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There are 11 species of triatomines in the USA, with seven reported in the American Southwest. These species are capable of transmitting Trypanosoma cruzi, the etiological agent of Chagas disease, but are generally sylvatic and rarely infect humans in the USA. iNaturalist is one of the most popular citizen science data portals, where users record encounters with any individual organism. As of November 2023, iNaturalist reported 722 confirmed triatomine observations in the American Southwest. Maximum entropy ecological niche modelling and bioclimatic environmental variables were used to predict zones of highest human-triatomine interaction. Models fit well for Triatoma protracta (0.85), T. rubida (0.94), and T. recurva (0.96). Precipitation in the warmest quarter was most predictive of T. protracta presence, while precipitation in the driest quarter was most predictive of T. rubida and T. recurva. Locations identified in the American Southwest with highest potential for human-triatomine interaction, and potential T. cruzi transmission, were coastal California, the Sierra Nevada foothills, southern Arizona and border areas of northern Mexico. Study findings can be used for targeted surveillance efforts to address the paucity of contemporary information regarding triatomine species diversity and geographical and ecological associations in the American Southwest. [ABSTRACT FROM AUTHOR]

By 1985, approximately 400,000 ha of the keystone species Shinnery oak's (Quercus havardii) historic distribution had been eliminated for agricultural purposes across the southwestern United States. These trends indicate a need for targeted conservation and restoration efforts, especially considering the increased attention received for its role in providing habitat for endangered fauna. Setting spatially explicit conservation targets can be challenging for species with limited distributions, as the change in climate conditions over time may disconnect the relationship between environmental suitability and static, topo‐edaphic factors. Our objective was to identify areas for Shinnery oak restoration and conservation and explore the role climate plays in determining these areas while considering topo‐edaphic relationships. We constructed ecological niche models to estimate Shinnery oak's distribution under current climate conditions and temporally transferred our model using an ensemble‐mean of general circulation models to identify areas predicted to retain environmental suitability for Shinnery oak through 2100. The current distribution model was best informed by one climate and two topo‐edaphic variables. We created a second distribution model excluding topo‐edaphic variables to estimate future plant–climate relationships. Incorporating insights from models informed by both static (e.g. soil) and dynamic (e.g. climate) variables, we identified areas for conservation characterized by persistent climate suitability and high soil type suitability. Lastly, we incorporated data on land use and ownership to explore socio‐ecological influences on management decisions. By identifying areas of agreement between our modeled distributions and considering social context, we prioritized conservation areas where environmental suitability persists under changing conditions to facilitate restoration success. [ABSTRACT FROM AUTHOR]

The New Mexico jumping mouse (Zapus luteus) is a federally endangered species that relies on riparian sites of the southwestern United States. Only isolated populations occur throughout its range and detecting potential suitable environments and identifying new populations are important for long‐term conservation of genetic diversity and habitat restoration by management agencies. We used a presence‐only data approach compiled from multiple surveys since 2000 in Arizona, Colorado, and New Mexico with bioclimatic and vegetation variables to generate species distribution models for the species. Our models predicted environmentally suitable areas outside the current species management units that could be prioritized in surveys. Our models also highlighted opportunities for collaboration among federal, state, tribal, and private landowners and managers to secure habitat and connectivity for the species and its long‐term survival. [ABSTRACT FROM AUTHOR]

This study elucidates the distribution of plants in Great Himalayan National Park (GHNP), India, in current and different future climate change scenarios. The distribution of plants and habitat suitability in GHNP due to climate change was analyzed by MaxEnt, species distribution model (SDM) algorithm. In this study, species presence records were retrieved through field survey and published literature. We have projected the distribution of 44 plant species using MaxEnt and tested whether GHNP is performing well in conserving the plant species. Initially, we have constructed a model for each species and created the habitat suitability map from average of ascii files and later we added the maps of all species in order to make binary map to show the species richness in the selected climate scenarios. The model was created using the HADGEM-2 global circulation model in 2050 and 2070 years by using climate change situations of RCP 2.6 and RCP 8.5. The area under curve (AUC) values in the final models of 44 plant species were in the range 0.70–0.97 that indicates statistically significant results. The model identified precipitation of driest month followed by altitude and annual mean temperature as most determining variables in the distribution of plants of GHNP in selected climate scenarios. In the present study, we found that overall suitable habitat increased for nine species, decreased for thirty-four, and unchanged for one plant species in terms of percent area change from current to future scenarios. So these nine species were found to be more adaptable towards changing climate than the other plant species in this study. The species richness was high in western and southwestern parts of GHNP in the current scenario, however under future climatic scenarios, species richness shows a decreasing trend. Based on our findings, it can be concluded that GHNP should be prioritized for conserving the plant species. [ABSTRACT FROM AUTHOR]

There are many ancient Zelkova schneideriana trees that are over one hundred years old in Hunan Province, China, which have cultural and ecological values. However, the distribution, growth status and determinants of these Z. schneideriana remain to be explored. We collected data on the location and growth status of Z. schneideriana from the Information Management System of Ancient and Precious Trees in Hunan Province. Then, Average Nearest Neighbor and kernel density analysis were applied to investigate the distribution patterns and characteristics of Z. schneideriana. The potential distribution area and habitat suitability of Z. schneideriana were studied using the MaxEnt model. Finally, the factors affecting the distribution and growth status of Z. schneideriana were analyzed. The results showed that there were 501 Z. schneideriana in Hunan Province, distributed in 34 counties of 10 prefecture-level cities. The spatial distribution of these Z. schneideriana was clustered, with Chengbu Miao Autonomous County and Xinhuang Dong Autonomous County being high-density distribution areas. More than 60% of Z. schneideriana occurs at altitudes between 400 and 800 m. The most important factor influencing its population distribution is solar radiation in May (Srad5), followed by precipitation in the driest month (Bio14), with the total contribution of 82.63%. Specifically, when Srad5 > 15,544 (KJ/ (m2 × day)) and Bio14 < 24 mm, the area is not suitable (LOV < 0.2) for the growth of Z. schneideriana. In various habitats, Z. schneideriana exhibits differences in growth conditions and tree characteristics. The highest number of Z. schneideriana (68.66%) are found along rural roadsides, but they grow in poorer conditions, are negatively impacted by road construction, and have lower tree height and crown width than that in other habitats. The size of Z. schneideriana is influenced by intraspecific competition, with scattered Z. schneideriana being taller and larger. These results can provide guidance for the conservation, management and tourism development of Z. schneideriana. [ABSTRACT FROM AUTHOR]

Global climate warming has led to changes in the suitable habitats for fungi. Colletotrichum acutatum, a common fungus causing anthracnose disease, is widely distributed in southern China. Currently, research on the relationship between C. acutatum and environmental warming was limited. In this study, MaxEnt and ArcGIS software were used to predict the suitable habitats of C. acutatum under current and future climate conditions based on its occurrence records and environmental factors. The optimal MaxEnt model parameters were set as feature combination (FC)  =  lp and regularization multiplier (RM)  =  2.6. Bio15, Bio12, Bio09, and Bio19 were identified as the main environmental factors influencing the distribution of C. acutatum. Under current climate conditions, C. acutatum was distributed across all continents globally, except Antarctica. In China, C. acutatum was primarily distributed south of the Qinling-Huaihe Line, with a total suitable area of 259.52  ×  104   km². Under future climate conditions, the potential suitable habitat area for C. acutatum was expected to increase and spread towards inland China. The results of this study provided timely risk assessment for the distribution and spread of C. acutatum in China and offer scientific guidance for monitoring and timely controlled of its distribution areas. [ABSTRACT FROM AUTHOR]

