Dependence of Europe's most threatened mammals on movement to adapt to climate change.

Current rates of climate change and gloomy climate projections confront managers and conservation planners with the need to integrate climate change into already complex decision-making processes. Predicting and prioritizing climatically stable areas and the areas likely to facilitate adaptive species' range adjustments are important stages in maximizing conservation outcomes and rationalizing future land management. I determined, for the most threatened European terrestrial mammal species, the spatial adaptive trajectories (SATs) of highest expected persistence up to 2080. I devised simple spatial network indices for evaluation of species in those SATs: total persistence; proportion of SATs that offer in situ adaptation (i.e., stable refugia); number of SATs converging in a site; and relationship between SAT convergence and persistence and protected areas, the Natura 2000 and Emerald networks, and areas of low human disturbance. I compared the performance of high-persistence SATs with a scenario in which each species remained in the areas with the best climatic conditions in the baseline period. The 1000 most persistence SATs for each of the 39 species covered one fifth of Europe. The areas with the largest adaptive potential (i.e., high persistence, stability, and SAT convergence) did not always overlap for all the species. Predominantly, these regions were located in southwestern Europe, Central Europe, and Scandinavia, with some occurrences in Eastern Europe. For most species, persistence in the most climatically suitable areas during the baseline period was lower than within SATs, underscoring their reliance on adaptive movements. Importantly, conservation areas (particularly protected areas) covered only minor fractions of species persistence among SATs, and hubs of spatial climate adaptation (i.e., areas of high SAT convergence) were seriously underrepresented in most conservation areas. These results highlight the need to perform analyses on spatial species' dynamics under climate change.

Los mamíferos más amenazados de Europa y su dependencia del movimiento para adaptarse al cambio climático Resumen La tasa actual del cambio climático y las proyecciones climáticas pesimistas confrontan a los gestores y a los planeadores de la conservación con la necesidad de integrar este cambio a la ya de por sí compleja toma de decisiones. La predicción y priorización de áreas con estabilidad climática y áreas con probabilidad de facilitarles ajustes adaptativos de distribución a las especies son etapas importantes para maximizar los resultados de conservación y racionalizar la gestión futura de las tierras. Determiné las trayectorias espaciales adaptativas (TEA) para la mayoría de los mamíferos terrestres más amenazados de Europa con la persistencia esperada más alta hasta el 2080. Diseñé los siguientes índices de redes espaciales simples para la evaluación de especies en aquellas TEA: persistencia total, proporción de TEA que brindan adaptación in situ (refugios estables), número de TEA que convergen en un sitio y relación entre la convergencia de TEA y la persistencia con las áreas protegidas, las redes Natura 2000 y Emerald y las áreas de poca perturbación humana. Comparé el desempeño de las TEA de gran persistencia con un escenario en el que las especies permanecían dentro de las áreas con las mejores condiciones climáticas en el periodo de línea base. Las mil TEA más persistentes para cada una de las 39 especies cubrieron la quinta parte de Europa. Las áreas con el mayor potencial adaptativo (es decir, gran persistencia, estabilidad y convergencia de TEA) no siempre se traslaparon para todas las especies. Estas regiones predominaron en el suroeste de Europa, Europa Central y Escandinavia, con algunas ocurrencias en el este de Europa. Para la mayoría de las especies, la persistencia de las áreas con el mejor clima posible durante el periodo de línea base fue menor que dentro de las TEA, lo que resalta su dependencia por los movimientos adaptativos. Destaca que las áreas de conservación (en particular las áreas protegidas) cubrieron sólo pequeñas fracciones de la persistencia de las especies entre las TEA y los núcleos de adaptación climática (es decir, las áreas de gran convergencia de TEA) contaban con muy poca representación dentro de la mayoría de las áreas de conservación. Estos resultados enfatizan la necesidad de realizar análisis de las dinámicas espaciales de las especies bajo el cambio climático.

Human disturbance increases spatiotemporal associations among mountain forest terrestrial mammal species.

