Novel methods to select environmental variables in MaxEnt: A case study using invasive crayfish

Mapping habitat suitability of invasive crayfish in aridland riverscapes: Virile crayfish (Faxonius virilis) in the Lower Colorado River Basin, USA

Correlative species distribution modeling (SDM) is an important tool to predict distributions of invasive species. A unique challenge of implementing SDMs in aridland stream networks is identifying which streams are perennial and which of those offer suitable habitat for obligate aquatic species. Here, we map perennial streams and habitat suitability of invasive virile crayfish (Faxonius virilis) in the Lower Colorado River Basin (LCRB) in the southwestern USA, and quantify drivers of uncertainty in these projections. First, we surveyed F. virilis at 122 stream sites in May-July of 2021, 2022, and 2023. We then implemented an ensemble of SDMs fit using combinations of randomly drawn sites, categories of environmental covariates measured at different spatial scales, survey years, and statistical algorithms. Next, we used open-source street view images from May-July of 2022 and 2023 to assess dry-wet status at 326 road-stream intersections and the same ensemble framework to map perennial stream reaches. Lastly, we quantified drivers of variation in predictive accuracy and mapped habitat suitability across replicates. Median true skill statistic (TSS) across F. virilis replicates was 0.613 and habitat suitability was highest in mountain ecoregions and lowest in desert ecoregions. Of the 130,847 stream km in the LCRB, we estimate 29,078 km (22.2 %) have wetted channels during the May-June dry season and median 50.3 % of these perennial streams provide suitable habitat for F. virilis. The statistical algorithm was the strongest driver of TSS variation across replicates, whereas the spatial scale at which covariates were measured was the strongest driver of variation in mapped habitat suitability across replicates. We confirm the widespread invasion of F. virilis throughout the LCRB, particularly in perennial mountain streams. The modest predictive accuracy highlights the generalistic niche of F. virilis. Overall, we demonstrate that spatiotemporally comprehensive datasets combined with ensemble modeling can guide management at regional extents.

Habitat suitability and distribution patterns of Rouget's rail (Rougetius rougetii Guérin-méneville, 1843) in Ethiopia

Geographical distribution and diversity patterns of bird species are influenced by climate change. The Rouget's rail (Rougetius rougetii) is a ground-dwelling endemic bird species distributed in Ethiopia and Eritrea. It is a near-threatened species menaced by habitat loss, one of the main causes of population declines for bird species. The increasing effects of climate change may further threaten the species' survival. So far, the spatial distribution of this species is not fully documented. With this study, we develop current potential suitable habitat and predict the future habitat shift of R. rougetii based on environmental data such as bioclimatic variables, population density, vegetation cover, and elevation using 10 algorithms. We evaluated the importance of environmental factors in shaping the bird's distribution and how it shifts under climate change scenarios. We used 182 records of R. rougetii from Ethiopia and nine bioclimatic, population density, vegetation cover, and elevation variables to run the 10 model algorithms. Among 10 algorithms, eight were selected for ensembling models according to their predictive abilities. The current suitable habitats for R. rougetii were predicted to cover an area of about 82,000 km2 despite being highly fragmented. The model suggested that temperature seasonality (bio4), elevation, and mean daily air temperatures of the driest quarter (bio9) contributed the most to delimiting suitable areas for this species. R. rougetii is sensitive to climate change associated with elevation, which leads shrinking distribution of suitable areas. The projected spatial and temporal pattern of habitat loss of R. rougetii suggests the importance of climate change mitigation and implementing long-term conservation and management strategies for this threatened endemic bird species.

Local environmental factors drive distributions of ecologically-contrasting mosquito species (Diptera: Culicidae)

Mosquitoes are important vectors of disease pathogens and multiple species are undergoing geographical shifts due to global changes. As such, there is a growing need for accurate distribution predictions. Ecological niche modelling (ENM) is an effective tool to assess mosquito distribution patterns and link these to underlying environmental preferences. Typically, macroclimatic variables are used as primary predictors of mosquito distributions. However, they likely undervalue local conditions and intraspecific variation in environmental preferences. This is problematic, as mosquito control takes place at the local scale. Utilising high-resolution (10 × 10 m) Maxent ENMs on the island of Bonaire as model system, we explore the influence of local environmental variables on mosquito distributions. Our results show a distinct set of environmental variables shape distribution patterns across ecologically-distinct species, with urban variables strongly associated with introduced species like Aedes aegypti and Culex quinquefasciatus, while native species show habitat preferences for either mangroves, forests, or ephemeral water habitats. These findings underscore the importance of distinct local environmental factors in shaping distributions of different mosquitoes, even on a small island. As such, these findings warrant further studies aimed at predicting high-resolution mosquito distributions, opening avenues for preventative management of vector-borne disease risks amidst ongoing global change and ecosystem degradation.

Utilizing digitized occurrence records of Midwestern feral Cannabis sativa to develop ecological niche models

Hemp (Cannabis sativa L.) has historically played a vital role in agriculture across the globe. Feral and wild populations have served as genetic resources for breeding, conservation, and adaptation to changing environmental conditions. However, feral populations of Cannabis, specifically in the Midwestern United States, remain poorly understood. This study aims to characterize the abiotic tolerances of these populations, estimate suitable areas, identify regions at risk of abiotic suitability change, and highlight the utility of ecological niche models (ENMs) in germplasm conservation. The Maxent algorithm was used to construct a series of ENMs. Validation metrics and MOP (Mobility-oriented Parity) analysis were used to assess extrapolation risk and model performance. We also projected the final projected under current and future climate scenarios (2021-2040 and 2061-2080) to assess how abiotic suitability changes with time. Climate change scenarios indicated an expansion of suitable habitat, with priority areas for germplasm collection in Indiana, Illinois, Kansas, Missouri, and Nebraska. This study demonstrates the application of ENMs for characterizing feral Cannabis populations and highlights their value in germplasm conservation and breeding efforts. Populations of feral C. sativa in the Midwest are of high interest, and future research should focus on utilizing tools to aid the collection of materials for the characterization of genetic diversity and adaptation to a changing climate.

Poleward migration of tropical corals inhibited by future trends of seawater temperature and calcium carbonate (CaCO3) saturation

Poleward range expansion of marine organisms is commonly attributed to anthropogenic ocean warming. However, the extent to which a single species can migrate poleward remains unclear. In this study, we used molecular data to examine the current distribution of the Pocillopora damicornis species complex in Taiwan waters and applied niche modeling to predict its potential range through the end of the 21st Century. The P. damicornis species complex is widespread across shallow, tropical and subtropical waters of the Indo-Pacific regions. Our results revealed that populations from subtropical nonreefal coral communities are P. damicornis, whose native geographical ranges are approximately between 23°N and 35°N. In contrast, those from tropical reefs are P. acuta. Our analysis of 50 environmental data layers demonstrated that the concentrations of CaCO3 polymorphs had the greatest contributions to the distributions of the two species. Future projections under intermediate shared socioeconomic pathways (SSP) 2-4.5 and very high (SSP5-8.5) scenarios of greenhouse gas emissions showed that while sea surface temperature (SST) isotherms would shift northwards, saturation isolines of two CaCO3 polymorphs, calcite (Ωcal) and aragonite (Ωarag), would shift southwards by 2100. Subsequent predictions of future suitable habitats under those conditions indicated that distinct delimitation of geographical ranges for the two species would persist, and neither would extend beyond its native geographical zones, indicating that tropical Taiwan waters are the northern limit for P. acuta. In contrast, subtropical waters are the southern limit for P. damicornis. We concluded that the decline in CaCO3 saturation would make high latitudes less inhabitable, which could be one of the boundary elements that limit poleward range expansion driven by rising SSTs and preserve the latitudinal diversity gradient (LDG) on Earth. Consequently, poleward migration of tropical reef corals to cope with warming oceans should be reevaluated.

