Predicting species distributions for conservation decisions

Unravelling the impact of soil data quality on species distribution models of temperate forest woody plants

Soil properties influence plant physiology and growth, playing a fundamental role in shaping species niches in temperate forest ecosystems. Here, we investigated the impact of soil data quality on the performance of species distribution models (SDMs) of 41 woody plant species in Swiss forests. We compared models based on measured soil properties with those based on digitally mapped soil properties on regional (Swiss Forest Soil Maps) and global scales (SoilGrids). We first calibrated topo-climatic SDMs with measured soil data and plant species presences and absences from mature temperate forest stand plots. We developed further models using the same soil predictors, but with values extracted from digital soil maps at the nearest neighbouring plots of the Swiss National Forestry Inventory. The predictive power of SDMs without soil information compared to those with soil information, as well as measured soil information vs digitally mapped, was evaluated with metrics of model performance and variable contribution. On average, models with measured and digitally mapped soil properties performed significantly better than those without soil information. SDMs based on measured and Swiss Forest Soil Maps showed higher performance, especially for species with an 'extreme' niche position (e.g., preference for high or low pH), compared to those using SoilGrids. Nevertheless, if no regional soil maps are available, SoilGrids should be tested for their potential to improve SDMs. Moreover, among the tested soil predictors, pH, and clay content of the topsoil layers most improved the predictive power of SDMs for forest woody plants. In conclusion, we demonstrate the value of regional soil maps for predicting the distribution of woody species across strong environmental gradients in temperate forests. The improved accuracy of SDMs and insights into drivers of distribution may support forest managers in strategies supporting e.g. biodiversity conservation, or climate adaptation planning.

Contrasting range changes and drivers of four forest foundation species under future climate change in China

Forest foundation species, vital for shaping community structure and dynamics through non-trophic level interactions, are key to forest succession and sustainability. Despite their ecological importance, the habitat ranges of these species in China and their responses to future climate change remain unclear. Our study employed the optimal MaxEnt model to assess the range shifts and their essential drivers of four typical forest foundation species from three climatic zones in China under climate scenarios, including Acer tegmentosum, Acer pseudo-sieboldianum (temperate zone), Quercus glandulifera (subtropical zone), and Ficus hispida (tropical zone). The optimal MaxEnt model exhibited high evaluation indices (AUC values > 0.90) for the four foundation species, indicating excellent predictive performance. Currently, we observed that A. tegmentosum and A. pseudo-sieboldianum are predominantly inhabited temperate forest areas in northeastern China, Q. glandulifera is primarily concentrated in subtropical forests in southeastern China, and F. hispida is mainly distributed across the tropical forests in southern China. Climate factors, particularly temperature, emerged as the primary environmental factors influencing the potential range of forest foundation species. Moreover, precipitation strongly influenced the potential range of A. tegmentosum and A. pseudo-sieboldianum, while elevation exhibited a greater impact on the range of Q. glandulifera and F. hispida. Under future climate scenarios, suitable areas for A. tegmentosum and A. pseudo-sieboldianum tend to expand southward, F. hispida tends to expand northward, while Q. glandulifera exhibited a tendency to contract towards the center. This study advances our understanding of the spatial and temporal dynamics of forest foundation species in China under climate change, providing critical insights for conservation efforts and sustainable forest management practices.

Pushing the envelope: do narrowly and widely distributed Eucalyptus species differ in response to climate warming?

Contemporary climate change will push many tree species into conditions that are outside their current climate envelopes. Using the Eucalyptus genus as a model, we addressed whether species with narrower geographical distributions show constrained ability to cope with warming relative to species with wider distributions, and whether this ability differs among species from tropical and temperate climates. We grew seedlings of widely and narrowly distributed Eucalyptus species from temperate and tropical Australia in a glasshouse under two temperature regimes: the summer temperature at seed origin and +3.5°C. We measured physical traits and leaf-level gas exchange to assess warming influences on growth rates, allocation patterns, and physiological acclimation capacity. Warming generally stimulated growth, such that higher relative growth rates early in development placed seedlings on a trajectory of greater mass accumulation. The growth enhancement under warming was larger among widely than narrowly distributed species and among temperate rather than tropical provenances. The differential growth enhancement was primarily attributable to leaf area production and adjustments of specific leaf area. Our results suggest that tree species, including those with climate envelopes that will be exceeded by contemporary climate warming, possess capacity to physiologically acclimate but may have varying ability to adjust morphology.

Policy analysis for informing climate adaptation, environmental resilience, and irrigation demands in the Rio Grande Basin

Water policymakers internationally face the challenge of adapting to climate, supporting environmental resource needs, and meeting irrigation demands for food security in the world's arid and semi-arid regions. Much recent work has assessed the economic performance of environmental river flows to support endangered species habitat protection. However, little published work to date has systematically formulated and applied methods to identify the economic performance of various policy measures that adapt to climate, support endangered species, and meet irrigation demands for water. This work's original contribution with international relevance is to address those gaps by identifying the economic performance of various water shortage sharing methods for handling climate water stress while supporting protection of critical habitat to protect the endangered Southwestern willow flycatcher (Empidonax traillii extimus) along with Willow tree (Salix bonplandiana) habitat in the middle part of the Rio Grande Basin in North America, a region facing a number of conflicts between commercial uses of water and protection of key ecological assets. It develops a hydroeconomic optimization model containing information on crop water use and endangered species requirements in that region to identify the economic performance of three climate adaptation policy scenarios for handling water shortages while respecting endangered species habitat protection requirements. Results show how water shortages as well as policy responses for handing those shortages affect the economic value of water in agriculture for food security both with and without critical habitat to support the endangered flycatcher. This work's international relevance comes from its capacity to inform policy debates on the costs of protecting endangered species habitat under various climate scenarios and climate policy adaptation measures. Findings provide a general framework to address existing gaps in understanding and measuring the economic performance of measures to promote environmental resilience.

Big-brained alien birds tend to occur climatic niche shifts through enhanced behavioral innovation

Identifying climatic niche shift and its influencing factors is of great significance in predicting the risk of alien species invasions accurately. Previous studies have attempted to identify the factors related to the niche shift of alien species in their invaded ranges, including changes in introduction history, selection of exact climate predictors, and anthropogenic factors. However, the effect of species-level traits on niche shift remains largely unexplored, especially those reflecting the species' adaptation ability to new environments. Based on the occurrence data of 117 successful alien bird invaders at a global scale, their native and invaded climatic niches were compared, and the potential influencing factors were identified. Our results show the niche overlap was low, with more than 75% of the non-native birds representing climatic niche shift (i.e. >10% niche expansion). In addition, 85% of the species showed a large proportion (mean ± SD, 39% ± 21%) of niche unfilling. Relative brain size (RBS) after accounting for body size had no direct effect on niche shift, but path analysis showed that RBS had an indirect effect on niche shift by acting on behavioral innovation primarily on technical innovation rather than consumer innovation. These findings suggested the incorporation of species' important behavioral adaptation traits may be promising to develop future prediction frameworks of biological invasion risk in response to the continued global change.

Predicting suitable habitats for foraging and migration in Eastern Indian Ocean pygmy blue whales from satellite tracking data

BACKGROUND

Accurate predictions of animal occurrence in time and space are crucial for informing and implementing science-based management strategies for threatened species.

METHODS

We compiled known, available satellite tracking data for pygmy blue whales in the Eastern Indian Ocean (n = 38), applied movement models to define low (foraging and reproduction) and high (migratory) move persistence underlying location estimates and matched these with environmental data. We then used machine learning models to identify the relationship between whale occurrence and environment, and predict foraging and migration habitat suitability in Australia and Southeast Asia.

RESULTS

Our model predictions were validated by producing spatially varying accuracy metrics. We identified the shelf off the Bonney Coast, Great Australian Bight, and southern Western Australia as well as the slope off the Western Australian coast as suitable habitat for migration, with predicted foraging/reproduction suitable habitat in Southeast Asia region occurring on slope and in deep ocean waters. Suitable foraging habitat occurred primarily on slope and shelf break throughout most of Australia, with use of the continental shelf also occurring, predominanly in South West and Southern Australia. Depth of the water column (bathymetry) was consistently a top predictor of suitable habitat for most regions, however, dynamic environmental variables (sea surface temperature, surface height anomaly) influenced the probability of whale occurrence.

CONCLUSIONS

Our results indicate suitable habitat is related to dynamic, localised oceanic processes that may occur at fine temporal scales or seasonally. An increase in the sample size of tagged whales is required to move towards developing more dynamic distribution models at seasonal and monthly temporal scales. Our validation metrics also indicated areas where further data collection is needed to improve model accuracy. This is of particular importance for pygmy blue whale management, since threats (e.g., shipping, underwater noise and artificial structures) from the offshore energy and shipping industries will persist or may increase with the onset of an offshore renewable energy sector in Australia.

