Low Suitability Areas Research Articles

Assessing Habitat Suitability for the Invasive Species Lantana camara on Bali Island: A Model Using the Biodiversity and Climate Change Virtual Laboratory (BCCVL)

Indonesia, known for its high biodiversity, is threatened due to alien plants that invade local plant species in forest areas. West Bali National Park is overgrown with invasive exotic plants, such as Lantana camara L., known locally as the kembang telek. The research aims to predict the distribution of L. camara using species distribution models (SDMs) and analysis variable contribution in the model featured in the biodiversity climate change virtual laboratory (BCCVL) application. L. camara distribution prediction model in Bali used the Bioclim data input by identifying areas of low, medium, and high habitat suitability. Central mountainous regions, including parts of Buleleng, Jembrana, Bangli, Karangasem, and Tabanan, show the highest suitability. Response curves demonstrated the correlation between climate variables and occurrence probability, highlighting the specific condition of rainfall and temperature ranges favoring Lantana's growth. The model showed a reliable AUC value of 0.89, indicating realibility. Potential improvements through additional environmental parameters were suggested. While L. camara has some potential benefits as a medicinal plant in Balinese culture, its invasive nature poses significant threats to native ecosystems. The predictive map offers valuable insights for authorities to implement initiative-taking strategies for preventing and controlling Lantanas spread in vulnerable areas of Bali.

Habitat Assessment of Bocachico (Prochilodus magdalenae) in Ciénaga de Betancí, Colombia, Using a Habitat Suitability Index Model

This study evaluates the habitat of the Bocachico fish (Prochilodus magdalenae) in the Ciénaga de Betancí, Colombia, using a habitat suitability index (HSI) model. Wetlands like the Ciénaga de Betancí are under significant pressure from anthropogenic activities, affecting biodiversity and ecosystem health. The Bocachico, a species of immense cultural and economic importance, faces habitat degradation and fragmentation. Using hydrodynamic and water quality data, a numerical model (EFDC+ Explorer 11.5), and field data collected from multiple sampling campaigns, we assessed habitat suitability based on five key parameters: water temperature, dissolved oxygen, ammonia nitrogen, velocity, and depth. The model results indicated that environmental conditions in the wetland remained relatively stable during the dry season, with an average HSI score of 0.67, where 9% of the wetland area displayed acceptable conditions, and the remaining 91% displayed medium conditions. The wet season, on the other hand, had an average HSI score of 0.64, with 7.2% of the area in the acceptable suitability range, and the remaining 92.8% in the medium category. Variations in HSI were primarily driven by ammonia nitrogen levels, water velocity, and depth. Despite limited fluctuations in the HSI, areas of low suitability were identified, particularly in regions impacted by human activities. These findings have practical implications for conservation strategies, providing valuable insights for the sustainable management and conservation of the Ciénaga de Betancí, informing strategies for improving habitat conditions for the Bocachico, and supporting wetland restoration efforts.

PREDICTING THE POTENTIAL DISTRIBUTION OF Pinus cernua L.K. PHAN EX AVER., K.S. NGUYEN AND T.H. NGUYEN, A CRITICALLY ENDANGERED CONIFER SPECIES

Pinus cernua L.K. Phan ex Aver., K.S. Nguyen and T.H. Nguyen (Pinaceae) is a critically endangered species restricted to the Laos - Vietnam border. The population of this species has been declining due to habitat loss and forest fire. Predicting the potential distribution of the species is an important priority for conservation plans and strategies. In this study, a MaxEnt model was used for predicting the potential distribution of P. cernua using 21 occurrence data and 13 environmental variables. Precipitation of driest month (with 32.3% of contribution), annual mean diurnal range (23.4%), elevation (18.4%), and aspect (12.3%) are crucial factors for predicting the species’ potential distribution in the MaxEnt model, while remaining factors are less important factors. The suitable distribution was predicted in the north-western region of Vietnam and the adjacent regions of Son La and Thanh Hoa provinces (Vietnam) and Houaphan province (Laos) with 1,544 km2 in total. The high, medium, and low suitability areas are 159 km2 (10%), 475 km2 (31%), and 910 km2 (59%), respectively. The current protected areas do not contain many of the possible habitats for this species. Priority should be given to conservation efforts for species in these potentially suitable locations both in- and outside of current protected areas, particularly in the surrounding area of Vietnam and Laos.

