Ecological niche variation in the Wilson's warbler Cardellina pusilla complex

Wilson's warbler comprises three subspecies separated into two geographic groups: C. p. pusilla that breeds in eastern North America; and C. p. pileolata and C. p. chryseola that breed in western North America. Given the differences between the groups in genetics, morphology, habitat use, and population decline, we tested for ecological niche similarity in both their breeding and wintering distribution using niche modeling based on temperature and precipitation data. We first conducted an inter‐prediction approach considering the percent of summer and winter localities of one group that are predicted by the potential distribution of the alternate group. We also applied a null model approach that compares self‐predictions and pseudoreplicates of each group to indicate similarity, divergence, or indeterminate niche overlap. Finally, we compared ecological distances between and within groups using the Gower similarity equation. We found that the western group had an ecological niche of broader climatic conditions, while the eastern group had a narrower ecological niche. The inter‐prediction approach showed that, for both summering and wintering ranges, ecological niche models of the western group predicted ～50% of the observed distribution of the eastern group, whereas eastern group models predicted < 18% of the western group distribution. The null model approach found that similarity in ecological niches was indeterminate, possibly due to the large area occupied by the two groups; but it suggests a more restricted set of climatic conditions of the eastern group distribution. However, the Gower coefficients demonstrated that the ecological distance between the two geographic groups was larger than the ecological distance within groups, indicating distinct ecological niches. Overall, our results support the hypothesis that the eastern and western groups of Wilson's warbler are two cryptic species; this should be taken into consideration for future analyses, particularly with respect to vulnerability categorization and conservation efforts.     

提高生态位模型转移能力来模拟入侵物种 的潜在分布

生态位模型利用物种分布点所关联的环境变量去推算物种的生态需求, 模拟物种的分布。在模拟入侵物种分布时, 经典生态位模型包括模型构建于物种本土分布地, 然后将其转移并投射至另一地理区域, 来模拟入侵物种的潜在分布。然而在模型运用时, 出现了模型的转移能力较低、模拟的结果与物种的实际分布不相符的情况, 由此得出了生态位漂移等不恰当的结论。提高生态位模型的转移能力, 可以准确地模拟入侵物种的潜在分布, 为入侵种的风险评估提供参考。作者以入侵种茶翅蝽(Halyomorpha halys)和互花米草(Spartina alterniflora)为例, 从模型的构建材料(即物种分布点和环境变量)入手, 全面阐述提高模型转移能力的策略。在构建模型之前, 需要充分了解入侵物种的生物学特性、种群平衡状态、本土地理分布范围及物种的生物历史地理等方面的知识。在模型构建环节上, 物种分布点不仅要充分覆盖物种的地理分布和生态空间的范围, 同时要降低物种采样点偏差; 环境变量的选择要充分考虑其对物种分布的限制作用、各环境变量之间的空间相关性, 以及不同地理种群间生态空间是否一致, 同时要降低环境变量的空间维度; 模型构建区域要真实地反映物种的地理分布范围, 并考虑种群的平衡状态。作者认为, 在生态位保守的前提下, 如果模型是构建在一个合理方案的基础上, 生态位模型的转移能力是可以保证的, 在以模型转移能力较低的现象来阐述生态位分化时需要引起注意。     

Alien Invasive Slider Turtle in Unpredicted Habitat: A Matter of Niche Shift or of Predictors Studied?

Background

Species Distribution Models (SDMs) aim on the characterization of a species'' ecological niche and project it into geographic space. The result is a map of the species'' potential distribution, which is, for instance, helpful to predict the capability of alien invasive species. With regard to alien invasive species, recently several authors observed a mismatch between potential distributions of native and invasive ranges derived from SDMs and, as an explanation, ecological niche shift during biological invasion has been suggested. We studied the physiologically well known Slider turtle from North America which today is widely distributed over the globe and address the issue of ecological niche shift versus choice of ecological predictors used for model building, i.e., by deriving SDMs using multiple sets of climatic predictor.

Principal Findings

In one SDM, predictors were used aiming to mirror the physiological limits of the Slider turtle. It was compared to numerous other models based on various sets of ecological predictors or predictors aiming at comprehensiveness. The SDM focusing on the study species'' physiological limits depicts the target species'' worldwide potential distribution better than any of the other approaches.

Conclusion

These results suggest that a natural history-driven understanding is crucial in developing statistical models of ecological niches (as SDMs) while “comprehensive” or “standard” sets of ecological predictors may be of limited use.     