Using explainable machine learning methods to evaluate vulnerability and restoration potential of ecosystem state transitions

Ecosystem state transitions can be ecologically devastating or be a restoration success. State transitions are common within aquatic systems worldwide, especially considering human-mediated changes to land use and water use. We created a transferable conceptual framework to enable multiscale assessments of state resilience and early warnings of state transitions that can inform strategic restorations and avoid ecosystem collapse. The conceptual framework integrated machine learning predictions with ecosystem state concepts (e.g., state classification, gradients of vulnerability, and recovery potential leading to state transitions) and was devised to investigate possible environmental drivers. As an application of the framework, we generated prediction probabilities of submersed aquatic vegetation (SAV) presence at nearly 10,000 sites in the Upper Mississippi River (United States). Then, we used an interpretability method to explain model predictions to gain insights into possible environmental drivers and thresholds or linear responses of SAV presence and absence. Model accuracy was 89% without spatial bias. Average water depth, suspended solids, substrate, and distance to nearest SAV were the best predictors and likely environmental drivers of SAV habitat suitability. These environmental drivers exhibited nonlinear, threshold-type responses for SAV. All the results are also presented in an online dashboard to explore results at many spatial scales. The habitat suitability model outputs and prediction explanations from many spatial scales (4 m to 400 km of river reach) can inform research and restoration planning.

Identification of potential suitable areas and conservation priority areas for representative wild animals in the Greater and Lesser Khingan Mountains

Species geographic distribution and conservation priority areas are important bases for in situ biodiversity conservation and conservation decision-making. In view of the urgency of endangered species protection, eight representative endangered species in the typical forest ecosystem of the Greater and Lesser Khingan Mountains were studied. Based on 1127 occurrence points and environmental data collected from 2016 to 2021, used BIOMOD2 and Zonation to reconstruct the potential distribution area and identify conservation priority areas of eight species (Tetrao parvirostris, T. tetrix, Gulo gulo, Alces alces, Martes zibellina, Moschus moschiferus, Lynx lynx, Lutra lutra). The results showed potential distribution areas for almost all species concentrated in the northern part of the Greater Khingan Mountains (GKM) and the central part of the Lesser Khingan Mountains (LKM). The potential distribution areas of each species were as follows: black-billed capercaillie, 102,623 km2; black grouse, 162,678 km2; wolverine, 63,410 km2; moose, 140,287 km2; sable, 112,254 km2; Siberian musk deer, 104,787 km2; lynx, 139,912 km2; and Eurasian otter, 49,386 km2. Conservation priority areas (CPAs) clustered in the north GKM and central LKM and totaled 220,801 km2, and only 16.94% of the CPAs were currently protected by nature reserves. We suggest that the Chinese government accelerate the integration of existing protected areas in the northern GKM and establish a larger GKM National Park based on cost-effective multi-species protection.

Fitting individual-based models of spatial population dynamics to long-term monitoring data

Generating spatial predictions of species distribution is a central task for research and policy. Currently, correlative species distribution models (cSDMs) are among the most widely used tools for this purpose. However, a fundamental assumption of cSDMs, that species distributions are in equilibrium with their environment, is rarely fulfilled in real data and limits the applicability of cSDMs for dynamic projections. Process-based, dynamic SDMs (dSDMs) promise to overcome these limitations as they explicitly represent transient dynamics and enhance spatiotemporal transferability. Software tools for implementing dSDMs are becoming increasingly available, but their parameter estimation can be complex. Here, we test the feasibility of calibrating and validating a dSDM using long-term monitoring data of Swiss red kites (Milvus milvus). This population has shown strong increases in abundance and a progressive range expansion over the last decades, indicating a nonequilibrium situation. We construct an individual-based model using the RangeShiftR modeling platform and use Bayesian inference for model calibration. This allows the integration of heterogeneous data sources, such as parameter estimates from published literature and observational data from monitoring schemes, with a coherent assessment of parameter uncertainty. Our monitoring data encompass counts of breeding pairs at 267 sites across Switzerland over 22 years. We validate our model using a spatial-block cross-validation scheme and assess predictive performance with a rank-correlation coefficient. Our model showed very good predictive accuracy of spatial projections and represented well the observed population dynamics over the last two decades. Results suggest that reproductive success was a key factor driving the observed range expansion. According to our model, the Swiss red kite population fills large parts of its current range but has potential for further increases in density. We demonstrate the practicality of data integration and validation for dSDMs using RangeShiftR. This approach can improve predictive performance compared to cSDMs. The workflow presented here can be adopted for any population for which some prior knowledge on demographic and dispersal parameters as well as spatiotemporal observations of abundance or presence/absence are available. The fitted model provides improved quantitative insights into the ecology of a species, which can greatly aid conservation and management efforts.

Regional uniqueness of tree species composition and response to forest loss and climate change

The conservation and restoration of forest ecosystems require detailed knowledge of the native plant compositions. Here, we map global forest tree composition and assess the impacts of historical forest cover loss and climate change on trees. The global occupancy of 10,590 tree species reveals complex taxonomic and phylogenetic gradients determining a local signature of tree lineage assembly. Species occupancy analyses indicate that historical forest loss has significantly restricted the potential suitable range of tree species in all forest biomes. Nevertheless, tropical moist and boreal forest biomes display the lowest level of range restriction and harbor extremely large ranged tree species, albeit with a stark contrast in richness and composition. Climate change simulations indicate that forest biomes are projected to differ in their response to climate change, with the highest predicted species loss in tropical dry and Mediterranean ecoregions. Our findings highlight the need for preserving the remaining large forest biomes while regenerating degraded forests in a way that provides resilience against climate change.

Climate change may reveal currently unavailable parts of species' ecological niches

The ability of climatic niche models to predict species extinction risks can be hampered if niches are incompletely quantified. This can occur when niches are estimated considering only currently available climatic conditions, disregarding the fact that climate change can open up portions of the fundamental niche that are currently inaccessible to species. Using a new metric, we estimate the prevalence of potential situations of fundamental niche truncation by measuring whether current ecological niche limits are contiguous to the boundaries of currently available climatic conditions for 24,944 species at the global scale in both terrestrial and marine realms and including animals and plants. We show that 12,172 (~49%) species are showing niche contiguity, particularly those inhabiting tropical ecosystems and the marine realm. Using niche expansion scenarios, we find that 86% of species showing niche contiguity could have a fundamental niche potentially expanding beyond current climatic limits, resulting in lower-yet still alarming-rates of predicted biodiversity loss, particularly within the tropics. Caution is therefore advised when forecasting future distributions of species presenting niche contiguity, particularly towards climatic limits that are predicted to expand in the future.

Socio-economic variables improve accuracy and change spatial predictions in species distribution models

In an era marked by increasing anthropogenic pressure, understanding the relations between human activities and wildlife is crucial for understanding ecological patterns, effective conservation, and management strategies. Here, we explore the potential and usefulness of socio-economic variables in species distribution modelling (SDM), focusing on their impact on the occurrence of wild mammals in Poland. Beyond the environmental factors commonly considered in SDM, like land-use, the study tests the importance of socio-economic characteristics of local human societies, such as age, income, working sector, gender, education, and village characteristics for explaining distribution of diverse mammalian groups, including carnivores, ungulates, rodents, soricids, and bats. The study revealed that incorporating socio-economic variables enhances the predictive power for >60 % of species and overall for most groups, with the exception being carnivores. For all the species combined, among the 10 predictors with highest predictive power, 6 belong to socio-economic group, while for specific species groups, socio-economic variables had similar predictive power as environmental variables. Furthermore, spatial predictions of species occurrence underwent changes when socio-economic variables were included in the model, resulting in a substantial mismatch in spatial predictions of species occurrence between environment-only models and models containing socio-economic variables. We conclude that socio-economic data has potential as useful predictors which increase prediction accuracy of wildlife occurrence and recommend its wider usage. Further, to our knowledge this is a first study on such a big scale for terrestrial mammals which evaluates performance based on presence or absence of socio-economic predictors in the model. We recognise the need for a more comprehensive approach in SDMs and that bridging the gap between human socio-economic dynamics and ecological processes may contribute to the understanding of the factors influencing biodiversity.

Incidence of the El Niño-Southern Oscillation Cycle on the Existing Fundamental Niche and Establishment Risk of Some Anastrepha Species (Diptera-Tephritidae) of Horticultural Importance in the Neotropics and Panama

To compare the environmental space of four Anastrepha species in different ENSO episodes (El Niño, El Neutro and La Niña), we built ecological niche models with NicheA software. We analysed the fundamental niche and the combined establishment risk maps of these species developed with the ArcGisPro combine geoprocess. A comparison of the ellipsoids that represent the fundamental niche existing for the species showed changes in the El Niño, El Neutro and La Niña episodes. For A. grandis in the El Niño vs. El Neutro episodes, there was a Jaccard index of 0.3841, while the comparison between the La Niña vs. El Neutro episodes presented a Jaccard index of 0.6192. A. serpentina in the El Niño vs. El Neutro and La Niña vs. El Neutro episodes presented Jaccard indices of 0.3281 and 0.6328, respectively. For A. obliqua, the comparison between the El Niño vs. El Neutro and La Niña vs. El Neutro episodes presented Jaccard indices of 0.3518 and 0.7472, respectively. For A. striata, comparisons between the episodes of El Niño vs. El Neutro and La Niña vs. El Neutro presented Jaccard indices of 0.3325 and 0.6022, respectively. When studying the comparison between Anastrepha species and the different ENSO climatic episodes, we found that in the El Niño episode, the comparisons with the best environmental similarity were A. obliqua vs. A. striata and A. obliqua vs. A. serpentina, with higher Jaccard indices (0.6064 and 0.6316, respectively). In the El Neutro episode, the comparisons with the best environmental similarity were A. serpentina vs. A. striata and A. obliqua vs. A. striata, which presented higher Jaccard indices (0.4616 and 0.6411, respectively). In the La Niña episode, the comparisons that presented the best environmental similarity were A. obliqua vs. A. serpentina and A. obliqua vs. A. striata, with higher Jaccard indices (0.5982 and 0.6228, respectively). Likewise, our results present the risk maps for the establishment of these species throughout the Neotropics, allowing us to predict the level of risk in order to develop integrated pest management plans.

