Niche-based Species Distribution Models Research Articles

Relationships between survival and habitat suitability of semi-aquatic mammals.

Spatial distribution and habitat selection are integral to the study of animal ecology. Habitat selection may optimize the fitness of individuals. Hutchinsonian niche theory posits the fundamental niche of species would support the persistence or growth of populations. Although niche‐based species distribution models (SDMs) and habitat suitability models (HSMs) such as maximum entropy (Maxent) have demonstrated fair to excellent predictive power, few studies have linked the prediction of HSMs to demographic rates. We aimed to test the prediction of Hutchinsonian niche theory that habitat suitability (i.e., likelihood of occurrence) would be positively related to survival of American beaver (Castor canadensis), a North American semi‐aquatic, herbivorous, habitat generalist. We also tested the prediction of ideal free distribution that animal fitness, or its surrogate, is independent of habitat suitability at the equilibrium. We estimated beaver monthly survival probability using the Barker model and radio telemetry data collected in northern Alabama, United States from January 2011 to April 2012. A habitat suitability map was generated with Maxent for the entire study site using landscape variables derived from the 2011 National Land Cover Database (30‐m resolution). We found an inverse relationship between habitat suitability index and beaver survival, contradicting the predictions of niche theory and ideal free distribution. Furthermore, four landscape variables selected by American beaver did not predict survival. The beaver population on our study site has been established for 20 or more years and, subsequently, may be approaching or have reached the carrying capacity. Maxent‐predicted increases in habitat use and subsequent intraspecific competition may have reduced beaver survival. Habitat suitability‐fitness relationships may be complex and, in part, contingent upon local animal abundance. Future studies of mechanistic SDMs incorporating local abundance and demographic rates are needed.

Scale effects on the performance of niche-based models of freshwater fish distributions: Local vs. upstream area influences

Niche-based species distribution models (SDMs) play a central role in studying species response to environmental change. Effective management and conservation plans for freshwater ecosystems require SDMs that accommodate hierarchical catchment ordering and provide clarity on the performance of such models across multiple scales. The scale-dependence components considered here are: (a) environment spatial structure, represented by hierarchical catchment ordering following the Strahler system; (b) analysis grain, that included 1st to 5th order catchments; and (c) response grain, the grain at which species respond most, represented by local and upstream catchment area effects. We used fish occurrence data from the Danube River Basin and various factors representing climate, land cover and anthropogenic pressures. Our results indicate that the choice of response grain – local vs. upstream area effects – and the choice of analysis grain, only marginally influence the performance of SDMs. Upstream effects tend to better predict fish distributions than corresponding local effects for anthropogenic and land cover factors, in particular for species sensitive to pollution. Key predictors and their relative importance are scale and species dependent. Consequently, choosing proper species dependent spatial scales and factors is imperative for effective river rehabilitation measures.

Scale effects on the performance of niche-based models of freshwater fish distributions

Niche-based species distribution models (SDMs) have become an essential tool in conservation and restoration planning. Given the current threats to freshwater biodiversity, it is of fundamental importance to address scale effects on the performance of niche-based SDMs of freshwater species’ distributions. The scale effects are addressed here in the context of hierarchical catchment ordering, considered as counterpart to coarsening grain-size by increasing grid-cell size. We combine fish occurrence data from the Danube River Basin, the hierarchical catchment ordering and multiple environmental factors representing topographic, climatic and anthropogenic effects to model fish occurrence probability across multiple scales. We focus on 1st to 5th order catchments. The spatial scale (hierarchical catchment order) only marginally influences the mean performance of SDMs, however the uncertainty of the estimates increases with scale. Key predictors and their relative importance are scale and species dependent. Our findings have useful implications for choosing proper species dependent spatial scales for river rehabilitation measures, and for conservation planning in areas where fine grain species data are unavailable.

