Predicting potential distribution of chestnut phylloxerid (Hemiptera: Phylloxeridae) based on GARP and Maxent ecological niche models

The chestnut phylloxerid, Moritziella castaneivora, has been recently recorded as a forest pest in China. It heavily damaged chestnut trees and has caused serious economic losses in some main chestnut production areas. In order to effectively monitor and manage this pest, it is necessary to investigate its potential geographical distribution worldwide. In this study, we used two ecological niche models, Genetic Algorithm for Rule‐set Production (GARP) and Maximum Entropy (Maxent), along with the geographical distribution of the host plants, Japanese chestnut (Castanea crenata) and Chinese chestnut (Castanea mollissima), to predict the potential geographical distribution of M. castaneivora. The results suggested that the suitable distribution areas based on GARP were general consistent with those based on Maxent, but GARP predicted distribution areas that extended more in size than did Maxent. The results also indicated that the suitable areas for chestnut phylloxerid infestations were mainly restricted to Northeast China (northern Liaoning), East China (southern Shandong, northern Jiangsu and western Anhui), North China (southern Hebei, Beijing and Tianjin), Central China (eastern Hubei and southern Henan), Japan (Kinki, Shikoku and Tohoku) and most parts of the Korean Peninsula. In addition, some provinces of central and western China were predicted to have low suitability or unsuitable areas (e.g. Xinjiang, Qinghai and Tibet). A jackknife test in Maxent showed that the average precipitation in July was the most important environmental variable affecting the distribution of this pest species. Consequently, the study suggests several reasonable regulations and management strategies for avoiding the introduction or invasion of this high‐risk chestnut pest to these potentially suitable areas.     

Potential geographic distribution of brown marmorated stink bug invasion (Halyomorpha halys)

Background

The Brown Marmorated Stink Bug (BMSB), Halyomorpha halys (Stål) (Hemiptera: Pentatomidae), native to Asia, is becoming an invasive species with a rapidly expanding range in North America and Europe. In the US, it is a household pest and also caused unprecedented damage to agriculture crops. Exploring its climatic limits and estimating its potential geographic distribution can provide critical information for management strategies.

Methodology/Principals

We used direct climate comparisons to explore the climatic niche occupied by native and invasive populations of BMSB. Ecological niche modelings based on the native range were used to anticipate the potential distribution of BMSB worldwide. Conversely, niche models based on the introduced range were used to locate the original invasive propagates in Asia. Areas with high invasion potential were identified by two niche modeling algorithms (i.e., Maxent and GARP).

Conclusions/Significance

Reduced dimensionality of environmental space improves native model transferability in the invade area. Projecting models from invasive population back to native distributional areas offers valuable information on the potential source regions of the invasive populations. Our models anticipated successfully the current disjunct distribution of BMSB in the US. The original propagates are hypothesized to have come from northern Japan or western Korea. High climate suitable areas at risk of invasion include latitudes between 30°–50° including northern Europe, northeastern North America, southern Australia and the North Island of New Zealand. Angola in Africa and Uruguay in South America also showed high climate suitability.     

Integrating mechanistic and empirical model projections to assess climate impacts on tree species distributions in northwestern North America

Empirical and mechanistic models have both been used to assess the potential impacts of climate change on species distributions, and each modeling approach has its strengths and weaknesses. Here, we demonstrate an approach to projecting climate‐driven changes in species distributions that draws on both empirical and mechanistic models. We combined projections from a dynamic global vegetation model (DGVM) that simulates the distributions of biomes based on basic plant functional types with projections from empirical climatic niche models for six tree species in northwestern North America. These integrated model outputs incorporate important biological processes, such as competition, physiological responses of plants to changes in atmospheric CO₂ concentrations, and fire, as well as what are likely to be species‐specific climatic constraints. We compared the integrated projections to projections from the empirical climatic niche models alone. Overall, our integrated model outputs projected a greater climate‐driven loss of potentially suitable environmental space than did the empirical climatic niche model outputs alone for the majority of modeled species. Our results also show that refining species distributions with DGVM outputs had large effects on the geographic locations of suitable habitat. We demonstrate one approach to integrating the outputs of mechanistic and empirical niche models to produce bioclimatic projections. But perhaps more importantly, our study reveals the potential for empirical climatic niche models to over‐predict suitable environmental space under future climatic conditions.     