Habitat and density effects on the demography of an expanding wolf population in Central Europe

Demographic parameters are key to understanding population dynamics. Here, we analyse the survival and reproduction of the German wolf population in the 20 years following recolonization. Specifically, we analysed the effects of environmental, ecological and individual characteristics on 1) survival probability of the population; 2) annual survival rates of age classes; 3) reproduction probability; and 4) reproductive output, measured as the number of detected pups/juveniles. Using Cox proportional hazards model, we estimated a median survival time of circa three years for wolves. Annual survival probabilities were found to be 0.75 for juveniles, 0.75 for subadults and 0.88 for adults. Survival was lower for juveniles in winter and for subadult males in summer, probably associated with dispersal events. Low habitat suitability was clearly associated with lower survival in juveniles and subadults, but not in adults. Local territory density was related to increased survival. Reproduction probability within a territory was 0.88, but explanatory variables had no effect. Reproductive output was four pups/juveniles on average, positively related to habitat suitability and female experience, but negatively related to territory density. Survival values were very high for the species when compared to other regions. We hypothesize that carrying capacity has not been reached in the study area, thus the survival may decrease in the future if the landscape becomes saturated. Furthermore, our results highlight a spatial pattern in survival and reproduction, with area of better habitat suitability favouring faster population growth. Thus, targeting conservation measures to low habitat suitability areas will have a strong population effect on the short term by boosting survival and reproduction of the individuals, while long‐term viability should be carefully planned with high suitability areas in mind, as those contain the territories with higher survival and reproduction potential.

Prediction of Potential Suitability Areas for Ephedra sinica in the Five Northwestern Provinces of China Under Climate Change

Ephedra sinica (E. sinica) holds significant economic and medicinal importance and is predominantly found in arid areas. Due to the limitations of environmental variables, growth habits, and human activities, the production and suitability areas of E. sinica have significantly decreased, especially in the five northwestern provinces of China. In this study, 212 distribution points of E. sinica and 40 environmental variables were obtained to project the habitat suitability of E. sinica under different emission scenarios in the future. It identified precipitation in the wettest month, monthly mean of the diurnal temperature difference, and solar radiation intensity in April and July as the primary environmental factors affecting the suitability of E. sinica in the region. The areas of high, medium, and low suitability in the region cover 103,000 km2, 376,500 km2, and 486,800 km2. Under future scenarios, the suitability areas from 2021 to 2100 will decrease by 20%, with high suitability areas decreasing by 65% to 85% particularly. With comprehensive environmental variables, the suitability areas of E. sinica from 2021 to 2100 are projected, filling the gap in the projection of E. sinica suitability areas in the five northwestern provinces of China over long time period. The suitability areas show a significant decreasing trend. This research provides valuable insights into the suitability areas and crucial environmental factors, offering theoretical support for future protection and management efforts for E. sinica.

Performance of artificial intelligence model (LSTM model) for estimating and predicting water quality index for irrigation purposes in order to improve agricultural production.

The primary goal of this study is to predict the current and future water quality index for irrigation (WQII) of the western Mitidja alluvial aquifer in northern Algeria. The modified WQII was used to evaluate groundwater suitability for irrigation through geographic information system (GIS) techniques. Additionally, a long short-term memory (LSTM) model was employed to calculate the WQII and map future groundwater quality, considering factors like overexploitation, anthropogenic pollution, and climate change. Two scenarios were analyzed for the year 2030. Results from applying the modified WQII model to 2020 data showed that about 83% of the study area has medium to high groundwater suitability for irrigation. The LSTM model exhibited strong predictive accuracy with determination coefficients (R2) of 0.992 and 0.987, and root mean square error (RMSE) values of 0.061 and 0.084 for the training and testing phases, respectively. For the first 2030 scenario, the area with low and medium groundwater suitability is expected to increase by 4% and 7% compared to the 2020 map. Conversely, under the second scenario, groundwater quality is predicted to improve, with a decrease of 14% and 11% in the low and medium suitability areas. The combination of the modified WQII and LSTM model proves to be an effective tool for estimating and predicting water quality indices in similar regions globally, offering valuable insights for water resource management and decision-making processes.

