A comparative evaluation of presence-only methods for modelling species distribution

In spite of increasing application of presence-only models in ecology and conservation and the growing number of such models, little is known about the relative performance of different modelling methods, and some of the leading models (e.g. GARP and ENFA) have never been compared with one another. Here we compare the performance of six presence-only models that have been selected to represent an increasing level of model complexity [BIOCLIM, HABITAT, Mahalanobis distance (MD), DOMAIN, ENFA, and GARP] using data on the distribution of 42 species of land snails, nesting birds, and insectivorous bats in Israel. The models were calibrated using data from museum collections and observation databases, and their predictions were evaluated using Cohen's Kappa based on field data collected in a standardized sampling design covering most parts of Israel. Predictive accuracy varied between modelling methods with GARP and MD showing the highest accuracy, BIOCLIM and ENFA showing the lowest accuracy, and HABITAT and DOMAIN showing intermediate accuracy levels. Yet, differences between the various models were relatively small except for GARP and MD that were significantly more accurate than BIOCLIM and ENFA. In spite of large differences among species in prevalence and niche width, neither prevalence nor niche width interacted with the modelling method in determining predictive accuracy. However, species with relatively narrow niches were modelled more accurately than species with wider niches. Differences among species in predictive accuracy were highly consistent over all modelling methods, indicating the need for a better understanding of the ecological and geographical factors that influence the performance of species distribution models.     

A phyloclimatic study of Cyclamen

Background

The impact of global climate change on plant distribution, speciation and extinction is of current concern. Examining species climatic preferences via bioclimatic niche modelling is a key tool to study this impact. There is an established link between bioclimatic niche models and phylogenetic diversification. A next step is to examine future distribution predictions from a phylogenetic perspective. We present such a study using Cyclamen (Myrsinaceae), a group which demonstrates morphological and phenological adaptations to its seasonal Mediterranean-type climate. How will the predicted climate change affect future distribution of this popular genus of garden plants?

Results

We demonstrate phylogenetic structure for some climatic characteristics, and show that most Cyclamen have distinct climatic niches, with the exception of several wide-ranging, geographically expansive, species. We reconstruct climate preferences for hypothetical ancestral Cyclamen. The ancestral Cyclamen lineage has a preference for the seasonal Mediterranean climate characteristic of dry summers and wet winters. Future bioclimatic niches, based on BIOCLIM and Maxent models, are examined with reference to a future climate scenario for the 2050s. Over the next 50 years we predict a northward shift in the area of climatic suitability, with many areas of current distribution becoming climatically unsuitable. The area of climatic suitability for every Cyclamen species is predicted to decrease. For many species, there may be no areas with a suitable climate regardless of dispersal ability, these species are considered to be at high risk of extinction. This risk is examined from a phylogenetic perspective.

Conclusion

Examining bioclimatic niches from a phylogenetic perspective permits novel interpretations of these models. In particular, reconstruction of ancestral niches can provide testable hypothesis about the historical development of lineages. In the future we can expect a northwards shift in climatic suitability for the genus Cyclamen. If this proves to be the case then dispersal is the best chance of survival, which seems highly unlikely for ant-dispersed Cyclamen. Human-assisted establishment of Cyclamen species well outside their native ranges offers hope and could provide the only means of dispersal to potentially suitable future environments. Even without human intervention the phylogenetic perspective demonstrates that major lineages could survive climate change even if many species are lost.     