Cinnamomum cassia Presl. is a subtropical plant that is used for food and medicine. Climate change has changed the suitable habitats of medicinal plants, which might have repercussions for the efficacy of herbal remedies. In this study, the potential distribution in each period of Cinnamomum cassia was predicted and the quality in different suitable habitats was evaluated. According to the results, (1) precipitation, temperature, and soil are the primary environmental variables influencing C. cassia distribution. (2) The high-suitable habitats of current climate scenarios were predominantly located in the southern regions (Guangdong and Guangxi etc.) of China, with an area of 706,129.08 km2. Under future climate scenarios, suitable habitats will increasingly move northward, with a greater concentration south of the Yangtze River, particularly in the 2090s SSP585 scenario, the total area of newly extended suitable habitat reaches 312,963.53 km2. (3) HPLC and FTIR, combined with chemometrics, can be effective methods for identifying different suitable habitats of C. cassia. The content of trans-cinnamaldehyde (0.85%) is significantly higher in the high suitability habitat compared to the medium-low suitability habitat (0.30%). Our findings can offer valuable guidance for the identification of suitable C. cassia cultivation areas in China, as well as for the evaluation of C. cassia resource quality and the rational use of resources in different suitable habitats. [ABSTRACT FROM AUTHOR]

Eucalyptus has become one of the most widely planted species in tropical and subtropical regions in China, with important economic, ecological, and social values. However, it is currently unclear how climate change will affect different Eucalyptus species. Therefore, it is urgent to investigate the potential distribution and dynamics of Eucalyptus under current and future climate scenarios. In this study, we analyzed the potential distribution patterns of the three main Eucalyptus species (Eucalyptus grandis, Eucalyptus urophylla, and Eucalyptus tereticornis) under current and future climatic conditions (2041-2060 and 2061-2080) using the optimized MaxEnt model, which integrates a variety of environmental data including climate, topography, soil, and human influence. We also identified the main factors affecting the potential distributions of the three main Eucalyptus species. Themodel indicated that E. grandis exhibited heightened sensitivity to the mean temperature of the coldest quarter (7.0-20.0 °C) and annual mean temperature (11.9-24.2 °C), whereas E. urophylla displayed heightened sensitivity to precipitation of the warmest quarter (272-1694 mm) and annual precipitation (812-2624mm). Conversely, E. tereticornis demonstrated heightened sensitivity to annual mean temperature (12.7-24.5 °C) and temperature seasonality (63.8-598.9). Under the current climate, E. tereticornis had the widest suitable distribution area (124.91 × 104 km²), followed by E. grandis (124.89 × 104 km²) and E. urophylla (119.81 × 104 km²). Under future climate change scenarios, the suitable ranges of E. grandis, E. urophylla and E. tereticornis will continue to expand. This study highlights the importance of climate change in Eucalyptus distribution and provides quantified potential distribution maps for three Eucalyptus species under current and future climate conditions in China. This research offers valuable scientific insights pertinent to the management and rational site selection for Eucalyptus plantations. [ABSTRACT FROM AUTHOR]

The multifunctionality of ecosystem services (ES) represents multiple benefits that support ES supply and demand. Watershed planning entails the adequate distribution of land use provided by subsystems such as the drainage network (water and biota), riparian forests, and productive systems. However, the multiple ES provided for watersheds is still a critical issue in water system management instruments, such as territorial planning. This study proposes a method for applying the concept of ES multifunctionality in environmental zoning at the watershed scale, integrating information on the supply and demand of ES and its relationship with biodiversity and ecosystem processes. The suitability model included areas of multiple ES supply identified from an ES multifunctionality index (MESLI), the evaluation of trade-offs and synergies between ES through spatial analysis, ecosystem processes associated with distribution patterns of fauna species with some degree of threat and roles in ecosystem processes related to pollination, seed dispersal, and litter fragmentation in streams, using MaxEnt to recognize zones related to habitat conservation and priority areas for conservation. The proposed method integrates different spatial information inputs and supports territorial zoning based on ecological and biological components. Zones with potential ES multifunctionality highlight synergies between services, thereby improving the categorization of land use in the watershed. Models of species distribution and land use help in the spatial analysis of ES by highlighting the ecological functions of key species. The suitability model obtained presents a base scenario for the environmental management of watersheds and is an input for the formulation and negotiation of land use and conservation areas among the stakeholders in the watershed. [ABSTRACT FROM AUTHOR]

Rubus idaeus is a pivotal cultivated species of raspberry known for its attractive color, distinct flavor, and numerous health benefits. It can be used in pharmaceutical, cosmetics, agriculture and food industries not only as fresh but also as a processed product. Nowadays due to climatic changes, genetic diversity of cultivars has decreased dramatically. However, until now, the status of wild R. idaeus resources in China have not been exploited. In this study, we investigated the resources of wild R. idaeus in China to secure its future potential and sustainability. The MaxEnt model was used to predict R. idaeus suitable habitats and spatial distribution patterns for current and future climate scenarios, based on wild domestic geographic distribution data, current and future climate variables, and topographic variables. The results showed that, mean temperature of the coldest quarter (bio11), precipitation of the coldest quarter (bio19), precipitation of the warmest quarter (bio18), and temperature seasonality (bio4) were crucial factors affecting the distribution of R. idaeus. Presently, the suitable habitats were mainly distributed in the north of China including Xinjiang, Inner Mongolia, Gansu, Ningxia, Shaanxi, Shanxi, Hebei, Beijing, Liaoning, Jilin, Heilongjiang. According to our results, in 2050s, the total suitable habitat area of R. idaeus will increase under SSP1-2.6 and then will be decreased with climate change, while in the 2090s, the total suitable habitat area will continue to decrease. From the present to the 2090s, the centroid distribution of R. idaeus in China will shift towards the east and the species will always be present in Inner Mongolia. Our results provide wild resource information and theoretical reference for the protection and rational utilization of R. idaeus. [ABSTRACT FROM AUTHOR]

Small felids play pivotal roles in India's ecosystems, regulating prey populations, facilitating nutrient transfer, and safeguarding critical habitats. Despite their ecological significance, these species receive inadequate conservation attention, contrasting sharply with the focus on larger carnivores. Our review assesses the conservation status of nine native Indian small felids, aiming to consolidate data for improved species conservation and to draw connections with global small carnivore conservation efforts. Over the last 50 years, data scarcity has impeded comprehensive understanding, hindering the assessment of crucial ecological dynamics.We delve into the factors influencing the distribution and abundance of small cats across India, identifying climate, human disturbances, the presence of large carnivores, topography, and vegetation cover as influential determinants. Notably, trade records reveal a decline in small wild felid trade since 1997, suggesting potentially positive outcomes from enhanced law‐enforcement measures.Highlighting the necessity of robust ecological data, particularly pertaining to demographic parameters, prey–predator relationships, and responses to human‐induced habitat alterations, we advocate for integrating these insights into conservation strategies. We stress the urgency of collaborative efforts supported by unwavering political commitment and sustained financial backing to ensure the successful conservation of small felids globally.This review underscores the imperative of filling knowledge gaps, integrating ecological findings into conservation frameworks, and fostering international collaborations to preserve the crucial ecological roles of small felids in terrestrial ecosystems worldwide. [ABSTRACT FROM AUTHOR]

Introduced species may exhibit variations in their preferred climatic niches between their native and introduced ranges, which can have important implications for the transferability of distribution models. In the Himalayan ecoregion, little is known about the geographic distribution and climatic niche overlap between native and introduced cold‐water species. Here, we used the COUE (centroid shift, overlap, unfilling, and expansion) framework to explore the invasive potential of rainbow (Oncorhynchus mykiss) and brown (Salmo trutta fario) trout and corresponding climatic niche overlap with native snow trout (Schizothorax plagiostomus and Schizothorax richardsonii) in the Indus and Ganges River basins. Although we found more stability in the climatic niche for O. mykiss (93%) than S. trutta (58%), both species do not conserve their climatic niches in this region (p > 0.05). S. trutta has expanded more toward new environmental conditions (42%) compared to O. mykiss (7%). However, there are still available environmental gaps that O. mykiss and S. trutta can potentially occupy in the future. There was a higher overlap in climatic niches between S. plagiostomus and O. mykiss and between S. richardsonii and S. trutta. Observed shifts in climatic niches of these introduced species can negatively affect the transferability of distribution models, which may underestimate the assessments of habitat suitability for introduced trout in the Himalayas. Our study demonstrates that the information on climatic niche dynamics can inform the model‐building process and improve the transferability and predictive performance to better assess vulnerability of sensitive habitats to introduced species in the Himalayas and elsewhere. [ABSTRACT FROM AUTHOR]

