MaxEnt's parameter configuration and small samples: are we paying attention to recommendations? A systematic review

Predicting the Potential Distribution of the Endangered Pyrethrum tatsienense in China Using an Optimized Maxent Model Under Climate Change Scenarios

Climate change can significantly impact the ecological suitability and diversity of species. Pyrethrum tatsienense, a critically endangered species in China, requires a thorough understanding of its habitat distribution and the environmental factors that affect it in the context of climate change. The Maxent algorithm was used to examine the key factors influencing the distribution of P. tatsienense in China, using data from 127 species occurrences and environmental variables from the Last Interglacial (LIG), Last Glacial Maximum (LGM), Mid-Holocene (MH), current, and future scenarios. The Maxent model was optimized utilizing the R package ENMeval, providing the most accurate predictions for suitable habitats across various scenarios. Results show that suitable regions for P. tatsienense encompass approximately 15.02% (14.42 × 105 km2) of China, predominantly on the Qinghai-Tibetan Plateau. The mean UV-B of the highest month (UVB3: 39.7%), elevation (elev: 28.7%), and the warmest season of precipitation (Bio18: 17.4%) are the major limiting factors for suitable habitat. The optimal species distribution ranges are identified as > 7500 J m-2 day-1 for UVB3, 2700-5600 m for elev, and 150-480 mm for Bio18. Predictions for the historical climate indicate the presence of refugia at the junction of Sichuan, Tibet, and Qinghai. The MH predictions show an increase in climatic suitability for P. tatsienense compared to the LIG and LGM, with an expansion of suitable areas westward. Future climate change scenarios indicate that the potential suitable habitat for P. tatsienense is expected to increase with increasing radiative forcing, with higher latitude regions becoming new marginally suitable habitats. However, predicted environmental changes in western Tibet may drive the loss of highly suitable habitats in the future. These findings enhance our understanding of how environmental factors impact the habitat suitability of P. tatsienense and provide valuable insights for developing effective management and conservation strategies for this important species.

Predicting the future distribution of the Barbary ground squirrel (Atlantoxerus getulus) under climate change using niche overlap analysis and species distribution modeling

This study combines niche overlap analysis with species distribution modeling (SDM) to examine the niche dynamics of Atlantoxerus getulus, a ground squirrel native to Morocco and Algeria that has been introduced to the Canary Islands. We compiled 1272 records of A. getulus in its native and exotic ranges and five bioclimatic variables for present and future climate conditions for the years 2050 and 2070. We assessed the ecological niche of the species using exploratory and ordination analyses, followed by the prediction of its distribution using the SpatialMaxent model. Our results showed that the niches of A. getulus exhibited equivalence (p > 0.05) and significant similarity (p < 0.05) between the native and exotic ranges. No observed niche expansion in the exotic area is shown to be associated with complete niche stability. However, 90% of the niche in the Canary Islands remains unfilled, suggesting potential for further invasion. Our results highlighted habitat contractions ranging from 41% (SSP245-2050) to 60% (SSP585-2070), associated with a shift in the centroid of suitable habitat towards the Atlantic coast. These contractions are particularly severe in Algeria, where suitable habitats could disappear by 2050, contrasting with stable habitats maintained in the Canary Islands under all scenarios. Urgent habitat restoration in Algeria is crucial, including efforts to combat poaching. In Morocco, targeted in situ conservation is recommended, while in the Canary Islands, the focus should be on invasive species management and public awareness campaigns to prevent further spread.

Spatial modeling and ecological suitability of Ebola virus disease in Africa

This paper looks into the MaxEnt model in a trial to comprehend the ecological and environmental conditions that propagate and drive the spread of Ebola Virus Disease in Africa. We use the MaxEnt model to assess risk determinants associated with the occurrence and distribution of EVD, taking into account non-correlated variables such as neighborhood mean temperature, rainfall, and human population density. Our findings indicate that among the factors that significantly shape the geographical distribution of EVD risk are human population density, annual rainfall, temperature variability, and seasonality. The model used is both reliable and accurate (the average value for training AUC was 0.987); it can be used as a valuable approach for the prediction of infectious disease outbreaks. High-risk areas are primarily identified in the western and central regions of Africa, with some of the others in the east also vulnerable. This further calls for specified public health interventions and enhanced surveillance in specified hotspots, contributing to global efforts to predict and mitigate risks associated with EVD outbreaks more adequately. The findings further support that it remains imperative to conduct additional research, including socio-economic and cultural variables, to enhance the understanding of how environmental factors contribute to the emergence and transmission of Ebola.

Incorporating Implicit Information to Disentangle the Impacts of Hydropower Dams and Climate Change on Basin-Scale Fish Habitat Distribution

The loss of freshwater fish habitats, exacerbated by climate change and dam constructions, poses a critical environmental concern. The upper Yangtze River basin, noted for its abundant fish fauna and concentrated dam development, serves as a crucial locale for investigating the impacts of climate shifts and dam construction. This study aims to disentangle the impacts of hydroelectric dams and climate change on fish habitat distribution by analyzing species presence data across different periods. Species distribution models were constructed using Maxent for Coreius guichenoti (a warm-water endangered fish) and Schizopygopsis malacanthus (a cold-water endangered fish). The model accuracy was assessed using the area under the curve of the receiver operating characteristic. Habitat distribution modeling and prediction for the pre-dam period (1970-2000) and post-dam period (2001-2020), as well as future climate change under two shared socioeconomic pathways scenarios, were conducted. The impacts of climate change and dam construction on the habitat suitability of two fish species were quantified. The results revealed dam construction predominantly diminished habitat suitability and range, with high-suitability habitats in the post-dam period decreasing by 56.3% (720.18 km) and 67.0% (1665.52 km) for the two fishes, respectively. Climate change would enhance the habitat suitability of Coreius guichenoti, while it would decrease the habitat suitability of Schizopygopsis malacanthus. The impact of dam construction is greater that of climate change for them. This study underscores the profound impacts of dam construction on fish habitats, particularly for cold-water species, and highlights the critical need for habitat restoration in sustainable hydropower development. Our method of disentangling these factors also provides a new approach to evaluating environmental impacts in large river basins.

Environmental Factors Affecting Spatio-Temporal Distribution of Crop-Exploiting Species: Implications for Coexistence Between Agricultural Production and Avifauna Conservation in Wetlands

Bird communities in agroecosystems bring both ecosystem services (e.g., pollination) and disservices (e.g., crop exploitation) to farmers. However, in the proximity of wetland reserves, farmers disproportionately experience harvest yield loss due to large aggregation of bird species that can utilize various agricultural resources. This often results in negative human-wildlife interactions which lower conservation support among farmers. Knowledge about the distribution of avian species that negatively influence yields, and its environmental drivers is thus fundamental to reconcile crop production and bird conservation. This study aims to examine the spatio-temporal patterns in richness and abundance of bird species known to cause agricultural yield loss as well as species-specific distribution patterns for the six bird species that are most challenging for local farmers. In combination with interview surveys of local farmers (n = 367) and seasonal bird surveys (n = 720), we investigated distribution of crop-exploiting avian species in the Indawgyi wetland ecosystem in Myanmar. Our results showed high richness and abundance of crop-exploiting species in the water habitat across all seasons, with most challenging species exhibiting higher presence closer to these water sources. The crop phenology had positive effect on species richness and abundance during the growing season. The agricultural use of crop-exploiting species was season- and species-specific, where the presence probability in the agricultural habitat was higher in habitat generalists than wetland specialists. Therefore, we suggest improved management of natural wetland habitats (e.g., habitat restoration), sustainable coexistence mechanisms in farms close to water (e.g., bird-friendly rice farming and Ecolabel certification) to reduce avian impacts on the farming communities and, at the same time, to promote bird conservation in wetlands of international importance.