Consensus Forecasting of Species Distributions: The Effects of Niche Model Performance and Niche Properties

Ensemble forecasting is advocated as a way of reducing uncertainty in species distribution modeling (SDM). This is because it is expected to balance accuracy and robustness of SDM models. However, there are little available data regarding the spatial similarity of the combined distribution maps generated by different consensus approaches. Here, using eight niche-based models, nine split-sample calibration bouts (or nine random model-training subsets), and nine climate change scenarios, the distributions of 32 forest tree species in China were simulated under current and future climate conditions. The forecasting ensembles were combined to determine final consensual prediction maps for target species using three simple consensus approaches (average, frequency, and median [PCA]). Species’ geographic ranges changed (area change and shifting distance) in response to climate change, but the three consensual projections did not differ significantly with respect to how much or in which direction, but they did differ with respect to the spatial similarity of the three consensual predictions. Incongruent areas were observed primarily at the edges of species’ ranges. Multiple stepwise regression models showed the three factors (niche marginality and specialization, and niche model accuracy) to be related to the observed variations in consensual prediction maps among consensus approaches. Spatial correspondence among prediction maps was the highest when niche model accuracy was high and marginality and specialization were low. The difference in spatial predictions suggested that more attention should be paid to the range of spatial uncertainty before any decisions regarding specialist species can be made based on map outputs. The niche properties and single-model predictive performance provide promising insights that may further understanding of uncertainties in SDM.     

Coarse-resolution Ecology of Etiological Agent,Vector, and Reservoirs of Zoonotic Cutaneous Leishmaniasis in Libya

Cutaneous leishmaniasis ranks among the tropical diseases least known and most neglected in Libya. World Health Organization reports recognized associations of Phlebotomus papatasi, Psammomys obesus, and Meriones spp., with transmission of zoonotic cutaneous leishmaniasis (ZCL; caused by Leishmania major) across Libya. Here, we map risk of ZCL infection based on occurrence records of L. major, P. papatasi, and four potential animal reservoirs (Meriones libycus, Meriones shawi, Psammomys obesus, and Gerbillus gerbillus). Ecological niche models identified limited risk areas for ZCL across the northern coast of the country; most species associated with ZCL transmission were confined to this same region, but some had ranges extending to central Libya. All ENM predictions were significant based on partial ROC tests. As a further evaluation of L. major ENM predictions, we compared predictions with 98 additional independent records provided by the Libyan National Centre for Disease Control (NCDC); all of these records fell inside the belt predicted as suitable for ZCL. We tested ecological niche similarity among vector, parasite, and reservoir species and could not reject any null hypotheses of niche similarity. Finally, we tested among possible combinations of vector and reservoir that could predict all recent human ZCL cases reported by NCDC; only three combinations could anticipate the distribution of human cases across the country.     

Evolution and Phylogenetic Analysis of Full-Length VP3 Genes of Eastern Mediterranean Bluetongue Virus Isolates

Bluetongue virus (BTV) is the ‘type’ species of the genus Orbivirus within the family Reoviridae. The BTV genome is composed of ten linear segments of double-stranded RNA (dsRNA), each of which codes for one of ten distinct viral proteins. Previous phylogenetic comparisons have evaluated variations in genome segment 3 (Seg-3) nucleotide sequence as way to identify the geographical origin (different topotypes) of BTV isolates. The full-length nucleotide sequence of genome Seg-3 was determined for thirty BTV isolates recovered in the eastern Mediterranean region, the Balkans and other geographic areas (Spain, India, Malaysia and Africa). These data were compared, based on molecular variability, positive-selection-analysis and maximum-likelihood phylogenetic reconstructions (using appropriate substitution models) to 24 previously published sequences, revealing their evolutionary relationships. These analyses indicate that negative selection is a major force in the evolution of BTV, restricting nucleotide variability, reducing the evolutionary rate of Seg-3 and potentially of other regions of the BTV genome. Phylogenetic analysis of the BTV-4 strains isolated over a relatively long time interval (1979–2000), in a single geographic area (Greece), showed a low level of nucleotide diversity, indicating that the virus can circulate almost unchanged for many years. These analyses also show that the recent incursions into south-eastern Europe were caused by BTV strains belonging to two different major-lineages: representing an ‘eastern’ (BTV-9, -16 and -1) and a ‘western’ (BTV-4) group/topotype. Epidemiological and phylogenetic analyses indicate that these viruses originated from a geographic area to the east and southeast of Greece (including Cyprus and the Middle East), which appears to represent an important ecological niche for the virus that is likely to represent a continuing source of future BTV incursions into Europe.     

