Variation in niche and distribution model performance: The need for a priori assessment of key causal factors

Climate change may reveal currently unavailable parts of species' ecological niches

The ability of climatic niche models to predict species extinction risks can be hampered if niches are incompletely quantified. This can occur when niches are estimated considering only currently available climatic conditions, disregarding the fact that climate change can open up portions of the fundamental niche that are currently inaccessible to species. Using a new metric, we estimate the prevalence of potential situations of fundamental niche truncation by measuring whether current ecological niche limits are contiguous to the boundaries of currently available climatic conditions for 24,944 species at the global scale in both terrestrial and marine realms and including animals and plants. We show that 12,172 (~49%) species are showing niche contiguity, particularly those inhabiting tropical ecosystems and the marine realm. Using niche expansion scenarios, we find that 86% of species showing niche contiguity could have a fundamental niche potentially expanding beyond current climatic limits, resulting in lower-yet still alarming-rates of predicted biodiversity loss, particularly within the tropics. Caution is therefore advised when forecasting future distributions of species presenting niche contiguity, particularly towards climatic limits that are predicted to expand in the future.

Predicting the potential distribution and coexistence of Chagas disease vectors in the Americas

Predicting the potential distribution and coexistence of suitable geographic areas for Chagas disease vectors in the Americas is a crucial task for understanding the eco-epidemiological dynamics of this disease. The potential distribution and coexistence of 3 species-Rhodnius prolixus (Hemiptera: Reduviidae), Cavernicola pilosa (Hemiptera: Reduviidae), and Rhodnius pictipes (Hemiptera: Reduviidae) were modeled. Presence records were obtained and environmental variables were selected based on correlation analysis, Jackknife analysis and knowledge of the biology and natural history of the species. The MaxEnt algorithm included in the kuenm package of R software was used for modeling the potential distribution, and various scenarios of the BAM diagram (Biotic, Abiotic, and Movement variables) were evaluated. The variables contributing to the final models were different for each species. Rhodnius pictipes showed a potential distribution in South America, particularly in Brazil, Bolivia, Peru, Colombia, Venezuela, Guyana, and Suriname. Areas with environmentally suitable conditions for R. prolixus were located in southern Brazil, Peru, Colombia, southern Mexico, Guatemala, El Salvador, and Honduras, whereas for C. pilosa they were in southeastern Brazil, southeastern Central America, Peru, Ecuador, Colombia, Venezuela, Guyana, Suriname, and French Guiana. Co-occurrence analysis revealed distinct patterns in the neotropical region, with some areas indicating the potential distribution of 1 or more species. In Brazil, occurrence and co-occurrence areas were concentrated in the northwest and southeast regions. Overall, this study provides valuable information on the potential distribution and coexistence of vectors, which can inform targeted vector control strategies and contribute to global efforts in combating Chagas disease.

Preserving the spots: Jaguar (Panthera onca) distribution and priority conservation areas in Colombia

The jaguar (Panthera onca) is a charismatic species considered Vulnerable in Colombia but yet largely unknown in the country. The species is mostly threatened by the continuous decline in its habitats, mostly derived from deforestation and habitat loss, additional to hunting and conflicts with humans. Thus, the future of jaguars in Colombia depends on protecting and recovering existing habitats. The aims of this study were to 1) evaluate jaguar distribution and identify the remnant patches of habitat in Colombia, 2) define an ecological connectivity network within the country, and 3) propose a priority areas portfolio for the conservation and recovery of jaguars. We used a presence background model for estimating species potential distribution and subsequently identified remaining habitat patches across the country based on land cover and species-specific ecological attributes. We then created an ecological connectivity network based on circuit theory and following a multi-criteria approach identified jaguar priority areas for conservation (JPCA) and recovery (JPRA). Jaguar potential distribution comprises 1103122.43 km2, from which 56.71% maintain suitable patches of potential habitat. We identified 960 corridors between remnant patches of natural or semi-natural vegetation. Based on the criteria, JPCAs with greater importance were identified in each of the five Colombian regions. JPRAs were located mainly towards the Andean and Caribbean regions. These JPCAs and JPRAs could serve as a guide for designing and implementing management strategies for the long-term conservation and recovery of the species in Colombia.

Incorporating eco-evolutionary information into species distribution models provides comprehensive predictions of species range shifts under climate change

As climate changes increasingly influence species distributions, ecosystem functions, and biodiversity, the urgency to understand how species' ranges shift under those changes is great. Species distribution models (SDMs) are vital approaches that can predict species distributions under changing climates. However, SDMs based on the species' current occurrences may underestimate the species' climatic tolerances. Integrating species' realized niches at different periods, also known as multi-temporal calibration, can provide an estimation closer to its fundamental niche. Based on this, we further proposed an integrated framework that combines eco-evolutionary data and SDMs (phylogenetically-informed SDMs) to provide comprehensive predictions of species range shifts under climate change. To evaluate our approach's performance, we applied it to a group of related species, the Chrysanthemum zawadskii species complex (Anthemidae, Asteracee). First, we investigated the niche differentiation between species and intraspecific lineages of the complex and estimated their rates of niche evolution. Next, using both standard SDMs and our phylogenetically-informed SDMs, we generated predictions of suitability areas for all species and lineages and compared the results. Finally, we reconstructed the historical range dynamics for the species of this complex. Our results showed that the species and intraspecific lineages of the complex had varying degrees of niche differentiation and different rates of niche evolution. Lineage-level SDMs can provide more realistic predictions for species with intraspecific differentiation than species-level models can. The phylogenetically-informed SDMs provided more complete environmental envelopes and predicted broader potential distributions for all species than the standard SDMs did. Range dynamics varied among the species that have different rates of niche evolution. Our framework integrating eco-evolutionary data and SDMs contributes to a better understanding of the species' responses to climate change and can help to make more targeted conservation efforts for the target species under climate change, particularly for rare species.

