Potential Distribution Area Research Articles

Prediction of the potential distribution area of Glycyrrhiza inflata in China using a MaxEnt model

Glycyrrhiza inflata Batalin is an important medical plant of the genus Glycyrrhiza. It is one of the key protected plants in China, distributed in the desert areas of southern Xinjiang and Dunhuang of Gansu Province. It has a strong resistance to drought, heat, and salt stresses, and plays a pivotal role in sand fixtion in desert areas. In this study, based on 157 valid distribution records and eight environmental factors including climate factors and altitude, the potential distribution area of G. inflata in the last glacial maximum, middle Holocen, modern, and future (2050) times in China were predicted, using the optimized MaxEnt model and ArcGis 10.2 software. The results showed that the predicted distribution area was highly consistent with the current distribution range, and the area under the receiver operating characteristic (AUC) curve was 0.986, indicating that the prediction performance was excellent. The key climatic factors affecting the distribution were precipitation in December and the average annual precipitation. Meanwhile, the suitable area of G. inflata in modern times was 1,831,026 km2, mainly distributed in Turpan-Hami Basin, Tarim Basin, and Dunhuang of Gansu Province, with Lop Nur Town of Xinjiang as the distribution center. In 2050, the potential suitable area forG. inflata in China will be 1,808,090 km2, 250,970 km2 of which will be highly suitable, which is 150,600 km2 smaller than that in modern times, with a reduction rate of 60.0%. Therefore, there is a trend of great reduction in the suitable area of G. inflata. From the last glaciation maximum to the middle Holocene, the geographical distribution center shifted to the southwest margin of the Kumtag Desert, Xinjiang, then later continued to shift to the southwest. This study will provide a basis for understanding the origin and evolution of G. inflata, developing conservation strategies to minimize the impacts of environment change, and utilizing plant resource.

Possible Change in Distribution Areas of Abies in Kastamonu due to Global Climate Change

Aim of the study: In the process of global climate change (GCC), the migration mechanism needed especially for forest trees must be provided by humans. For this purpose, contrary to the previous studies, detailed studies to be carried out on small areas are needed. 
 Area of study: In the present study carried out in Kastamonu Regional Directorate of Forestry, which performs the highest level of wood production in Türkiye, it was aimed to specify the actual distribution areas of the Abies and the change in their suitable distribution areas due to GCC. 
 Material and methods: In this study, besides the existing distribution areas and the potential future distribution areas, also the suitable distribution areas were determined by using SSP 126, SSP 370, and SSP 585 scenarios for the years 2040, 2070, and 2100 for Abies at Kastamonu. 
 Main results: The results achieved there showed that, depending on the results of climate change, distribution areas of Abies populations would change in the future and this change would be in form of an increase in general. 
 Research highlights: This species (Abies) seems incapable of keeping up with such changes without human intervention. Thus, considering the study results, it is recommended to make necessary amendments to the forest management plans.

Potential impacts of climate change on the geographic distribution of Achillea eriophora DC., a medicinal species endemic to Iran in southwestern Asia.

Climate change is considered to rank among the most important global issues affecting species' geographic distributions and biodiversity. Understanding effects of climate change on species can enhance conservation efficacy. In this study, we applied ecological niche modeling (ENM) using maximum entropy (MaxEnt) approaches to predict the potential geographic distribution of Achillea eriophora DC., a medicinal plant species to Iran in southwestern Asia, under current and future climate scenarios. We evaluated potential distributional areas of the species, under two shared socioeconomic pathways (SSP2-4.5 and SSP5-8.5) for the period 2041-2060. Most current potential suitable areas were identified for A. eriophora in montane regions. Our results anticipated that the potential distribution of A. eriophora will expand geographically toward higher elevations and northward. However, the species is expected to experience relatively high losses of suitability in its actual habitats under future climate scenarios. Consequently, we recommend regional-to-national conservation action plans for A. eriophora in its natural habitats.

Potential habitat areas and priority protected areas of Tilia amurensis Rupr in China under the context of climate change.