Impacts of Distribution Data on Accurate Species Modeling: A Case Study of Litsea auriculata (Lauraceae)

Global warming has caused many species to become endangered or even extinct. Describing and predicting how species will respond to global warming is one of the hotspots of biodiversity research. Species distribution models predict the potential distribution of species based on species occurrence data. However, the impact of the accuracy of the distribution data on the prediction results is poorly studied. In this study, we used the endemic plant Litsea auriculata (Lauraceae) as a case study. By collecting and assembling six different datasets of this species, we used MaxEnt to perform species distribution modeling and then conducted comparative analyses. The results show that, based on our updated complete correct dataset (dataset 1), the suitable distribution of this species is mainly located in the Ta-pieh Mountain, southwestern Hubei and northern Zhejiang, and that mean diurnal temperature range (MDTR) and temperature annual range (TAR) play important roles in shaping the distribution of Litsea auriculata. Compared with the correct data, the wrong data leads to a larger and expanded range in the predicted distribution area, whereas the species modeling based on the correct but incomplete data predicts a small and contracted range. We found that only about 23.38% of Litsea auriculata is located within nature reserves, so there is a huge conservation gap. Our study emphasized the importance of correct and complete distribution data for accurate prediction of species distribution regions; both incomplete and incorrect data can give misleading prediction results. In addition, our study also revealed the distribution characteristics and conservation gap of Litsea auriculata, laying the foundation for the development of reasonable conservation strategies for this species.

The importance of geography in forecasting future fire patterns under climate change

An increasing amount of California's landscape has burned in wildfires in recent decades, in conjunction with increasing temperatures and vapor pressure deficit due to climate change. As the wildland-urban interface expands, more people are exposed to and harmed by these extensive wildfires, which are also eroding the resilience of terrestrial ecosystems. With future wildfire activity expected to increase, there is an urgent demand for solutions that sustain healthy ecosystems and wildfire-resilient human communities. Those who manage disaster response, landscapes, and biodiversity rely on mapped projections of how fire activity may respond to climate change and other human factors. California wildfire is complex, however, and climate-fire relationships vary across the state. Given known geographical variability in drivers of fire activity, we asked whether the geographical extent of fire models used to create these projections may alter the interpretation of predictions. We compared models of fire occurrence spanning the entire state of California to models developed for individual ecoregions and then projected end-of-century future fire patterns under climate change scenarios. We trained a Maximum Entropy model with fire records and hydroclimatological variables from recent decades (1981 to 2010) as well as topographic and human infrastructure predictors. Results showed substantial variation in predictors of fire probability and mapped future projections of fire depending upon geographical extents of model boundaries. Only the ecoregion models, accounting for the unique patterns of vegetation, climate, and human infrastructure, projected an increase in fire in most forested regions of the state, congruent with predictions from other studies.

Combining distribution modelling and phylogeography to understand present, past and future of an endangered spider

BACKGROUND

Understanding how endangered species respond to climatic changes is fundamental for their conservation. Due to its restricted geographic range, its sensitivity to the ongoing global warming and its continuing decline, the Southwestern-Alpine endemic wolf spider Vesubia jugorum is currently classified as Endangered in the IUCN Red List. Here, we combined species distribution modelling (SDM) and phylogeographic inference to describe the present, the past and the future of this species in light of the mtDNA genetic structure of extant populations.

RESULTS

Phylogenetic and network analyses show a high level of genetic differentiation and a strong genetic structure of the populations, likely explicable by a long history of isolation and survival in separate refugia. The SDM projection into past climatic conditions supports these results by showing a smaller distribution range compared to present, mostly restricted to the Maritime and Ligurian Alps, which possibly served as main refugium. Future forecast shows a significant shift in the bioclimatic range towards higher altitudes and latitudes, with a drastic decrease of habitat suitability in the central and south-eastern parts of the range, with consequent general loss of haplotype diversity.

CONCLUSION

SDM and phylogeographic inference support the hypothesis that the current distribution and the genetic structure of the extant populations mirror the survival in situ of Vesubia jugorum across repeated glacial and interglacial phases, in line with the 'long-term stability hypothesis'. Future predictions show a significant shift in the bioclimatic range that V. jugorum will be likely unable to track, with profound impact on its long-term survival and its genetic diversity. Our considerations have implication for conservation genetics, highlighting the pivotal role of the transboundary protected areas of the SW-Alps in promoting conservation efforts for this species.

Exploring the distribution and habitat preferences of Polytrichaceae (Bryophyta) in Tibet, China

The Qinghai-Tibet Plateau stands as one of the most ecologically fragile and biodiversity-rich regions globally. Understanding the distribution of different taxa and their relationship with environmental factors is crucial for effective conservation and sustainable management. Polytrichaceae, a significant bryophyte family widely distributed in Tibet, displays distinct structural, morphological, and phylogenetic traits compared to other mosses. Despite its importance, the distribution of Polytrichaceae in Tibet and its correlation with environmental factors have yet to be explored. In this study, we used an optimized Maximum Entropy (MaxEnt) model to explore the potential suitable habitats of Polytrichaceae in Tibet, aiming to clarify their geographic distribution pattern as well as the key environmental influence factors. The model had high accuracy with an average Area Under the Curve (AUC) of 0.933 and True Skill Statistics (TSS) value of 0.789. The results showed that the potential suitability habitats of Polytrichaceae were mainly located in southeastern Tibet, and the low suitable, moderately suitable, and highly suitable habitats accounted for 12.53 %, 6.84 %, and 3.31 % of the total area of Tibet respectively. Unsuitable habitats were mainly located in northwestern Tibet, accounting for about 77.32 %. In Tibet, temperature factors (Mean Temperature of Coldest Quarter (Bio11) and Annual Mean Temperature (Bio1)) played a pivotal role in determining the potential suitable habitats for Polytrichaceae, and elevation, precipitation, and vegetation coverage also had an important influence. The family preferred warm, moist and densely vegetated habitats in Tibet. This study enriched our ecological understanding of bryophyte ecology in this region and provided data-driven support for biodiversity conservation and ecosystem management in Tibet.

Presence of Triatoma breyeri (Reduviidae, Triatominae) in Bolivia

The study focuses on identifying and understanding the ecological dynamics of Triatoma breyeri in Bolivia. Morphological identification and molecular analysis using gene fragments (COI, CytB and 16S) confirms T. breyeri's presence and its relation to other species. The species has been consistently found in the Estancia-Mataral-La Palma region since 2010 but has not spread to other regions in Bolivia. The region of occurrence is a small characteristic dry inter-Andean valley. A MaxEnt model suggests part of the Bolivian Montane Dry Forest ecoregion serves as a unique habitat within its range. The infrequent presence in Bolivia and the distance from its main range in Argentina suggest recent accidental introduction, possibly through human transport. Further research is needed to comprehend its persistence in this small area of Bolivia.