Effects of disturbances and environmental changes on an aridland riparian generalist

Anthropogenic climate change and ecosystem disturbances can detrimentally affect habitats and species. Areas with concentrated biodiversity, such as aridland riparian zones, often yield the greatest number of vulnerable species. A better understanding of ecological and environmental relationships can guide more effective conservation strategies. We used both visual transects and external (tape) radio telemetry to study the behavioral and spatial ecology of black-necked gartersnakes (Thamnophis cyrtopsis; n = 81)-a dietary generalist yet aquatic habitat specialist-in a heterogenous aridland riparian zone of lower Sabino Canyon, Tucson, Arizona, between 2018 and 2021. Our objectives were to (1) understand how extrinsic conditions influence population ecology dynamics, including immediately prior to and after major disturbances and environmental extremes; (2) analyze behavioral activity and microhabitat usage in relation to environmental factors; and (3) assess the efficacy of a less-invasive telemetry strategy. Between late spring 2020 and early summer 2021, ecosystem disturbances included near-record heat and drought, wildfire, and low overwinter precipitation. Many aquatic habitats either completely dried or were spatially disjunct; gartersnake prey species were noticeably sparse. Extreme drought rapidly shifted to excessive flooding during the 2021 monsoon that brought above-average streamflow magnitude and duration. Between 2019 and 2021, we observed a dramatic decline in T. cyrtopsis; odds of detection reduced by 92.8% (CI [56.0-99.1%]). Strong spatiotemporal links relative to the extent and timing of available surface water appear important. Prior to the onset of monsoonal stream recharge in early summer, shallow and drying aquatic habitats are used as parturition sites and foraging grounds; all age classes took advantage to corral fishes trapped in isolated and shrinking pools. Ambient conditions had varying effects on gartersnake behaviors. Variation in microhabitat assemblages occurred with distance from water, activity level, and developmental age class. Interestingly, associations remained consistent across seasons and years, which suggests a reliance on heterogenous habitat structure. Sampling techniques complemented each other, however, bioclimatic parameters rendered limitations and should be considered in methodological decisions. Overall, disadvantageous responses to major disturbances and climatic extremes by a presumably adaptable generalist like T. cyrtopsis are concerning. Insights from long-term monitoring of responses by common yet environmentally sensitive species such as T. cyrtopsis may serve to more broadly highlight demographic challenges that other taxa with similar semi-aquatic life histories may face in changing systems. Such information could inform more effective conservation management strategies in warming and drying ecosystems.

Wild canids and the ecological traps facing the climate change and deforestation in the Amazon Forest

Ecological traps occur when species choose to settle in lower-quality habitats, even if this reduces their survival or productivity. This happens in situations of drastic environmental changes, resulting from anthropogenic pressures. In long term, this could mean the extinction of the species. We investigated the dynamics of occurrence and distribution of three canid species (Atelocynus microtis, Cerdocyon thous, and Spheotos venaticus) considering human threats to their habitats in the Amazon Rainforest. We analyzed the environmental thresholds for the occurrence of these species and related to the future projections of climatic niches for each one. All three species will be negatively affected by climate change in the future, with losses of up to 91% of the suitable area of occurrence in the Brazilian Amazon. A. microtis appear to be more forest-dependent and must rely on the goodwill of decision-makers to be maintained in the future. For C. thous and S. venaticus, climatic variables and those associated with anthropogenic disturbances that modulate their niches today may not act the same way in the future. Even though C. thous is least dependent on the Amazon Forest; this species may be affected in the future due to the ecological traps. S. venaticus, can also undergo the same process, but perhaps more drastically due to the lower ecological plasticity of this species compared to C. thous. Our results suggest that the ecological traps may put these two species at risk in the future. Using the canid species as a model, we had the opportunity to investigate these ecological effects that can affect a large part of the Amazonian fauna in the current scenario. Considering the high degree of environmental degradation and deforestation in the Amazon Rainforest, the theory of ecological traps must be discussed at the same level as the habitat loss, considering the strategies for preserving the Amazon biodiversity.

Climate Change Impacts on the Potential Distribution Pattern of Osphya (Coleoptera: Melandryidae), an Old but Small Beetle Group Distributed in the Northern Hemisphere

Exploring the development of species distribution patterns under climate change is the basis of biogeography and macroecology. However, under the background of global climate change, few studies focus on how the distribution pattern and the range of insects have or will change in response to long-term climate change. An old but small, Northern-Hemisphere-distributed beetle group Osphya is an ideal subject to conduct the study in this aspect. Here, based on a comprehensive geographic dataset, we analyzed the global distribution pattern of Osphya using ArcGIS techniques, which declared a discontinuous and uneven distribution pattern across the USA, Europe, and Asia. Furthermore, we predicted the suitable habitats of Osphya under different climate scenarios via the MaxEnt model. The results showed that the high suitability areas were always concentrated in the European Mediterranean and the western coast of USA, while a low suitability exhibited in Asia. Moreover, by integrating the analyses of biogeography and habitat suitability, we inferred that the Osphya species conservatively prefer a warm, stable, and rainy climate, and they tend to expand towards higher latitude in response to the climate warming from the past to future. These results are helpful in exploring the species diversity and protection of Osphya.

An exhaustive evaluation of modeling ecological niches above species level to predict marine biological invasions

Identifying the areas of the world with suitable environmental conditions for the establishment of invasive species represents a fundamental basis for preventing their impacts. One of the most widely used tools for this is ecological niche modeling. Nonetheless, this approach may underestimate the specie's physiological tolerances (it's potential niche) since wildlife populations of species usually do not occupy their entire environmental tolerance. Recently, it has been suggested that incorporating occurrences of phylogenetically related species improves the prediction of biological invasions. However, the reproducibility of this technique remains unclear. Here, we evaluated the generality of this protocol by assessing whether the construction of modeling units above species level improves the capacity of niche models to predict the distribution of 26 target marine invasive species. For each, we constructed supraspecific modeling units based on published phylogenies by grouping the native occurrence records of each invasive species with the records of its phylogenetically closest relative. We also considered units at species level, including only the presence of records in the native areas of the target species. We generated ecological niche models for each unit with three modeling methods (minimum volume ellipsoids - MVE, machine learning algorithms - Maxent and a presence-absence method - GLM). In addition, we grouped the 26 target species based on whether or not the species are in environmental pseudo-equilibrium (i.e., it occupies all habitats where it can disperse) and have any geographical or biological constraints. Our results suggest that the construction of supraspecific units improves the predictive capacity of correlative models to estimate the invasion area of our target species. This modeling approach consistently generated models with a higher predictive ability for species in non-environmental pseudo-equilibrium and with geographical constraints.

