Unravelling the role of tropical cyclones in shaping present species distributions

Driven by climate change, tropical cyclones (TCs) are predicted to change in intensity and frequency through time. Given these forecasted changes, developing an understanding of how TCs impact insular wildlife is of heightened importance. Previous work has shown that extreme weather events may shape species distributions more strongly than climatic averages; however, given the coarse spatial and temporal scales at which TC data are often reported, the influence of TCs on species distributions has yet to be explored. Using TC data from the National Hurricane Center, we developed spatially and temporally explicit species distribution models (SDMs) to examine the role of TCs in shaping present-day distributions of Puerto Rico's 10 Anolis lizard species. We created six predictor variables to represent the intensity and frequency of TCs. For each occurrence of a species, we calculated these variables for TCs that came within 500 km of the center of Puerto Rico and occurred within the 1-year window prior to when that occurrence was recorded. We also included predictor variables related to landcover, climate, topography, canopy cover and geology. We used random forests to assess model performance and variable importance in models with and without TC variables. We found that the inclusion of TC variables improved model performance for the majority of Puerto Rico's 10 anole species. The magnitude of the improvement varied by species, with generalist species that occur throughout the island experiencing the greatest improvements in model performance. Range-restricted species experienced small, almost negligible, improvements but also had more predictive models both with and without the inclusion of TC variables compared to generalist species. Our findings suggest that incorporating data on TCs into SDMs may be important for modeling insular species that are prone to experiencing these types of extreme weather events.

Climate change and anthropogenic activities shrink the range and dispersal of an endangered primate in Sichuan Province, China

The golden snub-nosed monkey (Rhinopithecus roxellana) is a rare and endemic species in China. The population of golden snub-nosed monkeys in Sichuan Province has an isolated genetic status, large population size, and low genetic diversity, making it highly vulnerable to environmental changes. Our study aimed to evaluate the potential impact of climate and land-use changes on the distribution and dispersal paths of the species in Sichuan Province. We used three general circulation models (GCMs), three greenhouse gas emission scenarios, and three land-use change scenarios suitable for China to predict the potential distributions of the golden snub-nosed monkey in the current and 2070s using the MaxEnt model. The dispersal paths were identified by the circuit theory. Our results suggested that the habitats of the golden snub-nosed monkey were reduced under all three GCM scenarios. The suitable habitats for the golden snub-nosed monkey would be reduced by 82.67%, 82.47%, and 75.17% under the RCP2.6, RCP4.5, and RCP8.5 scenarios, respectively, compared to the currently suitable habitat area. Additionally, we found that the density of future dispersal paths of golden snub-nosed monkeys would decrease, and the dispersal resistance would increase. Therefore, relevant wildlife protection agencies should prioritize the climatically suitable distributions and key dispersal paths of golden snub-nosed monkeys to improve their conservation. We identified key areas for habitat preservation and increased habitat connectivity under climate change, which could serve as a reference for future adaptation strategies.

Assessing the effectiveness of protected areas for panda conservation under future climate and land use change scenarios

While the relatively stable land use and land cover (LULC) patterns is an important feature of protected areas (PAs), the influence of this feature on future species distribution and the effectiveness of the PAs has rarely been explored. Here, we assessed the role of land use patterns within PAs on the projected range of the giant panda (Ailuropoda melanoleuca) by comparing projections inside and outside of PAs for four model configurations: (1) only climate covariates, (2) climate and dynamic land use covariates, (3) climate and static land use covariates and (4) climate and hybrid dynamic-static land use covariates. Our objectives were twofold: to understand the role of protected status on projected panda habitat suitability and evaluate the relative efficacy of different climate modeling approaches. The climate and land use change scenarios used in the models include two shared socio-economic pathways (SSPs) scenarios: SSP126 [an optimistic scenario] and SSP585 [a pessimistic scenario]. We found that models including land-use covariates performed significantly better than climate-only models and that these projected more suitable habitat than climate-only models. Static land-use models projected more suitable habitat than both the dynamic and hybrid models under SSP126, while these models did not differ under SSP585. China's panda reserve system was projected to effectively maintain suitable habitat inside PAs. Panda dispersal ability also significantly impacted outcomes, with most models assuming unlimited dispersal forecasting range expansion and models assuming zero dispersal consistently forecasting range contraction. Our findings highlight that policies targeting improved land-use practices should be an effective means for offsetting some of the negative effects of climate change on pandas. As the effectiveness of PAs is projected to be maintained, we recommend the judicious management and expansion of the PA system to ensure the resilience of panda populations into the future.

Ecological response of an umbrella species to changing climate and land use: Habitat conservation for Asiatic black bear in the Sichuan-Chongqing Region, Southwestern China

Climate and land use changes are increasingly recognized as major threats to global biodiversity, with significant impacts on wildlife populations and ecosystems worldwide. The study of how climate and land use changes impact wildlife is of paramount importance for advancing our understanding of ecological processes in the face of global environmental change, informing conservation planning and management, and identifying the mechanisms and thresholds that underlie species' responses to shifting climatic conditions. The Asiatic black bear (Ursus thibetanus) is a prominent umbrella species in a biodiversity hotspot in Southwestern China, and its conservation is vital for safeguarding sympatric species. However, the extent to which this species' habitat may respond to global climate and land use changes is poorly understood, underscoring the need for further investigation. Our goal was to anticipate the potential impacts of upcoming climate and land use changes on the distribution and dispersal patterns of the Asiatic black bear in the Sichuan-Chongqing Region. We used MaxEnt modeling to evaluate habitat vulnerability using three General Circulation Models (GCMs) and three scenarios of climate and land use changes. Subsequently, we used Circuit Theory to identify prospective dispersal paths. Our results revealed that the current area of suitable habitat for the Asiatic black bear was 225,609.59 km² (comprising 39.69% of the total study area), but was expected to decrease by -53.1%, -49.48%, and -28.55% under RCP2.6, RCP4.5, and RCP8.5 projection scenarios, respectively. Across all three GCMs, the distribution areas and dispersal paths of the Asiatic black bear were projected to shift to higher altitudes and constrict by the 2070s. Furthermore, the results indicated that the density of dispersal paths would decrease, while the resistance to dispersal would increase across the study area. In order to protect the Asiatic black bear, it is essential to prioritize the protection of climate refugia and dispersal paths. Our findings provide a sound scientific foundation for the allocation of such protected areas in the Sichuan-Chongqing Region that are both effective and adaptive in the face of ongoing global climate and land use changes.