Study on the change of global ecological distribution of Nicotiana tabacum L. based on MaxEnt model

Nicotiana tabacum L. (tobacco) has extremely high economic value, medicinal value, scientific research value and some other uses. Though it has been widely cultivated throughout the world, classification and change of its suitable habitats is not that clear, especially in the context of global warming. In order to achieve rational cultivation and sustainable development of tobacco, current (average from 1970-2000) and future (2070, average from 2061-2080) potential suitable habitats of Nicotiana tabacum L. were forecasted with MaxEnt model and ArcGIS platform based on 854 occurrence data and 22 environmental factors in this study. The results revealed that mean temperature of warmest quarter (bio10), annual precipitation (bio12), solar radiation in September (Srad9), and clay content (CLAY) were the four decisive environment variables for the distribution of Nicotiana tabacum L. Under current climate conditions, suitable habitats of Nicotiana tabacum L. were mainly distributed in south-central Europe, south-central North America, most parts of South America, central Africa, south and southeast Asia, and southeast coast of Australia, and only 13.7% of these areas were highly suitable. By the year 2070, suitable habitats under SSP1-2.6, SSP3-7.0, and SSP5-8.5 climate scenarios would all increase with the largest increase found under SSP3-7.0 scenario, while suitable habitats would reduce under SSP2-4.5 climate scenario. Globally, the center of mass of suitable habitats would migrate to southeast to varying degrees within Libya under four different climate scenarios. The emergence of new habitats and the disappearance of old habitats would all occur simultaneously under each climate scenario, and the specific changes in each area, combined with the prediction results under current climate conditions, will provide an important reference for the adjustment of agronomic practices and rational cultivation of Nicotiana tabacum L. both currently and in the future.

Predicting the impact of climate change and land use change on the potential distribution of two economic forest trees in Northeastern China

Young shoots of Aralia elata and young leaves of Eleutherococcus senticosus are two major non-timber forest products in northeastern China. However, human activities and climate change have resulted in serious threats to the habitats of two trees, which greatly limits resource conservation and exploitation of economic forest trees. We used the MaxEnt model to predict the suitable habitats of the two economic trees and analyzed the dominant factors affecting their distribution. The results showed that the suitable habitat areas of A. elata and E. senticosus in the current period were 159950 km2 and 123449 km2, respectively, and the suitable habitats of both economic forest trees were located in the eastern part of the northeast region. Climate factors (Annual precipitation, Precipitation Seasonality) and land use factors are important variables influencing changes in suitable habitat for both trees. With the change of climate and land use in the future, the overall trend of suitable habitat for both economic forest trees shows a northward and then a southward migration. These results may provide assistance in developing strategies for resource conservation and sustainable use of A. elata and E. senticosus, and we suggest that stable and suitable habitats should be selected as areas for in situ conservation and breeding of the two economic forest trees.

Forest Orchids under Future Climate Scenarios: Habitat Suitability Modelling to Inform Conservation Strategies

Orchidaceae is one of the largest and most diverse families of flowering plants in the world but also one of the most threatened. Climate change is a global driver of plant distribution and may be the cause of their disappearance in some regions. Forest orchids are associated with specific biotic and abiotic environmental factors, that influence their local presence/absence. Changes in these conditions can lead to significant differences in species distribution. We studied three forest orchids belonging to different genera (Cephalanthera, Epipactis and Limodorum) for their potential current and future distribution in a protected area (PA) of the Northern Apennines. A Habitat Suitability Model was constructed for each species based on presence-only data and the Maximum Entropy algorithm (MaxEnt) was used for the modelling. Climatic, edaphic, topographic, anthropogenic and land cover variables were used as environmental predictors and processed in the model. The aim is to identify the environmental factors that most influence the current species distribution and the areas that are likely to contain habitats suitable for providing refuge for forest orchids and ensuring their survival under future scenarios. This will allow PA authorities to decide whether to invest more resources in conserving areas that are potential refuges for threatened species.

Potential distribution and ecological impacts of Acmella radicans (Jacquin) R.K. Jansen (a new Yunnan invasive species record) in China

BACKGROUND ACMELLA RADICANS: (Jacquin) R.K. Jansen is a new invasive species record for Yunnan Province, China. Native to Central America, it has also been recently recorded invading other parts of Asia. To prevent this weed from becoming a serious issue, an assessment of its ecological impacts and potential distribution is needed. We predicted the potential distribution of A. radicans in China using the MaxEnt model and its ecological impacts on local plant communities and soil nutrients were explored. RESULTS: Simulated training using model parameters produced an area under curve value of 0.974, providing a high degree of confidence in model predictions. Environmental variables with the greatest predictive power were precipitation of wettest month, isothermality, topsoil TEB (total exchangeable bases), and precipitation seasonality, with a cumulative contribution of more than 72.70% and a cumulative permutation importance of more than 69.20%. The predicted potential suitable area of A. radicans in China is concentrated in the southern region. Projected areas of A. radicans ranked as high and moderately suitable comprised 5425 and 26,338 km2, accounting for 0.06 and 0.27% of the Chinese mainland area, respectively. Over the 5 years of monitoring, the population density of A. radicans increased while at the same time the population density and importance values of most other plant species declined markedly. Community species richness, diversity, and evenness values significantly declined. Soil organic matter, total N, total P, available N, and available P concentrations decreased significantly with increasing plant cover of A. radicans, whereas pH, total K and available K increased. CONCLUSION: Our study was the first to show that A. radicans is predicted to expand its range in China and may profoundly affect plant communities, species diversity, and the soil environment. Early warning and monitoring of A. radicans must be pursued with greater vigilance in southern China to prevent its further spread.

The devil is in the detail: Environmental variables frequently used for habitat suitability modeling lack information for forest-dwelling bats in Germany

In response to the pressing challenges of the ongoing biodiversity crisis, the protection of endangered species and their habitats, as well as the monitoring of invasive species are crucial. Habitat suitability modeling (HSM) is often treated as the silver bullet to address these challenges, commonly relying on generic variables sourced from widely available datasets. However, for species with high habitat requirements, or for modeling the suitability of habitats within the geographic range of a species, variables at a coarse level of detail may fall short. Consequently, there is potential value in considering the incorporation of more targeted data, which may extend beyond readily available land cover and climate datasets. In this study, we investigate the impact of incorporating targeted land cover variables (specifically tree species composition) and vertical structure information (derived from LiDAR data) on HSM outcomes for three forest specialist bat species (Barbastella barbastellus, Myotis bechsteinii, and Plecotus auritus) in Rhineland-Palatinate, Germany, compared to commonly utilized environmental variables, such as generic land-cover classifications (e.g., Corine Land Cover) and climate variables (e.g., Bioclim). The integration of targeted variables enhanced the performance of habitat suitability models for all three bat species. Furthermore, our results showed a high difference in the distribution maps that resulted from using different levels of detail in environmental variables. This underscores the importance of making the effort to generate the appropriate variables, rather than simply relying on commonly used ones, and the necessity of exercising caution when using habitat models as a tool to inform conservation strategies and spatial planning efforts.

Predicting the potential distribution of Dendrolimus punctatus and its host Pinus massoniana in China under climate change conditions

Introduction

Dendrolimus punctatus, a major pest endemic to the native Pinus massoniana forests in China, displays major outbreak characteristics and causes severe destructiveness. In the context of global climate change, this study aims to investigate the effects of climatic variations on the distribution of D. punctatus and its host, P. massoniana.

Methods

We predict their potential suitable distribution areas in the future, thereby offering a theoretical basis for monitoring and controlling D. punctatus, as well as conserving P. massoniana forest resources. By utilizing existing distribution data on D. punctatus and P. massoniana, coupled with relevant climatic variables, this study employs an optimized maximum entropy (MaxEnt) model for predictions. With feature combinations set as linear and product (LP) and the regularization multiplier at 0.1, the model strikes an optimal balance between complexity and accuracy.

