GIS-based niche modeling for mapping species' habitat

Ecological "niche modeling" using presence-only locality data and large-scale environmental variables provides a powerful tool for identifying and mapping suitable habitat for species over large spatial extents. We describe a niche modeling approach that identifies a minimum (rather than an optimum) set of basic habitat requirements for a species, based on the assumption that constant environmental relationships in a species' distribution (i.e., variables that maintain a consistent value where the species occurs) are most likely to be associated with limiting factors. Environmental variables that take on a wide range of values where a species occurs are less informative because they do not limit a species' distribution, at least over the range of variation sampled. This approach is operationalized by partitioning Mahalanobis D2 (standardized difference between values of a set of environmental variables for any point and mean values for those same variables calculated from all points at which a species was detected) into independent components. The smallest of these components represents the linear combination of variables with minimum variance; increasingly larger components represent larger variances and are increasingly less limiting. We illustrate this approach using the California Gnatcatcher (Polioptila californica Brewster) and provide SAS code to implement it.     

K-select analysis: a new method to analyse habitat selection in radio-tracking studies

Two kinds of wildlife habitat studies can be distinguished in the literature: hindcasting and forecasting studies. Hindcasting studies aim to emphasize among a large set of habitat variables those that are of interest for the focus species, whereas forecasting studies are intended to predict habitat selection according to a small number of habitat variables for a given area. We provide here a new analytical tool which relies on the concept of ecological niche, the K-select analysis, for hindcasting studies of habitat selection by animals using radio-tracking data. Each habitat variable defines one dimension in the ecological space. For each animal, the difference between the vector of average available habitat conditions and the vector of average used conditions defines the marginality vector. Its size is proportional to the importance of habitat selection, and its direction indicates which variables are selected. By performing a non-centered principal component analysis of the table containing the coordinates of the marginality vectors of each animal (row) on the habitat variables (column), the K-select analysis returns a linear combination of habitat variables for which the average marginality is greatest. It is a synthesis of variables which contributes the most to the habitat selection. As with principal component analysis, the biological significance of the factorial axes is deduced from the loading of variables. An example is provided: habitat selection by wild boar is studied in a Mediterranean habitat using the K-select analysis. The numerous advantages of the analysis (a large number of variables that can be included, individual variability in habitat selection taken into account, a lack of too strict underlying hypotheses) make it a powerful approach in radio-tracking studies designed to identify habitat variables that are selected by animals.     

喀斯特山地青冈栎群落优势种的种间关系分析

采用2×2列联表的χ2检验和Spearman秩相关系数分析了喀斯特山地青冈栎（Cyclobalanopsis glauca）群落22个优势种的种间联结性和相关性。结果表明,在所组成的231个种对中,χ2检验中有100个种对为正联结,110个种对为负联结;Spearman秩相关系数检验有114个种对为正相关,117个种对为负相关,正、负联结或相关的种对数相近。正联结或正相关的种对主要体现了种间对生境具有相似的生态适应性和生物学特性,而负联结或负相关关系则主要由于对生境的不同偏好或相异的生物学特性所致。喀斯特山地高度的生境异质性促使优势种间的生态位相互分化,对生境的偏好趋异,负联结或负相关的种对趋于增加,因而喀斯特山地高度的生境异质性对植物种间关系的形成具有重要的影响。研究结果对于指导喀斯特地区进行人工植被恢复和重建具有一定的实践指导意义。     

The ecological niche of Daphnia magna characterized using population growth rate

The concept of an organism's niche is central to ecological theory, but an operational definition is needed that allows both its experimental delineation and interpretation of field distributions of the species. Here we use population growth rate (hereafter, pgr) to define the niche as the set of points in niche space where pgr > 0. If there are just two axes to the niche space, their relationship to pgr can be pictured as a contour map in which pgr varies along the axes in the same way that the height of land above sea level varies with latitude and longitude. In laboratory experiments we measured the pgr of Daphnia magna over a grid of values of pH and Ca2+, and so defined its "laboratory niche" in pH-Ca2+ space. The position of the laboratory niche boundary suggests that population persistence is only possible above 0.5 mg Ca2+/L and between pH 5.75 and pH 9, though more Ca2+ is needed at lower pH values. To see how well the measured niche predicts the field distribution of D. magna, we examined relevant field data from 422 sites in England and Wales. Of the 58 colonized water bodies, 56 lay within the laboratory niche. Very few of the sites near the niche boundary were colonized, probably because pgr there is so low that populations are vulnerable to extinction by other factors. Our study shows how the niche can be quantified and used to predict field distributions successfully.     