Tilia amurensis Rupr (T. amurensis) is one endangered and national class II key protected wild plant in China. It has ornamental, material, economic, edible and medicinal values. At present, the resources of T. amurensis are decreasing, and the prediction of the distribution of its potential habitat in China can provide a theoretical basis for the cultivation and rational management of this species. In this study, the R language was used to evaluate 358 distribution records and 38 environment variables. The MaxEnt model was used to predict the potential distribution areas of T. amurensis under the current and future climate scenarios. The dominant environmental factors affecting the distribution of T. amurensis were analyzed and the Marxan model was used to plan the priority protected areas of this species. The results showed that Bio18, Slope, Elev, Bio1, Bio9 and Bio2 were the dominant environmental factors affecting the distribution of T. amurensis. Under the future climatic scenarios, the potential suitable areas for T. amurensis will mainly distribute in the Northeast China, the total suitable area will reduce compared with the current climate scenarios, and the general trend of the centroid of suitable habitat will be towards higher latitudes. The SPF value of the best plan obtained from the priority conservation area planning was 1.1, the BLM value was 127,616, and the priority conservation area was about 57.61×104 km2. The results suggested that climate, soil and topographic factors jointly affected the potential geographical distribution of T. amurensis, and climate and topographic factors had greater influence than soil factors. The total suitable area of T. amurensis in China under different climate scenarios in the future will decrease, so more effective protection should be actively adopted.

Beyond the present: How climate change is relevant to pest risk analysis

AbstractClimate change is widely recognized as a critical global challenge with far‐reaching consequences. It affects pest species by altering their population dynamics, actual and potential distribution areas, as well as interactions with their hosts and natural enemies. Climate change thus has potentially important implications for multiple areas of the pest risk analysis (PRA) process. The importance of including climate change in PRA may vary depending on the climatic context of the PRA area in relation to the speed of climate change. If climatic changes within the time horizon of interest are minimal, their potential impact on pest risk is reduced accordingly. For PRAs in a changing climate, we need to be concerned with how future climates could alter our assessment of the risks currently posed by each pest species. While climate can influence the distribution and abundance of pests and hosts alike, its significance will vary depending on the situation. The inclusion of climate change within a PRA also presents challenges. The dynamic nature of climate change, with its complex interactions and uncertainties, can make it difficult to predict and assess the future risks posed by pests accurately. Uncertainties related to future predictions may be much greater than the potential effects associated with climate change and species’ responses to it. This paper outlines examples of the effects of climate change on hosts and different groups of pests, including invertebrates, pathogens, weeds and vector species. The aim is to review the opportunities and challenges of incorporating climate change into PRA, offering insights for a variety of stakeholders including policymakers on this topic.

Identifikasi Penyebaran Bencana Longsor Di Kecamatan Sentani Kota, Kabupaten Jayapura

Landslides are natural disasters that can result in loss of life and property. Therefore, it is necessary to carry out inventory research on areas prone to landslides. The model applied to determine the point of distribution of landslide disasters and areas of potential distribution of landslide disasters is a qualitative descriptive spatial method. Several factors that cause landslides are geology, rock properties, stratigraphy, geological structure, level of weathering and seismicity, climate, rainfall, thick soil, solum. , slope topography, vegetation density and human land use. The results of the analysis show that in Jayaura Regency, Sentani District, there are 3 classes of landslide hazard levels, namely not vulnerable, somewhat vulnerable, quite vulnerable, and vulnerable. In general, Jayapura Regency, Sentani sub-district, is quite prone to the spread of landslides, but there are three sub-districts that are vulnerable, namely Hinekombe sub-district, Sentani village, Bart, Sentani sub-district, Sereh village in the middle and Sentani sub-district, Tollan village, 
 
 

Predicting potential occurrence of Adelges tsugae (Homoptera: Adelgidae) on a global scale under climate change scenarios using maximum entropy model