Spatial and temporal associations between sympatric species underpin biotic interactions, structure ecological assemblages, and sustain ecosystem functioning and stability. However, the resilience of interspecific spatiotemporal associations to human activity remains poorly understood, particularly in mountain forests where anthropogenic impacts are often pervasive. Here, we applied context-dependent Joint Species Distribution Models to a systematic camera-trap survey dataset from a global biodiversity hotspot in eastern Himalayas to understand how prominent human activities in mountain forests influence species associations within terrestrial mammal communities. We obtained 10,388 independent detections of 17 focal species (12 carnivores and five ungulates) from 322 stations over 43,163 camera days of effort. We identified a higher incidence of positive associations in habitats with higher levels of human modification (87%) and human presence (83%) compared to those located in habitats with lower human modification (64%) and human presence (65%) levels. We also detected a significant reduction of pairwise encounter time at increasing levels of human disturbance, corresponding to more frequent encounters between pairs of species. Our findings indicate that human activities can push mammals together into more frequent encounters and associations, which likely influences the coexistence and persistence of wildlife, with potential far-ranging ecological consequences.

Predicting the potential risk of Caragana shrub encroachment in the Eurasian steppe under anthropogenic climate change.

Climate change and human activities drive widespread shrub encroachment in global grassland ecosystems, particularly in the Eurasian steppe. Caragana shrubs, the primary contributors to shrub encroachment in this region, play a crucial role in shaping the ecosystem's structure and function. Future changes in the suitable distribution range of Caragana species will directly affect the ecological security and sustainable socio-economic development of the Eurasian steppe ecosystem. We used an ensemble modeling approach to predict Caragana shrub-dominated plant communities' current and future distribution in three major steppe subregions: the Black Sea-Kazakhstan steppe, the Tibetan Plateau steppe, and the Central Asian steppe. We assessed the potential risk of Caragana shrub encroachment by predicting changes in the suitable distribution area of 19 Caragana shrub species under future climate changes. Our research findings suggest that the expansion of Caragana species in different subregions of the Eurasian steppe is influenced by the effects of climate change in various ways. The distribution of Caragana species is primarily influenced by precipitation and temperature, and the global human modification (ghm) has a significant impact on the Central Asian and Tibetan Plateau subregions. Minimal changes are expected in the Black Sea-Kazakhstan subregion, a slight increase on the Tibetan Plateau, and a substantial rise in the Central Asian subregion, which suggests a higher potential risk of Caragana species shrub encroachment in that area. Our research provides valuable insights into the response of Caragana shrub encroachment to changing climates and human activities. It also has implications for the sustainable management of different areas of the vast Eurasian steppe 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.

Can upwelling regions be potential thermal refugia for marine fishes during climate warming?

Species are expected to migrate to higher latitudes as warming intensifies due to anthropogenic climate change since physiological mechanisms have been adapted to maximize fitness under specific temperatures. However, literature suggests that upwellings could act as thermal refugia under climate warming protecting marine ecosystem diversity. This research aimed to predict the effects of climate warming on commercial and non-commercial fish species reported in official Mexican documents (>200 species) based on their thermal niche to observe if upwellings can act as potential thermal refugia. Present (2000-2014) and Representative Concentration Pathway (6.0 and 8.5) scenarios (2040-2050 and 2090-2100) have been considered for this work. Current and future suitability patterns, species distribution, richness, and turnover were calculated using the minimum volume ellipsoids as algorithm. The results in this study highlight that beyond migration to higher latitudes, upwelling regions could protect marine fishes, although the mechanism differed between the innate characteristics of upwellings. Most modeled species (primarily tropical fishes) found refuge in the tropical upwelling in Northern Yucatan. However, the highest warming scenario overwhelmed this region. In contrast, the Baja California region lies within the Eastern Boundary Upwelling Systems. While the area experiences an increase in suitability, the northern regions have a higher upwelling intensity acting as environmental barriers for many tropical species. Conversely, in the southern regions where upwelling is weaker, species tend to congregate and persist even during elevated warming, according to the turnover analysis. These findings suggest that tropicalization in higher latitudes may not be as straightforward as previously assumed. Nevertheless, climate change affects numerous ecosystem features, such as trophic relationships, phenology, and other environmental variables not considered here. In addition, uncertainty still exists about the assumption of increasing intensity of upwelling systems.

Incorporating physiological knowledge into correlative species distribution models minimizes bias introduced by the choice of calibration area.

