Habitat Suitability Projections Research Articles

Decline in the suitable habitat of dominant Abies species in response to climate change in the Hindu Kush Himalayan region: insights from species distribution modelling.

Reliable predictions of future distribution ranges of ecologically important species in response to climate change are required for developing effective management strategies. Here we used an ensemble modelling approach to predict the distribution of three important species of Abies namely, Abies pindrow, Abies spectabilis and Abies densa in the Hindu Kush Himalayan region under the current and two shared socioeconomic pathways (SSP245 and SSP585) and time periods of 2050 and 2090s. A correlative ensemble model using presence/absence data of the three Abies species and 22 environmental variables, including 19 bioclimatic variables and 3 topographic variables, from known distributions was built to predict the potential current and future distribution of these species. The individual models used to build the final ensemble performed well and provided reliable results for both the current and future distribution of all three species. For A. pindrow, precipitation of the driest month (Bio14) was the most important environmental variable with 83.3% contribution to model output while temperature seasonality (Bio4) and annual mean diurnal range (Bio2) were the most important variables for A. spectabilis and A. densa with 48.4% and 46.1% contribution to final model output, respectively. Under current climatic conditions, the ensemble models projected a total suitable habitat of about 433,003 km2, 790,837 km2 and 676,918 km2 for A. pindrow, A. spectabilis and A. densa, respectively, which is approximately 10.36%, 18.91% and 16.91% of the total area of Hindu Kush Himalayan region. Projections of habitat suitability under future climate scenarios for all the shared socioeconomic pathways showed a reduction in potentially suitable habitats with a maximum overall loss of approximately 14% of the total suitable area of A. pindrow under SSP 8.5 by 2090. A decline in total suitable habitat is predicted to be 9.6% in A. spectabilis by 2090 under the SSP585 scenario while in A. densa 6.67% loss in the suitable area is expected by 2050 under the SSP585 scenario. Furthermore, there is no elevational change predicted in the case of A. pindrow while A. spectabilis is expected to show an upward shift by about 29m per decade and A. densa is showing a downward shift at a rate of 11m per decade. The results are interesting, and intriguing given the occurrence of these species across the Hindu Kush Himalayan region. Thus, our study underscores the need for consideration of unexpected responses of species to climate change and formulation of strategies for better forest management and conservation of important conifer species, such as A. pindrow, A. spectabilis and A. densa.

Integrating physiology into correlative models can alter projections of habitat suitability under climate change for a threatened amphibian

Rapid global change has increased interest in developing ways to identify suitable refugia for species of conservation concern. Correlative and mechanistic species distribution models (SDMs) represent two approaches to generate spatially‐explicit estimates of climate vulnerability. Correlative SDMs generate distributions using statistical associations between environmental variables and species presence data. In contrast, mechanistic SDMs use physiological traits and tolerances to identify areas that meet the conditions required for growth, survival and reproduction. Correlative approaches assume modeled environmental variables influence species distributions directly or indirectly; however, the mechanisms underlying these associations are rarely verified empirically. We compared habitat suitability predictions between a correlative‐only SDM, a mechanistic SDM and a correlative framework that incorporated mechanistic layers (‘hybrid models'). Our comparison focused on green salamanders Aneides aeneus, a priority amphibian threatened by climate change throughout their disjunct range. We developed mechanistic SDMs using experiments to measure the thermal sensitivity of resistance to water loss (ri) and metabolism. Under current climate conditions, correlative‐only, hybrid and mechanistic SDMs predicted similar overlap in habitat suitability; however, mechanistic SDMs predicted habitat suitability to extend into regions without green salamanders but known to harbor many lungless salamanders. Under future warming scenarios, habitat suitability depended on climate scenario and SDM type. Correlative and hybrid models predicted a 42% reduction or 260% increase in area considered to be suitable depending on the climate scenario. In mechanistic SDMs, energetically suitable habitat declined with both climate scenarios and was driven by the thermal sensitivity of ri. Our study indicates that correlative‐only and hybrid approaches produce similar predictions of habitat suitability; however, discrepancies can arise for species that do not occupy their entire fundamental niche, which may hold consequences of conservation planning of threatened species.