Results

The results indicate that the primary climatic factors influencing the distribution of D. punctatus and P. massoniana include the minimum temperature of the coldest month, annual temperature range, and annual precipitation. Under the influence of climate change, the distribution areas of P. massoniana and its pests exhibit a high degree of similarity, primarily concentrated in the region south of the Qinling-Huaihe line in China. In various climate scenarios, the suitable habitat areas for these two species may expand to varying degrees, exhibiting a tendency to shift toward higher latitude regions. Particularly under the high emission scenario (SSP5-8.5), D. punctatus is projected to expand northwards at the fastest rate.

Discussion

By 2050, its migration direction is expected to closely align with that of P. massoniana, indicating that the pine forests will continue to be affected by the pest. These findings provide crucial empirical references for region-specific prevention of D. punctatus infestations and for the rational utilization and management of P. massoniana resources.

Predicting the geographical distribution and niche characteristics of Cotoneaster multiflorus based on future climate change

Introduction

Arid and semi-arid regions are climate-sensitive areas, which account for about 40% of the world's land surface area. Future environment change will impact the environment of these area, resulting in a sharp expansion of arid and semi-arid regions. Cotoneaster multiflorus is a multi-functional tree species with extreme cold, drought and barren resistance, as well as ornamental and medicinal functions. It was found to be one of the most important tree species for ecological restoration in arid and semi-arid areas. However, bioclimatic factors play an important role in the growth, development and distribution of plants. Therefore, exploring the response pattern and ecological adaptability of C. multiflorus to future climate change is important for the long-term ecological restoration of C. multiflorus in arid and semi-arid areas.

Methods

In this study, we predicted the potential distribution of C. multiflorus in China under different climate scenarios based on the MaxEnt 2.0 model, and discussed its adaptability and the major factors affecting its geographical distribution.

Results

The major factors that explained the geographical distribution of C. multiflorus were Annual precipitation (Bio12), Min air temperature of the coldest month (Bio6), and Mean air temperature of the coldest quarter (Bio11). However, C. multiflorus could thrive in environments where Annual precipitation (Bio12) >150 mm, Min air temperature of the coldest month (Bio6) > -42.5°C, and Mean air temperature of the coldest quarter (Bio11) > -20°C, showcasing its characteristics of cold and drought tolerance. Under different future climate scenarios, the total suitable area for C. multiflorus ranged from 411.199×104 km² to 470.191×104 km², which was 0.8~6.14 percentage points higher than the current total suitable area. Additionally, it would further shift towards higher latitude.

Discussion

The MaxEnt 2.0 model predicted the potential distribution pattern of C. multiflorus in the context of future climate change, and identified its ecological adaptability and the main climatic factors affecting its distribution. This study provides an important theoretical basis for natural vegetation restoration in arid and semi-arid areas.

Future climatically suitable areas for bats in South Asia

Climate change majorly impacts biodiversity in diverse regions across the world, including South Asia, a megadiverse area with heterogeneous climatic and vegetation regions. However, climate impacts on bats in this region are not well-studied, and it is unclear whether climate effects will follow patterns predicted in other regions. We address this by assessing projected near-future changes in climatically suitable areas for 110 bat species from South Asia. We used ensemble ecological niche modelling with four algorithms (random forests, artificial neural networks, multivariate adaptive regression splines and maximum entropy) to define climatically suitable areas under current conditions (1970-2000). We then extrapolated near future (2041-2060) suitable areas under four projected scenarios (combining two global climate models and two shared socioeconomic pathways, SSP2: middle-of-the-road and SSP5: fossil-fuelled development). Projected future changes in suitable areas varied across species, with most species predicted to retain most of the current area or lose small amounts. When shifts occurred due to projected climate change, new areas were generally northward of current suitable areas. Suitability hotspots, defined as regions suitable for >30% of species, were generally predicted to become smaller and more fragmented. Overall, climate change in the near future may not lead to dramatic shifts in the distribution of bat species in South Asia, but local hotspots of biodiversity may be lost. Our results offer insight into climate change effects in less studied areas and can inform conservation planning, motivating reappraisals of conservation priorities and strategies for bats in South Asia.

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.

Predicting the global potential distribution of Bursaphelenchus xylophilus using an ecological niche model: expansion trend and the main driving factors

Bursaphelenchus xylophilus (Steiner&Buhrer) Nickle is a global quarantine pest that causes devastating mortality in pine species. The rapid and uncontrollable parasitic spread of this organism results in substantial economic losses to pine forests annually. In this study, we used the MaxEnt model and GIS software ArcGIS10.8 to predict the distribution of B. xylophilus based on collected distribution points and 19 environmental variables (with a correlation coefficient of|R| > 0.8) for the contemporary period (1970-2000), 2041-2060 (2050s), 2061-2080 (2070s), and 2081-2100 (2090s) under four shared socioeconomic pathways (SSPs). We conducted a comprehensive analysis of the key environmental factors affecting the geographical distribution of B. xylophilus and suitable distribution areas. Our results indicate that in current prediction maps B. xylophilus had potential suitable habitats in all continents except Antarctica, with East Asia being the region with the most highly suitable areas and the most serious epidemic area currently. Precipitation of the warmest quarter, temperature seasonality, precipitation of the wettest month, and maximum temperature of the warmest month were identified as key environmental variables that determine the distribution of B. xylophilus. Under future climatic conditions, the potential geographic distribution of B. xylophilus will expand relative to current conditions. In particular, under the SSP5-8.5 scenario in 2081-2100, suitable areas will expand to higher latitudes, and there will be significant changes in suitable areas in Europe, East Asia, and North America. These findings are crucial for future prevention and control management and monitoring.

Identification of habitat suitability for the dominant zoonotic tick species Haemaphysalis flava on Chongming Island, China

Haemaphysalis ticks are pathogenic vectors that threaten human and animal health and were identified in Chongming, the third largest island in China. To understand the distribution of these ticks and determine their potential invasion risk, this study aimed to identify the habitat suitability of the dominant tick H. flava based on natural environmental factors. Geographic information system (GIS) images were combined with sample points from tick investigations to map the spatial distribution of H. flava. Data on 19 bioclimatic variables, environmental variables, and satellite-based landscapes of Chongming Island were retrieved to create a landcover map related to natural environmental determinants of H. flava. These data included 38 sites associated with the vectors to construct species distribution models with MaxEnt, a model based on the maximum entropy principle, and to predict habitat suitability for H. flava on Chongming Island in 2050 and 2070 under different climate scenarios. The model performed well in predicting the H. flava distribution, with a training area under the curve of 0.84 and a test area under the curve of 0.73. A habitat suitability map of the whole study area was created for H. flava. The resulting map and natural environment analysis highlighted the importance of the normalized difference vegetation index and precipitation in the driest month for the bioecology of H. flava, with 141.61 km2 (11.77%), 282.94 km2 (23.35%), and 405.30 km2 (33.69%) of highly, moderately, and poorly suitable habitats, respectively. The distribution decreased by 135.55 km2 and 138.82 km2 in 2050 and 2070, respectively, under the shared socioeconomic pathway (SSP) 1.2.6 climate change scenario. However, under SSP 5.8.5, the total area will decrease by 128.5 km2 in 2050 and increase by 151.64 km2 in 2070. From a One Health perspective, this study provides good knowledge that will guide tick control efforts to prevent the spread of Haemaphysalis ticks or transmission risk of Haemaphysalis-borne infections at the human-animal-environment interface on the island.