Forecasting Appropriate Habitats for Rare and Endangered Indocalamus Species in China in Response to Climate Change

China’s rare and endangered bamboo species belonging to the Indocalamus genus, specifically Indocalamus decorus Q. H. Dai, Indocalamus hirsutissimus Z. P. Wang & P. X. Zhang, and Indocalamus pedalis (Keng) P. C. Keng, possess notable value in biodiversity conservation and have significant potential for use in landscape design. Using an enhanced MaxEnt model, this study forecasted shifts in the species’ potential range under four separate climate scenarios (SSP1-RCP2.6, SSP2-RCP4.5, SSP3-RCP7.0, and SSP5-RCP8.5), considering both the historical period (1970–2000, referred to as “the current period”) and upcoming timeframes (2021–2040, 2041–2060, 2061–2080, and 2081–2100). The analysis disclosed that the present total potential habitat area for these species is approximately 251.79 × 104 km2, with high, medium, and low suitability areas occupying 0.15 × 104 km2, 125.39 × 104 km2, and 126.26 × 104 km2, respectively. The minimum temperature of the coldest month emerged as the critical determinant of their potential habitat distribution. Expected climate changes are likely to increase the suitable habitat for these species, although areas with low suitability might slightly diminish, with Guizhou and Chongqing showing the least impact. The distribution centers of suitable habitats for the three plant species consistently exhibit a westward shift under various climate scenarios. These results contribute valuable insights for the spatial distribution, continuous monitoring, sustainable management, and ex situ conservation in response to climate change.

GIS-based multi-criteria approach for ranking suitable areas for the implementation of PV-Powered MCDI desalination plants in the Rheris Watershed, Southeast Morocco

In Morocco's oases, which rely heavily on surface water from mountain sources, the threat of decreasing rainfall presents a significant challenge, leading to a decline in surface water availability. This study focuses on the Rheris Watershed in Southeast Morocco, where brackish water desalination emerges as a viable alternative to ensure sustainable water supply for agriculture. Prior to the deployment of a pilot plant integrating a desalination unit, selecting an optimal site for PV-powered MCDI desalination plants was critical. This selection was based on a range of criteria, including Groundwater Quantity, Global Horizontal Irradiation, Temperature, Evaporation, Water Salinity, Water Quantity, Well Density and Slope. These criteria were evaluated using a combination of the Analytical Hierarchy Process (AHP), and geospatial data obtained from Remote Sensing (RS) and Geographic Information System (GIS) techniques.This case study in the Rheris watershed identified potential sites for future Membrane Capacitive Deionization (MCDI) desalination projects, High suitability areas encompass 280.45 km² (30.91 %), located west of Tinejdad, Khettarat Moulay Hachem, north of Goulmima, and south of Tinghir. Low suitability areas cover 63.75 km² (7.02 % of the study area), including regions south of Tadighoust and Tinejdad. Moderate suitability areas span 562.86 km² (62.05 %), involving central regions of Goulmima, Tadighoust, Tinejdad, and Tinghir. Based on the results of the study, the recommendations include focusing on areas identified as highly suitable for MCDI technology for sustainable agriculture, refining selection criteria based on local data, exploring brine management strategies, and adopting integrated water management approaches to ensure sustainable resource use.

Geospatial analysis of elephant habitat suitability and movement for mapping the elephant corridor in Dalma Wildlife Sanctuary (India).