Interspecific hybridization explains rapid gorget colour divergence in Heliodoxa hummingbirds (Aves: Trochilidae)

Hybridization is a known source of morphological, functional and communicative signal novelty in many organisms. Although diverse mechanisms of established novel ornamentation have been identified in natural populations, we lack an understanding of hybridization effects across levels of biological scales and upon phylogenies. Hummingbirds display diverse structural colours resulting from coherent light scattering by feather nanostructures. Given the complex relationship between feather nanostructures and the colours they produce, intermediate coloration does not necessarily imply intermediate nanostructures. Here, we characterize nanostructural, ecological and genetic inputs in a distinctive Heliodoxa hummingbird from the foothills of eastern Peru. Genetically, this individual is closely allied with Heliodoxa branickii and Heliodoxa gularis, but it is not identical to either when nuclear data are assessed. Elevated interspecific heterozygosity further suggests it is a hybrid backcross to H. branickii. Electron microscopy and spectrophotometry of this unique individual reveal key nanostructural differences underlying its distinct gorget colour, confirmed by optical modelling. Phylogenetic comparative analysis suggests that the observed gorget coloration divergence from both parentals to this individual would take 6.6-10 My to evolve at the current rate within a single hummingbird lineage. These results emphasize the mosaic nature of hybridization and suggest that hybridization may contribute to the structural colour diversity found across hummingbirds.

An Agenda for Research of Uncovered Epidemiological Patterns of Tick-Borne Pathogens Affecting Human Health

The panorama of ticks and tick-borne pathogens (TBP) is complex due to the many interactions among vertebrates, vectors, and habitats, occurring at different scales. At a broad spatial range, climate and host availability regulate most tick processes, including questing activity, development, and survival. At a local scale, interactions are obscured by a high indeterminacy, making it arduous to record in field surveys. A solid modelling framework could translate the local/regional empirical findings into larger scales, shedding light on the processes governing the circulation of TBP. In this opinion paper, we advocate for a re-formulation of some paradigms in the research of these outstanding cycles of transmission. We propose revisiting concepts that faced criticisms or lacked solid support, together with the development of a conceptual scheme exploring the circulation of TBP under a range of conditions. We encourage (i) an adequate interpretation of the niche concept of both ticks and vertebrate/reservoir hosts interpreting the (a)biotic components that shape the tick's niche, (ii) an assessment of the role played by the communities of wild vertebrates on the circulation of pathogens, and (iii) the development of new approaches, based on state-of-the-art epidemiological concepts, to integrate findings and modelling efforts on TBP over large regions.

Risk analysis of the spread of the quarantine pest mite Schizotetranychus hindustanicus in Brazil

Schizotetranychus hindustanicus Hirst (Acari: Tetranychidae) known as the Hindustan citrus mite, is a quarantine pest present in Roraima, Brazil. In 1924 this pest was described in India. It was reported in 2002 in Venezuela and in Roraima in 2008. In 2010, the Hindustan citrus mite was reported in Colombia. It is possible that it will be introduced in other areas of Brazil, resulting in a threat to Brazilian citrus industry. Our objective was to determine the most suitable regions of Brazil for S. hindustanicus using a maximum entropy (Maxent) algorithm, based on native and invasive updated occurrence records from published research, field surveys and online databases. To avoid overfitting and improving transferability, we chose parameter settings of Maxent to construct and validate models by searching for the best combination of feature classes and regularization multipliers. The model obtained showed excellent performance according to all evaluation metrics used. A high potential for the establishment of S. hindustanicus was identified in large areas of Roraima, the extreme west of Amazonas, the entire north of the State of Pará, also in northeast, south, east, and north of the State of Amapá, and in a small portion northwest of the State of Maranhão (all states belonging to the northern region of Brazil). Our results provide information for policy making and quarantine measures, especially where S. hindustanicus is still absent in Brazil.

Species conservation profiles of the endemic spiders Troglohyphantes (Araneae, Linyphiidae) from the Alps and the north-western Dinarides

Background

The genus Troglohyphantes Joseph, 1882 (Araneae, Linyphiidae) includes 131 species, mainly distributed across the main European mountain ranges. The Alps and the north-western Dinarides account for 66 species, most of them showing narrow or even point-like distributions. The majority of Troglohyphantes spiders dwell in subterranean habitats including caves, mines, soil litter, rocky debris and other moist and shaded retreats. Despite being intensively studied from taxonomic, ecological and biogeographic standpoints, knowledge on the status of conservation and on the potential risk of extinction of these spiders is lagging. To date, only three species have been included in the global IUCN Red List, but their status has not been updated ever since their last assessment in 1996. The aim of this contribution is to assess the Alpine and north-western Dinaric species of the genus Troglohyphantes and to re-assess the species previously evaluated, according to the last version of the IUCN Red List Categories and Criteria.

New information

Amongst the 66 species here considered, 62 had sufficient data to allow the quantification of their Extent Of Occurrence (EOO) and Area Of Occupancy (AOO). Most of the species have a narrow distribution range, with an estimated EOO < 20,000 km² and AOO < 2,000 km², meeting the thresholds for the inclusion in the threatened categories. Five species have a more widespread distribution (EOO > 20,000 km²), extending across multiple countries. The quality of the data on distribution of four species was not sufficient to provide a reliable estimation of the distribution range.A continuing decline in EOO, AOO and habitat quality was inferred for 30 species. The majority of them were subterranean specialised species, with a reduced thermal tolerance and a low dispersal ability. Accordingly, changes in subterranean microclimatic conditions due to climate change represent a major threat for these species. Land-use change and habitat alteration were identified as additional relevant threats for several species.A considerable proportion of the species here assessed was found in protected areas and in sites of the Natura 2000 network. In addition, 14 species are formally protected by national and sub-national legislation. At present, 25 species are listed in the regional Red Lists.Long-term monitoring programmes, management plans for both the species and their habitats, expansion of the extant protected areas and designation of new ones, should be considered as the most effective approaches to species conservation.