MaxEnt Modeling for Predicting the Potential Wintering Distribution of Eurasian Spoonbill (Platalea leucorodia leucorodia) under Climate Change in China

Global climate change has become a trend and is one of the main factors affecting biodiversity patterns and species distributions. Many wild animals adapt to the changing living environment caused by climate change by changing their habitats. Birds are highly sensitive to climate change. Understanding the suitable wintering habitat of the Eurasian Spoonbill (Platalea leucorodia leucorodia) and its response to future climatic change is essential for its protection. In China, it was listed as national grade II key protected wild animal in the adjusted State List of key protected wild animals in 2021, in Near Threatened status. Few studies on the distribution of the wintering Eurasian Spoonbill have been carried out in China. In this study, we simulated the suitable habitat under the current period and modeled the distribution dynamics of the wintering Eurasian Spoonbill in response to climate change under different periods by using the MaxEnt model. Our results showed that the current suitable wintering habitats for the Eurasian Spoonbill are mainly concentrated in the middle and lower reaches of the Yangtze River. Distance from the water, precipitation of the driest quarter, altitude, and mean temperature of the driest quarter contributed the most to the distribution model for the wintering Eurasian Spoonbill, with a cumulative contribution of 85%. Future modeling showed that the suitable distribution of the wintering Eurasian Spoonbill extends to the north as a whole, and the suitable area shows an increasing trend. Our simulation results are helpful in understanding the distribution of the wintering Eurasian Spoonbill under different periods in China and support species conservation.

Global-scale parameters for ecological models

This paper presents a collection of environmental, geophysical, and other marine-related data for marine ecological models and ecological-niche models. It consists of 2132 raster data for 58 distinct parameters at regional and global scales in the ESRI-GRID ASCII format. Most data originally belonged to open data owned by the authors of this article but residing on heterogeneous repositories with different formats and resolutions. Other data were specifically created for the present publication. The collection includes 565 data with global scale range; 154 at 0.5° resolution and 411 at 0.1° resolution; 196 data with annual temporal aggregation over ~10 key years between 1950 and 2100; 369 data with monthly aggregation at 0.1° resolution from January 2017 to ~May 2021 continuously. Data were also cut out on 8 European marine regions. The collection also includes forecasts for different future scenarios such as the Representative Concentration Pathways 2.6 (63 data), 4.5 (162 data), and 8.5 (162 data), and the A2 scenario of the Intergovernmental Panel on Climate Change (180 data).

Predicting potential global distribution and risk regions for potato cyst nematodes (Globodera rostochiensis and Globodera pallida)

Potato cyst nematodes (PCNs), golden (yellow) cyst nematode (Globodera rostochiensis, gPCN) and pale (white) cyst nematode (G. pallida, pPCN), are important invasive pests in many countries and regions where they can cause significant yield and economic loss for agriculture. Prediction and identification of habitats suitable for PCNs are critical for developing biosecurity strategies, both pre and post border, to maximise the potential for early elimination should an incursion occur. To date, the potential global distribution of PCNs has not been thoroughly studied. Therefore, this study conducted a species distribution model to illustrate the potential global distribution of PCNs and risk regions. In this study, the Maximum Entropy Model (Maxent) associated with the Geographic Information System (GIS) was employed to reveal the potential distribution of the gPCN and pPCN. In addition to bioclimate, soil quality was also included in the model. The global cultivated lands, whether the susceptible hosts were present or not, were used to assess the maximum potential risk regions. The limitation factors for PCNs distribution were also assessed. Results showed that 66% of the global land surface was suitable for gPCN or pPCN or both, and both species can colonise more than 75% of the global cultivated lands. The coldest quarter's mean temperature and precipitation were critical limitations in unsuitable regions. In summary, the global risk maps of PCNs contribute valuable additional information that complements previous national/regional distribution predictions. The results of this distribution research will contribute practical support for decision-makers and practitioners to implement biosecurity strategies from a global perspective, that incorporate prevention or promptly enforce control practices to limit the damage caused by future incursions.

Predicting the effects of climate change on deep-water coral distribution around New Zealand-Will there be suitable refuges for protection at the end of the 21st century?

Deep-water corals are protected in the seas around New Zealand by legislation that prohibits intentional damage and removal, and by marine protected areas where bottom trawling is prohibited. However, these measures do not protect them from the impacts of a changing climate and ocean acidification. To enable adequate future protection from these threats we require knowledge of the present distribution of corals and the environmental conditions that determine their preferred habitat, as well as the likely future changes in these conditions, so that we can identify areas for potential refugia. In this study, we built habitat suitability models for 12 taxa of deep-water corals using a comprehensive set of sample data and predicted present and future seafloor environmental conditions from an earth system model specifically tailored for the South Pacific. These models predicted that for most taxa there will be substantial shifts in the location of the most suitable habitat and decreases in the area of such habitat by the end of the 21st century, driven primarily by decreases in seafloor oxygen concentrations, shoaling of aragonite and calcite saturation horizons, and increases in nitrogen concentrations. The current network of protected areas in the region appear to provide little protection for most coral taxa, as there is little overlap with areas of highest habitat suitability, either in the present or the future. We recommend an urgent re-examination of the spatial distribution of protected areas for deep-water corals in the region, utilising spatial planning software that can balance protection requirements against value from fishing and mineral resources, take into account the current status of the coral habitats after decades of bottom trawling, and consider connectivity pathways for colonisation of corals into potential refugia.

Distribution of Breeding Population and Predicting Future Habitat under Climate Change of Black-Necked Crane (Grus nigricollis Przevalski, 1876) in Shaluli Mountains

Climate change is affecting biodiversity by altering the geographical distribution range of species, and this effect is amplified in climate-sensitive areas. Studying the geographic distribution of flagship species in response to climate change is important for the long-term conservation of species and the maintenance of regional biodiversity. Therefore, we collected field survey records from 2016 to 2020 and conducted field surveys of black-necked cranes in the Shaluli Mountains (SLLMs) in May–June and August–October 2021; 103 breeding records were acquired totally, and the geographical distribution range under the current and four future climate scenarios was modeled with the MaxEnt model to predict the impact of climate change on its distribution and habitat quality. The results showed that 152 black-necked cranes were surveyed in seven counties of SLLMs in total; the estimated number of black-necked cranes in the entire SLLMs was about 200. The currently suitable habitat area is 27,122 km2, mainly distributed in gentle meadows and wetland habitats along the lake where the Annual Mean Temperature is −1 °C and the Mean Diurnal Range (16 °C) and Precipitation Seasonality (105) are comparatively large. Furthermore, the breeding range would expand to varying degrees under future climate scenarios and showed a migration trend toward the northwest and higher elevation. Besides, as time goes by, the habitat for black-necked cranes in SLLMs would become more homogeneous and more suitable. The conservation effectiveness of the existing reserve network would keep stable with climate change, although there are large conservation gaps between protected areas, and these gaps will gradually expand over time. Overall, this study provides a preliminary understanding of the population and distribution and predicts the future distribution of black-necked cranes in the SLLMs. It also demonstrates the importance of SLLMs for protecting the central population of black-necked cranes and maintaining regional biodiversity. Therefore, we recommend long-term monitoring and conservation of the black-necked crane population and wetland resources in the region.