Invasive alien species pose grave threats to natural ecosystems and human society. The hemlock woolly adelgid (HWA; Adelges tsugae Annand) is an invasive alien species in several countries, causing severe damage to forest mainly composed of hemlock and spruce. This study employed a maximum entropy model to predict the global potential occurrence areas of HWA based on worldwide HWA occurrence data and four bioclimatic variables: mean diurnal range (BIO2), mean temperature of the wettest quarter (BIO8), mean temperature of the coldest quarter (BIO11), and annual precipitation (BIO12). Future climate change scenarios were used to assess the effects of climate change on HWA distribution. The developed model showed good predictive performance for HWA occurrence (AUC:0.992, F1 score: 0.876), with BIO11 being the most influential factor for HWA occurrence, followed by BIO12. The model identified high-risk areas in North America and eastern Asia including Korea, the Himalayan regions, central and western Europe, Oceania including southeastern Australia and New Zealand, and western part of South America. Additionally, most distribution areas of hemlock trees were in areas where HWA could potentially occur. According to climate change, the model predicted a northward shift in the average latitude of the predicted potential distribution areas showing that the range of HWA may potentially expand even into subarctic regions, where the occurrence probability is currently lower than that of temperate regions. The findings of this study provide valuable insights into the potential occurrence and invasion risk of HWA in current and future climates and emphasize the importance of proactive measures to monitor and manage its spread.

Mapping the potential distribution of Asian elephants: Implications for conservation and human–elephant conflict mitigation in South and Southeast Asia

Asian elephants play a pivotal role in their ecosystem. Understanding the potential distribution area of this species is vital for effective conservation efforts and mitigation of human-elephant conflicts. In this study, we used the maximum entropy to simulate the potential distribution area of Asian elephants across South and Southeast Asia, leveraging Maximum Entropy (MaxEnt) and presence data sourced from the Global Biodiversity Information Facility (GBIF). The analysis revealed that the potential distribution area of Asian elephants spans 530,418 km2 (10.59% of the study area), with significant potential distribution areas observed in Indonesia (136,890 km2) and Malaysia (119,497 km2). Vegetation type emerged as the dominant environmental factor influencing model outcomes, encompassing aspects such as broadleaved evergreen tree coverage, broadleaved deciduous closed tree coverage and EVI. The potential distribution area of Asian elephants overlaps with regions inhabited by 55.25 million people, with 6.07 million people residing in highly suitable habitats. India and Malaysia have high potential for human-elephant conflict (HEC) due to the high number of people living in potential and highly suitable habitats for elephants. Bangladesh and Nepal, on the other hand, have fewer people living in these habitats suitable for elephants, but they face relatively high human population density in these areas.

Current and future distribution of Eucalyptus globulus under changing climate in Ethiopia: implications for forest management

Eucalyptus globulus is a species endemic to southeastern Australia. It has naturalized non-native ranges in other parts of Australia, Europe, Africa, and the western United States. This study is the first of its kind in Ethiopia to model and map the spatiotemporal distribution of the species using species distribution models (SDMs). A total of 874 occurrence records were used from the online Global Biodiversity Information Facility (GBIF) database and field observation. Three environmental variables, including terrain, climate, and soil were used to predict the species’ distribution. The terrain, climate, and soil raster grids were resampled to a 200-meter resolution. The Global Circulation Model (GCM) HadGEM3-GC3.1 was used to extract future climate data. This GCM has a good match between the atmospheric and oceanic components showing little drift in its surface climate. Besides, it has the best coverage of Africa. Three climate change scenarios (SSPs 1-2.6, SSPs 2-4.5, and SSPs 5-8.5) were used for predicting suitable habitat of the species. The jackknife test was chosen to assess the importance of each environmental predictor variable. The model’s performance was evaluated using the Area under the Curve (AUC) of the Receiver Operating Characteristic (ROC) curve. The model had excellent predictive performance with an average AUC of 0.94. Altitude, rooting conditions, slope, dry-month precipitation, and temperature seasonality are the most important environmental factors in shaping E. globulus distribution. Ethiopian highlands are predicted to be more suitable to the species, but the increase in temperature seasonality may reduce suitable habitat under the high-forcing climate change scenario. Climate change is expected to create more suitable habitats for eucalyptus in the future which may encourage plantations in potential distribution areas. Consequently, ensuring long-term forest health necessitates robust management systems prioritizing native trees and responsible grower or farmer practices.