Assessing Risks to Biodiversity from Future Landscape Change

We examined the impacts of possible future land development patterns on the biodiversity of a landscape. Our landscape data included a remote sensing derived map of the current habitat of the study area and six maps of future habitat distributions resulting from different land development scenarios. Our species data included lists of all bird, mammal, reptile, and amphibian species in the study area, their habitat associations, and area requirements for each. We estimated the area requirements using home ranges, sampled population densities, or genetic area requirements that incorporate dispersal distances. Our measures of biodiversity were species richness and habitat abundance. We calculated habitat abundance in two ways. First, we computed the total habitat area for each species in each landscape. Second, we calculated the number of habitat units for each species in each landscape by dividing the size of each habitat patch in the landscape by the area requirement and summing over all patches. Species richness was based on presence of habitat. Species became extinct in the landscape if they had no habitat area or no habitat units, respectively. We then computed ratios of habitat abundance in each future landscape to habitat abundance in the present for each species. We also computed the ratio of future to present species richness. We then calculated summary statistics across all species. Species richness changed little from present to future. There were distinctly greater risks to habitat abundance in landscapes that extrapolated from present trends or zoning patterns, however, as opposed to landscapes in which land development activities followed more constrained patterns. These results were stable when tested using Monte Carlo simulations and sensitivity tests on the area requirements. We conclude that this methodology can begin to discriminate the effects of potential changes in land development on vertebrate biodiversity.     

Interspecific competition between native Eurasian red squirrels and alien grey squirrels: does resource partitioning occur?

In heterogeneous environments, differential niche selection by two competing species will result in niche partitioning so that individuals of each species can maximise their fitness under different sets of environmental variables. Thus, niche partitioning is considered essential to allow co-existence of ecologically related species. To assess whether niche partitioning was occurring between native red squirrels and alien grey squirrels living together in a 13-ha high-quality mixed deciduous woodland in north Italy, we investigated temporal and spatial patterns in their activity and foraging behaviour between 1996 and 1998. We used live trapping and radio-tracking to study numbers, distribution and behaviour of squirrels. Daily and seasonal temporal activity patterns, and activity on the ground and in the trees, were similar in the two species. However, grey squirrels were more tree specialists and had a narrower tree-species niche width than red squirrels, in particular making greater use of oak. Other studies of red and grey squirrels in allopatry show that the two species differ in the extent they utilise oak. Overall, tree-species niche overlap was about 70%. Grey squirrels had larger home ranges than red squirrels. Home ranges and core areas of both species were larger in males than females. Also, intraspecific home range and core-area overlap patterns were similar to those found in allopatric populations of these species. Overall, there was no evidence that the use of space of one species was affected by the other. Our results show that there was no niche partitioning of activity or foraging behaviour in time or space during the study. This suggests that, at moderate grey-squirrel densities, red squirrels are unable to avoid competition with grey squirrels, and that competition for food and/or space will occur when these resources become limiting.     

Ecological niche modeling of customary medicinal plant species used by Australian Aborigines to identify species-rich and culturally valuable areas for conservation

Customary medicinal plant species used by Australian Aborigines are disappearing rapidly with its associated knowledge, due to the loss of habitats. Conservation and protection of these species is important as they represent sources of novel therapeutic phytochemical compounds and are culturally valuable. Information on the spatial distribution and use of customary medicinal plants is often inadequate and fragmented, posing limitations on the identification and conservation of species-rich areas and culturally valuable habitats.In this study, the habitat suitability modeling program, MaxEnt, was used to predict the potential ecological niches of 431 customary medicinal plant species, based on bioclimatic variables. Specimen locality records were obtained from the Global Biodiversity Information Facility (GBIF) data portal and from Australia's Virtual Herbarium (AVH).Ecological niche models of 414 predicted species, which had 30 or more occurrence points, were used to produce maps indicating areas that were ecologically suitable for multiple species (concordance of high predicted ecological suitability) and having cultural values. For the concordance map, individual species niche models were thresholded and summed. To derive a map of culturally valuable areas, customary medicinal uses from Customary Medicinal Knowledgebase (CMKb) (www.biolinfo.org/cmkb) were used to weight individual species models, resulting in a value within each grid cell reflecting its cultural worth.Even though the available information is scarce and fragmented, our approach provides an opportunity to infer areas predicted to be suitable for multiple species (i.e. concordance hotspots) and to estimate the cultural value of a particular geographical area. Our results also indicate that to conserve bio-cultural diversity, comprehensive information and active participation of Aboriginal communities is indispensable.     