The bad and the super-bad: prioritising the threat of six invasive alien to three imperilled native crayfishes

Multiple species invasions and limited resources for management require prioritisation of deleterious effects of invaders on imperilled native species. This study prioritises the threat of six non-indigenous crayfish species (NICS) to three indigenous crayfish species (ICS) in southwestern Germany, a European region with high diversity of crayfish species and freshwater habitats. Using multivariate statistical analyses and niche-based species distribution models, the (1) contemporary and potential range overlap, (2) habitat overlap, and (3) rate of spread of the nine species were assessed. Predicted and contemporary range overlap with ICS was consistently the highest for the alien signal crayfish. Environmental niches of ICS tended to be associated with cooler temperatures (except for white-clawed crayfish), lower Human Influence Index, and higher terrain slope than that of alien Orconectes and Procambarus species, but were mostly similar to that of signal crayfish. Habitat overlap was found to be the highest between signal crayfish and ICS. In contrast to Orconectes and Procambarus species, signal crayfish also invade headwaters, where the most ICS populations occur. Range expansion during the past 15 years was the highest for signal crayfish, followed by Orconectes species. Because of the great potential to invade as-yet isolated refuge areas and spread at a high rate, signal crayfish is of the highest concern for conservation of ICS and should be primarily targeted by prevention and control measures. However, it merely represents the ‘worst of the worst’, since all NICS of North American origin are natural reservoirs of crayfish plague, a fatal disease of ICS.

Imprints of multiple glacial refugia in the Pyrenees revealed by phylogeography and palaeodistribution modelling of an endemic spider.

Mediterranean mountain ranges harbour highly endemic biota in islandlike habitats. Their topographic diversity offered the opportunity for mountain species to persist in refugial areas during episodes of major climatic change. We investigate the role of Quaternary climatic oscillations in shaping the demographic history and distribution ranges in the spider Harpactocrates ravastellus, endemic to the Pyrenees. Gene trees and multispecies coalescent analyses on mitochondrial and nuclear DNA sequences unveiled two distinct lineages with a hybrid zone around the northwestern area of the Catalan Pyrenees. The lineages were further supported by morphological differences. Climatic niche-based species distribution models (SDMs) identified two lowland refugia at the western and eastern extremes of the mountain range, which would suggest secondary contact following postglacial expansion of populations from both refugia. Neutrality test and approximate Bayesian computation (ABC) analyses indicated that several local populations underwent severe bottlenecks followed by population expansions, which in combination with the deep population differentiation provided evidence for population survival during glacial periods in microrefugia across the mountain range, in addition to the main Atlantic and Mediterranean (western and eastern) refugia. This study sheds light on the complexities of Quaternary climatic oscillations in building up genetic diversity and local endemicity in the southern Europe mountain ranges.

Predicting spatio-temporal Culicoides imicola distributions in Spain based on environmental habitat characteristics and species dispersal

The use of distance variables expressing the likelihood of species occurrence at a given site in relation to the distance to observed species presence is demonstrated to improve species distribution models, especially when combined with environmental variables which relate species occurrence to the environmental habitat characteristics. In this study we developed models to predict the spatio-temporal distribution of Culicoides imicola, which is the main transmission vector for the bluetongue virus in the Mediterranean region. We investigated (i) the importance of the environmental habitat characterization by means of bioclimatic variables, (ii) the effect of different distance variables to model the dispersal process, and (iii) the suitability of two different parameter identification procedures to determine the distance variables for species distribution modeling. Results showed that niche-based species distribution models, which only use environmental data, could estimate the occurrence of Culicoides imicola accurately, given that environmental data of the period of high species abundance (April until October) was included. The use of these models may therefore be hampered for predictive risk assessment aiming to estimate the probabilities and magnitude of undesired effects caused by the occurrence of C. imicola. Species distribution models accounting for species dispersal in addition to the environmental habitat characteristics, i.e. hybrid models, did provide accurate predictions of C. imicola distributions well before the onset of the season of high species abundance. A Gaussian or negative exponential function of the distance to presence locations was most suitable to model insect dispersal. The enhanced predictive capacity of these models potentially leads towards an increased model applicability in risk assessment and disease control.

