Potential Habitat Suitability Research Articles

Using an ensemble modeling to predict the potential distribution and habitat suitability of caracal (Caracal caracal) in southwestern Iran

Anthropogenic activities and climate change are degrading wildlife habitats, making it crucial to assess suitability of remaining habitat for effective conservation and management of threatened wildlife. This study aimed to determine the variables influencing habitat selection and spatial distribution of caracal (Caracal caracal) in southwestern Iran from 2019 to 2020. Ensembles of Small Models (ESM) were used based on eight species distribution models that included a combination of statistical and machine learning methods (GLM, CTA, FDA, GBM, ANN, MARS, RF, and MaxEnt). The outputs of two ensemble models were hybridized by simple averaging. In ESM 1, distance to water resources was used as a representative of environmental variables and in ESM 2, annual precipitation was used as a representative of bioclimatic variables. In both ESMs, these variables were combined with ecological variables such as the distribution of wild goat (Capra aegagrus) and livestock. The average importance of the model variables for ESM 1 and ESM 2 showed that the distribution of wild goat and livestock were the most important factors in predicting suitable habitat for caracals, respectively. Habitat suitability was higher close to the distribution of wild goat and livestock, near water sources and during periods of higher precipitation. Probabilistic predictions of caracal presence based on the hybridization of ESM 1 and ESM 2 suggest that only 1.3 % (206 ha) of the study area was highly suitable habitat, while 58.4 % (9570 ha) was unsuitable. Based on the ensemble of binary presence-absence maps, caracals were certainly absent in 76.2 % (12,490 ha) of the area, while their presence was uncertain in 21.6 % (3536 ha). The presence of caracals was certain in 2.2 % (363 ha) of the study area. Awareness of the habitat and distribution of caracal can help to make better decisions towards conservation and management and also reduce its conflict with humans.

Predicting suitable habitat for the endangered tree Ormosia microphylla in China

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

Multi-Model Analysis to Predict the Potential Suitable Habitat for Quercus oblongata D. Don (Fagaceae) in the Western Himalayan Region

Quercus oblongata D. Don is an economically and ecologically important tree species. It is distributed in the western Himalayan region of India as well as Nepal, Pakistan, Thailand, and Vietnam. The present study explored the potential distribution and habitat suitability of Q. oblongata using ensemble modeling. Eleven environmental variables (eight bioclimatic and three topographic), and 121 occurrence records were used in the analysis. Four algorithms: Generalized Additive Model (GAM), Generalized Linear Model (GLM), Random Forest (RF), and Maximum Entropy (Max Ent) were used to build the ensemble model for potential suitable habitat of Q. oblongata. To evaluate the model performance, AUC and TSS metrics were used, which showed high AUC (>0.94) and TSS (>0.86) metrics for all the models. The environmental variables that displayed high contribution in the prediction were temperature annual range (bio7, 48.5%), precipitation of wettest period (bio13 ; 41%), and elevation (elev ; 40%). The total suitable area was 22634 km2, including the least (12546 km2), moderate (7935 km2), and highly (2153 km2) suitable areas. Habitat suitability of Q. oblongata is predicted in most of the regions of Nainital, Almora, central Tehri Garhwal, eastern Mussoorie and Chakrata region of Dehradun District of Uttarakhand. A sizeable wide patch was found in Southern Chamba with Northern Kangra District, including the northern region of Mandi District of Himachal Pradesh. The predicted suitable habitat can be used for future exploration for the study of genetic diversity and conservation purposes.

Ensemble model-based analysis of the effects of environmental factors on the distribution and chemical composition of Asparagus cochinchinensis (Lour.) Merr.