Acido‐ and neutrophilic temperate forest plants display distinct shifts in ecological pH niche across north‐western Europe

Ecological niches of organisms vary across geographical space, but niche shift patterns between regions and the underlying mechanisms remain largely unexplored. We studied shifts in the pH niche of 42 temperate forest plant species across a latitudinal gradient from northern France to boreo‐nemoral Sweden. We asked 1) whether species restrict their niches with increasing latitude as they reach their northern range margin (environmental constraints); 2) whether species expand their niches with increasing latitude as regional plant species richness decreases (competitive release); and 3) whether species shift their niche position toward more acidic sites with increasing latitude as the relative proportion of acidic soils increases (local adaptation). Based on 1458 vegetation plots and corresponding soil pH values, we modelled species response curves using Huisman–Olff–Fresco models. Four niche measures (width, position, left and right border) were compared among regions by randomization tests. We found that with increasing latitude, neutrophilic species tended to retreat from acidic sites, indicating that these species retreat to more favorable sites when approaching their range margin. Alternatively, these species might benefit from enhanced nitrogen deposition on formerly nutrient‐poor, acidic sites in southern regions or lag behind in post‐glacial recolonization of potential habitats in northern regions. Most acidophilic species extended their niche toward more base‐rich sites with increasing latitude, indicating competitive release from neutrophilic species. Alternatively, acidophilic species might benefit from optimal climatic conditions in the north where some have their core distribution area. Shifts in the niche position suggested that local adaptation is of minor importance. We conclude that shifts in the pH niche of temperate forest plants are the rule, but the directions of the niche shifts and possible explanations vary. Our study demonstrates that differentiating between acidophilic and neutrophilic species is crucial to identify general patterns and underlying mechanisms.     

Genetic structure and ecological niche segregation of Indian gray mongoose (Urva edwardsii) in Iran

Combining genetic data with ecological niche models is an effective approach for exploring climatic and nonclimatic environmental variables affecting spatial patterns of intraspecific genetic variation. Here, we adopted this combined approach to evaluate genetic structure and ecological niche of the Indian gray mongoose (Urva edwardsii) in Iran, as the most western part of the species range. Using mtDNA, we confirmed the presence of two highly differentiated clades. Then, we incorporated ensemble of small models (ESMs) using climatic and nonclimatic variables with genetic data to assess whether genetic differentiation among clades was coupled with their ecological niche. Climate niche divergence was also examined based on a principal component analysis on climatic factors only. The relative habitat suitability values predicted by the ESMs for both clades revealed their niche separation. Between‐clade climate only niche comparison revealed that climate space occupied by clades is similar to some extent, but the niches that they utilize differ between the distribution ranges of clades. We found that in the absence of evidence for recent genetic exchanges, distribution models suggest the species occurs in different niches and that there are apparent areas of disconnection across the species range. The estimated divergence time between the two Iranian clades (4.9 Mya) coincides with the uplifting of the Zagros Mountains during the Early Pliocene. The Zagros mountain‐building event seems to have prevented the distribution of U. edwardsii populations between the western and eastern parts of the mountains as a result of vicariance events. Our findings indicated that the two U. edwardsii genetic clades in Iran can be considered as two conservation units and can be utilized to develop habitat‐specific and climate change‐integrated management strategies.     

Biotic attrition from tropical forests correcting for truncated temperature niches

Species migration in response to warming temperatures is expected to lead to ‘biotic attrition,’ or loss of local diversity, in areas where the number of species emigrating or going locally extinct exceeds the number immigrating. Biotic attrition is predicted be especially severe in the low‐lying hot tropics since elevated temperatures may surpass the observed tolerances of most extant species. It is possible, however, that the estimated temperature niches of many species are inaccurate and truncated with respect to their true tolerances due to the absence of hotter areas under current global climate. If so, these species will be capable of persisting in some areas where future temperatures exceed current temperatures, reducing rates of biotic attrition. Here, we use natural history collections data to estimate the realized thermal niches of > 2000 plant species from the tropical forests of South America. In accord with the truncation hypothesis, we find that the thermal niches of species from hot lowland areas are several degrees narrower than the thermal niches of species from cooler areas. We estimate rates of biotic attrition for South American tropical forests due to temperature increases ranging from 1 to 5 °C, and under two niche assumptions. The first is that the observed thermal niches truly reflect the plant's tolerances and that the reduction in niche breadth is due to increased specialization. The second is that lowland species have the same mean thermal niche breadth as nonlowland and nonequatorial species. The differences between these two models are dramatic. For example, using observed thermal niches we predict an almost complete loss of plant diversity in most South American tropical forests due to a 5 °C temperature increase, but correcting for possible niche truncation we estimate that most forests will retain > 50–70% of their current species richness. The different predictions highlight the importance of using fundamental vs. realized niches in predicting the responses of species to global climate change.     