Global Patterns of Coastal Cephalopod Diversity Under Climate Change

Coastal marine ecosystems are currently being exposed to climate change at a much faster rate than many other ecosystems, with coastal species being exposed to multiple stressors. Cephalopod mollusks play a pivotal role in marine trophic webs, and most are “keystone” species due to their influence on ecosystem dynamics. In this study, we characterized the global patterns of coastal cephalopod diversity and present, for the first time, a global forecast of potential changes in richness, mean body size, and assemblage composition (i.e., species replacement, nestedness, and combinations of both) for 161 coastal cephalopod species under climate change, using an ensemble of ecological niche models (ENMs) for an end of the century mitigation scenario. We have shown that, for the baseline period, coastal cephalopod diversity is higher in the Central Indo-Pacific area and that body size patterns follow the temperature-size rule, with larger animals occurring at higher latitudes. The end-century projections of habitat suitability show a different picture, with 96% of cephalopod species predicted to experience range contraction and 15% completely losing their environmental space. Nestedness is projected to be the main effect of species compositional change. Maximum body size is projected to increase in 44% of the pixels and decrease in 37%. Regarding fisheries, the projected changes are more favorable to the countries at higher latitudes, although the search for refugia of smaller tropical species might potentially lead to a mitigation of the negative effects of climate change in these areas, as measured by the total capture (ton). While the model has limitations, our findings reflect major climatic drivers of change and highlight the idea that even though cephalopod species seem good candidates to replace overexploited fish stocks in the near future, they may not have the environmental space to do so.

Iterative species distribution modeling results in the discovery of novel populations of a rare cold desert perennial

Niche modeling for rare and range-restricted species can generate inaccurate predictions leading to an overestimation of a species geographic distribution. We used an iterative ensemble modeling approach and model-stratified field surveys to improve niche model formulation and better understand the ecological drivers of Ivesia webberi distribution. I. webberi is a US federally threatened herbaceous species, narrowly distributed in the western Great Basin Desert. Niche models for I. webberi were fitted using 10 replicates each of 6 modeling algorithms, while geographical projections of habitat suitability were generated using weighted ensembles of models with optimal performance. The resulting model projections were used to guide field surveys for 5 yr, generating additional spatial data, which were added to the existing dataset for subsequent modeling. Model performance across iterations was investigated and niche differences in the spatial dataset were explored. Model-guided field surveys resulted in the discovery of several new locations of I. webberi and an expansion of the species known range by 63 km. Model performance was higher in the earlier overfitted niche models. Overfitting was corrected in the final models, and predicted habitat suitability reduced from 5.98% in the 2015 model to 3.34% in the 2020 model. Findings show that I. webberi niche is associated with biotic, topographic and bioclimatic variables. Furthermore, a partial overlap was observed between environmental conditions of the initial and the new locations (Schoener’s D = 0.47), which can be decomposed into 93% of niche stability. This indicates that the majority of the newly discovered locations are within the environmental niche of the initial data.

Niche differentiation in a postglacial colonizer, the bank vole Clethrionomys glareolus.

Species‐level environmental niche modeling has been crucial in efforts to understand how species respond to climate variation and change. However, species often exhibit local adaptation and intraspecific niche differences that may be important to consider in predicting responses to climate. Here, we explore whether phylogeographic lineages of the bank vole originating from different glacial refugia (Carpathian, Western, Eastern, and Southern) show niche differentiation, which would suggest a role for local adaptation in biogeography of this widespread Eurasian small mammal. We first model the environmental requirements for the bank vole using species‐wide occurrences (210 filtered records) and then model each lineage separately to examine niche overlap and test for niche differentiation in geographic and environmental space. We then use the models to estimate past [Last Glacial Maximum (LGM) and mid‐Holocene] habitat suitability to compare with previously hypothesized glacial refugia for this species. Environmental niches are statistically significantly different from each other for all pairs of lineages in geographic and environmental space, and these differences cannot be explained by habitat availability within their respective ranges. Together with the inability of most of the lineages to correctly predict the distributions of other lineages, these results support intraspecific ecological differentiation in the bank vole. Model projections of habitat suitability during the LGM support glacial survival of the bank vole in the Mediterranean region and in central and western Europe. Niche differences between lineages and the resulting spatial segregation of habitat suitability suggest ecological differentiation has played a role in determining the present phylogeographic patterns in the bank vole. Our study illustrates that models pooling lineages within a species may obscure the potential for different responses to climate change among populations.