Forecasting the combined effects of future climate and land use change on the suitable habitat of Davidia involucrata Baill

Accurately predicting the future distribution of species is crucial for understanding how species will response to global environmental change and for evaluating the effectiveness of current protected areas (PAs). Here, we assessed the effect of climate and land use change on the projected suitable habitats of Davidia involucrata Baill under different future scenarios using the following two types of models: (a) only climate covariates (climate SDMs) and (b) climate and land use covariates (full SDMs). We found that full SDMs perform significantly better than climate SDMs in terms of both AUC (p < .001) and TSS (p < .001) and also projected more suitable habitat than climate SDMs both in the whole study area and in its current suitable range, although D. involucrate is predicted to loss at least 26.96% of its suitable area under all future scenarios. Similarly, we found that these range contractions projected by climate SDMs would negate the effectiveness of current PAs to a greater extent relative to full SDMs. These results suggest that although D. involucrate is extremely vulnerability to future climate change, conservation intervention to manage habitat may be an effective option to offset some of the negative effects of a changing climate on D. involucrate and can improve the effectiveness of current PAs. Overall, this study highlights the necessity of integrating climate and land use change to project the future distribution of species.

Climate change, land cover change, and overharvesting threaten a widely used medicinal plant in South Africa

Medicinal plants contribute substantially to the well-being of people in large parts of the world, providing traditional medicine and supporting livelihoods from trading plant parts, which is especially significant for women in low-income communities. However, the availability of wild medicinal plants is increasingly threatened; for example, the Natal Lily (Clivia miniata), which is one of the most widely traded plants in informal medicine markets in South Africa, lost over 40% of individuals over the last 90 years. Understanding the species' response to individual and multiple pressures is essential for prioritizing and planning conservation actions. To gain this understanding, we simulated the future range and abundance of C. miniata by coupling Species Distribution Models with a metapopulation model (RAMAS-GIS). We contrasted scenarios of climate change (RCP2.6 vs. RCP8.5), land cover change (intensification vs. expansion), and harvesting (only juveniles vs. all life-stages). All our scenarios pointed to continuing declines in suitable habitat and abundance by the 2050s. When acting independently, climate change, land cover change, and harvesting each reduced the projected abundance substantially, with land cover change causing the most pronounced declines. Harvesting individuals from all life stages affected the projected metapopulation size more negatively than extracting only juveniles. When the three pressures acted together, declines of suitable habitat and abundance accelerated but uncertainties were too large to identify whether pressures acted synergistically, additively, or antagonistically. Our results suggest that conservation should prioritize the protection of suitable habitat and ensure sustainable harvesting to support a viable metapopulation under realistic levels of climate change. Inadequate management of C. miniata populations in the wild will likely have negative consequences for the well-being of people relying on this ecosystem service, and we expect there may be comparable consequences relating to other medicinal plants in different parts of the world.

Predicting Potential Habitat Changes of Two Invasive Alien Fish Species with Climate Change at a Regional Scale

Developing national-level policies related to climate change induced expansions of invasive species requires predictive modelling at a regional scale level. This study aimed to predict future changes in the habitat distributions of two major invasive alien fish species, Micropterus salmoides and Lepomis macrochirus, in South Korea. An ensemble system with multiple species distribution models was used for the prediction, and gridded water portion data from the linear-structure information on river channels inputted as habitat characteristics of freshwater ecosystem into the models. Bioclimatic variables at 20-year intervals from 2001 to 2100 were generated from predicted temperature and precipitation data under the representative concentration pathway 4.5 and 8.5 scenarios. The overall distribution probabilities of the potential habitats increased with time in both climate change scenarios, and the potential habitats were predicted to expand to upstream areas. Combined with regional ecological value information, such as biodiversity in freshwater ecosystems, these results can be an important basis for deriving regional priority information for managing alien species in climate change. Additionally, the modelling approach is highly applicable to various national-level policies for ecosystem conservation since it is not greatly restricted by spatial scales.

Prediction of the potential geographical distribution of Betula platyphylla Suk. in China under climate change scenarios

Climate is a dominant factor affecting the potential geographical distribution of species. Understanding the impact of climate change on the potential geographic distribution of species, which is of great significance to the exploitation, utilization, and protection of resources, as well as ecologically sustainable development. Betula platyphylla Suk. is one of the most widely distributed temperate deciduous tree species in East Asia and has important economic and ecological value. Based on 231 species distribution data points of Betula platyphylla Suk. in China and 37 bioclimatic, soil, and topography variables (with correlation coefficients < 0.75), the potential geographical distribution pattern of Betula platyphylla Suk. under Representative Concentration Pathway (RCP) climate change scenarios at present and in the 2050s and 2070s was predicted using the MaxEnt model. We analyzed the main environmental variables affecting the distribution and change of suitable areas and compared the scope and change of suitable areas under different climate scenarios. This study found: (1) At present, the main suitable area for Betula platyphylla Suk. extends from northeastern to southwestern China, with the periphery area showing fragmented distribution. (2) Annual precipitation, precipitation of the warmest quarter, mean temperature of the warmest quarter, annual mean temperature, and precipitation of the driest month are the dominant environmental variables that affect the potential geographical distribution of Betula platyphylla Suk. (3) The suitable area for Betula platyphylla Suk. is expected to expand under global warming scenarios. In recent years, due to the impact of diseases and insect infestation, and environmental damage, the natural Betula platyphylla Suk. forest in China has gradually narrowed. This study accurately predicted the potential geographical distribution of Betula platyphylla Suk. under current and future climate change scenarios, which can provide the scientific basis for the cultivation, management, and sustainable utilization of Betula platyphylla Suk. resources.

Climate change and alpine-adapted insects: modelling environmental envelopes of a grasshopper radiation

Mountains create steep environmental gradients that are sensitive barometers of climate change. We calibrated 10 statistical models to formulate ensemble ecological niche models for 12 predominantly alpine, flightless grasshopper species in Aotearoa New Zealand, using their current distributions and current conditions. Niche models were then projected for two future global climate scenarios: representative concentration pathway (RCP) 2.6 (1.0°C rise) and RCP8.5 (3.7°C rise). Results were species specific, with two-thirds of our models suggesting a reduction in potential range for nine species by 2070, but surprisingly, for six species, we predict an increase in potential suitable habitat under mild (+1.0°C) or severe global warming (+3.7°C). However, when the limited dispersal ability of these flightless grasshoppers is taken into account, all 12 species studied are predicted to suffer extreme reductions in range, with a quarter likely to go extinct due to a 96-100% reduction in suitable habitat. Habitat loss is associated with habitat fragmentation that is likely to escalate stochastic vulnerability of remaining populations. Here, we present the predicted outcomes for an endemic radiation of alpine taxa as an exemplar of the challenges that alpine species, both in New Zealand and internationally, are subject to by anthropogenic climate change.

