Ensemble modeling of the potential distribution of the whale shark in the Atlantic Ocean

The whale shark (Rhincodon typus) is an endangered marine fish species which can be adversely affected by the fishing activities of the industrial purse seine fleet targeting tropical tuna. Tuna tend to aggregate around all types of floating objects, including whale sharks. We analyzed and modeled the spatial distribution and environmental preferences of whale sharks based on the presence and absence data from fishing observations in the Atlantic Ocean. We used a thorough multialgorithm analysis, based on a new presence–absence dataset, and endeavored to follow the most recent recommendations on best practices in species distribution modeling. First, we selected a subset of relevant variables using a generalized linear model that addressed multicollinearity, statistical errors, and information criteria. We then used the selected variables to build a model ensemble including 19 different algorithms. After eliminating models with insufficient performance, we assessed the potential distribution of whale sharks using the mean of the predictions of the selected models. We also assessed the variance among the predictions of different algorithms, in order to identify areas with the highest model consensus. The results show that several coastal regions and warm shallow currents, such as the Gulf Stream and the Canary and Benguela currents, are the most suitable areas for whale sharks under current environmental conditions. Future environmental projections for the Atlantic Ocean suggest that some of the suitable regions will shift northward, but current concentration areas will continue to be suitable for whale shark, although with less productivity, which could have negative consequences for conservation of the species. We discuss the implications of these predictions for the conservation and management of this charismatic marine species.     

Fauna habitat modelling and mapping: A review and case study in the Lower Hunter Central Coast region of NSW

Abstract Habitat models are now broadly used in conservation planning on public lands. If implemented correctly, habitat modelling is a transparent and repeatable technique for describing and mapping biodiversity values, and its application in peri‐urban and agricultural landscape planning is likely to expand rapidly. Conservation planning in such landscapes must be robust to the scrutiny that arises when biodiversity constraints are placed on developers and private landholders. A standardized modelling and model evaluation method based on widely accepted techniques will improve the robustness of conservation plans. We review current habitat modelling and model evaluation methods and provide a habitat modelling case study in the New South Wales central coast region that we hope will serve as a methodological template for conservation planners. We make recommendations on modelling methods that are appropriate when presence‐absence and presence‐only survey data are available and provide methodological details and a website with data and training material for modellers. Our aim is to provide practical guidelines that preserve methodological rigour and result in defendable habitat models and maps. The case study was undertaken in a rapidly developing area with substantial biodiversity values under urbanization pressure. Habitat maps for seven priority fauna species were developed using logistic regression models of species‐habitat relationships and a bootstrapping methodology was used to evaluate model predictions. The modelled species were the koala, tiger quoll, squirrel glider, yellow‐bellied glider, masked owl, powerful owl and sooty owl. Models ranked sites adequately in terms of habitat suitability and provided predictions of sufficient reliability for the purpose of identifying preliminary conservation priority areas. However, they are subject to multiple uncertainties and should not be viewed as a completely accurate representation of the distribution of species habitat. We recommend the use of model prediction in an adaptive framework whereby models are iteratively updated and refined as new data become available.     

Habitat selection by a threatened desert amphibian

Habitat degradation and fragmentation are major drivers of amphibian declines. The loss of environmental features that allow for movement between water sources may be particularly detrimental for amphibians in arid environments. Climate changes will increase the importance of microhabitats to amphibians. Enhancing areas to facilitate movement may be a necessary conservation strategy for many animal species that depend on wetlands, including federally threatened Chiricahua leopard frogs (Lithobates chiricahuensis). Habitat preferences of this frog species are not well understood. We sought to better understand fine‐scale habitat selection, to inform conservation of Chiricahua leopard frogs. We conducted our study on the Ladder Ranch, a privately owned working bison ranch in New Mexico, USA that supports a large proportion of the remaining Chiricahua leopard frogs in the state. We attached radio transmitters to 44 frogs during summer 2014. We located each frog daily for up to 8 weeks (median = 30 days). We assessed fine‐scale habitat selection by comparing characteristics at each frog location and a random location 5 m away using conditional logistic regression. Frogs preferred features that likely reduce desiccation, even after accounting for the presence of water. Frogs selected areas with more low‐lying cover, especially aquatic vegetation and woody debris, a tree overstory, and a mud substrate. We recommend managing potential movement corridors for Chiricahua leopard frogs by ensuring the presence of muddy creek bottoms, woody debris, riparian overstory, low‐lying ground cover, and pools. Microclimates created by these features seem especially valuable given warming temperatures and modified precipitation regimes, resulting in decreased surface water, soil moisture, and vegetation cover. Retaining or creating preferred habitat features and microclimates in areas between water sources may increase connectivity among isolated populations of Chiricahua leopard frogs and could improve persistence and recovery of other water‐obligate species in arid landscapes.     