Linking ecological niche models and common garden experiments to predict phenotypic differentiation in stressful environments: Assessing the adaptive value of marginal populations in an alpine plant

Environmental variation within a species' range can create contrasting selective pressures, leading to divergent selection and novel adaptations. The conservation value of populations inhabiting environmentally marginal areas remains in debate and is closely related to the adaptive potential in changing environments. Strong selection caused by stressful conditions may generate novel adaptations, conferring these populations distinct evolutionary potential and high conservation value under climate change. On the other hand, environmentally marginal populations may be genetically depauperate, with little potential for new adaptations to emerge. Here, we explored the use of ecological niche models (ENMs) linked with common garden experiments to predict and test for genetically determined phenotypic differentiation related to contrasting environmental conditions. To do so, we built an ENM for the alpine plant Silene ciliata in central Spain and conducted common garden experiments, assessing flowering phenology changes and differences in leaf cell resistance to extreme temperatures. The suitability patterns and response curves of the ENM led to the predictions that: (1) the environmentally marginal populations experiencing less snowpack and higher minimum temperatures would have delayed flowering to avoid risks of late-spring frosts and (2) those with higher minimum temperatures and greater potential evapotranspiration would show enhanced cell resistance to high temperatures to deal with physiological stress related to desiccation and heat. The common garden experiments revealed the expected genetically based phenotypic differentiation in flowering phenology. In contrast, they did not show the expected differentiation for cell resistance, but these latter experiments had high variance and hence lower statistical power. The results highlight ENMs as useful tools to identify contrasting putative selective pressures across species ranges. Linking ENMs with common garden experiments provides a theoretically justified and practical way to study adaptive processes, including insights regarding the conservation value of populations inhabiting environmentally marginal areas under ongoing climate change.

A comparison in species distribution model performance of succulents using key species and subsets of environmental predictors

Identifying the environmental drivers of the global distribution of succulent plants using the Crassulacean acid metabolism pathway of photosynthesis has previously been investigated through ensemble‐modeling of species delimiting the realized niche of the natural succulent biome. An alternative approach, which may provide further insight into the fundamental niche of succulent plants in the absence of dispersal limitation, is to model the distribution of selected species that are globally widespread and have become naturalized far beyond their native habitats. This could be of interest, for example, in defining areas that may be suitable for cultivation of alternative crops resilient to future climate change. We therefore explored the performance of climate‐only species distribution models (SDMs) in predicting the drivers and distribution of two widespread CAM plants, Opuntia ficus‐indica and Euphorbia tirucalli. Using two different algorithms and five predictor sets, we created distribution models for these exemplar species and produced an updated map of global inter‐annual rainfall predictability. No single predictor set produced markedly more accurate models, with the basic bioclim‐only predictor set marginally out‐performing combinations with additional predictors. Minimum temperature of the coldest month was the single most important variable in determining spatial distribution, but additional predictors such as precipitation and inter‐annual precipitation variability were also important in explaining the differences in spatial predictions between SDMs. When compared against previous projections, an a posteriori approach correctly does not predict distributions in areas of ecophysiological tolerance yet known absence (e.g., due to biotic competition). An updated map of inter‐annual rainfall predictability has successfully identified regions known to be depauperate in succulent plants. High model performance metrics suggest that the majority of potentially suitable regions for these species are predicted by these models with a limited number of climate predictors, and there is no benefit in expanding model complexity and increasing the potential for overfitting.

Sampling and modelling rare species: Conceptual guidelines for the neglected majority

Biodiversity conservation faces a methodological conundrum: Biodiversity measurement often relies on species, most of which are rare at various scales, especially prone to extinction under global change, but also the most challenging to sample and model. Predicting the distribution change of rare species using conventional species distribution models is challenging because rare species are hardly captured by most survey systems. When enough data are available, predictions are usually spatially biased towards locations where the species is most likely to occur, violating the assumptions of many modelling frameworks. Workflows to predict and eventually map rare species distributions imply important trade-offs between data quantity, quality, representativeness and model complexity that need to be considered prior to survey and analysis. Our opinion is that study designs need to carefully integrate the different steps, from species sampling to modelling, in accordance with the different types of rarity and available data in order to improve our capacity for sound assessment and prediction of rare species distribution. In this article, we summarize and comment on how different categories of species rarity lead to different types of occurrence and distribution data depending on choices made during the survey process, namely the spatial distribution of samples (where to sample) and the sampling protocol in each selected location (how to sample). We then clarify which species distribution models are suitable depending on the different types of distribution data (how to model). Among others, for most rarity forms, we highlight the insights from systematic species-targeted sampling coupled with hierarchical models that allow correcting for overdispersion and spatial and sampling sources of bias. Our article provides scientists and practitioners with a much-needed guide through the ever-increasing diversity of methodological developments to improve the prediction of rare species distribution depending on rarity type and available data.

Worldclim 2.1 versus Worldclim 1.4: Climatic niche and grid resolution affect between‐version mismatches in Habitat Suitability Models predictions across Europe

The influence of climate on the distribution of taxa has been extensively investigated in the last two decades through Habitat Suitability Models (HSMs). In this context, the Worldclim database represents an invaluable data source as it provides worldwide climate surfaces for both historical and future time horizons. Thousands of HSMs‐based papers have been published taking advantage of Worldclim 1.4, the first online version of this repository. In 2017, Worldclim 2.1 was released. Here, we evaluated spatially explicit prediction mismatch at continental scale, focusing on Europe, between HSMs fitted using climate surfaces from the two Worldclim versions (between‐version differences). To this aim, we simulated occurrence probability and presence‐absence across Europe of four virtual species (VS) with differing climate‐occurrence relationships. For each VS, we fitted HSMs upon uncorrelated bioclimatic variables derived from each Worldclim version at three grid resolutions. For each factor combination, HSMs attaining sufficient discrimination performance on spatially independent test data were projected across Europe under current conditions and various future scenarios, and importance scores of the single variables were computed. HSMs failed in accurately retrieving the simulated climate‐occurrence relationships for the climate‐tolerant VS and the one occurring under a narrow combination of climatic conditions. Under current climate, noticeable between‐version prediction mismatch emerged across most of Europe for these two VSs, whose simulated suitability mainly depended upon diurnal or yearly variability in temperature; differently, between‐version differences were more clustered toward areas showing extreme values, like mountainous massifs or southern regions, for VSs responding to average temperature and precipitation trends. Under future climate, the chosen emission scenarios and Global Climate Models did not evidently influence between‐version prediction discrepancies, while grid resolution synergistically interacted with VSs' niche characteristics in determining extent of such differences. Our findings could help in re‐evaluating previous biodiversity‐related works relying on geographical predictions from Worldclim‐based HSMs.