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.

Prediction of the potential distribution area of Spodoptera frugiperda and its parasitic wasp, Trichogramma pretiosum.

Spodoptera frugiperda is a migratory agricultural pest with fast-spreading speed, long migration distance, and wide host range, which seriously threatens the safety of economic crops. To predict the trends of S. frugiperda and its parasitoid wasp Trichogramma pretiosum in their habitats under current and future climatic conditions, based on MaxEnt model and geographic distribution data of their historical occurrence, we project the feasibility of introducing T. pretiosum to control S. frugiperda by evaluating on their potential global distribution. The results show that, under the current greenhouse gasconcentration, the potential distribution area of S. frugiperda is concentrated in 50° N-30° S, with a total area of 1.74 × 106 km2 , and the potential distribution area of T. pretiosum in the whole world is 2.91 × 106 km2 . The suitable areas of T. pretiosum cover almost all the suitable areas of S. frugiperda, which indicates that T. pretiosum can be introduced to control S. frugiperda. The results of this study can provide a theoretical basis for the monitoring and early warning of S. frugiperda and the use of T. pretiosum to control S. frugiperda.

Current and Future Distribution of Camellia sinensis in China Estimated by MaxEnt

Tea (Camellia sinensis L.) is an important cash crop. In the context of climate change, analyzing the current distribution of tea trees and climate change environmental variables to predict the potential distribution area of tea trees in the future can help decision-makers make appropriate planting decisions and promote sustainable management. In this study, an optimized MaxEnt model was used to predict the limiting factors of tea tree growth and distribution under current and future climate change scenarios. The climate soil mixing model [area under the curve (AUC) = 0.934] performed excellently. The results showed that precipitation, temperature, slope, and soil factors all affected the distribution of suitable habitats for tea trees. Compared with the current distribution area of tea trees, under three shared socioeconomic pathways (SSP126, SSP245, and SSP585), the area of highly suitable habitats for tea trees will expand, especially in 2061–2080 and 2081–2100 years, and the suitable area will extend overall to the north of China, indicating that future climate change may create more new suitable habitats for tea production, especially in Shandong, Shaanxi, Guizhou, and Yunnan provinces. This study will provide important scientific insights for tea production decision-making, tea garden location selection, and future adaptation methods, and will help in the cultivation and transplantation of tea trees in the future.

Modeling the Effects of Climate Change on the Current and Future Potential Distribution of Berberis vulgaris L. with Machine Learning

Species of the Berberis genus, which are widely distributed naturally throughout the world, are cultivated and used for various purposes such as food, medicinal applications, and manufacturing dyes. Model-based machine learning is a language for specifying models, allowing the definition of a model using concise code, and enabling the automatic creation of software that implements the specified model. Maximum entropy (MaxEnt 3.4.1) is an algorithm used to model the appropriate distribution of species across geographical regions and is based on the species distribution model that is frequently also used in modeling the current and future potential distribution areas of plant species. Therefore, this study was conducted to estimate the current and future potential distribution areas of Berberis vulgaris in Türkiye for the periods 2041–2060 and 2081–2100, according to the SSP2 4.5 and SSP5 8.5 scenarios based on the IPSL-CM6A-LR climate change model. For this purpose, the coordinates obtained in the WGS 84 coordinate system were marked using the 5 m high spatial resolution Google Satellite Hybrid base maps, which are readily available in the 3.10.4 QGIS program, the current version of QGIS (Quantum GIS). The CM6A-LR climate model, the latest version of the IPSL climate models, was used to predict the species’ future distribution area. The area showed a high correlation with the points representing B. vulgaris, which is generally distributed in the Mediterranean and the central and eastern Black Sea regions of Türkiye, and the very suitable areas encompassed 45,413.82 km2. However, when the SSP2 4.5 scenario was considered for the period 2041–2060, the areas very suitable for Berberis vulgaris comprised 59,120.05 km2, and in the SSP2 4.5 scenario, very suitable areas were found to encompass 56,730.46 km2 in the 2081–2100 period. Considering the SSP5 8.5 scenario for the period 2041–2060, the area most suitable for the B. vulgaris species is 66,670.39 km2. In the SSP5 8.5 scenario, very suitable areas were found to cover 20,108.29 km2 in the 2081–2100 period. Careful consideration of both the potential positive and negative impacts of climate change is essential, and these should be regarded as opportunities to implement appropriate adaptation strategies. The necessary conditions for the continued existence and sustainability of B. vulgaris—that is, areas with ecological niche potential—have been determined.