Correlative species distribution models (SDMs) are important tools to estimate species' geographic distribution across space and time, but their reliability heavily relies on the availability and quality of occurrence data. Estimations can be biased when occurrences do not fully represent the environmental requirement of a species. We tested to what extent species' physiological knowledge might influence SDM estimations. Focusing on the Japanese sea cucumber Apostichopus japonicus within the coastal ocean of East Asia, we compiled a comprehensive dataset of occurrence records. We then explored the importance of incorporating physiological knowledge into SDMs by calibrating two types of correlative SDMs: a naïve model that solely depends on environmental correlates, and a physiologically informed model that further incorporates physiological information as priors. We further tested the models' sensitivity to calibration area choices by fitting them with different buffered areas around known presences. Compared with naïve models, the physiologically informed models successfully captured the negative influence of high temperature on A. japonicus and were less sensitive to the choice of calibration area. The naïve models resulted in more optimistic prediction of the changes of potential distributions under climate change (i.e., larger range expansion and less contraction) than the physiologically informed models. Our findings highlight benefits from incorporating physiological information into correlative SDMs, namely mitigating the uncertainties associated with the choice of calibration area. Given these promising features, we encourage future SDM studies to consider species physiological information where available. Supplementary Information: The online version contains supplementary material available at 10.1007/s42995-024-00226-0.

Spatial distribution of the range-expanding species Seriola fasciata (Bloch, 1793) in Mediterranean Sea: From past to future.

The Mediterranean Sea is a highly susceptible area to climate change, that facilitates the introduction of warm-affinity exotic species, contributing to the expansion of their biogeographical range. One such thermophilic species is the Atlantic fish Seriola fasciata, which has colonised this area over the past three decades. The present study analyzed its spatial distribution in the Mediterranean Sea to identify aggregation areas and dynamics over time, and the environmental predictors influencing its presence. The utilized statistical tools and the Species Distribution Model proved effective in identifying specific spatial and temporal distribution patterns, as well as discerning some environmental variables influencing the species presence, with distinctions recorded between juveniles and adults. S. fasciata was observed to be established in the central Mediterranean, with Fishing Aggregating Devices potentially influencing its presence, particularly of juveniles. Sea floor temperature and habitats emerged as the primary factors driving species distribution. An aggregation area in the Levant Sea, conducive mainly for the adults, was identified and is expected to intensify over time. These findings contribute valuable insights into a relatively understudied species and its presence in the Mediterranean Sea, where climate change is affecting marine biodiversity.

Variable intraspecific response to climate change in a medicinally important African tree species, Vachellia sieberiana (DC.) (paperbark thorn).

Climate change is predicted to disproportionately impact sub-Saharan Africa, with potential devastating consequences on plant populations. Climate change may, however, impact intraspecific taxa differently. The aim of the study was to determine the current distribution and impact of climate change on three varieties of Vachellia sieberiana, that is, var. sieberiana, var. villosa and var. woodii. Ensemble species distribution models (SDMs) were built in "biomod2" using 66, 45, and 137 occurrence records for var. sieberiana, var. villosa, and var. woodii, respectively. The ensemble SDMs were projected to 2041-2060 and 2081-2100 under three general circulation models (GCMs) and two shared socioeconomic pathways (SSPs). The three GCMs were the Canadian Earth System Model version 5, the Institut Pierre-Simon Laplace Climate Model version 6A Low Resolution, and the Model for Interdisciplinary Research on Climate version 6. The suitable habitat of var. sieberiana predominantly occurs in the Sudanian and Zambezian phytochoria while that of var. villosa largely occurs in the Sudanian phytochorion. The suitable habitat of var. woodii mainly occurs in the Zambezian phyotochorion. There is coexistence of var. villosa and var. sieberiana in the Sudanian phytochorion while var. sieberiana and var. woodii coexist in the Zambezian phytochorion. Under SSP2-4.5 in 2041-2060 and averaged across the three GCMs, the suitable habitat expanded by 33.8% and 119.7% for var. sieberiana and var. villosa, respectively. In contrast, the suitable habitat of var. woodii contracted by -8.4%. Similar trends were observed in 2041-2060 under SSP5-8.5 [var. sieberiana (38.6%), var. villosa (139.0%), and var. woodii (-10.4%)], in 2081-2100 under SSP2-4.5 [var. sieberiana (4.6%), var. villosa (153.4%), and var. woodii (-14.4%)], and in 2081-2100 under SSP5-8.5 [var. sieberiana (49.3%), var. villosa (233.4%), and var. woodii (-30.7%)]. Different responses to climate change call for unique management and conservation decisions for the varieties.

Predicting suitable habitat for the endangered tree Ormosia microphylla in China.