Toward ecologically realistic predictions of species distributions: A cross‐time example from tropical montane cloud forests

There is an urgent need for more ecologically realistic models for better predicting the effects of climate change on species’ potential geographic distributions. Here we build ecological niche models using MAXENT and test whether selecting predictor variables based on biological knowledge and selecting ecologically realistic response curves can improve cross‐time distributional predictions. We also evaluate how the method chosen for extrapolation into nonanalog conditions affects the prediction. We do so by estimating the potential distribution of a montane shrew (Mammalia, Soricidae, Cryptotis mexicanus) at present and the Last Glacial Maximum (LGM). Because it is tightly associated with cloud forests (with climatically determined upper and lower limits) whose distributional shifts are well characterized, this species provides clear expectations of plausible vs. implausible results. Response curves for the MAXENT model made using variables selected via biological justification were ecologically more realistic compared with those of the model made using many potential predictors. This strategy also led to much more plausible geographic predictions for upper and lower elevational limits of the species both for the present and during the LGM. By inspecting the modeled response curves, we also determined the most appropriate way to extrapolate into nonanalog environments, a previously overlooked factor in studies involving model transfer. This study provides intuitive context for recommendations that should promote more realistic ecological niche models for transfer across space and time.     

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.     

Ecological niche models display nonlinear relationships with abundance and demographic performance across the latitudinal distribution of Astragalus utahensis (Fabaceae)

The potential for ecological niche models (ENMs) to accurately predict species' abundance and demographic performance throughout their geographic distributions remains a topic of substantial debate in ecology and biogeography. Few studies simultaneously examine the relationship between ENM predictions of environmental suitability and both a species' abundance and its demographic performance, particularly across its entire geographic distribution. Yet, studies of this type are essential for understanding the extent to which ENMs are a viable tool for identifying areas that may promote high abundance or performance of a species or how species might respond to future climate conditions. In this study, we used an ensemble ecological niche model to predict climatic suitability for the perennial forb Astragalus utahensis across its geographic distribution. We then examined relationships between projected climatic suitability and field‐based measures of abundance, demographic performance, and forecasted stochastic population growth (λ_s). Predicted climatic suitability showed a J‐shaped relationship with A. utahensis abundance, where low‐abundance populations were associated with low‐to‐intermediate suitability scores and abundance increased sharply in areas of high predicted climatic suitability. A similar relationship existed between climatic suitability and λ_s from the center to the northern edge of the latitudinal distribution. Patterns such as these, where density or demographic performance only increases appreciably beyond some threshold of climatic suitability, support the contention that ENM‐predicted climatic suitability does not necessarily represent a reliable predictor of abundance or performance across large geographic regions.     

A Tale of Four “Carp”: Invasion Potential and Ecological Niche Modeling

Background

Invasive species are a serious problem in ecosystems, but are difficult to eradicate once established. Predictive methods can be key in determining which areas are of concern regarding invasion by such species to prevent establishment [1]. We assessed the geographic potential of four Eurasian cyprinid fishes (common carp, tench, grass carp, black carp) as invaders in North America via ecological niche modeling (ENM). These “carp” represent four stages of invasion of the continent (a long-established invader with a wide distribution, a long-established invader with a limited distribution, a spreading invader whose distribution is expanding, and a newly introduced potential invader that is not yet established), and as such illustrate the progressive reduction of distributional disequilibrium over the history of species'' invasions.

Methodology/Principal Findings

We used ENM to estimate the potential distributional area for each species in North America using models based on native range distribution data. Environmental data layers for native and introduced ranges were imported from state, national, and international climate and environmental databases. Models were evaluated using independent validation data on native and invaded areas. We calculated omission error for the independent validation data for each species: all native range tests were highly successful (all omission values <7%); invaded-range predictions were predictive for common and grass carp (omission values 8.8 and 19.8%, respectively). Model omission was high for introduced tench populations (54.7%), but the model correctly identified some areas where the species has been successful; distributional predictions for black carp show that large portions of eastern North America are at risk.

Conclusions/Significance

ENMs predicted potential ranges of carp species accurately even in regions where the species have not been present until recently. ENM can forecast species'' potential geographic ranges with reasonable precision and within the short screening time required by proposed U.S. invasive species legislation.     