Predicting the Potential Distribution Areas of the Asian Redtail Catfi sh (Hemibagrus wyckioides Fang and Chaux, 1949) in the Chao Phraya River, Thailand, using Maximum Entropy Modelling

Hemibagrus wyckioides is recognized as an economically important freshwater fi sh in Thailand. However, there are no available comprehensive data regarding the geographic distribution and habitat suitability of H. wyckioides in Thailand. In addition, its natural population has tended to continuously decrease. This study aimed to predict the suitable distribution areas of H. wyckioides in the Chao Phraya River, Thailand, using the maximum entropy (MaxEnt) algorithm based on climatic factors, including 11 temperature and 8 precipitation indices from the WorldClim database. Model performance was evaluated by the area under the receiver operating characteristic curve (AUC). The jackknife test was used to assess the contribution of each variable to the model. The results revealed that the MaxEnt model performed acceptably well, with an AUC value of 0.939, representing excellent accuracy in predicting the appropriate distribution areas of H. wyckioides in the Chao Phraya River. The potential distribution areas of H. wyckioides were observed mostly along the Chao Phraya River in Sing Buri and Ang Thong Provinces. According to the results of the jackknife test, 11 climatic variables impacted the distribution of H. wyckioides. The annual mean temperature (BIO1), precipitation of driest month (BIO14), and annual temperature range (BIO7) were the most important infl uencing variables, with impact values of 53.5%, 15.9%, and 11.9%, respectively. Therefore, understanding the potential distribution areas can assist researchers in monitoring, management, and conservation activities or with the development of new natural protected areas of H. wyckioides in high-quality areas in the Chao Phraya River.

Following the trail of the grey brocket deer (Mazama gouazoubira) in Argentina: new locality records, activity patterns and habitat use

The brown brocket deer (Mazama gouazoubira) is a species of neotropical ungulate that inhabits several countries in South America. In Argentina, it is distributed in the northern portion of the country, while historical records do not mention it in the province of Mendoza. However, in the Categorization of Mammals of Argentina (2019), the NE of Mendoza is proposed as a potential distribution area of the species. In this work we confirm the presence of the brown brocket deer in the province of Mendoza (locality of Desaguadero - RAMSAR Site), and we also evaluate its activity patterns and habitat preferences. We established 1 km2 grids in three environments: salt flats, shrublands, and forests. A camera trap (n = 38) was placed in each grid, active for 55 days between October 2022 and April 2023 for fauna survey. In addition, NDVI values (Normalized Difference Vegetation Index) were calculated from LANDSAT-8 images as an estimator of vegetation cover for each grid. We obtained 25 independent records of 11 individuals (5 males and 6 females) from a sampling effort of 51,072 hours of camera operation (2,090 night/trap = 55 night * 38 camera). The males were individually identified based on the presence of antlers, their size, dimension and texture, while the females by their body size and gestation condition. In terms of activity patterns, we observed that these animals are most active in the afternoon (16 to 19 hs) and morning (8 to 9 hs), avoiding the moments of greatest solar radiation (Rayleigh-test r = 0.99, p < 0.001). NDVI was significantly different among the three environments (Chisq = 32.98; p < 0.001), with the forest having the highest vegetation cover. Finally, generalized linear models with binomial distribution were used to evaluate the effect of vegetation on the presence of brown brocket deer. We found that the higher the NDVI value, the higher the probability of presence of the deer (z = 2.27; p < 0.05). These results expand the distribution of the species and increase the diversity of mammals for Mendoza province, which generates added value to the planning of the proposed protected area for Desaguadero in the RAMSAR site Lagunas de Guanacache, Desaguadero y del Bebedero.