What Will Remain? Predicting the Representation in Protected Areas of Suitable Habitat for Endangered Tropical Avifauna in Borneo under a Combined Climate- and Land-Use Change Scenario

The responses of threatened tropical avian species to projected climate change and land-use change are important for evaluating the ability of the existing protected areas to provide habitat to these species under future scenarios in biodiversity hotspots. This study uses Maxent, a species distribution model that employs a maximum entropy machine learning approach to map the spatial distributions of habitats suitable for the International Union for Conservation of Nature threatened birds under present and future climate and land-use change in Borneo. We find that the existing protected areas provide very low coverage of the threatened bird species’ suitable habitat areas (95%CI = 9.3–15.4%). Analysis of habitat suitability projections for 18 species of threatened birds suggests that in 2050, under Special Report on Emissions Scenarios A1B and B1, avian species with currently little suitable habitat may gain area but lose in the proportion of this that is protected. Large-ranged species are likely to lose habitat area and this will inflate the proportion of this remaining in protected areas. The present availability of suitable habitat was the most important determinant of future habitat availability under both the scenarios. Threat level, as measured by the International Union for Conservation of Nature and the habitat preferences considered here, Lowland or Lowland–Montane, are poor predictors of the amount of habitat contraction or expansion undergone by the species.

A hippo in the room: Predicting the persistence and dispersion of an invasive mega-vertebrate in Colombia, South America

Biological invasions are a big concern due to their potential to impact ecosystems, as well as local people. The hippo Hippopotamus amphibius, native to Africa, has invaded extensive areas of the Magdalena River basin (Colombia) over the past decades, and has been considered the largest invasive animal in the world. Here, we propose the use of two approaches of predictive modeling, in order to guide recommendations for the management of this biological invasion. First, we developed a population viability analysis (PVA) to simulate a hypothetical population growth under different management scenarios. Next, we explored the potential invasion area under future climate change scenarios throughout ecological niche modeling analyses. PVA models predicted that in the absence of an intense culling/hunting pressure, the population size will continue to steadily increase, which is consistent with the population growth observed during the last 20 years. Furthermore, our static and dynamic habitat suitability projections suggested that without dispersal limiting factors, potential colonization habitat for hippos may become very extensive across the landscape and can be favored by climate change in the future. Therefore, our findings show the urgent need of taking critical management decisions by the Colombian authorities, which should be focused on limiting the hippos' population growth and expansion. Ignoring cost-benefit considerations for the control of this invasive species may have unexpected and long-term social and ecological implications. However, the proposal of a course of action can become controversial when the species has a charismatic value for the society, regardless of its ecological or social impact.

Potential distribution of Abies, Picea, and Juniperus species in the sub-alpine forest of Minjiang headwater region under current and future climate scenarios and its implications on ecosystem services supply