Asparagus cochinchinensis (Lour.) Merr., is a traditional Chinese herbal medicine with pharmacological effects such as cough and asthma suppression, anti-inflammation, and immunity enhancement. Currently, as a wild resource it is scarce and its distribution has not been well defined. Especially in the context of climate change, the effect of the environment on its chemical composition is also unknown. In this study, we constructed an ensemble model of species distribution for A. cochinchinensis to predict its current and future potential suitable habitat areas, and explored the relationship between its chemical composition and key environmental factor using statistical analysis. The results showed that the Mean Diurnal Range (Bio2) contributed 67.74% to the model and was the key environmental factor influencing the distribution of A. cochinchinensis. The current habitat of A. cochinchinensis was mainly distributed in south-central and southeastern China, such as Sichuan, Chongqing, Guangxi, Guangdong and Fujian. Under the influence of climate change, its potential habitat would gradually decrease, especially in highly suitable areas. The results of chemical analysis showed that the quality of A. cochinchinensis was higher in Neijiang than other locations, which might be related to the fact that Bio2 in Neijiang was most suitable for growth. In addition, the correlation results showed that 12 out of 36 chemical indicators had significant correlation with Bio2, and all of them except protein and Tyr had significantly negative correlation with Bio2, indicating that the environment affected the biosynthesis of chemical composition of A. cochinchinensis. The results of the study provide theoretical guidance for the cultivation, management, and sustainable use of A. cochinchinensis resources, as well as a theoretical basis for their quality improvement.

Predicting the Spatial Distribution of the Mangshan Pit Viper (Protobothrops mangshanensis) under Climate Change Scenarios Using MaxEnt Modeling

This study explores the critical issue of understanding the potential impacts of climate change on the habitat suitability of the highly endangered forest-dwelling Mangshan pit viper (Protobothrops mangshanensis) in China. Through the application of the MaxEnt model, high-resolution bioclimatic datasets, and species occurrence data, the research aims to elucidate the spatial and temporal dynamics of P. mangshanensis distribution from the present to the years 2050 and 2070. Through the integration of three climate models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and exploring different shared socioeconomic pathway (SSP) scenarios (SSP126, SSP370, and SSP585), the study seeks to provide comprehensive insights into the potential variations in habitat suitability under diverse future climate conditions. The methodology employed involves the construction of the MaxEnt model utilizing the BioClim dataset and 83 species occurrence points. The SSP scenarios mentioned above represent future climate change scenarios, and the accuracy of the model is evaluated using the area under the receiver-operating characteristic (ROC) curve (AUC). Key findings reveal that the MaxEnt model exhibits high accuracy (AUC = 0.998), pinpointing the current suitable habitat for P. mangshanensis to be confined to the Mangshan area within the Nanling Mountains, covering an approximate area of 1023.12 km2. However, projections based on future climate scenarios suggest notable shifts in habitat suitability dynamics. While potential suitable habitats may emerge in the northwest of the current range, the existing suitable habitats are anticipated to undergo significant reduction or even complete disappearance. Notably, precipitation during the driest month emerges as a critical determinant influencing the distribution of the species. In conclusion, the study underscores the exacerbating impact of climate change on habitat deterioration and survival risks for P. mangshanensis, emphasizing the urgent need for conservation measures to safeguard the remaining suitable habitats for this endangered species. The implications of these findings are far-reaching, with the anticipated contraction of the snake’s range potentially leading to its disappearance and increased habitat fragmentation. By shedding light on the potential distributional changes of P. mangshanensis in Mangshan, the research provides valuable insights for informing targeted conservation strategies and policy interventions aimed at mitigating the adverse effects of climate change on endangered species.

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

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

Potential Suitable Habitats of Chili Pepper in China under Climate Change.

Chili pepper (Capsicum annuum L.) is extensively cultivated in China, with its production highly reliant on regional environmental conditions. Given ongoing climate change, it is imperative to assess its impact on chili pepper cultivation and identify suitable habitats for future cultivation. In this study, the MaxEnt model was optimized and utilized to predict suitable habitats for open-field chili pepper cultivation, and changes in these habitats were analyzed using ArcGIS v10.8. Our results showed that the parameter settings of the optimal model were FC = LQPTH and RM = 2.7, and the critical environmental variables influencing chili pepper distribution were annual mean temperature, isothermality, maximum temperature of the warmest month, and precipitation of the warmest quarter. Under current climate conditions, suitable habitats were distributed across all provinces in China, with moderately- and highly-suitable habitats concentrated in the east of the Qinghai-Tibetan Plateau and south of the Inner Mongolia Plateau. Under future climate scenarios, the area of suitable habitats was expected to be larger than the current ones, except for SSP126-2050s, and reached the maximum under SSP126-2090s. The overlapping suitable habitats were concentrated in the east of the Qinghai-Tibetan Plateau and south of the Inner Mongolia Plateau under various climate scenarios. In the 2050s, the centroids of suitable habitats were predicted to shift towards the southwest, except for SSP126, whereas this trend was reversed in the 2090s. Our results suggest that climate warming is conductive to the cultivation of chili pepper, and provide scientific guidance for the introduction and cultivation of chili pepper in the face of climate warming.