Integrating habitat-masked range maps with quantifications of prevalence to estimate area of occupancy in IUCN assessments

Estimates of species geographic ranges constitute critical input for biodiversity assessments, including those for the International Union for the Conservation of Nature (IUCN) Red List of Threatened Species. Area of occupancy (AOO) is one metric that IUCN uses to quantify a species’ range, but data limitations typically lead to either under- or overestimates (and unnecessarily wide bounds of uncertainty). Fortunately, existing methods in which range maps and land-cover data are used to estimate the area currently holding habitat for a species can be extended to yield an unbiased range of plausible estimates for AOO. Doing so requires estimating the proportion of sites (currently containing habitat) that a species occupies within its range (i.e., prevalence). Multiplying a quantification of habitat area by prevalence yields an estimate of what the species inhabits (i.e., AOO). For species with intense sampling at many sites, presence–absence data sets or occupancy modeling allow calculation of prevalence. For other species, primary biodiversity data (records of a species’ presence at a point in space and time) from citizen-science initiatives and research collections of natural history museums and herbaria could be used. In such cases, estimates of sample prevalence should be corrected by dividing by the species’ detectability. To estimate detectability from these data sources, extensions of inventory-completeness analyses merit development. With investments to increase the quality and availability of online biodiversity data, consideration of prevalence should lead to tighter and more realistic bounds of AOO for many taxonomic groups and geographic regions. By leading to more realistic and representative characterizations of biodiversity, integrating maps of current habitat with estimates of prevalence should empower conservation practitioners and decision makers and thus guide actions and policy worldwide.     

Use of Habitats as Surrogates of Biodiversity for Efficient Coral Reef Conservation Planning in Pacific Ocean Islands

Abstract: Marine protected areas (MPAs) have been highlighted as a means toward effective conservation of coral reefs. New strategies are required to more effectively select MPA locations and increase the pace of their implementation. Many criteria exist to design MPA networks, but generally, it is recommended that networks conserve a diversity of species selected for, among other attributes, their representativeness, rarity, or endemicity. Because knowledge of species’ spatial distribution remains scarce, efficient surrogates are urgently needed. We used five different levels of habitat maps and six spatial scales of analysis to identify under which circumstances habitat data used to design MPA networks for Wallis Island provided better representation of species than random choice alone. Protected‐area site selections were derived from a rarity–complementarity algorithm. Habitat surrogacy was tested for commercial fish species, all fish species, commercially harvested invertebrates, corals, and algae species. Efficiency of habitat surrogacy varied by species group, type of habitat map, and spatial scale of analysis. Maps with the highest habitat thematic complexity provided better surrogates than simpler maps and were more robust to changes in spatial scales. Surrogates were most efficient for commercial fishes, corals, and algae but not for commercial invertebrates. Conversely, other measurements of species‐habitat associations, such as richness congruence and composition similarities provided weak results. We provide, in part, a habitat‐mapping methodology for designation of MPAs for Pacific Ocean islands that are characterized by habitat zonations similar to Wallis. Given the increasing availability and affordability of space‐borne imagery to map habitats, our approach could appreciably facilitate and improve current approaches to coral reef conservation and enhance MPA implementation.     

若尔盖湿地3种无尾两栖类不同发育阶段的生态位宽度

研究了若尔盖湿地国家级自然保护区的3种无尾两栖类,高原林蛙(Rana kukunoris)、倭蛙(Nanorana pleskei)和岷山蟾蜍(Bufo minshanicus)的成体和亚成体在7个生境因子(牧场性质、牛粪数量、植被高度、植被盖度、距水塘距离、地表温度、地表湿度)上的生态位宽度.结果表明,岷山蟾蜍成体在牧场性质、牛粪数量、植被盖度、地表温度、地表湿度5个维度上的生态位宽度最窄,其亚成体在牧场性质、牛粪数量、植被高度、距水塘距离、地表湿度5个维度上的生态位宽度最宽;倭蛙亚成体在牧场性质、牛粪数量、地表温度、地表湿度4个维度上的生态位宽度最窄,而其成体在牛粪数量、植被高度、植被盖度、距水塘距离4个维度上的生态位宽度最宽;高原林蛙在微气候因子的两个维度上具有较大的生态位宽度值,而在水塘距离维度上的生态位宽度值则很小.当人类活动导致生境变更时,倭蛙的反应最为敏感;比较3种无尾两栖类在不同生长阶段(成体、亚成体)的生态位宽度,发现它们利用资源的策略不同.表3参16     