Wildlife and natural resources constitute an integral part of the ecosystem, whereas human interventions dismantled the living conditions of the wildlife. This is testified in the Dalma Wildlife Sanctuary (DWS) where the habitats of Asian elephants have changed due to human intervention and deforestation over the decades. The present study aimed to assess the elephant habitat suitability in the DWS of Jharkhand state (India) using the geospatial parameters such as forest density, degree of slope, proximity to water bodies, land use land cover, proximity to agricultural land, built-up density, and road density. The analytical hierarchical process technique was utilized to determine habitat preference and selection of relevant factors to categorize criteria. The study revealed that about 6.7% (26.74 km2) of the area is very highly suitable for elephant habitat, while 52.26% (208.49 km2) of the forest area was found highly suitable. The most suitable habitat was identified in the core parts of the forest, while the least suitable areas were found in the southern part, where the presence of roads, built-up, and agricultural land was prominent. It was also observed that most human-elephant conflicts were exhibited in the low and very low suitable areas, while 90% of the elephant movement was witnessed in the high and very high suitable areas. Among the four identified corridors, three are inactive, and their location corresponds with low to very low suitable habitats. The study identified the migratory corridor routes inside the sanctuary where effective management is required for the conservation of elephant habitats and minimizing conflicts.

Ecological niche modeling to identify cultivation areas for pineapple in the Republic of Benin

Pineapple is one of the most important tropical fruit species, widely cultivated and economically important in Benin. This study aimed to identify potentially favorable areas for the cultivation of pineapple under current and future environmental conditions in Benin. The two cultivars of pineapple grown in Benin were separately considered: Sugarloaf and Smooth Cayenne. Five (05) modeling algorithms such as Maxent, Random Forest (RF), Support-Vector Machines (SVM), Boosted Regression Trees (BRT) and Generalized Linear Model (GLM) were compared using the criteria: area under the curve (AUC), sensitivity, specificity, Cohen’s Kappa, deviance and True Skill Statistic (TSS). The future climate models available for Africa at horizon 2055 were used under the “Representative Concentration Pathways” scenario 4.5 and 8.5. Results suggested that pineapple suitable areas were governed by a combination of effects of climate (temperature and precipitation) and soils characteristics. Indeed, soil pH, temperature seasonality and precipitation of driest quarter were the main variables driving pineapple production in Benin. Results also indicated that RF was the most suitable technique to model the distribution of pineapples regardless of the variety. The current potential range of favorable areas for the two varieties was mainly found in the central and southern parts of the country. In the future, following the RCP4.5 scenario, there will be an increase in the area favorable for the cultivation of Smooth Cayenne variety by 5.28% compared to the current situation whereas, the area favorable for the cultivation of the Sugarloaf variety will be increased by 7.7%. However, suitable areas for cultivation of Smooth Cayenne and Sugarloaf following the RCP8.5 scenario will be increased, respectively by 21.82% and 31.64%. The low and medium suitability areas for the cultivation of smooth cayenne will decrease by 15.57% and 2.93%, respectively at the horizon 2055 with future conditions under RCP4.5, and 15.48% and 4.97%, respectively at the horizon 2055 with future conditions under RCP8.5. For sugarloaf, the low and medium suitable cultivation areas will decrease by 1.59% and 14.24, respectively at the horizon 2055 with future conditions under RCP4.5. According to RCP8.5, the low suitable areas will decrease by 5.08%. This study constitutes an initial step towards a sustainable scheme for planning exploration of the possibility of extending pineapple cultivation in Benin. Key words: Climate change, modeling, algorithms, pineapple, potential area distribution

Effects of environment and human activities on rice planting suitability based on MaxEnt model.

Rice is one of the major food crops, and the study of suitable planting areas for rice plays an important role in improving rice yield and optimizing the production layout. This study used Maximum Entropy (MaxEnt) model to simulate and predict the distribution of suitable rice planting areas in China from 1981 to 2020 by combining the climate, soil, and human activities, analyzed the spatial and temporal changes of suitable rice planting areas in China, and determined the main factors affecting rice planting suitability. The results indicated that the main factors influencing the distribution of suitable planting areas for rice in China were gross domestic product (GDP), population density (Pop), and annual sunshine duration (Sun), with human activities playing a dominant role. The high suitable planting areas of rice were mainly distributed in Hubei, Hunan, Jiangxi, Anhui, Guangdong, southeastern Sichuan and western Guizhou. The total suitable planting areas for rice were 346.00 × 104 km2, 345.66 × 104 km2, 347.01 × 104 km2, and 355.57 × 104 km2 from 1981 to 1990, 1991 to 2000, 2001 to 2010 and 2011 to 2020, respectively. With the passage of time, the area of unsuitable areas for rice gradually decreased, and the area of medium suitable areas increased, with large changes in the area of high- and low-suitable areas. Moreover, due to the transfer of a large number of rural laborers to the cities in recent years, the tension between people and land caused by the population explosion has led to the increasing impact of Pop on rice suitable areas and the relatively weakening of the impact of GDP on rice production interventions. The results can be used to provide scientific evidence for the management of rice cultivation and food production safety, with a view to reducing the impacts of climate change on agricultural production in the context of global climate change.

