Maxent模型复杂度对物种潜在分布区预测的影响

生态位模型在入侵生物学和保护生物学中具有广泛的应用, 其中Maxent模型最为流行, 被越来越多地应用在预测物种的现实分布和潜在分布的研究中。在Maxent模型中, 多数研究者采用默认参数来构建模型, 这些默认参数源自早期对266个物种的测试, 以预测物种的现实分布为目的。近期研究发现, Maxent模型采用复杂机械学习算法, 对采样偏差敏感, 易产生过度拟合, 模型转移能力仅在低阈值情况下较好。基于默认参数的Maxent模型不仅预测结果不可靠, 而且有时很难解释。在本研究中, 作者以入侵害虫茶翅蝽(Halyomorpha halys)为例, 采用经典模型构建方案(即构建本土模型然后将其转移至入侵地来评估), 利用ENMeval数据包来调整本土Maxent模型调控倍频和特征组合参数, 分析各种参数条件下模型的复杂度, 然后选取最低复杂度的模型参数(即为最优模型), 综合比较默认参数和调整参数后Maxent模型的响应曲线和预测结果, 探讨Maxent模型复杂度对预测结果的影响及Maxent模型构建时所需注意事项, 以期对物种潜在分布进行合理的预测, 促进Maxent模型在我国的合理运用和发展。作者认为, 环境变量的选择至关重要, 需要综合分析其对所模拟物种分布的限制作用和环境变量之间的空间相关性。构建Maxent模型前需对物种分布采样偏差及模型的构建区域进行合理地判断, 模型构建时需要比较不同参数下模型的预测结果和响应曲线, 选取复杂度较低的模型参数来最终建模。在茶翅蝽的分析中, Maxent模型的默认参数和最优模型参数不同, 与Maxent模型默认参数相比, 采用调整参数后所构建的模型预测效果较好, 响应曲线较为平滑, 模型转移能力较高, 能够较为合理反映物种对环境因子的响应和准确地模拟该物种的潜在分布。     

Testing the ability of species distribution models to infer variable importance

Models of species’ distributions and niches are frequently used to infer the importance of range- and niche-defining variables. However, the degree to which these models can reliably identify important variables and quantify their influence remains unknown. Here we use a series of simulations to explore how well models can 1) discriminate between variables with different influence and 2) calibrate the magnitude of influence relative to an ‘omniscient’ model. To quantify variable importance, we trained generalized additive models (GAMs), Maxent and boosted regression trees (BRTs) on simulated data and tested their sensitivity to permutations in each predictor. Importance was inferred by calculating the correlation between permuted and unpermuted predictions, and by comparing predictive accuracy of permuted and unpermuted predictions using AUC and the continuous Boyce index. In scenarios with one influential and one uninfluential variable, models failed to discriminate reliably between variables when training occurrences were < 8–64, prevalence was > 0.5, spatial extent was small, environmental data had coarse resolution and spatial autocorrelation was low, or when pairwise correlation between environmental variables was |r| > 0.7. When two variables influenced the distribution equally, importance was underestimated when species had narrow or intermediate niche breadth. Interactions between variables in how they shaped the niche did not affect inferences about their importance. When variables acted unequally, the effect of the stronger variable was overestimated. GAMs and Maxent discriminated between variables more reliably than BRTs, but no algorithm was consistently well-calibrated vis-à-vis the omniscient model. Algorithm-specific measures of importance like Maxent's change-in-gain metric were less robust than the permutation test. Overall, high predictive accuracy did not connote robust inferential capacity. As a result, requirements for reliably measuring variable importance are likely more stringent than for creating models with high predictive accuracy.     

提高生态位模型转移能力来模拟入侵物种 的潜在分布

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

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.     

Tracing the future of epidemics: Coincident niche distribution of host animals and disease incidence revealed climate-correlated risk shifts of main zoonotic diseases in China

Climate has critical roles in the origin, pathogenesis and transmission of infectious zoonotic diseases. However, large-scale epidemiologic trend and specific response pattern of zoonotic diseases under future climate scenarios are poorly understood. Here, we projected the distribution shifts of transmission risks of main zoonotic diseases under climate change in China. First, we shaped the global habitat distribution of main host animals for three representative zoonotic diseases (2, 6, and 12 hosts for dengue, hemorrhagic fever, and plague, respectively) with 253,049 occurrence records using maximum entropy (Maxent) modeling. Meanwhile, we predicted the risk distribution of the above three diseases with 197,098 disease incidence records from 2004 to 2017 in China using an integrated Maxent modeling approach. The comparative analysis showed that there exist highly coincident niche distributions between habitat distribution of hosts and risk distribution of diseases, indicating that the integrated Maxent modeling is accurate and effective for predicting the potential risk of zoonotic diseases. On this basis, we further projected the current and future transmission risks of 11 main zoonotic diseases under four representative concentration pathways (RCPs) (RCP2.6, RCP4.5, RCP6.0, and RCP8.5) in 2050 and 2070 in China using the above integrated Maxent modeling with 1,001,416 disease incidence records. We found that Central China, Southeast China, and South China are concentrated regions with high transmission risks for main zoonotic diseases. More specifically, zoonotic diseases had diverse shift patterns of transmission risks including increase, decrease, and unstable. Further correlation analysis indicated that these patterns of shifts were highly correlated with global warming and precipitation increase. Our results revealed how specific zoonotic diseases respond in a changing climate, thereby calling for effective administration and prevention strategies. Furthermore, these results will shed light on guiding future epidemiologic prediction of emerging infectious diseases under global climate change.     