Understanding current fire dynamics in the Amazon is vital for designing effective fire management strategies and setting a baseline for climate change projections. This study aimed to analyze recent fire probabilities and project future "fire niches" under global warming scenarios across the Legal Amazon, a scale chosen for its relevance in social and economic planning. Utilizing the maximum entropy method, this study combined a complex set of predictors with fire occurrences detected during 1985–2022. It allowed for the estimation of current fire patterns and projecting changes for the near future (2020–2040) under two contrasting socioeconomic pathways. The results showed strong model performance, with AUC values consistently above 0.85. Key predictors included "Distance to Farming" (53.4%), "Distance to Non-Vegetated Areas" (11.2%), and "Temperature Seasonality" (9.3%), revealing significant influences from human activities alongside climatic predictors. The baseline model indicated that 26.5% of the Amazon has "moderate" to "very high" fire propensity, especially in the southern and southeastern regions, notably the "Arc of Deforestation". Future projections suggest that fire-prone areas may expand, particularly in the southern border regions and near the Amazon riverbanks. The findings underscore the importance of incorporating both ecological and human factors into fire management strategies to effectively address future risks. [ABSTRACT FROM AUTHOR]

Climate change has increasingly impacted the marine environment, with various marine environmental factors interacting to influence fish distribution. Assessing the impact of climate change on the future distribution of fish depends on understanding how biological responses interact with environmental conditions. Enhancing our understanding of the potential impacts of climate change is crucial for the sustainable development of marine fisheries. In this study, we analyzed the habitat suitability of Scomber japonicus and Konosirus punctatus in the coastal waters of China (17°–41° N, 107°–130° E) using marine environmental data, including, as follows: sea surface temperature (SST); sea surface salinity (SSS); pH; and biological occurrence data from 2000 to 2010. A maximum entropy (MaxEnt) model was employed to predict the future distribution of these two species based on the shared socioeconomic pathway (SSP) scenarios for 2040–2050 and 2090–2100. The results indicate that climate change will significantly affect the future habitat distribution of S. japonicus and K. punctatus, leading to a decrease in suitable habitat areas offshore China and a gradual shift northeastward in the center of these habitats. These findings are essential for understanding the impacts of climate change on the distribution of S. japonicus and K. punctatus, with significant implications for fisheries resource assessment and management. [ABSTRACT FROM AUTHOR]

We conducted a habitat suitability assessment for two burrowing rodents, Anatolian or Nehring's blind mole rat (Nannospalax xanthodon) and Harting's vole (Microtus hartingi), on the island of Lesvos using a niche-based approach. We collected data on the presence of the two species across the island and selected several environmental variables, including land cover, geology, and habitat topography, to assess their influence on habitat suitability. We used the Maxent species distribution modelling algorithm to predict suitable habitats. The results showed that both species preferred habitats with low slopes and specific geological substrates, i.e., alluvial deposits and volcanic rocks. M. hartingi showed a preference for open habitats such as saltmarshes and non-irrigated arable land, while N. xanthodon preferred non-irrigated arable land, pastures, and discontinuous urban fabric. The model predicted a wider area of suitable habitats for Microtus hartingi compared to N. xanthodon. Interestingly, the two species are absent from the southeastern part of the island despite our model predicting high suitability; this indicates that a natural barrier of hilly terrain, extensive pine forests, and limestone rock formations may exist that impedes dispersal. Our study provides valuable insights into the habitat preferences of these two burrowing rodents on the island of Lesvos, which can inform biodiversity conservation and ecosystem management strategies. [ABSTRACT FROM AUTHOR]

Simple Summary: Latoia consocia Walker is an important herbivorous pest that has severely invaded North China in recent years. This study utilized the MaxEnt model system to investigate the impact of climate conditions on its distribution. The results show that the optimum temperature range of L. consocia is 5~14.5 °C, and the optimum annual precipitation range is 1980~2580 mm. With the warming of the climate, the potential habitat area of L. consocia will decrease in the future. These findings help to provide a scientific basis for pest control and inform scientific management strategies. Latoia consocia Walker is an important phytophagous pest that has rapidly spread across North China in recent years, posing a severe threat to related plants. To study the impact of climatic conditions on its distribution and to predict its distribution under current and future climate conditions, the MaxEnt niche model and ArcGIS 10.8 software were used. The results showed that the MaxEnt model performs well in predicting the distribution of L. consocia, with an AUC value of 0.913. The annual precipitation (Bio12), the precipitation of the driest month (Bio14), the temperature annual range (Bio7), and the minimum temperature of the coldest month (Bio6) are key environmental factors affecting the potential distribution of L. consocia. Under current climate conditions, L. consocia has a highly suitable growth area of 2243 km2 in China, among which Taiwan has the largest high-suitable area with a total area of 1450 km2. With climate warming, the potential habitat area for L. consocia shows an overall decreasing trend in future. This work provides a scientific basis for research on pest control and ecological protection. A "graded response" detection and early warning system, as well as prevention and control strategies, can be developed for potentially suitable areas to effectively address this pest challenge. [ABSTRACT FROM AUTHOR]

This study aims to clarify the taxonomy of Loxanthocereus riomajensis, as well as to understand its actual and potential geographic distribution, and to present its conservation status. Specialized literature was reviewed, and field visits were conducted. The collected data, including herbarium samples, presence records, and additional information, were used to describe the species in detail, create a geographical distribution map, generate potential distribution models using the MaxEnt algorithm, and assess its conservation status using IUCN considerations. The results demonstrate that morphologically, L. riomajensis is an independent species endemic to the departament of Arequipa, found in the provinces of Condesuyos and Caylloma, spanning an altitudinal range from 1600 to 2100 m asl. The potential distribution covers an area of 1135.3 km², in the provinces of Condesuyos, Castilla, La Unión, Caravelí, Caylloma, and Arequipa. Regarding its conservation status, it is classified as endangered (EN). Finally, a lectotype is designated. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The widespread and complex formation of saline soils in China significantly affects the sustainable development of regional ecosystems. Intense climate changes and regional land use further exacerbate the uncertainties faced by ecosystems in saline areas. Therefore, studying the distribution characteristics of typical halophytic vegetation under the influence of climate change and human activities, and exploring their potential distribution areas, is crucial for maintaining ecological security in saline regions. This study focuses on Tamarix chinensis, Tamarix austromongolica, and Tamarix leptostachya, integrating geographic information systems, remote sensing, species distribution models, and landscape ecological risk (LER) theories and technologies. An optimized MaxEnt model was established using the ENMeval package, incorporating 143, 173, and 213 distribution records and 13 selected environmental variables to simulate the potential suitable habitats of these three Tamarix species. A quantitative assessment of the spatial characteristics and the area of their potential geographical distribution was conducted. Additionally, a landscape ecological risk assessment (LERA) of the highly suitable habitats of these three Tamarix species was performed using land use data from 1980 to 2020, and the results of the LERA were quantified using the Landscape Risk Index (LERI). The results showed that the suitable areas of Tamarix chinensis, Tamarix austromongolica, and Tamarix leptostachya were 9.09 × 105 km2, 6.03 × 105 km2, and 5.20 × 105 km2, respectively, and that the highly suitable habitats for the three species were concentrated in flat areas such as plains and basins. Tamarix austromongolica faced increasing ecological risk in 27.22% of its highly suitable habitat, concentrated in the northern region, followed by Tamarix chinensis in 16.70% of its area with increasing ecological risk, concentrated in the western and northern highly suitable habitats; Tamarix chinensis was the least affected, with an increase in ecological risk in only 1.38% of its area. This study provides valuable insights for the protection of halophytic vegetation, represented by Tamarix, in the context of China's national land development. [ABSTRACT FROM AUTHOR]

