A Mechanistic Niche Model for Measuring Species' Distributional Responses to Seasonal Temperature Gradients

Niche theory is central to understanding how species respond geographically to climate change. It defines a species'' realized niche in a biological community, its fundamental niche as determined by physiology, and its potential niche—the fundamental niche in a given environment or geographic space. However, most predictions of the effects of climate change on species'' distributions are limited to correlative models of the realized niche, which assume that species are in distributional equilibrium with respect to the variables or gradients included in the model. Here, I present a mechanistic niche model that measures species'' responses to major seasonal temperature gradients that interact with the physiology of the organism. I then use lethal physiological temperatures to parameterize the model for bird species in North and South America and show that most focal bird species are not in direct physiological equilibrium with the gradients. Results also show that most focal bird species possess broad thermal tolerances encompassing novel climates that could become available with climate change. I conclude with discussion of how mechanistic niche models may be used to (i) gain insights into the processes that cause species to respond to climate change and (ii) build more accurate correlative distribution models in birds and other species.     

Vanishing islands in the sky? A comparison of correlation- and mechanism-based forecasts of range dynamics for montane salamanders under climate change

Forecasting the effects of climate change on species and populations is a fundamental goal of conservation biology, especially for montane endemics which seemingly are under the greatest threat of extinction given their association with cool, high elevation habitats. Species distribution models (also known as niche models) predict where on the landscape there is suitable habitat for a species of interest. Correlative niche modeling, the most commonly employed approach to predict species' distributions, relies on correlations between species' localities and current environmental data. This type of model could spuriously forecast less future suitable habitat because species' current distributions may not adequately represent their thermal tolerance, and future climate conditions may not be analogous to current conditions. We compared the predicted distributions for three montane species of Plethodon salamanders in the southern Appalachian Mountains of North America using a correlative modeling approach and a mechanistic model. The mechanistic model incorporates species-specific physiology, morphology and behavior to predict an annual energy budget on the landscape. Both modeling approaches performed well at predicting the species' current distributions and predicted that all species could persist in habitats at higher elevation through 2085. The mechanistic model predicted more future suitable habitat than the correlative model. We attribute these differences to the mechanistic approach being able to model shifts in key range-limiting biological processes (changes in surface activity time and energy costs) that the correlative approach cannot. Choice of global circulation model (GCM) contributed significantly to distribution predictions, with a tenfold difference in future suitability based on GCM, indicating that GCM variability should be either directly included in models of species distributions or, indirectly, through the use of multi-model ensemble averages. Our results indicate that correlative models are over-predicting habitat loss for montane species, suggesting a critical need to incorporate mechanisms into forecasts of species' range dynamics.     

The range implications of lizard traits in changing environments

Aim Most predictions of species ranges are based on correlating current species localities to environmental conditions. These correlative models do not explicitly include a species' biology. In contrast, some mechanistic models link traits to energetics and population dynamics to predict species distributions. These models enable one to ask whether considering a species' biology is important for predicting its range. I implement mechanistic models to investigate how a species' morphology, physiology and life history influence its range. Location North America. Methods I compare the mechanistic model predictions with those of correlative models for eight species of North American lizards in both current environments and following a uniform 3 °C temperature warming. I then examine the implications of superimposing habitat and elevation requirements on constraints associated with environmental tolerances. Results In the mechanistic model, species with a narrower thermal range for activity are both predicted and observed to have more restricted distributions. Incorporating constraints on habitat and elevation further restricts species distributions beyond areas that are thermally suitable. While correlative models generally outperform mechanistic models at predicting current distributions, the performance of mechanistic models improves when incorporating additional factors. In response to a 3 °C temperature warming, the northward range shifts predicted by the mechanistic model vary between species according to trait differences and are of a greater extent than those predicted by correlative models. Main conclusions These findings highlight the importance of species traits for understanding the dynamics of species ranges in changing environments. The analysis demonstrates that mechanistic models may provide an important complement to correlative models for predicting range dynamics, which may underpredict climate‐induced range shifts.     

Truncation of thermal tolerance niches among Australian plants

Aim

Despite recognition that realized distributions inherently underestimate species' physiological tolerances, we are yet to identify the extent of these differences within diverse taxonomic groups. The degree to which species could tolerate environmental conditions outside their observed distributions may have a significant impact on the perceived extinction risk in ecological models. More information on this potential error is required to improve our confidence in management strategies.

Location

Australia.

Time Period

1983–2012.

Major Taxa Studied

Plants.