Modeling habitat suitability for the lesser-known populations of endangered mountain nyala (Tragelaphus buxtoni) in the Arsi and Ahmar Mountains, Ethiopia.

Habitat suitability models have become a valuable tool for wildlife conservation and management, and are frequently used to better understand the range and habitat requirements of rare and endangered species. In this study, we employed two habitat suitability modeling techniques, namely Boosted Regression Tree (BRT) and Maximum Entropy (Maxent) models, to identify potential suitable habitats for the endangered mountain nyala (Tragelaphus buxtoni) and environmental factors affecting its distribution in the Arsi and Ahmar Mountains of Ethiopia. Presence points, used to develop our habitat suitability models, were recorded from fecal pellet counts (n = 130) encountered along 196 randomly established transects in 2015 and 2016. Predictor variables used in our models included major landcover types, Normalized Difference Vegetation Index (NDVI), greenness and wetness tasseled cap vegetation indices, elevation, and slope. Area Under the Curve model evaluations for BRT and Maxent were 0.96 and 0.95, respectively, demonstrating high performance. Both models were then ensembled into a single binary output highlighting an area of agreement. Our results suggest that 1864 km2 (9.1%) of the 20,567 km2 study area is suitable habitat for the mountain nyala with land cover types, elevation, NDVI, and slope of the terrain being the most important variables for both models. Our results highlight the extent to which habitat loss and fragmentation have disconnected mountain nyala subpopulations. Our models demonstrate the importance of further protecting suitable habitats for mountain nyala to ensure the species' conservation.

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

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

Prediction on the changes in potential suitable areas for mangroves along the coast of Guangxi and the threat from Spartina alterniflora invasion.

As one of the important blue carbon pools in tropical and subtropical intertidal zones, mangroves are widely distributed along the coast of Guangxi in China. To deeply explore the variations of potential suitable habitats for mangroves in China under the background of climate change, based on remote sensing interpretation data of coastal wetlands in Guangxi, global marine environment and bioclimatic environment data in 2021, we constructed a maximum entropy habitat distribution model to simulate the spatial distribution of potential suitable areas for mangroves and the invasive species, Spartina alterniflora, along the coast of Guangxi, and predicted the patterns under extreme climate change scenarios (SSP5-8.5). The results showed that the interpreted area of mangrove forests along the coastline of Guangxi was 9136.7 hm2 in 2021, while the predicted area of potential suitable habitat area was 55955.9 hm2. Current distribution area of mangroves had basically covered its potential high suitability area and nearly 10% of the moderate suitability area. The current area of S. alterniflora was 1320.4 hm2, and the predicted area of potential high suitability area was twice of current area, indicating that there was still a large proportion of high suitability area that was not occupied by S. alterniflora. The most important environmental factors driving the distribution of potential habitats in mangroves were offshore Euclidean distance (62.2%), terrain deviation index (8.7%), average sea surface temperature in the hottest season (6.1%), and seabed terrain elevation (5.6%). The contribution of geographical conditions on mangrove distribution was predominant. Under the climate change scenario (SSP5-8.5), potential suitable area for mangroves would increase by 5.3%, while that for S. alterniflora would decrease by 3.1%. The overlapping proportion of the potential suitable area for mangroves and S. alterniflora was similar under current and SSP5-8.5 scenarios, being 15.2% and 14.5%, respectively. In the future, it is necessary to strengthen the protection and ecological restoration of mangroves along the coast of Guangxi and there is great challenge for preventing further invasion of S. alterniflora.