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.

Modeling the Potential Distribution Patterns of the Invasive Plant Species Phytolacca americana in China in Response to Climate Change

Phytolacca americana, introduced to China in the 20th century for its medicinal properties, has posed a significant ecological and agricultural challenge. Its prolific fruit production, high reproductive coefficient, adaptability, and toxic roots and fruits have led to the formation of monoculture communities, reducing native species diversity and posing threats to agriculture, human and animal health, and local ecosystems. Understanding its potential distribution patterns at a regional scale and its response to climate change is essential for effective monitoring, management, and control. In this study, we utilized the Maxent model to simulate potential habitat areas of P. americana across three timeframes (current, 2050s, and 2070s) under three climate change scenarios (SSP126, SSP245, and SSP585). Leveraging data from 556 P. americana sites across China, we employed ROC curves to assess the prediction accuracy. Our findings highlight key environmental factors influencing P. americana's geographical distribution, including the driest month's precipitation, the coldest month's minimum temperature, the wettest month's precipitation, isothermality, and temperature annual range. Under current climate conditions, P. americana potentially inhabits 280.26 × 104 km2 in China, with a concentration in 27 provinces and cities within the Yangtze River basin and its southern regions. While future climate change scenarios do not drastically alter the total suitable area, the proportions of high and low-suitability areas decrease over time, shifting towards moderate suitability. Specifically, in the SSP126 scenario, the centroid of the predicted suitable area shifts northeastward and then southwestward. In contrast, in the SSP245 and SSP585 scenarios, the centroid shifts northward.

Unravelling the impact of climate change on honey bees: An ensemble modelling approach to predict shifts in habitat suitability in Queensland, Australia

Honey bees play a vital role in providing essential ecosystem services and contributing to global agriculture. However, the potential effect of climate change on honey bee distribution is still not well understood. This study aims to identify the most influential bioclimatic and environmental variables, assess their impact on honey bee distribution, and predict future distribution. An ensemble modelling approach using the biomod2 package in R was employed to develop three models: a climate-only model, an environment-only model, and a combined climate and environment model. By utilising bioclimatic data (radiation of the wettest and driest quarters and temperature seasonality) from 1990 to 2009, combined with observed honey bee presence and pseudo absence data, this model predicted suitable locations for honey bee apiaries for two future time spans: 2020-2039 and 2060-2079. The climate-only model exhibited a true skill statistic (TSS) value of 0.85, underscoring the pivotal role of radiation and temperature seasonality in shaping honey bee distribution. The environment-only model, incorporating proximity to floral resources, foliage projective cover, and elevation, demonstrated strong predictive performance, with a TSS of 0.88, emphasising the significance of environmental variables in determining habitat suitability for honey bees. The combined model had a higher TSS of 0.96, indicating that the combination of climate and environmental variables enhances the model's performance. By the 2020-2039 period, approximately 88% of highly suitable habitats for honey bees are projected to transition from their current state to become moderate (14.84%) to marginally suitable (13.46%) areas. Predictions for the 2060-2079 period reveal a concerning trend: 100% of highly suitable land transitions into moderately (0.54%), marginally (17.56%), or not suitable areas (81.9%) for honey bees. These results emphasise the critical need for targeted conservation efforts and the implementation of policies aimed at safeguarding honey bees and the vital apiary industry.

Impact of Climate Change on the Distribution of Three Rare Salamanders (Liua shihi, Pseudohynobius jinfo, and Tylototriton wenxianensis) in Chongqing, China, and Their Conservation Implications

The Wushan Salamander (Liua shihi), Jinfo Salamander (Pseudohynobius jinfo), and Wenxian Knobby Salamander (Tylototriton wenxianensis) are rare national Class II protected wild animals in China. We performed MaxEnt modeling to predict and analyze the potential distribution and trends of these species in Chongqing under current and future climate conditions. Species distribution data were primarily obtained from field surveys, supplemented by museum collections and the existing literature. These efforts yielded 636 records, including 43 for P. jinfo, 23 for T. wenxianensis, and 570 for L. shihi. Duplicate records within the same 100 m × 100 m grid cell were removed using ENMTools, resulting in 10, 12, and 58 valid distribution points for P. jinfo, T. wenxianensis, and L. shihi, respectively. The optimization of feature class parameters (FC) and the regularization multiplier (RM) were applied using R package "ENMeval 2.0" to establish the optimal model with MaxEnt. The refined models were applied to simulate the suitable distribution areas for the three species. The results indicate that the current suitable habitat area for L. shihi accounted for 9.72% of the whole region of the Chongqing municipality. It is projected that, by 2050, the proportion of suitable habitat will increase to 12.54% but will decrease to 11.98% by 2070 and further decline to 8.80% by 2090. The current suitable habitat area for P. jinfo accounted for 1.08% of the whole region of the Chongqing municipality, which is expected to decrease to 0.31%% by 2050, 0.20% by 2070, and 0.07% by 2090. The current suitable habitat area for T. wenxianensis accounted for 0.81% of the whole region of the Chongqing municipality, which is anticipated to decrease to 0.37% by 2050, 0.21% by 2070, and 0.06% by 2090. Human disturbance, climate variables, and habitat characteristics are the primary factors influencing the distribution of three salamander species in Chongqing. The proximity to roads significantly impacts L. shihi, while climate conditions mainly affect P. jinfo, and the distance to water sources is crucial for T. wenxianensis. The following suggestions were made based on key variables identified for each species: (1) For L. shihi, it is imperative to minimize human disturbances and preserve areas without roads and the existing vegetation within nature reserves to ensure their continued existence. (2) For P. jinfo, the conservation of high-altitude habitats is of utmost importance, along with the reduction in disturbances caused by roads to maintain the species' ecological niche. (3) For T. wenxianensis, the protection of aquatic habitats is crucial. Additionally, efforts to mitigate the impacts of road construction and enhance public awareness are essential for the preservation of this species and the connectivity of its habitats.

Predicting the current habitat refugia of Himalayan Musk deer (Moschus chrysogaster) across Nepal

Himalayan Musk deer, Moschus chrysogaster is widely distributed but one of the least studied species in Nepal. In this study, we compiled a total of 429 current presence points of direct observation of the species, pellets droppings, and hoofmarks based on field-based surveys during 2018-2021 and periodic data held by the Department of National Park and Wildlife Conservation. We developed the species distribution model using an ensemble modeling approach. We used a combination of bioclimatic, anthropogenic, topographic, and vegetation-related variables to predict the current suitable habitat for Himalayan Musk deer in Nepal. A total of 16 predictor variables were used for habitat suitability modeling after the multicollinearity test. The study shows that the 6973.76 km2 (5%) area of Nepal is highly suitable and 8387.11 km2 (6%) is moderately suitable for HMD. The distribution of HMD shows mainly by precipitation seasonality, precipitation of the warmest quarter, temperature ranges, distance to water bodies, anthropogenic variables, and land use and land cover change (LULC). The probability of occurrence is less in habitats with low forest cover. The response curves indicate that the probability of occurrence of HMD decreases with an increase in precipitation seasonality and remains constant with an increase in precipitation of the warmest quarter. Thus, the fortune of the species distribution will be limited by anthropogenic factors like poaching, hunting, habitat fragmentation and habitat degradation, and long-term forces of climate change.