Modelling the spatial distribution of White Stork Ciconia ciconia breeding populations in Southeast Europe

Capsule Spatial environmental modelling well predicted nesting distribution of the White stork in Southeast Europe and can be used in conservation planning with respect to climate change.

Aims To create spatial models for predicting White Stork presence and densities in the Southeast Europe to identify areas of suitable habitat for White Storks.

Methods We quantified the habitat used by nesting White storks in Southeast Europe. Using spatial modelling, we defined a set of free and available online environmental variables that predict the breeding localities of the species. We employed pseudo-absences and the kriging of the residuals in order to create predictive models of nest presence and density.

Results The presence–absence model was found to be precise in predicting the presence of nests. Both density and presence of breeding pairs were best explained negatively by elevation, slope, minimum temperature during May, and distance to the nearest human settlement and positively by topographic wetness index, total area of human settlement and spring precipitation.

Conclusion Our robust and easily repeatable models offer a conservation tool to reveal suitable but unoccupied localities for breeding White Storks pairs which may inform our understanding of how climate change might affect the species' distribution in the future. For example, protecting White Storks on the Dalmatian coast may become even more significant in the future, because the Dalmatian coast is predicted as the only suitable breeding area in Croatia later this century.     

Response of the endangered tropical dry forests to climate change and the role of Mexican Protected Areas for their conservation

Assuming that co‐distributed species are exposed to similar environmental conditions, ecological niche models (ENMs) of bird and plant species inhabiting tropical dry forests (TDFs) in Mexico were developed to evaluate future projections of their distribution for the years 2050 and 2070. We used ENM‐based predictions and climatic data for two Global Climate Models, considering two Representative Concentration Pathway scenarios (RCP4.5/RCP8.5). We also evaluated the effects of habitat loss and the importance of the Mexican system of protected areas (PAs) on the projected models for a more detailed prediction of TDFs and to identify hot spots that require conservation actions. We identified four major distributional areas: the main one located along the Pacific Coast (from Sonora to Chiapas, including the Cape and Bajío regions, and the Balsas river basin), and three isolated areas: the Yucatán peninsula, central Veracruz, and southern Tamaulipas. When considering the effect of habitat loss, a significant reduction (~61%) of the TDFs predicted area occurred, whereas climate‐change models suggested (in comparison with the present distribution model) an increase in area of 3.0–10.0% and 3.0–9.0% for 2050 and 2070, respectively. In future scenarios, TDFs will occupy areas above its current average elevational distribution that are outside of its present geographical range. Our findings show that TDFs may persist in Mexican territory until the middle of the XXI century; however, the challenges about long‐term conservation are partially addressed (only 7% unaffected within the Mexican network of PAs) with the current Mexican PAs network. Based on our ENM approach, we suggest that a combination of models of species inhabiting present TDFs and taking into account change scenarios represent an invaluable tool to create new PAs and ecological corridors, as a response to the increasing levels of habitat destruction and the effects of climate change on this ecosystem.     

Where are the survivors? Tracking relictual populations of endangered frogs in Costa Rica