Setting restorative goals with a regional outlook: Mine-rehabilitation outcomes influence landscape connectivity

Mining is increasing worldwide and is typically associated with highly negative environmental impacts, such as habitat loss and fragmentation. To counteract these effects and improve restoration practices, decisions, such as setting mine rehabilitation goals, could incorporate the assessment and restoration of landscape connectivity into their regional and local-scale planning. The overarching goal of this work was to assess landscape connectivity for flora and fauna and explore mine-rehabilitation scenarios that can be used as a tool for prioritising biodiversity outcomes. Our study area comprised the Fitzroy Basin (Queensland, Australia), where the disturbance footprints from mining cover a cumulative area of 121,239 ha. We considered two scenarios: rehabilitation to agriculture and restoration to native ecosystems. To compare these scenarios, we created differential maps, which highlighted that restoring to native ecosystems represented connectivity gains over agricultural rehabilitation goals. These maps revealed three ways to prioritise rehabilitation outcomes, giving priority to mines that: 1) presented medium to high connectivity values, 2) covered a large area of influence (contributing to connectivity on a larger scale, regardless of current flow values), and 3) showed a gain of important paths/corridors. We explored four case studies and found that three benefited from restoration outcomes, while the fourth did not benefit by either scenario. Our methods can be used for decision-making in restoration ecology and conservation, including mine rehabilitation priorities and goals, as well as for evaluating connectivity gains or losses.

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.

Prediction of potential distributions of Morina kokonorica and Morina chinensis in China

Changes in the habitats of species can provide insights into the impact of climate change on their habitats. Species in the genus Morina (Morinoideae) are perennial herbaceous plants that are mainly distributed in the South Asian Mountains and Eastern Mediterranean. In China, there are four species and two varieties of this genus distributed across the Yunnan, Sichuan, Qinghai, and Gansu provinces. This study used the optimal MaxEnt model to simulate past, current, and future potentially suitable habitats of Morina kokonorica and Morina chinensis. Seventy data of M. kokonorica occurrences and 3 of M. chinensis were used in the model to predict potentially suitable habitats. The model prediction results indicated that both M. kokonorica and M. chinensis exhibited trends of northward migration to higher latitudes and westward migration along the Himalayas to higher elevations, suggesting that the northern valleys of Hengduan Mountains and northern and eastern parts of the Himalayas were potential refugia for M. kokonorica, and the potential refugia for M. chinensis was located in the eastern part of Qinghai-Tibet Plateau. The results of this niche analysis showed that the two species had higher levels of interspecific competition and that the environmental adaptability of M. chinensis was stronger. This research could help further understand the response pattern of Morina to environmental change, to understand the adaptability of species to the environment, and promote the protection of species.

Predicting the potential distribution of 12 threatened medicinal plants on the Qinghai-Tibet Plateau, with a maximum entropy model

Climate change is a vital driver of biodiversity patterns and species distributions, understanding how organisms respond to climate change will shed light on the conservation of endangered species. In this study, the MaxEnt model was used to predict the potential suitable area of 12 threatened medicinal plants in the QTP (Qinghai-Tibet Plateau) under the current and future (2050s, 2070s) three climate scenarios (RCP2.6, RCP4.5, RCP8.5). The results showed that the climatically suitable habitats for the threatened medicinal plants were primarily found in the eastern, southeast, southern, and some parts of the central regions on the QTP. Moreover, 25% of the threatened medicinal plants would have reduced suitable habitat areas within the next 30-50 years in the different future global warming scenarios. Among these medicinal plants, RT (Rheum tanguticum) would miss the most habitat (98.97%), while the RAN (Rhododendron anthopogonoides) would miss the least habitat (10.15%). Nevertheless, 33.3% of the threatened medicinal plants showed an increase in their future habitat area because of their physiological characteristics which are more adaptable to a wide range of climates. The climatic suitable habitat for 50% of the threatened medicinal plants would migrate to higher altitudes or higher latitudes regions. This study provides a data foundation for the conservation of biodiversity and wild medicinal plants on the QTP.

The global distribution of plants used by humans

Plants sustain human life. Understanding geographic patterns of the diversity of species used by people is thus essential for the sustainable management of plant resources. Here, we investigate the global distribution of 35,687 utilized plant species spanning 10 use categories (e.g., food, medicine, material). Our findings indicate general concordance between utilized and total plant diversity, supporting the potential for simultaneously conserving species diversity and its contributions to people. Although Indigenous lands across Mesoamerica, the Horn of Africa, and Southern Asia harbor a disproportionate diversity of utilized plants, the incidence of protected areas is negatively correlated with utilized species richness. Finding mechanisms to preserve areas containing concentrations of utilized plants and traditional knowledge must become a priority for the implementation of the Kunming-Montreal Global Biodiversity Framework.

Comparative Assessment of Habitat Suitability and Niche Overlap of Three Cytospora Species in China

The plant pathogenic fungus Cytospora is notoriously known for causing woody plant canker diseases, resulting in substantial economic losses to biological forests and fruit trees worldwide. Despite their strong negative ecological impact, the existing and prospective distribution patterns of these plant pathogens in China, according to climate change, have received little attention. In this study, we chose three widely dispersed and seriously damaging species, namely, Cytospora chrysosperma, Cytospora mali, and Cytospora nivea, which are the most common species that damage the Juglans regia, Malus domestica, Eucalyptus, Pyrus sinkiangensis, Populus spp., and Salix spp. in China. We utilized ecological niche modeling to forecast their regional distribution in China under four climate change scenarios (present, SSP 126, SSP 370, and SSP 585). The results show that temperature-related climate factors limit the current distribution ranges of the three species. Currently, the three studied species are highly suitable for northeast, northwest, north, and southwest China. Under future climate scenarios, the distribution ranges of the three species are projected to increase, and the centers of the adequate distribution areas of the three species are expected to shift to high-latitude regions. The three species coexist in China, primarily in the northwest and north regions. The ecological niches of C. chrysosperma and C. nivea are more similar. The distribution range of C. mali can reach the warmer and wetter eastern region, whereas C. chrysosperma and C. nivea are primarily found in drought-prone areas with little rainfall. Our findings can help farmers and planners develop methods to avoid the spread of Cytospora spp. and calculate the costs of applying pesticides to reduce contamination and boost yields.

The ecological suitability area of Cirsium lineare (Thunb.) Sch.-Bip. under future climate change in China based on MaxEnt modeling

Many kinds of medicinal ingredients occur in Cirsium lineare that have good clinical efficacy, conferring on this species its high medicinal development value. However, with a rapidly changing global climate, it is increasingly imperative to study the factors affecting the habitat distribution and survival of species. We predicted the current and future distribution areas of suitable habitats for C. lineare, analyzed the importance of environmental variables in influencing habitat shifts, and described the alterations to suitable habitats of C. lineare in different periods (modern, 2050s, and 2070s) and scenarios (RCP2.6, RCP4.5, and RCP8.5). The results show that, under the current climate, the total suitable area of C. lineare is about 2,220,900 km2, of which the highly suitable portion amounts to ca. 292,600 km2. The minimum temperature of the coldest month, annual precipitation, and mean daily temperature range are the chief environmental variables affecting the distribution of habitat for C. lineare. In the same period, with rising greenhouse gas emission concentrations, the total suitable area will increase. In general, under future climate change, the suitable habitat for C. lineare will gradually migrate to the west and north, and its total suitable area will also expand. The results of this experiment can be used for the conservation and management of the wild resources of C. lineare. We can choose suitable growth areas to protect the medicinal resources of C. lineare through in situ conservation and artificial breeding.

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.