Conservation applications of niche modeling: Native and naturalized ferns may compete for limited Hawaiian dryland habitat

Premise

Competition from naturalized species and habitat loss are common threats to native biodiversity and may act synergistically to increase competition for decreasing habitat availability. We use Hawaiian dryland ferns as a model for the interactions between land-use change and competition from naturalized species in determining habitat availability.

Methods

We used fine-resolution climatic variables and carefully curated occurrence data from herbaria and community science repositories to estimate the distributions of Hawaiian dryland ferns. We quantified the degree to which naturalized ferns tend to occupy areas suitable for native species and mapped the remaining available habitat given land-use change.

Results

Of all native species, Doryopteris angelica had the lowest percentage of occurrences of naturalized species in its suitable area while D. decora had the highest. However, all Doryopteris spp. had a higher percentage overlap, while Pellaea ternifolia had a lower percentage overlap, than expected by chance. Doryopteris decora and D. decipiens had the lowest proportions (<20%) of suitable area covering native habitat.

Discussion

Areas characterized by shared environmental preferences of native and naturalized ferns may decrease due to human development and fallowed agricultural lands. Our study demonstrates the value of place-based application of a recently developed correlative ecological niche modeling approach for conservation risk assessment in a rapidly changing and urbanized island ecosystem.

Data-centric species distribution modeling: Impacts of modeler decisions in a case study of invasive European frog-bit

Premise

Species distribution models (SDMs) are widely utilized to guide conservation decisions. The complexity of available data and SDM methodologies necessitates considerations of how data are chosen and processed for modeling to enhance model accuracy and support biological interpretations and ecological applications.

Methods

We built SDMs for the invasive aquatic plant European frog-bit using aggregated and field data that span multiple scales, data sources, and data types. We tested how model results were affected by five modeler decision points: the exclusion of (1) missing and (2) correlated data and the (3) scale (large-scale aggregated data or systematic field data), (4) source (specimens or observations), and (5) type (presence-background or presence-absence) of occurrence data.

Results

Decisions about the exclusion of missing and correlated data, as well as the scale and type of occurrence data, significantly affected metrics of model performance. The source and type of occurrence data led to differences in the importance of specific explanatory variables as drivers of species distribution and predicted probability of suitable habitat.

Discussion

Our findings relative to European frog-bit illustrate how specific data selection and processing decisions can influence the outcomes and interpretation of SDMs. Data-centric protocols that incorporate data exploration into model building can help ensure models are reproducible and can be accurately interpreted in light of biological questions.

Rethinking ecological niches and geographic distributions in face of pervasive human influence in the Anthropocene

Species are distributed in predictable ways in geographic spaces. The three principal factors that determine geographic distributions of species are biotic interactions (B), abiotic conditions (A), and dispersal ability or mobility (M). A species is expected to be present in areas that are accessible to it and that contain suitable sets of abiotic and biotic conditions for it to persist. A species' probability of presence can be quantified as a combination of responses to B, A, and M via ecological niche modeling (ENM; also frequently referred to as species distribution modeling or SDM). This analytical approach has been used broadly in ecology and biogeography, as well as in conservation planning and decision-making, but commonly in the context of 'natural' settings. However, it is increasingly recognized that human impacts, including changes in climate, land cover, and ecosystem function, greatly influence species' geographic ranges. In this light, historical distinctions between natural and anthropogenic factors have become blurred, and a coupled human-natural landscape is recognized as the new norm. Therefore, B, A, and M (BAM) factors need to be reconsidered to understand and quantify species' distributions in a world with a pervasive signature of human impacts. Here, we present a framework, termed human-influenced BAM (Hi-BAM, for distributional ecology that (i) conceptualizes human impacts in the form of six drivers, and (ii) synthesizes previous studies to show how each driver modifies the natural BAM and species' distributions. Given the importance and prevalence of human impacts on species distributions globally, we also discuss implications of this framework for ENM/SDM methods, and explore strategies by which to incorporate increasing human impacts in the methodology. Human impacts are redefining biogeographic patterns; as such, future studies should incorporate signals of human impacts integrally in modeling and forecasting species' distributions.

Habitat Suitability and Determinants for Anatidae in Multi-Watershed Composite Wetlands in Anhui, China

Habitat suitability analysis is essential in habitat and species conservation. Anatidae are known for their migratory behaviour, high population density, and wide distribution range. Understanding their habitat utilzation and influencing factors is crucial in targeted conservation and management. In this study, we collected Anatidae diversity data, including the number of species, through field surveys from October 2021 to March 2022 and thirty habitat variables through an online database in Anhui Province, China. By using MaxEnt, we simulated the habitat suitability of twenty-one Anatidae species, revealing potential distribution sites in Anhui Province. Generalized linear mixed models (GLMM) were employed to identify factors affecting the distribution of geese and ducks. The results showed that high-suitability habitats were predominantly located in the large lakes of the Yangtze River floodplain. The GLMM analysis showed significant correlations between Anatidae richness and altitude, distribution of farmland, and human footprint. In addition, ducks were more sensitive to the human interference factor than geese. In summary, the lakes in the Yangtze River floodplain emerged as the most important Anatidae habitats in Anhui Province due to their abundant wetland resources, flat terrain, and high distribution of farmlands. These findings provide a scientific basis for the development of relevant conservation strategies and measures, aiding in wildlife epidemic monitoring, prevention, and control.

Predicting future climate change impacts on the potential distribution of the black howler monkey (Alouatta pigra): an endangered arboreal primate

Climate change is one of the main factors affecting biodiversity worldwide at an alarming rate. In addition to increases in global extreme weather events, melting of polar ice caps, and subsequent sea level rise, climate change might shift the geographic distribution of species. In recent years, interest in understanding the effects of climate change on species distribution has increased, including species which depend greatly on forest cover for survival, such as strictly arboreal primates. Here, we generate a series of species distribution models (SDMs) to evaluate future projections under different climate change scenarios on the distribution of the black howler monkey (Alouatta pigra), an endemic endangered primate species. Using SDMs, we assessed current and future projections of their potential distribution for three Social Economic Paths (SSPs) for the years 2030, 2050, 2070, and 2090. Specifically, we found that precipitation seasonality (BIO15, 30.8%), isothermality (BIO3, 25.4%), and mean diurnal range (BIO2, 19.7.%) are the main factors affecting A. pigra distribution. The future climate change models suggested a decrease in the potential distribution of A. pigra by projected scenarios (from - 1.23 to - 12.66%). The highly suitable area was the most affected above all in the more pessimist scenario most likely related to habitat fragmentation. Our study provides new insights into the potential future distribution and suitable habitats of Alouatta pigra. Such information could be used by local communities, governments, and non-governmental organizations for conservation planning of this primate species.

Mapping the habitat refugia of Isidella elongata under climate change and trawling impacts to preserve Vulnerable Marine Ecosystems in the Mediterranean

The bamboo-coral Isidella elongata is a key habitat-forming species in the deep Mediterranean Sea. This alcyonacean is listed as an indicator of Vulnerable Marine Ecosystems (VMEs) and as Critically Endangered due to bottom trawling impacts. In this work, a modeling approach was used to predict and map the habitat suitability of I. elongata in the Mediterranean Sea under current environmental conditions. Occurrence data were modeled as a function of environmental parameters. Using climate change scenarios and fishing effort data, the risk of climate change and fisheries impacts on habitat suitability were estimated, and climate refugia were identified. A drastic loss of habitat is predicted, and climate change scenarios suggest a loss of 60% of suitable habitats by 2100. In the central Mediterranean, climate refugia overlapped with active fishing grounds. This study represents the first attempt to identify hot spots for the protection of soft bottom Vulnerable Marine Ecosystems for the entire Mediterranean Sea, and highlights areas most at risk from trawling. This work is relevant to the objectives of the EU Marine Strategy Framework and Maritime Spatial Planning Directives, the Biodiversity Strategy for 2030 regarding priority areas for conservation.

