianas. Fruit availability was higher at Ganga (ecotone) than at Bekob and Njuma. Seasonal variation in fruit availability was highest at Ganga, and periods of fruit scarcity were longer than at the rainforest sites. Introduced and secondary forest species linked with anthropogenic modification were common at Bekob, which reduced seasonality in fruit availability. Our findings highlight the value of incorporating fine scale species‐relevant ecological data to create more realistic models, which have implications for local conservation planning efforts.     

生态位模型在流行病学中的应用

随着新冠肺炎(COVID-19)疫情在全球逐渐开始蔓延, 对其传播范围以及强度的风险评估工作越来越受到人们的重视。作为生态学和生物地理学中常用的研究手段, 生态位模型也被应用到该项工作中来。虽然预测流行病的传播热点和趋势是生态位模型的应用方向之一, 但由于新冠病毒(SARS-CoV-2)自身特点, 生态位模型并非预测其潜在传播范围的有力工具。本文回顾了近些年来生态位模型在各种流行病学研究中的应用, 比较了疫病传播中常用生态位建模方法的优势与不足, 分析了适用生态位建模的疫病案例以及不适用于生态位建模的疫病特点, 明确指出, 生态位模型只能用于分析流行病在传播过程中受自然环境干扰的部分, 如中间宿主的潜在分布等。而对于包括COVID-19在内的主要通过人传人的流行病, 生态位模型尚无有效的手段进行预测。尽管生态位模型可用于分析流行病的传播范围, 但在使用时需要根据疾病特点有针对性地选择合适的建模方法与建模对象。为了量化疫病传播风险, 还需要考虑其他干扰因素, 以便准确测试和评估生态位模型。若不加选择地滥用生态位模型的工具, 反而会误导决策者的判断。总之, 在应用生态位模型进行研究工作, 特别是预测流行病的传播范围时, 首先要考虑建模对象是否满足生态学假设。     

Identifying Pleistocene refugia in North American cold deserts using phylogeographic analyses and ecological niche modelling

Aim We analysed phylogeographic patterns and ecological niche models (ENMs) of the widespread velvet ant (Hymenoptera: Mutillidae) Sphaeorpthalma difficilis to understand the history of diversification in the Nearctic deserts and to identify areas that may have been cold‐desert refugia during the Pleistocene. These areas should be targeted for conservation because of their climatic stability throughout historical climate change events. Location North American arid regions. Methods The two internal transcribed spacer regions (ITS1 and ITS2) were sequenced and analysed using Bayesian techniques to uncover phylogeographic patterns of relatedness among S. difficilis populations. History of diversification was estimated using parsimony‐based and maximum likelihood character reconstructions. Molecular dating analyses were implemented in the program r8s and were calibrated with Dominican amber fossils. ENMs were developed based on current climate data and projected onto Pleistocene climate surfaces. Results The analyses suggest that S. difficilis had a complex history of Pleistocene range expansion and contraction that led to the formation of genetically distinct populations inhabiting distinct arid regions. ENMs and phylogeographic patterns indicate that several cold‐desert refugia existed in North America, particularly in the Colorado Plateau and parts of the Great Basin Desert. Main conclusions Analyses of S. difficilis are used to identify potential Pleistocene refugia in the North American cold deserts. Because these areas represent climatically stable locations, they are critical for the long‐term persistence of biodiversity. This research provides evidence that in addition to desert‐like conditions persisting through the ice age in parts of the Nearctic warm deserts, many areas maintained desert‐like characteristics in the regional cold deserts. Further work is needed to elucidate options for preserving biodiversity in these cold‐desert refugia.     

Acute Effects of TiO2 Nanomaterials on the Viability and Taxonomic Composition of Aquatic Bacterial Communities Assessed via High-Throughput Screening and Next Generation Sequencing

The nanotechnology industry is growing rapidly, leading to concerns about the potential ecological consequences of the release of engineered nanomaterials (ENMs) to the environment. One challenge of assessing the ecological risks of ENMs is the incredible diversity of ENMs currently available and the rapid pace at which new ENMs are being developed. High-throughput screening (HTS) is a popular approach to assessing ENM cytotoxicity that offers the opportunity to rapidly test in parallel a wide range of ENMs at multiple concentrations. However, current HTS approaches generally test one cell type at a time, which limits their ability to predict responses of complex microbial communities. In this study toxicity screening via a HTS platform was used in combination with next generation sequencing (NGS) to assess responses of bacterial communities from two aquatic habitats, Lake Michigan (LM) and the Chicago River (CR), to short-term exposure in their native waters to several commercial TiO₂ nanomaterials under simulated solar irradiation. Results demonstrate that bacterial communities from LM and CR differed in their sensitivity to nano-TiO₂, with the community from CR being more resistant. NGS analysis revealed that the composition of the bacterial communities from LM and CR were significantly altered by exposure to nano-TiO₂, including decreases in overall bacterial diversity, decreases in the relative abundance of Actinomycetales, Sphingobacteriales, Limnohabitans, and Flavobacterium, and a significant increase in Limnobacter. These results suggest that the release of nano-TiO₂ to the environment has the potential to alter the composition of aquatic bacterial communities, which could have implications for the stability and function of aquatic ecosystems. The novel combination of HTS and NGS described in this study represents a major advance over current methods for assessing ENM ecotoxicity because the relative toxicities of multiple ENMs to thousands of naturally occurring bacterial species can be assessed simultaneously under environmentally relevant conditions.     