Mountain forest ecosystems provide us with life-supporting ecosystem services that are valuable for local, regional, and global communities. Ecological niche-based models have been used extensively, with remarkable success, in understanding the influence of climate change on potential distribution of species. In this study, we used maximum entropy (MaxEnt) modelling to predict the potential distribution of ecologically important tree species, Abies, Picea, and Juniperus, at the eastern edge of the Tibetan Plateau in China. The potential distribution of tree species was modelled and predicted on genus level for current and three representative concentration pathway (RCPs) based future (2050s and 2070s) climate conditions. The model performed well and gave reliable results for current and potential species’ distribution. Precipitation of wettest month was the most important environmental variable for determining the habitat suitability of all tree species, with 30.3% (Abies), 51.2% (Picea), and 57% (Juniperus) contribution to model output, respectively. Temperature seasonality, temperature annual range, and soil type also made the most significant contribution to model outputs. Model projections under current climate highlight that the total suitable habitats, which included regions with different probability of species occurrence, for Abies (3234.2 km2) was much higher than Picea (2003.7 km2) and Juniperus (1784.8 km2). However, projections of habitat suitability under current climate scenario projected onto future climate change scenarios for all concentration pathways in 2050s and 2070s, showed a clear decline in potentially suitable habitats for all three species. The shifts in geographic distributions under future climate scenarios showed an unusual pattern, with slight downward shift of the mean elevation with high habitat suitability for the occurrence of tree species in most RCPs, accompanied by a decrease in the elevational range of suitable habitats. The results of this study highlight the urgent need for forest management strategies to conserve the habitats of these species. Our study offers base-line information on the impact of climate-change on major tree species which can aid in guiding adaptation strategies for forest conservation and management in order to sustain the delivery of ecosystem services in the future.

Integrating multiple data sources and multi-scale land-cover data to model the distribution of a declining amphibian

Determining the spatial scale at which landscape features influence population persistence is an important task for conservation planning. One challenge is that sampling biases confound factors that influence species occurrence and survey effort. Recent developments in Point Process Models (PPMs) enable researchers to disentangle the sampling process from ecological drivers of species' distributions. Land-cover change is a driver of decline for the western spadefoot (Spea hammondii), which has been extirpated from much of its range in California. Assessing this species' status requires information on the current distribution of suitable habitat within its historical range, but little is known about the effect of the landscape surrounding breeding ponds on spadefoot occurrence. Critically, surveys for western spadefoots often occur along roads, potentially biasing data used to fit species distribution models. We created PPMs integrating historical presence/non-detection and presence-only data for western spadefoots and land-cover data at multiple spatial scales to model the distribution of this species while removing the influence of sampling bias. There was spatial sampling bias in presence-only data; records were more likely to be reported near roads and urban centers and PPMs that removed sampling bias outperformed models that ignored sampling bias. The occurrence of western spadefoots was positively related to the proportion of grassland within a 2000 m buffer. The remaining habitat for western spadefoots is largely found in the foothills surrounding California's Central Valley. Our study illustrates how PPMs can improve projections of habitat suitability and our understanding of the drivers of species' distributions.

Genetic diversity of Cedrela fissilis (Meliaceae) in the Brazilian Atlantic Forest reveals a complex phylogeographic history driven by Quaternary climatic fluctuations

AbstractQuaternary climatic fluctuations have shaped the geographic distribution of lineages, potentially affecting the demography, genetic structure, and patterns of genetic diversity of extant species. Different phylogeographic scenarios have been proposed for plants in neotropical cloud forests during the Last Glacial Maximum based on paleoecological data: the dry refugia hypothesis (DRH) and the moist forest hypothesis. We specifically focus on the Brazilian Atlantic Forest (BAF) range of Cedrela fissilis (Meliaceae), sampling 410 specimens from 50 localities. Our study combines analyses of the genetic diversity, phylogeographic patterns, and past geographic distributions with a particular focus on highland populations. We identified 283 alleles across the 11 microsatellite loci, ranging from 18 to 33 alleles per locus, distributed across five genetic groups. Most populations of C. fissilis from the BAF exhibited a diffuse genetic structure, reflected in low pairwise FST values, which could be the consequence of high gene flow. In addition, the plastid data showed a connection between the western, southern, and eastern populations in the North‐East of Brazil, but no association between genetic data and elevation was observed. Habitat suitability projections over the past 140 000 years showed less fragmentation relative to the present, indicating a higher connectivity and gene flow. Our results provide support for both the moist forest as well as the DRH, suggesting that most likely, a mixture of these processes has acted through space and time.

The effect of ocean warming on black sea bass (Centropristis striata) aerobic scope and hypoxia tolerance.