Flood-irrigated agriculture mediates climate-induced wetland scarcity for summering sandhill cranes in western North America

Information about species distributions is lacking in many regions of the world, forcing resource managers to answer complex ecological questions with incomplete data. Information gaps are compounded by climate change, driving ecological bottlenecks that can act as new demographic constraints on fauna. Here, we construct greater sandhill crane (Antigone canadensis tabida) summering range in western North America using movement data from 120 GPS-tagged individuals to determine how landscape composition shaped their distributions. Landscape variables developed from remotely sensed data were combined with bird locations to model distribution probabilities. Additionally, land-use and ownership were summarized within summer range as a measure of general bird use. Wetland variables identified as important predictors of bird distributions were evaluated in a post hoc analysis to measure long-term (1984-2022) effects of climate-driven surface water drying. Wetlands and associated agricultural practices accounted for 1.2% of summer range but were key predictors of occurrence. Bird distributions were structured by riparian floodplains that concentrated wetlands, and flood-irrigated agriculture in otherwise arid and semi-arid landscapes. Findings highlighted the role of private lands in greater sandhill crane ecology as they accounted for 78% of predicted distributions. Wetland drying observed in portions of the range from 1984 to 2022 represented an emerging ecological bottleneck that could limit future greater sandhill crane summer range. Study outcomes provide novel insight into the significance of ecosystem services provided by flood-irrigated agriculture that supported nearly 60% of wetland resources used by birds. Findings suggest greater sandhill cranes function as a surrogate species for agroecology and climate change adaptation strategies seeking to reduce agricultural water use through improved efficiency while also maintaining distinct flood-irrigation practices supporting greater sandhill cranes and other wetland-dependent wildlife. We make our wetland and sandhill crane summering distributions available as interactive web-based mapping tools to inform conservation design.

Mapping multiscale breeding bird species distributions across the United States and evaluating their conservation applications

Species distribution models are vital to management decisions that require understanding habitat use patterns, particularly for species of conservation concern. However, the production of distribution maps for individual species is often hampered by data scarcity, and existing species maps are rarely spatially validated due to limited occurrence data. Furthermore, community-level maps based on stacked species distribution models lack important community assemblage information (e.g., competitive exclusion) relevant to conservation. Thus, multispecies, guild, or community models are often used in conservation practice instead. To address these limitations, we aimed to generate fine-scale, spatially continuous, nationwide maps for species represented in the North American Breeding Bird Survey (BBS) between 1992 and 2019. We developed ensemble models for each species at three spatial resolutions-0.5, 2.5, and 5 km-across the conterminous United States. We also compared species richness patterns from stacked single-species models with those of 19 functional guilds developed using the same data to assess the similarity between predictions. We successfully modeled 192 bird species at 5-km resolution, 160 species at 2.5-km resolution, and 80 species at 0.5-km resolution. However, the species we could model represent only 28%-56% of species found in the conterminous US BBSs across resolutions owing to data limitations. We found that stacked maps and guild maps generally had high correlations across resolutions (median = 84%), but spatial agreement varied regionally by resolution and was most pronounced between the East and West at the 5-km resolution. The spatial differences between our stacked maps and guild maps illustrate the importance of spatial validation in conservation planning. Overall, our species maps are useful for single-species conservation and can support fine-scale decision-making across the United States and support community-level conservation when used in tandem with guild maps. However, there remain data scarcity issues for many species of conservation concern when using the BBS for single-species models.

Double jeopardy: global change and interspecies competition threaten Siberian cranes

Anthropogenic global change is precipitating a worldwide biodiversity crisis, with myriad species teetering on the brink of extinction. The Arctic, a fragile ecosystem already on the frontline of global change, bears witness to rapid ecological transformations catalyzed by escalating temperatures. In this context, we explore the ramifications of global change and interspecies competition on two arctic crane species: the critically endangered Siberian crane (Leucogeranus leucogeranus) and the non-threatened sandhill crane (Grus canadensis). How might global climate and landcover changes affect the range dynamics of Siberian cranes and sandhill cranes in the Arctic, potentially leading to increased competition and posing a greater threat to the critically endangered Siberian cranes? To answer these questions, we integrated ensemble species distribution models (SDMs) to predict breeding distributions, considering both abiotic and biotic factors. Our results reveal a profound divergence in how global change impacts these crane species. Siberian cranes are poised to lose a significant portion of their habitats, while sandhill cranes are projected to experience substantial range expansion. Furthermore, we identify a growing overlap in breeding areas, intensifying interspecies competition, which may imperil the Siberian crane. Notably, we found the Anzhu Islands may become a Siberian crane refuge under global change, but competition with Sandhill Cranes underscores the need for enhanced conservation management. Our study underscores the urgency of considering species responses to global changes and interspecies dynamics in risk assessments and conservation management. As anthropogenic pressures continue to mount, such considerations are crucial for the preservation of endangered species in the face of impending global challenges.

The relationship between the body and air temperature in a terrestrial ectotherm

Ectotherms make up the majority of terrestrial biodiversity, so it is important to understand their potential responses to climate change. Often, models aiming to achieve this understanding correlate species distributions with ambient air temperature. However, this assumes a constant relationship between the air temperature and body temperature, which determines an ectotherm's thermal performance. To test this assumption, we develop and validate a method for retrospective estimation of ectotherm body temperature using heat exchange equations. We apply the model to predict the body temperature of wild field crickets (Gryllus campestris) in Northern Spain for 1985-2019 and compare these values to air temperature. We show that while air temperature impacts ectotherm body temperature, it captures only a fraction of its thermal experience. Solar radiation can increase the body temperature by more than 20°C above air temperature with implications for physiology and behaviour. The effect of solar radiation on body temperature is particularly important given that climate change will alter cloud cover. Our study shows that the impacts of climate change on species cannot be assumed to be proportional only to changing air temperature. More reliable models of future species distributions require mechanistic links between environmental conditions and thermal ecophysiologies of species.

What explains the high island endemicity of Philippine Rafflesia? A species distribution modeling analysis of three threatened parasitic plant species and their hosts

PREMISE

Rafflesia are rare holoparasitic plants. In the Philippines, all but one species are found only on single islands. This study aimed to better understand the factors contributing to this distributional pattern. Specifically, we sought to determine whether narrow environmental tolerances of host and/or parasite species might explain their island endemicity.

METHODS

We used Maxent species distribution modeling to identify areas with suitable habitat for R. lagascae, R. lobata, and R. speciosa and their Tetrastigma host species. These analyses were carried out for current climate conditions and two future climate change scenarios.

RESULTS

Although species distribution models indicated suitable environmental conditions for the Tetrastigma host species in many parts of the Philippines, considerably fewer areas were inferred to have suitable conditions for the three Rafflesia species. Some of these areas are on islands from which they have not been reported. All three species will face significant threats as a result of climate change.

CONCLUSIONS

Our results suggest that limited inter-island dispersibility and/or specific environmental requirements are likely responsible for the current pattern of island endemicity of the three Rafflesia species, rather than environmental requirements of their Tetrastigma host species.

Niche differentiation, reproductive interference, and range expansion

Understanding species distributions and predicting future range shifts requires considering all relevant abiotic factors and biotic interactions. Resource competition has received the most attention, but reproductive interference is another widespread biotic interaction that could influence species ranges. Rubyspot damselflies (Hetaerina spp.) exhibit a biogeographic pattern consistent with the hypothesis that reproductive interference has limited range expansion. Here, we use ecological niche models to evaluate whether this pattern could have instead been caused by niche differentiation. We found evidence for climatic niche differentiation, but the species that encounters the least reproductive interference has one of the narrowest and most peripheral niches. These findings strengthen the case that reproductive interference has limited range expansion and also provide a counterexample to the idea that release from negative species interactions triggers niche expansion. We propose that release from reproductive interference enables species to expand in range while specializing on the habitats most suitable for breeding.

Tracking long-term shifts in non-native freshwater macroinvertebrates across three European countries

Non-native species introductions have been acknowledged as one of the main drivers of freshwater biodiversity decline worldwide, compromising provided ecosystem services and functioning. Despite growing introduction numbers of non-native species, their impacts in conjunction with anthropogenic stressors remain poorly documented. To fill this gap, we studied temporal changes in α (local scale) and γ (regional scale), as well as β (ratio between γ and α) diversity of non-native freshwater macroinvertebrate species in three European countries (the Netherlands, England and Hungary) using long-term time series data of up to 17 years (2003-2019). We further calculated four ecological and four biological trait metrics to identify changes in trait occurrences over time. We found that α and γ diversities of non-native species were increasing across all countries whereas β diversity remained stable. We did not identify any significant changes in any trait metric over time, while the predictors tested (land use, climatic predictors, site-specific factor) were similar across countries (e.g., site characteristics or climatic predictors on non-native species trends). Additionally, we projected trends of α, β, and γ diversity and trait metrics until 2040, which indicated that non-native species will decline across all countries to lower levels except in England for γ diversity and the Netherlands for α diversity where an increase was observed. Thus, our findings indicate shifts in non-native freshwater macroinvertebrate diversity at both local and regional scales in response to the various growing anthropogenic pressures. Our findings underscore the continuous dynamics of non-native species distribution, with the diversity of individual communities and overall landscapes witnessing changes. However, the differentiation in species composition between communities remains unaltered. This could have profound implications for conservation strategies and ecological management in the face of continuously changing biodiversity patterns.