Climate Change Threatens Barringtonia racemosa: Conservation Insights from a MaxEnt Model

Barringtonia racemosa (L.) Spreng. (Lecythidaceae), a crucial species in mangrove ecosystems, is facing endangerment primarily due to habitat loss. To address this issue, research is imperative to identify suitable conservation habitats for the endangered B. racemosa within mangrove ecosystems. The utilization of the optimized Maximum Entropy (MaxEnt) model has been instrumental in predicting potential suitable regions based on global distribution points and environmental variables under current and future climates conditions. The study revealed that the potential distribution area of B. racemosa closely aligns with its existing range with an Area Under the Curve (AUC) greater than 0.95. The Jackknife, AUC, percent contribution (PC), and permutation importance (PI) tests were employed alongside the optimized MaxEnt model to examine the influence of environmental variables on the distribution of B. racemosa. The primary factors identified as significant predictors of B. racemosa distribution included the average temperature of the ocean surface (Temperature), average salinity of the ocean surface (Salinity), precipitation of the warmest quarter (Bio18), precipitation of the driest month (Bio14), seasonal variation coefficient of temperature (Bio4), and isothermality (Bio3). Currently, the habitat range of B. racemosa is predominantly found in tropical and subtropical coastal regions near the equator. The total suitable habitat area measures 246.03 km2, with high, medium, low, and unsuitable areas covering 3.90 km2, 8.57 km2, 16.94 km2, and 216.63 km2, respectively. These areas represent 1.58%, 3.48%, 6.88%, and 88.05% of the total habitat area, respectively. The potential distribution area of B. racemosa demonstrated significant variations under three climate scenarios (SSP126, SSP245, and SSP585), particularly in Asia, Africa, and Oceania. Both low and high suitable areas experienced a slight increase in distribution. In summary, the research suggests that B. racemosa primarily flourishes in coastal regions of tropical and subtropical areas near the equator, with temperature and precipitation playing a significant role in determining its natural range. This study offers important implications for the preservation and control of B. racemosa amidst habitat degradation and climate change threats. Through a comprehensive understanding of the specific habitat needs of B. racemosa and the implementation of focused conservation measures, efforts can be made to stabilize and rejuvenate its populations in their natural environment.

Current and future invasion risk of tomato red spider mite under climate change.

Tomato red spider mite Tetranychus evansi Baker and Pritchard (Acari: Tetranychidae) is a phytophagous pest that causes severe damage to Solanaceous plants worldwide, resulting in significant economic losses. In this study, the maximum entropy model was used to predict the potential current (1970-2000) and future (2021-2060) global distribution of the species based on its past occurrence records and high-resolution environmental data. The results showed that the mean values of the area under the curve were all >0.96, indicating that the model performed well. The three bioclimatic variables with the highest contributions were the coldest quarterly mean temperature (bio11), coldest monthly minimum temperature (bio6), and annual precipitation (bio12). A wide range of suitable areas was found across continents except Antarctica, both currently and in the future, with a much larger distribution area in South America, Africa, and Oceania (Australia), dominated by moderately and low suitable areas. A comparison of current and future suitable areas reveals a general trend of north expansion and increasing expansion over time. This study provides information for the prevention and management of this pest mite in the future.

Predicting the current and future suitable distribution range of Trilocha varians (Walker, 1855) (Lepidoptera: Bombycidae) in China.