Assessment of the potential habitat suitability and ephedrine quality of two Ephedra species in China under climate change

Ephedra sinica and Ephedra intermedia are important medicinal plants and critical raw materials for ephedrine extraction in the pharmaceutical industry. Climate change will affect their distribution and quality. In our study, information on E. sinica and E. intermedia was collected through wilderness and online surveys. Using high-performance liquid chromatography, we determined the contents of ephedrine and pseudoephedrine. We then utilized the maximum entropy model to assess the potential impact of future climate on the distribution and quality of the two Ephedra. The results showed that the two Ephedra species were predominantly found in the arid and semiarid regions of northern China. The suitable habitats and quality area of E. intermedia will be severely degraded under RCP 2.6, RCP 4.5 and RCP 8.5 conditions and the results for E. sinica are the opposite. The accumulation of chemical components in E. sinica depends on the precipitation of the wettest month (Bio13) and soil sand content, while the accumulation of chemical components in E. intermedia depends on the mean temperature of the warmest quarter (Bio10) and the precipitation seasonality (Bio15). Overall, the research results provide the basis for the two high-quality Ephedra species for conservation and sustainable resource development.

Locustamigratoria (L.) (Orthoptera) in a warming world: unravelling the ecological consequences of climate change using GIS.

The migratory locust, Locustamigratoria (L.), a significant grasshopper species known for its ability to form large swarms and cause extensive damage to crops and vegetation, is subject to the influence of climate change. This research paper employs geographic information system (GIS) and MaxEnt ecological modelling techniques to assess the impact of climate change on the distribution patterns of L.migratoria. Occurrence data and environmental variables are collected and analysed to create predictive models for the current and future distribution of the species. The study highlights the crucial role of climate factors, particularly temperature and precipitation, in determining the locust's distribution. The MaxEnt models exhibit high-performance indicators, accurately predicting the potential habitat suitability of L.migratoria. Additionally, specific bioclimatic variables, such as mean temperature and annual precipitation, are identified as significant factors influencing the species' presence. The generated future maps indicate how this species will invade new regions especially in Europe. Such results predict the risk of this destructive species for many agriculture communities as a direct result of a warming world. The research provides valuable insights into the complex relationship between locust distribution and environmental factors, enabling the development of effective strategies for locust management and early warning systems to mitigate the impact on agriculture and ecosystems.

Prediction of potential suitable habitats in the 21st century and GAP analysis of priority conservation areas of Chionanthus retusus based on the MaxEnt and Marxan models.

Chionanthus retusus (C. retusus) has a high economic and medicinal value, but in recent years it has been included in the list of China's major protected plants and China's Red List of Biodiversity due to the serious destruction of its wild germplasm resources. Based on 131 sample points of C. retusus, this study simulated potential habitats and spatial changes of C. retusus in the 21st century using the Maxent model combined with the geographic information system ArcGIS, predicted prioritized protected areas by the Marxan model, and assessed current conservation status through GAP analysis. The results showed that (1) when the regularization multiplier was 1.5 and the feature combinations were linear, quadratic, and fragmented, the area under the curve of the subjects in the training and test sets were both above 0.9, the true skill statistic value was 0.80, and the maximum Kappa value was 0.62, meaning that the model had high accuracy; (2) Temperature seasonality, annual precipitation, min temperature for coldest month, and precipitation of wettest month had relatively strong influences on species' ranges. (3) The moderately and optimally suitable habitats of C. retusus were primly located in the areas of southwestern Shanxi, central Hebei, western Henan, Shandong, Shaanxi, Anhui and Hubei; (4) Under different future climate scenarios, the area of each class of suitable habitat will increase for varied amounts compared to the current period, with a general trend of expansion to the south; (5) The C. retusus priority protected areas were mainly located in most of Shandong, southern Liaoning, southwestern Shanxi, western Henan, and central Hebei, and its conservation vacancy area was relatively large compared to its protected area. These results will provide scientific strategies for implementing long-term conservation of C. retusus in China and similar regions under warming conditions in the 21st century.

Habitat suitability modelling of Koklass pheasant (Pucrasia macrolopha) in moist temperate forest.