Profound climatic effects on two East Asian black-throated tits (Ave: Aegithalidae), revealed by ecological niche models and phylogeographic analysis

Although a number of studies have assessed the effects of geological and climatic changes on species distributions in East Asian, we still have limited knowledge of how these changes have impacted avian species in south-western and southern China. Here, we aim to study paleo-climatic effects on an East Asian bird, two subspecies of black-throated tit (A. c. talifuensis-concinnus) with the combined analysis of phylogeography and Ecological Niche Models (ENMs). We sequenced three mitochondrial DNA markers from 32 populations (203 individuals) and used phylogenetic inferences to reconstruct the intra-specific relationships among haplotypes. Population genetic analyses were undertaken to gain insight into the demographic history of these populations. We used ENMs to predict the distribution of target species during three periods; last inter-glacial (LIG), last glacial maximum (LGM) and present. We found three highly supported, monophyletic MtDNA lineages and different historical demography among lineages in A. c. talifuensis-concinnus. These lineages formed a narrowly circumscribed intra-specific contact zone. The estimated times of lineage divergences were about 2.4 Ma and 0.32 Ma respectively. ENMs predictions were similar between present and LGM but substantially reduced during LIG. ENMs reconstructions and molecular dating suggest that Pleistocene climate changes had triggered and shaped the genetic structure of black-throated tit. Interestingly, in contrast to profound impacts of other glacial cycles, ENMs and phylogeographic analysis suggest that LGM had limited effect on these two subspecies. ENMs also suggest that Pleistocene climatic oscillations enabled the formation of the contact zone and thus support the refuge theory.     

Predicting the distribution of Sasquatch in western North America: anything goes with ecological niche modelling

The availability of user-friendly software and publicly available biodiversity databases has led to a rapid increase in the use of ecological niche modelling to predict species distributions. A potential source of error in publicly available data that may affect the accuracy of ecological niche models (ENMs), and one that is difficult to correct for, is incorrect (or incomplete) taxonomy. Here we remind researchers of the need for careful evaluation of database records prior to use in modelling, especially when the presence of cryptic species is suspected or many records are based on indirect evidence. To draw attention to this potential problem, we construct ENMs for the North American Sasquatch (i.e. Bigfoot). Specifically, we use a large database of georeferenced putative sightings and footprints for Sasquatch in western North America, demonstrating how convincing environmentally predicted distributions of a taxon's potential range can be generated from questionable site-occurrence data. We compare the distribution of Bigfoot with an ENM for the black bear, Ursus americanus , and suggest that many sightings of this cryptozoid may be cases of mistaken identity.     

Environmental (in)dependence of a hybrid zone: Insights from molecular markers and ecological niche modeling in a hybrid zone of Origanum (Lamiaceae) on the island of Crete

The role of environment and the relative significance of endogenous versus exogenous selection in shaping hybrid zones have been crucial issues in the studies of hybridization. Recent advances in ecological niche modeling (ENM) offer new methodological tools, especially in combination with the genotyping of individuals in the hybrid zone. Here, we study the hybrid zone between the widely known spices Origanum onites and Origanum vulgare ssp. hirtum in Crete. We analyze the genetic structure of both parental taxa and their hybrid Origanum × intercendens using AFLP markers on 15 sympatric and 12 allopatric populations and employ ecological niche modeling and niche similarity tests to study their niche patterns. We complement these analyses with seed viability measurements. Our study revealed that the hybridizing taxa O. onites and O. vulgare ssp. hirtum and the resulting genotypic classes showed geographical and environmental niche similarities based on the predictions of ENMs and the subsequent similarity tests. The occurrence of the hybrid zone is not directly dependent on environmental factors which favor the fitness of the hybrid compared to the parental taxa, but rather on aspects such as historical factors and management practices, which may contribute to the localization and maintenance of the contact zone between parental species. Our results suggest that if a minimum required niche differentiation between genotypic classes is not achieved, environmental dependence might not have a prominent role on the outcome of the hybridization.