Ixodes ricinus ticks are ubiquitous in Europe, including in North-East Italy. These ticks are important vectors of several zoonotic pathogens of public health relevance. In this study, the habitat suitability range of I. ricinus ticks infected with zoonotic pathogens was predicted in North-East Italy, and relevant spatial predictors were identified. In 2015–2021, ticks were collected at 26 sampling sites in the study area. The collected ticks were screened for the presence of pathogens using PCR assays. For Borrelia, Rickettsia and Anaplasma/Ehrlichia species, data allowed for ecological niche modelling using Maxent. Environmental determinants potentially related to tick habitat suitability were used as model inputs. Predicted suitable habitat distributions revealed hotspots of the probability of pathogen presence in I. ricinus ticks mainly in the central and upper parts of the study area. Key environmental predictors were temperature, rainfall and altitude, and vegetation index for specific pathogens (Rickettsia and Anaplasma/Ehrlichia species). Increased risk of exposure to tick-borne pathogens upon tick bites in the predicted hotspot areas can, therefore, be expected. This provides useful information for public health risk managers in this and other similar regions. [ABSTRACT FROM AUTHOR]

AbstractSudden outbreaks of agricultural pests are increasing in India due to the growing prominence of environmental issues like global warming, the occurrence of weather extremes, and hydrological extremes. Climate change impacts the developmental rates and population dynamics of agricultural pests. As rice is a staple food widely used in India, it often suffers intensive damage by various pests, leading to a considerable decrease in crop yield. One of the most common pests in rice fields in India and neighboring countries is the rice thrips (Stenchaetothrips biformis). However, the degree of pest infestation of rice crops under climate change scenarios is poorly known. Therefore, this study aimed to understand the potential geographical distribution of the rice thrips in India for future scenarios using the MaxEnt modeling framework. Future projections from global climate models (GCMs), such as HadGEM3-GC31 and MPI-ESMI-2, are used to predict the most affected regions in 2050 under three greenhouse gas emission scenarios: SSP1-2.6, SSP3-4.5, and SSP5-8.5. The results from the MaxEnt indicate that the southern and northeastern parts of India will be highly affected by rice thrips in 2050. The affected number of districts are found to be 256, 330 and 313 under SSP1-2.6, SSP3-4.5, and SSP5-8.5 scenarios, respectively. It has been observed that the maximum temperature is the most influential climatic parameter for the geographical distribution of rice thrips, followed by the annual mean and minimum temperatures. It can be concluded from these results that the elevated temperature enhances the growth and distribution of rice thrips. [ABSTRACT FROM AUTHOR]

Nature-based solutions (NbS) offer an exciting opportunity to work with nature to conserve heritage sites and objects. Soft capping is a novel form of NbS used commonly in Britain and Ireland to help conserve ruined and free-standing walls; soil and vegetation is placed on the wall head to help reduce deterioration by buffering thermal fluctuations and regulating moisture. While this conservation practice has proved cheaper and more effective at reducing deterioration than traditional hard capping, soft caps need to be resilient to future environmental changes. Previous research has shown that the sedum species commonly used in soft caps are vulnerable to climate change. Thus, following feedback from an interactive webinar with practicing heritage professionals, here we assess the climate resilience of four grass species commonly found in western Europe as possible soft-capping species: Festuca rubra (red fescue), Poa pratensis (smooth meadow-grass), Catapodium rigidum (fern-grass) and Poa annua (annual meadow-grass). We use species distribution modelling (Maxent) to assess the likelihood of species survival by mid and end century based on presence probabilities derived using three climate models (HadGEM3-GC31-LL, IPSL-CM6A-LR, and MIROC6). Results show that all four species are resilient under mid-century projections, and P. annua proved resilient under all scenarios. Therefore, using turf-based soft caps incorporating one or more of these grass species could enhance the future resilience of this conservation technique. Given the growing interest in the use of nature-based approaches to heritage conservation, our study represents an important attempt to account for and adapt to a changing climate. [ABSTRACT FROM AUTHOR]

Introduction: Jacaranda mimosifolia, native to South America, is a notable ornamental tree widely used in Chinese urban landscaping due to its aesthetic and environmental value. Despite its popularity, the cultivation of J. mimosifolia in China faces challenges, including intermittent failures in various regions. This study assesses the potential distribution of J. mimosifolia in China and its response to climate change, providing insights for its application and promotion. Methods: Using MaxEnt software, we developed an ecological niche model from 218 distribution records and selected 10 environmental variables to predict the tree's distribution under various climate scenarios (SSP126, SSP245, SSP370). Results: Our model demonstrates high predictive accuracy (AUC > 0.90) across scenarios, identifying key factors such as the mean temperature of the coldest quarter (bio11), precipitation of the driest month (bio14), temperature annual range (bio7), and minimum temperature of the coldest month (bio6). Their relative contribution rates were 49.3%, 18.4%, 15.6%, and 2.0%, respectively. The average temperature of the coldest quarter was not lower than 5°C, with the ideal range being 7.38~14.88°C. Currently, J. mimosifolia predominantly thrives in Taiwan, Fujian, Guangdong, Hainan, Guangxi, Yunnan, and to a lesser extent in the Sichuan Basin, southern Guizhou, Tibet, Hunan, Jiangxi, and Zhejiang province, covering a total area of approximately 122.19×104 km2. Future predictions indicate that under the SSP126 scenario, the most significant contraction occurs between the 2050s and 2070s, with a total change of -1.08×104 km2. Conversely, under the SSP370 scenario, the greatest expansion is observed from the 2030s to the 2050s, amounting to a change of 2.08×104 km2. Suitable area expansion is anticipated in most periods and scenarios, except for SSP126 in the 2070s, SSP245 in the 2050s, and SSP370 in the 2030s and 2070s. The distribution center shifts observed include movements northwestward, southwestward, and eastward with distances ranging from 5.12 km to 18.84 km. These shifts are likely driven by global warming, resulting in movements to higher elevations and latitudes. Discussion: These predictions will provide a solid theoretical foundation for the future application of J. mimosifolia in urban landscaping and serve as a valuable reference for its introduction and cultivation. [ABSTRACT FROM AUTHOR]

Simple Summary: Human activities have led to significant global habitat degradation and fragmentation. However, some carnivores have adapted to these conditions and are expanding, leading to closer coexistence with humans and potential conflicts. This study analysed over 350 sightings of the European wildcat (Felis silvestris) in NW Spain over 17 years to develop suitability models based on environmental, topographic, climatic, and human impact factors. Using MaxEnt, the study predicted the species' potential regional distribution. The results revealed that less than a third of the suitable areas for wildcats had confirmed their presence. Elevation, forested area percentage, and footpath density were key factors influencing wildcat presence, with the first two having positive effects and footpath density having a negative impact. The wildcats' preference for high and forested areas likely relates to food availability, while avoiding footpaths is linked to human-related mortality. These findings provide insights for conservation strategies to protect the species. Human activities have resulted in severe habitat degradation and fragmentation at a global scale. Despite this scenario, some carnivore species that adapted to the new conditions are expanding, leading to close coexistence with humans and the emergence of potential conflicts. In this work, we used a European wildcat (Felis silvestris) observations database of more than 350 sightings over 17 years in NW Spain to build suitability models based on environmental, topographic, climatic, and human impact variables. MaxEnt was used to analyse the availability of suitable habitats for the species at a regional scale. Our results showed that less than one third of the suitable area for the species had confirmed wildcat presence. Elevation, the percentage of forested area, and footpath density were the three main variables conditioning wildcat presence, with the first two variables having positive effects and footpath density negatively affecting wildcat presence. The selection of high areas and forest areas by the species seems to be related to food availability, while the avoidance of footpaths seems to be related to the fact that main mortality causes are linked to human disturbances. The results enhance the understanding of the European wildcat ecology and provide insight into potential management plans to ensure the conservation of one of the main populations of the species throughout its range. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