Potential impact of climatic factors on the distribution of Graphium sarpedon in China

Graphium sarpedon is a significant foliar pest of Laurel plants in China. In this study, the MaxEnt model was used to investigate the distribution of G. sarpedon and predict its potential distribution areas in China in the future (2050s and 2090s) based on three Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5, and SSP5-8.5), and key environmental variables affecting its distribution were identified. The results showed that under the current climatic conditions, the suitable distribution areas of G. sarpedon were 92.17°-134.96° E and 18.04°-33.61° N, including Yangtze Plain (Middle and Lower), Pearl River Delta, Yangtze River Delta, and Lingnan areas. Under the future climate conditions, the total suitable distribution area of G. sarpedon decreased, but the area of medium suitable area increased. The study identified 11 key environmental variables affecting the distribution of G. sarpedon, the most critical of which was Precipitation of Warmest Quarter (bio18) and precipitation in April, May, June, and September (prec4, prec5, prec6, and prec9). This study is beneficial for monitoring and preventing the possible changes of G. sarpedon and provides theoretical references for its prevention and control.

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.

Towards effective management of the marine-origin Prymnesium parvum (Haptophyta): A growing concern in freshwater reservoirs?

Freshwater ecosystems are highly susceptible to harmful algal blooms (HABs), which are often caused by monospecific dense blooms. Effective preventive management strategies are urgently needed to avoid wide-ranging and severe impacts often resulting in costly damage to resources and unsustainable management options. In this study, we utilized SDM techniques focused on Prymnesium parvum, one of the most notorious HABs species worldwide. We first compare the climatic space occupied by P. parvum in North America, Europe and Australia. Additionally, we use MaxEnt algorithm to infer, for the first time, the potentially suitable freshwater environments in the aforementioned ranges. We also discuss the risks of invasion in reservoirs - prone habitats to persistent blooms of pests and invasive phytoplanktonic species. Our results show populations with distinctive niches suggesting ecophysiological tolerances, perhaps reflecting different strains. Our model projections revealed that the potential extent for P. parvum invasions is much broader than its current geographic distribution. The spatial configuration of reservoirs, if not sustaining dense blooms due to non-optimal conditions, favors colonization of multiple basins and ecoregions not yet occupied by P. parvum. Our models can provide valuable insights to decision-makers and monitoring programs while reducing the resources required to control the spread of P. parvum in disturbed habitats. Lastly, as impact magnitude is influenced by toxicity which in turn varies between different strains, we suggest future studies to incorporate intraspecific genetic information and fine-scale environmental variables to estimate potential distribution of P. parvum.

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 neglected role of abandoned cropland in supporting both food security and climate change mitigation

Despite the looming land scarcity for agriculture, cropland abandonment is widespread globally. Abandoned cropland can be reused to support food security and climate change mitigation. Here, we investigate the potentials and trade-offs of using global abandoned cropland for recultivation and restoring forests by natural regrowth, with spatially-explicit modelling and scenario analysis. We identify 101 Mha of abandoned cropland between 1992 and 2020, with a capability of concurrently delivering 29 to 363 Peta-calories yr-1 of food production potential and 290 to 1,066 MtCO2 yr-1 of net climate change mitigation potential, depending on land-use suitability and land allocation strategies. We also show that applying spatial prioritization is key to maximizing the achievable potentials of abandoned cropland and demonstrate other possible approaches to further increase these potentials. Our findings offer timely insights into the potentials of abandoned cropland and can inform sustainable land management to buttress food security and climate goals.

Distribution pattern and change prediction of Phellodendron habitat in China under climate change

Phellodendron has always been of great significance in promoting human health and ecological restoration. However, human activities and climate change have severely affected habitat, population dynamics and sustainable use of Phellodendron. Little is known about the geographical distribution pattern and their responses to climate change of Phellodendron. In order to reveal the impact of climate change on Phellodendron, we conducted a study based on natural distribution data of two species (297 occurrence points), 20 environmental factors, and an optimized MaxEnt model. Our results identified the main environmental factors influencing Phellodendron, predicted their potential geographical distribution, and assessed migration trends under climate change in China. Our analysis showed that Ph. amurense and Ph. chinense have potential suitable habitats of 62.89 × 104 and 70.71 × 104 km2, respectively. Temperature and precipitation were found to play an essential role in shaping the present geographical distribution of Phellodendron populations. Based on two future climate scenarios, we forecasted that the potential suitable habitat of Ph. amurense would decrease by 12.52% (SSP245) and increase by 25.28% (SSP585), while Ph. chinense would decline by 19.61% (SSP245) and 15.78% (SSP585) in the late-21st century. The potential suitable habitats of Ph. amurense and Ph. chinense would shift to northward and westward, respectively. Hydrothermal change was found to be the primary driver of the suitable habitat of Phellodendron populations in the future. We recommend establishing nature reserves for existing Phellodendron populations, especially Ph. chinense. Our study provided a practical framework for the impact of climate change on the suitable habitat of Phellodendron species and guided regional cultivation, long-term conservation, and sustainable use.

Predicting the Impact of Climate Change on the Geographical Distribution of Leafhopper, Cicadella viridis in China through the MaxEnt Model

Cicadella viridis (Hemiptera: Cicadellidae) is an omnivorous leafhopper that feeds on plant sap. It significantly reduces the yield of agricultural and forestry crops while feeding or ovipositing on the host plant. In recent years, the rapid expansion of C. viridis has posed a serious threat to agricultural and forestry crops. To study the impact of climate change on the geographical distribution of the leafhopper, the maximum entropy (MaxEnt) model and ArcGIS software, combined with 253 geographic distribution records of the pest and 24 environmental variables, were used, for the first time, to predict the potential distribution of C. viridis in China under conditions of climatic change. The results showed that the currently suitable areas for C. viridis are 29.06-43° N, 65.25-85.15° E, and 93.45-128.85° E, with an estimated area of 11,231,423.79 km², i.e., 11.66% of China. The Loess Plateau, the North China Plain, and the Shandong Peninsula are the main suitable areas. The potential distribution of the leafhopper for the high and medium suitability areas decreased under each climate scenario (except RCP8.5 in the 2090s). Several key variables that have the most significant effect on the distribution of C. viridis were identified, including the mean annual temperature (Bio1), the standard deviation of temperature seasonality (Bio4), the minimum temperature of the coldest month (Bio6), and the precipitation of the coldest quarter (Bio19). Our research provides important guidance for developing effective monitoring and pest control methods for C. viridis, given the predicted challenges of altered pest dynamics related to future climate change.