Over the last decade, ocean temperature on the U.S. Northeast Continental Shelf (U.S. NES) has warmed faster than the global average and is associated with observed distribution changes of the northern stock of black sea bass (Centropristis striata). Mechanistic models based on physiological responses to environmental conditions can improve future habitat suitability projections. We measured maximum, standard metabolic rate, and hypoxia tolerance (Scrit) of the northern adult black sea bass stock to assess performance across the known temperature range of the species. Two methods, chase and swim-flume, were employed to obtain maximum metabolic rate to examine whether the methods varied, and if so, the impact on absolute aerobic scope. A subset of individuals was held at 30°C for one month (30chronic°C) prior to experiments to test acclimation potential. Absolute aerobic scope (maximum–standard metabolic rate) reached a maximum of 367.21 mgO2 kg-1 hr-1 at 24.4°C while Scrit continued to increase in proportion to standard metabolic rate up to 30°C. The 30chronic°C group exhibited a significantly lower maximum metabolic rate and absolute aerobic scope in relation to the short-term acclimated group, but standard metabolic rate or Scrit were not affected. This suggests a decline in performance of oxygen demand processes (e.g. muscle contraction) beyond 24°C despite maintenance of oxygen supply. The Metabolic Index, calculated from Scrit as an estimate of potential aerobic scope, closely matched the measured factorial aerobic scope (maximum / standard metabolic rate) and declined with increasing temperature to a minimum below 3. This may represent a critical threshold value for the species. With temperatures on the U.S. NES projected to increase above 24°C in the next 80-years in the southern portion of the northern stock’s range, it is likely black sea bass range will continue to shift poleward as the ocean continues to warm.

Identifying conservation priorities for plant species in the Himalaya in current and future climates: A case study from Sikkim Himalaya, India

In recent years, scientific investigations on the effectiveness of Protected Areas (PAs) in conserving biodiversity and sustaining ecosystem functions under the impact of climate change have increasingly received more attention from researchers and park managers. In this study, we used a combination of species distribution modelling (SDM) and spatial hierarchical systematic conservation planning technique to delineate and prioritize areas for endemic plant species conservation under current and future (2050s, 2070s) climate conditions in Sikkim Himalaya. Data on endemic plant species occurrence were sourced from our already published studies and their potential suitable habitats under current and future climates were modelled using Maximum Entropy (MaxEnt) SDM. The MaxEnt habitat suitability projections of species were used in Zonation software to identify priority conservation areas in Sikkim Himalaya. We found that the existing PA network in the region was inadequate in conserving the endemic plant diversity either in the current or future climate scenarios. Based on our results, we propose addition of 896 square kilometres (sq km) to the existing PA network in the study area to ensure meaningful conservation goals. Additionally, we propose creation of 3 new PAs (Yumsedong, Lachen and Chungthang) and the need for expanding the boundaries of existing PAs (Maenam, Fambong Lho and Barsey) in the study area. Our analyses show that to mitigate the effects of ensuing climate change, a single large PA with wide geographic and elevational extents instead of several smaller PAs would be a more prudent strategy for conserving the plant diversity in the Himalaya.

A species distribution model for Paracentrotus lividus: predicted projections of habitat suitability

A species distribution model for Paracentrotus lividus: predicted projections of habitat suitability

Species distribution models predict temporal but not spatial variation in forest growth

Bioclimate envelope models have been widely used to illustrate the discrepancy between current species distributions and their potential habitat under climate change. However, the realism and correct interpretation of such projections has been the subject of considerable discussion. Here, we investigate whether climate suitability predictions correlate to tree growth, measured in permanent inventory plots and inferred from tree‐ring records. We use the ensemble classifier RandomForest and species occurrence data from ~200,000 inventory plots to build species distribution models for four important European forestry species: Norway spruce, Scots pine, European beech, and pedunculate oak. We then correlate climate‐based habitat suitability with volume measurements from ~50‐year‐old stands, available from ~11,000 inventory plots. Secondly, habitat projections based on annual historical climate are compared with ring width from ~300 tree‐ring chronologies. Our working hypothesis is that habitat suitability projections from species distribution models should to some degree be associated with temporal or spatial variation in these growth records. We find that the habitat projections are uncorrelated with spatial growth records (inventory plot data), but they do predict interannual variation in tree‐ring width, with an average correlation of .22. Correlation coefficients for individual chronologies range from values as high as .82 or as low as −.31. We conclude that tree responses to projected climate change are highly site‐specific and that local suitability of a species for reforestation is difficult to predict. That said, projected increase or decrease in climatic suitability may be interpreted as an average expectation of increased or reduced growth over larger geographic scales.