Predicting the occurrence of rare Brazilian birds with species distribution models

Species distribution models (SDMs) yield reliable and needed predictions to identify regions that have similar environmental conditions and were used here to predict potential ranges of rare species to identify new localities were they might occur based on their occurrence probability (i.e. niche suitability). We modeled the potential distribution ranges of ten endangered or rare birds from the South American Cerrado biome, using four temperature- and four precipitation-related bioclimatic variables, three topographical variables, and nine different niche modeling methods for each species. We used an ensemble-forecasting approach to reach a consensus scenario to obtain the average distribution for each species based on the five best models generating a distribution map of each species. Model efficiency was related to sample size and not appropriate below ten independent spatial occurrences. The potential distributions of seven species revealed that their occurrence ranges might go beyond their known ranges, but that most of them seem to occur near the regions where they have already been reported. The models of only three species were considered unsatisfactory in helping identify their potential distribution. Models created maps with higher occurrence probability regions where rare Cerrado birds might occur. These range projections can potentially decrease the costs and improve the efficiency of future field searches. On methodological terms, the application of SDMs to predict species ranges should compare different modeling methods and evaluate the effect of sample size on their performance.     

Climate change likely to reduce orchid bee abundance even in climatic suitable sites

Studies have tested whether model predictions based on species’ occurrence can predict the spatial pattern of population abundance. The relationship between predicted environmental suitability and population abundance varies in shape, strength and predictive power. However, little attention has been paid to the congruence in predictions of different models fed with occurrence or abundance data, in particular when comparing metrics of climate change impact. Here, we used the ecological niche modeling fit with presence–absence and abundance data of orchid bees to predict the effect of climate change on species and assembly level distribution patterns. In addition, we assessed whether predictions of presence–absence models can be used as a proxy to abundance patterns. We obtained georeferenced abundance data of orchid bees (Hymenoptera: Apidae: Euglossina) in the Brazilian Atlantic Forest. Sampling method consisted in attracting male orchid bees to baits of at least five different aromatic compounds and collecting the individuals with entomological nets or bait traps. We limited abundance data to those obtained by similar standard sampling protocol to avoid bias in abundance estimation. We used boosted regression trees to model ecological niches and project them into six climate models and two Representative Concentration Pathways. We found that models based on species occurrences worked as a proxy for changes in population abundance when the output of the models were continuous; results were very different when outputs were discretized to binary predictions. We found an overall trend of diminishing abundance in the future, but a clear retention of climatically suitable sites too. Furthermore, geographic distance to gained climatic suitable areas can be very short, although it embraces great variation. Changes in species richness and turnover would be concentrated in western and southern Atlantic Forest. Our findings offer support to the ongoing debate of suitability–abundance models and can be used to support spatial conservation prioritization schemes and species triage in Atlantic Forest.     

Can species distribution modelling provide estimates of population densities? A case study with jaguars in the Neotropics

Aim To test the prediction that environmental suitability derived from species distribution modelling (SDM) could be a surrogate for jaguar local population density estimates. Location Americas. Methods We used 1409 occurrence records of jaguars to model the distribution of the species using 11 SDM methods. We tested whether models’ suitability is linearly correlated with jaguar population densities estimated from 37 different locations. We evaluated whether the relationship between density and suitability forms a constraint envelope, in which higher densities are found mainly in regions with high suitability, whereas low densities can occur in regions with variable suitability. We tested this using heteroscedasticity test and quantile regressions. Results A positive linear relationship between suitability and jaguar density was found only for four methods [bioclimatic envelope (BIOCLIM), genetic algorithm for rule set production (GARP), maximum entropy (Maxent) and generalized boosting models (GBM)], but with weak explanatory power. BIOCLIM showed the strongest relationship. Variance of suitability for lower densities values was larger than for higher values for many of the SDM models used, but the quantile regression was significantly positive only for BIOCLIM and random forests (RF). RF and GBM provided the most accurate models when measured with the standard SDM evaluation metrics, but possess poor relationship with local density estimates. Main conclusions Results indicate that the relationship between density and suitability could be better described as a triangular constraint envelope than by a straight positive relationship, and some of the SDM methods tested here were able to discriminate regions with high or low local population densities. Low jaguar densities can occur in areas with low or high suitability, whereas high values are restricted to areas where the suitability is greater. In high suitability areas but with low jaguar density estimates, we discuss how extrinsic factors driving abundance could act at local scales and then prevent higher densities that would be expected by the favourable regional environmental conditions.     