Prediction of the Current and Future Distribution of Tomato Leafminer in China Using the MaxEnt Model

Tomato leafminer (Tuta absoluta), an important quarantine pest in China, was first detected in China in Yili, Xinjiang Uygur Autonomous Region, in 2017. Its damage has grown in recent years, severely harming Solanaceae plants in China and causing enormous economic losses. The study and prediction of the current and future suitable habitats for tomato leafminer in China can provide an important reference for the monitoring, early warning, and prevention and control of the pest. Here, tomato leafminer's potential distributions in China under the current climate and four future climate models (SSP1-26, SSP2-45, SSP3-70, and SSP5-85) were predicted using the maximum entropy (MaxEnt) model with ArcGIS software, and the accuracy of the prediction results was tested. The areas under the receiver operating characteristic curves of the models were all greater than 0.8, and the test omission rate of the model simulation results basically agreed with the theoretical omission rate, suggesting that the prediction results had satisfactory accuracy and reliability. Under the current climatic conditions, the highly suitable habitats for tomato leafminer in China are mainly distributed in most of North China, most of East China, most of South China, most of Central China, most of Southwest China, some parts of Northeast China, and only a few parts of Northwest China. Annual mean temperature is the main environmental factor limiting the distribution. The suitable habitats for tomato leafminer will shift under different future climate models: Under SSP1-26, the highly suitable habitats will spread to the north and northeast and to the southeast coastal areas; under SSP2-45, the size of highly suitable habitats will grow from the present to 2080 and shrink from 2081 to 2100; under SSP3-70, the highly suitable habitats will spread northeastwards, but the highly suitable habitats in southeast coastal areas will shrink from 2081 to 2100 and turn into moderately suitable habitats. Under SSP5-85, the highly suitable habitats will spread northeastwards and northwestwards, with the size of highly suitable habitats gradually decreasing and the size of moderately suitable habitats increasing. Different climates will lead to different distributions of suitable habitats for tomato leafminer, with annual mean temperature, isothermality, and mean diurnal range as the main environmental influences.

Streams in the Mediterranean Region are not for mussels: Predicting extinctions and range contractions under future climate change

Climate change is becoming the leading driver of biodiversity loss. The Mediterranean region, particularly southwestern Europe, is already confronting the consequences of ongoing global warming. Unprecedented biodiversity declines have been recorded, particularly within freshwater ecosystems. Freshwater mussels contribute to essential ecosystem services but are among the most threatened faunal groups on Earth. Their poor conservation status is related to the dependence on fish hosts to complete the life cycle, which also makes them particularly vulnerable to climate change. Species Distribution Models (SDMs) are commonly used to predict species distributions, but often disregard the potential effect of biotic interactions. This study investigated the potential impact of future climate on the distribution of freshwater mussel species while considering their obligatory interaction with fish hosts. Specifically, ensemble models were used to forecast the current and future distribution of six mussel species in the Iberian Peninsula, including environmental conditions and the distribution of fish hosts as predictors. We found that climate change is expected to severely impact the future distribution of Iberian mussels. Species with narrow ranges, namely Margaritifera margaritifera and Unio tumidiformis, were predicted to have their suitable habitats nearly lost and could potentially be facing regional and global extinctions, respectively. Anodonta anatina, Potomida littoralis, and particularly Unio delphinus and Unio mancus, are expected to suffer distributional losses but may gain new suitable habitats. A shift in their distribution to new suitable areas is only possible if fish hosts are able to disperse while carrying larvae. We also found that including the distribution of fish hosts in the mussels' models avoided the underprediction of habitat loss under climate change. This study warns of the imminent loss of mussel species and populations and the urgent need of management actions to reverse current trends and mitigate irreversible damage to species and ecosystems in Mediterranean regions.

Predicting of the current and future geographical distribution of Laurus nobilis L. under the effects of climate change

Today, climate change affects all living things on earth. It also leads to serious losses in terms of biodiversity, ecosystem services, and human welfare. In this context, Laurus nobilis L. is a very important species for Turkey, and the Mediterranean countries. This research aimed to simulate the current distribution of the suitable habitat for L. nobilis in Turkey and to predict its possible range shifts in future climate scenarios. To predict the geographical distribution of L. nobilis, the study used the maximum-entropy algorithm-based MaxEnt 3.4.1 with seven bioclimatic variables created using the Community Climate System Model 4.0 (CCSM4) and the prediction models RCP4.5-8.5 for the years 2050-2070. The results indicated that the most important bioclimatic variables that shape the distribution of L. nobilis are BIO11-mean temperature of coldest quarter, and BIO7-annual temperature range. Two climate change scenarios predicted that the geographical distribution of L. nobilis would increase slightly and then decrease in the future. However, the spatial change analysis showed that the general geographical distribution area of L. nobilis did not change significantly, but the "moderate," "high," and "very high" suitable habitats changed towards "low" suitable habitats. These changes were particularly effective in Turkey's Mediterranean region, which shows that climate change is instrumental in determining the future of the Mediterranean ecosystem. Therefore, suitability mapping and change analysis of potential future bioclimatic habitats can help in planning for land use, conservation, and ecological restoration of L. nobilis.

Habitat Suitability and Conflict Zone Mapping for the Blue Bull (Boselaphus tragocamelus) across Nepal

Rapidly changing environmental conditions (bioclimatic, anthropogenic, topographic, and vegetation-related variables) are likely to alter the spatial distribution of flora and fauna. To understand the influence of environmental variables on the Blue bull's distribution and to identify potential conflict zones, the habitat suitability analysis of the Blue bull was performed using ensemble modeling. We modelled the distribution of the Blue bull using an extensive database on the current distribution of the Blue bull and selected 15 ecologically significant environmental variables. We used ten species distribution modeling algorithms available in the BIOMOD2 R package. Among the ten algorithms, the Random Forest, Maxent, and Generalized linear model had the highest mean true skill statistics scores, ensuring better model performance, and were considered for further analysis. We found that 22,462.57 km² (15.26%) of Nepal is suitable for the Blue bull. Slope, precipitation seasonality, and distance to the road are the environmental variables contributing the most to the distribution of Blue bull. Of the total predicted suitable habitats, 86% lies outside protected areas and 55% overlaps with agricultural land. Thus, we recommend that the future conservation initiatives including appropriate conflict mitigation measures should be prioritized equally in both protected areas and outside protected areas to ensure the species' survival in the region.

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.

Prediction of the Current and Future Distributions of the Hessian Fly, Mayetiola destructor (Say), under Climatic Change in China

The Hessian fly, Mayetiola destructor (Say) (Diptera: Cecidomyiidae), is a destructive wheat pest worldwide and an important alien species in China. Based on 258 distribution records and nine environmental factors of the Hessian fly, we predicted the potential distribution area in China under three current and future (2050s and 2070s) climate change scenarios (RCP2.6, RCP4.5, and RCP8.5) via the optimized MaxEnt model. Under the current climate conditions, the suitable distribution areas of the Hessian fly in China were 25-48° N, 81-123° E, and the total highly suitable distribution area is approximately 9.63 × 10⁵ km², accounting for 9.99% of the total national area. The highly suitable areas are mainly located in northern Xinjiang and central and eastern China. With the rising global temperatures, except for the high-suitable areas under the RCP8.5 scenario, most potential geographic distribution areas would expand in the future. The minimum temperature in February (tmin-2), precipitation in March (prec-3), maximum temperature in November (tmax-11), and precipitation seasonality (bio-15) are important factors that affect the potential geographic distribution of the Hessian fly. This study provides an important reference and empirical basis for management of the Hessian fly in the future.