Consensual predictions of potential distributional areas for invasive species: a case study of Argentine ants in the Iberian Peninsula

Invasive species are known to influence the structure and function of invaded ecological communities, and preventive measures appear to be the most efficient means of controlling these effects. However, management of biological invasions requires use of adequate tools to understand and predict invasion patterns in recently introduced areas. The present study: (1) estimates the potential geographic distribution and ecological requirements of the Argentine ant (Linepithema humile Mayr), one of the most conspicuous invasive species throughout the world, in the Iberian Peninsula using ecological niche modeling, and (2) provides new insights into the process of selection of consensual areas among predictions from several modeling methodologies. Ecological niche models were developed using 5 modeling techniques: generalized linear models (GLM), generalized additive models (GAM), generalized boosted models (GBM), Genetic Algorithm for Rule-Set Prediction (GARP), and Maximum Entropy (Maxent). Models for the eastern and western portions of the Iberian Peninsula were built using subsets of occurrence and environmental data to investigate the potential for ecological niche differences between the invading populations. Our results indicate geographic differences between predictions of different approaches, and the utility of ensemble predictions in identifying areas of uncertainty regarding the species’ invasive potential. More generally, our models predict coastal areas and major river corridors as highly suitable for Argentine ants, and indicate that western and eastern Iberian Peninsula populations occupy similar environmental conditions.

The contribution of small collections to species distribution modelling: A case study from Fuireneae (Cyperaceae)

The recent and rapid digitization of biodiversity data from natural history collection (NHC) archives has enriched collections based data repositories; this data continues to inform studies of species' geographic distributions. Here we investigate the relative impact of plant data from small natural history collections (collections with < 100,000 specimens) on species distributional models in an effort to document the potential of data from small NHCs to contribute to and inform biodiversity research. We modelled suitable habitat of five test case species from Fuireneae (Cyperaceae) in the United States using specimen records available via the Global Biodiversity Information Facility and that of data ready to mobilize from two regional small herbaria. Data were partitioned into three datasets based on their source: 1) collections-based records from large NHCs accessed GBIF, 2) collections-based records from small NHCs accessed from GBIF, and 3) collections-based records from two small regional herbaria not yet mobilized to GBIF. We extracted and evaluated the ecological niche represented for each of the three datasets by applying dataset occurrences to 14 environmental factors, and we modelled habitat suitability using Maxent to compare the represented distribution of the environmental values among the datasets. Our analyses indicate that the data from small NHCs contributed unique information in both geographic and environmental space. When data from small collections were combined with data from large collections, species models of the ecological niche resulted in more refined predictions of habitat suitability, indicating that small collections can contribute unique occurrence data which enhance species distribution models by bridging geographic collection gaps and shifting modelled predictions of suitable habitat. Inclusion of specimen records from small collections in ongoing digitization efforts is essential for generating informed models of a species' niche and distribution.     

Do geographic distribution,niche property and life form explain plants' vulnerability to global change?

We modelled the future distribution in 2050 of 975 endemic plant species in southern Africa distributed among seven life forms, including new methodological insights improving the accuracy and ecological realism of predictions of global changes studies by: (i) using only endemic species as a way to capture the full realized niche of species, (ii) considering the direct impact of human pressure on landscape and biodiversity jointly with climate, and (iii) taking species' migration into account. Our analysis shows important promises for predicting the impacts of climate change in conjunction with land transformation. We have shown that the endemic flora of Southern Africa on average decreases with 41% in species richness among habitats and with 39% on species distribution range for the most optimistic scenario. We also compared the patterns of species' sensitivity with global change across life forms, using ecological and geographic characteristics of species. We demonstrate here that species and life form vulnerability to global changes can be partly explained according to species' (i) geographical distribution along climatic and biogeographic gradients, like climate anomalies, (ii) niche breadth or (iii) proximity to barrier preventing migration. Our results confirm that the sensitivity of a given species to global environmental changes depends upon its geographical distribution and ecological proprieties, and makes it possible to estimate a priori its potential sensitivity to these changes.     

Ecological Niche Transferability Using Invasive Species as a Case Study

Species distribution modeling is widely applied to predict invasive species distributions and species range shifts under climate change. Accurate predictions depend upon meeting the assumption that ecological niches are conserved, i.e., spatially or temporally transferable. Here we present a multi-taxon comparative analysis of niche conservatism using biological invasion events well documented in natural history museum collections. Our goal is to assess spatial transferability of the climatic niche of a range of noxious terrestrial invasive species using two complementary approaches. First we compare species’ native versus invasive ranges in environmental space using two distinct methods, Principal Components Analysis and Mahalanobis distance. Second we compare species’ native versus invaded ranges in geographic space as estimated using the species distribution modeling technique Maxent and the comparative index Hellinger’s I. We find that species exhibit a range of responses, from almost complete transferability, in which the invaded niches completely overlap with the native niches, to a complete dissociation between native and invaded ranges. Intermediate responses included expansion of dimension attributable to either temperature or precipitation derived variables, as well as niche expansion in multiple dimensions. We conclude that the ecological niche in the native range is generally a poor predictor of invaded range and, by analogy, the ecological niche may be a poor predictor of range shifts under climate change. We suggest that assessing dimensions of niche transferability prior to standard species distribution modeling may improve the understanding of species’ dynamics in the invaded range.     