Insect occurrence in agricultural land-uses depends on realized niche and geographic range properties

Geographic range size predicts species’ responses to land-use change and intensification, but the reason why is not well established because many correlates of larger geographic ranges, such as realized niche breadth, may mediate species’ responses to environmental change. Agricultural land uses (hereafter ‘agroecosystems’) have warm, dry and more variable microclimates than do cooler and wetter mature forests, so are predicted to filter for species that have warmer, drier and broader fundamental and realized niches. To test these predictions, we estimated species’ realized niches, for temperature and precipitation, and geographic range sizes of 764 insect species by matching GBIF occurrence records to global climate layers, and modelled how species presence/absence in mature forest and nearby agroecosystems depend on species’ realized niches or geographic ranges. The predicted species niche effects consistently matched the expected direction of microclimatic transition from mature forest to agroecosystems. We found a clear signal that species with preference for warmer and drier climates were more likely to be present in agroecosystems. In addition, the probability that species occurred in different land-use types was predicted better by species’ realized niche than their geographic range size. However, niche effects are often context-dependent and varied amongst studies, taxonomic groups and regions used in this analysis: predicting which particular aspects of species’ realized niche cause sensitivity to land-use change, and the underpinning mechanisms, remains a major challenge for future research and multiple components of species’ realized niches may be important to consider. Using realized niches derived from open-source occurrence records can be a simple and widely applicable tool to help identify when biodiversity responds to the microclimate component of land-use change.     

Effects of bird species-level environmental preference on landscape-level richness-heterogeneity relationships

The niche-based argument that species are filtered from environments in which they cannot sustain viable populations is the basis of the Richness-Heterogeneity Relationship (RHR). However, the multi-dimensionality of niches suggests that the RHR may take different shapes along different environmental axes, with potential confounding effects if filtering along the axes is not equally strong. Here, we explore how different structural and landscape variables drive the RHR as the accumulative outcome of environmental preferences at the species-level while considering the intercorrelation between heterogeneity levels along three niche axes. We used occurrence data of avifauna from 226 sites situated along a grassland-to-woodland gradient in a Midwestern USA study area. In each site, we quantified horizontal (habitat cover type), vertical (vegetation height structure), and spatial (habitat configuration) heterogeneity and explored the shape of the observed RHR at the landscape scale, as well as the correlations among heterogeneity levels at different axes. We then fitted species distribution models to environmental variables from the three axes separately and compared the stacked probabilities of occurrences of all species to the observed species richness. We found that predictions of richness patterns improved when more than one heterogeneity axis was included in RHR models, and that habitat suitability along different axes is not equally strong. Furthermore, a unimodal RHR along the vegetation height axis, which the species distribution models revealed to be a weak predictor for most species, may arise through intercorrelation with heterogeneity along the two other axes, along which we recorded stronger signals of environmental preference at the species level. Our results emphasize the importance of selecting relevant niche axes in studies of species richness patterns because ultimately, these patterns reflect the various environmental preferences of individual species.     