Predicting range shifts of Davidia involucrata Ball. under future climate change

Understanding and predicting how species will respond to climate change is crucial for biodiversity conservation. Here, we assessed future climate change impacts on the distribution of a rare and endangered plant species, Davidia involucrate in China, using the most recent global circulation models developed in the sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC6). We assessed the potential range shifts in this species by using an ensemble of species distribution models (SDMs). The ensemble SDMs exhibited high predictive ability and suggested that the temperature annual range, annual mean temperature, and precipitation of the driest month are the most influential predictors in shaping distribution patterns of this species. The projections of the ensemble SDMs also suggested that D. involucrate is very vulnerable to future climate change, with at least one-third of its suitable range expected to be lost in all future climate change scenarios and will shift to the northward of high-latitude regions. Similarly, at least one-fifth of the overlap area of the current nature reserve networks and projected suitable habitat is also expected to be lost. These findings suggest that it is of great importance to ensure that adaptive conservation management strategies are in place to mitigate the impacts of climate change on D. involucrate.

Global potential distribution prediction of Xanthium italicum based on Maxent model

Alien invasive plants pose a threat to global biodiversity and the cost of control continues to rise. Early detection and prediction of potential risk areas are essential to minimize ecological and socio-economic costs. In this study, the Maxent model was used to predict current and future climatic conditions to estimate the potential global distribution of the invasive plant Xanthium italicum. The model consists of 366 occurrence records (10 repeats, 75% for calibration and 25% for verification) and 10 climate prediction variables. According to the model forecast, the distribution of X. italicum was expected to shrink in future climate scenarios with human intervention, which may be mainly caused by the rise in global average annual temperature. The ROC curve showed that the AUC values of the training set and the test set are 0.965 and 0.906, respectively, indicating that the prediction result of this model was excellent. The contribution rates of annual mean temperature, monthly mean diurnal temperature range, standard deviation of temperature seasonal change and annual average precipitation to the geographical distribution of X. italicum were 65.3%, 11.2%, 9.0%, and 7.7%, respectively, and the total contribution rate was 93.2%. These four variables are the dominant environmental factors affecting the potential distribution of X. italicum, and the influence of temperature is greater than that of precipitation. Through our study on the potential distribution prediction of X. italicum under the future climatic conditions, it has contribution for all countries to strengthen its monitoring, prevention and control, including early warning.

The impact of climate change on western Plethodon salamanders' distribution

AIM

Given that salamanders have experienced large shifts in their distributions over time, we determined how each species of Plethodon in the Pacific Northwest would respond to climate change. We incorporated several greenhouse scenarios both on a species-by-species basis, and also using phylogenetic groups, with the aim to determine the best course of action in managing land area to conserve diversity in this group.

LOCATION

Pacific Northwest of the United States (northern CA, OR, WA, ID, and MT).

MAJOR TAXA STUDIED

Western Plethodon salamanders.

METHODS

Species distribution models were estimated using MaxEnt for the current time period and for several future climate scenarios using bioclimatic data layers. We used several methods to quantify the change in habitat suitability over time from the models. We explored aspects of the climate layers to determine whether we can expect a concerted response to climate change due to similarity in ecological niche or independent responses that could be harder to manage.

RESULTS

The distribution of western Plethodon salamander species is strongly influenced by precipitation and less so by temperature. Species responses to climate change resulted in both increases and decreases in predicted suitable habitat, though most species ranges do not contract, especially when taken as a phylogenetic group.

MAIN CONCLUSIONS

While some established habitats may become more or less climatically suitable, the overall distribution of species in this group is unlikely to be significantly affected. Clades of Plethodon species are unlikely to be in danger of extirpation despite the possibility that individual species may be threatened as a result of limited distributions. Grouping species into lineages with similar geographic ranges can be a viable method of determining conservation needs. More biotic and dispersal information is needed to determine the true impact that changes in climate will have on the distribution of Plethodon species.

Is New Always Better? Frontiers in Global Climate Datasets for Modeling Treeline Species in the Himalayas

Comparing and evaluating global climate datasets and their effect on model performance in regions with limited data availability has received little attention in ecological modeling studies so far. In this study, we aim at comparing the interpolated climate dataset Worldclim 1.4, which is the most widely used in ecological modeling studies, and the quasi-mechanistical downscaled climate dataset Chelsa, as well as their latest versions Worldclim 2.1 and Chelsa 1.2, with regard to their suitability for modeling studies. To evaluate the effect of these global climate datasets at the meso-scale, the ecological niche of Betula utilis in Nepal is modeled under current and future climate conditions. We underline differences regarding methodology and bias correction between Chelsa and Worldclim versions and highlight potential drawbacks for ecological models in remote high mountain regions. Regarding model performance and prediction plausibility under current climatic conditions, Chelsa-based models significantly outperformed Worldclim-based models, however, the latest version of Chelsa contains partially inherent distorted precipitation amounts. This study emphasizes that unmindful usage of climate data may have severe consequences for modeling treeline species in high-altitude regions as well as for future projections, if based on flawed current model predictions. The results illustrate the inevitable need for interdisciplinary investigations and collaboration between climate scientists and ecologists to enhance climate-based ecological model quality at meso- to local-scales by accounting for local-scale physical features at high temporal and spatial resolution.