BackgroundAimsMethodsResultsConclusions\nKey policy highlightsThe remarkable floristic diversity of the Atlantic Forest is partly related to the diversity of environmental conditions across its vast geographic extent that has resulted in distinct plant communities. Four areas (Pernambuco, Bahia and Northern Espírito Santo, São Paulo, and Araguaia-Tocantins refugia) have been hypothesised to have particularly high modern diversity due to their being located in areas of multi-millennial climate stability.To test if species persistence and climatic stability over the last 21,000 years can predict hypothesised refugia in the Atlantic Forest domain.We modelled the distributions of 282 tree species from various habitats and projected them using eight past climate scenarios in the last c. 21000 years. Based on the spatial overlaps among these projections, we inferred three types of refugia: species persistence refugium based on probability of occurrence, climatic stability refugium based on climate suitability and bioclimatic refugium based on the intersection of the previous two. We validated model projections with fossil pollen data.We identified five potential bioclimatic refugia (Bahia and Northern Espírito Santo, São Paulo, Paranaíba, Serra do Espinhaço and Subtropical Serra do Mar) and one climatic stability refugium (Pernambuco).We validated three of four previously hypothesised refugia and detected two additional ones by considering both species persistence and climatic stability as key determinants of refugia. Conservation policies are needed to protect areas of refugia in the Brazilian Atlantic Forest, named: (1) Pernambuco bioclimatic refugium, (2) Bahia and Northern Espírito Santo bioclimatic refugium, (3) São Paulo bioclimatic refugium, (4) Paranaiba bioclimatic refugium, (5) Serra do Espinhaço bioclimatic refugium and (6) Subtropical Serra do Mar bioclimatic refugium;Financing studies with focus in determining refugia extension and understanding the region’s dynamics is key to promote the sustainability of ecosystem services in face of climate change;Promoting restoration strategies in regions considered as refugia can help sustain habitats.Conservation policies are needed to protect areas of refugia in the Brazilian Atlantic Forest, named: (1) Pernambuco bioclimatic refugium, (2) Bahia and Northern Espírito Santo bioclimatic refugium, (3) São Paulo bioclimatic refugium, (4) Paranaiba bioclimatic refugium, (5) Serra do Espinhaço bioclimatic refugium and (6) Subtropical Serra do Mar bioclimatic refugium;Financing studies with focus in determining refugia extension and understanding the region’s dynamics is key to promote the sustainability of ecosystem services in face of climate change;Promoting restoration strategies in regions considered as refugia can help sustain habitats. [ABSTRACT FROM AUTHOR]

The Fall armyworm, Spodoptera frugiperda is the most notorious invasive pest species on maize, recently reported in India. The continuous spread of Fall armyworms to new ecological niches raises global concern. The current study is the first in India to forecast the suitability of a habitat for S. frugiperda using a maximum entropy algorithm. Predictions were made based on an analysis of the relationship between 109 occurrence records of S. frugiperda and pertinent historical, current, and predicted climatic data for the study area. The model indicated that S. frugiperda could thrive in different habitats under the current environmental circumstances, particularly in the west and south Indian states like Maharashtra, Tamil Nadu, and Karnataka. The model predicted that areas with higher latitudes, particularly in Uttar Pradesh, Odisha, West Bengal, and some portions of Telangana, Rajasthan, Chhattisgarh, and Madhya Pradesh, as well as some tracts of northeastern states like Assam and Arunachal Pradesh, would have highly climate-suitable conditions for S. frugiperda to occur in the future. The average AUC value was 0.852, which indicates excellent accuracy of the prediction. A Jackknife test of variables indicated that isothermality with the highest gain value was determining the potential geographic distribution of S. frugiperda. Our results will be useful for serving as an early warning tool to guide decision-making and prevent further spread toward new areas in India. [ABSTRACT FROM AUTHOR]

Simple Summary: Cyrtotrachelus buqueti (C. buqueti) primarily feeds on the tender tips of clustered bamboo shoots and is currently one of the major pests in bamboo forests. In this study, the MaxEnt model, a species distribution model, was used to predict the potential current and future global distribution of suitable habitats for C. buqueti. The results indicate that climate change significantly impacts the area and geographical distribution of four suitable habitat zones for C. buqueti. Under future climate conditions, the area of high, medium, and low suitability zones is expected to increase. In this study, environmental factors affecting the distribution of this species were screened, with temperature and precipitation identified as two key factors likely influencing its distribution. This research provides a scientific basis for preventing the invasion and spread of C. buqueti. Cyrtotrachelus buqueti Guer is a major pest affecting bamboo forests economically, causing significant damage to bamboo forests in Sichuan Province, China. To understand how C. buqueti responds to future climate conditions, an optimized Maximum Entropy Model (Maxent) was used to simulate the potential global distribution patterns of C. buqueti under current climate conditions and three different future climate scenarios and to analyze the dominant factors influencing its distribution. The results indicate that Bio18 (precipitation of the warmest quarter), Bio04 (temperature seasonality), Bio06 (minimum temperature of the coldest month), and Bio02 (mean diurnal temperature range) are the main environmental factors affecting the distribution of this species. The global area of high-suitability habitats for C. buqueti is 9.00 × 104 km2, primarily distributed in China. Under three different future climate scenarios, there are varying degrees of expansion in both the total suitable habitat and the medium-suitability areas for C. buqueti. Under the SSP5-8.5 scenario, the medium-suitability area of the species increases the most, reaching 9.83 × 104 km2. Additionally, these findings can serve as a reference for developing and implementing control strategies, assisting relevant authorities in more effectively managing and controlling this pest, and mitigating its potential threats to bamboo forest ecosystems and economies. [ABSTRACT FROM AUTHOR]

Simple Summary: To predict the future distribution of Phenacoccus solenopsis Tinsley, this study combines MaxEnt modeling and meta-analysis. The MaxEnt model effectively predicts species distribution by analyzing environmental variables and occurrence data, providing accurate predictions of potential suitable habitats even with limited data. Meanwhile, the meta-analysis aggregates data from multiple experimental studies to assess P. solenopsis's response to temperature changes. By combining these methods, we can enhance prediction reliability and delve into the potential impacts of climate change on pest spread. This integrated approach offers detailed and reliable forecasts of P. solenopsis's future distribution, providing valuable insights for effective pest management and agricultural planning. Phenacoccus solenopsis Tinsley is a pest that poses a significant threat to agricultural crops, especially cotton, and is now widely distributed across many regions worldwide. In this study, we performed a meta-analysis on the collected experimental data and found that within the suitable temperature range, the survival rate of P. solenopsis increases with rising temperatures, indicating that climate plays a decisive role in its distribution. Using the MaxEnt model this study predicted that under three future climate scenarios (SSP1–2.6, SSP3–7.0, and SSP5–8.5), the distribution of P. solenopsis will expand and move towards higher latitudes. Climate change is the primary factor influencing changes in pest distribution. We conducted a meta-analysis of P. solenopsis, including seven independent studies covering 221 observation results, and examined the impact of temperature ranging from 18 °C to 39 °C on the developmental cycle of P. solenopsis. As the temperature rises, the development cycle of P. solenopsis gradually decreases. Additionally, by combining the MaxEnt model, we predicted the current and potential future distribution range of P. solenopsis. The results show that under future climate warming, the distribution area of P. solenopsis in China will expand. This research provides a theoretical basis for early monitoring and control of this pest's occurrence and spread. Therefore, the predictive results of this study will provide important information for managers in monitoring P. solenopsis and help them formulate relevant control strategies. [ABSTRACT FROM AUTHOR]

Climate change is a major threat to the Middle East and North Africa (MENA) region, which can cause significant harm to its plant and animal species. We predicted the habitat distribution of Cataglyphis nodus (Brullé, 1833) in MENA using MaxEnt models under current and future climate conditions. Our analysis indicates that the cooler regions of the MENA are projected to experience temperature increases of 1–2 °C by 2040 and 2–4 °C by the 2070s. Similarly, the warmer regions may anticipate rises of 0.5–2 °C by 2040 and 2–4 °C by the 2070s. MaxEnt model results for the current climate show good agreement with observations (mean area under the curve value of 0.975 and mean true statistical skill value of 0.8), indicating good potential habitat suitability for C. nodus. Significant factors affecting habitat suitability are elevation, mean monthly precipitation of the coldest quarter, temperature seasonality, and precipitation amount of the driest month. The research predicts that under Shared Socioeconomic Pathway (SSP) 1.2.6, the habitat suitability area may increase by 6% in 2040, while SSP 3.7.0 (0.3%) and SSP 5.8.5 (2.6%) predict a decrease. For 2070, SSP 5.8.5 predicts a 2.2% reduction in habitat suitability, while SSP 1.2.6 (0.4%) and SSP 3.7.0 (1.3%) predict slight increases. The results provide insight into the potential impacts of climate change on the species and regional biodiversity changes associated with the projected species distribution. [ABSTRACT FROM AUTHOR]