Modelling the potential geographic distribution of invasive ant species in New Zealand

Despite their economic and environmental impacts, there have been relatively few attempts to model the distribution of invasive ant species. In this study, the potential distribution of six invasive ant species in New Zealand are modelled using three fundamentally different methods (BIOCLIM, DOMAIN, MAXENT). Species records were obtained from museum collections in New Zealand. There was a significant relationship between the length of time an exotic species had been present in New Zealand and its geographic range. This is the first time such a time lag has been described for exotic ant species, and shows there is a considerable time lag in their spread. For example, it has taken many species several decades (40–60 years) to obtain a distribution of 17–25% of New Zealand regions. For all six species, BIOCLIM performed poorly compared to the other two modelling methods. BIOCLIM had lower AUC scores and higher omission error, suggesting BIOCLIM models under-predicted the potential distribution of each species. Omission error was significantly higher between models fitted with all 19 climate variables compared to those models with fewer climate variables for BIOCLIM, but not DOMAIN or MAXENT. Widespread species had a greater commission error. A number of regions in New Zealand are predicted to be climatically suitable for the six species modelled, particularly coastal and lowland areas of both the North and South Islands.     

Different facets of the same niche: Integrating citizen science and scientific survey data to predict biological invasion risk under multiple global change drivers

Citizen science initiatives have been increasingly used by researchers as a source of occurrence data to model the distribution of alien species. Since citizen science presence-only data suffer from some fundamental issues, efforts have been made to combine these data with those provided by scientifically structured surveys. Surprisingly, only a few studies proposing data integration evaluated the contribution of this process to the effective sampling of species' environmental niches and, consequently, its effect on model predictions on new time intervals. We relied on niche overlap analyses, machine learning classification algorithms and ecological niche models to compare the ability of data from citizen science and scientific surveys, along with their integration, in capturing the realized niche of 13 invasive alien species in Italy. Moreover, we assessed differences in current and future invasion risk predicted by each data set under multiple global change scenarios. We showed that data from citizen science and scientific surveys captured similar species niches though highlighting exclusive portions associated with clearly identifiable environmental conditions. In terrestrial species, citizen science data granted the highest gain in environmental space to the pooled niches, determining an increased future biological invasion risk. A few aquatic species modelled at the regional scale reported a net loss in the pooled niches compared to their scientific survey niches, suggesting that citizen science data may also lead to contraction in pooled niches. For these species, models predicted a lower future biological invasion risk. These findings indicate that citizen science data may represent a valuable contribution to predicting future spread of invasive alien species, especially within national-scale programmes. At the same time, citizen science data collected on species poorly known to citizen scientists, or in strictly local contexts, may strongly affect the niche quantification of these taxa and the prediction of their future biological invasion risk.     

How do Snow Partridge (Lerwa lerwa) and Tibetan Snowcock (Tetraogallus tibetanus) coexist in sympatry under high‐elevation conditions on the Qinghai–Tibetan Plateau?

The Qinghai–Tibetan Plateau (QTP) has the highest elevations of all biodiversity hotspots. Difficulties involved in fieldwork at high elevations cause challenges in researching mechanisms facilitating species coexistence. Herein, we investigated Snow Partridge (Lerwa lerwa) and Tibetan Snowcock (Tetraogallus tibetanus), the only two endemic Galliformes on the QTP, to understand species coexistence patterns and determine how they live in sympatry for the first time. We assembled occurrence data, estimated habitat suitability differences and the underlying factors between two species at different scales using ecological niche models. Niche overlap tests were used to investigate whether niche differences between these species allow for their coexistence. We found that elevation was the most important factor determining habitat suitability for both species. At the meso‐scale, two species have similar ecological niches with their suitable habitats lying predominantly along ridge crests. However, ridge crests were more influential for habitat suitability by L. lerwa than for that of T. tibetanus because the latter species ranges further afield than ridge crests. Thus, differences in habitat suitability between these species lead to habitat partitioning, which allows stable coexistence. At the macro‐scale, temperature and precipitation were major factors influencing habitat suitability differences between these species. Tetraogallus tibetanus extended into the hinterland of the QTP and occurred at higher elevations, where colder and drier alpine conditions are commonplace. Conversely, L. lerwa occurred along the southeastern margin of the QTP with a lower snow line, an area prone to rainy and humid habitats. Niche overlap analysis showed that habitat suitability differences between these species are not driven by niche differentiation. We concluded that the coexistence of these two pheasants under high‐elevation conditions could be an adaption to different alpine conditions.     

