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.     

The population genomic basis of geographic differentiation in North American common ragweed (Ambrosia artemisiifolia L.)

Common ragweed (Ambrosia artemisiifolia L.) is an invasive, wind‐pollinated plant nearly ubiquitous in disturbed sites in its eastern North American native range and present across growing portions of Europe, Africa, Asia, and Australia. Phenotypic divergence between European and native‐range populations has been described as rapid evolution. However, a recent study demonstrated major human‐mediated shifts in ragweed genetic structure before introduction to Europe and suggested that native‐range genetic structure and local adaptation might fully explain accelerated growth and other invasive characteristics of introduced populations. Genomic differentiation that potentially influenced this structure has not yet been investigated, and it remains unclear whether substantial admixture during historical disturbance of the native range contributed to the development of invasiveness in introduced European ragweed populations. To investigate fine‐scale population genetic structure across the species' native range, we characterized diallelic SNP loci via a reduced‐representation genotyping‐by‐sequencing (GBS) approach. We corroborate phylogeographic domains previously discovered using traditional sequencing methods, while demonstrating increased power to resolve weak genetic structure in this highly admixed plant species. By identifying exome polymorphisms underlying genetic differentiation, we suggest that geographic differentiation of this important invasive species has occurred more often within pathways that regulate growth and response to defense and stress, which may be associated with survival in North America's diverse climatic regions.     

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.     

Wrong place,wrong time: climate change‐induced range shift across fragmented habitat causes maladaptation and declined population size in a modelled bird species

Many species are locally adapted to decreased habitat quality at their range margins, and therefore show genetic differences throughout their ranges. Under contemporary climate change, range shifts may affect evolutionary processes at the expanding range margin due to founder events. In addition, populations that are affected by such founder events will, in the course of time, become located in the range centre. Recent studies investigated evolutionary changes at the expanding range margin, but have not assessed eventual effects across the species' range. We explored the possible influence of range shift on the level of adaptation throughout the species' total range. For this we used a spatially explicit, individual‐based simulation model of a woodland bird, parameterized after the middle spotted woodpecker ( Dendrocopos medius) in fragmented habitat. We simulated its range under climate change, and incorporated genetic differences at a single locus that determined the individual's degree of adaptation to optimal temperature conditions. Generalist individuals had a large thermal tolerance, but relatively low overall fitness, whereas climate specialists had high fitness combined with a small thermal tolerance. In equilibrium, the populations in the range centre were comprised of the specialists, whereas the generalists dominated the margins. In contrast, under temperature increase, the generalist numbers increased at the expanding margin and eventually also occupied the centre of the shifting range, whereas the specialists were located in the retracting margins. This was caused by founder events and led to overall maladaptation of the species, which resulted in a reduced metapopulation size and thus impeded the species' persistence. We therefore found no evidence for a complementary effect of local adaptation and range shifts on species' survival. Instead, we showed that founder events can cause local maladaptation which can amplify throughout the species' range, and, as such, hamper the species' persistence under climate change.     

Mutualist‐mediated effects on species' range limits across large geographic scales

Understanding the processes determining species range limits is central to predicting species distributions under climate change. Projected future ranges are extrapolated from distribution models based on climate layers, and few models incorporate the effects of biotic interactions on species' distributions. Here, we show that a positive species interaction ameliorates abiotic stress, and has a profound effect on a species' range limits. Combining field surveys of 92 populations, 10 common garden experiments throughout the range, species distribution models and greenhouse experiments, we show that mutualistic fungal endophytes ameliorate drought stress and broaden the geographic range of their native grass host Bromus laevipes by thousands of square kilometres (~ 20% larger) into drier habitats. Range differentiation between fungal‐associated and fungal‐free grasses was comparable to species‐level range divergence of congeners, indicating large impacts on range limits. Positive biotic interactions may be underappreciated in determining species' ranges and species' responses to future climates across large geographic scales.     