Climate change will have various impacts on the survival and development of species, and it is important to explore whether plants can adapt to future climate conditions. Dipteronia dyeriana is an endangered species with a narrow distribution in Yunnan, characterized by a small population size. However, studies on its current distribution and the impact of climate change on its future survival and distribution are very limited. In this study, the current and future (2050 and 2090) potential habitats under the SSP1-2.6, SSP3-7.0, and SSP5-8.5 scenarios were predicted using both maximum entropy (MaxEnt) and random forest (RF) models based on the current range points of D. dyeriana, soil, topographical, land cover, and climate data. The results showed that the RF model demonstrated significantly higher AUC, TSS, and Kappa scores than the MaxEnt model, suggesting high accuracy of the RF model. Isothermality (bio_3), minimum temperature of the coldest month (bio_6), and annual precipitation (bio_12) are the main environmental factors affecting the distribution of D. dyeriana. At present, the high suitability area of D. dyeriana is mainly concentrated in the eastern part of Yunnan Province and part of southern Tibet, covering an area of 3.53 × 104 km2. Under future climate change scenarios, the total area suitable for D. dyeriana is expected to increase. Although, the highly suitable area has a tendency to decrease. With regards to land use, more than 77.53% of the suitable land area (29.67 × 104 km2) could be used for D. dyeriana planting under different SSP scenarios. In 2090, the centroid shifts of the two models exhibit a consistent trend. Under the SSP1-2.6 scenario, the centroids transfer to the southeast. However, under the SSP3-7.0 and SSP5-8.5 scenarios, the centroids of high suitability areas migrate toward the northwest. In summary, this study enhances our understanding of the influence of climate change on the geographic range of D. dyeriana and provides essential theoretical backing for efforts in its conservation and cultivation. [ABSTRACT FROM AUTHOR]

Pine wilt disease (PWD) is a devastating plant disease caused by the pinewood nematode (PWN, Bursaphelenchus xylophilus) that is transmitted by several beetle species in the genus, Monochamus. Once present, the disease is difficult to control. Prevention rather than control is regarded as an effective strategy for PWD management. Central to this prevention strategy is the ability to predict the potential distribution of the disease. Here, we employed an integrated MaxEnt and CLIMEX approach to model the potential distribution of PWD under various climate‐change scenarios. Our results indicate that rising temperatures and lower humidity under climate change will render some of the northern regions of China more suitable for the nematode and these beetles, causing the gradual northward movement of PWD. Furthermore, suitable habitats for three pine species, Pinus massoniana, P. taiwanensis and P. shurbergia, overlap with PWN and Monochamus, suggesting that these three species are potentially at high risk of PWD. Thus, PWD management should target the northern regions of China and the three pine species that are most susceptible to PWD. [ABSTRACT FROM AUTHOR]

Marine protected areas (MPAs) make an essential contribution to the spatial management of critical areas, the conservation of coastal species exploited by human activities, and the sustainable use of marine resources. Within MPAs, fishing closure areas are among the most used small‐scale fishery management tools, even though their effectiveness largely remains untested or controversial. To reduce the impact of small‐scale fisheries on marine resources, a seasonal fishing closure area (SFCA) was established beginning in 2022 in autumn–winter season inside the Capo Caccia–Isola Piana MPA (Sardinia, northwestern Mediterranean Sea). Here, we assessed a posteriori whether the areas of higher habitat suitability for eight species/taxa of relevant ecological value and economic interest to small‐scale fisheries were included in the established SFCA, adequately meeting the ecological objectives of the MPA. Thus, landing data (from 2019 to 2023) were used as occurrence records to develop MaxEnt distribution models for the eight target species/taxa. The model outputs allow us to draw important insights about the spatial adequacy of the SFCA established within the MPA aimed to protect the most exploited marine resources. Furthermore, the modeling exercises were useful for understanding the local processes influencing species' habitat selection and to identify essential areas for the target species that could remain unrevealed in larger‐scale investigations. [ABSTRACT FROM AUTHOR]

Hucks, K.D. and Leberg, P.L., 2024. Evaluation of maximum entropy models for assessing coastal bird distributions under restoration scenarios. Journal of Coastal Research, 40(5), 901–918. Charlotte (North Carolina), ISSN 0749-0208. Coastal systems are facing many challenges, including climate change, sea-level rise, storm surge, and erosion, all of which contribute to land loss. In Louisiana, this has led to the development of a coastal master plan supported by habitat suitability index (HSI) models to predict wildlife responses under various management scenarios. However, HSI models were not originally intended for this purpose, and their functionality at large spatial scales is unclear. The goal was to use maximum entropy modeling to predict how various bird distributions might change with coastal restoration and management and to compare those results to HSI model predictions. Using field surveys and sources of bird locations, as well as environmental projections from the Comprehensive Master Plan habitat and hydrology models, the authors predicted the probability of occurrence for each target species for current conditions and projected the distributions into the future at 25 and 50 years using sea-level rise and coastal change scenarios. Predictive models for each species under current conditions show good agreement with field observations. Future models generally show reductions in areas of potentially high habitat use, with a few notable exceptions in the Brown Pelican habitat. Both MaxEnt and HSI modeling approaches had advantages and disadvantages; neither was clearly superior for predicting wildlife habitat. Increasing the resolution and quality of environmental data used in coastal monitoring efforts, as well as additional field validation of model predictions, will improve estimates of suitable habitat, habitat use, and restoration outcomes for wildlife. [ABSTRACT FROM AUTHOR]

Aim: The continuous development of statistical tools applied to ecology has contributed to great advances for modelling species' niches and distributions from opportunistic observations. However, as these observations are subject to biases caused by spatial variation in sampling effort, ecological niche models (ENMs) are also frequently biased. Among several bias correction methods that have been proposed, spatial filtering—imposing a minimum distance between occurrences—is widely used, yet lacks clear guidelines for choosing the filtering distance. Here, we aimed to explore the impact of spatial filtering distances on the performance of ENMs. Location: Europe. Taxon: Virtual species. Methods: We applied ENMs to two virtual species with contrasting levels of specialisation, across a spectrum of modelling conditions, bias types and sample sizes. Results: Models applied to the specialist species had on average a lower performance than those applied to the generalist species. Using a biased sample reduced model performance, especially when the bias was strong, and when the sample size was large. In many cases, spatial filtering failed to improve model performance or even reduced it. We did find an improvement for the generalist species modelled with large and strongly biased datasets. However, there was no optimal filtering distance, as this improvement was linearly and positively associated with filtering distance. Moreover, because the initial bias was strong and the filtered dataset became very small, the resulting models had only very low accuracy. Main Conclusions: Our results suggest that there is no optimal filtering distance for dealing with sampling bias in ENMs, and that spatial filtering never improves model performance enough to draw accurate predictions. We therefore recommend spatial filtering to be employed cautiously, only when enough data are available, and bearing in mind that its effectiveness remains highly uncertain. [ABSTRACT FROM AUTHOR]

The Kunming–Montreal Global Biodiversity Framework (GBF) is a recently signed protocol by the conference of the parties (COP 15) with an aim to protect biodiversity from risks imposed by biological threats such as invasive alien species (IAS). The present work is an effort to meet target 6 of GBF which directly deals with IAS by assessing the current and future distribution of Ageratum species in regions of the Eastern Ghats of India. Prediction of Ageratum distribution was done based on greenhouse gas emission levels, namely RCP 4.5, 6.0 and 8.5 for the climatic years 2030, 2050 and 2080. Of a total of 23 environmental parameters (19 bioclimatic, 1 land use land cover (LULC) and 3 topographic) seven were selected for species distribution modeling (SDM) considering value inflation factor (VIF) scores <3 by using maximum entropy. In the current climatic scenario, 40.09% of the geographical area (TGA) is covered by Ageratum species which will reach 76.51%, 77.44%, 82.58% for RCP 4.5, 6.0 and 8.5 respectively by the end of 2100. Both the AUC value (0.884) and Jackknife test have shown a good model performance. The Eastern Ghats, being a biodiversity-rich zone, needs efficient conservation and management strategies to decrease the extent of invaded areas to maximize biodiversity returns. [ABSTRACT FROM AUTHOR]