Predicting Potential Habitat of a Plant Species with Small Populations under Climate Change: Ostryarehderiana

Ostrya rehderiana is a famous plant species with extremely small populations. With ongoing global climate change, the extremely small populations would face more uncertainties and risks, including the loss of genetic diversity and extirpation. Thus, assessing the impact of climate change on suitable habitat of O. rehderiana is particularly important for its conservation and restoration. Here, we built niche models with climate variables and soil and human footprint variables. Furthermore, new methods were applied to avoid confounding effects between climate and soil and human footprint variables to simulate the potential habitats of O. rehderiana in current and future climates. We found that the Hargreaves climatic moisture deficit, degree-days below 0 °C, chilling degree-days, and the temperature difference between mean warmest month temperature and mean coldest month temperature, or continentality, were the most important climate factors. The topsoil USDA texture classification, topsoil cation exchange capacity of (clay), and topsoil sodicity (ESP) were the key soil factors determining the suitable distribution of O. rehderiana. Compared with soil factors, human footprint has less influence on the suitable distribution of O. rehderiana. The niche range of this species was projected to expand and shift to north in the Representative Concentration Pathway (RCP) 4.5 scenario for the 2050s. Our study results could be referenced in further extremely small populations ecological restoration studies and provide the scientific strategies for the conservation and restoration of O. rehderiana.

The role of littoral cliffs in the niche delimitation on a microendemic plant facing climate change

Obligate coastline taxa generally occupy very limited areas, especially when there is a close affinity with a specific coast type. Climate change can be a meaningful threat for them, reducing suitable habitat or forcing migration events. Cistus ladanifer subsp. sulcatus is an endemic plant of Portugal, known to occur only in the top of its south-western coast's prominent cliffs. In spite of being included in the annexes II and IV of the European Habitats Directive of Natura 2000 Network, this taxon is still understudied, especially regarding the effects of climate change on its distribution. To overcome such gap, Maxent was used to model the current distribution of C. ladanifer subsp. sulcatus and project its future distribution considering different General Circulation Models, periods (2050 and 2070) and Representation Concentration Pathways (4.5 and 8.5). The results suggested an extensive range contraction in the future, and extinction is a possible scenario. The proximity to littoral cliffs is crucial for this plant's occurrence, but these formations are irregularly distributed along the coast, hindering range expansions, further inhibited by a small dispersal capacity. Cistus ladanifer subsp. sulcatus will probably remain confined to south-western Portugal in the future, where it will continue to face relevant threats like human activity, reinforcing the need for its conservation.

Dengue disease dynamics are modulated by the combined influences of precipitation and landscape: A machine learning approach

BACKGROUND

Dengue is an endemic vector-borne disease influenced by environmental factors such as landscape and climate. Previous studies separately assessed the effects of landscape and climate factors on mosquito occurrence and dengue incidence. However, both factors concurrently coexist in time and space and can interact, affecting mosquito development and dengue disease transmission. For example, eggs laid in a suitable environment can hatch after being submerged in rain water. It has been difficult for conventional statistical modeling approaches to demonstrate these combined influences due to mathematical constraints.

OBJECTIVES

To investigate the combined influences of landscape and climate factors on mosquito occurrence and dengue incidence.

METHODS

Entomological, epidemiological, and landscape data from the rainy season (July-December) were obtained from respective government agencies in Metropolitan Manila, Philippines, from 2012 to 2014. Temperature, precipitation and vegetation data were obtained through remote sensing. A random forest algorithm was used to select the landscape and climate variables. Afterward, using the identified key variables, a model-based (MOB) recursive partitioning was implemented to test the combined influences of landscape and climate factors on ovitrap index (vector mosquito occurrence) and dengue incidence.

RESULTS

The MOB recursive partitioning for ovitrap index indicated a high sensitivity of vector mosquito occurrence on environmental conditions generated by a combination of high residential density areas with low precipitation. Moreover, the MOB recursive partitioning indicated high sensitivity of dengue incidence to the effects of precipitation in areas with high proportions of residential density and commercial areas.

CONCLUSIONS

Dengue dynamics are not solely influenced by individual effects of either climate or landscape, but rather by their synergistic or combined effects. The presented findings have the potential to target vector surveillance in areas identified as suitable for mosquito occurrence under specific climatic conditions and may be relevant as part of urban planning strategies to control dengue.

Using climatic variables alone overestimate climate change impacts on predicting distribution of an endemic species

Plant species distribution is constrained by both dynamic and static environmental variables. However, relative contribution of dynamic and static variables in determining species distributions is not clear and has far reaching implications for range change dynamics in a changing world. Prunus eburnea (Spach) Aitch. & Hemsl. is an endemic and medicinal plant species of Iran. It has rendered itself as ecologically important for its functions and services and is currently in need of habitat conservation measures requiring investigation of future potential distribution range. We conducted sampling of 500 points that cover most of Iran plateau and recorded the P. eburnea presence and absence during the period 2015-2017. In this study, we evaluated impacts of using only climatic variables versus combined with topographic and edaphic variables on accuracy criteria and predictive ability of current and future habitat suitability of this species under climate change (CCSM4, RCP 2.6 in 2070) by generalized linear model and generalized boosted model. Models' performances were evaluated using area under the curve, sensitivity, specificity and the true skill statistic. Then, we evaluated here, driving environmental variables determining the distribution of P. eburnea by using principal component analysis and partitioning methods. Our results indicated that prediction with high accuracy of the spatial distribution of P. eburnea requires both climate information, as dynamic primary factors, but also detailed information on soil and topography variables, as static factors. The results emphasized that environmental variable grouping influenced the modelling prediction ability strongly and the use of only climate variables would exaggerate the predicted distribution range under climate change. Results supported using both dynamic and static variables improved accuracy of the modeling and provided more realistic prediction of species distribution under influence of climate change.

Soil predictors are crucial for modelling vegetation distribution and its responses to climate change

Bioclimatic envelope models have been extensively used to predict the vegetation dynamics in response to climate changes. However, they are prone to the uncertainties arising from General Circulation Models (GCMs), classification algorithms and predictors, with low-resolution results and little detail at the regional level. Novel research has focused on the improvement of these models through a combination of climate and soil predictors to enhance ecological consistency. In this framework, we aimed to apply a joint edaphoclimatic envelope to predict the current and future vegetation distribution in the semiarid region of Brazil, which encompasses several classes of vegetation in response to the significant environmental heterogeneity. We employed a variety of machine learning algorithms and GCMs under RCP 4.5 and 8.5 scenarios of Coupled Model Intercomparison Project Phase 5 (CMIP5), in 1 km resolution. The combination of climate and soil predictors resulted in higher detail at landscape-scale and better distinction of vegetations with overlapping climatic niches. In forecasts, soil predictors imposed a buffer effect on vegetation dynamics as they reduced shifts driven solely by climatic drift. Our results with the edaphoclimatic approach pointed to an expansion of the dry Caatinga vegetation, ranging from an average of 16% to 24% on RCP 4.5 and RCP8.5 scenarios, respectively. The shift in environmental suitability from forest to open and dry vegetation implies a major loss to biodiversity, as well as compromising the provision of ecosystem services important for maintaining the economy and livelihoods of the world's largest semiarid population. Predicting the most susceptible regions to future climate change is the first step in developing strategies to mitigate impacts in these areas.