The decreasing status of on IUCN of Koklass pheasant (Pucrasia macrolopha) belongs to the family Phasianidae and the order Galliform needs the attention of researchers. The species with habitats as low as 6,000 feet and as high as 11,000 feet certainly cover a broad variety of habitats, such a wide altitude range embraces a diverse range of habitats. Insufficient research has been conducted on the suitability of moist temperate forests as a potential habitat for the Koklass pheasant. Therefore, this study was carried out to explore habitat suitability in 15 different sites which were located in the 4 districts of Hazara Division using GIS data science and environmental variables. A random sampling technique was used for laying out the transect. Overall, 45 line transects (Length 2-4 km, Width 10-30 m) were laid out in study sites. The size of sample plots for trees was 10x10m, for shrubs (4 x4m), and herbs and grasses 1x1m. The other habitat parameters like elevation, slope, cover, and frequency of plant at each point were also considered. We found the uneven distribution of Koklass pheasant in the Hazara Division. There were 59 occurrence points identified and highlighted the distribution of Koklass pheasant in the study area. Although all environmental variables were preferred by Koklass pheasant in its habitat statistical analysis proved that slope, level of disturbance, tree and shrub frequency of habitat contributed mostly to the presence of Koklass in each study site except the contribution of soil and herbs. The potential suitable habitat of Koklass pheasant was estimated to be 439.6 km2 areas starting from Abbottabad to Mansehra in the Hazara division. Awareness and enforcing legal protection are recommended for the conservation of Koklass Pheasant in Moist temperate forest.

Climate Change Threatens the Habitat of Pinus massoniana in China

Pinus massoniana Lamb. is one of the main timber tree species. There is a large artificial planting area in South China, and this tree has important economic and ecological value. In this research, we built a comprehensive habitat suitability model based on 115 current data and 22 environmental variables to analyze the potential suitable habitat distribution of this species. Future climate change scenarios were defined as four shared socioeconomic pathways (SSPs): SSP 1–2.6, SSP 2–4.5, SSP 3–7.0, SSP 5–8.5) and four periods (including 2021–2040, 2041–2060, 2061–2080, and 2081–2100) based on nine global circulation model datasets. To fully consider the potential distribution of P. massoniana under specific climate change conditions and soil conditions, we constructed an ensemble model using four commonly used model algorithms. The results indicated that the current suitable habitat for P. massoniana covers approximately 1.10 × 106 km2 in southeastern China. In the future, the model results showed that under different climate change scenarios and at different times, the change in suitable habitat for P. massoniana varied; moreover, under moderate climate change scenarios, the average temperature decreased by less than 3 °C and the suitable habitat area decreased slightly, with an area larger than 0.95 × 106 km2. However, under intense warming scenarios, for which the average temperature increased above 3 °C, the suitable habitat for P. massoniana decreased. In the most severe warming scenario, the suitable habitat area for P. massoniana was reduced to 44% of the base climate conditions with severe habitat fragmentation, which should be fully considered in future planting initiatives and plant protection.

Modeling the potential distribution of the energy tree species Triadica sebifera in response to climate change in China

As an important woody oilseed species in China, Triadica sebifera is not only concerned with the substitution of traditional energy sources, but also plays a considerable role in coping with energy shortages. Accurately predicting the potential geographic distribution of Triadica sebifera in China and understanding its ecological needs are crucial for alleviating the energy crisis and effectively implementing energy substitution strategies. In this study, the potential geographic distribution of Triadica sebifera in China at contemporary and future periods was predicted based on the distribution data of Triadica sebifera in China and the environmental factor variables by Maxent model and ArcGIS software. The combination of important factors governing the potential geographic distribution of Triadica sebifera was assessed by the contribution of environmental factor variables. The accuracy of Maxent model's predictions was assessed by AUC values, TSS values and Kappa statistics. The results show that: High AUC and TSS values indicate high accuracy and performance of the model. The crucial environmental factors limiting the potential geographic distribution of Triadica sebifera are the temperature factor (mean air temperature of the driest quarter), precipitation factor (precipitation of the coldest quarter, precipitation of the wettest month), and the intensity of human activities (hf). The total suitable area for Triadica sebifera is 233.64 × 104 km2, primarily located in Yunnan, Sichuan, Hubei, Guizhou, Jiangxi, Guangdong province and Guangxi Zhuang Autonomous Region; its high suitability area is 30.89 × 104 km2, accounting for 13.22% of the total suitable area, mainly distributed in Jiangxi, Sichuan and Hunan provinces in the shape of a cake. Under the four typical greenhouse gas emission concentration patterns in the 2050s and 2070s, the areas of high and medium suitable areas for Triadica sebifera will increase, while the area of its low suitable area will decrease. However, the total suitable area will remain relatively unchanged. Its potential suitable habitats show a trend of shifting towards lower latitudes and southeast regions. The study predicted the pattern of Triadica sebifera under different climate change conditions, which can provide guidance for future cultivation of Triadica sebifera as well as for biofuel development and utilization.