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Context: Large carnivores have faced severe extinction pressures throughout Europe during the last centuries, where human-induced disturbances reached unprecedented levels. In the late twentieth century, the Cantabrian brown bear population was on the verge of extinction, due to poaching. Yet, the end of the last century was a turning point for this population. Presence data on the western Cantabrian subpopulation was collected since the beginning of the century and insights provided by this long-term monitoring may be useful for brown bear conservation. Objectives: Here, we aim to: (i) identify the landscape features relevant to bears’ recovery; and (ii) understand if and how the landscape use patterns by bears changed over time. Methods: We tested the influence of landscape structure (i.e., composition and configuration) on bear occurrence patterns using MAXENT in three periods representative of land cover change. Results: Despite variation across the 19-year monitoring period, brown bears were more often detected near broad-leaf forests and bare rock areas and at lower to intermediate altitudes, but avoided arable lands, permanent crops, and burnt areas. Human population density or distance to roads—often used for modelling habitat suitability for Cantabrian brown bears—were not identified as relevant variables for this brown bear subpopulation. Artificial areas were identified as relevant landscape features, but not as disturbance. Conclusions: These findings reinforce the importance of preserving bears’ native habitats and provide new insights, namely on the use of humanized landscapes. [ABSTRACT FROM AUTHOR]

Species distribution modelling is a technique used in ecology and conservation biology to predict the potential distribution of a species based on environmental variables. It involves analysing the relationship between known occurrences of a species and environmental factors to create a model that can then predict where the species might be found. Amblypodia anita is a species of butterfly belonging to the family Lycaenidae, found primarily in Southeast Asia. Information about the specific conservation status of Amblypodia anita varies based on regional assessments. However, like many butterfly species, threats such as habitat destruction, climate change, and habitat fragmentation pose risks to its populations. The study trained a model on the current distribution of Amblypodia anita in West Bengal, India, using MaxEnt modelling. Fourteen environmental variables were selected to build the model. Results suggest that cultivated and managed vegetation (36.5%) serves as the most important variable. Running the developed model, the team was then able to predict that 6619 km2 of suitable habitat for Amblypodia anita butterflies exists in West Bengal, India. This analytical approach to area-based conservation may be used in conservation management and focuses on protecting specific geographical areas to preserve biodiversity, ecosystems, and natural resources. [ABSTRACT FROM AUTHOR]

Climate change has significantly altered in the distribution of plant and animal species, potentially resulting in either species expansion or extinction. The genus Chimonanthus, an economically significant and endemic group in China, holds substantial medicinal and ornamental value; however, its wild resources are limited. There is a paucity of knowledge regarding the distribution characteristics of the genus Chimonanthus species and the critical ecological factors influencing habitat suitability. Utilizing species distribution data and environmental variables, we performed simulations and analyses to identify suitable habitats, evaluate the primary environmental factors influencing distribution, determine potential distribution areas and centroids, and predict changes in suitable areas under three future climate scenarios (SSP-126, SSP-245, SSP-585) employing MaxEnt and ArcGIS. These findings indicated that the Area Under Curve (AUC) values exceeded 0.97 for all five Chimonanthus species, suggesting that the model predictions are highly accurate. The primary environmental variables influencing the distribution of C. grammatus are temperature, particularly isothermality (BIO3), and the mean temperature of warmest quarter (BIO10). However, precipitation of warmest quarter (BIO18) was an important environmental factor limiting the distributions of C. praecox, C. nitens, C. salicifolius and C. zhejiangensis. In the current period, the area of habitat suitability for C. praecox is the largest, at 2,498,600 km2, while that for C. zhejiangensis is the smallest, at 700,400 km2. The five Chimonanthus species are distributed mainly in southern China under the current climate scenario and will migrate to higher latitudes under future climate scenarios. C. nitens had high niche overlap and range overlap with C. zhejiangensis and C. salicifolius, respectively. A similar situation occurs between C. zhejiangensis and C. salicifolius. These findings suggest that there may be strong interspecific competition among adjacent species. Our results indicate that the establishment of nature reserves at current distribution sites within optimal areas is crucial for the conservation of germplasm resources, particularly for C. grammatus and C. salicifolius. The data generated from this research can serve as a valuable reference for the selection of in situ conservation sites, the determination of appropriate planting locations, the scientific introduction of species, and the development of long-term conservation and management strategies for Chimonanthus. [ABSTRACT FROM AUTHOR]

In recent years, the problem of ecosystem degradation caused by human activities has become increasingly serious. Vegetation restoration is a key means to solve this problem, which has increased. To address the suitability and structural optimization of vegetation restoration in the Loess Plateau (China), the MaxEnt model was used to quantify the impacts of environmental and human activities on the planting suitability of vegetation restoration species at the raster scale. Three layers of trees, shrubs, and herbs with 12 common vegetation restoration species were selected. The factor index system was constructed by combining climatic, ecological, and socio-economic data, and the MaxEnt model predicted land suitability. It was found that human activities significantly increased the unsuitable planting area. This especially affected Robinia pseudoacacia in the tree layer and Amorpha fruticosa in the shrub layer. High and medium suitable areas were mainly sparsely populated areas with close water sources. Through maximum suitability optimization, it was identified that the overall spatial distribution of the three layers in the study area was relatively consistent, and the structural dominance of trees + shrubs + herbs and single herbs in the vertical structure was obvious; these were concentrated in the southwestern and northeastern parts of the study area, respectively. In addition, organic content (OC) and distance from the road to woodland (RW) were the dominant factors affecting land suitability, with a contribution rate of more than 50% and up to 80%. These results provide a scientific basis for optimizing planting structures. They are of significant theoretical and practical significance in guiding vegetation restoration work. [ABSTRACT FROM AUTHOR]

Background: Situational awareness is an essential component of wildland firefighter safety. In the US, crew lookouts provide situational awareness by proxy from ground-level locations with visibility of both fire and crew members. Aims: To use machine learning to predict potential lookout locations based on incident data, mapped visibility, topography, vegetation, and roads. Methods: Lidar-derived topographic and fuel structural variables were used to generate maps of visibility across 30 study areas that possessed lookout location data. Visibility at multiple viewing distances, distance to roads, topographic position index, canopy height, and canopy cover served as predictors in presence-only maximum entropy modelling to predict lookout suitability based on 66 known lookout locations from recent fires. Key results and conclusions: The model yielded a receiver-operating characteristic area under the curve of 0.929 with 67% of lookouts correctly identified by the model using a 0.5 probability threshold. Spatially explicit model prediction resulted in a map of the probability a location would be suitable for a lookout; when combined with a map of dominant view direction these tools could provide meaningful support to fire crews. Implications: This approach could be applied to produce maps summarising potential lookout suitability and dominant view direction across wildland environments for use in pre-fire planning. We use machine learning to predict the probability an area is suitable for a wildland firefighter lookout based on incident data, roads, and lidar-derived visibility, terrain, and vegetation information. This approach may aid pre-fire planning and enhance situational awareness by providing maps of potential lookout locations. [ABSTRACT FROM AUTHOR]

The Sparreboom's Crocodile Newt (Tylototriton sparreboomi) is a recently discovered species of crocodile newts from Vietnam and it is currently known only from Sin Ho District in Lai Chau Province. Due to the limited information available on its population status and distribution, the species has been classified as Data Deficient in the IUCN Red List. As a result of our field surveys in 2021 and 2022 in north-western Vietnam, novel data on distribution and population status of and threats to this poorly-known species were collected. We combined the newly-discovered locations with previous occurrence records and used the data as input for modelling the potential distribution of the Sparreboom's Crocodile Newt. The results showed that the Sparreboom's Crocodile Newt's potential distribution encompasses areas in Lai Chau, Dien Bien and Son La Provinces, Vietnam, as well as a section in Jinping County, Yunnan Province, China. Based on the findings, we suggest that protected areas in the eastern side of Hoang Lien Mountain Range, such as Che Tao, Muong La, Hoang Lien – Van Ban and Bat Xat Nature Reserves and Hoang Lien National Park in Vietnam and Jinping Feishuling Nature Reserve in China be priority sites for the species conservation. Future research and conservation initiatives should prioritise efforts in such areas in an effort to find and protect new populations of the newt. [ABSTRACT FROM AUTHOR]