Methods

To quantify the scale and spatial patterns of this disparity, we estimated the existing tolerance to thermal extremes of 7,124 Australian plants, more than one‐third of the native continental flora, using data from cultivated records at 128 botanical gardens and nurseries. Hierarchical Bayesian beta regression was used to assess whether factors such as realized niches, traits or phylogeny could predict the incidence or magnitude of niche truncation (underestimation of thermal tolerances), while controlling for sources of collection bias.

Results

Approximately half of the cultivated species analysed could tolerate temperature extremes beyond those experienced in their native range. Niche truncation was predictable from the breadth and extremes of their realized niches and by traits such as plant growth form. Phylogenetic relationships with niche truncation were weak and appeared more suited to predicting thermal tolerances directly.

Main conclusions

This study highlights a widespread disparity between realized and potential thermal limits that may have significant implications for species' capacity to persist in situ with a changing climate. Identifying whether thermal niche truncation is the result of biotic interactions, dispersal constraints or other environmental factors could provide significant insight into community assembly at macroecological scales. Estimating niche truncation may help to explain why certain ecological communities are more resilient to change and may potentially improve the reliability of model projections under climate change.     

Commentary on Ditch,Stitch and Pitch: the niche is here to stay

A recent set of discussion papers in the Journal of Biogeography by McInerny and Etienne (henceforth M&E) questions the value of niche concepts in relation to a diverse group of practices collectively labelled species distribution modelling (SDM), and specifically the usefulness of the idea of a fundamental niche. In this Correspondence, I argue that certain types of SDM may indeed dispense with niche concepts, but that such is not the case for an important class of SDM‐based activities, including transferring predictions in space and time. Using a single term (SDM) to denote diverse objectives and practices does not help to clarify issues; I discuss this point. I also review several criticisms raised by M&E about the use of the concept of fundamental niche in the context of modelling species' distributions and their environments.     

How Can Model Comparison Help Improving Species Distribution Models?

Today, more than ever, robust projections of potential species range shifts are needed to anticipate and mitigate the impacts of climate change on biodiversity and ecosystem services. Such projections are so far provided almost exclusively by correlative species distribution models (correlative SDMs). However, concerns regarding the reliability of their predictive power are growing and several authors call for the development of process-based SDMs. Still, each of these methods presents strengths and weakness which have to be estimated if they are to be reliably used by decision makers. In this study we compare projections of three different SDMs (STASH, LPJ and PHENOFIT) that lie in the continuum between correlative models and process-based models for the current distribution of three major European tree species, Fagus sylvatica L., Quercus robur L. and Pinus sylvestris L. We compare the consistency of the model simulations using an innovative comparison map profile method, integrating local and multi-scale comparisons. The three models simulate relatively accurately the current distribution of the three species. The process-based model performs almost as well as the correlative model, although parameters of the former are not fitted to the observed species distributions. According to our simulations, species range limits are triggered, at the European scale, by establishment and survival through processes primarily related to phenology and resistance to abiotic stress rather than to growth efficiency. The accuracy of projections of the hybrid and process-based model could however be improved by integrating a more realistic representation of the species resistance to water stress for instance, advocating for pursuing efforts to understand and formulate explicitly the impact of climatic conditions and variations on these processes.     

Forecasting Distributional Responses of Limber Pine to Climate Change at Management-Relevant Scales in Rocky Mountain National Park

Resource managers at parks and other protected areas are increasingly expected to factor climate change explicitly into their decision making frameworks. However, most protected areas are small relative to the geographic ranges of species being managed, so forecasts need to consider local adaptation and community dynamics that are correlated with climate and affect distributions inside protected area boundaries. Additionally, niche theory suggests that species'' physiological capacities to respond to climate change may be underestimated when forecasts fail to consider the full breadth of climates occupied by the species rangewide. Here, using correlative species distribution models that contrast estimates of climatic sensitivity inferred from the two spatial extents, we quantify the response of limber pine (Pinus flexilis) to climate change in Rocky Mountain National Park (Colorado, USA). Models are trained locally within the park where limber pine is the community dominant tree species, a distinct structural-compositional vegetation class of interest to managers, and also rangewide, as suggested by niche theory. Model forecasts through 2100 under two representative concentration pathways (RCP 4.5 and 8.5 W/m²) show that the distribution of limber pine in the park is expected to move upslope in elevation, but changes in total and core patch area remain highly uncertain. Most of this uncertainty is biological, as magnitudes of projected change are considerably more variable between the two spatial extents used in model training than they are between RCPs, and novel future climates only affect local model predictions associated with RCP 8.5 after 2091. Combined, these results illustrate the importance of accounting for unknowns in species'' climatic sensitivities when forecasting distributional scenarios that are used to inform management decisions. We discuss how our results for limber pine may be interpreted in the context of climate change vulnerability and used to help guide adaptive management.     