A field-validated ensemble species distribution model of Eriogonum pelinophilum, an endangered subshrub in Colorado, USA

Understanding the suitable habitat of endangered species is crucial for agencies such as the Bureau of Land Management to plan management and conservation. However, few species distribution models are directly validated, potentially limiting their application in management. In preparation for a Species Status Assessment of clay-loving wild buckwheat (Eriogonum pelinophilum), an endangered subshrub found in southwest Colorado, we ran a series of species distribution models to estimate the species' potential occupied habitat and validated these models in the field. A 1-meter resolution digital elevation model derived from LiDAR and a high-resolution geology mapping helped identify biologically relevant characteristics of the species' habitat. We employed a weighted ensemble model based on two Random Forest and one Boosted Regression Tree model, and discrimination performance of the ensemble model was high (AUC-PR = 0.793). We then conducted a systematic field survey of model habitat suitability predictions, during which we discovered 55 new subpopulations of the species and demonstrated that new species observations were strongly associated with model predictions (p < .0001, Cliff's delta = 0.575). We further refined our original models by incorporating the additional species occurrences collected in the field survey, a new explanatory variable, and a more diverse set of models. These iterative changes marginally improved performance of the ensemble model (AUC-PR = 0.825). Direct validation of species distribution models is extremely rare, and our field survey provides strong validation of our model results. This helps increase confidence to utilize predictions in planning. The final model predictions greatly improve the Bureau of Land Management's understanding of the species' habitat and increase our ability to consider potential habitat in planning land use activities such as road development and travel management.

Establishment and Expansion Scenario of Drosophila suzukii (Diptera: Drosophilidae) in Central Brazil

Drosophila suzukii Matsumura (Diptera: Drosophilidae), also known as spotted wing drosophila (SWD), is an important pest that damages various wild and cultivated soft fruits worldwide, especially in the Northern Hemisphere. In Brazil, it occurs mainly in the subtropical climates of the southern and southeastern regions. However, SWD has also been sporadically found in the central region of the country in the natural vegetation of the tropical Brazilian Savanna. In this study, we investigated the occurrence of SWD at the northern limit of its range in South America - the central region of Brazil - by monitoring an established drosophilid community in an orchard located in the Brazilian Federal District. We also investigated the current geographical distribution of this pest in Brazil and its potential geographical distribution using species distribution models under two different future shared socioeconomic pathways scenarios (2040 and 2060, optimist and pessimist). Twenty drosophilid species were detected among the 6,396 captured specimens, most of which are exotic in the Neotropical region. The fly community greatly fluctuated throughout the year, and the highest abundance of SWD (3.5% relative abundance and 1.38 flies/trap/day) was recorded in April during the rainy season. Potential distribution models indicate that suitable areas for SWD spread will decrease in the south and southeast but increase in the central region of Brazil. We recommend continuous SWD monitoring and improving bioclimatic forecast models for mitigating damage to local fruit production.

Potentially suitable distribution areas of Populus euphratica and Tamarix chinensis by MaxEnt and random forest model in the lower reaches of the Heihe River, China

Populus euphratica and Tamarix chinensis play a vital role in windbreak and sand fixation, maintaining species diversity and ensuring community stability. Managing and protecting the P. euphratica and T. chinensis forests in the Heihe River's lower reaches is an urgent issue to maintain the desert region's ecological balance. In this study, based on the distribution points of P. euphratica and T. chinensis species and environmental data, MaxEnt and random forest (RF) models were used to characterize the potential distribution areas of P. euphratica and T. chinensis in the lower reaches of the Heihe River. The results showed that the accuracy of the RF model was much higher than that of the MaxEnt model. Both the RF and MaxEnt models showed that the distance to the river greatly influenced the distribution of P. euphratica and T. chinensis. Furthermore, the RF model predicted significantly larger highly suitable areas for both P. euphratica and T. chinensis than the MaxEnt model. Our study enhances the understanding of the species' spatial distribution, offering valuable insights for practical management and conservation strategies.

Habitat selection of resident and non-resident gray wolves: implications for habitat connectivity

Habitat selection studies facilitate assessing and predicting species distributions and habitat connectivity, but habitat selection can vary temporally and among individuals, which is often ignored. We used GPS telemetry data from 96 Gray wolves (Canis lupus) in the western Great Lakes region of the USA to assess differences in habitat selection while wolves exhibited resident (territorial) or non-resident (dispersing or floating) movements and discuss implications for habitat connectivity. We used a step-selection function (SSF) to assess habitat selection by wolves exhibiting resident or non-resident movements, and modeled circuit connectivity throughout the western Great Lakes region. Wolves selected for natural land cover and against areas with high road densities, with no differences in selection among wolves when resident, dispersing, or floating. Similar habitat selection between resident and non-resident wolves may be due to similarity in environmental conditions, when non-resident movements occur largely within established wolf range rather than near the periphery or beyond the species range. Alternatively, non-resident wolves may travel through occupied territories because higher food availability or lower human disturbance outweighs risks posed by conspecifics. Finally, an absence of differences in habitat selection between resident and non-resident wolf movements may be due to other unknown reasons. We recommend considering context-dependency when evaluating differences in movements and habitat use between resident and non-resident individuals. Our results also provide independent validation of a previous species distribution model and connectivity analysis suggesting most potential wolf habitat in the western Great Lakes region is occupied, with limited connectivity to unoccupied habitat.

Integrating suitable habitat dynamics under typical hydrological regimes as guides for the conservation and restoration of different waterbird groups

The operation of the Three Gorges Project (TGP) has influenced the wetland ecosystems downstream, thereby affecting the distribution of habitats suitable for waterbirds. However, dynamic studies on habitat distribution under different water regimes are lacking. Here, using data from three successive wintering periods representing three typical water regimes, we modelled and mapped the habitat suitability of three waterbird groups in Dongting Lake, which is the first river-connected lake downstream of the TGP, and a crucial wintering ground for waterbirds along the East Asian-Australasian Flyway. The results showed that the spatial pattern of habitat suitability varied among the wintering periods and waterbird groups. The analysis estimated the largest suitable habitat area for the herbivorous/tuber-eating group (HTG) and the insectivorous waterbird group (ING) under a normal water recession pattern, whereas early water recession had a more adverse effect. The suitable habitat area for the piscivorous/omnivorous group (POG) was higher under late water recession than under normal conditions. The ING was the most affected by hydrological changes among the three waterbird groups. Further, we identified the key conservation and potential restoration habitats. The HTG exhibited the largest key conservation habitat area compared to the other two groups, while the ING showed a potential restoration habitat area larger than its key conservation habitat area, indicating its sensitivity to environmental changes. The optimal inundation durations from September 1 to January 20 for HTG, ING and POG were 52 ± 7 d, 68 ± 18 d, and 132 ± 22 d, respectively. Therefore, the water recession starting in mid-October may be favourable for waterbirds in Dongting Lake. Altogether, our results can be used as guidance for prioritising certain management actions for waterbird conservation. Moreover, our study highlighted the importance of considering habitat spatiotemporal variation in highly dynamic wetlands when implementing management practices.

Predicting the spatial expansion of an animal population with presence-only data

Predictive models can improve the efficiency of wildlife management by guiding actions at the local, landscape and regional scales. In recent decades, a vast range of modelling techniques have been developed to predict species distributions and patterns of population spread. However, data limitations often constrain the precision and biological realism of models, which make them less useful for supporting decision-making. Complex models can also be challenging to evaluate, and the results are often difficult to interpret for wildlife management practitioners. There is therefore a need to develop techniques that are appropriately robust, but also accessible to a range of end users. We developed a hybrid species distribution model that utilises commonly available presence-only distribution data and minimal demographic information to predict the spread of roe deer (Capreolus caprelous) in Great Britain. We take a novel approach to representing the environment in the model by constraining the size of habitat patches to the home-range area of an individual. Population dynamics are then simplified to a set of generic rules describing patch occupancy. The model is constructed and evaluated using data from a populated region (England and Scotland) and applied to predict regional-scale patterns of spread in a novel region (Wales). It is used to forecast the relative timing of colonisation events and identify important areas for targeted surveillance and management. The study demonstrates the utility of presence-only data for predicting the spread of animal species and describes a method of reducing model complexity while retaining important environmental detail and biological realism. Our modelling approach provides a much-needed opportunity for users without specialist expertise in computer coding to leverage limited data and make robust, easily interpretable predictions of spread to inform proactive population management.