Aim We used abiotic environmental variables and historical locality records to infer distributions of endangered anuran species of Costa Rica to promote efficient strategies for future amphibian surveys. Location Costa Rica. Methods We used a Maximum Entropy Algorithm (Maxent) to predict potential distribution maps for 17 species of endangered anurans and create a consensus map of species richness. We compared the environmental conditions from localities where relictual amphibian populations were recently rediscovered with the conditions across their historical range to evaluate the possibility that these relictual populations might occur in specific climatic conditions that could explain their persistence. We used a multicriteria analysis considering the following factors: the intersection zones between the consensus map, conservation areas, potential Batrachochytrium dendrobatidis (Bd) distribution, collecting effort and areas within the precipitation range at which reappearances had occurred to locate sites for future surveys. Results The resulting predictions suggest that suitable areas for the highest number of species occur between 1300 and 2500 m.a.s.l and are concentrated along the Pacific slopes of the Cordillera de Talamanca and Cordillera Volcánica Central. Around 45% of the high potential richness area is under protection. Relictual populations of declined species seem to persist mainly in highly humid localities (2500–3500 mm of mean annual precipitation). Around 240 km² has an ideal environment for the rediscovery of relictual populations. The multicriteria analysis showed that around 0.5% of the Costa Rican territory should be surveyed exhaustively for frogs. Main conclusions Many of the potential refugia we identified here have not been surveyed since 2000, the areas identified by the best model predictions correspond well with the localities of the relictual populations recently reported. We suggest future surveys of missing amphibian species should focus on these areas. The discovery of populations of endangered species can be used to propose conservation areas.     

Altitudinal distribution of chytrid (Batrachochytrium dendrobatidis) infection in subtropical Australian frogs

The disappearance of amphibian populations from seemingly pristine upland areas worldwide has become a major focus of conservation efforts in the last two decades, and a parasitic chytrid fungus, Batrachochytrium dendrobatidis, is thought to be the causative agent of the population declines. We examined the altitudinal distribution of chytrid infections in three stream‐dwelling frog species (Litoria wilcoxii, L. pearsoniana and L. chloris) in southeast Queensland, Australia, and hypothesized that if B. dendrobatidis were responsible for the disappearance of high‐altitude frog populations, infection prevalence and intensity would be greatest at higher altitudes. Overall, 37.7% of the 798 adult frogs we sampled were infected with B. dendrobatidis, and infections were found in all the populations we examined. Contrary to our initial hypothesis, we found no consistent evidence that high‐altitude frogs were more likely to be infected than were lowland frogs. Further, the intensity of fungal infections (number of zoospores) on high‐altitude frogs did not differ significantly from that of lowland frogs. Batrachochytrium dendrobatidis appears to be capable of infecting frogs at all altitudes in the subtropics, suggesting that all populations are at risk of decline when conditions favour disease outbreaks. We did find evidence, however, that chytrid infections persist longer into summer in upland as compared with lowland areas, suggesting that montane amphibian populations remain susceptible to disease outbreaks for longer periods than do lowland populations. Further, we found that at high altitudes, temperatures optimal for chytrid growth and reproduction coincide with frog metamorphosis, the life‐stage at which frogs are most susceptible to chytrid infections. While these altitudinal differences may account for the differential population‐level responses to the presence of B. dendrobatidis, the reason why many of southeast Queensland's montane frog populations declined precipitously while lowland populations remained stable has yet to be resolved.     

Impacts of climate change and urban development on the spotted marsh frog (Limnodynastes tasmaniensis)

Climate change and urbanization are among the most serious threats to amphibians, although little is known about their combined effects. We used a predictive spatial habitat suitability model to explore the potential impacts of climate change and urban development on the spotted marsh frog (Limnodynastes tasmaniensis) on the urban‐fringe of Melbourne, Australia. The CSIRO climate‐change predictions for the region indicate likely temperature increases of 3°C, and annual rainfall reductions of around 200 mm by the year 2070. Much of the study area overlaps a region that has been identified as one of the city's growth corridors. We used Bayesian logistic regression modelling to estimate current and future habitat suitability of pond sites in the Merri Creek catchment, exploring a range of best‐ to worst‐case scenarios through the use of hydrological and urbanization models. Our predictions for 2070, even under a moderate climate‐change scenario, suggest that the majority of ponds in the study area will be dry throughout much of the year. This has obvious implications for L. tasmaniensis, which is an aquatic breeding species. However, in the short term, urbanization is likely to have a more significant effect on the distribution of L. tasmaniensis in the Merri Creek catchment, particularly if development moves beyond the current urban growth boundary. The combined effects of climate change and urbanization could have a profound impact on the species, potentially causing it to disappear from within the study area. We provide recommendations for including such predictive models in urban planning and restoration activities to prepare for future conservation challenges.     