Using ecological niche modelling to evaluate niche stability in deep time

Aim To investigate relative niche stability in species responses to various types of environmental pressure (biotic and abiotic) on geological time‐scales using the fossil record. Location The case study focuses on Late Ordovician articulate brachiopods of the Cincinnati Arch in eastern North America. Methods Species niches were modelled for a suite of fossil brachiopod species based on five environmental variables inferred from sedimentary parameters using GARP and Maxent . Niche stability was assessed by comparison of (1) the degree of overlap of species distribution models developed for a time‐slice and those generated by projecting niche models of the previous time‐slice onto environmental layers of a second time‐slice using GARP and Maxent , (2) Schoener’s D statistic, and (3) the similarity of the contribution of each environmental parameter within Maxent niche models between adjacent time‐slices. Results Late Ordovician brachiopod species conserved their niches with high fidelity during intervals of gradual environmental change but responded to inter‐basinal species invasions through niche evolution. Both native and invasive species exhibited similar levels of niche evolution in the invasion and post‐invasion intervals. Niche evolution was related mostly to decreased variance within the former ecological niche parameters rather than to shifts to new ecospace. Main conclusions Although the species examined exhibited morphological stasis during the study interval, high levels of niche conservatism were observed only during intervals of gradual environmental change. Rapid environmental change, notably inter‐basinal species invasions, resulted in high levels of niche evolution among the focal taxa. Both native and invasive species responded with similar levels of niche evolution during the invasion interval and subsequent environmental reorganization. The assumption of complete niche conservatism frequently employed in ecological niche modelling (ENM) analyses to forecast or hindcast species geographical distributions is more likely to be accurate for climate change studies than for invasive species analyses over geological time‐scales.     

Sampling bias and the use of ecological niche modeling in conservation planning: a field evaluation in a biodiversity hotspot

Ecological niche modeling (ENM) has become an important tool in conservation biology. Despite its recent success, several basic issues related to algorithm performance are still being debated. We assess the ability of two of the most popular algorithms, GARP and Maxent, to predict distributions when sampling is geographically biased. We use an extensive data set collected in the Brazilian Cerrado, a biodiversity hotspot in South America. We found that both algorithms give richness predictions that are very similar to other traditionally used richness estimators. Also, both algorithms correctly predicted the presence of most species collected during fieldwork, and failed to predict species collected only in very few cases (usually species with very few known localities, i.e., <5). We also found that Maxent tends to be more sensitive to sampling bias than GARP. However, Maxent performs better when sampling is poor (e.g., low number of data points). Our results indicates that ENM, even when provided with limited and geographically biased localities, is a very useful technique to estimate richness and composition of unsampled areas. We conclude that data generated by ENM maximize the utility of existing biodiversity data, providing a very useful first evaluation. However, for reliable conservation decisions ENM data must be followed by well-designed field inventories, especially for the detection of restricted range, rare species.     

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

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

Mexican alpine plants in the face of global warming: potential extinction within a specialized assemblage of narrow endemics

Alpine ecosystems occur under extreme climatic conditions and, as a result, house a unique and vulnerable biota. They are very scarce at tropical latitudes; in Mexico occur mainly along the Trans-Mexican Volcanic Belt, where species richness is not high but narrow endemics stand out. We investigate the effects of climate change under hypothesized contrasting climate warming scenarios using ecological niche modeling of five microendemic alpine species. Occurrence data was obtained mainly from field trips, but herbaria were also examined. A total of 21 climatic and topographic variables, as well as individual selections of 12–16 variables were employed to construct models with Maxent and GARP. Depending on the number of occurrences, current models were validated with Partial-ROC or Jackknife procedures; and projections to 2050 and 2070 were made using two Representative Concentration Pathways and two Global Circulation Models. All species’ models showed a clear pattern of contraction under the explored scenarios; over 58 % of contemporary climatic distribution disappeared, suggesting that analyzed species face imminent extinction due to climatic habitat loss. The models are useful in representing the endemic component of Mexican alpine grassland by reciprocal correspondence in geographic distribution, and we consider it as a highly endangered ecosystem due to climate change, which is probably applicable to other tropical alpine ecosystems. The Pico de Orizaba volcano seems the best option to preserve due to its extension and elevation. However, further studies at finer scales are needed to improve in situ preservation and conservation strategies that include translocation, assisted migration and seed banking.     