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.     

The contribution of small collections to species distribution modelling: A case study from Fuireneae (Cyperaceae)

The recent and rapid digitization of biodiversity data from natural history collection (NHC) archives has enriched collections based data repositories; this data continues to inform studies of species' geographic distributions. Here we investigate the relative impact of plant data from small natural history collections (collections with < 100,000 specimens) on species distributional models in an effort to document the potential of data from small NHCs to contribute to and inform biodiversity research. We modelled suitable habitat of five test case species from Fuireneae (Cyperaceae) in the United States using specimen records available via the Global Biodiversity Information Facility and that of data ready to mobilize from two regional small herbaria. Data were partitioned into three datasets based on their source: 1) collections-based records from large NHCs accessed GBIF, 2) collections-based records from small NHCs accessed from GBIF, and 3) collections-based records from two small regional herbaria not yet mobilized to GBIF. We extracted and evaluated the ecological niche represented for each of the three datasets by applying dataset occurrences to 14 environmental factors, and we modelled habitat suitability using Maxent to compare the represented distribution of the environmental values among the datasets. Our analyses indicate that the data from small NHCs contributed unique information in both geographic and environmental space. When data from small collections were combined with data from large collections, species models of the ecological niche resulted in more refined predictions of habitat suitability, indicating that small collections can contribute unique occurrence data which enhance species distribution models by bridging geographic collection gaps and shifting modelled predictions of suitable habitat. Inclusion of specimen records from small collections in ongoing digitization efforts is essential for generating informed models of a species' niche and distribution.     

Temporal variation in trophic relationships among three congeneric penguin species breeding in sympatry

Penguins are a monophyletic group in which many species are found breeding sympatrically, raising questions regarding how these species coexist successfully. Here, the isotopic niche of three sympatric pygoscelid penguin species was investigated at Powell Island, South Orkney Islands, during two breeding seasons (austral summers 2013–2014 and 2015–2016). Measurements of carbon (δ¹³C) and nitrogen (δ¹⁵N) stable isotope ratios were obtained from blood (adults) or feather (chicks) samples collected from Adélie Pygoscelis adeliae, chinstrap P. antarctica, and gentoo P. papua penguins. Isotopic niche regions (a proxy for the realized trophic niches) were computed to provide estimates of the trophic niche width of the studied species during the breeding season. The isotopic niche regions of adults of all three species were similar, but gentoo chicks had noticeably wider isotopic niches than the chicks of the other two species. Moderate to strong overlap in isotopic niche among species was found during each breeding season and for both age groups, suggesting that the potential for competition for shared food sources was similar during the two study years, although the actual level of competition could not be determined owing to the lack of data on resource abundance. Clear interannual shifts in isotopic niche were seen in all three species, though of lower amplitude for adult chinstrap penguins. These shifts were due to variation in carbon, but not nitrogen, isotopic ratios, which could indicate either a change in isotopic signature of their prey or a switch to an alternative food web. The main conclusions of this study are that (1) there is a partial overlap in the isotopic niches of these three congeneric species and that (2) they responded similarly to changes that likely occurred at the base of their food chain between the 2 years of the study.     