Physical and ecological isolation contribute to maintain genetic differentiation between fire salamander subspecies

Landscape features shape patterns of gene flow among populations, ultimately determining where taxa lay along the continuum between panmixia to complete reproductive isolation. Gene flow can be restricted, leading to population differentiation in two non-exclusive ways: “physical isolation”, in which geographic distance in combination with the landscape features restricts movement of individuals promoting genetic drift, and “ecological isolation”, in which adaptive mechanisms constrain gene flow between different environments via divergent natural selection. In central Iberia, two fire salamander subspecies occur in parapatry across elevation gradients along the Iberian Central System mountains, while in the adjacent Montes de Toledo Region only one of them occurs. By integrating population and landscape genetic analyses, we show a ubiquitous role of physical isolation between and within mountain ranges, with unsuitable landscapes increasing differentiation between populations. However, across the Iberian Central System, we found strong support for a significant contribution of ecological isolation, with low genetic differentiation in environmentally homogeneous areas, but high differentiation across sharp transitions in precipitation seasonality. These patterns are consistent with a significant contribution of ecological isolation in restricting gene flow among subspecies. Overall, our results suggest that ecological divergence contributes to reduce genetic admixture, creating an opportunity for lineages to follow distinct evolutionary trajectories.Subject terms: Evolutionary ecology, Speciation     

Genetically informed ecological niche models improve climate change predictions

We examined the hypothesis that ecological niche models (ENMs) more accurately predict species distributions when they incorporate information on population genetic structure, and concomitantly, local adaptation. Local adaptation is common in species that span a range of environmental gradients (e.g., soils and climate). Moreover, common garden studies have demonstrated a covariance between neutral markers and functional traits associated with a species’ ability to adapt to environmental change. We therefore predicted that genetically distinct populations would respond differently to climate change, resulting in predicted distributions with little overlap. To test whether genetic information improves our ability to predict a species’ niche space, we created genetically informed ecological niche models (gENMs) using Populus fremontii (Salicaceae), a widespread tree species in which prior common garden experiments demonstrate strong evidence for local adaptation. Four major findings emerged: (i) gENMs predicted population occurrences with up to 12‐fold greater accuracy than models without genetic information; (ii) tests of niche similarity revealed that three ecotypes, identified on the basis of neutral genetic markers and locally adapted populations, are associated with differences in climate; (iii) our forecasts indicate that ongoing climate change will likely shift these ecotypes further apart in geographic space, resulting in greater niche divergence; (iv) ecotypes that currently exhibit the largest geographic distribution and niche breadth appear to be buffered the most from climate change. As diverse agents of selection shape genetic variability and structure within species, we argue that gENMs will lead to more accurate predictions of species distributions under climate change.     

Spatial scale,topography and thermoregulatory behaviour interact when modelling species’ thermal niches

The spatial scale at which climate and species’ occupancy data are gathered, and the resolution at which ecological models are run, can strongly influence predictions of species performance and distributions. Running model simulations at coarse rather than fine spatial resolutions, for example, can determine if a model accurately predicts the distribution of a species. The impacts of spatial scale on a model's accuracy are particularly pronounced across mountainous terrain. Understanding how these discrepancies arise requires a modelling approach in which the underlying processes that determine a species’ distribution are explicitly described. Here we use a process‐based model to explore how spatial resolution, topography and behaviour alter predictions of a species thermal niche, which in turn constrains its survival and geographic distribution. The model incorporates biophysical equations to predict the operative temperature (T_e), thermal‐dependent performance and survival of a typical insect, with a complex life‐cycle, in its microclimate. We run this model with geographic data from a mountainous terrain in South Africa using climate data at three spatial resolutions. We also explore how behavioural thermoregulation affects predictions of a species performance and survival by allowing the animal to select the optimum thermal location within each coarse‐grid cell. At the regional level, coarse‐resolution models predicted lower T_e at low elevations and higher T_e at high elevations than models run at fine‐resolutions. These differences were more prominent on steep, north‐facing slopes. The discrepancies in T_e in turn affected estimates of the species thermal niche. The modelling framework revealed how spatial resolution and topography influence predictions of species distribution models, including the potential impacts of climate change. These systematic biases must be accounted for when interpreting the outputs of future modelling studies, particularly when species distributions are predicted to shift from uniform to topographically heterogeneous landscapes.     