Predicting the current and future distribution of Monochamus carolinensis (Coleoptera: Cerambycidae) based on the maximum entropy model

BACKGROUND

Monochamus carolinensis is an important vector of pinewood nematodes in North America that is under quarantine in several countries worldwide. The distribution of M. carolinensis was previously thought to be limited to North America; however, we discovered it during trapping in China in 2022. Using this discovery and information regarding the area of origin, we applied a machine-learning algorithm based on the maximum entropy principle to predict the current and future (2050s, 2070s) potential distribution areas of M. carolinensis using bioclimatic variables.

RESULTS

The biological suitability of M. carolinensis was mainly driven by precipitation factors (BIO18, BIO15, BIO19), with 87.18% of the potential distribution areas located in South America, Asia, North America and Africa. Future potential distribution areas of M. carolinensis are predicted to expand to high latitudes, with an average increase of 10 245 874.88 km2 , and only 6.89% of the current suitable areas will become unsuitable. The potential distribution areas in 2070 are largest under the SSP585 scenario, with a 41.40% predicted increase (52 309 803.61 km2 ) above the current distribution, mainly reflecting an increase of the marginally and highly suitable areas.

CONCLUSION

The determination of dominant climatic factors and potential distribution areas will help provide an early warning for an M. carolinensis invasion, as well as provide a scientific basis for the spread and outbreak, facilitating development of effective governmental prevention and control measures. © 2023 Society of Chemical Industry.

Potential changes in the extent of suitable habitats for geladas (Theropithecus gelada) in the Anthropocene

BACKGROUND

Climate change coupled with other anthropogenic pressures may affect the extent of suitable habitat for species and thus their distributions. This is particularly true for species occupying high-altitude habitats such as the gelada (Theropithecus gelada) of the Ethiopian highlands. To explore the impact of climate change on species distributions, Species Distribution Modelling (SDM) has been extensively used. Here we model the current and future extent of sutibale habitat for geladas. Our modelling was based on 285 presence locations of geladas, covering their complete current distribution. We used different techniques to generate pseudoabsence datasets, MaxEnt model complexities, and cut-off thresholds to map the potential distribution of gelada under current and future climates (2050 and 2070). We assembled maps from these techniques to produce a final composite map. We also evaluated the change in the topographic features of gelada over the past 200 years by comparing the topography in current and historical settings.

RESULTS

All model runs had high performances, AUC = 0.87-0.96. Under the current climate, the suitable habitat predicted with high certainty was 90,891 km2, but it decreased remarkably under future climates, -36% by 2050 and - 52% by 2070. However, since the habitats of geladas already extend to mountaintop grasslands, no remarkable range shifts across elevation gradients were predicted under future climates.

CONCLUSIONS

Our findings indicated that climate change most likely results in a loss of suitable habitat for geladas, particularly south of the Rift Valley. Currently geladas are confined to higher altitudes and steep slopes compared to historical sightings, probably qualifying geladas as refugee species. The difference in topography is potentially associated with anthropogenic pressures that drove niche truncation to higher altitudes, undermining the climatic and topographic niche our models predicted. We recommend protecting the current habitats of geladas even when they are forecasted to become climatically unsuitable in the future, in particular for the population south of the Rift Valley.

Assessing the suitability and dynamics of three medicinal Sambucus species in China under current and future climate scenarios

Climate change exerts profound influences on the ecological environments on a global scale, leading to habitat destruction and altering distribution patterns for numerous plant species. Traditional Chinese medicinal plants, such as those belonging to the Sambucus genus, have been extensively utilized for several centuries to treat fractures, rheumatism, and inflammation. However, our understanding of their geographic distribution and climatic adaptation within China still needs to be improved. In this study, we screened the optimal predictive model (random forest model) to predict the potential suitable distribution of three Sambucus species (Sambucus adnata, Sambucus javanica, and Sambucus williamsii) across China under both current and future climate scenarios. Moreover, we identified key climate factors that influence their potential distributions. Our findings revealed that S. adnata and S. javanica are predominantly shaped by temperature seasonality and mean diurnal range, respectively, whereas S. williamsii is significantly affected by the precipitation of the wettest month. Currently, S. williamsii is primarily distributed in north and central south China (covering 9.57 × 105 km2), S. javanica is prevalent in the south and east regions (covering 6.41×105 km2), and S. adnata predominantly thrives in the southwest China (covering 1.99×105 km2). Under future climate change scenarios, it is anticipated that S. adnata may migrate to higher latitudes while S. javanica may shift to lower latitudes. However, potentially suitable areas for S. williamsii may contract under certain scenarios for the years 2050 and 2090, with an expansion trend under the SSP585 scenario for the year 2090. Our study emphasizes the importance of climatic variables in influencing the potential geographic distribution of Sambucus species. These findings provide valuable theoretical insights for the preservation, cultivation, and utilization of Sambucus medicinal plant resources in the context of ongoing climate change.

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.

The Mysterious Amurian Grig Paracyphoderris erebeus Storozhenko, 1980 (Orthoptera: Prophalangopsidae): New Data on Its Distribution, Ecology and Biology

New data on distribution, ecology and biology of the rare extant species Paracyphoderris erebeus of the almost completely ancient family Prophalangopsidae (Orthoptera) are given. This montane species prefers humid areas with relatively low summer temperatures. Habits, mating behaviour and life history of P. erebeus are extremely similar to those of the North American representatives of the genus Cyphoderris. Nowadays, the Amurian grig is known from the Myaochan, Badzhalsky, Dusse-Alin, Bureinsky and Aezop ridges in the Khabarovsk Territory (north of the Amur River) and Bydyr Mountain in the Jewish Autonomous Region of Russia only. The analysis of the predicted distribution of P. erebeus based on the occurrence data reveals that the populations of the species may be more widely distributed over the southern part of the Russian Far East, at least up to 56° N. The ecologo-geographic model of the species distribution over its range is generated using the Maxent 3.4.4 software for the first time. Modelling of the P. erebeus distribution for 2021-2040 and 2041-2060 shows that the position of the species range appears to be relatively stable but a weak decline in the foretold suitability during climate warming may result in a reduction in population sizes and the subsequent fragmentation of the species population system. In this case, the Amurian grig will become a prospective to be included on the IUCN Red List.

Phylogeography and ecological niche modeling implicate multiple microrefugia of Swertia tetraptera during quaternary glaciations

BACKGROUND

Climate fluctuations during the Pleistocene and mountain uplift are vital driving forces affecting geographic distribution. Here, we ask how an annual plant responded to the Pleistocene glacial cycles.

METHODS

In this study, we analyzed the population demographic history of the annual herb Swertia tetraptera Maxim (Gentianaceae) endemic to Qinghai-Tibetan Plateau (QTP). A total of 301 individuals from 35 populations of S. tetraptera were analyzed based on two maternally inherited chloroplast fragments (trnL-trnF and trnS-trnG). Phylogeographic analysis was combined with species distribution modeling to detect the genetic variations in S. tetraptera.

RESULTS

The genetic diversity of S. tetraptera was high, likely due to its wide natural range, high proportion of endemic haplotypes and evolutionary history. Fifty-four haplotypes were identified in S. tetraptera. Only a few haplotypes were widespread (Hap_4, Hap_1, Hap_3), which were dispersed throughout the present geographical range of S. tetraptera, while many haplotypes were confined to single populations. The cpDNA dataset showed that phylogeographic structuring was lacking across the distribution range of S. tetraptera. Analyses of molecular variance showed that most genetic variation was found within populations (70.51%). In addition, the relationships of the haplotypes were almost completely unresolved by phylogenetic reconstruction. Both mismatch distribution analysis and neutrality tests showed a recent expansion across the distribution range of S. tetraptera. The MaxEnt analysis showed that S. tetraptera had a narrow distribution range during the Last Glacial Maximum (LGM) and a wide distribution range during the current time, with predictions into the future showing the distribution range of S. tetraptera expanding.