Predicting the Geographical Distribution Shift of Medicinal Plants in South Africa Due to Climate Change

There has been a recent rise in the number of medicinal plant users in Southern Africa, with approximately a million users reported to utilize these plants for various health conditions. Unfortunately, some of these plants are reportedly endangered and facing extinction due to harvesting pressure. In addition, climate change is likely to negatively affect the geographical distribution of these medicinal plants. In the current study, future greenhouse gas emission scenarios of the representative concentration pathways, RCP2.6 and RCP8.5, for future projections to 2050 and 2080 were used to simulate the effect of climate change on three medicinal plants’ (Aloe ferox, Bowiea volubilis, and Dioscorea elephantipes) distribution in South Africa. We studied these plant species as the International Union for Conservation of Nature stated that A. ferox is currently of least concern in South Africa, while B. volubilis and D. elephantipes are categorised as declining and vulnerable, respectively. Specifically, we utilised a species distribution model (i.e., the maximum entropy: MaxEnt) to investigate the effect of climate change on the future spatial distribution of medicinal plants in South Africa. In 2050 and 2080, under both RCP scenarios, the suitable habitat of the studied plant species will reduce in the country’s northern parts. Specifically, the habitat for D. elephantipes will totally disappear in the country’s northern parts. However, there will be slight additions of suitable habitats for the species in the country’s southern parts. Model validation indicated that the area under curve (AUC) for A. ferox was 0.924 ± 0.004, while for B. volubilis and D. elephantipes it was 0.884 ± 0.050 and 0.944 ± 0.030, respectively. Using the results from this study, there is a need for the long-term in situ and ex situ conservation of these medicinal plants. The results of the present study could guide the development of effective and efficient policies and strategies for managing and conserving medicinal plants in South Africa.

Ecological niche modelling as a tool to identify candidate indigenous chicken ecotypes of Tigray (Ethiopia)

The Tigray region is an ancient entry route for the domestic chickens into Africa. The oldest African chicken bones were found in this region at Mezber, a pre-Aksumite rural farming settlement. They were dated to around 800–400 BCE. Since then, the farming communities of the region have integrated chicken into their livelihoods. The region is also recognised for its high chicken-to-human population ratio and diverse and complex geography, ranging from 500 to 4,000 m above sea level (m.a.s.l.). More than 15 agro-ecological zones have been described. Following exotic chicken introductions, the proportion of indigenous chicken is now 70% only in the region. It calls for the characterisation of indigenous Tigrayan chicken ecotypes and their habitats. This study reports an Ecological Niche Modelling using MaxEnt to characterise the habitats of 16 indigenous village chicken populations of Tigray. A total of 34 ecological and landscape variables: climatic (22), soil (eight), vegetation, and land cover (four), were included. We applied Principal Component Analysis correlation, and MaxentVariableSelection procedures to select the most contributing and uncorrelated variables. The selected variables were three climatic (bio5 = maximum temperature of the warmest month, bio8 = mean temperature of the wettest quarter, bio13 = precipitation of the wettest month), three vegetation and land cover (grassland, forest land, and cultivated land proportional areas), and one soil (clay content). Following our analysis, we identified four main chicken agro-ecologies defining four candidates indigenous Tigrayan chicken ecotypes. The study provides baseline information for phenotypic and genetic characterisation as well as conservation interventions of indigenous Tigrayan chickens.

Genic distribution modelling predicts adaptation of the bank vole to climate change

The most likely pathway for many species to survive future climate change is by pre-existing trait variation providing a fitness advantage under the new climate. Here we evaluate the potential role of haemoglobin (Hb) variation in bank voles under future climate change. We model gene-climate relationships for two functionally distinct Hb types, HbS and HbF, which have a north-south distribution in Britain presenting an unusually tractable system linking genetic variation in physiology to geographical and temporal variation in climate. Projections to future climatic conditions suggest a change in relative climatic suitability that would result in HbS being displaced by HbF in northern Britain. This would facilitate local adaptation to future climate—without Hb displacement, populations in northern Britain would likely be suboptimally adapted because their Hb would not match local climatic conditions. Our study shows how pre-existing physiological differences can influence the adaptive capacity of species to climate change.

Haemoglobin variation in British bank voles combined with climate models predict future regional allelic replacement reflecting capacity for adaptation to climate change.

The effectiveness of a large protected area to conserve a global endemism hotspot may vanish in the face of climate and land-use changes

Endemic vertebrates are a crucial component of biodiversity, yet face disproportionally high extinction risk as climate and land-use changes drive habitat loss. Large protected areas are therefore deemed necessary to mitigate biodiversity loss. In 2021, China’s Giant Panda National Park (GPNP, 27,134 km2) was established in one of the global endemism hotspots. In this study we ask the question whether this large national park is able to conserve the many threatened endemic vertebrates occurring in the region in the face of climate and land-use changes, in order to assess the long-term effectiveness of the GPNP. We used species distribution modeling techniques to project the distributions of 40 threatened terrestrial (and freshwater) endemic vertebrates under land-use and climate change scenarios SSP2–4.5, SSP3–7.0 and SSP5–8.5 in 2081–2100, and assessed the extent to which their distributions are covered by the GPNP, now and in the future. We found that by 2081–2100, two thirds of the threatened endemic vertebrates are predicted to lose part (15–79%, N = 4) of or (nearly) their entire (80–100% loss, N = 23) range under all three climate and land-use change scenarios. Consequently, fewer species are predicted to occur in the GPNP than at present. Our findings confirm the high vulnerability of threatened endemic species to climate and land-use changes, despite protected areas. Habitat loss due to climate and land-use changes elevate extinction risk of species in endemism hotspots across the globe. Urgent, widespread and intensified mitigation measures and adaptation measures are required at a landscape scale for effective conservation efforts in the future.

Predicting the distribution of suitable habitat of the poisonous weed Astragalus variabilis in China under current and future climate conditions

Astragalus variabilis is a locoweed of northwest China that can seriously impede livestock development. However, it also plays various ecological roles, such as wind protection and sand fixation. Here, we used an optimized MaxEnt model to predict the distribution of suitable habitat of A. variabilis under current (1970-2000) conditions and future (2021-2080) climate change scenarios based on recent occurrence records. The most important environmental variables (suitability ranges in parentheses) affecting the distribution of A. variabilis were average maximum temperature of February (-2.12-5.34^°C), followed by total precipitation of June (2.06-37.33 mm), and topsoil organic carbon (0.36-0.69%). The habitat suitability of A. variabilis was significantly correlated with the frequency of livestock poisoning (p < 0.05). Under current climate conditions, the suitable environment of A. variabilis was distributed in central and western Inner Mongolia, Ningxia, central and northwestern Gansu, central and northwestern Qinghai, and the four basins around the Tianshan Mountains in Xinjiang. Under future climate conditions, the suitable habitat of A. variabilis shifted to higher latitudes and altitudes. No previous studies have used niche models to predict the suitable environment of this species nor analyzed the relationship between the habitat suitability of poisonous plants and the frequency of animal poisoning. Our findings provide new insights that will aid the prevention of livestock animal poisoning and the control of poisonous plants, promote the development of the livestock husbandry industry, and provide basic information that will facilitate the maintenance of the ecological balance of grassland ecosystems.