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.     

Evidence for rapid evolution of phenology in an invasive grass

Evolutionary dynamics of integrative traits such as phenology are predicted to be critically important to range expansion and invasion success, yet there are few empirical examples of such phenomena. In this study, we used multiple common gardens to examine the evolutionary significance of latitudinal variation in phenology of a widespread invasive species, the Asian short‐day flowering annual grass Microstegium vimineum. In environmentally controlled growth chambers, we grew plants from seeds collected from multiple latitudes across the species' invasive range. Flowering time and biomass were both strongly correlated with the latitude of population origin such that populations collected from more northern latitudes flowered significantly earlier and at lower biomass than populations from southern locations. We suggest that this pattern may be the result of rapid adaptive evolution of phenology over a period of less than one hundred years and that such changes have likely promoted the northward range expansion of this species. We note that possible barriers to gene flow, including bottlenecks and inbreeding, have apparently not forestalled evolutionary processes for this plant. Furthermore, we hypothesize that evolution of phenology may be a widespread and potentially essential process during range expansion for many invasive plant species.     

Modelle für den Wandel der Natur

Ecological Modelling – Scenarios of future environmental changes Climate change affects ecosystems at different levels. Changes in species phenology, distribution and interactions are today well described phenomena documenting species responses to increasing temperatures. Environmental niche models (ENMs) have developed as powerful tools to address various questions in macroecology. Aiming at a species environmental niche, statistical modelling can be employed to predict a species' potential occurrence by projecting environmental information recorded at locality records over space and time. In climate change biology, ENMs are used to identify individual species' fates as range expansions or retractions as well as features that affect the structure of species assemblages and species interactions within and across different taxonomic groups. ENMs help to promote the persistence of species by identifying spatial patterns of species richness or endangerment to target conservation priorities. Moreover, they are an essential part of risk assessments to set up preventive measures against non‐native species most likely to adversely impact native ecosystems.     

Illuminating geographical patterns in species' range shifts

Species' range shifts in response to ongoing climate change have been widely documented, but although complex spatial patterns in species' responses are expected to be common, comprehensive comparisons of species' ranges over time have undergone little investigation. Here, we outline a modeling framework based on historical and current species distribution records for disentangling different drivers (i.e. climatic vs. nonclimatic) and assessing distinct facets (i.e. colonization, extirpation, persistence, and lags) of species' range shifts. We used extensive monitoring data for stream fish assemblages throughout France to assess range shifts for 32 fish species between an initial period (1980–1992) and a contemporary one (2003–2009). Our results provide strong evidence that the responses of individual species varied considerably and exhibited complex mosaics of spatial rearrangements. By dissociating range shifts in climatically suitable and unsuitable habitats, we demonstrated that patterns in climate‐driven colonization and extirpation were less marked than those attributed to nonclimatic drivers, although this situation could rapidly shift in the near future. We also found evidence that range shifts could be related to some species' traits and that the traits involved varied depending on the facet of range shift considered. The persistence of populations in climatically unsuitable areas was greater for short‐lived species, whereas the extent of the lag behind climate change was greater for long‐lived, restricted‐range, and low‐elevation species. We further demonstrated that nonclimatic extirpations were primarily related to the size of the species' range, whereas climate‐driven extirpations were better explained by thermal tolerance. Thus, the proposed framework demonstrated its potential for markedly improving our understanding of the key processes involved in range shifting and also offers a template for informing management decisions. Conservation strategies would greatly benefit from identifying both the geographical patterns and the species' traits associated with complex modifications of species' distributions in response to global changes.     