Investigating uncertainties in zooplankton composition shifts under climate change scenarios in the Mediterranean Sea

Ensemble niche modelling has become a common framework to predict changes in assemblages composition under climate change scenarios. The amount of uncertainty generated by the different components of this framework has rarely been assessed. In the marine realm forecasts have usually focused on taxa representing the top of the marine food‐web, thus overlooking their basal component: the plankton. Calibrating environmental niche models at the global scale, we modelled the habitat suitability of 106 copepod species and estimated the dissimilarity between present and future zooplanktonic assemblages in the surface Mediterranean Sea. We identified the patterns (species replacement versus nestedness) driving the predicted dissimilarity, and quantified the relative contributions of different uncertainty sources: environmental niche models, greenhouse gas emission scenarios, circulation model configurations and species prevalence. Our results confirm that the choice of the niche modelling method is the greatest source of uncertainty in habitat suitability projections. Presence‐only and presence–absence methods provided different visions of the niches, which subsequently lead to different future scenarios of biodiversity changes. Nestedness with decline in species richness is the pattern driving dissimilarity between present and future copepod assemblages. Our projections contrast with those reported for higher trophic levels, suggesting that different components of the pelagic food‐web may respond discordantly to future climatic changes.

Model‐based integration of observed and expert‐based information for assessing the geographic and environmental distribution of freshwater species

Freshwater ecosystems harbor specialized and vulnerable biodiversity, and the prediction of potential impacts of freshwater biodiversity to environmental change requires knowledge of the geographic and environmental distribution of taxa. To date, however, such quantitative information about freshwater species distributions remains limited. Major impediments include heterogeneity in available species occurrence data, varying detectability of species in their aquatic environment, scarcity of contiguous freshwater‐specific predictors, and methods that support addressing these issues in a single framework. Here we demonstrate the use of a hierarchical Bayesian modeling (HBM) framework that combines disparate species occurrence information with newly‐developed 1 km freshwater‐specific predictors, to account for imperfect species detection and make fine‐grain (1 km) estimates of distributions in freshwater organisms. The approach integrates a Bernoulli suitability and a Binomial observability process into a hierarchical zero‐inflated Binomial model. The suitability process includes point presence observations, records of site visits, 1 km environmental predictors and expert‐derived species range maps integrated with a distance‐decay function along the within‐stream distance as covariates. The observability process uses repeated observations to estimate a probability of observation given that the species was present. The HBM accounts for the spatial autocorrelation in species habitat suitability projections using an intrinsic Gaussian conditional autoregressive model. We used this framework for three fish species native to different regions and habitats in North America. Model comparison shows that HBMs significantly outperformed non‐spatial GLMs in terms of AUC and TSS scores, and that expert information when appropriately included in the model can provide an important refinement. Such ancillary species information and an integrative, hierarchical Bayesian modeling framework can therefore be used to advance fine‐grain habitat suitability predictions and range size estimates in the freshwater realm. Our approach is extendable in terms of data availability and generality and can be used on other freshwater organisms and regions.

Correction to ‘Present and future projections of habitat suitability of the Asian tiger mosquito, a vector of viral pathogens, from global climate simulation’

Correction to ‘Present and future projections of habitat suitability of the Asian tiger mosquito, a vector of viral pathogens, from global climate simulation’

Uncertainty in Various Habitat Suitability Models and Its Impact on Habitat Suitability Estimates for Fish