Richness and distribution of endangered orchid species under different climate scenarios on the Qinghai-Tibetan Plateau

Predicting the potential influences of climate change on the richness and distribution is essential for the protection of endangered species. Most orchid species are narrowly distributed in specific habitats and are very vulnerable to habitat disturbance, especially for endangered orchid species on the Qinghai-Tibetan Plateau (QTP). In this study, we simulated the potential influences of climate change on the richness and distribution of 17 endangered orchid species on the QTP using the MaxEnt model based on the shared socioeconomic pathways scenarios (SSPs) in the 2050s and 2070s. The results showed that aspect, annual precipitation, elevation, mean temperature of driest quarter, topsoil pH (H₂O), and topsoil sand fraction had a large influence on the potential distribution of endangered orchid species on the QTP. The area of potential distribution for orchid species richness ranging from 6 to 11 under the current climate scenario was 14,462 km² (accounting for 0.56% of QTP), and it was mostly distributed in the southeastern part of QTP. The area of orchid species richness ranging from 6 to 11 under SSP370 in the 2070s was the smallest (9,370 km²: only accounting for 0.36% of QTP). The largest area of potential distribution for orchid species richness ranging from 6 to 11 was 45,394 km² (accounting for 1.77% of QTP) under SSP585 in the 2070s. The total potential distribution area of 17 orchid species richness all increased from the 2050s to the 2070s under SSP126, SSP245, SSP370, and SSP585. The orchid species richness basically declined with the increasing elevation under current and future climate scenarios. The mean elevation of potential distribution for orchid species richness ranging from 6 to 11 under different climate scenarios was between 3,267 and 3,463 m. The mean elevation of potential distribution for orchid species richness ranging from 6 to 11 decreased from SSP126 (3,457 m) to SSP585 (3,267 m) in the 2070s. Based on these findings, future conservation plans should be concentrated on the selection of protected areas in the southeastern part of QTP to protect the endangered orchid species.

Habitat distribution change of commercial species in the Adriatic Sea during the COVID-19 pandemic

The COVID-19 pandemic has led to reduced anthropogenic pressure on ecosystems in several world areas, but resulting ecosystem responses in these areas have not been investigated. This paper presents an approach to make quick assessments of potential habitat changes in 2020 of eight marine species of commercial importance in the Adriatic Sea. Measurements from floating probes are interpolated through an advection-equation based model. The resulting distributions are then combined with species observations through an ecological niche model to estimate habitat distributions in the past years (2015–2018) at 0.1° spatial resolution. Habitat patterns over 2019 and 2020 are then extracted and explained in terms of specific environmental parameter changes. These changes are finally assessed for their potential dependency on climate change patterns and anthropogenic pressure change due to the pandemic. Our results demonstrate that the combined effect of climate change and the pandemic could have heterogeneous effects on habitat distributions: three species (Squilla mantis, Engraulis encrasicolus, and Solea solea) did not show significant niche distribution change; habitat suitability positively changed for Sepia officinalis, but negatively for Parapenaeus longirostris, due to increased temperature and decreasing dissolved oxygen (in the Adriatic) generally correlated with climate change; the combination of these trends with an average decrease in chlorophyll, probably due to the pandemic, extended the habitat distributions of Merluccius merluccius and Mullus barbatus but reduced Sardina pilchardus distribution. Although our results are based on approximated data and reliable at a macroscopic level, we present a very early insight of modifications that will possibly be observed years after the end of the pandemic when complete data will be available. Our approach is entirely based on Findable, Accessible, Interoperable, and Reusable (FAIR) data and is general enough to be used for other species and areas.

Predicting potential distribution of Ziziphus spinosa (Bunge) H.H. Hu ex F.H. Chen in China under climate change scenarios

Ziziphus spinosa (Bunge) H.H. Hu ex F.H. Chen is a woody plant species of the family Rhamnaceae (order Rhamnales) that possesses high nutritional and medicinal value. Predicting the effects of climate change on the distribution of Z. spinosa is of great significance for the investigation, protection, and exploitation of this germplasm resource. For this study, optimized maximum entropy models were employed to predict the distribution patterns and changes of its present (1970-2000) and future (2050s, 2070s, and 2090s) potential suitable regions in China under multiple climate scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0 & SSP5-8.5). The results revealed that the total area of the present potential suitable region for Z. spinosa is 162.60 × 104 km2, which accounts for 16.94% of China's territory. Within this area, the regions having low, medium, and high suitability were 80.14 × 104 km2, 81.50 × 104 km2, and 0.96 × 104 km2, respectively, with the high suitability regions being distributed primarily in Shanxi, Hebei, and Beijing Provinces. Except for SSP-1-2.6-2070s, SSP-5-8.5-2070s, and SSP-5-8.5-2090s, the suitable areas for Z. spinosa in the future increased to different degrees. Meanwhile, considering the distribution of Z. spinosa during different periods and under different climate scenarios, our study predicted that the low impact areas of Z. spinosa were mainly restricted to Shanxi, Shaanxi, Ningxia, Gansu, Liaoning, Inner Mongolia, and Jilin Provinces. The results of core distributional shifts showed that, except for SSP1-2.6, the center of the potential suitable region of Z. spinosa exhibited a trend of gradually shifting to the northwest.

Automatic variable selection in ecological niche modeling: A case study using Cassin's Sparrow (Peucaea cassinii)

MERRA/Max provides a feature selection approach to dimensionality reduction that enables direct use of global climate model outputs in ecological niche modeling. The system accomplishes this reduction through a Monte Carlo optimization in which many independent MaxEnt runs, operating on a species occurrence file and a small set of randomly selected variables in a large collection of variables, converge on an estimate of the top contributing predictors in the larger collection. These top predictors can be viewed as potential candidates in the variable selection step of the ecological niche modeling process. MERRA/Max's Monte Carlo algorithm operates on files stored in the underlying filesystem, making it scalable to large data sets. Its software components can run as parallel processes in a high-performance cloud computing environment to yield near real-time performance. In tests using Cassin's Sparrow (Peucaea cassinii) as the target species, MERRA/Max selected a set of predictors from Worldclim's Bioclim collection of 19 environmental variables that have been shown to be important determinants of the species' bioclimatic niche. It also selected biologically and ecologically plausible predictors from a more diverse set of 86 environmental variables derived from NASA's Modern-Era Retrospective Analysis for Research and Applications Version 2 (MERRA-2) reanalysis, an output product of the Goddard Earth Observing System Version 5 (GEOS-5) modeling system. We believe these results point to a technological approach that could expand the use global climate model outputs in ecological niche modeling, foster exploratory experimentation with otherwise difficult-to-use climate data sets, streamline the modeling process, and, eventually, enable automated bioclimatic modeling as a practical, readily accessible, low-cost, commercial cloud service.

Modelling habitat suitability of the invasive tick Rhipicephalus microplus in West Africa

Ticks have medical and economic importance due to their ability to transmit pathogens to humans and animals. In tropical and sub-tropical countries, tick-borne diseases (TBD) are among the most important diseases affecting livestock and humans. The fast spread of ticks and TBD requires a quick development and application of efficient prevention and/or control programs. Therefore, prior investigations on TBD and related vectors epidemiology, for instance, through accurate epidemiological models, are mandatory. This study aims to develop models to forecast suitable habitat for Rhipicephalus microplus distribution in West Africa. Tick occurrences were assembled from 10 different studies carried out in six West African countries in the past decade. Six statistical models (maximum entropy in a single model and generalised linear model, generalised additive model, random forest, boosted regression tree and support vector machine model in an ensemble model) were applied and compared to predict the habitat suitability of R. microplus distribution in West Africa. Each model was evaluated with the area under the receiver operating characteristic curve (AUC), the true skill statistic (TSS) and the Boyce index (BI). The selected models had good performance according to their AUC (above .8), TSS (above .7) and BI (above .8). Temperature played a key role in MaxEnt model, whereas normalised difference vegetation index (NDVI) was the most important variable in the ensemble model. The model predictions showed coastal countries of West Africa as more suitable for R. microplus. However, some Sahelian areas seems also favourable. We stress the importance of vector surveillance and control in countries that have not yet detected R. microplus but are in the areas predicted to host suitable habitat. Indeed, awareness-raising and training of different stakeholders must be reinforced for better prevention and control of this tick in these different countries according to their status.