Climate change has significantly influenced the growth and distribution of plant species, particularly those with a narrow ecological niche. Understanding climate change impacts on the distribution and spatial pattern of endangered species can improve conservation strategies. The MaxEnt model is widely applied to predict species distribution and environmental tolerance based on occurrence data. This study investigated the suitable habitats of the endangered Ormosia microphylla in China and evaluated the importance of bioclimatic factors in shaping its distribution. Occurrence data and environmental variables were gleaned to construct the MaxEnt model, and the resulting suitable habitat maps were evaluated for accuracy. The results showed that the MaxEnt model had an excellent simulation quality (AUC = 0.962). The major environmental factors predicting the current distribution of O. microphylla were the mean diurnal range (bio2) and precipitation of the driest month (bio14). The current core potential distribution areas were concentrated in Guangxi, Fujian, Guizhou, Guangdong, and Hunan provinces in south China, demonstrating significant differences in their distribution areas. Our findings contribute to developing effective conservation and management measures for O. microphylla, addressing the critical need for reliable prediction of unfavorable impacts on the potential suitable habitats of the endangered species.

Experimental evidence that root-associated fungi improve plant growth at high altitude.

Unravelling how species communities change along environmental gradients requires a dual understanding: the direct responses of the species to their abiotic surroundings and the indirect variation of these responses through biotic interactions. Here, we focus on the interactive relationships between plants and their symbiotic root-associated fungi (RAF) along stressful abiotic gradients. We investigate whether variations in RAF community composition along altitudinal gradients influence plant growth at high altitudes, where both plants and fungi face harsher abiotic conditions. We established a translocation experiment between pairs of Bistorta vivipara populations across altitudinal gradients. To separate the impact of shifting fungal communities from the overall influence of changing abiotic conditions, we used a root barrier to prevent new colonization by RAF following translocation. To characterize the RAF communities, we applied DNA barcoding to the root samples. Through the utilization of joint species distribution modelling, we assessed the relationship between changes in plant functional traits resulting from experimental treatments and the corresponding changes in the RAF communities. Our findings indicate that RAF communities influence plant responses to stressful abiotic conditions. Plants translocated from low to high altitudes grew more when they were able to associate with the resident high-altitude RAF compared to those plants that were not allowed to associate with the resident RAF. We conclude that interactions with RAF impact how plants respond to stressful abiotic conditions. Our results provide experimental support that interactions with RAF improve plant stress tolerance to altitudinal stressors such as colder temperatures and less nutrient availability.

Ecological niche modelling of Culicoides imicola and future range shifts under climate change scenarios in Italy.

Culicoides imicola is the main vector of viral diseases of livestock in Europe such as bluetongue (BT), African horse sickness and epizootic haemorrhagic disease. Climatic factors are the main drivers of C. imicola occurrence and its distribution might be subject to rapid shifts due to climate change. Entomological data, collected during BT surveillance, and climatic/environmental variables were used to analyse ecological niche and to model C. imicola distribution and possible future range shifts in Italy. An ensemble technique was used to weigh the performance of machine learning, linear and profile methods. Updated future climate projections from the latest phase of the Climate Model Intercomparison Project were used to generate future distributions for the next three 20-year periods, according to combinations of general circulation models and shared socioeconomic pathways and considering different climate change scenarios. Results indicated the minimum temperature of the coldest month (BIO 6) and precipitation of the driest-warmest months (BIO 14) as the main limiting climatic factors. Indeed, BIO 6 and BIO 14 reported the two highest values of variable importance, respectively, 9.16% (confidence interval [CI] = 7.99%-10.32%), and 2.01% (CI = 1.57%-2.44%). Under the worst-case scenario of climate change, C. imicola range is expected to expand northward and shift away from the coasts of central Italy, while in some areas of southern Italy, environmental suitability will decrease. Our results provide predictions of C. imicola distribution according to the most up-to-date future climate projections and should be of great use to surveillance management at regional and national scales.

Updated range map of an endangered salamander and congeneric competitor reveals different niche preferences.

Estimating distributions for cryptic and highly range-restricted species induces unique challenges for species distribution modeling. In particular, bioclimatic covariates that are typically used to model species ranges at regional and continental scales may not show strong variation at scales of 100s and 10s of meters. This limits both the likelihood and usefulness of correlated occurrence to data typically used in distribution models. Here, we present analyses of species distributions, at 100 × 100 m resolution, for a highly range restricted salamander species (Shenandoah salamander, Plethodon shenandoah) and a closely related congener (red-backed salamander, Plethodon cinereus). We combined data across multiple survey types, account for seasonal variation in availability of our target species, and control for repeated surveys at locations- all typical challenges in range-scale monitoring datasets. We fit distribution models using generalized additive models that account for spatial covariates as well as unexplained spatial variation and spatial uncertainty. Our model accommodates different survey protocols using offsets and incorporates temporal variation in detection and availability resulting from survey-specific variation in temperature and precipitation. Our spatial random effect was crucial in identifying small-scale differences in the occurrence of each species and provides cell-specific estimates of uncertainty in the density of salamanders across the range. Counts of both species were seen to increase in the 3 days following a precipitation event. However, P. cinereus were observed even in extremely wet conditions, while surface activity of P. shenandoah was associated with a more narrow range. Our results demonstrate how a flexible analytical approach improves estimates of both distribution and uncertainty, and identify key abiotic relationships, even at small spatial scales and when scales of empirical data are mismatched. While our approach is especially valuable for species with small ranges, controlling for spatial autocorrelation, estimating spatial uncertainty, and incorporating survey-specific information in estimates can improve the reliability of distribution models in general.