Species distribution models (SDMs) are extensively used to project habitat suitability of species in stream ecological studies. Owing to complex sources of uncertainty, such models may yield projections with varying degrees of uncertainty. To better understand projected spatial distributions and the variability between habitat suitability projections, this study uses five SDMs that are based on the outputs of a two-dimensional hydraulic model to project the suitability of habitats and to evaluate the degree of variability originating from both differing model types and the split-sample procedure. The habitat suitability index (HSI) of each species is based on two stream flow variables, including current velocity (V), water depth (D), as well as the heterogeneity of these flow conditions as quantified by the information entropy of V and D. The six SDM approaches used to project fish abundance, as represented by HSI, included two stochastic models: the generalized linear model (GLM) and the generalized additive model (GAM); as well as three machine learning models: the support vector machine (SVM), random forest (RF) and the artificial neural network (ANN), and an ensemble model (where the latter is the average of the preceding five models). The target species Sicyopterus japonicas was found to prefer habitats with high current velocities. The relationship between mesohabitat diversity and fish abundance was indicated by the trends in information entropy and weighted usable area (WUA) over the study area. This study proposes a method for quantifying habitat suitability, and for assessing the uncertainties in HSI and WUA that are introduced by the various SDMs and samples. This study also demonstrated both the merits of the ensemble modeling approach and the necessity of addressing model uncertainty.

Present and future projections of habitat suitability of the Asian tiger mosquito, a vector of viral pathogens, from global climate simulation.

Climate change can influence the transmission of vector-borne diseases (VBDs) through altering the habitat suitability of insect vectors. Here we present global climate model simulations and evaluate the associated uncertainties in view of the main meteorological factors that may affect the distribution of the Asian tiger mosquito (Aedes albopictus), which can transmit pathogens that cause chikungunya, dengue fever, yellow fever and various encephalitides. Using a general circulation model at 50 km horizontal resolution to simulate mosquito survival variables including temperature, precipitation and relative humidity, we present both global and regional projections of the habitat suitability up to the middle of the twenty-first century. The model resolution of 50 km allows evaluation against previous projections for Europe and provides a basis for comparative analyses with other regions. Model uncertainties and performance are addressed in light of the recent CMIP5 ensemble climate model simulations for the RCP8.5 concentration pathway and using meteorological re-analysis data (ERA-Interim/ECMWF) for the recent past. Uncertainty ranges associated with the thresholds of meteorological variables that may affect the distribution of Ae. albopictus are diagnosed using fuzzy-logic methodology, notably to assess the influence of selected meteorological criteria and combinations of criteria that influence mosquito habitat suitability. From the climate projections for 2050, and adopting a habitat suitability index larger than 70%, we estimate that approximately 2.4 billion individuals in a land area of nearly 20 million km2 will potentially be exposed to Ae. albopictus. The synthesis of fuzzy-logic based on mosquito biology and climate change analysis provides new insights into the regional and global spreading of VBDs to support disease control and policy making.

Modeling Hawaiian ecosystem degradation due to invasive plants under current and future climates.

Occupation of native ecosystems by invasive plant species alters their structure and/or function. In Hawaii, a subset of introduced plants is regarded as extremely harmful due to competitive ability, ecosystem modification, and biogeochemical habitat degradation. By controlling this subset of highly invasive ecosystem modifiers, conservation managers could significantly reduce native ecosystem degradation. To assess the invasibility of vulnerable native ecosystems, we selected a proxy subset of these invasive plants and developed robust ensemble species distribution models to define their respective potential distributions. The combinations of all species models using both binary and continuous habitat suitability projections resulted in estimates of species richness and diversity that were subsequently used to define an invasibility metric. The invasibility metric was defined from species distribution models with <0.7 niche overlap (Warrens I) and relatively discriminative distributions (Area Under the Curve >0.8; True Skill Statistic >0.75) as evaluated per species. Invasibility was further projected onto a 2100 Hawaii regional climate change scenario to assess the change in potential habitat degradation. The distribution defined by the invasibility metric delineates areas of known and potential invasibility under current climate conditions and, when projected into the future, estimates potential reductions in native ecosystem extent due to climate-driven invasive incursion. We have provided the code used to develop these metrics to facilitate their wider use (Code S1). This work will help determine the vulnerability of native-dominated ecosystems to the combined threats of climate change and invasive species, and thus help prioritize ecosystem and species management actions.