Across Africa, space for conservation is sometimes limited to formally protected areas that have become progressively more isolated. There is a need for targeted conservation initiatives such as the demarcation of landscape connections, defined as areas that encompass environmental variables that promote the natural movement of individuals between populations, which can facilitate gene flow. Landscape connections can mitigate genetic isolation, genetic drift, and inbreeding, which can occur in isolated populations in protected areas. Promoting gene flow can reduce the risk of extirpation often associated with isolated populations. Here we develop and test models for identifying landscape connections among African savannah elephant (Loxodonta africana) populations by combining habitat suitability modeling with gene flow estimates across a large region including seven countries. We find a pronounced non-linear response to unsuitable habitat, consistent with previous studies showing that non-transformed habitat models are poor predictors of gene flow. We generated a landscape connections map that considers both suitable habitats based on telemetry occurrence data and gene flow estimated as the inverse of individual genetic distance, delineating areas that are important for maintaining elephant population connectivity. Our approach represents a novel framework for developing spatially and genetically informed conservation strategies for elephants and many other taxa distributed across heterogeneous and fragmented landscapes. [ABSTRACT FROM AUTHOR]

Türkiye is one of the first regions where olives were domesticated, and olives reflect the country's millennia-old agricultural and cultural heritage. Moreover, Türkiye is one of the leading nations in olive and olive oil production in terms of quality and diversity. This study aims to determine the current and future distribution areas of olives, which is important for Türkiye's socio-economic structure. For this purpose, 19 different bioclimatic variables, such as annual mean temperature (Bio1), temperature seasonality (Bio4), and annual precipitation (Bio12), have been used. The RCP4.5 and RCP8.5 emission scenarios of the CCSM4 model were used for future projections (2050 and 2070). MaxEnt software, which uses the principle of maximum entropy, was employed to determine the current and future habitat areas of the olives. Currently and in the future, it is understood that the Mediterranean, Aegean, Marmara, and Black Sea coastlines have areas with potential suitability for olives. However, the model projections indicate that the species may shift from south to north and to higher elevations in the future. Analyses indicate that the Aegean Region is the most sensitive area and that a significant portion of habitats in the Marmara Region will remain unaffected by climate change. [ABSTRACT FROM AUTHOR]

Abstract Cinnamomum cassia Presl. is a subtropical plant that is used for food and medicine. Climate change has changed the suitable habitats of medicinal plants, which might have repercussions for the efficacy of herbal remedies. In this study, the potential distribution in each period of Cinnamomum cassia was predicted and the quality in different suitable habitats was evaluated. According to the results, (1) precipitation, temperature, and soil are the primary environmental variables influencing C. cassia distribution. (2) The high-suitable habitats of current climate scenarios were predominantly located in the southern regions (Guangdong and Guangxi etc.) of China, with an area of 706,129.08 km2. Under future climate scenarios, suitable habitats will increasingly move northward, with a greater concentration south of the Yangtze River, particularly in the 2090s SSP585 scenario, the total area of newly extended suitable habitat reaches 312,963.53 km2. (3) HPLC and FTIR, combined with chemometrics, can be effective methods for identifying different suitable habitats of C. cassia. The content of trans-cinnamaldehyde (0.85%) is significantly higher in the high suitability habitat compared to the medium-low suitability habitat (0.30%). Our findings can offer valuable guidance for the identification of suitable C. cassia cultivation areas in China, as well as for the evaluation of C. cassia resource quality and the rational use of resources in different suitable habitats.

Abstract Rubus idaeus is a pivotal cultivated species of raspberry known for its attractive color, distinct flavor, and numerous health benefits. It can be used in pharmaceutical, cosmetics, agriculture and food industries not only as fresh but also as a processed product. Nowadays due to climatic changes, genetic diversity of cultivars has decreased dramatically. However, until now, the status of wild R. idaeus resources in China have not been exploited. In this study, we investigated the resources of wild R. idaeus in China to secure its future potential and sustainability. The MaxEnt model was used to predict R. idaeus suitable habitats and spatial distribution patterns for current and future climate scenarios, based on wild domestic geographic distribution data, current and future climate variables, and topographic variables. The results showed that, mean temperature of the coldest quarter (bio11), precipitation of the coldest quarter (bio19), precipitation of the warmest quarter (bio18), and temperature seasonality (bio4) were crucial factors affecting the distribution of R. idaeus. Presently, the suitable habitats were mainly distributed in the north of China including Xinjiang, Inner Mongolia, Gansu, Ningxia, Shaanxi, Shanxi, Hebei, Beijing, Liaoning, Jilin, Heilongjiang. According to our results, in 2050s, the total suitable habitat area of R. idaeus will increase under SSP1-2.6 and then will be decreased with climate change, while in the 2090s, the total suitable habitat area will continue to decrease. From the present to the 2090s, the centroid distribution of R. idaeus in China will shift towards the east and the species will always be present in Inner Mongolia. Our results provide wild resource information and theoretical reference for the protection and rational utilization of R. idaeus.

Over the last decade, access to global data has become increasingly critical for research, allowing insights into diverse biological, environmental and societal questions at a macro scale. Digitisation has greatly enhanced the use of herbarium data in the analysis of species distributions and ecological niche modelling. Yet, sources on modelling and mapping methodology using open-source software is greatly lacking for beginners. We have created a replicable and thorough tutorial to visualise species occurrence data and exploratory analysis that was developed by undergraduates with broad backgrounds and levels of experience. This tutorial integrates the open-source programmes QGIS, MaxEnt and R to develop distribution maps, using bryophytes as a case study, to promote the accessibility of open-source software and remote access learning. This tutorial has already set the foundation for further research into distribution modelling of rare Illinois bryophytes to better understand the potential impact of climate change.

The Sparreboom's Crocodile Newt (Tylototriton sparreboomi) is a recently discovered species of crocodile newts from Vietnam and it is currently known only from Sin Ho District in Lai Chau Province. Due to the limited information available on its population status and distribution, the species has been classified as Data Deficient in the IUCN Red List. As a result of our field surveys in 2021 and 2022 in north-western Vietnam, novel data on distribution and population status of and threats to this poorly-known species were collected. We combined the newly-discovered locations with previous occurrence records and used the data as input for modelling the potential distribution of the Sparreboom's Crocodile Newt. The results showed that the Sparreboom's Crocodile Newt’s potential distribution encompasses areas in Lai Chau, Dien Bien and Son La Provinces, Vietnam, as well as a section in Jinping County, Yunnan Province, China. Based on the findings, we suggest that protected areas in the eastern side of Hoang Lien Mountain Range, such as Che Tao, Muong La, Hoang Lien – Van Ban and Bat Xat Nature Reserves and Hoang Lien National Park in Vietnam and Jinping Feishuling Nature Reserve in China be priority sites for the species conservation. Future research and conservation initiatives should prioritise efforts in such areas in an effort to find and protect new populations of the newt.

Abstract Zingiber striolatum Diels is a unique medicine food homology plant native to China. In recent years, due to severe habitat destruction, studying the impact of climate change on the distribution of wild resources is of great significance for the ecological conservation and artificial cultivation of Z. striolatum. This study collected 141 valid species distribution records, and 37 environmental variables, and projected two future climate scenarios (SSP126 and SSP585) for two periods (2050s and 2090s). By employing Pearson analysis, Maximum Entropy Model (MaxEnt), and Geographic Information System (ArcGIS), we predicted the potential suitable habitats for Z. striolatum under present and future climates, as well as identified the dominant environmental variables influencing its distribution. The results indicated that the MaxEnt model performed well (AUC > 0.9) with high accuracy and reliability. The dominant environmental factors included Precipitation of driest quarter (39.0 ~ 473.8 mm), Precipitation of wettest quarter (593.2 ~ 1269.4 mm), Temperature annual range (9.8 ~ 28.6℃), and Mean diurnal range (6.5 ~ 9.6℃). The highly suitable areas for Z. striolatum were mainly distributed in western and southern Yunnan, northern and western Guangxi, Guangdong, Fujian, and central Hainan. Under future climate change, the centroid of the total suitable area for Z. striolatum is projected to shift towards the southwest (Yungui Plateau) at higher elevations.