CONCLUSION

Our study implies that the current geographic and genetic distribution of S. tetraptera is likely to have been shaped by Quaternary periods. Multiple microrefugia of S. tetraptera existed during Quaternary glaciations. Rapid intraspecific diversification and hybridization and/or introgression may have played a vital role in shaping the current distribution patterns of S. tetraptera. The distribution range of S. tetraptera appeared to have experienced contraction during the LGM; in the future, when the global climate becomes warmer with rising carbon dioxide levels, the distribution of S. tetraptera will expand.

Three-dimensional species distribution modelling reveals the realized spatial niche for coral recruitment on contemporary Caribbean reefs

The three-dimensional structure of habitats is a critical component of species' niches driving coexistence in species-rich ecosystems. However, its influence on structuring and partitioning recruitment niches has not been widely addressed. We developed a new method to combine species distribution modelling and structure from motion, and characterized three-dimensional recruitment niches of two ecosystem engineers on Caribbean coral reefs, scleractinian corals and gorgonians. Fine-scale roughness was the most important predictor of suitable habitat for both taxa, and their niches largely overlapped, primarily due to scleractinians' broader niche breadth. Crevices and holes at mm scales on calcareous rock with low coral cover were more suitable for octocorals than for scleractinian recruits, suggesting that the decline in scleractinian corals is facilitating the recruitment of octocorals on contemporary Caribbean reefs. However, the relative abundances of the taxa were independent of the amount of suitable habitat on the reef, emphasizing that niche processes alone do not predict recruitment rates.

Conservation planning for the endemic and endangered medicinal plants under the climate change and human disturbance: a case study of Gentiana manshurica in China

Human activities and climate change have significantly impacted the quantity and sustainable utilization of medicinal plants. Gentiana manshurica Kitagawa, a high-quality original species of Gentianae Radix et Rhizoma, has significant medicinal value. However, wild resources have experienced a sharp decline due to human excavation, habitat destruction, and other factors. Consequently, it has been classified as an Endangered (EN) species on the IUCN Red List and is considered a third-level national key-protected medicinal material in China. The effects of climate change on G. manshurica are not yet known in the context of the severe negative impacts of climate change on most species. In this study, an optimized MaxEnt model was used to predict the current and future potential distribution of G. manshurica. In addition, land use data in 1980, 2000, and 2020 were used to calculate habitat quality by InVEST model and landscape fragmentation by the Fragstats model. Finally, using the above-calculated results, the priority protection areas and wild tending areas of G. manshurica were planned in ZONATION software. The results show that the suitable area is mainly distributed in the central part of the Songnen Plain. Bio15, bio03, bio01, and clay content are the environmental variables affecting the distribution. In general, the future potential distribution is expected to show an increasing trend. However, the species is expected to become threatened as carbon emission scenarios and years increase gradually. At worst, the high suitability area is expected to disappear completely under SSP585-2090s. Combined with the t-test, this could be due to pressure from bio01. The migration trends of climate niche centroid are inconsistent and do not all move to higher latitudes under different carbon emission scenarios. Over the past 40 years, habitat quality in the current potential distribution has declined yearly, and natural habitat has gradually fragmented. Existing reserves protect only 9.52% of G. manshurica's priority conservation area. To avoid extinction risk and increase the practicality of the results, we clarified the hotspot counties of priority protection area gaps and wild tending areas. These results can provide an essential reference and decision basis for effectively protecting G. manshurica under climate change.

Mapping Brazilian Expansion Risk Levels of Mango Weevil (Sternochetus mangiferae Fabricius) Based on MaxEnt

The mango weevil, Sternochetus mangiferae (Fabricius) (Curculionidae), pest present in Brazil and is restricted to some municipalities in the Rio de Janeiro State. This curculionid attacks the mango crop exclusively and puts mango production globally at risk, especially those destined for export. Using ecological modeling tools, this study is the first to map the potential risk of S. mangiferae in Brazil. We aimed to identify the potential distribution of this pest in Brazilian states, drawing up thematic maps of regions that present suitable and unsuitable climatic conditions for the establishment of the pest using the MaxEnt ecological niche model. The average annual temperature, the annual precipitation, the average daytime temperature range, and the annual temperature range were the variables that contributed most to the selected model. The MaxEnt model predicted highly suitable areas for S. mangiferae throughout the Brazilian coast, especially on the northeast coast. The region responsible for more than 50% of mango production in Brazil, the São Francisco Valley, was classified by the model with suitability for the pest; it can impacts exportations due to the imposition of phytosanitary barriers. This information can be used in strategies to prevent the introduction and establishment of this pest in new areas and monitor programs in areas with recent occurrence. In addition, the model results can be used in future research plans on S. mangiferae in worldwide modeling studies and climate change scenarios.

Cryptosporidiosis threat under climate change in China: prediction and validation of habitat suitability and outbreak risk for human-derived Cryptosporidium based on ecological niche models

BACKGROUND

Cryptosporidiosis is a zoonotic intestinal infectious disease caused by Cryptosporidium spp., and its transmission is highly influenced by climate factors. In the present study, the potential spatial distribution of Cryptosporidium in China was predicted based on ecological niche models for cryptosporidiosis epidemic risk warning and prevention and control.

METHODS

The applicability of existing Cryptosporidium presence points in ENM analysis was investigated based on data from monitoring sites in 2011-2019. Cryptosporidium occurrence data for China and neighboring countries were extracted and used to construct the ENMs, namely Maxent, Bioclim, Domain, and Garp. Models were evaluated based on Receiver Operating Characteristic curve, Kappa, and True Skill Statistic coefficients. The best model was constructed using Cryptosporidium data and climate variables during 1986‒2010, and used to analyze the effects of climate factors on Cryptosporidium distribution. The climate variables for the period 2011‒2100 were projected to the simulation results to predict the ecological adaptability and potential distribution of Cryptosporidium in future in China.

RESULTS

The Maxent model (AUC = 0.95, maximum Kappa = 0.91, maximum TSS = 1.00) fit better than the other three models and was thus considered the best ENM for predicting Cryptosporidium habitat suitability. The major suitable habitats for human-derived Cryptosporidium in China were located in some high-population density areas, especially in the middle and lower reaches of the Yangtze River, the lower reaches of the Yellow River, and the Huai and the Pearl River Basins (cloglog value of habitat suitability > 0.9). Under future climate change, non-suitable habitats for Cryptosporidium will shrink, while highly suitable habitats will expand significantly (χ² = 76.641, P < 0.01; χ² = 86.836, P < 0.01), and the main changes will likely be concentrated in the northeastern, southwestern, and northwestern regions.

CONCLUSIONS

The Maxent model is applicable in prediction of Cryptosporidium habitat suitability and can achieve excellent simulation results. These results suggest a current high risk of transmission and significant pressure for cryptosporidiosis prevention and control in China. Against a future climate change background, Cryptosporidium may gain more suitable habitats within China. Constructing a national surveillance network could facilitate further elucidation of the epidemiological trends and transmission patterns of cryptosporidiosis, and mitigate the associated epidemic and outbreak risks.