The Minimal Impact of Anthropogenic Disturbances on the Spatial Activities of Leopard Cats in Xinlong, China

The habitat plays a crucial role in ensuring the survival of wildlife. However, the increasing disturbances caused by human activities present a substantial threat to habitats, especially for species such as the leopard cat (Prionailurus bengalensis), which is a significant small predator. Currently, research on leopard cats predominantly focuses on low-altitude regions within its distribution range, leaving plateau areas understudied. To enhance our understanding of the impact of human disturbances on leopard cat habitats, we undertook a study employing infrared camera trappings to monitor leopard cats' activity in Xinlong of southwestern China between 2015 and 2023. We analyzed the spatial distribution and habitat suitability of the leopard cats by utilizing ensemble species distribution models (ESDMs). Moreover, we employed two-species occupancy models to investigate the spatial interaction between leopard cats and human disturbances. The results indicated that (1) the potential suitable habitat area for leopard cats encompassed approximately 1324.93 km2 (14.3%), primarily located along the banks of Yalong river. (2) The distribution of suitable habitat was predominantly influenced by competitors, specifically the yellow-throated marten (YTM), accounting for 52.4% of the influence, as well as environmental factors such as distance to water (DTW) at 12.0% and terrain roughness index (TRI) at 10.0%. Human interference, including cattle presence (4.6%), distance to road (DTD, 4.9%), and distance to settlement (DTS, 3.5%), had a limited impact on the habitat distribution. (3) Within a 5 km radius, habitat suitability increased with proximity to human settlements. (4) Leopard cats exhibited spatial independence from humans and domestic cattle (species interaction factor (SIF) = 1.00) while avoiding domestic horses (SIF = 0.76 ± 0.03). The relatively minor impact of human disturbances in Xinlong could be attributed to traditional cultural practices safeguarding wildlife and the leopard cat's environmental adaptability. We recommend establishing a novel conservation paradigm based on the living dynamics of wildlife communities in Xinlong, thereby offering a more targeted approach to biodiversity preservation in the future.

Biophysical models accurately characterize the thermal energetics of a small invasive passerine bird

Effective management of invasive species requires accurate predictions of their invasion potential in different environments. By considering species' physiological tolerances and requirements, biophysical mechanistic models can potentially deliver accurate predictions of where introduced species are likely to establish. Here, we evaluate biophysical model predictions of energy use by comparing them to experimentally obtained energy expenditure (EE) and thermoneutral zones (TNZs) for the common waxbill Estrilda astrild, a small-bodied avian invader. We show that biophysical models accurately predict TNZ and EE and that they perform better than traditional time-energy budget methods. Sensitivity analyses indicate that body temperature, metabolic rate, and feather characteristics were the most influential traits affecting model accuracy. This evaluation of common waxbill energetics represents a crucial step toward improved parameterization of biophysical models, eventually enabling accurate predictions of invasion risk for small (sub)tropical passerines.

A Benford's law-based framework to determine the threshold of occurrence sites for species distribution modelling from ecological monitoring databases

The use of data-based species distribution models (SDMs) has increased significantly in recent years. However, studies of determining the minimum requirements of occurrence sites from ecological monitoring datasets used in species distribution modelling remain insufficient. Therefore, this study proposed a framework to determine the threshold of minimum occurrence sites for SDMs by assessing compliance with Benford's law. The compliance test verified that the national-scale freshwater fish monitoring dataset was natural and reliable. Results derived from true skill statistics (TSS) determined the minimum number of occurrence sites for reliable species distribution modelling was 20 with a TSS value of 0.793 and an overall accuracy of 0.804. The Benford compliance test has shown to be a useful tool for swift and efficient evaluation of the reliability of species occurrence datasets, or the determination of the threshold of occurrence sites before species distribution modelling. Further studies regarding the evaluation of this method's transferability to other species and validation using SDM performance are required. Overall, the framework proposed in this study demonstrates that Benford compliance test applied to species monitoring datasets can be used to derive a universal and model-independent minimum occurrence threshold for SDMs.

spatialMaxent: Adapting species distribution modeling to spatial data

Conventional practices in species distribution modeling lack predictive power when the spatial structure of data is not taken into account. However, choosing a modeling approach that accounts for overfitting during model training can improve predictive performance on spatially separated test data, leading to more reliable models. This study introduces spatialMaxent (https://github.com/envima/spatialMaxent), a software that combines state-of-the-art spatial modeling techniques with the popular species distribution modeling software Maxent. It includes forward-variable-selection, forward-feature-selection, and regularization-multiplier tuning based on spatial cross-validation, which enables addressing overfitting during model training by considering the impact of spatial dependency in the training data. We assessed the performance of spatialMaxent using the National Center for Ecological Analysis and Synthesis dataset, which contains over 200 anonymized species across six regions worldwide. Our results show that spatialMaxent outperforms both conventional Maxent and models optimized according to literature recommendations without using a spatial tuning strategy in 80 percent of the cases. spatialMaxent is user-friendly and easily accessible to researchers, government authorities, and conservation practitioners. Therefore, it has the potential to play an important role in addressing pressing challenges of biodiversity conservation.

Distribution patterns of Quercus ilex from the last interglacial period to the future by ecological niche modeling

The plants' geographic distribution is affected by natural or human-induced climate change. Numerous studies at both the global and regional levels currently focus on the potential changes in plant distribution areas. Ecological niche modeling can help predict the likely distribution of species according to environmental variables under different climate scenarios. In this study, we predicted the potential geographic distributions of Quercus ilex L. (holm oak), a keystone species of the Mediterranean ecosystem, for the Last Interglacial period (LIG: ~130 Ka), the Last Glacial Maximum (LGM: ~22 Ka), mid-Holocene (MH: ~6 Ka), and future climate scenarios (Representative Concentration Pathway (RCP) 4.5 and 8.5 scenarios) for 2050-2070 obtained from CCSM4 and MIROC-ESM global climate scenarios respectively. The models were produced with algorithms from the R-package "biomod2" and assessed by AUC of the receiver operating characteristic plot and true skill statistics. Aside from BIOCLIM (SRE), all model algorithms performed similarly and produced projections that are supported by good evaluation scores, although random forest (RF) slightly outperformed all the others. Additionally, distribution maps generated for the past period were validated through a comparison with pollen data acquired from the Neotoma Pollen Database. The results revealed that southern areas of the Mediterranean Basin, particularly coastal regions, served as long-term refugia for Q. ilex, which was supported by fossil pollen data. Furthermore, the models suggest long-term refugia role for Anatolia and we argue that Anatolia may have served as a founding population for the species. Future climate scenarios indicated that Q. ilex distribution varied by region, with some areas experiencing range contractions and others range expands. This study provides significant insights into the vulnerability of the Q. ilex to future climate change in the Mediterranean ecosystem and highlights the crucial role of Anatolia in the species' historical distribution.

Impacts of physiological characteristics and human activities on the species distribution models of orchids taking the Hengduan Mountains as a case

The biogeography research of orchids through species distribution models (SDMs), a vital tool in the biogeography field, is critical to understanding the fundamental geographic distribution patterns and identifying conservation priorities. The correspondence between species occurrence and environmental information is crucial to the model's performance. However, ecological preferences unique to different orchid species, such as their life forms, are often overlooked during the modeling process. This oversight can introduce bias and increase model uncertainty. Additionally, human activities, as an important potential predictor, have not been quantified in any orchid SDMs. Taking the Hengduan Mountains as an example, we preprocessed all orchid species' occurrences based on physiological characteristics. Choosing five spatial factors related to human activities to quantify the interference and enter into models as HI factor. Using different modeling methods (GLM, MaxEnt, and RF) and evaluation indices (AUC, TSS, and Kappa), diverse modeling strategies have been constructed in the study. A double-ranking method has been adopted to select the critical orchid distribution regions. The results showed that classification models based on physiological characteristics significantly improved the model's accuracy while adding the HI factor had the same effect but the absence of enough significance. Suitability maps indicated that highly heterogeneous mountainous areas were vital for the distribution of orchids in the Hengduan Mountains. Different distribution patterns and critical regions existed between various orchid life forms geographically - terrestrial orchids were dominant in the mountain, and mycoherterophical orchids were primarily located in the north, more influenced by vegetation and temperature. Critical regions of epiphytic orchids were in the south due to a greater dependence on precipitation and temperature. These studies are informative for understanding the orchids' geographic distribution patterns in the Hengduan Mountains, promoting conservation and providing references for similar research beyond orchids.

Beyond protected areas: The importance of mixed-use landscapes for the conservation of Sumatran elephants (Elephas maximus sumatranus)

Elephants were once widely distributed across the Indonesian island of Sumatra but now exist in small, isolated populations. Using the best data available on elephant occurrence, we aimed to (a) predict potential habitat suitability for elephants (Elephas maximus sumatranus) across the island of Sumatra and (b) model landscape connectivity among the extant elephant populations. We used direct sightings and indirect observations of elephant signs, as well as six remotely sensed proxies of surface ruggedness, vegetation productivity and structure, and human land use and disturbance, to model habitat suitability in a Google Earth Engine (GEE) environment. We validated the habitat suitability prediction using 10-fold spatial block cross validation and by calculating the area under the precision-recall curve (AUC-PR), sensitivity, and specificity for each model iteration. We also used a geolocation dataset collected from global positioning system (GPS) collars fitted on elephants as an independent validation dataset. Models showed good predictive performance with a mean AUC-PR of 0.73, sensitivity of 0.76, and specificity of 0.68. Greater than 83% of the independent GPS collar geolocations were located in predicted suitable habitat. We found human modification, surface ruggedness, and normalized difference vegetation index to be the most important variables for predicting suitable elephant habitat. Thirty-two percent, or 135,646 km2, of Sumatra's land area was predicted to be suitable habitat, with 43 patches of suitable habitat located across Sumatra. Areas with high connectivity were concentrated in the Riau and North Sumatra provinces. Though our analysis highlights the need to improve the quality of data collected on Sumatran elephants, more suitable habitat remains on Sumatra than is used by known populations. Targeted habitat conservation, especially of the suitable habitat in and around the Lamno, Balai Raja, Tesso Tenggara, Tesso Utara, Bukit Tigapuluh, Seblat, Padang Sugihan, and Bukit Barisan Selatan ranges, may improve the long-term viability of this critically endangered species.