The effect of aquatic and terrestrial habitat characteristics on occurrence and breeding probability in a montane amphibian: insights from a spatially explicit multistate occupancy model

Understanding species distribution and predicting range shifts are major goals of ecology and biogeography. Obtaining reliable predictions of how species distribution might change in response to habitat change requires knowledge of habitat availability, occupancy, use for breeding, and spatial autocorrelation in these parameters. Amphibians in alpine areas provide an excellent model system for disentangling habitat drivers of occupancy from that of breeding while explicitly accounting for spatial autocorrelation. We focused on the widespread common frog (Rana temporaria) inhabiting alpine lakes in the Southern Carpathians, Romania. We used single season multistate occupancy models developed to account for imperfect detection and spatial autocorrelation to estimate the occupancy and breeding probabilities and to evaluate their response to habitat characteristics. We found that frogs do not occur in all water bodies [occupancy probability: 0.697; 95% credible interval (0.614, 0.729)] and do not breed in a substantial proportion of water bodies where they occur [breeding probability conditional on occupancy: 0.707; 95% credible interval (0.670, 0.729)]. Habitat characteristics explain water body occupancy but not breeding probability; and altitude, water body surface area, water body sinuosity and permanency, presence of invertebrates, and grazing along the banks all had positive effects on occupancy. We also detected strong spatial autocorrelation in occupancy and breeding probabilities. Thus, our results indicate that habitat choice by montane amphibians is influenced by both spatial autocorrelation and habitat characteristics. Because spatial autocorrelations matter and because the presence of adults is not the same as the presence of a reproducing population, it will be difficult to predict the effects of habitat change on high altitude amphibian populations.     

An evaluation of four threshold selection methods in species occurrence modelling with random forest: Case studies with Davidia involucrata and Cunninghamia lanceolata

Aims Predictive species distribution models (SDMs) are increasingly applied in resource assessment, environmental conservation and biodiversity management. However, most SDM models often yield a predicted probability (suitability) surface map. In conservation and environmental management practices, the information presented as species presence/absence (binary) may be more practical than presented as probability or suitability. Therefore, a threshold is needed to transform the probability or suitability data to presence/absence data. However, little is known about the effects of different threshold-selection methods on model performance and species range changes induced by future climate. Of the numerous SDM models, random forest (RF) can produce probabilistic and binary species distribution maps based on its regression and classification algorisms, respectively. Studies dealing with the comparative test of the performances of RF regression and classification algorisms have not been reported.
Methods Here, the RF was used to simulate the current and project the future potential distributions of Davidia involucrata and Cunninghamia lanceolata. Then, four threshold-setting methods (Default 0.5, MaxKappa, MaxTSS and MaxACC) were selected and used to transform modelled probabilities of occurrence into binary predictions of species presence and absence. Lastly, we investigated the difference in model performance among the threshold selection methods by using five model accuracy measures (Kappa, TSS, Overall accuracy, Sensitivity and Specificity). We also used the map similarity measure, Kappa, for a cell-by-cell comparison of similarities and differences of distribution map under current and future climates.
Important findings We found that the choice of threshold method altered estimates of model performance, species habitat suitable area and species range shifts under future climate. The difference in selected threshold cut-offs among the four threshold methods was significant for D. involucrata, but was not significant for C. lanceolata. Species’ geographic ranges changed (area change and shifting distance) in response to climate change, but the projections of the four threshold methods did not differ significantly with respect to how much or in which direction, but they did differ against RF classification predictions. The pairwise similarity analysis of binary maps indicated that spatial correspondence among prediction maps was the highest between the MaxKappa and the MaxTSS, and lowest between RF classification algorism and the four threshold-setting methods. We argue that the MaxTSS and the MaxKappa are promising methods for threshold selection when RF regression algorism is used for the distribution modeling of species. This study also provides promising insights to our understanding of the uncertainty of threshold selection in species distribution modeling.     