Climate warming will increase chances of hybridization and introgression between two Takydromus lizards (Lacertidae)

Coexisting species may experience population and range changes alone or jointly in response to environmental change. Here, we used six climate variables and ten modeling algorithms to predict the distribution of two Takydromus species (T. septentrionalis and T. sexlineatus) in China. We identified the sympatric and allopatric areas by comparing projections between the two species based on habitat suitability under present and future climate scenarios. We constructed the hypervolumes of six climate variables for the two species and then evaluated overlaps between hypervolumes. From this study, we know the following. First, minimum temperature of coldest month contributes the most to the prediction of habitat suitability. Second, habitats suitable for the two species will shift northward in response to climate warming. Third, the range of T. sexlineatus will expand across the four future time intervals before 2,100, namely the 2021-2040, 2041-2060, 2061-2080, and 2081-2100 intervals, under both Shared socioeconomic pathway (SSP) 245 and SSP585 scenarios, and the range of T. septentrionalis will also expand in the future except at the 2081-2100 interval under the SSP585 scenario. Fourth, the sympatric areas will contract or expand under the SSP245 scenario and expand across the four future time intervals before 2,100 under the SSP585 scenario. Fifth, the niche hypervolumes of the two species partially overlapped, and the differences in niche centroid show some degree of niche differentiation between the two species. These results allow to conclude that climate warming will not only drive the northward drift of sympatric areas but also increase the size of these areas if nothing is done to limit the emission of greenhouse gases. Given the existence of hybridization and introgression between T. septentrionalis and T. sexlineatus in the field where they coexist, we also conclude that climate warming will increase chances of hybridization and introgression between the two species.

Predicting the potential distribution and forest impact of the invasive species Cydalima perspectalis in Europe

Invasive species have considerably increased in recent decades due to direct and indirect effects of ever-increasing international trade rates and new climate conditions derived from global change. We need to better understand how the dynamics of early species invasions develop and how these result in impacts on the invaded ecosystems. Here we studied the distribution and severe defoliation processes of the box tree moth (Cydalima perspectalis W.), a tree defoliator insect native to Asia and invasive in Europe since 2007, through the combination of species distribution models based on climate and landscape composition information. The results showed that the combination of data from the native and the invaded areas was the most effective methodology for the appropriate invasive species modeling. The species was not influenced by overall landscape factors, but only by the presence of its host plant, dispersal capacity, and climate suitability. Such climate suitability was described by low precipitation seasonality and minimum annual temperatures around 0°C, defining a continentality effect throughout the territory. We emphasize the need of studying distribution and severe defoliation processes separately because we identified that climate suitability was slightly involved in limiting species spread processes but strongly constrained ecosystem impact in terms of defoliation before the species reaches equilibrium with the new environment. New studies on habitat recovery after disturbance, ecological consequences of such impact, and community dynamics in a context of climate change are required for a better understanding of this invasive species.

Drivers of distributions and niches of North American cold-adapted amphibians: evaluating both climate and land use

Species distribution estimates are often used to understand the niche of a species; however, these are often based solely on climatic predictors. When the influences of biotic factors are ignored, erroneous inferences about range and niche may be made. We aimed to integrate climate data with a unique set of available land cover and land use data for the six cold-adapted amphibians of North America (Ambystoma macrodactylum, Anaxyrus hemiophrys, Anaxyrus boreas, Pseudacris maculata, Rana sylvatica, Rana luteiventris) to determine the relative importance of climate and non-climate drivers through the use of ecological niche models for present-day range estimates. We compared climate-only, land use-only, and combination models of climate and land use, derived from two different model selection techniques, to determine which was most likely to drive current distributions of cold-adapted amphibian species. Land use layers included land cover type, human population, vegetation type, ecoregion, and the overall human footprint. The most supported models included both climate and land use, with climate and human footprint variables having the highest permutation importance and percent contribution. Models that incorporated climate and land use data performed best as measured with AIC and AUC, although qualitatively most underestimated the northern range edge, implying potential sampling bias or locations of reduced habitat quality for these species in the northern area of the ranges. There were small differences in overall combination models dependent on the method of model selection. The overall effect sizes of landscape factors within the combination models were small except for one landscape feature: human footprint, which incorporated multiple aspects of anthropogenic change on the landscape, including human population density, travel access, and agricultural impact. This aspect of the landscape was just as important as climate, and counter to what we expected, the association was mostly positive, with a negative response only occurring at very high levels. This highlights the importance of moving beyond climate only species range estimates as land cover, specifically human impact, may be driving the patterns of species' ranges.

Zeeshan Ali, Dasgpta N, Uniyal VP, Johnson JA, Hussain SA. Evaluating performance of four species distribution models using Blue-tailed Green Darner Anax guttatus (Insecta: Odonata) as model organism from the Gangetic riparian zone

In this paper we evaluated the performance of four species distribution models: generalized linear (GLM), maximum entropy (MAXENT), random forest (RF) and support vector machines (SVM) model, using the distribution of the dragonfly Blue-tailed Green Darner Anax guttatus in the Gangetic riparian zone between Bijnor and Kanpur barrage, Uttar Pradesh, India.  We used forest cover type, land use, land cover and five bioclimatic variable layers: annual mean temperature, isothermality, temperature seasonality, mean temperature of driest quarter, and precipitation seasonality to build the models.  We found that the GLM generated the highest values for AUC, Kappa statistic, TSS, specificity and sensitivity, and the lowest values for omission error and commission error, while the MAXENT model generated the lowest variance in variable importance. We suggest that researchers should not rely on any single algorithm, instead, they should test performance of all available models for their species and area of interest, and choose the best one to build a species distribution model.  

Species range shifts in response to climate change and human pressure for the world's largest amphibian

The Chinese giant salamander, Andrias davidianus, the world's largest amphibian, is critically endangered and has an extremely unique evolutionary history. Therefore, this species represents a global conservation priority and will be impacted by future climate and human pressures. Understanding the range and response to environmental change of this species is a priority for the identification of targeted conservation activities. We projected future range shifts of the Chinese giant salamander under the independent and combined impacts of climate change and human population density (HPD) variations by using ensemble species distribution models. We further evaluated the sustainability of existing nature reserves and identified priority areas for the mitigation or prevention of such pressures. Both climate change and increasing HPD tended to reduce the species range, with the latter leading to greater range losses and fragmentation of the range. Notably, 65.6%, 18.0% and 18.4% of the range loss were attributed solely to HPD change, solely to climate change and to their overlapping impacts, respectively. Overall, the average total and net losses of the species range were 52.5% and 23.4%, respectively, and HPD and climate changes were responsible for 71.4% and 28.6% of the net losses, respectively. We investigated the stability of the remaining species range and found that half of the nature reserves are likely vulnerable, with 57.1% and 66.7% of them likely to lose their conservation value in 2050 and 2070, respectively. To effectively protect this salamander, conservation policies should address both pressures simultaneously, especially considering the negative impact of human pressures in both contemporary periods and the near future. The species range shifts over space and time projected by this research could help guide long-term surveys and the sustainable conservation of wild habitats and populations of this ancient and endangered amphibian.