Assessing the Current and Future Potential Distribution of Solanum rostratum Dunal in China Using Multisource Remote Sensing Data and Principal Component Analysis

Accurate information concerning the spatial distribution of invasive alien species’ habitats is essential for invasive species prevention and management, and ecological sustainability. Currently, nationwide identification of suitable habitats for the highly destructive and potentially invasive weed, Solanum rostratum Dunal (S. rostratum), poses a series of challenges. Simultaneously, research on potential future invasion areas and likely directions of spread has not received adequate attention. This study, based on species occurrence data and multi-dimensional environmental variables constructed from multi-source remote sensing data, utilized Principal Component Analysis (PCA) in combination with the Maxent model to effectively model the current and future potential habitat distribution of S. rostratum in China, while quantitatively assessing the various factors influencing its distribution. Research findings indicate that the current suitable habitat area of S. rostratum covers 1.3952 million km2, all of which is located in northern China. As the trend of climate warming persists, the potential habitat suitability range of S. rostratum is projected to shift southward and expand in the future; while still predominantly located in northern China, it will have varying degrees of expansion at different time frames. Notably, during the period from 2040 to 2061, under the SSP1-2.6 scenario, the habitat area exhibits the most significant increase, surpassing the current scenario by 19.23%. Furthermore, attribution analysis based on PCA inverse transformation reveals that a combination of soil, climate, spatial, humanistic, and topographic variables collectively influence the suitability of S. rostratum habitats, with soil factors, in particular, playing a dominant role and contributing up to 75.85%. This study identifies target areas for the management and control of S. rostratum, providing valuable insights into factor selection and variable screening methods in species distribution modeling (SDM).

Habitat Suitability, Distribution Modelling and GAP Analysis of Przewalski's Gazelle Conservation.

Although the population of Przewalski's gazelle (Procapra przewalskii) has increased, this species is still threatened by a variety of risk factors, such as habitat loss and fragmentation, grassland fencing, grazing conflict, the segmentation of different populations, and declines in population genetic diversity. In order to determine the potential suitable habitat of Przewalski's gazelle and find a new suitable location for its conservation translocation, we used the MaxEnt model to predict the suitable habitats in Qinghai Province, Gansu Province, and the Ordos Plateau in Inner Mongolia and other regions with historical distribution records. On the basis of the MaxEnt model's prediction of the potential suitable habitat of Przewalski's gazelle, we used GAP analysis to determine the existing protection gaps and provide a new reference for the future protection of Przewalski's gazelle. We found that altitude, temperature, vegetation type, and distance from roads were the main environmental factors affecting the geographical distribution of Przewalski's gazelle. Most of the suitable habitat of Przewalski's gazelle is confined around Qinghai Lake. GAP analysis revealed that most of the suitable habitats of Przewalski's gazelle are not included in the established reserves, and Qinghai Lake National Nature Reserve only covers a small area around Qinghai Lake. The whole reserve only accounts for 7.11% of the area of the suitable habitat for Przewalski's gazelle and 15.79% of the area of the highly suitable habitat for Przewalski's gazelle. We suggest that conservation translocation for Przewalski's gazelle should be put on the agenda. It is necessary to consider reintroducing these gazelles into their potential suitable habitats as a feasible way of establishing new populations and saving this species.

Future habitat changes of Bactrocera minax Enderlein along the Yangtze River Basin using the optimal MaxEnt model.