Potential range shift of a long-distance migratory rice pest, Nilaparvata lugens, under climate change.

The biogeographical range shift of insect pests is primarily governed by temperature. However, the range shift of seasonal long-distance migratory insects may be very different from that of sedentary insects. Nilaparvata lugens (BPH), a serious rice pest, can only overwinter in tropical-to-subtropical regions, and some populations migrate seasonally to temperate zones with the aid of low-level jet stream air currents. This study utilized the CLIMEX model to project the overwintering area under the climate change scenarios of RCP2.6 and RCP8.5, both in 2030s and 2080s. The overwintering boundary is predicted to expand poleward and new overwintering areas are predicted in the mid-latitude regions of central-to-eastern China and mid-to-southern Australia. With climate change, the habitable areas remained similar, but suitability decreased substantially, especially in the near-equatorial regions, owing to increasing heat stress. The range shift is similar between RCP2.6-2030s, RCP2.6-2080s, and RCP8.5-2030s, but extreme changes are projected under RCP8.5-2080s with marginal areas increasing from 27.2 to 38.8% and very favorable areas dropping from 27.5 to 3.6% compared to the current climate. These findings indicate that climate change will drive range shifts in BPH and alter regional risks differently. Therefore, international monitoring programs are needed to effectively manage these emerging challenges.

A new threshold selection method for species distribution models with presence-only data: Extracting the mutation point of the P/E curve by threshold regression.

Selecting thresholds to convert continuous predictions of species distribution models proves critical for many real-world applications and model assessments. Prevalent threshold selection methods for presence-only data require unproven pseudo-absence data or subjective researchers' decisions. This study proposes a new method, Boyce-Threshold Quantile Regression (BTQR), to determine thresholds objectively without pseudo-absence data. We summarize that the mutation point is a typical shape feature of the predicted-to-expected (P/E) curve after reviewing relevant articles. Analysis based on source-sink theory suggests that this mutation point may represent a transition in habitat types and serve as an appropriate threshold. Threshold regression is introduced to accurately locate the mutation point. To validate the effectiveness of BTQR, we used four virtual species of varying prevalence and a real species with reliable distribution data. Six different species distribution models were employed to generate continuous suitability predictions. BTQR and nine other traditional methods transformed these continuous outputs into binary results. Comparative experiments show that BTQR has advantages in terms of accuracy, applicability, and consistency over the existing methods.

Impacts of Climate Change on the Biogeography and Ecological Structure of Zelkova schneideriana Hand.-Mazz. in China.

This study utilized the platform for ensemble forecasting of species distributions, biomod2, to predict and quantitatively analyze the distribution changes of Zelkova schneideriana Hand.-Mazz. under different climate scenarios (SSP1-2.6 and SSP5-8.5) based on climate and land-use data. This study evaluated the geographic range changes in future distribution areas and the results indicated that, under both SSP1-2.6 and SSP5-8.5 scenarios, the distribution area of Zelkova schneideriana would be reduced, showing a trend towards migration to higher latitudes and elevations. Particularly, in the more extreme SSP5-8.5 scenario, the contraction of the distribution area was more pronounced, accompanied by more significant migration characteristics. Furthermore, the ecological structure within the distribution area of Zelkova schneideriana also experienced significant changes, with an increasing degree of fragmentation. The variables of Bio6 (minimum temperature of the coldest month), Bio2 (mean diurnal temperature range), Bio15 (precipitation seasonality), and elevation exhibited important influences on the distribution of Zelkova schneideriana, with temperature being particularly significant. Changes in land use, especially the conversion of cropland, had a significant impact on the species' habitat. These research findings highlight the distributional pressures faced by Zelkova schneideriana in the future, emphasizing the crucial need for targeted conservation measures to protect this species and similar organisms.

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.

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.