The Distribution Pattern and Species Richness of Scorpionflies (Mecoptera: Panorpidae)

The uneven distribution of species diversity on earth, with mountainous regions housing half of the high species diversity areas, makes mountain ecosystems vital to biodiversity conservation. The Panorpidae are ecological indicators, ideal for studying the impact of climate change on potential insect distribution. This study examines the impact of environmental factors on the distribution of the Panorpidae and analyzes how their distribution has changed over three historical periods, the Last Interglacial (LIG), the Last Glacial Maximum (LGM), and Current. The MaxEnt model is used to predict the potential distribution area of Panorpidae based on global distribution data. The results show that precipitation and elevation are the primary factors affecting species richness, and the suitable areas for Panorpidae are distributed in southeastern North America, Europe, and southeastern Asia. Throughout the three historical periods, there was an initial increase followed by a decrease in the area of suitable habitats. During the LGM period, there was a maximum range of suitable habitats for cool-adapted insects, such as scorpionflies. Under the scenarios of global warming, the suitable habitats for Panorpidae would shrink, posing a challenge to the conservation of biodiversity. The study provides insights into the potential geographic range of Panorpidae and helps understand the impact of climate change on their distribution.

Linking life history to landscape for threatened species conservation in a multiuse region

Landscape-scale conservation that considers metapopulation dynamics will be essential for preventing declines of species facing multiple threats to their survival. Toward this end, we developed a novel approach that combines occurrence records, spatial-environmental data, and genetic information to model habitat, connectivity, and patterns of genetic structure and link spatial attributes to underlying ecological mechanisms. Using the threatened northern quoll (Dasyurus hallucatus) as a case study, we applied this approach to address the need for conservation decision-making tools that promote resilient metapopulations of this threatened species in the Pilbara, Western Australia, a multiuse landscape that is a hotspot for biodiversity and mining. Habitat and connectivity were predicted by different landscape characteristics. Whereas habitat suitability was overwhelmingly driven by terrain ruggedness, dispersal was facilitated by proximity to watercourses. Although there is limited evidence for major physical barriers in the Pilbara, areas with high silt and clay content (i.e., alluvial and hardpan plains) showed high resistance to dispersal. Climate subtlety shaped distributions and patterns of genetic turnover, suggesting the potential for local adaptation. By understanding these spatial-environmental associations and linking them to life-history and metapopulation dynamics, we highlight opportunities to provide targeted species management. To support this, we have created habitat, connectivity, and genetic uniqueness maps for conservation decision-making in the region. These tools have the potential to provide a more holistic approach to conservation in multiuse landscapes globally.

Integrating eDNA and citizen science observations to model distribution of a temperate freshwater turtle near its northern range limit

Background

To determine species distributions and the factors underlying them, reliable occurrence data are crucial. Assembling such data can be challenging for species with cryptic life histories or that occur at low densities.

Methods

We developed species-specific eDNA protocols, from sampling through data interpretation, to detect the common musk turtle (Sternotherus odoratus) and tested whether eDNA occurrences change our understanding of the species distribution and the factors that shape its northern range limit. We used Species Distribution Models (SDMs) with full parameter optimization on citizen science observations of S. odoratus in Southern Ontario alone and together with eDNA occurrences.

Results

Our eDNA protocol was robust and sensitive. SDMs built from traditional observations and those supplemented with eDNA detections were comparable in prediction accuracy. However, models with eDNA detections suggested that the distribution of S. odoratus in Southern Ontario is underestimated, especially near its northern range limit, and that it is shaped by thermal conditions, hydrology, and elevation. Our study underscores the promise of eDNA for surveying cryptic aquatic organisms in undocumented areas, and how such insights can help us to improve our understanding of species distributions.

Cordyceps cicadae and Cordyceps gunnii have closer species correlation with Cordyceps sinensis: from the perspective of metabonomic and MaxEnt models

Cordyceps sinensis is a second-class nationally-protected medicinal fungus and functional food. Cordyceps sinensis resources are endangered, and finding new medicinal materials is a fast and economical way to meet the current demonstrated demand, which can effectively solve the shortage of C. sinensis resources. In this study, the metabolite characteristics of Cordyceps were comprehensively revealed by LC-QTOF-MS technology. The maxent model can be used to predict the habitat suitability distribution of Cordyceps and screen out the main climatic factors affecting its distribution. The correlation model between climate factors and chemical components was established by Pearson correlation analysis. Finally, based on the analysis of climate factors and metabolites, we will analyze the high correlation species with C. sinensis, and develop them as possible alternative species of C. sinensis in the future. The results showed that the suitable area of Cordyceps cicadae demonstrated a downward trend, while that of C. sinensis, Cordyceps militaris and Cordyceps gunnii demonstrated an upwards trend. The suitable areas all shifted to the northwest. The temperature seasonality and max temperature of the warmest month are the maximum climatic factors affecting nucleosides. Compared with C. sinensis, the metabolic spectrum similarities of C. cicadae, C. militaris, and C. gunnii were 94.42%, 80.82%, and 91.00%, respectively. Cordyceps sinensis, C. cicadae, and C. gunnii were correlated well for compounds and climate factors. This study will explore whether C. cicadae, C. militaris and C. gunnii can be used as substitutes for C. sinensis. Our results may provide a reference for resource conservation and sustainable utilization of endangered C. sinensis.

The Fate of Endemic Species Specialized in Island Habitat under Climate Change in a Mediterranean High Mountain

Mediterranean high-mountain endemic species are particularly vulnerable to climatic changes in temperature, precipitation and snow-cover dynamics. Sierra Nevada (Spain) is a biodiversity hotspot in the western Mediterranean, with an enormous plant species richness and endemicity. Moehringia fontqueri is a threatened endemic plant restricted to north-facing siliceous rocks along a few ridges of the eastern Sierra Nevada. To guide conservation actions against climate change effects, here we propose the simultaneous assessment of the current reproductive success and the possible species' range changes between current and future climatic conditions, assessing separately different subpopulations by altitude. Reproductive success was tested through the seed-set data analysis. The species' current habitat suitability was modeled in Maxent using species occurrences, topographic, satellite and climatic variables. Future habitat suitability was carried out for two climatic scenarios (RCP 2.6 and 8.5). The results showed the lowest reproductive success at the lowest altitudes, and vice versa at the highest altitudes. Habitat suitability decreased by 80% from current conditions to the worst-case scenario (RCP 8.5). The lowest subpopulations were identified as the most vulnerable to climate change effects while the highest ones were the nearest to future suitable habitats. Our simultaneous assessment of reproductive success and habitat suitability aims to serve as a model to guide conservation, management and climate change mitigation strategies through adaptive management to safeguard the persistence of the maximum genetic pool of Mediterranean high-mountain plants threatened by climate change.

Environmental Niche Modelling Predicts a Contraction in the Potential Distribution of Two Boreal Owl Species under Different Climate Scenarios

Studying current and future geographic distribution is essential for conserving endangered species such as the Boreal Owl and Eurasian Pygmy Owl. The main aim of this study was to determine the potential distribution of both species in the Balkan Peninsula by using spatial distribution models (SDMs) in MaxEnt. We used data from field surveys, the scientific and grey literature, and an online database. We considered the current time and two future periods, 2041-2060 and 2061-2080. For future periods, we included different climate scenarios (SSP 126, 245, 370, and 585) in studying the potential geographic distribution of both species. We identified two types of potential future refugia for species: in situ and ex situ. Our study shows the highly suitable area for the Boreal Owl increased during the 2041-2060 period compared with the current area in all scenarios, except in SSP 585. However, during the 2061-2080 period, the highly suitable areas contracted. For the Eurasian Pygmy Owl, highly suitable areas decreased during 2041-2060, but during the 2061-2080 period, it was larger than the current area. Our study is of importance for conservation and preserving areas of potential distribution and refugia for Boreal and Eurasian Pygmy Owls in the face of climate change.