Incorporating evolutionary adaptation in species distribution modelling reduces projected vulnerability to climate change

Based on the sensitivity of species to ongoing climate change, and numerous challenges they face tracking suitable conditions, there is growing interest in species' capacity to adapt to climatic stress. Here, we develop and apply a new generic modelling approach (AdaptR) that incorporates adaptive capacity through physiological limits, phenotypic plasticity, evolutionary adaptation and dispersal into a species distribution modelling framework. Using AdaptR to predict change in the distribution of 17 species of Australian fruit flies (Drosophilidae), we show that accounting for adaptive capacity reduces projected range losses by up to 33% by 2105. We identify where local adaptation is likely to occur and apply sensitivity analyses to identify the critical factors of interest when parameters are uncertain. Our study suggests some species could be less vulnerable than previously thought, and indicates that spatiotemporal adaptive models could help improve management interventions that support increased species' resilience to climate change.     

Projecting marine species range shifts from only temperature can mask climate vulnerability

Climate change is causing range shifts in many marine species, with implications for biodiversity and fisheries. Previous research has mainly focused on how species' ranges will respond to changing ocean temperatures, without accounting for other environmental covariates that could affect future distribution patterns. Here, we integrate habitat suitability modeling approaches, a high‐resolution global climate model projection, and detailed fishery‐independent and ‐dependent faunal datasets from one of the most extensively monitored marine ecosystems—the U.S. Northeast Shelf. We project the responses of 125 species in this region to climate‐driven changes in multiple oceanographic factors (e.g., ocean temperature, salinity, sea surface height) and seabed characteristics (i.e., rugosity and depth). Comparing model outputs based on ocean temperature and seabed characteristics to those that also incorporated salinity and sea surface height (proxies for primary productivity and ocean circulation features), we explored how an emphasis on ocean temperature in projecting species' range shifts can impact assessments of species' climate vulnerability. We found that multifactor habitat suitability models performed better in explaining and predicting species historical distribution patterns than temperature‐based models. We also found that multifactor models provided more concerning assessments of species' future distribution patterns than temperature‐based models, projecting that species' ranges will largely shift northward and become more contracted and fragmented over time. Our results suggest that using ocean temperature as a primary determinant of range shifts can significantly alter projections, masking species' climate vulnerability, and potentially forestalling proactive management.     

Mechanistic forecasts of species responses to climate change: The promise of biophysical ecology

A core challenge in global change biology is to predict how species will respond to future environmental change and to manage these responses. To make such predictions and management actions robust to novel futures, we need to accurately characterize how organisms experience their environments and the biological mechanisms by which they respond. All organisms are thermodynamically connected to their environments through the exchange of heat and water at fine spatial and temporal scales and this exchange can be captured with biophysical models. Although mechanistic models based on biophysical ecology have a long history of development and application, their use in global change biology remains limited despite their enormous promise and increasingly accessible software. We contend that greater understanding and training in the theory and methods of biophysical ecology is vital to expand their application. Our review shows how biophysical models can be implemented to understand and predict climate change impacts on species' behavior, phenology, survival, distribution, and abundance. It also illustrates the types of outputs that can be generated, and the data inputs required for different implementations. Examples range from simple calculations of body temperature at a particular site and time, to more complex analyses of species' distribution limits based on projected energy and water balances, accounting for behavior and phenology. We outline challenges that currently limit the widespread application of biophysical models relating to data availability, training, and the lack of common software ecosystems. We also discuss progress and future developments that could allow these models to be applied to many species across large spatial extents and timeframes. Finally, we highlight how biophysical models are uniquely suited to solve global change biology problems that involve predicting and interpreting responses to environmental variability and extremes, multiple or shifting constraints, and novel abiotic or biotic environments.     

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.     