The chytrid fungus Batrachochytrium dendrobatidis is non-randomly distributed across amphibian breeding habitats

The chytrid fungus Batrachochytrium dendrobatidis has been implicated as the causative agent of mass mortalities, population declines, and the extinctions of stream-breeding amphibian species worldwide. While the factors that limit the distribution and abundance of B. dendrobatidis across large geographical regions are fairly well understood, little is known about the distribution of the fungus within localized areas such as individual catchments. The accurate identification of amphibian populations likely to be exposed to the fungus is urgently required for effective disease management. We conducted disease surveys of frogs representing five ecological guilds in south-east Queensland, Australia, and hypothesized that if B. dendrobatidis were responsible for the disappearance of stream-breeding amphibian populations, infection prevalence and intensity would be greatest in frogs breeding in permanent, flowing water. Overall, 30.3% of the 519 frogs we sampled were infected with B. dendrobatidis . However, infections were not evenly distributed across the ecological guilds, being almost completely restricted to frogs breeding at permanent waterbodies. Of these, stream breeders were significantly more likely to be infected than were pond breeders, though the intensity of frogs' infections did not differ significantly between the two guilds. Batrachochytrium dendrobatidis was detected on only one of the 117 frogs that were found at ephemeral ponds, ephemeral streams, or terrestrial sites. These findings provide strong support for the hypothesis that B. dendrobatidis was responsible for many of the unexplained disappearances of stream-breeding amphibian populations in recent decades, and will enable wildlife managers to more accurately focus conservation efforts on those species at highest risk of disease-related decline.     

Synergistic effects of climate and land-use change on representation of African bats in priority conservation areas

Bats are considered important bioindicators and deliver key ecosystem services to humans. However, it is not clear how the individual and combined effects of climate change and land-use change will affect their conservation in the future. We used a spatial conservation prioritization framework to determine future shifts in the priority areas for the conservation of 169 bat species under projected climate and land-use change scenarios across Africa. Specifically, we modelled species distribution models under four different climate change scenarios at the 2050 horizon. We used land-use change scenarios within the spatial conservation prioritization framework to assess habitat quality in areas where bats may shift their distributions. Overall, bats’ representation within already existing protected areas in Africa was low (∼5% of their suitable habitat in protected areas which cover ∼7% of Africa). Accounting for future land-use change resulted in the largest shift in spatial priority areas for conservation actions, and species representation within priority areas for conservation actions decreased by ∼9%. A large proportion of spatial conservation priorities will shift from forested areas with little disturbance under present conditions to agricultural areas in the future. Planning land use to reduce impacts on bats in priority areas outside protected areas where bats will be shifting their ranges in the future is crucial to enhance their conservation and maintain the important ecosystem services they provide to humans.     

Living quarters of a living fossil—Uncovering the current distribution pattern of the rediscovered Hula painted frog (Latonia nigriventer) using environmental DNA

One of the greatest challenges of effective conservation measures is the correct identification of sites where rare and elusive organisms reside. The recently rediscovered Hula painted frog (Latonia nigriventer) has not been seen for many decades and was therefore categorized extinct. Since its rediscovery in 2011, individuals from the critically endangered species have been found, with great effort, only in four restricted sites. We applied the environmental DNA (eDNA) approach to search for new populations of the Hula painted frog in suitable aquatic habitats. We further used the eDNA data to classify the landscape factors associated with the species distribution and to predict its suitable habitats. We sampled 52 aquatic sites in the Hula Valley during the spring of 2015 and 2016 and amplified the samples with a species‐specific qPCR assay. DNA of the Hula painted frog was detected in 22 of the sites, all of which clustered within three main areas. A boosting classification model showed that soil type, vegetation cover and the current and former habitats are all key predictors of the frog's current distribution. Intriguingly, the habitat suitability models reveal a high affinity of the species to its long‐lost habitat of the historical wetlands. Our findings encourage a series of informed searches for new populations of this threatened frog and provide guidance for future conservation management programmes. In the era of global conservation crisis of amphibians, developing the eDNA approach, a reliable detection method for many critically endangered and elusive amphibians, is of particular importance.     

Nesting habitat preference of the African White-backed Vulture Gyps africanus and the effects of anthropogenic disturbance

The African White-backed Vulture Gyps africanus is widely distributed across sub-Saharan Africa but populations are in decline. Loss of suitable habitat for foraging and breeding are among the most important causes, and future conservation will require identification of suitable remaining habitat and the threats to it and to the vultures in it. Like many large raptors, African White-backed Vultures have a long breeding cycle and thus spend much of each year near their nest site, but ecological correlates of nest sites have not been quantified for any African vulture species. We use nest-site data for African White-backed Vultures collected during aerial and ground surveys and habitat data derived from a GIS to develop statistical models that estimate the probability of nest presence in relation to habitat characteristics, and test these models against an independent dataset. The models predicted that both direct and indirect disturbance by humans limit the potential distribution. Suitable habitat needs to be identified and receive adequate protection from poaching. Poaching of vultures is thought to be mainly for use in traditional medicine and does not target any particular species, so all vulture species can be considered equally at risk. We predict the likelihood of individuals nesting in currently unprotected areas should they become protected. These predictions show that readily available GIS data combined with relatively simple statistical modelling can provide meaningful large-scale predictions of habitat availability.     