Causes of habitat divergence in two species of agamid lizards in arid central Australia

The deserts of central Australia contain richer communities of lizards than any other arid regions, with the highest diversity occurring in sand dune habitats dominated by hummock-forming spinifex grasses. To investigate the mechanisms that permit coexistence, we studied two species of coexisting agamid lizards that exhibit striking divergence in their use of habitat in the Simpson Desert of central Australia. Here, the military dragon Ctenophorus isolepis is restricted primarily to sites providing > 30% cover of hard spinifex Triodia basedowii, whereas the central netted dragon C. nuchalis occurs in areas with much sparser (< 10%) cover. We constructed four mechanistic models to explain this pattern and then derived hypotheses to test them. One hypothesis, that competition restricts each species to its preferred habitat, was rejected after dyad encounters in field enclosures failed to elicit any habitat shift or any overt interactions between the species. Our next hypotheses were that each species exhibits preferences for different thermal environments or different prey types and that each selects the habitats that maximize access to them. Both were supported. C. isolepis preferred lower temperatures when active and specialized in eating ants < 5 mm long and selected spinifex-dominated areas where these requirements were met. In contrast, C. nuchalis preferred higher temperatures and a diversity of prey, both of which were available mostly in open areas. Finally, we used plasticine models to test the hypothesis that each species faced lower risk of predation in its selected habitat. This was partly supported, as models of both species were attacked more often in the open than under spinifex cover. The results show that habitat divergence occurs along several, probably covarying, niche axes. We suggest that different levels of spinifex cover provide the template for a broad range of ecological interactions, allowing lizard species to partition biotic and abiotic resources and achieve the extraordinarily high levels of local diversity that are observed.     

Transferability of Species Distribution Models: a Functional Habitat Approach for Two Regionally Threatened Butterflies

Abstract:  Numerous models for predicting species distribution have been developed for conservation purposes. Most of them make use of environmental data (e.g., climate, topography, land use) at a coarse grid resolution (often kilometres). Such approaches are useful for conservation policy issues including reserve-network selection. The efficiency of predictive models for species distribution is usually tested on the area for which they were developed. Although highly interesting from the point of view of conservation efficiency, transferability of such models to independent areas is still under debate. We tested the transferability of habitat-based predictive distribution models for two regionally threatened butterflies, the green hairstreak ( Callophrys rubi ) and the grayling ( Hipparchia semele ), within and among three nature reserves in northeastern Belgium. We built predictive models based on spatially detailed maps of area-wide distribution and density of ecological resources. We used resources directly related to ecological functions (host plants, nectar sources, shelter, microclimate) rather than environmental surrogate variables. We obtained models that performed well with few resource variables. All models were transferable—although to different degrees—among the independent areas within the same broad geographical region. We argue that habitat models based on essential functional resources could transfer better in space than models that use indirect environmental variables. Because functional variables can easily be interpreted and even be directly affected by terrain managers, these models can be useful tools to guide species-adapted reserve management.     

Eigenanalysis of selection ratios from animal radio-tracking data

The development of methods to analyze habitat selection when resources are defined by several categories (e.g., vegetation types) is a topical issue in radio-tracking studies. The White and Garrott statistic, an extension of the widely used test of Neu et al., can be used to determine whether habitat selection is significant. As well, Manly's selection ratio, a particularly useful measure of resource selectivity by resource users, allows detection of the most strongly selected habitat types. However, when both the number of animals and types of habitat are large, the biologist often has to deal with an excessively large number of measures. In this paper we present a new method, the eigenanalysis of selection ratios, that generalizes these two common methods within the framework of eigenanalyses. This method undertakes an additive linear partitioning of the White and Garrott statistic, so that the difference between habitat use and availability is maximized on the first factorial axes. The eigenanalysis of selection ratios is therefore optimal in habitat selection studies. Although we primarily consider the case where the habitat availability is the same for all animals (design II), we also extend this analysis to the case where the habitat availability varies from one animal to another (design III). An application of this method is provided using radio-tracking data collected on 17 squirrels in five habitat types. The results indicate variability in habitat selection, with two groups of animals displaying two patterns of preference. This difference between the two groups is explained by the patch structure of the study area. Because this method is mainly exploratory, and therefore does not rely on any distributional assumption, we recommend its use in studies of habitat selection.     