Dynamics of coastal land-based aquaculture pond in China and Southeast Asia from 1990 to 2020

The extensive expansion of coastal land-based aquaculture ponds (CLAP) has resulted in substantial wetland loss. To effectively monitor the dynamics of CLAP on a large scale, critical spatial information derived from continuous datasets is essential. Here, we generate the inaugural map depicting the changes in aquaculture pond coverage across the coastal regions both of China and Southeast Asia from 1990 to 2020 by utilizing the long time-series Landsat archive with an object-oriented hierarchical classification method. We extracted coastal water bodies using the Otsu algorithm and established a water inundation frequency index to eliminate interference from temporary water facilities. This process allowed us to identify potential distribution areas of aquaculture ponds. To precisely map the spatial distribution of CLAP within these identified areas, we employed an object-oriented K-nearest neighbor approach with spectral, geometric, and water index features as classification features. The cumulative coverage of CLAP in China and Southeast Asia reached 23,121 km2 by 2020, marking a net increase of 12,700 km2 since 1990. Notably, China, Indonesia, and Vietnam emerged as the primary contributors to these changes within our study area. Regions exhibiting dense aquaculture activities are predominantly concentrated in the northern region above 10 degrees latitude and along the eastern coastlines of various countries. This aquaculture pond map reserves fine spatial detail by effectively distinguishing drainage channels, rice seedling fields, and embankments surrounding aquaculture ponds. It serves as a valuable resource for guiding coastal resource management and environmental protection initiatives.

Geographical distribution of two major quarantine fruit flies (Bactrocera minax Enderlein and Bactrocera dorsalis Hendel) in Sichuan Basin based on four SDMs.

Both Bactrocera minax and Bactrocera dorsalis are phytophagous insects, and their larvae are latent feeders, which cause great damage and economic losses to agriculture production and trade. This study aimed to provide a scientific reference for researching and developing the feasible countermeasures against these two pests. Based on the distribution data of B. minax and B. dorsalis in China, obtained from the Chinese herbaria, investigation and literature. Four niche models (Garp, Bioclim, Domain, and Maxent) were used to analyze the key environmental factors affecting the distribution of both pests and to build prediction models of the potential distribution in Sichuan Basin. Combined with two statistical standards, area under the receiver operating characteristic curve (AUC) and Kappa, the validity of prediction models were analyzed and compared. The results show that: the average AUC values of the four models are all above 0.90, and the average Kappa values are all above 0.75, indicating that the four models are suitable for predicting the potential distribution area of B. minax and B.dorsalis. The annual range of temperature, the mean temperature in the driest quarter, the mean temperature in the warmest quarter, the annual precipitation, and the precipitation in driest month are the key environmental factors affecting the distribution of B. minax, while the mean diurnal temperature range, the mean temperature in the driest quarter, the seasonal temperature variations and the precipitation in driest month affect the potential distribution of B. dorsalis. The suitable areas for B. minax are mainly concentrated in the eastern of Sichuan Basin, while the suitable areas for B. dorsalis are concentrated in the southeastern. Except for the Bioclim model, the highly-suitable area for both pests predicted by the other three models are all greater than 15.94 × 104 km2 and the moderately-suitable areas are greater than 13.57 × 104 km2. In conclusion, the suitable areas for both pests in Sichuan Basin are quite wide. Therefore, the relevant authorities should be given strengthened monitoring of both pests, especially in areas with high incursion rates.

Global potential distribution of mangroves: Taking into account salt marsh interactions along latitudinal gradients