Threats to land and environmental defenders in nature's last strongholds

Land and environmental defenders are a major bulwark against environmental destruction and biodiversity loss resulting from unsustainable nature resource extraction. Resultant conflicts can lead to violence against and deaths of these defenders. Along with mounting environmental pressures, homicides of these defenders are increasing globally. Yet, this issue has only recently started to receive scientific attention. While existing studies indicate the importance of socio-economic processes in driving such murders, spatially explicit global analyses considering environmental components are largely missing. Here, we take a broad spatial approach to assess relative contributions of environmental factors to the killing of environmental defenders. We find higher rates of such homicides are typically found in areas where limited or underutilized resources (e.g., freshwater, land and forests) are more available. Our results point towards a prevalent global land scarcity that results in industries targeting the last remaining strongholds for biodiversity and the environmental defenders within.

The Influence of Climate Change on Three Dominant Alpine Species under Different Scenarios on the Qinghai–Tibetan Plateau

The Qinghai–Tibetan Plateau (QTP) with high altitude and low temperature is one of the most sensitive areas to climate change and has recently experienced continuous warming. The species distribution on the QTP has undergone significant changes especially an upward shift with global warming in the past decades. In this study, two dominant trees (Picea crassifolia Kom and Sabina przewalskii Kom) and one dominant shrub (Potentilla parvifolia Fisch) were selected and their potential distributions using the MaxEnt model during three periods (current, the 2050s and the 2070s) were predicted. The predictions were based on four shared socio-economic pathway (SSPs) scenarios, namely, SSP2.6, SSP4.5, SSP7.0, SSP8.5. The predicted current potential distribution of three species was basically located in the northeastern of QTP, and the distribution of three species was most impacted by aspect, elevation, temperature seasonality, annual precipitation, precipitation of driest month, Subsoil CEC (clay), Subsoil bulk density and Subsoil CEC (soil). There were significant differences in the potential distribution of three species under four climate scenarios in the 2050s and 2070s including expanding, shifting, and shrinking. The total suitable habitat for Picea crassifolia shrank under SSP2.6, SSP4.5, SSP7.0 and enlarged under SSP8.5 in the 2070s. On the contrary, the total suitable habitat for Sabina przewalskii enlarged under SSP2.6, SSP4.5, SSP7.0 and shrank under SSP8.5 in the 2070s. The total suitable habitat for Potentilla parvifolia continued to increase with SSP2.6 to SSP8.5 in the 2070s. The average elevation in potentially suitable habitat for Potentilla parvifolia all increased except under SSP8.5 in the 2050s. Our study provides an important reference for the conservation of Picea crassifolia, Sabina przewalskii, Potentilla parvifolia and other dominant plant species on the QTP under future climate change.

Predicted declines in suitable habitat for greater one-horned rhinoceros (Rhinoceros unicornis) under future climate and land use change scenarios

Rapidly changing climate is likely to modify the spatial distribution of both flora and fauna. Land use change continues to alter the availability and quality of habitat and further intensifies the effects of climate change on wildlife species. We used an ensemble modeling approach to predict changes in habitat suitability for an iconic wildlife species, greater one-horned rhinoceros due to the combined effects of climate and land use changes. We compiled an extensive database on current rhinoceros distribution and selected nine ecologically meaningful environmental variables for developing ensemble models of habitat suitability using ten different species distribution modeling algorithms in the BIOMOD2 R package; and we did this under current climatic conditions and then projected them onto two possible climate change scenarios (SSP1-2.6 and SSP5-8.5) and two different time frames (2050 and 2070). Out of ten algorithms, random forest performed the best, and five environmental variables-distance from grasslands, mean temperature of driest quarter, distance from wetlands, annual precipitation, and slope, contributed the most in the model. The ensemble model estimated the current suitable habitat of rhinoceros to be 2610 km2, about 1.77% of the total area of Nepal. The future habitat suitability under the lowest and highest emission scenarios was estimated to be: (1) 2325 and 1904 km2 in 2050; and (2) 2287 and 1686 km2 in 2070, respectively. Our results suggest that over one-third of the current rhinoceros habitat would become unsuitable within a period of 50 years, with the predicted declines being influenced to a greater degree by climatic changes than land use changes. We have recommended several measures to moderate these impacts, including relocation of the proposed Nijgad International Airport given that a considerable portion of potential rhinoceros habitat will be lost if the airport is constructed on the currently proposed site.

Predicting the suitable habitats of parasitic desert species based on a niche model with Haloxylon ammodendron and Cistanche deserticola as examples

Haloxylon ammodendron, an excellent tree species for sand fixation and afforestation in the desert areas of western China, is threatened by climate change and anthropogenic activities. The suitable habitat of this species is shrinking at a remarkable rate, although conservation measures have been implemented. Cistanche deserticola is an entirely parasitic herb that occurs in deserts, is a source of "desert ginseng" worldwide, and has extremely high medicinal value. Little is known about using niche models to simulate habitat suitability and evaluate important environmental variables related to parasitic species. In this study, we modeled the current suitable habitat of H. ammodendron and C. deserticola by MaxEnt based on occurrence record data of the distributions of these two species in China. We grouped H. ammodendron and C. deserticola into three groups according to the characteristics of parasitic species and modeled them with environmental factors. The results showed that bioclimate was the most important environmental parameter affecting the H. ammodendron and C. deserticola distribution. Precipitations, such as annual precipitation, precipitation seasonality, and precipitation in the driest quarter, were identified as the most critical parameters. The slope, diurnal temperature range, water vapor pressure, ground-frost frequency, and solar radiation also substantially contributed to the distribution of the two species. The proportions of the most suitable areas for Groups 1, 2, and 3 were 1.2%, 1.3%, and 1.7%, respectively, in China. When combined with cultural geography, five hot spot conservation areas were determined within the distribution of H. ammodendron and C. deserticola. The comprehensive analysis indicated that by using MaxEnt to model the suitable habitat of parasitic species, we further improved the accuracy of the prediction and coupled the error of the distribution of a single species. This study provides a useful reference for the protection of H. ammodendron forests and the management of C. deserticola plantations.

Spatial patterns of phylogenetic diversity and endemism in the Western Ghats, India: A case study using ancient predatory arthropods

The Western Ghats (WG) mountain chain in peninsular India is a global biodiversity hotspot, one in which patterns of phylogenetic diversity and endemism remain to be documented across taxa. We used a well-characterized community of ancient soil predatory arthropods from the WG to understand diversity gradients, identify hotspots of endemism and conservation importance, and highlight poorly studied areas with unique biodiversity. We compiled an occurrence dataset for 19 species of scolopendrid centipedes, which was used to predict areas of habitat suitability using bioclimatic and geomorphological variables in Maxent. We used predicted distributions and a time-calibrated species phylogeny to calculate taxonomic and phylogenetic indices of diversity, endemism, and turnover. We observed a decreasing latitudinal gradient in taxonomic and phylogenetic diversity in the WG, which supports expectations from the latitudinal diversity gradient. The southern WG had the highest phylogenetic diversity and endemism, and was represented by lineages with long branch lengths as observed from relative phylogenetic diversity/endemism. These results indicate the persistence of lineages over evolutionary time in the southern WG and are consistent with predictions from the southern WG refuge hypothesis. The northern WG, despite having low phylogenetic diversity, had high values of phylogenetic endemism represented by distinct lineages as inferred from relative phylogenetic endemism. The distinct endemic lineages in this subregion might be adapted to life in lateritic plateaus characterized by poor soil conditions and high seasonality. Sites across an important biogeographic break, the Palghat Gap, broadly grouped separately in comparisons of species turnover along the WG. The southern WG and Nilgiris, adjoining the Palghat Gap, harbor unique centipede communities, where the causal role of climate or dispersal barriers in shaping diversity remains to be investigated. Our results highlight the need to use phylogeny and distribution data while assessing diversity and endemism patterns in the WG.