Does probability of occurrence relate to population dynamics?

Hutchinson defined species' realized niche as the set of environmental conditions in which populations can persist in the presence of competitors. In terms of demography, the realized niche corresponds to the environments where the intrinsic growth rate (r) of populations is positive. Observed species occurrences should reflect the realized niche when additional processes like dispersal and local extinction lags do not have overwhelming effects. Despite the foundational nature of these ideas, quantitative assessments of the relationship between range‐wide demographic performance and occurrence probability have not been made. This assessment is needed both to improve our conceptual understanding of species' niches and ranges and to develop reliable mechanistic models of species geographic distributions that incorporate demography and species interactions. The objective of this study is to analyse how demographic parameters (intrinsic growth rate r and carrying capacity K ) and population density (N ) relate to occurrence probability (P_occ ). We hypothesized that these relationships vary with species' competitive ability. Demographic parameters, density, and occurrence probability were estimated for 108 tree species from four temperate forest inventory surveys (Québec, western USA, France and Switzerland). We used published information of shade tolerance as indicators of light competition strategy, assuming that high tolerance denotes high competitive capacity in stable forest environments. Interestingly, relationships between demographic parameters and occurrence probability did not vary substantially across degrees of shade tolerance and regions. Although they were influenced by the uncertainty in the estimation of the demographic parameters, we found that r was generally negatively correlated with P_occ, while N, and for most regions K, was generally positively correlated with P_occ. Thus, in temperate forest trees the regions of highest occurrence probability are those with high densities but slow intrinsic population growth rates. The uncertain relationships between demography and occurrence probability suggests caution when linking species distribution and demographic models.     

Integrating multiple lines of evidence into historical biogeography hypothesis testing: a Bison bison case study

One of the grand goals of historical biogeography is to understand how and why species'' population sizes and distributions change over time. Multiple types of data drawn from disparate fields, combined into a single modelling framework, are necessary to document changes in a species''s demography and distribution, and to determine the drivers responsible for change. Yet truly integrated approaches are challenging and rarely performed. Here, we discuss a modelling framework that integrates spatio-temporal fossil data, ancient DNA, palaeoclimatological reconstructions, bioclimatic envelope modelling and coalescence models in order to statistically test alternative hypotheses of demographic and potential distributional changes for the iconic American bison (Bison bison). Using different assumptions about the evolution of the bioclimatic niche, we generate hypothetical distributional and demographic histories of the species. We then test these demographic models by comparing the genetic signature predicted by serial coalescence against sequence data derived from subfossils and modern populations. Our results supported demographic models that include both climate and human-associated drivers of population declines. This synthetic approach, integrating palaeoclimatology, bioclimatic envelopes, serial coalescence, spatio-temporal fossil data and heterochronous DNA sequences, improves understanding of species'' historical biogeography by allowing consideration of both abiotic and biotic interactions at the population level.     

Combining physiological threshold knowledge to species distribution models is key to improving forecasts of the future niche for macroalgae

Species distribution models (SDM) are a useful tool for predicting species range shifts in response to global warming. However, they do not explore the mechanisms underlying biological processes, making it difficult to predict shifts outside the environmental gradient where the model was trained. In this study, we combine correlative SDMs and knowledge on physiological limits to provide more robust predictions. The thermal thresholds obtained in growth and survival experiments were used as proxies of the fundamental niches of two foundational marine macrophytes. The geographic projections of these species’ distributions obtained using these thresholds and existing SDMs were similar in areas where the species are either absent‐rare or frequent and where their potential and realized niches match, reaching consensus predictions. The cold‐temperate foundational seaweed Himanthalia elongata was predicted to become extinct at its southern limit in northern Spain in response to global warming, whereas the occupancy of southern‐lusitanic Bifurcaria bifurcata was expected to increase. Combined approaches such as this one may also highlight geographic areas where models disagree potentially due to biotic factors. Physiological thresholds alone tended to over‐predict species prevalence, as they cannot identify absences in climatic conditions within the species’ range of physiological tolerance or at the optima. Although SDMs tended to have higher sensitivity than threshold models, they may include regressions that do not reflect causal mechanisms, constraining their predictive power. We present a simple example of how combining correlative and mechanistic knowledge provides a rapid way to gain insight into a species’ niche resulting in consistent predictions and highlighting potential sources of uncertainty in forecasted responses to climate change.     