On using integral projection models to generate demographically driven predictions of species' distributions: development and validation using sparse data

Knowledge of species' geographic distributions is critical for understanding and forecasting population dynamics, responses to environmental change, biodiversity patterns, and conservation planning. While many suggestive correlative occurrence models have been used to these ends, progress lies in understanding the underlying population biology that generates patterns of range dynamics. Here, we show how to use a limited quantity of demographic data to produce demographic distribution models (DDMs) using integral projection models for size‐structured populations. By modeling survival, growth, and fecundity using regression, integral projection models can interpolate across missing size data and environmental conditions to compensate for limited data. To accommodate the uncertainty associated with limited data and model assumptions, we use Bayesian models to propagate uncertainty through all stages of model development to predictions. DDMs have a number of strengths: 1) DDMs allow a mechanistic understanding of spatial occurrence patterns; 2) DDMs can predict spatial and temporal variation in local population dynamics; 3) DDMs can facilitate extrapolation under altered environmental conditions because one can evaluate the consequences for individual vital rates. To illustrate these features, we construct DDMs for an overstory perennial shrub in the Proteaceae family in the Cape Floristic Region of South Africa. We find that the species' population growth rate is limited most strongly by adult survival throughout the range and by individual growth in higher rainfall regions. While the models predict higher population growth rates in the core of the range under projected climates for 2050, they also suggest that the species faces a threat along arid range margins from the interaction of more frequent fire and drying climate. The results (and uncertainties) are helpful for prioritizing additional sampling of particular demographic parameters along these gradients to iteratively refine projections. In the appendices, we provide fully functional R code to perform all analyses.     

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.     

Similarities in butterfly emergence dates among populations suggest local adaptation to climate

Phenology shifts are the most widely cited examples of the biological impact of climate change, yet there are few assessments of potential effects on the fitness of individual organisms or the persistence of populations. Despite extensive evidence of climate‐driven advances in phenological events over recent decades, comparable patterns across species' geographic ranges have seldom been described. Even fewer studies have quantified concurrent spatial gradients and temporal trends between phenology and climate. Here we analyse a large data set (~129 000 phenology measures) over 37 years across the UK to provide the first phylogenetic comparative analysis of the relative roles of plasticity and local adaptation in generating spatial and temporal patterns in butterfly mean flight dates. Although populations of all species exhibit a plastic response to temperature, with adult emergence dates earlier in warmer years by an average of 6.4 days per °C, among‐population differences are significantly lower on average, at 4.3 days per °C. Emergence dates of most species are more synchronised over their geographic range than is predicted by their relationship between mean flight date and temperature over time, suggesting local adaptation. Biological traits of species only weakly explained the variation in differences between space‐temperature and time‐temperature phenological responses, suggesting that multiple mechanisms may operate to maintain local adaptation. As niche models assume constant relationships between occurrence and environmental conditions across a species' entire range, an important implication of the temperature‐mediated local adaptation detected here is that populations of insects are much more sensitive to future climate changes than current projections suggest.     

Spatial scale affects bioclimate model projections of climate change impacts on mountain plants

Plant species have responded to recent increases in global temperatures by shifting their geographical ranges poleward and to higher altitudes. Bioclimate models project future range contractions of montane species as suitable climate space shifts uphill. The species–climate relationships underlying such models are calibrated using data at either ‘macro’ scales (coarse resolution, e.g. 50 km × 50 km, and large spatial extent) or ‘local’ scales (fine resolution, e.g. 50 m × 50 m, and small spatial extent), but the two approaches have not been compared. This study projected macro (European) and local models for vascular plants at a mountain range in Scotland, UK, under low (+1.7 °C) and high (+3.3 °C) climate change scenarios for the 2080s. Depending on scenario, the local models projected that seven or eight out of 10 focal montane species would lose all suitable climate space at the site. However, the European models projected such a loss for only one species. The cause of this divergence was investigated by cross‐scale comparisons of estimated temperatures at montane species' warm range edges. The results indicate that European models overestimated species' thermal tolerances because the input coarse resolution climate data were biased against the cold, high‐altitude habitats of montane plants. Although tests at other mountain ranges are required, these results indicate that recent large‐scale modelling studies may have overestimated montane species' ability to cope with increasing temperatures, thereby underestimating the potential impacts of climate change. Furthermore, the results suggest that montane species persistence in microclimatic refugia might not be as widespread as previously speculated.     