Modeling potential habitats for alien species Dreissena polymorpha in Continental USA

The effective measure to minimize the damage of invasive species is to block the potential invasive species to enter into suitable areas. 1864 occurrence points with GPS coordinates and 34 environmental variables from Daymet datasets were gathered, and 4 modeling methods, i.e., Logistic Regression (LR), Classification and Regression Trees (CART), Genetic Algorithm for Rule-Set Prediction (GARP), and maximum entropy method (Maxent), were introduced to generate potential geographic distributions for invasive species Dreissena polymorpha in Continental USA. Then 3 statistical criteria of the area under the Receiver Operating Characteristic curve (AUC), Pearson correlation (COR) and Kappa value were calculated to evaluate the performance of the models, followed by analyses on major contribution variables. Results showed that in terms of the 3 statistical criteria, the prediction results of the 4 ecological niche models were either excellent or outstanding, in which Maxent outperformed the others in 3 aspects of predicting current distribution habitats, selecting major contribution factors, and quantifying the influence of environmental variables on habitats. Distance to water, elevation, frequency of precipitation and solar radiation were 4 environmental forcing factors. The method suggested in the paper can have some reference meaning for modeling habitats of alien species in China and provide a direction to prevent Mytilopsis sallei on the Chinese coast line.     

Modeling potential habitats for alien species Dreissena polymorpha in Continental USA

The effective measure to minimize the damage of invasive species is to block the potential invasive species to enter into suitable areas. 1864 occurrence points with GPS coordinates and 34 environmental variables from Daymet datasets were gathered, and 4 modeling methods, i.e., Logistic Regression (LR), Classification and Regression Trees (CART), Genetic Algorithm for Rule-Set Prediction (GARP), and maximum entropy method (Maxent), were introduced to generate potential geographic distributions for invasive species Dreissena polymorpha in Continental USA. Then 3 statistical criteria of the area under the Receiver Operating Characteristic curve (AUC), Pearson correlation (COR) and Kappa value were calculated to evaluate the performance of the models, followed by analyses on major contribution variables. Results showed that in terms of the 3 statistical criteria, the prediction results of the 4 ecological niche models were either excellent or outstanding, in which Maxent outperformed the others in 3 aspects of predicting current distribution habitats, selecting major contribution factors, and quantifying the influence of environmental variables on habitats. Distance to water, elevation, frequency of precipitation and solar radiation were 4 environmental forcing factors. The method suggested in the paper can have some reference meaning for modeling habitats of alien species in China and provide a direction to prevent Mytilopsis sallei on the Chinese coast line.     

Climate change effects on turtles of the genus Kinosternon (Testudines: Kinosternidae): an assessment of habitat suitability and climate niche conservatism

The Chelonian lineage has been exposed to several climate change events along its evolutionary history, but the rapid contemporary change in climate patterns has the potential to erode turtle populations. This study focuses on (1) evaluating the climatically suitable area available for 15 species of mud turtles of the genus Kinosternon, and on (2) assessing whether or not these species retain their ancestral climate niche. Occurrence data was collected for these species and, using the Maxent algorithm and WorldClim bioclimatic variables, suitable present and future climatic niche areas were modeled. In addition, we also carried out climatic niche similarity analyses between pairs of species to evaluate whether these conserve their climatic niche. Our models suggest that most species of Kinosternon will lose a high proportion of their suitable habitat in the future. Most mud turtle species seem to conserve their climatic niche, suggesting the prevalence of niche conservatism in the group. Our results indicate that several mud turtle species could be at severe risk of disappearing over the next few decades due to the loss of climatically suitable areas and of the conservation of their climatic niches.

     

Assassin bugs of the subfamily Diaspidiinae (Heteroptera: Reduviidae): distribution and potential ecological niches