Wolf-Hunting Dog Interactions in a Biodiversity Hot Spot Area in Northern Greece: Preliminary Assessment and Implications for Conservation in the Dadia-Lefkimi-Soufli Forest National Park and Adjacent Areas

Simple Summary

Wolf attacks on hunting dogs are on the rise in many European countries, triggering retaliatory killing and poisoning of wolves. Poisoning may have detrimental effects on endangered vulture species. In critical areas for vulture conservation such as the Dadia-Lefkimi-Soufli Forest National Park, the conflict should be urgently evaluated. We assessed levels, trends, and defined related factors, by interviewing hunters and undertaking a diet analysis of wolf scats. Attacks affected mostly hare hunters, certain dog breeds and age classes, averaged one dog per hunter and decade, and happened under certain circumstances. Affected areas had specific landscape characteristics, fewer livestock, more hunting, and presence of wolf reproduction. Trends of wolf attacks on hunting dogs were positive and those on livestock negative. Wolves fed mainly on roe deer in summer and wild boar in winter, while the presence of dogs in scats was 5.1% in winter. Reduced dependence of wolves on livestock, as well as changes in wolf diet and hunting practices, may have predisposed wolves to kill more dogs recently. Wild boar also injured or killed hunting dogs, very often perplexing assessment of the conflict. The study concludes on practical measures for verifying and reducing hunting dog losses from wolf attacks.

Abstract

Hunting dog depredation by wolves triggers retaliatory killing, with negative impacts on wildlife conservation. In the wider area of the Dadia-Lefkimi-Soufli Forest National Park, reports on such incidents have increased lately. To investigate this conflict, we interviewed 56 affected hunters, conducted wolf trophic analysis, analyzed trends for 2010–2020, applied MAXENT models for risk-map creation, and GLMs to explore factors related to depredation levels. Losses averaged approximately one dog per decade and hunter showing a positive trend, while livestock depredations showed a negative trend. Wolves preyed mainly on wild prey, with dogs consisting of 5.1% of the winter diet. Low altitude areas, with low to medium livestock availability favoring wolf prey and game species, were the riskiest. Dogs were more vulnerable during hare hunting and attacks more frequent during wolf post-weaning season or in wolf territories with reproduction. Hunter experience and group hunting reduced losses. Wolves avoided larger breeds or older dogs. Making noise or closely keeping dogs reduced attack severity. Protective dog vests, risk maps, and enhancing wolf natural prey availability are further measures to be considered, along with a proper verification system to confirm and effectively separate wolf attacks from wild boar attacks, which were also common.

Assessing the effects of climate change on the distribution of Daphne mucronata in Iran

Zagros Mountains are like an island in the Middle East and they are subjected to changes in climate. Daphne mucronata Royle is an important medicinal plant species preserved in the high elevation regions in these mountains. Maxent species distribution model was used to integrate presence data (2413 points) and environmental variables to model the current and future potential distribution of D. mucronata in Iran. The most important variables were Bio19 with 50.5% contribution, followed by Bio8 and Bio2 with 30% and 11.4% contributions, respectively. The best Maxent model included seven variables, 4 feature types (linear, quadratic, product, and hinge), and had a test AUC value of 0.894. The current potential distribution indicated that 8% of Iran's drylands are suitable for growing D. mucronata and this area could decrease to 5.2% under representative concentration pathway (RCP) 4.5, and 3.1% under RCP 8.5 due to climate change. Our results suggest that D. mucronata may lose overall about 2.8% and 4.9% of its current distribution under RCP 4.5 and RCP 8.5, respectively, by 2050. There would be only 0.7 and 0.2% gains under RCP 4.5 and 8.5, respectively. The species would locally disappear between 1500- and 2000-m elevation under RCP 4.5 and 8.5, respectively. The establishment of some stations for monitoring the changes in transition zone or lost areas especially on the southeastern parts of Zagros Mountain can help in detecting changes in the future. Additionally, stable habitats may be good target areas for future conservation planning.

Distribution modelling of the garden dormouse Eliomys quercinus (Linnaeus, 1766) with novel climate change indicators

The garden dormouse Eliomys quercinus has been declining in both abundance and range since the mid-twentieth century. The eastern edge of its range has contracted from the Ural Mountains to eastern Germany. Habitat loss and fragmentation has been the most supported theory to explain the observed decline. Climate change has been implicated in declines of other terrestrial mammals, but not investigated for E. quercinus. To better understand the factors influencing the distribution of this species and to map habitat suitability for E. quercinus across Europe, we created a Maxent species distribution model. Among the main environmental variables used for the modelling, two novel climate change indicator variables were produced to indicate the degree of climate change between the early twentieth century and the present. Areas of high suitability were mapped, and variable importance estimated using jackknife tests and variable contribution metrics. The climate change indicators outperformed many conventional variables, which could indicate that climate change is a factor behind the current distribution of E. quercinus. We also analysed the land use types where presence points of E. quercinus were located and whether they were in areas of “high nature value farmland”. Over 30% of all spatially filtered presence points corresponded to high nature value farmland areas. Our results could indicate a role for changing climate (particularly in temperature) in the range decline E. quercinus, and for high nature value farmland practices in conserving this species. Field studies and improved monitoring for this species are recommended to confirm both possible findings.

Niche differentiation in a postglacial colonizer, the bank vole Clethrionomys glareolus

Species-level environmental niche modeling has been crucial in efforts to understand how species respond to climate variation and change. However, species often exhibit local adaptation and intraspecific niche differences that may be important to consider in predicting responses to climate. Here, we explore whether phylogeographic lineages of the bank vole originating from different glacial refugia (Carpathian, Western, Eastern, and Southern) show niche differentiation, which would suggest a role for local adaptation in biogeography of this widespread Eurasian small mammal. We first model the environmental requirements for the bank vole using species-wide occurrences (210 filtered records) and then model each lineage separately to examine niche overlap and test for niche differentiation in geographic and environmental space. We then use the models to estimate past [Last Glacial Maximum (LGM) and mid-Holocene] habitat suitability to compare with previously hypothesized glacial refugia for this species. Environmental niches are statistically significantly different from each other for all pairs of lineages in geographic and environmental space, and these differences cannot be explained by habitat availability within their respective ranges. Together with the inability of most of the lineages to correctly predict the distributions of other lineages, these results support intraspecific ecological differentiation in the bank vole. Model projections of habitat suitability during the LGM support glacial survival of the bank vole in the Mediterranean region and in central and western Europe. Niche differences between lineages and the resulting spatial segregation of habitat suitability suggest ecological differentiation has played a role in determining the present phylogeographic patterns in the bank vole. Our study illustrates that models pooling lineages within a species may obscure the potential for different responses to climate change among populations.