Mangrove is one of the most productive and sensitive ecosystems in the world. Due to the complexity and specificity of mangrove habitat, the development of mangrove is regulated by several factors. Species distribution models (SDMs) are effective tools to identify the potential habitats for establishing and regenerating the ecosystem. Such models usually include exclusively environmental factors. Nevertheless, recent studies have challenged this notion and highlight the importance of including biotic interactions. Both factors are necessary for a mechanistic understanding of the mangrove distribution in order to promote the protection and restoration of mangroves. Thus, we present a novel approach of combining environmental factors and interactions with salt marsh for projecting mangrove distributions at the global level and within latitudinal zones. To test the salt marsh interaction, we fit the MaxEnt model with two predicting sets: (1) environments only and (2) environments + salt marsh interaction index (SII). We found that both sets of models had good predictive ability, although the SII improved model performance slightly. Potential distribution areas of mangrove decrease with latitudes, and are controlled by biotic and abiotic factors. Temperature, precipitation and wind speed are generally critical at both global scale and ecotones along latitudes. SII is important on global scale, with a contribution of 5.9%, ranking 6th, and is particularly critical in the 10–30°S and 20–30°N zone. Interactions with salt marsh, including facilitation and competition, are shown to affect the distribution of mangroves at the zone of coastal ecotone, especially in the latitudinal range from 10° - 30°. The contribution of SII to mangrove distribution increases with latitudes due to the difference in the adaptive capacity of salt marsh plants and mangroves to environments. Totally, this study identified and quantified the effects of salt marsh on mangrove distribution by establishing the SII. The results not only facilitate to establish a more accurate mangrove distribution map, but also improve the efficiency of mangrove restoration by considering the salt marsh interaction in the mangrove management projects. In addition, the method of incorporating biotic interaction into SDMs through establish the biotic interaction index has contributed to the development of SDMs.

Effects of climate change on the distribution of Pinus chihuahuana and Pinus leiophylla: a proposal for the conservation of both species in Mexico

The use of distribution models is a tool used to solve biological and environmental problems. Geographic data andenvironmental variables were analyzed to test the hypothesis that the distribution of Pinus chihuahuana and Pinus leiophyllawill be maintained by 2050 and 2080 in Mexico. Records of both species and environmental variables for the period 1910-2009 and Global Circulation Models (GFDL-CM3 and CNRM-CM5) were used under two RCP 4.5 and 8.5 scenariosprojected to 2050 and 2080. The MaxEnt algorithm was used. The results were evaluated and validated using AUC, partialRoc and Z-statistic tests. The contribution of each variable in the models was determined using the Jackknife test. Themodels estimated a current potential distribution area for P. chihuahuana of 81,614.8 km² and 15,105.3 km² for P. leiophylla.The relevant variables in the current period for P. chihuahuana were Bio1, Bio6, Bio13 and Bio19, while in P. leiophylla theywere Bio1, Veget and Edaf. However, for the future period they were Bio1, Bio19 and Bio13 for P. chihuahuana, and Bio1,Bio14 and Bio4 for P. leiophylla. The CNRM-CM5 and GFDL-CM3 GCM projections estimated a reduction in the rangesof both species from 2080 onwards. Conservation areas of 79,078.12 km² for P. chihuahuana and 10,517.8 km² for P.leiophylla were estimated at the end of the century. Areas suitable for the conservation of P. chihuahuana (Chihuahua andDurango) and P. leiophylla (Michoacán) in Mexico were identified and proposed.

The impact of climate change on plant distribution and niche dynamics over the past 250 years in Switzerland

Herbarium specimens provide an irreplaceable source of historical plant distribution data, enabling analysis of changes in plant distribution spanning centuries. Most studies on plant distribution shifts focus on recent decades and rare species, especially along elevational gradients. We examined about 2000 historical herbarium specimens from the Botanical Garden of the University of Bern, representing 30 plant species from five Swiss lowland habitats (six species per habitat) dating back to 1768 and covering all Swiss cantons. All historical data were transcribed, georeferenced and then combined with current data resulting in about 170 000 plant records over 250 years. Combined with climatic data from the same period, we found that all habitats increased their potential distribution area with a significant gain in the semi-arid grasslands (+8.15 %, p-value = 0.031). On species level, 75 % of the selected species expanded their distribution, while 25 % of the species retracted. Despite these shifts, 90–99.6 % niche stability was observed between historical and current climatic niches across all species. Shifts in co-occurring species were specific to the species, not to the habitat. The consistent overlap in historical and current climatic niches suggest that distribution expansion is due to the growth of areas with suitable climates, pointing to climate change as a driving factor for plant distribution changes over the past 250 years.