Unpacking the mechanisms captured by a correlative species distribution model to improve predictions of climate refugia

Climate refugia are regions that animals can retreat to, persist in and potentially then expand from under changing environmental conditions. Most forecasts of climate change refugia for species are based on correlative species distribution models (SDMs) using long‐term climate averages, projected to future climate scenarios. Limitations of such methods include the need to extrapolate into novel environments and uncertainty regarding the extent to which proximate variables included in the model capture processes driving distribution limits (and thus can be assumed to provide reliable predictions under new conditions). These limitations are well documented; however, their impact on the quality of climate refugia predictions is difficult to quantify. Here, we develop a detailed bioenergetics model for the koala. It indicates that range limits are driven by heat‐induced water stress, with the timing of rainfall and heat waves limiting the koala in the warmer parts of its range. We compare refugia predictions from the bioenergetics model with predictions from a suite of competing correlative SDMs under a range of future climate scenarios. SDMs were fitted using combinations of long‐term climate and weather extremes variables, to test how well each set of predictions captures the knowledge embedded in the bioenergetics model. Correlative models produced broadly similar predictions to the bioenergetics model across much of the species' current range – with SDMs that included weather extremes showing highest congruence. However, predictions in some regions diverged significantly when projecting to future climates due to the breakdown in correlation between climate variables. We provide unique insight into the mechanisms driving koala distribution and illustrate the importance of subtle relationships between the timing of weather events, particularly rain relative to hot‐spells, in driving species–climate relationships and distributions. By unpacking the mechanisms captured by correlative SDMs, we can increase our certainty in forecasts of climate change impacts on species.     

How sensitive are climatic niche inferences to distribution data sampling? A comparison of Biota of North America Program (BONAP) and Global Biodiversity Information Facility (GBIF) datasets

Climatic niche modeling is widely used in modern macroecology and evolutionary biology to model species' distributions and ecological niches. Frequently, Global Biodiversity Information Facility (GBIF) distribution data are used as raw data for such models. Unfortunately, the accuracy of resulting niche estimates is difficult to assess, and GBIF users continue to call for a better understanding of GBIF data precision and uncertainty. Our research evaluates how GBIF data perform in comparison with curated, county-level species distributions from the Biota of North America Program (BONAP; www.bonap.org) to estimate the climatic niche for Carex (Cyperaceae), one of the largest angiosperm genera in the temperate zone. In particular, we investigate the complementary strengths and weaknesses of the two datasets in the context of climatic niche estimation, namely (1) the incomplete sampling coverage of species distributions of GBIF data, and (2) elevation bias in climatic niche estimates resulting from the coarse resolution of the BONAP distribution dataset. To do so, we quantified climatic niches for 388 North American Carex species and calculated the distance of GBIF and BONAP climatic niche estimates in principal component space. We found little to no relationship between differences in climatic niche estimates and sampling coverage metrics, suggesting that sparse sampling coverage of GBIF data may have negligible average effects on mean climate estimates at the species level. However, elevation had a significant effect on differences in niche estimates, suggesting that using county-level distribution data—in our study, represented by BONAP—may introduce a bias in estimated climatic niche. To investigate if any such bias is phylogenetically structured, we examined the relationship between GBIF and BONAP climatic niche tip states using Phylogenetic Generalized Least Squares Regression (PGLS), estimating phylogenetic signal in the residuals of the regression by estimating Pagel's λ simultaneously with other regression parameters. Estimates were tightly correlated, with little to no phylogenetic signal—low λ—in the regression residuals, suggesting that any potential bias is more or less independent of phylogeny for the sedges of North America. Based on our results, we recommend a hybrid GBIF and BONAP data approach for the best understanding of species' climatic niche, relying on BONAP to fill in distributions primarily where collection records may be sparse. Our findings provide needed context and perspective on the implications of alternative distribution datasets for climatic niche estimation, especially in a macroevolutionary context.     

Phenology is a major determinant of tree species range

Global warming is expected to have a major impact on plant distributions, an issue of key importance in biological conservation. However, very few models are able to predict species distribution accurately, although we know species respond individually to climate change. Here we show, using a process-based model ( PHENOFIT ), that tree species distributions can be predicted precisely if the biological processes of survival and reproductive success only are incorporated as a function of phenology. These predictions showed great predictive power when tested against present distributions of two North American species – quaking aspen and sugar maple – indicating that on a broad scale, the fundamental niche of trees coincides with their realized niche. Phenology is shown here to be a major determinant of plant species range and should therefore be used to assess the consequences of global warming on plant distributions, and the spread of alien plant species.     