Trilocha varians is one of the major pests of Ficus spp. Based on 19 bioclimatic variables provided by the Worldclim, our study analysed the suitable distribution areas of T. varians under current and future climate changes (SSP1-2.6, SSP2-4.5, SSP5-8.5) for two periods (the 2050s and 2090s) using the maximum entropy algorithm (MaxEnt) model. Key environmental variables affecting the geographic distribution of T. varians were also identified, and the changes in the area of suitable range under current and future climate changes were compared. The results showed that the key environmental variables affecting the distribution of T. varians were temperature and precipitation, comprising annual mean temperature (bio1), temperature seasonality (standard deviation × 100) (bio4), precipitation of driest month (bio14), and precipitation of driest quarter (bio17). Under the current climatic conditions, the suitable distribution area of T. varians is within the range of 92°13'E-122°08'E, 18°17'N-31°55'N. The current high, medium, and low suitable areas for T. varians predicted by the MaxEnt model are 14.00 × 104, 21.50 × 104, and 71.95 × 104 km2, of which the high suitable areas are mainly distributed in southern Guangdong, southwestern Guangxi, western Taiwan, Hong Kong, and Hainan. Under different future climatic conditions, some of the high, medium, and low suitability zones for T. varians increased and some decreased, but the mass centre did not migrate significantly. The Pearl River Basin is predicted to remain the main distribution area of T. varians.

An ideal location selection of electric vehicle charging stations: Employment of integrated analytical hierarchy process with geographical information system

Electric vehicle charging station identification is more essential in developing countries regions. Two major Middle Eastern capital cities are used to identify the EVCS which is important for environmentally friendly scenarios using the Analytical Hierarchy Process (AHP) and the Fuzzy-AHP (FAHP) in Baghdad (Iraq), and Riyadh (Saudi Arabia). With the help of GIS and multi-criteria decision analysis, suitable sites aimed at EVCSs are identified using twelve criteria. Based on the analysis very high suitable zones of Baghdad city have 179.99 km2 (AHP), and 162.61 km2 (FAHP), while Riyadh has 44.51 km2 (AHP), and 34.27 km2 (FAHP) respectively. Whereas, very low suitable areas for Baghdad have 552.47 km2 (AHP), and 1596.74 km2 (FAHP), while Riyadh has 518.43 km2 (AHP), and 463.59 km2 (FAHP) correspondingly. Karkh, Dora, Hurriya, Yarmouk, Binouk, and near the Baghdad international airport are more suitable for EVCSs establish while in Riyadh Dhahrat Laban, Ash Shifa, Al-Sina'yah, Tuwaiq, Al-Olaya and Al-Murabba is more Suitable for EVCSs. Green energy-based vehicle fuel is required for future development and reduction of fossil fuel use. Near the future, electric vehicles capture the maximum vehicle market, therefore identification of suitable sites for EVCSs plays a vital role in sustainable development.

GIS-based optimal site selection of the biogas facility installation using the Best-Worst Method

Renewable energy is currently a part of the energy supply. Türkiye, which has a significant potential in terms of renewable energy, offers various supports for biogas energy production. Biogas plants should be established at appropriate locations based on their legal requirements and efficiency. In this study, the application of the Best Worst Method (BWM) and Geographic Information System (GIS) integration for determining suitable locations for biogas plant installation in Türkiye, is presented. First, a suitable region for facilities was determined in a nationwide study. Subsequently, six criteria were determined for the selection of appropriate locations in line with the opinions of experts in this region. By overlay analysis using a GIS software, six criteria were combined using weight values and a site selection suitability map was generated. This map was divided into four classes as unsuitable, low suitability, moderate suitability and high suitability. When the spatial distribution of the suitable areas for the establishment of a biogas facility was examined, it was determined that the high suitability areas were 19931 ha (7.17%), the moderate suitability areas were 22805 ha (8.20%), the low suitability areas were 18300 ha (6.58%), and the unsuitable areas were 2786 ha (1%). The restricted area in this study were 219519 ha (77.04%). In this study, the site selection process was carefully planned and local factors, regulations and environmental impacts were taken into consideration. Correct site selection for biogas plants ensures efficient, environmentally friendly and economically sustainable operation of the plant.