The population genetics of nonmigratory Allen's Hummingbird (Selasphorus sasin sedentarius) following a recent mainland colonization

Allen's Hummingbird comprises two subspecies, one migratory (Selasphorus sasin sasin) and one nonmigratory (S. s. sedentarius). The nonmigratory subspecies, previously endemic to the California Channel Islands, apparently colonized the California mainland on the Palos Verdes Peninsula some time before 1970 and now breeds throughout coastal southern California. We sequenced and compared populations of mainland nonmigratory Allen's Hummingbird to Channel Island populations from Santa Catalina, San Clemente, and Santa Cruz Island. We found no evidence of founder effects on the mainland population. Values of nucleotide diversity on the mainland were higher than on the Channel Islands. There were low levels of divergence between the Channel Islands and the mainland, and Santa Cruz Island was the most genetically distinct. Ecological niche models showed that rainfall and temperature variables on the Channel Islands are similar in the Los Angeles basin and predicted continued expansion of nonmigratory Allen's Hummingbird north along the coast and inland. We also reviewed previous genetic studies of vertebrate species found on the Channel Islands and mainland and showed that broad conclusions regarding island-mainland patterns remain elusive. Challenges include the idiosyncratic nature of colonization itself as well as the lack of a comprehensive approach that incorporates similar markers and sampling strategies across taxa, which, within the context of a comparative study of island-mainland relationships, may lead to inconsistent results.

Supraspecific units in correlative niche modeling improves the prediction of geographic potential of biological invasions

BACKGROUND

Biological invasions rank among the most significant threats to biodiversity and ecosystems. Correlative ecological niche modeling is among the most frequently used tools with which to estimate potential distributions of invasive species. However, when areas accessible to the species across its native distribution do not represent the full spectrum of environmental conditions that the species can tolerate, correlative studies often underestimate fundamental niches.

METHODS

Here, we explore the utility of supraspecific modeling units to improve the predictive ability of models focused on biological invasions. Taking into account phylogenetic relationships in correlative ecological niche models, we studied the invasion patterns of three species (Aedes aegypti, Pterois volitans and Oreochromis mossambicus).

RESULTS

Use of supraspecific modeling units improved the predictive ability of correlative niche models in anticipating potential distributions of three invasive species. We demonstrated that integrating data on closely related species allowed a more complete characterization of fundamental niches. This approach could be used to model species with invasive potential but that have not yet invaded new regions.

Multiple invasions of a generalist herbivore-Secondary contact between two divergent lineages of Nezara viridula Linnaeus in Australia

The presence of distinct evolutionary lineages within herbivorous pest insect taxa requires close attention. Scientific understanding, biosecurity planning and practice, and pest management decision-making each suffer when such situations remain poorly understood. The pest bug Nezara viridula Linnaeus has been recorded from numerous host plants and has two globally distributed mitochondrial (mtDNA) lineages. These mtDNA lineages co-occur in few locations globally, and the consequences of their divergence and recent secondary contact have not been assessed. We present evidence that both mtDNA lineages of N. viridula are present in Australia and their haplotype groups have a mostly separate distribution from one another. The north-western population has only Asian mtDNA haplotypes, and the population with an eastern distribution is characterized mostly by European mtDNA haplotypes. Haplotypes of both lineages were detected together at only one site in the north of eastern Australia, and microsatellite data indicate that this secondary contact has resulted in mating across the lineages. Admixture and the movement of mtDNA haplotypes outside of this limited area of overlap has not, however, been extensive. Some degree of mating incompatibility or differences in the climatic requirements and tolerances of the two lineages, and perhaps a combination of these influences, might limit introgression and the movement of individuals, but this needs to be tested. This work provides the foundation for further ecological investigation of the lineages of N. viridula, particularly the consequences of admixture on the ecology of this widespread pest. We propose that for now, the Asian and European lineages of N. viridula would best be investigated as subspecies, so that "pure" and admixed populations of this bug can each be considered directly with respect to management and research priorities.

CJ, Peterson AT. Acknowledging uncertainty in evolutionary reconstructions of ecological niches

Reconstructing ecological niche evolution can provide insight into the biogeography and diversification of evolving lineages. However, comparative phylogenetic methods may infer the history of ecological niche evolution inaccurately because (a) species' niches are often poorly characterized; and (b) phylogenetic comparative methods rely on niche summary statistics rather than full estimates of species' environmental tolerances. Here, we propose a new framework for coding ecological niches and reconstructing their evolution that explicitly acknowledges and incorporates the uncertainty introduced by incomplete niche characterization. Then, we modify existing ancestral state inference methods to leverage full estimates of environmental tolerances. We provide a worked empirical example of our method, investigating ecological niche evolution in the New World orioles (Aves: Passeriformes: Icterus spp.). Temperature and precipitation tolerances were generally broad and conserved among orioles, with niche reduction and specialization limited to a few terminal branches. Tools for performing these reconstructions are available in a new R package called nichevol.

Modelling sexually deceptive orchid species distributions under future climates: the importance of plant-pollinator interactions

Biotic interactions play an important role in species distribution models, whose ignorance may cause an overestimation of species' potential distributions. Species of the family Orchidaceae are almost totally dependent on mycorrhizal symbionts and pollinators, with sexually deceptive orchids being often highly specialized, and thus the interactions with their pollinators are expected to strongly affect distribution predictions. We used Maxent algorithm to explore the extent of current and future habitat suitability for two Greek endemic sexually deceptive orchids (Ophrys argolica and Ophrys delphinensis) in relation to the potential distribution of their unique pollinator (Anthophora plagiata). Twelve climate change scenarios were used to predict future distributions. Results indicated that the most important factors determining potential distribution were precipitation seasonality for O. argolica and geological substrate for O. delphinensis. The current potential distribution of the two orchids was almost of the same extent but spatially different, without accounting for their interaction with A. plagiata. When the interaction was included in the models, their potentially suitable area decreased for both species. Under future climatic conditions, the effects of the orchid-pollinator interaction were more intense. Specifically, O. argolica was restricted in specific areas of southern Greece, whereas O. delphinensis was expected to become extinct. Our findings highlighted the significant role of plant–pollinator interactions in species distribution models. Failing to study such interactions might expose plant species to serious conservation issues.