Directionality of recent bird distribution shifts and climate change in Great Britain

There is good evidence that species' distributions are shifting poleward in response to climate change and wide interest in the magnitude of such responses for scientific and conservation purposes. It has been suggested from the directions of climatic changes that species' distribution shifts may not be simply poleward, but this has been rarely tested with observed data. Here, we apply a novel approach to measuring range shifts on axes ranging through 360°, to recent data on the distributions of 122 species of British breeding birds during 1988–1991 and 2008–2011. Although previously documented poleward range shifts have continued, with an average 13.5 km shift northward, our analysis indicates this is an underestimate because it ignores common and larger shifts that occurred along axes oriented to the north‐west and north‐east. Trailing edges contracted from a broad range of southerly directions. Importantly, these results are derived from systematically collected data so confounding observer‐effort biases can be discounted. Analyses of climate for the same period show that whilst temperature trends should drive species along a north–north‐westerly trajectory, directional responses to precipitation will depend on both the time of year that is important for determining a species' distribution, and the location of the range margin. Directions of species' range centroid shift were not correlated with spatial trends in any single climate variable. We conclude that range shifts of British birds are multidirectional, individualistic and probably determined by species‐specific interactions of multiple climate factors. Climate change is predicted to lead to changes in community composition through variation in the rates that species' ranges shift; our results suggest communities could change further owing to constituent species shifting along different trajectories. We recommend more studies consider directionality in climate and range dynamics to produce more appropriate measures of observed and expected responses to climate change.     

Modelling the potential distribution of endangered Prunus africana (Hook.f.) Kalkm. in East Africa

Continued harvesting and climate change are affecting the distributions of many plant species and may lead to numerous extinctions over the next century. Endangered species are likely to be a special concern, but the extent to which they are sensitive to climate is currently unclear. Species distribution modelling, if carefully implemented, can be used to assess climate sensitivity and potential climate change impacts, of tree species. We used MaxEnt algorithm for species distribution modelling to assess the potential distribution and climate change risks for a threatened Prunus africana, in East Africa. Data from different herbaria on its distribution were linked to data on climate to test hypotheses on the factors determining its distribution. Predictive models were developed and projected onto a climate scenario for 2050 to assess climate change risks. Precipitation of driest quarter and annual precipitation appeared to be the main factors influencing its distribution. Climate change was predicted to result in reductions of the species' habitats (e.g. Erasmus et al., Glob. Change Biol. 2002; 8 : 679). Prunus africana distribution is thus highly vulnerable to a warming climate and highlights the fact that both in‐situ and ex‐situ conservation will be a solution to global warming.     

Predicting fundamental and realized distributions based on thermal niche: A case study of a freshwater turtle

Species distribution models (SDM) have been broadly used in ecology to address theoretical and practical problems. Currently, there are two main approaches to generate SDMs: (i) correlative, which is based on species occurrences and environmental predictor layers and (ii) process-based models, which are constructed based on species' functional traits and physiological tolerances. The distributions estimated by each approach are based on different components of species niche. Predictions of correlative models approach species realized niches, while predictions of process-based are more akin to species fundamental niche. Here, we integrated the predictions of fundamental and realized distributions of the freshwater turtle Trachemys dorbigni. Fundamental distribution was estimated using data of T. dorbigni's egg incubation temperature, and realized distribution was estimated using species occurrence records. Both types of distributions were estimated using the same regression approaches (logistic regression and support vector machines), both considering macroclimatic and microclimatic temperatures. The realized distribution of T. dorbigni was generally nested in its fundamental distribution reinforcing theoretical assumptions that the species' realized niche is a subset of its fundamental niche. Both modelling algorithms produced similar results but microtemperature generated better results than macrotemperature for the incubation model. Finally, our results reinforce the conclusion that species realized distributions are constrained by other factors other than just thermal tolerances.