The prediction and definition of the conditions for the potentially suitable ecological niche of the subfamily Diaspidiinae was the main goal of this study. Our research was based on 283 specimens of all known species of assassin bugs belonging to the subfamily Diaspidiinae stored in European museum collections and a set of 21 environmental variables in the form of a 1 × 1 km grid covering Africa and Madagascar. Based on occurrence localities, as well as a digital elevation model and layer of the tree cover‐continuous fields, information about the distribution of each species is given. Using Maxent software, potentially useful ecological niches were modeled, which allowed for the creation of a map of the potential distribution of the members of this subfamily and for determining their climatic preferences. A jackknife test showed that annual precipitation, annual temperature range and tree cover‐continuous fields were the most important environmental variables affecting the distribution of the subfamily Diaspidiinae. An analysis of climatic preferences suggested that the representatives of the subfamily were linked mainly to the tropical climate. An analysis of environmental variables also showed that the subfamily preferred areas with herbaceous vegetation and some trees, and this preference is probably caused by the food preferences of their prey. On the basis of the museum data on the species occurrence, as well as ecological niche modeling methods, we provided new and valuable information on potentially suitable habitat and the possible range of distribution of the subfamily Diaspidiinae along with its climatic preferences.     

Modelling ecological niches from low numbers of occurrences: assessment of the conservation status of poorly known viverrids (Mammalia, Carnivora) across two continents

The conservation of poorly known species is difficult because of incomplete knowledge on their biology and distribution. We studied the contribution of two ecological niche modelling tools, the Genetic Algorithm for Rule-set Prediction (GARP) and maximum entropy (Maxent), in assessing potential ranges and distributional connectivity among 12 of the least known African and Asian viverrids. The level of agreement between GARP and Maxent predictions was low when < 15 occurrences were available, probably indicating a minimum number below that necessary to obtain models with good predictive power. Unexpectedly, our results suggested that Maxent extrapolated more than GARP in the context of small sample sizes. Predictions were overlapped with current land use and location of protected areas to estimate the conservation status of each species. Our analyses yielded range predictions generally contradicting with extents of occurrence established by the IUCN. We evidenced a high level of disturbance within predicted distributions in West and East Africa, Sumatra, and South-East Asia, and identified within West African degraded lowlands four relatively preserved areas that might be of prime importance for the conservation of rainforest taxa. Knowing whether these species of viverrids may survive in degraded or alternative habitats is of crucial importance for further conservation planning. The level of coverage of species suitable ranges by existing and proposed IUCN reserves was low, and we recommend that the total surface of protected areas be substantially increased on both continents.     

Impact of climate change on vector transmission of Trypanosoma cruzi (Chagas, 1909) in North America

Climate change can influence the geographical range of the ecological niche of pathogens by altering biotic interactions with vectors and reservoirs. The distributions of 20 epidemiologically important triatomine species in North America were modelled, comparing the genetic algorithm for rule‐set prediction (GARP) and maximum entropy (MaxEnt), with or without topographical variables. Potential shifts in transmission niche for Trypanosoma cruzi (Trypanosomatida: Trypanosomatidae) (Chagas, 1909) were analysed for 2050 and 2070 in Representative Concentration Pathway (RCP) 4.5 and RCP 8.5. There were no significant quantitative range differences between the GARP and MaxEnt models, but GARP models best represented known distributions for most species [partial‐receiver operating characteristic (ROC) > 1]; elevation was an important variable contributing to the ecological niche model (ENM). There was little difference between niche breadth projections for RCP 4.5 and RCP 8.5; the majority of species shifted significantly in both periods. Those species with the greatest current distribution range are expected to have the greatest shifts. Positional changes in the centroid, although reduced for most species, were associated with latitude. A significant increase or decrease in mean niche elevation is expected principally for Neotropical 1 species. The impact of climate change will be specific to each species, its biogeographical region and its latitude. North American triatomines with the greatest current distribution ranges (Nearctic 2 and Nearctic/Neotropical) will have the greatest future distribution shifts. Significant shifts (increases or decreases) in mean elevation over time are projected principally for the Neotropical species with the broadest current distributions. Changes in the vector exposure threat to the human population were significant for both future periods, with a 1.48% increase for urban populations and a 1.76% increase for rural populations in 2050.     

How much do we overestimate future local extinction rates when restricting the range of occurrence data in climate suitability models?