Increased diversification rates are coupled with higher rates of climate space exploration in Australian Acacia (Caesalpinioideae)

Australia is an excellent setting to explore relationships between climate change and diversification dynamics. Aridification since the Eocene has resulted in spectacular radiations within one or more Australian biomes. Acacia is the largest plant genus on the Australian continent, with around 1000 species, and is present in all biomes. We investigated the macroevolutionary dynamics of Acacia within climate space. We analysed phylogenetic and climatic data for 503 Acacia species to estimate a time-calibrated phylogeny and central climatic tendencies for BioClim layers from 132 000 herbarium specimens. Diversification rate heterogeneity and rates of climate space exploration were tested. We inferred two diversification rate increases, both associated with significantly higher rates of climate space exploration. Observed spikes in climate disparity within the Pleistocene correspond with onset of Pleistocene glacial-interglacial cycling. Positive time dependency in environmental disparity applies in the basal grade of Acacia, though climate space exploration rates were lower. Incongruence between rates of climate space exploration and disparity suggests different Acacia lineages have experienced different macroevolutionary processes. The second diversification rate increase is associated with a south-east Australian mesic lineage, suggesting adaptations to progressively aridifying environments and ability to transition into mesic environments contributed to Acacia's dominance across Australia.

A checklist for maximizing reproducibility of ecological niche models

Reporting specific modelling methods and metadata is essential to the reproducibility of ecological studies, yet guidelines rarely exist regarding what information should be noted. Here, we address this issue for ecological niche modelling or species distribution modelling, a rapidly developing toolset in ecology used across many aspects of biodiversity science. Our quantitative review of the recent literature reveals a general lack of sufficient information to fully reproduce the work. Over two-thirds of the examined studies neglected to report the version or access date of the underlying data, and only half reported model parameters. To address this problem, we propose adopting a checklist to guide studies in reporting at least the minimum information necessary for ecological niche modelling reproducibility, offering a straightforward way to balance efficiency and accuracy. We encourage the ecological niche modelling community, as well as journal reviewers and editors, to utilize and further develop this framework to facilitate and improve the reproducibility of future work. The proposed checklist framework is generalizable to other areas of ecology, especially those utilizing biodiversity data, environmental data and statistical modelling, and could also be adopted by a broader array of disciplines.

Collinearity in ecological niche modeling: Confusions and challenges

Ecological niche models are widely used in ecology and biogeography. Maxent is one of the most frequently used niche modeling tools, and many studies have aimed to optimize its performance. However, scholars have conflicting views on the treatment of predictor collinearity in Maxent modeling. Despite this lack of consensus, quantitative examinations of the effects of collinearity on Maxent modeling, especially in model transfer scenarios, are lacking. To address this knowledge gap, here we quantify the effects of collinearity under different scenarios of Maxent model training and projection. We separately examine the effects of predictor collinearity, collinearity shifts between training and testing data, and environmental novelty on model performance. We demonstrate that excluding highly correlated predictor variables does not significantly influence model performance. However, we find that collinearity shift and environmental novelty have significant negative effects on the performance of model transfer. We thus conclude that (a) Maxent is robust to predictor collinearity in model training; (b) the strategy of excluding highly correlated variables has little impact because Maxent accounts for redundant variables; and (c) collinearity shift and environmental novelty can negatively affect Maxent model transferability. We therefore recommend to quantify and report collinearity shift and environmental novelty to better infer model accuracy when models are spatially and/or temporally transferred.

Climatic shifts drove major contractions in avian latitudinal distributions throughout the Cenozoic

Many higher level avian clades are restricted to Earth's lower latitudes, leading to historical biogeographic reconstructions favoring a Gondwanan origin of crown birds and numerous deep subclades. However, several such "tropical-restricted" clades (TRCs) are represented by stem-lineage fossils well outside the ranges of their closest living relatives, often on northern continents. To assess the drivers of these geographic disjunctions, we combined ecological niche modeling, paleoclimate models, and the early Cenozoic fossil record to examine the influence of climatic change on avian geographic distributions over the last ∼56 million years. By modeling the distribution of suitable habitable area through time, we illustrate that most Paleogene fossil-bearing localities would have been suitable for occupancy by extant TRC representatives when their stem-lineage fossils were deposited. Potentially suitable habitat for these TRCs is inferred to have become progressively restricted toward the tropics throughout the Cenozoic, culminating in relatively narrow circumtropical distributions in the present day. Our results are consistent with coarse-scale niche conservatism at the clade level and support a scenario whereby climate change over geological timescales has largely dictated the geographic distributions of many major avian clades. The distinctive modern bias toward high avian diversity at tropical latitudes for most hierarchical taxonomic levels may therefore represent a relatively recent phenomenon, overprinting a complex biogeographic history of dramatic geographic range shifts driven by Earth's changing climate, variable persistence, and intercontinental dispersal. Earth's current climatic trajectory portends a return to a megathermal state, which may dramatically influence the geographic distributions of many range-restricted extant clades.

Niche conservatism predominates in adaptive radiation: comparing the diversification of Hawaiian arthropods using ecological niche modelling

The role of the environmental niche in fostering ecological divergence during adaptive radiation remains enigmatic. In this study, we examine the interplay between environmental niche divergence and conservatism in the context of adaptive radiation on oceanic islands, by characterizing the niche breadth of four Hawaiian arthropod radiations: Tetragnatha spiders (Tetragnathidae Latreille, 1804), Laupala crickets (Gryllidae Otte, 1994), a clade of Drosophila flies (Drosophilidae Fallén, 1823) and Nesosydne planthoppers (Delphacidae Kirkaldy, 1907). We assembled occurrence datasets for the four lineages, modelled their distributions and quantified niche overlap. All four groups occupy the islands in distinct ways, highlighting the contrasting axes of diversification for different lineages. Laupala and Nesosydne have opposite environmental niche extents (broad and narrow, respectively), whereas Tetragnatha and Drosophila share relatively intermediate tolerances. Temperature constrains the distributions of all four radiations. Tests of phylogenetic signal suggest that, for Tetragnatha and Drosophila, closely related species exhibit similar environmental niches; thus, diversification is associated with niche conservatism. Sister species comparisons also show that populations often retain similar environmental tolerances, although exceptions do occur. Results imply that diversification does not occur through ecological speciation; instead, adaptive radiation occurs largely within a single environment.

kuenm: an R package for detailed development of ecological niche models using Maxent

Background

Ecological niche modeling is a set of analytical tools with applications in diverse disciplines, yet creating these models rigorously is now a challenging task. The calibration phase of these models is critical, but despite recent attempts at providing tools for performing this step, adequate detail is still missing. Here, we present the kuenm R package, a new set of tools for performing detailed development of ecological niche models using the platform Maxent in a reproducible way.