Distribution models for the amphibian chytrid Batrachochytrium dendrobatidis in Costa Rica: proposing climatic refuges as a conservation tool

Aim We use novel data on the occurrence of the amphibian chytrid fungus Batrachochytrium dendrobatidis in Costa Rica to model its potential distribution in that country. Location Lowland and montane areas of Costa Rica. Methods We use published and new data on the presence of B. dendrobatidis on 647 amphibians (35 species). Screening was performed through histological techniques by which 156 sites were surveyed. Of these, 21 were found to have the amphibian chytrid. Maxent, a presence‐only distribution modelling technique, was used to create 100 predictions of B. dendrobatidis occurrence, of which the most accurate 10 (based on area under the receiver‐operating characteristic curve) were chosen to create a composite distribution model. This approach increased confidence in model predictions, distinguishing areas of high probability of occurrence and low variability across model runs (higher confidence) from those with high probability but high variability (lower confidence). Results Predicted distribution patterns were not uniform along Costa Rica's mountains, where most amphibian declines have occurred. The pathogen was predicted to occur with greater probability on the Caribbean slopes than on the Pacific slopes. While high temperature seems to constrain the distribution of the pathogen, areas that also have small amounts of rainfall during the driest period of the year were predicted to have low probability of B. dendrobatidis occurrence. Main conclusions The model predicts that the Santa Elena Peninsula and the Central Valley have low probabilities of B. dendrobatidis occurrence, suggesting that they could function as refuges for amphibians. In such refugial areas, one could expect B. dendrobatidis to be absent, or to be present in low abundance (rendering an epidemic outbreak of chytridiomycosis unlikely). Craugastor ranoides, which belongs to a group of frogs particularly sensitive to chytridiomycosis outbreaks, persists in the hot and seasonally dry Santa Elena Peninsula but disappeared in the nearby colder and more humid Guanacaste Volcanic Chain. This information suggests that climatic refuges, where environmental conditions prevent disease outbreaks, could be an important component in amphibian conservation.     

Macroecology and extinction risk correlates of frogs

Aim  Our aim was to test whether extinction risk of frog species could be predicted from their body size, fecundity or geographical range size. Because small geographical range size is a correlate of extinction risk in many taxa, we also tested hypotheses about correlates of range size in frogs.
Location  Global.
Methods  Using a large comparative data set ( n  = 527 species) compiled from the literature, we performed bivariate and multiple regressions through the origin of independent contrasts to test proposed macroecological patterns and correlates of extinction risk in frogs. We also created minimum adequate models to predict snout–vent length, clutch size, geographical range size and IUCN Red List status in frogs. Parallel non-phylogenetic analyses were also conducted. We verified the results of the phylogenetic analyses using gridded data accounting for spatial autocorrelation.
Results  The most threatened frog species tend to have small geographical ranges, although the relationship between range and extinction risk is not linear. In addition, tropical frogs with small clutches have the smallest ranges. Clutch size was strongly positively correlated with geographical range size ( r ² = 0.22) and body size ( r ² = 0.28).
Main conclusions  Our results suggest that body size and fecundity only affect extinction risk indirectly through their effect on geographical range size. Thus, although large frogs with small clutches tend to be endangered, there is no comparative evidence that this relationship is direct. If correct, this inference has consequences for conservation strategy: it would be inefficient to allocate conservation resources on the basis of low fecundity or large body size; instead it would be better to protect areas that contain many frog species with small geographical ranges.     

Conservation of Chinese Theaceae species under future climate and land use changes

Aim

Climate and land use changes are two major pervasive and growing global causes of rapid changes in the distribution patterns of biodiversity, challenging the future effectiveness of protected areas (PAs), which were mainly designed based on a static view of biodiversity. Therefore, evaluating the effectiveness of protected areas for protecting the species threatened by climate and land use change is critical for future biodiversity conservation.