Links between plant species' spatial and temporal responses to a warming climate.

To generate realistic projections of species' responses to climate change, we need to understand the factors that limit their ability to respond. Although climatic niche conservatism, the maintenance of a species's climatic niche over time, is a critical assumption in niche-based species distribution models, little is known about how universal it is and how it operates. In particular, few studies have tested the role of climatic niche conservatism via phenological changes in explaining the reported wide variance in the extent of range shifts among species. Using historical records of the phenology and spatial distribution of British plants under a warming climate, we revealed that: (i) perennial species, as well as those with weaker or lagged phenological responses to temperature, experienced a greater increase in temperature during flowering (i.e. failed to maintain climatic niche via phenological changes); (ii) species that failed to maintain climatic niche via phenological changes showed greater northward range shifts; and (iii) there was a complementary relationship between the levels of climatic niche conservatism via phenological changes and range shifts. These results indicate that even species with high climatic niche conservatism might not show range shifts as instead they track warming temperatures during flowering by advancing their phenology.

Climate change and fire effects on a prairie-woodland ecotone: projecting species range shifts with a dynamic global vegetation model.

Large shifts in species ranges have been predicted under future climate scenarios based primarily on niche-based species distribution models. However, the mechanisms that would cause such shifts are uncertain. Natural and anthropogenic fires have shaped the distributions of many plant species, but their effects have seldom been included in future projections of species ranges. Here, we examine how the combination of climate and fire influence historical and future distributions of the ponderosa pine–prairie ecotone at the edge of the Black Hills in South Dakota, USA, as simulated by MC1, a dynamic global vegetation model that includes the effects of fire, climate, and atmospheric CO2 concentration on vegetation dynamics. For this purpose, we parameterized MC1 for ponderosa pine in the Black Hills, designating the revised model as MC1-WCNP. Results show that fire frequency, as affected by humidity and temperature, is central to the simulation of historical prairies in the warmer lowlands versus woodlands in the cooler, moister highlands. Based on three downscaled general circulation model climate projections for the 21st century, we simulate greater frequencies of natural fire throughout the area due to substantial warming and, for two of the climate projections, lower relative humidity. However, established ponderosa pine forests are relatively fire resistant, and areas that were initially wooded remained so over the 21st century for most of our future climate x fire management scenarios. This result contrasts with projections for ponderosa pine based on climatic niches, which suggest that its suitable habitat in the Black Hills will be greatly diminished by the middle of the 21st century. We hypothesize that the differences between the future predictions from these two approaches are due in part to the inclusion of fire effects in MC1, and we highlight the importance of accounting for fire as managed by humans in assessing both historical species distributions and future climate change effects.

Niche-based prediction of establishment of biocontrol agents: an example with Gratiana boliviana and tropical soda apple

Successful establishment of a biological control agent is a prerequisite for effective reduction of an invasive weed. Niche-based species distribution models can generate valuable information about the potential spread of a biological control agent and help to predict its distribution. The Maximum Entropy Species Distribution Model was used in our study to predict distributions of the leaf beetle Gratiana boliviana Spaeth (Coleoptera: Chrysomelidae) and its target weed, tropical soda apple (TSA), Solanum viarum Dunal (Solanaceae). The specific objectives of this study were to (1) assess the climatic suitability for establishment of this insect across the invasive range of the weed by overlapping predicted current distributions and, (2) examine the niche-related restriction in distribution of the insect by visualising the predictive niche in multivariate space. Accuracy of predicted distributions was tested using binomial tests and area under the curve scores. The results of statistical tests confirmed that the predictions were significantly better than random. The predictions indicated that the potential distribution of G. boliviana in the USA will be more restricted than that of its host plant. Consequently, the beetle's ability to inflict damage to TSA will be geographically limited. Niche visualisation, using a PCA-based analysis, provided evidence of the niche imposed restriction on the distribution of G. boliviana. Overall, this study proposes a new approach for understanding the spatial limitations in establishment of biological control agents, allowing researchers to establish more realistic expectations of success.