Predicting potential distributions of Monochamus saltuarius, a novel insect vector of pine wilt disease in China

Monochamus saltuarius Gebler was first identified as a new vector of pine wilt disease in Northeast China in 2018, and monitoring of M. saltuarius has become a key strategy to prevent and control the disease in this region. However, the potential distributions of M. saltuarius in China are unclear. In this study, we clarified bioclimatic environmental variables affecting the distribution of M. saltuarius, predicted the geographically suitable habitats of M. saltuarius in current and future climate conditions, and determined changes in the spatial pattern of a suitable distribution area of M. saltuarius under current and future climate conditions. This is the first study to use the optimized maximum entropy model and ArcGIS to accurately predict suitable geographical areas for M. saltuarius based on different climatic conditions in China. and the average area under the receiver operating characteristic curve reached 0.954 ± 0.0024. Of the 32 bioclimatic variables, temperature seasonality, precipitation of wettest month, precipitation seasonality, maximum temperature of the warmest month, and elevation played significant roles in determining the potential distribution of M. saltuarius, with contribution rates to the model of 32.1, 31.8, 11.5, 7.5, and 6.5%, respectively. Under the current climate scenario, the predicted suitable areas for M. saltuarius were mainly at latitudes north of 33° in China, and larger suitable areas were mainly distributed in Northeast China and North China, with areas of 87.04 × 104 and 73.15 × 104 km2, respectively. Using future climatic scenarios SSP126 and SSP585, the predicted suitable areas of M. saltuarius will continue to expand from that of 2040, 2070, and 2100, with highly and moderately suitable areas showing larger increasing trends but low suitable distribution areas will decrease to varying degrees. The potential suitable areas of M. saltuarius may increase greatly in Northwest, Central, and Eastern China. This study provides important scientific theoretical knowledge for effectively controlling and preventing M. saltuarius and pine wilt disease in northern China.

Land Use Suitability Model for Grapevine (Vitis vinifera L.) Cultivation Using the Best Worst Method: A Case Study from Ankara/Türkiye

The product of grapes with the highest added value is wine. Wine grapes play an important role in the evaluation of barren lands, where no other plants generally grow. Viticulture in Türkiye is generally conducted on small areas of agricultural land. In order to develop viticulture, it is important to determine suitable areas. This study presents a model for assessing land suitability for cultivation of grapevines (Vitis vinifera L.) in the Ankara region (Türkiye). The aim is to provide a spatial decision support system based on geographic information system multi-criteria assessment, taking into account the perspectives of expert agricultural engineers and local product growers. In this study, 11 criteria were evaluated to determine the most suitable locations for grapevine cultivation. The best worst method was used to calculate the weights of the determined evaluation criteria. When the spatial distribution of the areas suitable for grapevine cultivation was examined from the resulting map produced, it was seen that 1879.29 km2 (7%) of highly suitability areas, 5062.03 km2 (20%) of medium suitability areas, 4706.20 km2 (18%) of low suitability areas, and 8355.36 km2 (33%) of unsuitable areas were detected. According to the results obtained, the southern parts of the study area are more suitable for grapevine cultivation. This study will be an important and useful regional guide for agricultural land use planning and the cultivation of grapevines.

Maxent Modeling for Predicting the Potential Geographical Distribution of Castanopsis carlesii under Various Climate Change Scenarios in China