Encounter rate and relative abundance of eight cetaceans off the central Catalan coast (Northwestern Mediterranean sea)

This study provides information on cetacean occurrence in the central Catalan coast (NE Iberian Peninsula), an area characterised by an underwater canyon system. Encounter rates (ER), relative abundances (RA) and seasonality were assessed for eight species. This information was combined with physiographic features of the seafloor to understand their influence on cetacean distribution. Data were collected along 189 surveys from January 2017 to December 2022. In total, 479 sightings of eight species of cetaceans were recorded. Striped, bottlenose and Risso's dolphins and fin whales were the most frequently sighted. ER and RA were similar or higher than in other areas of the Mediterranean Sea. Species were distributed differently according to physiographic features: bottlenose dolphins in coastal waters and Risso's dolphins and fin whales above the Garraf underwater canyon system. These results highlight the importance of the central Catalan coast, particularly the underwater canyon system, for at least four species of cetaceans.

Ultra-sensitive detection of ecologically rare fish from eDNA samples based on the RPA-CRISPR/Cas12a technology

Environmental DNA (eDNA) research holds great promise for improving biodiversity science and conservation efforts by enabling worldwide species censuses in near real-time. Current eDNA methods face challenges in detecting low-abundance ecologically important species. In this study, we used isothermal recombinase polymerase amplification (RPA)-CRISPR/Cas detection to test Ctenopharyngodon idella. RPA-CRISPR-Cas12a detected 6.0 eDNA copies/μL within 35 min. Ecologically rare species were identified in the Three Gorges Reservoir Area (TGRA) using functional distinctiveness and geographical restrictiveness, with seven fish species (9%) classified as potentially ecologically rare including three species in this investigation. RPA-CRISPR/Cas12a-FQ outperformed high-throughput sequencing (HTS) and qPCR in detecting low-abundance eDNA (AUC = 0.883∗∗). A significant linear correlation (R2 = 0.682∗∗) between RPA-CRISPR/Cas12a-FQ and HTS quantification suggests its potential for predicting species abundance and enhancing eDNA-based fish biodiversity monitoring. This study highlights the value of RPA-CRISPR/Cas12a-FQ as a tool for advancing eDNA research and conservation efforts.

Future distribution of the epiphytic leafless orchid (Dendrophylax lindenii), its pollinators and phorophytes evaluated using niche modelling and three different climate change projections

The identification of future refugia for endangered species from the effects of global warming is crucial for improving their conservation. Because climate-driven shifts in ranges and local extinctions can result in a spatial mismatch with their symbiotic organisms, however, it is important to incorporate in niche modelling the ecological partners of the species studied. The aim of this study was to evaluate the effect of climate change on the distribution of suitable niches for the ghost orchid (Dendrophylax lindenii) and its phorophytes and pollinators. Thus, its five species of host trees and three pollen vectors were included in the analysis. Climatic preferences of all the species studied were evaluated. The modelling was based on three different climate change projections and four Shared Socio-economic Pathway trajectories. All the species analysed are characterized by narrow temperature tolerances, which with global warming are likely to result in local extinctions and range shifts. D. lindenii is likely to be subjected to a significant loss of suitable niches, but within a reduced geographical range, both host trees and pollen vectors will be available in the future. Future conservation of this orchid should focus on areas that are likely be suitable for it and its ecological partners.

Matrilineal phylogeny and habitat suitability of the endangered spotted pond turtle (Geoclemys hamiltonii; Testudines: Geoemydidae): a two-dimensional approach to forecasting future conservation consequences

The spotted pond turtle (Geoclemys hamiltonii) is a threatened and less explored species endemic to Bangladesh, India, Nepal, and Pakistan. To infer structural variation and matrilineal phylogenetic interpretation, the present research decoded the mitogenome of G. hamiltonii (16,509 bp) using next-generation sequencing technology. The mitogenome comprises 13 protein-coding genes (PCGs), 22 transfer RNAs (tRNAs), two ribosomal RNAs (rRNAs), and one AT-rich control region (CR) with similar strand symmetry in vertebrates. The ATG was identified as a start codon in most of the PCGs except Cytochrome oxidase subunit 1 (cox1), which started with the GTG codon. The non-coding CR of G. hamiltonii was determined to have a unique structure and variation in different domains and stem-loop secondary structure as compared with other Batagurinae species. The PCGs-based Bayesian phylogeny inferred strong monophyletic support for all Batagurinae species and confirmed the sister relationship of G. hamiltonii with Pangshura and Batagur taxa. We recommend generating more mitogenomic data for other Batagurinae species to confirm their population structure and evolutionary relationships. In addition, the present study aims to infer the habitat suitability and habitat quality of G. hamiltonii in its global distribution, both in the present and future climatic scenarios. We identify that only 58,542 km2 (7.16%) of the total range extent (817,341 km2) is suitable for this species, along with the fragmented habitats in both the eastern and western ranges. Comparative habitat quality assessment suggests the level of patch shape in the western range is higher (71.3%) compared to the eastern range. Our results suggest a massive decline of approximately 65.73% to 70.31% and 70.53% to 75.30% under ssp245 and ssp585 future scenarios, respectively, for the years between 2021-2040 and 2061-2080 compared with the current distribution. The present study indicates that proper conservation management requires greater attention to the causes and solutions to the fragmented distribution and safeguarding of this endangered species in the Indus, Ganges, and Brahmaputra (IGB) river basins.

The Endangered Sardinian Grass Snake: Distribution Update, Bioclimatic Niche Modelling, Dorsal Pattern Characterisation, and Literature Review

The Sardinian grass snake, Natrix helvetica cetti, is an endangered endemic snake subspecies with a restricted and highly fragmented geographic distribution. Information on its ecology and detailed geographic distribution are scarce and may negatively impact on its conservation status. Therefore, a literature review on its taxonomy, morphology, ecology, and conservation is presented here. Moreover, field records from the authors, citizen science and the existing literature provide an updated geographic distribution highlighting its presence within 13 new and 7 historic 10 × 10 km cells. Bioclimatic niche modelling was then applied to explore patterns of habitat suitability and phenotypic variation within N. h. cetti. The geographic distribution of the species was found to be positively correlated with altitude and precipitation values, whereas temperature showed a negative correlation. Taken together, these outcomes may explain the snake's presence, particularly in eastern Sardinia. In addition, analysis of distribution overlap with the competing viperine snake (N. maura) and the urodeles as possible overlooked trophic resources (Speleomantes spp. and Euproctus platycephalus) showed overlaps of 66% and 79%, respectively. Finally, geographical or bioclimatic correlations did not explain phenotypic variation patterns observed in this highly polymorphic taxon. Perspectives on future research to investigate N. h. cetti's decline and support effective conservation measures are discussed.

Mapping suitable habitats for globally endangered raptors in Kenya: Integrating climate factors and conservation planning

Raptors face global threats like electrocution, collisions, and habitat fragmentation. Many species remain understudied, and their distribution patterns are unknown. Understanding their current and future distribution is crucial for conservation. Protecting these top predators requires knowledge of their spatial distribution and environmental influences. This study addresses knowledge gaps in raptor habitats and distributions in Kenya, considering current and future climate changes. Using species distribution models and occurrence data from the Global Biodiversity Information Facility, we evaluated suitable habitats for four endangered Kenyan raptor species: Martial eagle, Secretarybird, Bateleur, and Steppe Eagle. We assessed the impact of climatic predictors on their distribution, considering two climate change scenarios for 2020-2040. Our findings reveal that raptor distribution in Kenya is predominantly concentrated in the southwestern region, extending into the central region of the country. The most significant predictors of raptor species distribution varied for each species, with Steppe eagle and Secretarybird being highly influenced by precipitation during the warmest quarter, Martial eagle being influenced by mean temperature during the driest quarter, and Bateleur being primarily influenced by precipitation during the coldest quarter. When projecting our model into the climate change scenarios for 2020-2040, all species except the Bateleur exhibited a negative range shift. The results of our study suggest that climate change may have adverse impacts on the raptor species examined. In light of these findings, we recommend implementing targeted monitoring and conducting surveys in accordance with our current model predictions. Specifically, our focus should be on monitoring areas that exhibit the highest climate suitability, as these areas are likely to undergo significant shifts in the near future. By conducting regular monitoring and engaging in further research, we can enhance our understanding of these raptor species and gather valuable data to improve the accuracy and reliability of our model predictions.