Climate suitability models are used to make projections of species’ potential future distribution under climate change. When studying the species richness with such modeling methods, the extent of the study range is of particular importance, especially when the full range of occurrence is not considered for some species, often because of geographical or political limits. Here we examine biases induced by the use of range‐restricted occurrence data on predicted changes in species richness and predicted extinction rates, at study area margins. We compared projections of future suitable climate space for 179 bird species breeding in Iberia and North Africa (27 of them breeding only in North Africa though potential colonizers in Europe), using occurrence data from the full Western Palaearctic (WP) species range and from the often‐considered European‐restricted range. Current and future suitable climatic spaces were modeled using an ensemble forecast technique applied to five general circulation models and three climate scenarios, with eight climatic variables and eight modeling techniques. The use of range‐restricted compared to the full WP occurrence data of a species led to an underestimate of its suitable climatic space. The projected changes in species richness across the focus area (Iberia) varied considerably according to the occurrence data we used, with higher local extinction rates with European‐restricted data (on average 38 vs 12% for WP data). Modeling results for species currently breeding only in North Africa revealed potential colonization of the Iberian Peninsula (from a climatic point of view), which highlights the necessity to consider species outside the focus area if interested in forecasted changes in species richness. Therefore, the modeling of current and future species richness can lead to misleading conclusions when data from a restricted range of occurrence is used. Consequently, climate suitability models should use occurrence data from the complete distribution range of species, or at least within biogeographical areas.     

Transferability and model evaluation in ecological niche modeling: a comparison of GARP and Maxent

We compared predictive success in two common algorithms for modeling species' ecological niches, GARP and Maxent, in a situation that challenged the algorithms to be general – that is, to be able to predict the species' distributions in broad unsampled regions, here termed transferability. The results were strikingly different between the two algorithms – Maxent models reconstructed the overall distributions of the species at low thresholds, but higher predictive levels of Maxent predictions reflected overfitting to the input data; GARP models, on the other hand, succeeded in anticipating most of the species' distributional potential, at the cost of increased (apparent, at least) commission error. Receiver operating characteristic (ROC) tests were weak in discerning models able to predict into broad unsampled areas from those that were not. Such transferability is clearly a novel challenge for modeling algorithms, and requires different qualities than does predicting within densely sampled landscapes – in this case, Maxent was transferable only at very low thresholds, and biases and gaps in input data may frequently affect results based on higher Maxent thresholds, requiring careful interpretation of model results.     

基于最大熵值法生态位模型（Maxent）的三种实蝇潜在适生性分布预测

本研究首先对3种重要生态位模型BIOCLIM, DOMAIN和Maxent（基于最大熵值原理模型）的分布预测精确度进行了分析和比较, 再结合分布点记录以及一系列环境数据图层对3种重要外来入侵性检疫害虫（葫芦寡鬃实蝇Dacus bivittatus、埃塞俄比亚寡鬃实蝇D. ciliatus和西瓜寡鬃实蝇D. vertebratus）的潜在适生性分布区域进行了预测和分析。在模型预测精确度的比较过程中, 3种评估指标（ROC/AUC, Kappa, TSS）均显示Maxent拥有最好的预测结果和最好的运行性能。由Maxent对葫芦寡鬃实蝇、埃塞俄比亚寡鬃实蝇和西瓜寡鬃实蝇的预测结果显示, 这3种实蝇在中美洲、南美洲、东南亚和澳大利亚沿岸的广大地区在总体上具有相似的分布区域。相对而言, 埃塞俄比亚寡鬃实蝇在全球范围具有最为广泛的分布区域, 除前述地区外, 其潜在适生区还包括地中海沿岸、沙特阿拉伯、也门、安曼和伊朗南部的大片地区, 这也意味着在3种寡鬃实蝇中, 它能忍受变化幅度最广的生态、环境条件。在中国, 云南和海南都极适宜于3种实蝇的生存, 同时广东南部及台湾的部分地区也是它们的潜在适生区。基于Maxent的预测结果显示, 相对而言, 埃塞俄比亚寡鬃实蝇在中国范围也具有最为广泛的分布区域, 除前述省份和地区外, 四川、贵州和西藏的南部部分地区以及中国南部的部分沿海地区, 也都是它的潜在适生区。综合所得出的预测结果, 3种寡鬃实蝇从境外传入广东并在此定殖的风险可能性是实际存在的。Jackknife分析显示, 温度以及与此有关的环境因子对于3种实蝇在全球和局部地区的分布模式和分布情况都有极大的影响, 并需要进一步的研究。     