Projections of climate-driven biogeographical changes of benthic mollusks in the Yellow Sea and East China Sea.

Climate change influences the distribution of many marine species. To project the biogeographical changes of benthic mollusks in response to climate change in the Yellow Sea and East China Sea, ensemble species distribution models (SDMs) were applied. Ensemble SDMs performed well for ten of the thirteen selected benthic mollusks with environmental variables including temperature, salinity, current velocity, and depth. Six cold water mollusks, including bivalves Acila mirabilis, Ennucula niponica, Ennucula tenuis, Nuculana yokoyamai, Pendaloma otohimeae and Megayoldia japonica, were projected to contract their habitats and move northward in 2050s and 2100s under all of the RCP2.6, 4.5, 6.0 and 8.5 climate scenarios, with temperature being the most important environmental variable. Two warm water mollusks (bivalves Nucula tokyoensis and Leptomya minuta) were projected to lose their suitable habitats under future climate scenarios (all RCP scenarios), while two (the gastropod Cylichna biplicata and the bivalve Moerella hilaris) were projected to expand their habitats to the deeper water area. The most important environmental variable varied among warm water species between temperature, salinity and depth. This study will contribute to better understanding the marine species biogeographical changes under climate change, and thus we can better protect their biodiversity.

Distribution and protection of Thesium chinense Turcz. under climate and land use change.

Wild medicinal plants are prominent in the field of Traditional Chinese Medicine (TCM), but their availability is being impacted by human activities and ecological degradation in China. To ensure sustainable use of these resources, it is crucial to scientifically plan areas for wild plant cultivation. Thesium chinense, a known plant antibiotic, has been overharvested in recent years, resulting in a sharp reduction in its wild resources. In this study, we employed three atmospheric circulation models and four socio-economic approaches (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) to investigate the primary environmental factors influencing the distribution of T. chinense. We also examined changes in its suitable area using the Biomod2 package. Additionally, we utilized the PLUS model to project and analyze future land use changes in climate-stable regions for T. chinense. Our planning for wild tending areas of T. chinense was facilitated by the ZONATION software. Over the next century, the climate-stable regions for T. chinense in China is approximately 383.05 × 104 km2, while the natural habitat in this region will progressively decline. Under the current climate conditions, about 65.06% of the habitats in the high suitable areas of T. chinense are not affected by future land use changes in China. Through hotspot analysis, we identified 17 hotspot cities as ideal areas for the wild tending of T. chinense, including 6 core hotspot cities, 6 sub-hotspot cities, and 5 fringe hotspot cities. These findings contribute to a comprehensive research framework for the cultivation planning of T. chinense and other medicinal plants.

Dermacentor (Indocentor) auratus Supino 1897: Potential geographic range, and medical and veterinary significance.

Dermacentor (Indocentor) auratus Supino, 1897 occurs in many regions of Southeast Asia and South Asia. In many regions of Southeast Asia and South Asia, targeted tick sampling and subsequent screening of collected D. auratus ticks have detected pathogenic bacteria and viruses in D. auratus. These disease-causing pathogens that have been detected in D. auratus include Anaplasma, Bartonella, Borrelia, Rickettsia (including spotted fever group rickettsiae), African swine fever virus, Lanjan virus, and Kyasanur forest disease virus. Although D. auratus predominantly infests wild pigs, this tick is also an occasional parasite of humans and other animals. Indeed, some 91 % of human otoacariasis cases in Sri Lanka were due to infestation by D. auratus. With the propensity of this tick to feed on multiple species of hosts, including humans, and the detection of pathogenic bacteria and viruses from this tick, D. auratus is a tick of medical, veterinary, and indeed zoonotic concern. The geographic range of this tick, however, is not well known. Therefore, in the present paper, we used the species distribution model, BIOCLIM, to project the potential geographic range of D. auratus, which may aid pathogen and tick-vector surveillance. We showed that the potential geographic range of D. auratus is far wider than the current geographic distribution of this tick, and that regions in Africa, and in North and South America seem to have suitable climates for D. auratus. Interestingly, in Southeast Asia, Borneo and Philippines also have suitable climates for D. auratus, but D. auratus has not been found in these regions yet despite the apparent close proximity of these regions to Mainland Southeast Asia, where D. auratus occurs. We thus hypothesize that the geographic distribution of D. auratus is largely dependent on the movement of wild pigs and whether or not these wild pigs are able to overcome dispersal barriers. We also review the potential pathogens and the diseases that may be associated with D. auratus and provide an updated host index for this tick.