毛竹混交林主要种群多维生态位特征

应用生态位空间分割法，分别考虑资源利用率与否测定毛竹混交林多维资源空间中主要种群多维生态位宽度及多维生态位重叠，结果表明：考虑资源利用率与否对多维生态位宽度的测定有较大的影响，毛竹混交林中主要种群的多维生态位宽度与物种的生物学特性及竞争力密切相关，同一生境中物种的多维生态位重叠可通过生态位分化而减少竞争，研究毛竹混交林主要种群多维生态位特征对毛竹混交林营造具有指导作用．表8参24．     

Bayesian Small Area Models for Assessing Wildlife Conservation Risk in Patchy Populations

Abstract:  Species conservation risk assessments require accurate, probabilistic, and biologically meaningful maps of population distribution. In patchy populations, the reasons for discontinuities are not often well understood. We tested a novel approach to habitat modeling in which methods of small area estimation were used within a hierarchical Bayesian framework. Amphibian occurrence was modeled with logistic regression that included third-order drainages as hierarchical effects to account for patchy populations. Models including the random drainage effects adequately represented species occurrences in patchy populations of 4 amphibian species in the Oregon Coast Range (U.S.A.). Amphibian surveys from other locations within the same drainage were used to calibrate local drainage-scale effects. Cross-validation showed that prediction errors for calibrated models were 77% to 86% lower than comparable regionally constructed models, depending on species. When calibration data were unavailable, small area and regional models performed similarly, although poorly. Small area estimation models complement wildlife ecology and habitat studies, and can help managers develop a regional picture of the conservation status for relatively rare species.     

The importance of incorporating functional habitats into conservation planning for highly mobile species in dynamic systems

The distribution of mobile species in dynamic systems can vary greatly over time and space. Estimating their population size and geographic range can be problematic and affect the accuracy of conservation assessments. Scarce data on mobile species and the resources they need can also limit the type of analytical approaches available to derive such estimates. We quantified change in availability and use of key ecological resources required for breeding for a critically endangered nomadic habitat specialist, the Swift Parrot (Lathamus discolor). We compared estimates of occupied habitat derived from dynamic presence‐background (i.e., presence‐only data) climatic models with estimates derived from dynamic occupancy models that included a direct measure of food availability. We then compared estimates that incorporate fine‐resolution spatial data on the availability of key ecological resources (i.e., functional habitats) with more common approaches that focus on broader climatic suitability or vegetation cover (due to the absence of fine‐resolution data). The occupancy models produced significantly (P < 0.001) smaller (up to an order of magnitude) and more spatially discrete estimates of the total occupied area than climate‐based models. The spatial location and extent of the total area occupied with the occupancy models was highly variable between years (131 and 1498 km²). Estimates accounting for the area of functional habitats were significantly smaller (2–58% [SD 16]) than estimates based only on the total area occupied. An increase or decrease in the area of one functional habitat (foraging or nesting) did not necessarily correspond to an increase or decrease in the other. Thus, an increase in the extent of occupied area may not equate to improved habitat quality or function. We argue these patterns are typical for mobile resource specialists but often go unnoticed because of limited data over relevant spatial and temporal scales and lack of spatial data on the availability of key resources. Understanding changes in the relative availability of functional habitats is crucial to informing conservation planning and accurately assessing extinction risk for mobile resource specialists.     

Climatic niche divergence or conservatism? Environmental niches and range limits in ecologically similar damselflies

The factors that determine species' range limits are of central interest to biologists. One particularly interesting group comprises odonates (dragonflies and damselflies), which show large differences in secondary sexual traits and respond quickly to climatic factors, but often have minor interspecific niche differences, challenging models of niche-based species coexistence. We quantified the environmental niches at two geographic scales to understand the ecological causes of northern range limits and the coexistence of two congeneric damselflies (Calopteryx splendens and C. virgo). Using environmental niche modeling, we quantified niche divergence first across the whole geographic range in Fennoscandia, and second only in the sympatric part of this range. We found evidence for interspecific divergence along the environmental axes of temperature and precipitation across the northern range in Fennoscandia, suggesting that adaptation to colder and wetter climate might have allowed C. virgo to expand farther north than C. splendens. However, in the sympatric zone in southern Fennoscandia we found only negligible and nonsignificant niche differences. Minor niche differences in sympatry lead to frequent encounters and intense interspecific sexual interactions at the local scale of populations. Nevertheless, niche differences across Fennoscandia suggest that species differences in physiological tolerances limit range expansions northward, and that current and future climate could have large effects on the distributional ranges of these and ecologically similar insects.     