Modelling the distribution of a threatened habitat: the California sage scrub

Aim Using predictive species distribution and ecological niche modelling our objectives are: (1) to identify important climatic drivers of distribution at regional scales of a locally complex and dynamic system – California sage scrub; (2) to map suitable sage scrub habitat in California; and (3) to distinguish between bioclimatic niches of floristic groups within sage scrub to assess the conservation significance of analysing such species groups. Location Coastal mediterranean‐type shrublands of southern and central California. Methods Using point localities from georeferenced herbarium records, we modelled the potential distribution and bioclimatic envelopes of 14 characteristic sage scrub species and three floristic groups (south‐coastal, coastal–interior disjunct and broadly distributed species) based upon current climate conditions. Maxent was used to map climatically suitable habitat, while principal components analysis followed by canonical discriminant analysis were used to distinguish between floristic groups and visualize species and group distributions in multivariate ecological space. Results Geographical distribution patterns of individual species were mirrored in the habitat suitability maps of floristic groups, notably the disjunct distribution of the coastal–interior species. Overlap in the distributions of floristic groups was evident in both geographical and multivariate niche space; however, discriminant analysis confirmed the separability of floristic groups based on bioclimatic variables. Higher performance of floristic group models compared with sage scrub as a whole suggests that groups have differing climate requirements for habitat suitability at regional scales and that breaking sage scrub into floristic groups improves the discrimination between climatically suitable and unsuitable habitat. Main conclusions The finding that presence‐only data and climatic variables can produce useful information on habitat suitability of California sage scrub species and floristic groups at a regional scale has important implications for ongoing efforts of habitat restoration for sage scrub. In addition, modelling at a group level provides important information about the differences in climatic niches within California sage scrub. Finally, the high performance of our floristic group models highlights the potential a community‐level modelling approach holds for investigating plant distribution patterns.     

Unveiling the Conservation Biogeography of a Data-Deficient Endangered Bird Species under Climate Change

It remains a challenge to identify the geographical patterns and underlying environmental associations of species with unique ecological niches and distinct behaviors. This in turn hinders our understanding of the ecology as well as effective conservation management of threatened species. The white-eared night heron (Gorsachius magnificus) is a non-migratory nocturnal bird species that has a patchy distribution in the mountainous forests of East Asia. It is currently categorized as “Endangered” on the IUCN Red List, primarily due to its restricted range and fragmented habitat. To improve our knowledge of the biogeography and conservation of this species, we modeled the geographical pattern of its suitable habitat and evaluated the potential impacts of climate change using ecological niche modeling with a maximum entropy approach implemented in Maxent. Our results indicated that the amount of suitable habitat in all of East Asia was about 130 000 km², which can be spatially subdivided into several mountain ranges in southern and southwestern China and northern Vietnam. The extent of suitable habitat range may shrink by more than 35% under a predicted changing climate when assuming the most pessimistic condition of dispersal, while some more suitable habitat would be available if the heron could disperse unrestrainedly. The significant future changes in habitat suitability suggested for Gorsachius magnificus urge caution in any downgrading of Red List status that may be considered. Our results also discern potentially suitable areas for future survey efforts on new populations. Overall, this study demonstrates that ecological niche modeling offers an important tool for evaluating the habitat suitability and potential impacts of climate change on an enigmatic and endangered species based on limited presence data.     

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.     

Shifts in potential geographical distribution of Pterocarya stenoptera under climate change scenarios in China

Climate change poses a serious threat to biodiversity. Predicting the effects of climate change on the distribution of a species' habitat can help humans address the potential threats which may change the scope and distribution of species. Pterocarya stenoptera is a common fast‐growing tree species often used in the ecological restoration of riverbanks and alpine forests in central and eastern China. Until now, the characteristics of the distribution of this species' habitat are poorly known as are the environmental factors that influence its preferred habitat. In the present study, the Maximum Entropy Modeling (Maxent) algorithm and the Genetic Algorithm for Ruleset Production (GARP) were used to establish the models for the potential distribution of this species by selecting 236 sites with known occurrences and 14 environmental variables. The results indicate that both models have good predictive power. Minimum temperature of coldest month (Bio6), mean temperature of warmest quarter (Bio10), annual precipitation (Bio12), and precipitation of driest month (Bio14) were important environmental variables influencing the prediction of the Maxent model. According to the models, the temperate and subtropical regions of eastern China had high environmental suitability for this species, where the species had been recorded. Under each climate change scenario, climatic suitability of the existing range of this species increased, and its climatic niche expanded geographically to the north and higher elevation. GARP predicted a more conservative expansion. The projected spatial and temporal patterns of P. stenoptera can provide reference for the development of forest management and protection strategies.