Location

China.

Methods

Here, using distributions of 200 Chinese Theaceae species and ensemble species distribution models, we identified species threatened by future climate and land use change (i.e. species with predicted loss of suitable habitat ≥30%) under scenarios incorporating climate change, land use change and dispersal. We then estimate the richness distribution patterns of threatened species and identify priority conservation areas and conservation gaps of the current PA network.

Results

Our results suggest that 36.30%–51.85% of Theaceae species will be threatened by future climate and land use conditions and that although the threatened species are mainly distributed at low latitudes in China under both current and future periods, the mean richness of the threatened species per grid cell will decline by 0.826–3.188 species by the 2070s. Moreover, we found that these priority conservation areas are highly fragmented and that the current PA network only covers 14.21%–20.87% of the ‘areas worth exploring’ and 6.91%–7.91% of the ‘areas worth attention’.

Main Conclusions

Our findings highlight the necessity of establishing new protected areas and ecological corridors in priority conservation areas to protect the threatened species. Moreover, our findings also highlight the importance of taking into consideration the potential threatened species under future climate and land use conditions when designating priority areas for biodiversity conservation.     

A simple non-parametric GIS model for predicting species distribution: endemic birds in Bioko Island, West Africa

Species mapping is a useful conservation tool for predicting patterns of biological diversity, or identifying geographical areas of conservation significance. Mapping can also improve our understanding of the appropriateness of habitat areas for individual species. We outline a computer-based methodology, PREDICT, for the analysis of the habitat requirements of species in a combined GIS-statistical programming environment. The paper details the statistical background to the approach adopted, the program structure and input file information and then applies these techniques to bird data from Bioko Island, West Africa. It produces images and statistics that assess the potential of unstudied areas for wildlife for which presence/absence data and basic habitat information are available. Suitability for target species is determined within surveyed and non-surveyed squares by a form of weights of evidence. The program measures the degree of association between habitat factors and presence/absence of target species by means of ² tests. The overall suitability weighting of each square, as the sum of all individual habitat factor weightings, is finally displayed in maps depicting areas of highly suitable, suitable, unsuitable and highly unsuitable habitat. Statistical relations between vegetation, rainfall and landscape features on Bioko Island and the location of 9 endemic bird taxa are presented herein. Final confirmation of the accuracy of predictions of the studied bird taxa will ensue from future field observations. However, in a series of misclassification tests of the program, actual distribution detection rate was in excess of 90%. The use of PREDICT can guide investigations of little known species in remote areas and provide a practical solution to identify areas of high rare species diversity in need of conservation.     

Predicting Distribution and Density of European Badger (<Emphasis Type="Italic">Meles Meles</Emphasis>) Setts in Denmark

Predictive models of the spatial distribution and abundance of species based on habitat characteristics are finding increasing use in management and conservation. The European badger attracts interest as a model species both for conservation reasons and because of the important role the species is playing in understanding carnivore sociality. We developed a statistical habitat model based on presence/absence data on badger setts. To maximise the utility of the model in management, we limited the choice of model variables to those that had a clear basis in badger ecology and that could be obtained on a nation-wide digital format. We extrapolated the habitat model to a region in Denmark and developed a threshold-independent sett distribution algorithm to estimate sett densities. The habitat model was simpler than previously published models of badger sett habitat selection, but nevertheless had a predictive ability in excess of 80% judged against independent data. The sett distribution algorithm was able to simultaneously reproduce several observed patterns of sett density and distribution over the probability gradient. It thus represents a significant improvement over threshold-dependent methods used to discriminate between suitable and unsuitable habitat predicted by presence/absence regression models. Our approach demonstrates that a model of badger sett habitat suitability with high predictive power can be obtained using easily accessible map-variables and presence/absence data. This is a prerequisite for using habitat models as predictive tools over large areas. The use of a simple sett distribution algorithm circumvents the common problem of subjectively fixing a threshold to discriminate between suitable and unsuitable habitat. In conjunction the models presented here constitute an important contribution to the management of the badger in Denmark and, upon further validation, possibly to similar regions in Northern Europe.     

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

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