Potential Effects of Climate Change on the Geographic Distribution of the Endangered Plant Species Manihot walkerae

Walker’s Manihot, Manihot walkerae, is an endangered plant that is endemic to the Tamaulipan thornscrub ecoregion of extreme southern Texas and northeastern Mexico. M. walkerae populations are highly fragmented and are found on both protected public lands and private property. Habitat loss and competition by invasive species are the most detrimental threats for M. walkerae; however, the effect of climate change on M. walkerae’s geographic distribution remains unexplored and could result in further range restrictions. Our objectives are to evaluate the potential effects of climate change on the distribution of M. walkerae and assess the usefulness of natural protected areas in future conservation. We predict current and future geographic distribution for M. walkerae (years 2050 and 2070) using three different general circulation models (CM3, CMIP5, and HADGEM) and two climate change scenarios (RCP 4.5 and 8.5). A total of nineteen spatially rarefied occurrences for M. walkerae and ten non-highly correlated bioclimatic variables were inputted to the maximum entropy algorithm (MaxEnt) to produce twenty replicates per scenario. The area under the curve (AUC) value for the consensus model was higher than 0.90 and the partial ROC value was higher than 1.80, indicating a high predictive ability. The potential reduction in geographic distribution for M. walkerae by the effect of climate change was variable throughout the models, but collectively they predict a restriction in distribution. The most severe reductions were 9% for the year 2050 with the CM3 model at an 8.5 RCP, and 14% for the year 2070 with the CMIP5 model at the 4.5 RCP. The future geographic distribution of M. walkerae was overlapped with protected lands in the U.S. and Mexico in order to identify areas that could be suitable for future conservation efforts. In the U.S. there are several protected areas that are potentially suitable for M. walkerae, whereas in Mexico no protected areas exist within M. walkerae suitable habitat.

Shifts in potential geographical distribution of Pterocarya stenoptera under climate change scenarios in China

Climate change poses a serious threat to biodiversity. Predicting the effects of climate change on the distribution of a species' habitat can help humans address the potential threats which may change the scope and distribution of species. Pterocarya stenoptera is a common fast-growing tree species often used in the ecological restoration of riverbanks and alpine forests in central and eastern China. Until now, the characteristics of the distribution of this species' habitat are poorly known as are the environmental factors that influence its preferred habitat. In the present study, the Maximum Entropy Modeling (Maxent) algorithm and the Genetic Algorithm for Ruleset Production (GARP) were used to establish the models for the potential distribution of this species by selecting 236 sites with known occurrences and 14 environmental variables. The results indicate that both models have good predictive power. Minimum temperature of coldest month (Bio6), mean temperature of warmest quarter (Bio10), annual precipitation (Bio12), and precipitation of driest month (Bio14) were important environmental variables influencing the prediction of the Maxent model. According to the models, the temperate and subtropical regions of eastern China had high environmental suitability for this species, where the species had been recorded. Under each climate change scenario, climatic suitability of the existing range of this species increased, and its climatic niche expanded geographically to the north and higher elevation. GARP predicted a more conservative expansion. The projected spatial and temporal patterns of P. stenoptera can provide reference for the development of forest management and protection strategies.

Habitat patches for newts in the face of climate change: local scale assessment combining niche modelling and graph theory

Triturus cristatus and Triturus marmoratus are two protected and declining newts occurring in the administrative department of Vienne, in France. They have limited dispersal abilities and rely on the connectivity between habitats and their suitability. In a warming climate, the locations of suitable habitats are expected to change, as is the connectivity. Here, we wondered how climate change might affect shifts in habitat suitability and connectivity of habitat patches, as connectivity is a key element enabling species to realize a potential range shift. We used ecological niche modelling (ENM), combining large-scale climate suitability with local scale, high-resolution habitat features, to identify suitable areas for the two species, under low and high warming scenarios (RCP 2.6 and RCP 8.5). We associated it with connectivity assessment through graph theory. The variable 'small ponds' contributed most to land cover-only ENMs for both species. Projections with climate change scenarios revealed a potential impact of warming on suitable habitat patches for newts, especially for T. cristatus. We observed a decrease in connectivity following a decrease in patch suitability. Our results highlight the important areas for newt habitat connectivity within the study area, and define those potentially threatened by climate warming. We provide information for prioritizing sites for acquisition, protection or restoration, and to advise landscape policies. Our framework is a useful and easily reproducible way to combine global climate requirements of the species with detailed information on species habitats and occurrence when available.

Identifying climate refugia and its potential impact on Tibetan brown bear (Ursus arctos pruinosus) in Sanjiangyuan National Park, China

Climate change has direct impacts on wildlife and future biodiversity protection efforts. Vulnerability assessment and habitat connectivity analyses are necessary for drafting effective conservation strategies for threatened species such as the Tibetan brown bear (Ursus arctos pruinosus). We used the maximum entropy (MaxEnt) model to assess the current (1950-2000) and future (2041-2060) habitat suitability by combining bioclimatic and environmental variables, and identified potential climate refugia for Tibetan brown bears in Sanjiangyuan National Park, China. Next, we selected Circuit model to simulate potential migration paths based on current and future climatically suitable habitat. Results indicate a total area of potential suitable habitat under the current climate scenario of approximately 31,649.46 km2, of which 28,778.29 km2 would be unsuitable by the 2050s. Potentially suitable habitat under the future climate scenario was projected to cover an area of 23,738.6 km2. Climate refugia occupied 2,871.17 km2, primarily in the midwestern and northeastern regions of Yangtze River Zone, as well as the northern region of Yellow River Zone. The altitude of climate refugia ranged from 4,307 to 5,524 m, with 52.93% lying at altitudes between 4,300 and 4,600 m. Refugia were mainly distributed on bare rock, alpine steppe, and alpine meadow. Corridors linking areas of potentially suitable brown bear habitat and a substantial portion of paths with low-resistance value were distributed in climate refugia. We recommend various actions to ameliorate the impact of climate change on brown bears, such as protecting climatically suitable habitat, establishing habitat corridors, restructuring conservation areas, and strengthening monitoring efforts.

Cold spot microrefugia hold the key to survival for Brazil's Critically Endangered Araucaria tree

Brazil's Araucaria tree (Araucaria angustifolia) is an iconic living fossil and a defining element of the Atlantic Forest global biodiversity hotspot. But despite more than two millennia as a cultural icon in southern Brazil, Araucaria is on the brink of extinction, having lost 97% of its extent to 20th-century logging. Although logging is now illegal, 21st-century climate change constitutes a new-but so far unevaluated-threat to Araucaria's future survival. We use a robust ensemble modelling approach, using recently developed climate data, high-resolution topography and fine-scale vegetation maps, to predict the species' response to climate change and its implications for conservation on meso- and microclimate scales. We show that climate-only models predict the total disappearance of Araucaria's most suitable habitat by 2070, but incorporating topographic effects allows potential highland microrefugia to be identified. The legacy of 20th-century destruction is evident-more than a third of these likely holdouts have already lost their natural vegetation-and 21st-century climate change will leave just 3.5% of remnant forest and 28.4% of highland grasslands suitable for Araucaria. Existing protected areas cover only 2.5% of the surviving microrefugia for this culturally important species, and none occur in any designated indigenous territory. Our results suggest that anthropogenic climate change is likely to commit Araucaria to a second consecutive century of significant losses, but targeted interventions could help ensure its survival in the wild.