Castanopsis carlesii (Hemsl.) Hayata. 1917 is an established subtropical evergreen broad-leaved tree species with rapid growth rates and a strong plasticity to environmental changes. It is widely distributed in East Asia; however, it is unclear how climate change influences the distribution of this tree species. Based on 210 valid occurrence records and 10 environmental variables, we used maximum entropy model (Maxent) to predict its potential geographical distribution under present and three future climate scenarios (SSP126, SSP245 and SSP585) in both the 2050s and 2070s, and determined the influence of climate on the distribution of C. carlesii. The area under the curve (AUC) value of the simulated training and the test were 0.949 and 0.920, respectively, indicating an excellent forecast. The main climatic factors affecting the distribution of C. carlesii are mainly precipitation, especially that of the driest month (Bio14, 75.5%), and annual precipitation (Bio12, 14.3%); its total contribution rate is 89.8%. However, the impact of average mean temperature is lesser in comparison (Bio1, 5.7%). According to the present-day predictions, C. carlesii has a suitable habitat of 208.66 × 104 km2 across most of the tropical and subtropical regions south of the Yangtze River. The medium and high suitability areas are mainly in Taiwan, Fujian, Jiangxi, Guangdong, Hainan and Guangxi Provinces. With the climate projected to warm in the future, the distribution area of C. carlesii exhibited a tendency of northward expansion along the Qinling–Huaihe line, mainly manifested as the increase in low and medium suitable areas. The area of high-suitable areas decreased significantly under the three climate scenarios both for the 2050s and 2070s, and only a few areas showed contraction of suitable areas. Therefore, expansion areas can be used for cultivation or introduction trials, while contraction areas require enhanced preservation and collection of genetic resources. Our findings provide a theoretical basis for formulating the adaptation and protection strategies to cope with future climate change as well as theoretical guidance for the introduction, cultivation and sustainable development of C. carlesii.

Impact of Climate Change on Paddy Farming in the Village Tank Cascade Systems of Sri Lanka

Consequences of global climate change are predicted to increase risks to crop production in the future. However, the possible broader impact of climate change on social-ecological systems still needs to be evaluated. Therefore, the present study focuses on one such globally important agricultural social-ecological system referred to as the Village Tank Cascade System (VTCS) in the dry zone of Sri Lanka. The VTCS has considerable potential to withstand seasonal climate variability mainly through continuous supply of water by the village tank storage throughout the year. The current study aimed to investigate trends of climate variability and possible impacts on paddy production in the North and North-central VTCS zone. Observed and projected rainfall and temperature data were analysed to evaluate the past variability trends (1970 to 2020) and model future (up to 2100) scenarios of climate variability and trends. Long-term observed rainfall and temperature data (1946 to 2020) were analysed to identify possible anomalies. The Maximum Entropy (MaxEnt) model has been used to predict the situation of future paddy farming (2050 and 2070) under two climate scenarios (RCP4.5 and RCP8.5) of the Intergovernmental Panel on Climate Change (IPCC). Six variables that would affect paddy growth and yield quality were used alongside the average monthly rainfall and temperature of two Global Climate Models (MIROC5 and MPI-ESM-LR). Climate suitability for two paddy cultivation seasons (Yala and Maha) were predicted for current and future climate scenarios. The findings revealed that observed and projected climate changes show considerable deviation of expected rainfall and temperature trends across the VTCS zone. Temperature exhibits warming of approximately 1.0 °C during the declared Global Warming Period (1970 to 2020) in the study area. In addition, there is a trend of significant warming by 0.02 °C/year, RCP4.5 and 0.03 °C/year, RCP8.5 from 1950 to 2100. Rainfall (1970–2020) shows high interannual variability but trends were not significant and less discernible. However, long-term projected rainfall data (1950–2100) analysis detected a significant (p = 0) upward trend (2.0 mm/year, RCP4.5 and 2.9 mm/year, RCP8.5), which is expected to continue up to the end of this century. Further, the study revealed some shifts in temperature towards higher values and positive anomalies in rainfall affecting seasonality and the likelihood of more extreme occurrences in the future, especially during the Maha cultivation season. The MaxEnt model predicts the following under future climate scenarios: (i) spatio-temporal shifts (conversions) in climate suitability for paddy farming in the VTCS zone; (ii) substantial low and moderate suitability areas that are currently suitable will remain unchanged; (iii) up to 96% of highly suitable and 38% of moderately suitable paddy growing areas in the VTCS zone will be at risk due to a decline in future climate suitability; and (iv) expansion of lower suitability areas by approximately 22% to 37%, due to conversion from moderate suitability areas. The study provides evidence that the continuous warming trend with increasing variability in rainfall and shifting seasonality could increase the vulnerability of future paddy farming in the VTCS. Thus, findings of this study will help planners to make more targeted solutions to improve adaptive capacity and regain the resilience to adjust the paddy farming pattern to deal with predicted climate variability and change.