MaxEnt模型参数设置对其所模拟物种地理分布和生态位的影响——以茶翅蝽为例

【目的】生态位模型被广泛应用于入侵生物学和保护生物学研究,现有建模工具中,MaxEnt是最流行和运用最广泛的生态位模型。然而最近研究表明,基于MaxEnt模型的默认参数构建模型时,模型倾向于过度拟合,并非一定为最佳模型,尤其是在处理一些分布点较少的物种。【方法】以茶翅蝽为例,通过设置不同的特征参数、调控倍频以及背景拟不存在点数分别构建茶翅蝽的本土模型,然后将其转入入侵地来验证和比较模型,通过检测模型预测的物种对环境因子的响应曲线、潜在分布在生态空间中的生态位映射以及潜在分布的空间差异性,探讨3种参数设置对MaxEnt模型模拟物种分布和生态位的影响。【结果】在茶翅蝽的案例分析中,特征参数的设置对MaxEnt模型所模拟的潜在分布和生态位的影响最大,调控倍频的影响次之,背景拟不存在点数的影响最小。与其他特征相比,基于特征H和T的模型其响应曲线较为曲折;随着调控倍频的增加,响应曲线变得圆滑。【结论】在构建MaxEnt模型时,需要从生态空间中考虑物种的生态需求,分析模型参数对预测物种分布和生态位可能造成的影响。     

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.     

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

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

Ecological Niche 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.     

Climatic niche divergence and habitat suitability of eight alien invasive weeds in China under climate change

Testing climatic niche divergence and modeling habitat suitability under conditions of climate change are important for developing strategies to limit the introduction and expansion of alien invasive weeds (AIWs) and providing important ecological and evolutionary insights. We assessed climatic niches in both native and invasive ranges as well as habitat suitability under climate change for eight representative Chinese AIWs from the American continent. We used climatic variables associated with occurrence records and developed ecological niche models with Maxent. Interestingly, the climatic niches of all eight AIWs diverged significantly between the native and invasive ranges (the American continent and China). Furthermore, the AIWs showed larger climatic niche breadths in the invasive ranges than in the native ranges. Our results suggest that climatic niche shifts between native and invasive ranges occurred. Thus, the occurrence records of both native and invasive regions must be considered when modeling and predicting the spatial distributions of AIWs under current and future climate scenarios. Owing to high habitat suitability, AIWs were more likely to expand into regions of low latitude, and future climate change was predicted to result in a shift in the AIWs in Qinghai and Tibet (regions of higher altitude) as well as Heilongjiang, Jilin, Liaoning, Inner Mongolia, and Gansu (regions of higher latitude). Our results suggest that we need measures to prevent and control AIW expansion at the country‐wide level.     

Wrong,but useful: regional species distribution models may not be improved by range‐wide data under biased sampling

Species distribution modeling (SDM) is an essential method in ecology and conservation. SDMs are often calibrated within one country's borders, typically along a limited environmental gradient with biased and incomplete data, making the quality of these models questionable. In this study, we evaluated how adequate are national presence‐only data for calibrating regional SDMs. We trained SDMs for Egyptian bat species at two different scales: only within Egypt and at a species‐specific global extent. We used two modeling algorithms: Maxent and elastic net, both under the point‐process modeling framework. For each modeling algorithm, we measured the congruence of the predictions of global and regional models for Egypt, assuming that the lower the congruence, the lower the appropriateness of the Egyptian dataset to describe the species' niche. We inspected the effect of incorporating predictions from global models as additional predictor (“prior”) to regional models, and quantified the improvement in terms of AUC and the congruence between regional models run with and without priors. Moreover, we analyzed predictive performance improvements after correction for sampling bias at both scales. On average, predictions from global and regional models in Egypt only weakly concur. Collectively, the use of priors did not lead to much improvement: similar AUC and high congruence between regional models calibrated with and without priors. Correction for sampling bias led to higher model performance, whatever prior used, making the use of priors less pronounced. Under biased and incomplete sampling, the use of global bats data did not improve regional model performance. Without enough bias‐free regional data, we cannot objectively identify the actual improvement of regional models after incorporating information from the global niche. However, we still believe in great potential for global model predictions to guide future surveys and improve regional sampling in data‐poor regions.     