Bactrocera minax (Enderlein, 1920) (Diptera: Tephritidae) is a destructive citrus pest. It is mainly distributed throughout Shaanxi, Sichuan, Chongqing, Guizhou, Yunnan, Hubei, Hunan, and Guangxi in China and is considered to be a second-class pest that is prohibited from entering that country. Climate change, new farming techniques, and increased international trade has caused the habitable area of this pest to gradually expand. Understanding the suitable habitats of B. minax under future climate scenarios may be crucial to reveal the expansion pattern of the insect and develop corresponding prevention strategies in China. Using on the current 199 distribution points and 11 environmental variables for B. minax, we chose the optimal MaxEnt model to screen the dominant factors that affect the distribution of B. minax and to predict the potential future distribution of B. minax in China under two shared socio-economic pathways (SSP1-2.6, SSP5-8.5). The current habitat of B. minax is located at 24.1-34.6°N and 101.1-122.9°E, which encompasses the provinces of Guizhou, Sichuan, Hubei, Hunan, Chongqing, and Yunnan (21.64 × 104 km2). Under future climate scenarios, the potential suitable habitat for B. minax may expand significantly toward the lower-middle reaches of the Yangtze River. The land coverage of highly suitable habitats may increase from 21.64 × 104 km2 to 26.35 × 104 × 104 km2 (2050s, SSP5-8.5) ~ 33.51 × 104 km2 (2090s, SSP5-8.5). This expansion area accounts for 29% (2050s, SSP1-2.6) to 34.83% (2090s, SSP1-2.6) of the current habitat. The center of the suitable habitat was predicted to expand towards the northeast, and the scenario with a stronger radiative force corresponded to a more marked movement of the center toward higher latitudes. A jackknife test showed that the dominant variables affecting the distribution of B. minax were the mean temperature of the driest quarter (bio9), the annual precipitation (bio12), the mean diurnal range (bio2), the temperature annual range (bio7), and the altitude (alt). Currently, it is possible for B. minax to expand its damaging presence. Regions with appropriate climate conditions and distribution of host plants may become potential habitats for the insects, and local authorities should strengthen their detection and prevention strategies. Climate changes in the future may promote the survival and expansion of B. minax species in China, which is represented by the significant increase of suitable habitats toward regions of high altitudes and latitudes across all directions but with some shrinkage in the east and west sides.

Prioritizing ecological connectivity among protected areas in Colombia using a functional approach for birds

Ecological connectivity among Protected Areas (PAs) is essential to improve biodiversity conservation and management effectiveness under global change. In Colombia, developing strategic plans and locating spatial priorities for PA connectivity is fundamental for conserving its extraordinary bird diversity in the face of multiple threats, including deforestation and climate change. Here, we develop a multispecies bird connectivity model to identify critical sites for preserving and enhancing the ecological connections among PAs in Colombia. We focused our analyses on 26 forest-dependent bird species, determining their potential suitable habitat across Colombia using species distribution models and climatic variables. Expert knowledge guided the construction of movement resistance surfaces across these distributions to describe how different land covers impede or facilitate species movement. Using these inputs, we mapped Least-Cost Corridors (LCCs) connecting national and subnational PAs meeting the area requirements for the selected species. Additionally, we used circuit and least-cost models to locate conservation priorities and restoration opportunities, estimating the potential connectivity gains through the Equivalent Connected Area (ECA) index. We aggregated individual species results to create multispecies composite maps highlighting spatial agreements for corridors, priority conservation areas, and restoration opportunities. We found 581,531 km2 belonging to corridors among PAs for all focal species. Priority sites for movement within corridors covered 212,551 km2 and were predominantly located across Andean and Amazonian forests. Restoration opportunities covered 79,203 km2 and were concentrated in agricultural lands of the Andes and Caribbean regions. Restoring these areas could increase the national forest cover by 7% and connectivity by 14%. Our results provide a national-level assessment of functional connectivity priorities to maintain and improve the interconnections among PAs in Colombia. This assessment could guide efforts related to conservation, restoration, and implementation of management tools that facilitate the movement of native species across transformed lands. These actions are crucial to meet the targets outlined in the post-2020 global biodiversity framework to achieve well-connected systems of PAs during this decade and until 2050.