Biotic and abiotic variables show little redundancy in explaining tree species distributions

Abiotic factors such as climate and soil determine the species fundamental niche, which is further constrained by biotic interactions such as interspecific competition. To parameterize this realized niche, species distribution models (SDMs) most often relate species occurrence data to abiotic variables, but few SDM studies include biotic predictors to help explain species distributions. Therefore, most predictions of species distributions under future climates assume implicitly that biotic interactions remain constant or exert only minor influence on large‐scale spatial distributions, which is also largely expected for species with high competitive ability. We examined the extent to which variance explained by SDMs can be attributed to abiotic or biotic predictors and how this depends on species traits. We fit generalized linear models for 11 common tree species in Switzerland using three different sets of predictor variables: biotic, abiotic, and the combination of both sets. We used variance partitioning to estimate the proportion of the variance explained by biotic and abiotic predictors, jointly and independently. Inclusion of biotic predictors improved the SDMs substantially. The joint contribution of biotic and abiotic predictors to explained deviance was relatively small (~9%) compared to the contribution of each predictor set individually (~20% each), indicating that the additional information on the realized niche brought by adding other species as predictors was largely independent of the abiotic (topo‐climatic) predictors. The influence of biotic predictors was relatively high for species preferably growing under low disturbance and low abiotic stress, species with long seed dispersal distances, species with high shade tolerance as juveniles and adults, and species that occur frequently and are dominant across the landscape. The influence of biotic variables on SDM performance indicates that community composition and other local biotic factors or abiotic processes not included in the abiotic predictors strongly influence prediction of species distributions. Improved prediction of species' potential distributions in future climates and communities may assist strategies for sustainable forest management.     

Cetacean range and climate in the eastern North Atlantic: future predictions and implications for conservation

There is increasing evidence that the distributions of a large number of species are shifting with global climate change as they track changing surface temperatures that define their thermal niche. Modelling efforts to predict species distributions under future climates have increased with concern about the overall impact of these distribution shifts on species ecology, and especially where barriers to dispersal exist. Here we apply a bio‐climatic envelope modelling technique to investigate the impacts of climate change on the geographic range of ten cetacean species in the eastern North Atlantic and to assess how such modelling can be used to inform conservation and management. The modelling process integrates elements of a species' habitat and thermal niche, and employs “hindcasting” of historical distribution changes in order to verify the accuracy of the modelled relationship between temperature and species range. If this ability is not verified, there is a risk that inappropriate or inaccurate models will be used to make future predictions of species distributions. Of the ten species investigated, we found that while the models for nine could successfully explain current spatial distribution, only four had a good ability to predict distribution changes over time in response to changes in water temperature. Applied to future climate scenarios, the four species‐specific models with good predictive abilities indicated range expansion in one species and range contraction in three others, including the potential loss of up to 80% of suitable white‐beaked dolphin habitat. Model predictions allow identification of affected areas and the likely time‐scales over which impacts will occur. Thus, this work provides important information on both our ability to predict how individual species will respond to future climate change and the applicability of predictive distribution models as a tool to help construct viable conservation and management strategies.     

Assessing the Congruence of Thermal Niche Estimations Derived from Distribution and Physiological Data. A Test Using Diving Beetles

A basic aim of ecology is to understand the determinants of organismal distribution, the niche concept and species distribution models providing key frameworks to approach the problem. As temperature is one of the most important factors affecting species distribution, the estimation of thermal limits is crucially important for inferring range constraints. It is expectable that thermal physiology data derived from laboratory experiments and species'' occurrences may express different aspects of the species'' niche. However, there is no study systematically testing this prediction in a given taxonomic group while controlling by potential phylogenetic inertia. We estimate the thermal niches of twelve Palaearctic diving beetles species using physiological data derived from experimental analyses in order to examine the extent to which these coincided with those estimated from distribution models based on observed occurrences. We found that thermal niche estimates derived from both approaches lack general congruence, and these results were similar before and after controlling by phylogeny. The congruence between potential distributions obtained from the two different procedures was also explored, and we found again that the percentage of agreement were not very high (∼60%). We confirm that both thermal niche estimates derived from geographical and physiological data are likely to misrepresent the true range of climatic variation that these diving beetles are able to tolerate, and so these procedures could be considered as incomplete but complementary estimations of an inaccessible reality.     