Effect of inventory method on niche models: Random versus systematic error

Data from large-scale biological inventories are essential for understanding and managing Earth's ecosystems. The Forest Inventory and Analysis Program (FIA) of the U.S. Forest Service is the largest biological inventory in North America; however, the FIA inventory recently changed from an amalgam of different approaches to a nationally-standardized approach in 2000. Full use of both data sets is clearly warranted to target many pressing research questions including those related to climate change and forest resources. However, full use requires lumping FIA data from different regionally-based designs (pre-2000) and/or lumping the data across the temporal changeover. Combining data from different inventory types must be approached with caution as inventory types represent different probabilities of detecting trees per sample unit, which can ultimately confound temporal and spatial patterns found in the data. Consequently, the main goal of this study is to evaluate the effect of inventory on a common analysis in ecology, modeling of climatic niches (or species-climate relations). We use non-parametric multiplicative regression (NPMR) to build and compare niche models for 41 tree species from the old and new FIA design in the Pacific coastal United States. We discover two likely effects of inventory on niche models and their predictions. First, there is an increase from 4 to 6% in random error for modeled predictions from the different inventories when compared to modeled predictions from two samples of the same inventory. Second, systematic error (or directional disagreement among modeled predictions) is detectable for 4 out of 41 species among the different inventories: Calocedrus decurrens, Pseudotsuga menziesii, and Pinus ponderosa, and Abies concolor. Hence, at least 90% of niche models and predictions of probability of occurrence demonstrate no obvious effect from the change in inventory design. Further, niche models built from sub-samples of the same data set can yield systematic error that rivals systematic error in predictions for models built from two separate data sets. This work corroborates the pervasive and pressing need to quantify different types of error in niche modeling to address issues associated with data quality and large-scale data integration.     

Scaling of species distribution models across spatial resolutions and extents along a biogeographic gradient. The case of the Iberian mole Talpa occidentalis

Scaling is a key process in modelling approaches since it allows for translating information from one scale to another. However, the success of this procedure may depend on ‘source’ and ‘target’ scales, but also on the biogeographic/ecological context of the study area. We aimed to quantify the performance and success of scaling species distribution model (SDM) predictions across spatial resolution and extent along a biogeographic gradient using the Iberian mole as study case. We ran separate MaxEnt models at two extents (national and regional) using independent datasets (species locations and environmental predictors) collected at 10 km and 50 m resolutions respectively. Model performance and success of scaling SDMs were quantified on the basis of accuracy measures and spatial predictions. Complementarily, we calculated marginality and tolerance as indicators of habitat availability and niche truncation along the biogeographic gradient. Model performance increased with resolution and extent, as well as from north to south (mainly for high resolution models). When regional models were validated at different scales, their performance reduced severely, particularly in the case of coarse resolution models (some of them performed worse than random). However, when the 10 km‐national model was downscaled within regions, it performed better (AUC_test: 0.82, 0.85 and 0.55 respectively for Galicia, Madrid and Granada) than models specifically calibrated within each region at 10 km (0.47, 0.65, 0.44). Indeed, it also had a better accuracy when projected at 50 m (0.77, 0.91, 0.79) than models fitted at that resolution (0.62, 0.83, 0.96) in two of the three cases. The success of scaling model predictions decreased along the biogeographic gradient, being these differences associated to niche truncation. Models representing non‐truncated niches were more successfully scaled across resolutions and extents (particularly in areas not offering all possible habitats for species), which has important implications for SDM applications.     

Niche shift in four non‐native estrildid finches and implications for species distribution models

Non‐native species can have severe impacts on ecosystems. Therefore, predictions of potentially suitable areas that are at risk of the establishment of non‐native populations are desirable. In recent years, species distribution models (SDMs) have been widely applied for this purpose. However, the appropriate selection of species records, whether from the native area alone or also from the introduced range, is still a matter of debate. We combined analyses of native and non‐native realized climate niches to understand differences between models based on all locations, as well as on locations from the native range only. Our approach was applied to four estrildid finch species that have been introduced to many regions around the world. Our results showed that SDMs based on location data from native areas alone may underestimate the potential distribution of a given species. The climatic niches of species in their native ranges differed from those of their non‐native ranges. Niche comparisons resulted in low overlap values, indicating considerable niche shifts, at least in the realized niches of these species. All four species have high potential to spread over many tropical and subtropical areas. However, transferring these results to temperate areas has a high degree of uncertainty, and we urge caution when assessing the potential spread of tropical species that have been introduced to higher latitudes.