Identifying potential refugia and corridors under climate change: A case study of endangered Sichuan golden monkey (Rhinopithecus roxellana) in Qinling Mountains, China

Climate change threatens endangered species and challenges current conservation strategies. Effective conservation requires vulnerability assessments for species susceptible to climate change and adaptive strategies to mitigate threats associated with climate. In this paper, we used the Maxent to model the impacts of climate change on habitat suitability of Sichuan golden monkey Rhinopithecus roxellana. Our results showed that (i) suitable habitat for Sichuan golden monkey was predicted to decrease by 37% in 2050s under climate change; (ii) the mean elevations of suitable habitat in the 2050s was estimated to shift 160 m higher; (iii) nature reserves protect 62% of current suitable habitat and 56% of future suitable habitat; and (iv) 49% of current suitable habitat was predicted to be vulnerable to future climate change. Given these results, we proposed conservation implications to mitigate the impacts of climate change on Sichuan golden monkey, including adjusting range of national park, establishing habitat corridors, and conducting long‐term monitoring.

Research applications of primary biodiversity databases in the digital age

Our world is in the midst of unprecedented change-climate shifts and sustained, widespread habitat degradation have led to dramatic declines in biodiversity rivaling historical extinction events. At the same time, new approaches to publishing and integrating previously disconnected data resources promise to help provide the evidence needed for more efficient and effective conservation and management. Stakeholders have invested considerable resources to contribute to online databases of species occurrences. However, estimates suggest that only 10% of biocollections are available in digital form. The biocollections community must therefore continue to promote digitization efforts, which in part requires demonstrating compelling applications of the data. Our overarching goal is therefore to determine trends in use of mobilized species occurrence data since 2010, as online systems have grown and now provide over one billion records. To do this, we characterized 501 papers that use openly accessible biodiversity databases. Our standardized tagging protocol was based on key topics of interest, including: database(s) used, taxa addressed, general uses of data, other data types linked to species occurrence data, and data quality issues addressed. We found that the most common uses of online biodiversity databases have been to estimate species distribution and richness, to outline data compilation and publication, and to assist in developing species checklists or describing new species. Only 69% of papers in our dataset addressed one or more aspects of data quality, which is low considering common errors and biases known to exist in opportunistic datasets. Globally, we find that biodiversity databases are still in the initial stages of data compilation. Novel and integrative applications are restricted to certain taxonomic groups and regions with higher numbers of quality records. Continued data digitization, publication, enhancement, and quality control efforts are necessary to make biodiversity science more efficient and relevant in our fast-changing environment.

Phylogeography and ecological niche modeling unravel the evolutionary history of the Yarkand hare, Lepus yarkandensis (Mammalia: Leporidae), through the Quaternary

Background

The Taklimakan Desert in China is characterized by unique geological and historical dynamics and endemic flora and fauna, but the influence of historical climate oscillations on the evolutionary history of endemic animals is poorly understood. Lepus yarkandensis is an oases-dependent Near Threatened species that lives in fragmented oasis habitats in the Taklimakan Desert, China. We investigated the geological and climatic impacts on its geographical differentiation, demographic history and influence of Pleistocene glacial-interglacial cycles on the evolutionary history of L. yarkandensis. Further, studied the impact of climatic oscillation based modification on phylogeography, distribution and diversification pattern of Yarkand hare by using Cytb (1140 bp), MGF (592 bp) and SPTBN1 (619 bp) markers. Ecological niche modeling (ENM) revealed the evolutionary history of this species in response to climate change during the Quaternary. Paleodistribution modeling was used to identify putative refugia and estimate their historical distributions.

Results

Both historical demographic analyses and climatic niche modeling revealed strong effects of glacial climate changes, suggesting recurrent range contractions and expansions. The EBSP results indicated clear population expansion of L. yarkandensis since the Pleistocene. In the “early Pleistocene”, the demographic expansion continued from 0.83 MYA to the last glacial period. The ENM analysis supported a wide distribution of Lepus yarkandensis at high altitudes during the last interglacial (LIG) period. During the last glacial maximum (LGM), the suitable climate was reduced and restricted to the western part of the Taklimakan Desert.

Conclusions

Inland aridification, oasis evolution and river flow played major roles in the population differentiation and demographic history of Yarkand hares. Historically, the large, continuous oases in the Taklimakan Desert contained a viable and unique population of L. yarkandensis. The fragmented desert environment might have caused low gene flow between individuals or groups, thus leading to predominant genetic differentiation. The Pleistocene climatic cycles triggered the diversification and expansion of this species during cold and warm periods, respectively, leading to multiple colonization events within the Taklimakan Desert. These events might be due to the expansion of the Taklimakan Desert during the Middle Pleistocene. Yarkand hare previously occupied vast areas at low and intermediate altitudes in Xinjiang, Gansu, Shanxi, Henan and Shaanxi Provinces in China. The past aridification, climate change-induced oasis modifications, changes in river volumes and flow directions, and human activities all affected the population demography and phylogeography of the Yarkand hare.

Electronic supplementary material

The online version of this article (10.1186/s12862-019-1426-z) contains supplementary material, which is available to authorized users.

Distributional responses to climate change for alpine species of Cyananthus and Primula endemic to the Himalaya-Hengduan Mountains

Global warming increases the vulnerability of plants, especially alpine herbaceous species, to local extinction. In this study, we collected species distribution information from herbarium specimens for ten selected Cyananthus and Primula alpine species endemic to the Himalaya-Hengduan Mountains (HHM). Combined with climate data from WorldClim, we used Maximum Entropy Modeling (MaxEnt) to project distributional changes from the current time period to 2070. Our predictions indicate that, under a wide range of climate change scenarios, the distributions of all species will shift upward in elevation and northward in latitude; furthermore, under these scenarios, species will expand the size of their range. For the majority of the species in this study, habitats are available to mitigate upward and northward shifts that are projected to be induced by changing climate. If current climate projections, however, increase in magnitude or continue to increase past our projection dates, suitable habitat for future occupation by alpine species will be limited as we predict range contraction or less range expansion for some of the species under more intensified climate scenarios. Our study not only underscores the value of herbarium source information for future climate model projections but also suggests that future studies on the effects of climate change on alpine species should include additional biotic and abiotic factors to provide greater resolution of the local dynamics associated with species persistence under a warming climate.