Forest Composition: More Altered by Future Climate Change than by Euro-American Settlement in Western New York and Pennsylvania?

The amount of forest compositional change that occurred due to Euro-American settlement over the past two centuries is compared with changes simulated to occur in the future under 2X and 3.5X atmospheric CO2 scenarios. The comparison employs data from presettlement land survey records, modern forest inventory data, and future predictions from niche-based species distribution models. Comparisons are made in four independent study areas in western Pennsylvania and New York. Forest compositional changes in the recent past, attributed largely to anthropogenic factors other than climate change, are intermediate in size to changes predicted to occur as the result of climate change under the 2X CO2 and 3.5X CO2 scenarios. Results are similar across the four study areas, and are robust to variations in data collection and compilation methods. These results disagree with previous pollen-based estimates that suggested a greater relative influence of a 2X CO2 climate change, but do indicate that a 3.5X CO2 climate change may cause greater changes in forest composition than has already occurred due to anthropogenic impacts.

Patch configuration affects alpine plant distribution

The relative importance of niche requirements and dispersal limitation in controlling the landscape-scale distribution of plants is still contentious. Local occurrence and abundance of alpine plants are commonly thought to be driven by abiotic site conditions due to pronounced environmental gradients over short distances. However, explicit tests of the additional role of dispersal-related processes for alpine plant distribution patterns are lacking. Here, we combine niche-based species distribution models with variables describing patch size and connectivity to evaluate if, besides abiotic limitations, spatial habitat configuration affects the occurrence and abundance of six plant species inhabiting patchy snowbed mosaics of the northeastern Calcareous Alps in Austria. Moreover, we assess if eventual effects of spatial patch configuration are more clearly detectable when calculating connectivity based on parameterized mechanistic dispersal kernels for both wind and animal vectors instead of using nearest neighbour metrics. We show that patch size and connectivity are significantly correlated to the occurrence of all and to the abundance of four out of six study species, although the relative importance of these variables, as compared to niche constraints, varies among species. In addition, connectivity measures derived from parameterized dispersal kernels were more closely related to occupancy, and in particular to abundance patterns than a simple nearest neighbour metric. The fitted kernels also suggest that dispersal by alpine chamois plays an important role for inter-patch seed exchange. We conclude that, despite evident abiotic limitations, recurrent local extinctions and delayed re-colonizations indeed play a role for the distribution of our study species, and that alpine plants may hence be less in equilibrium with their abiotic environment than commonly thought. Moreover, the relatively high long-distance dispersal probabilities of animal kernels indicate that the ability of alpine plants to adapt their ranges to a rapidly warming climate may, among other factors, depend on the availability of dispersal services by large mammals.

Niche based distribution modelling of an invasive alien plant: effects of population status, propagule pressure and invasion history

Forecasting the spatial spread of invasive species is important to inform management planning. Niche-based species distribution models offer a well-developed framework for assessing the potential range of species. However, these models assume equilibrium between the species’ distribution and its ecological requirements. During range expansion, invasive species are not in such equilibrium due to both dispersal limitation and frequent casual occurrence in sites unsuitable to persistent populations. In this article we use the example of the invasive annual plant Ambrosia artemisiifolia in Austria to evaluate if model accuracy can be enhanced in such non-equilibrium situations by taking account of propagule pressure and by restricting model calibration to naturalized populations. Moreover, we test if model accuracy increases during invasion history using distribution data from 1984 to 2005. The results suggest that models calibrated with naturalized populations are much more accurate than those based on the total set of records. Proxies of propagule pressure slightly but significantly improve goodness of fit, accuracy, and Type I and II error rates of models calibrated with all available records but have less consistent effects on models of naturalized populations. Model accuracy did not increase during the recent invasion history, probably because the species is still far from an equilibrium distribution. We conclude that even a coarse assessment of population status with records of invasive species delivers important information for predictive modelling and that proxies of propagule pressure should be included into such models at least during early to intermediate stages of the invasion history.