The role of abiotic and biotic factors in determining coexistence of multiple pollinators in the yucca–yucca moth mutualism

The determinants of a species' geographic distribution are a combination of both abiotic and biotic factors. Environmental niche modeling of climatic factors has been instrumental in documenting the role of abiotic factors in a species' niche. Integrating this approach with data from species interactions provides a means to assess the relative roles of abiotic and biotic components. Here, we examine whether the high host specificity typically exhibited in the active pollination mutualism between yuccas and yucca moths is the result of differences in climatic niche requirements that limit yucca moth distributions or the result of competition among mutualistic moths that would co‐occur on the same yucca species. We compared the species distribution models of two Tegeticula pollinator moths that use the geographically widespread plant Yucca filamentosa. Tegeticula yuccasella occurs throughout eastern North America whereas T. cassandra is restricted to the southeastern portion of the range, primarily occurring in Florida. Species distribution models demonstrate that T. cassandra is restricted climatically to the southeastern United States and T. yuccasella is predicted to be able to live across all of eastern North America. Data on moth abundances in Florida demonstrate that both moth species are present on Y. filamentosa; however, T. cassandra is numerically dominant. Taken together, the results suggest that moth geographic distributions are heavily influenced by climate, but competition among pollinating congeners will act to restrict populations of moth species that co‐occur.     

Climate niche shift in invasive species: the case of the brown anole

Anolis sagrei, a Cuba and Bahama native lizard, is a successful invader in Florida and adjacent areas. Herein, we focus on conservatism in its climate niche axes and possible congruencies with its natural history properties. The not mutually exclusive hypotheses of the present study explaining its northern range limit are: (1) climatic conditions within species' native and invasive ranges are identical; (2) the species is pre‐adapted to novel conditions as a result of historical climate variations; and (3) only some niche axes limit the species' invasive distribution and the observed pattern is explained by an interplay between the potential niche within its native range and life‐history. Species distribution models for native and invasive distributions were built on ten bioclimatic variables. Using Schoener's niche overlap index, the degree of niche conservatism among variables was identified. Significances of hypothesis (1) were tested using null‐model approaches. Possible climatic pre‐adaptations were evaluated by comparing its actual tolerance within its invasive range with that of the Last Glacial Maximum (LGM) within its native range (hypothesis 2). Results of (1) and (2) are discussed in relation to natural history, approaching hypothesis 3. We detect varying overlaps in niche axes, indicating that natural history properties are associated with conservative niche axes. Climatic comparisons with LGM of native and current conditions of invasive range suggest that pre‐adaptations are unlikely. Possible shifts in the fundamental niche of the species may have been facilitated by enhanced genetic diversity in northern invasive populations. © 2011 The Linnean Society of London, Biological Journal of the Linnean Society, 2011, 104 , 943–954.     

Different climatic envelopes among invasive populations may lead to underestimations of current and future biological invasions

Aim We explore the impact of calibrating ecological niche models (ENMs) using (1) native range (NR) data versus (2) entire range (ER) data (native and invasive) on projections of current and future distributions of three Hieracium species. Location H. aurantiacum, H. murorum and H. pilosella are native to Europe and invasive in Australia, New Zealand and North America. Methods Differences among the native and invasive realized climatic niches of each species were quantified. Eight ENMs in BIOMOD were calibrated with (1) NR and (2) ER data. Current European, North American and Australian distributions were projected. Future Australian distributions were modelled using four climate change scenarios for 2030. Results The invasive climatic niche of H. murorum is primarily a subset of that expressed in its native range. Invasive populations of H. aurantiacum and H. pilosella occupy different climatic niches to those realized in their native ranges. Furthermore, geographically separate invasive populations of these two species have distinct climatic niches. ENMs calibrated on the realized niche of native regions projected smaller distributions than models incorporating data from species’ entire ranges, and failed to correctly predict many known invasive populations. Under future climate scenarios, projected distributions decreased by similar percentages, regardless of the data used to calibrate ENMs; however, the overall sizes of projected distributions varied substantially. Main conclusions This study provides quantitative evidence that invasive populations of Hieracium species can occur in areas with different climatic conditions than experienced in their native ranges. For these, and similar species, calibration of ENMs based on NR data only will misrepresent their potential invasive distribution. These errors will propagate when estimating climate change impacts. Thus, incorporating data from species’ entire distributions may result in a more thorough assessment of current and future ranges, and provides a closer approximation of the elusive fundamental niche.     

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

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