Appreciating Ecological Complexity: Habitat Contours as a Conceptual Landscape Model

Abstract:  Organisms respond to their surroundings at multiple spatial scales, and different organisms respond differently to the same environment. Existing landscape models, such as the "fragmentation model" (or patch-matrix-corridor model) and the "variegation model," can be limited in their ability to explain complex patterns for different species and across multiple scales. An alternative approach is to conceptualize landscapes as overlaid species-specific habitat contour maps. Key characteristics of this approach are that different species may respond differently to the same environmental conditions and at different spatial scales. Although similar approaches are being used in ecological modeling, there is much room for habitat contours as a useful conceptual tool. By providing an alternative view of landscapes, a contour model may stimulate more field investigations stratified on the basis of ecological variables other than human-defined patches and patch boundaries. A conceptual model of habitat contours may also help to communicate ecological complexity to land managers. Finally, by incorporating additional ecological complexity, a conceptual model based on habitat contours may help to bridge the perceived gap between pattern and process in landscape ecology. Habitat contours do not preclude the use of existing landscape models and should be seen as a complementary approach most suited to heterogeneous human-modified landscapes.     

Validating graph-based connectivity models with independent presence–absence and genetic data sets

Habitat connectivity is a key objective of current conservation policies and is commonly modeled by landscape graphs (i.e., sets of habitat patches [nodes] connected by potential dispersal paths [links]). These graphs are often built based on expert opinion or species distribution models (SDMs) and therefore lack empirical validation from data more closely reflecting functional connectivity. Accordingly, we tested whether landscape graphs reflect how habitat connectivity influences gene flow, which is one of the main ecoevolutionary processes. To that purpose, we modeled the habitat network of a forest bird (plumbeous warbler [Setophaga plumbea]) on Guadeloupe with graphs based on expert opinion, Jacobs’ specialization indices, and an SDM. We used genetic data (712 birds from 27 populations) to compute local genetic indices and pairwise genetic distances. Finally, we assessed the relationships between genetic distances or indices and cost distances or connectivity metrics with maximum-likelihood population-effects distance models and Spearman correlations between metrics. Overall, the landscape graphs reliably reflected the influence of connectivity on population genetic structure; validation R² was up to 0.30 and correlation coefficients were up to 0.71. Yet, the relationship among graph ecological relevance, data requirements, and construction and analysis methods was not straightforward because the graph based on the most complex construction method (species distribution modeling) sometimes had less ecological relevance than the others. Cross-validation methods and sensitivity analyzes allowed us to make the advantages and limitations of each construction method spatially explicit. We confirmed the relevance of landscape graphs for conservation modeling but recommend a case-specific consideration of the cost-effectiveness of their construction methods. We hope the replication of independent validation approaches across species and landscapes will strengthen the ecological relevance of connectivity models.     

Assumption‐versus data‐based approaches to summarizing species’ ranges

For conservation decision making, species’ geographic distributions are mapped using various approaches. Some such efforts have downscaled versions of coarse‐resolution extent‐of‐occurrence maps to fine resolutions for conservation planning. We examined the quality of the extent‐of‐occurrence maps as range summaries and the utility of refining those maps into fine‐resolution distributional hypotheses. Extent‐of‐occurrence maps tend to be overly simple, omit many known and well‐documented populations, and likely frequently include many areas not holding populations. Refinement steps involve typological assumptions about habitat preferences and elevational ranges of species, which can introduce substantial error in estimates of species’ true areas of distribution. However, no model‐evaluation steps are taken to assess the predictive ability of these models, so model inaccuracies are not noticed. Whereas range summaries derived by these methods may be useful in coarse‐grained, global‐extent studies, their continued use in on‐the‐ground conservation applications at fine spatial resolutions is not advisable in light of reliance on assumptions, lack of real spatial resolution, and lack of testing. In contrast, data‐driven techniques that integrate primary data on biodiversity occurrence with remotely sensed data that summarize environmental dimensions (i.e., ecological niche modeling or species distribution modeling) offer data‐driven solutions based on a minimum of assumptions that can be evaluated and validated quantitatively to offer a well‐founded, widely accepted method for summarizing species’ distributional patterns for conservation applications.