Risk of biodiversity collapse under climate change in the Afro-Arabian region

For 107 endemic mammal species in the Afro-Arabian region, Sahara-Sahel and Arabian Desert, we used ensemble species distribution models to: (1) identify the hotspot areas for conservation, (2) assess the potential impact of the projected climate change on the distribution of the focal species, and (3) assign IUCN threat categories for the focal species according to the predicted changes in their potential distribution range. We identified two main hotspot areas for endemic mammals: the Sinai and its surrounding coastal area in the East, and the Mediterranean Coast around Morocco in the West. Alarmingly, our results indicate that about 17% of the endemic mammals in the Afro-Arabian region under the current climate change scenarios could go extinct before 2050. Overall, a substantial number of the endemic species will change from the IUCN threat category “Least Concern” to “Critically Endangered” or “Extinct” in the coming decades. Accordingly, we call for implementing an urgent proactive conservation action for these endemic species, particularly those that face a high risk of extinction in the next few years. The results of our study provide conservation managers and practitioners with the required information for implementing an effective conservation plan to protect the biodiversity of the Afro-Arabian region.

Assessing the multi-scale predictive ability of ecosystem functional attributes for species distribution modelling

Global environmental changes are rapidly affecting species' distributions and habitat suitability worldwide, requiring a continuous update of biodiversity status to support effective decisions on conservation policy and management. In this regard, satellite-derived Ecosystem Functional Attributes (EFAs) offer a more integrative and quicker evaluation of ecosystem responses to environmental drivers and changes than climate and structural or compositional landscape attributes. Thus, EFAs may hold advantages as predictors in Species Distribution Models (SDMs) and for implementing multi-scale species monitoring programs. Here we describe a modelling framework to assess the predictive ability of EFAs as Essential Biodiversity Variables (EBVs) against traditional datasets (climate, land-cover) at several scales. We test the framework with a multi-scale assessment of habitat suitability for two plant species of conservation concern, both protected under the EU Habitats Directive, differing in terms of life history, range and distribution pattern (Iris boissieri and Taxus baccata). We fitted four sets of SDMs for the two test species, calibrated with: interpolated climate variables; landscape variables; EFAs; and a combination of climate and landscape variables. EFA-based models performed very well at the several scales (AUCmedian from 0.881±0.072 to 0.983±0.125), and similarly to traditional climate-based models, individually or in combination with land-cover predictors (AUCmedian from 0.882±0.059 to 0.995±0.083). Moreover, EFA-based models identified additional suitable areas and provided valuable information on functional features of habitat suitability for both test species (narrowly vs. widely distributed), for both coarse and fine scales. Our results suggest a relatively small scale-dependence of the predictive ability of satellite-derived EFAs, supporting their use as meaningful EBVs in SDMs from regional and broader scales to more local and finer scales. Since the evaluation of species' conservation status and habitat quality should as far as possible be performed based on scalable indicators linking to meaningful processes, our framework may guide conservation managers in decision-making related to biodiversity monitoring and reporting schemes.

Australian wheat production expected to decrease by the late 21st century

Climate change threatens global wheat production and food security, including the wheat industry in Australia. Many studies have examined the impacts of changes in local climate on wheat yield per hectare, but there has been no assessment of changes in land area available for production due to changing climate. It is also unclear how total wheat production would change under future climate when autonomous adaptation options are adopted. We applied species distribution models to investigate future changes in areas climatically suitable for growing wheat in Australia. A crop model was used to assess wheat yield per hectare in these areas. Our results show that there is an overall tendency for a decrease in the areas suitable for growing wheat and a decline in the yield of the northeast Australian wheat belt. This results in reduced national wheat production although future climate change may benefit South Australia and Victoria. These projected outcomes infer that similar wheat-growing regions of the globe might also experience decreases in wheat production. Some cropping adaptation measures increase wheat yield per hectare and provide significant mitigation of the negative effects of climate change on national wheat production by 2041-2060. However, any positive effects will be insufficient to prevent a likely decline in production under a high CO₂ emission scenario by 2081-2100 due to increasing losses in suitable wheat-growing areas. Therefore, additional adaptation strategies along with investment in wheat production are needed to maintain Australian agricultural production and enhance global food security. This scenario analysis provides a foundation towards understanding changes in Australia's wheat cropping systems, which will assist in developing adaptation strategies to mitigate climate change impacts on global wheat production.

Ecological niche modeling for a cultivated plant species: a case study on taro (Colocasia esculenta) in Hawaii

Under the threat of ongoing and projected climate change, communities in the Pacific Islands face challenges of adapting culture and lifestyle to accommodate a changing landscape. Few models can effectively predict how biocultural livelihoods might be impacted. Here, we examine how environmental and anthropogenic factors influence an ecological niche model (ENM) for the realized niche of cultivated taro (Colocasia esculenta) in Hawaii. We created and tuned two sets of ENMs: one using only environmental variables, and one using both environmental and cultural characteristics of Hawaii. These models were projected under two different Intergovernmental Panel on Climate Change (IPCC) Representative Concentration Pathways (RCPs) for 2070. Models were selected and evaluated using average omission rate and area under the receiver operating characteristic curve (AUC). We compared optimal model predictions by comparing the percentage of taro plots predicted present and measured ENM overlap using Schoener's D statistic. The model including only environmental variables consisted of 19 Worldclim bioclimatic variables, in addition to slope, altitude, distance to perennial streams, soil evaporation, and soil moisture. The optimal model with environmental variables plus anthropogenic features also included a road density variable (which we assumed as a proxy for urbanization) and a variable indicating agricultural lands of importance to the state of Hawaii. The model including anthropogenic features performed better than the environment-only model based on omission rate, AUC, and review of spatial projections. The two models also differed in spatial projections for taro under anticipated future climate change. Our results demonstrate how ENMs including anthropogenic features can predict which areas might be best suited to plant cultivated species in the future, and how these areas could change under various climate projections. These predictions might inform biocultural conservation priorities and initiatives. In addition, we discuss the incongruences that arise when traditional ENM theory is applied to species whose distribution has been significantly impacted by human intervention, particularly at a fine scale relevant to biocultural conservation initiatives.

How complex should models be? Comparing correlative and mechanistic range dynamics models

Criticism has been levelled at climate-change-induced forecasts of species range shifts that do not account explicitly for complex population dynamics. The relative importance of such dynamics under climate change is, however, undetermined because direct tests comparing the performance of demographic models vs. simpler ecological niche models are still lacking owing to difficulties in evaluating forecasts using real-world data. We provide the first comparison of the skill of coupled ecological-niche-population models and ecological niche models in predicting documented shifts in the ranges of 20 British breeding bird species across a 40-year period. Forecasts from models calibrated with data centred on 1970 were evaluated using data centred on 2010. We found that more complex coupled ecological-niche-population models (that account for dispersal and metapopulation dynamics) tend to have higher predictive accuracy in forecasting species range shifts than structurally simpler models that only account for variation in climate. However, these better forecasts are achieved only if ecological responses to climate change are simulated without static snapshots of historic land use, taken at a single point in time. In contrast, including both static land use and dynamic climate variables in simpler ecological niche models improve forecasts of observed range shifts. Despite being less skilful at predicting range changes at the grid-cell level, ecological niche models do as well, or better, than more complex models at predicting the magnitude of relative change in range size. Therefore, ecological niche models can provide a reasonable first approximation of the magnitude of species' potential range shifts, especially when more detailed data are lacking on dispersal dynamics, demographic processes underpinning population performance, and change in land cover.