Using maximum entropy to predict the potential distribution of an invasive freshwater snail

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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。     

Ecological niche modeling of the invasive potential of Nile tilapia Oreochromis niloticus in African river systems: concerns and implications for the conservation of indigenous congenerics

This study applied ecological niche models to determine the potential invasive range of Nile tilapia, Oreochromis niloticus, with a particular focus on river systems in southern Africa where it is now established and spreading. Computational tools such as niche models are useful in predicting the potential range of invasive species, but there are limitations to their application. In particular, models trained on native records may fail to predict the full extent of an invasion. This failure is often attributed to changes in either the niche of the invading species or the variables used to develop the models. In this study, we therefore evaluated the differences in the predictive power of models trained with different environmental variables, the effect of species range (native vs. introduced) on model performance and assessed whether or not there is evidence suggestive of a niche shift in Nile tilapia following its introduction. Niche models were constructed using Maxent and the degree of niche similarity was assessed using Schoener`s index. Null models were used to test for significance. Model performance and niche conservatism varied significantly with variable selection and species range. This indicates that the environmental conditions available to Nile tilapia in its native and introduced ranges are not congruent. Nile tilapia exhibited broad invasive potential over most of southern Africa that overlaps the natural range of endemic congenerics. Of particular concern are areas which are free of exotic species but are now vulnerable due to the promotion of fish introductions mainly for aquaculture and sport fishing.     

On population abundance and niche structure

Recent published evidence indicates a negative correlation between density of populations and the distance of their environments to a suitably defined ‘niche centroid’. This empirical observation lacks theoretical grounds. We provide a theoretical underpinning for the empirical relationship between population density and position in niche space, and use this framework to understand the circumstances under which the relationship will fail. We propose a metapopulation model for the area of distribution, as a system of ordinary differential equations coupled with a dispersal kernel. We present an analytical approximation to the solution of the system as well as R code to solve the full model numerically. We use this tool to analyze various scenarios and assumptions. General and realistic demographic assumptions imply a good correlation between position in niche space and population abundance. Factors that modify this correlation are: transitory states, a heterogeneous spatial structure of suitability, and Allee effects. We also explain why the raw output of the niche modeling algorithm MaxEnt is not a good predictor of environmental suitability. Our results elucidate the empirical results for spatial patterns of population size in niche terms, and provide a theoretical basis for a structured theory of the niche.     

Occurrence of an invasive coral in the southwest Atlantic and comparison with a congener suggest potential niche expansion

Tubastraea tagusensis, a coral native to the Galapagos Archipelago, has successfully established and invaded the Brazilian coast where it modifies native tropical rocky shore and coral reef communities. In order to understand the processes underlying the establishment of T. tagusensis, we tested whether Maxent, a tool for species distribution modeling, based on the native range of T. tagusensis correctly forecasted the invasion range of this species in Brazil. The Maxent algorithm was unable to predict the Brazilian coast as a suitable environment for the establishment of T. tagusensis. A comparison between these models and a principal component analysis (PCA) allowed us to examine the environmental dissimilarity between the two occupied regions (native and invaded) and to assess the species' occupied niche breadth. According to the PCA results, lower levels of chlorophyll‐a and nitrate on the Atlantic coast segregate the Brazilian and Galapagos environments, implying that T. tagusensis may have expanded its realized niche during the invasion process. We tested the possible realized niche expansion in T. tagusensis by assuming that Tubastraea spp. have similar fundamental niches, which was supported by exploring the environmental space of T. coccinea, a tropical‐cosmopolitan congener of T. tagusensis. We believe that the usage of Maxent should be treated with caution, especially when applied to biological invasion (or climate change) scenarios where the target species has a highly localized native (original) distribution, which may represent only a small portion of its fundamental niche, and therefore a violation of a SDM assumption.     

Measuring ecological niche overlap from occurrence and spatial environmental data

Aim Concerns over how global change will influence species distributions, in conjunction with increased emphasis on understanding niche dynamics in evolutionary and community contexts, highlight the growing need for robust methods to quantify niche differences between or within taxa. We propose a statistical framework to describe and compare environmental niches from occurrence and spatial environmental data. Location Europe, North America and South America. Methods The framework applies kernel smoothers to densities of species occurrence in gridded environmental space to calculate metrics of niche overlap and test hypotheses regarding niche conservatism. We use this framework and simulated species with pre‐defined distributions and amounts of niche overlap to evaluate several ordination and species distribution modelling techniques for quantifying niche overlap. We illustrate the approach with data on two well‐studied invasive species. Results We show that niche overlap can be accurately detected with the framework when variables driving the distributions are known. The method is robust to known and previously undocumented biases related to the dependence of species occurrences on the frequency of environmental conditions that occur across geographical space. The use of a kernel smoother makes the process of moving from geographical space to multivariate environmental space independent of both sampling effort and arbitrary choice of resolution in environmental space. However, the use of ordination and species distribution model techniques for selecting, combining and weighting variables on which niche overlap is calculated provide contrasting results. Main conclusions The framework meets the increasing need for robust methods to quantify niche differences. It is appropriate for studying niche differences between species, subspecies or intra‐specific lineages that differ in their geographical distributions. Alternatively, it can be used to measure the degree to which the environmental niche of a species or intra‐specific lineage has changed over time.