Cryptic niche conservatism among evolutionary lineages of an invasive lizard

Aim There is increasing evidence that the quality and breadth of ecological niches vary among individuals, populations, evolutionary lineages and therefore also across the range of a species. Sufficient knowledge about niche divergence among clades might thus be crucial for predicting the invasion potential of species. We tested for the first time whether evolutionary lineages of an invasive species vary in their climate niches and invasive potential. Furthermore, we tested whether lineage‐specific models show a better performance than combined models. Location Europe. Methods We used species distribution models (SDMs) based on climatic information at native and invasive ranges to test for intra‐specific niche divergence among mitochondrial DNA (mtDNA) clades of the invasive wall lizard Podarcis muralis. Using DNA barcoding, we assigned 77 invasive populations in Central Europe to eight geographically distinct evolutionary lineages. Niche similarity among lineages was assessed and the predictive power of a combination of clade‐specific SDMs was compared with a combined SDM using the pooled records of all lineages. Results We recorded eight different invasive mtDNA clades in Central Europe. The analysed clades had rather similar realized niches in their native and invasive ranges, whereas inter‐clade niche differentiation was comparatively strong. However, we found only a weak correlation between geographic origin (i.e. mtDNA clade) and invasive occurrences. Clades with narrow realized niches still became successful invaders far outside their native range, most probably due to broader fundamental niches. The combined model using data for all invasive lineages achieved a much better prediction of the invasive potential. Conclusions Our results indicate that the observed niche differentiation among evolutionary lineages is mainly driven by niche realization and not by differences in the fundamental niches. Such cryptic niche conservatism might hamper the success of clade‐specific niche modelling. Cryptic niche conservatism may in general explain the invasion success of species in areas with apparently unsuitable climate.     

Niche theory‐based modeling of assembly processes of viral communities in bats

Understanding the assembly processes of symbiont communities, including viromes and microbiomes, is important for improving predictions on symbionts’ biogeography and disease ecology. Here, we use phylogenetic, functional, and geographic filters to predict the similarity between symbiont communities, using as a test case the assembly process in viral communities of Mexican bats. We construct generalized linear models to predict viral community similarity, as measured by the Jaccard index, as a function of differences in host phylogeny, host functionality, and spatial co‐occurrence, evaluating the models using the Akaike information criterion. Two model classes are constructed: a “known” model, where virus–host relationships are based only on data reported in Mexico, and a “potential” model, where viral reports of all the Americas are used, but then applied only to bat species that are distributed in Mexico. Although the “known” model shows only weak dependence on any of the filters, the “potential” model highlights the importance of all three filter types—phylogeny, functional traits, and co‐occurrence—in the assemblage of viral communities. The differences between the “known” and “potential” models highlight the utility of modeling at different “scales” so as to compare and contrast known information at one scale to another one, where, for example, virus information associated with bats is much scarcer.     

Environmental marginality and geographic range limits: a case study with Arabidopsis lyrata ssp. lyrata

Understanding the factors that govern the distribution of species is a central goal of evolutionary ecology. It is commonly assumed that geographic range limits reflect ecological niche limits and that species experience increasingly marginal conditions towards the edge of their ranges. Using spatial data and ecological niche models we tested these hypotheses in Arabidopsis lyrata. Specifically, we asked whether range limits coincide with predicted niche limits in this system and whether the suitability of sites declines towards the edge of the species’ range in North America. We further explored patterns of environmental change towards the edge of the range and asked whether genome‐wide patterns of genetic diversity decline with increasing peripherality and environmental marginality. Our results suggest that latitudinal range limits coincide with niche limits. Populations experienced increasingly marginal environments towards these limits – though patterns of environmental change were more complex than most theoretical models for range limits assume. Genomic diversity declined towards the edge of the species’ range and with increasing distance from the estimated centre of the species’ niche in environmental space, but not with the suitability of sites based on niche model predictions. Thus while latitudinal range limits in this system are broadly associated with niche limits, the link between environmental conditions and genetic diversity (and thus the adaptive potential of populations) is less clear.