Modeling the Wintering Habitat Distribution of the Black Stork in Shaanxi, China: A Hierarchical Integration of Climate and Land Use/Land Cover Data

Species distribution models (SDMs) are effective tools for wildlife conservation and management, as they employ the quantification of habitat suitability and environmental niches to evaluate the patterns of species distribution. The utilization of SDMs at various scales in a hierarchical approach can provide additional and complementary information, significantly improving decision-making in local wildlife conservation initiatives. In this study, we considered the appropriate spatial scale and data resolution to execute species distribution modeling, as these factors greatly influence the modeling procedures. We developed SDMs for wintering black storks at both the regional and local scales. At the regional scale, we used climatic and climate-driven land use/land cover (LULC) variables, along with wintering occurrence points, to develop models for mainland China. At the local scale, we used local environmental variables and locally gathered wintering site data to develop models for Shaanxi province. The predictions from both the regional and local models were then combined at the provincial level by overlapping suitable areas based on climatic and local conditions. We compared and evaluated the resulting predictions using seven statistical metrics. The national models provide information on the appropriate climatic conditions for the black stork during the wintering period throughout China, while the provincial SDMs capture the important local ecological factors that influence the suitability of habitats at a finer scale. As anticipated, the national SDMs predict a larger extent of suitable areas compared to the provincial SDMs. The hierarchical prediction approach is considered trustworthy and, on average, yields better outcomes than non-hierarchical methods. Our findings indicate that human-driven LULC changes have a significant and immediate impact on the wintering habitat of the black stork. However, the effects of climate change seem to be reducing the severity of this impact. The majority of suitable wintering habitats lie outside the boundaries of protected areas, highlighting the need for future conservation and management efforts to prioritize addressing these conservation gaps and focusing on the protection of climate refuges.

Modelling the effects of topographic heterogeneity on distribution of Nitraria tangutorum Bobr. species in deserts using LiDAR-data

Microclimate ecology is attracting renewed attention because of its fundamental importance in understanding how organisms respond to climate change. Many hot issues can be investigated in desert ecosystems, including the relationship between species distribution and environmental gradients (e.g., elevation, slope, topographic convergence index, and solar insolation). Species Distribution Models (SDMs) can be used to understand these relationships. We used data acquired from the important desert plant Nitraria tangutorum Bobr. communities and desert topographic factors extracted from LiDAR (Light Detection and Ranging) data of one square kilometer in the inner Mongolia region of China to develop SDMs. We evaluated the performance of SDMs developed with a variety of both the parametric and nonparametric algorithms (Bioclimatic Modelling (BIOCLIM), Domain, Mahalanobi, Generalized Linear Model, Generalized Additive Model, Random Forest (RF), and Support Vector Machine). The area under the receiver operating characteristic curve was used to evaluate these algorithms. The SDMs developed with RF showed the best performance based on the area under curve (0.7733). We also produced the Nitraria tangutorum Bobr. distribution maps with the best SDM and suitable habitat area of the Domain model. Based on the suitability map, we conclude that Nitraria tangutorum Bobr. is more suited to southern part with 0-20 degree slopes at an elevation of approximately 1010 m. This is the first attempt of modelling the effects of topographic heterogeneity on the desert species distribution on a small scale. The presented SDMs can have important applications for predicting species distribution and will be useful for preparing conservation and management strategies for desert ecosystems on a small scale.

Landscape Dynamics and Ecological Risk Assessment of Cold Temperate Forest Moose Habitat in the Great Khingan Mountains, China

The change in habitat pattern is one of the key factors affecting the survival of the moose population. The study of the habitat landscape pattern is the key to protecting the Chinese cold-temperate forest moose population and monitoring the global distribution of moose. Through the ecological risk assessment of the moose habitat landscape pattern in a cold-temperate forest, we hope to assess the strength of habitat resistance under stress factors. This study provides a theoretical basis for the protection of the moose population in the cold-temperate forest in China and the establishment of the cold-temperate forest national park. In the study, the MaxEnt model, landscape index calculation and ecological risk assessment model construction were used to analyze the field survey and infrared camera monitoring data from April 2014 to January 2023. The habitat suitability layer of the moose population in the Nanwenghe National Nature Reserve of the Great Khingan Mountains was calculated, and the range of the moose habitat was divided based on the logical threshold of the model. The landscape pattern index of the moose habitat was calculated by Fragstats software and a landscape ecological risk assessment model was established to analyze the landscape pattern and ecological risk dynamic changes of the moose habitat in 2015 and 2020. The results showed that under the premise of global warming, the habitat landscape contagion index decreased by 4.53 and the split index increased by 4.86 from 2015 to 2020. In terms of ecological risk: the area of low ecological risk areas increased by 0.88%; the area of medium ecological risk areas decreased by 1.11%; and the area of high ecological risk areas increased by 0.23%. The fragmentation risk of the landscape pattern of the moose habitat tends to increase, the preferred patch type is dispersed, the degree of aggregation is low, and the risk of patch type transformation increases. The middle and high ecological risk areas are mainly concentrated in the river area and its nearby forests, showing a fine and scattered distribution. Under the interference of global warming and human activities, the fragmentation trend of the moose habitat in the study area is increasing, and the habitat quality is declining, which is likely to cause moose population migration. For this reason, the author believes that the whole cold temperate forest is likely to face the risk of increasing the transformation trend of dominant patch types in the cold-temperate coniferous forest region mainly caused by global warming, resulting in an increase in the risk of habitat fragmentation. While the distribution range of moose is reduced, it has a significant impact on the diversity and ecological integrity of the whole cold-temperate forest ecosystem. This study provides theoretical references for further research on the impact of climate warming on global species distribution and related studies. It is also helpful for humans to strengthen their protection awareness of forest and river areas and formulate reasonable protection and sustainable development planning of cold-temperate forests. Finally, it provides theoretical references for effective monitoring and protection of cold-temperate forests and moose population dynamics.

Marine spatial planning to solve increasing conflicts at sea: A framework for prioritizing offshore windfarms and marine protected areas

Direct and indirect anthropogenic pressures on biodiversity and ecosystems are expected to lower the provided ecosystem services (ES) in the near future. To limit these impacts, protected areas will be implemented as part of the Post-2020 Global Biodiversity Framework. Simultaneously, as an answer to climate change, renewable energies are being rapidly developed on a worldwide scale, leading to a significant increase in space use in the coming decades. Sharing space is an increasingly complex task, especially because of the high rate of emergence of such competitors for space. In fisheries-dominated socio-ecosystems, acceptability of offshore windfarms (OWFs) and marine protected areas (MPAs) is usually very low, partly due to an underrepresentation of fisheries in spatial plans and poor attention to equity in the spatial distribution of restrictive areas. Here we developed a framework with a marine spatial planning case study in the Bay of Biscay represented by the socio-ecosystem of the Grande Vasière, a mid-shelf mud belt spanning over 21,000 km². We collected biological, environmental, and anthropogenic data to model the distribution of 62 bentho-demersal species, 7 regulating ES layers related to nutrient cycling, life cycle maintenance and food web functioning, as well as provisioning ES of 18 commercial species and 82 fisheries subdivisions. We used these spatial layers and a prioritization algorithm to explore siting scenarios of OWFs and two types of MPAs (benthic and total protection), aimed at conserving species, regulating and provisioning ES, while also ensuring that fisheries are equitably impacted. We demonstrate that equitable scenarios are not necessarily costlier and provide alternative spatial prioritizations. We emphasize the importance of exploring multiple targets with a Shiny app to visualize results and stimulate dialogue among stakeholders and policymakers. Overall, we show how our flexible, inclusive framework with particular attention to equity could be an ideal discussion tool to improve management practices.

Effect of global warming on the potential distribution of a holoparasitic plant (Phelypaea tournefortii): both climate and host distribution matter

Phelypaea tournefortii (Orobanchaceae) primarily occurs in the Caucasus (Armenia, Azerbaijan, Georgia, and N Iran) and Turkey. This perennial, holoparasitic herb is achlorophyllous and possesses one of the most intense red flowers among all plants worldwide. It occurs as a parasite on the roots of several Tanacetum (Asteraceae) species and prefers steppe and semi-arid habitats. Climate change may affect holoparasites both directly through effects on their physiology and indirectly as a consequence of its effects on their host plants and habitats. In this study, we used the ecological niche modeling approach to estimate the possible effects of climate change on P. tournefortii and to evaluate the effect of its parasitic relationships with two preferred host species on the chances of survival of this species under global warming. We used four climate change scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP5-8.5) and three different simulations (CNRM, GISS-E2, INM). We modeled the species' current and future distribution using the maximum entropy method implemented in MaxEnt using seven bioclimatic variables and species occurrence records (Phelypaea tournefortii - 63 records, Tanacetum argyrophyllum - 40, Tanacetum chiliophyllum - 21). According to our analyses, P. tournefortii will likely contract its geographical range remarkably. In response to global warming, the coverage of the species' suitable niches will decrease by at least 34%, especially in central and southern Armenia, Nakhchivan in Azerbaijan, northern Iran, and NE Turkey. In the worst-case scenario, the species will go completely extinct. Additionally, the studied plant's hosts will lose at least 36% of currently suitable niches boosting the range contraction of P. tournefortii. The GISS-E2 scenario will be least damaging, while the CNRM will be most damaging to climate change for studied species. Our study shows the importance of including ecological data in niche models to obtain more reliable predictions of the future distribution of parasitic plants.