Results

This package takes advantage of the versatility of R and Maxent to enable detailed model calibration and selection, final model creation and evaluation, and extrapolation risk analysis. Best parameters for modeling are selected considering (1) statistical significance, (2) predictive power, and (3) model complexity. For final models, we enable multiple parameter sets and model transfers, making processing simpler. Users can also evaluate extrapolation risk in model transfers via mobility-oriented parity (MOP) metric.

Discussion

Use of this package allows robust processes of model calibration, facilitating creation of final models based on model significance, performance, and simplicity. Model transfers to multiple scenarios, also facilitated in this package, significantly reduce time invested in performing these tasks. Finally, efficient assessments of strict-extrapolation risks in model transfers via the MOP and MESS metrics help to prevent overinterpretation in model outcomes.

Effects of mis-alignment between dispersal traits and landscape structure on dispersal success in fragmented landscapes

Dispersal is fundamental to population dynamics and hence extinction risk. The dispersal success of animals depends on the biophysical structure of their environments and their biological traits; however, comparatively little is known about how evolutionary trade-offs among suites of biological traits affect dispersal potential. We developed a spatially explicit agent-based simulation model to evaluate the influence of trade-offs among a suite of biological traits on the dispersal success of vagile animals in fragmented landscapes. We specifically chose traits known to influence dispersal success: speed of movement, perceptual range, risk of predation, need to forage during dispersal, and amount of suitable habitat required for successful settlement in a patch. Using the metric of relative dispersal success rate, we assessed how the costs and benefits of evolutionary investment in these biological traits varied with landscape structure. In heterogeneous environments with low habitat availability and scattered habitat patches, individuals with more equal allocation across the trait spectrum dispersed most successfully. Our analyses suggest that the dispersal success of animals in heterogeneous environments is highly dependent on hierarchical interactions between trait trade-offs and the geometric configurations of the habitat patches in the landscapes through which they disperse. In an applied sense, our results indicate potential for ecological mis-alignment between species' evolved suites of dispersal-related traits and altered environmental conditions as a result of rapid global change. In many cases identifying the processes that shape patterns of animal dispersal, and the consequences of abiotic changes for these processes, will require consideration of complex relationships among a range of organism-specific and environmental factors.

Species distribution models and empirical test: Comparing predictions with well-understood geographical distribution of Bothrops alternatus in Argentina

Species distribution models (SDMs) estimate the geographical distribution of species although with several limitations due to sources of inaccuracy and biases. Empirical tests arose as the most important steps in scientific knowledge to assess the efficiency of model predictions, which are poorly rigorous in SDMs. A good approach to the empirical distribution (ED) of a species can be obtained from comprehensive empirical knowledge, that is, well-understood distributions gathered from large amount of data generated with appropriate spatial and temporal samples coverage. The aims of this study were to (a) compare different SDMs predictions with an ED; and (b) evaluate if fuzzy global matching (FGM) could be used as an index to compare SDMs predictions and ED. Six algorithms with 5 and 20 variables were used to assess their accuracy in predicting the ED of the venomous snake Bothrops alternatus (Viperidae). Its entire distribution is known, thanks to thorough field surveys across Argentina, with 1,767 records. ED was compared with SDMs predictions using Map Comparison Kit. SDMs predictions showed important biases in all methods used, from 70% sub-estimation to 40% over-estimation of ED. BIOCLIM predicted ≈31% of B. alternatus ED. DOMAIN predicted 99% of ED, but over-estimated 40% of the area. GLM with five variables calculated 75% of ED, while Genetic Algorithm for Rule-set Prediction showed ≈60% of ED; the last two presenting overpredictions in areas with favorable climatic conditions but not inhabited by the species. MaxEnt and RF were the only methods to detect isolated populations in the southern distribution of B. alternatus. Although SDMs proved useful in making predictions about species distribution, predictions need validation with expert maps knowledge and ED. Moreover, FGM showed a good performance as an index with values similar to True Skill Statistic, so that it could be used to relate ED and SDMs predictions.

Reconstructing Ecological Niche Evolution When Niches Are Incompletely Characterized

Evolutionary dynamics of abiotic ecological niches across phylogenetic history can shed light on large-scale biogeographic patterns, macroevolutionary rate shifts, and the relative ability of lineages to respond to global change. An unresolved question is how best to represent and reconstruct evolution of these complex traits at coarse spatial scales through time. Studies have approached this question by integrating phylogenetic comparative methods with niche estimates inferred from correlative and other models. However, methods for estimating niches often produce incomplete characterizations, as they are inferred from present-day distributions that may be limited in full expression of the fundamental ecological niche by biotic interactions, dispersal limitations, and the existing set of environmental conditions. Here, we test whether incomplete niche characterizations inherent in most estimates of species' niches bias phylogenetic reconstructions of niche evolution, using simulations of virtual species with known niches. Results establish that incompletely characterized niches inflate estimates of evolutionary change and lead to error in ancestral state reconstructions. Our analyses also provide a potential mechanism to explain the frequent observation that maximum thermal tolerances are more conserved than minimum thermal tolerances: populations and species experience more spatial variation in minimum temperature than in maximum temperature across their distributions and, consequently, may experience stronger diversifying selection for cold tolerance.