Future Potential Distribution Research Articles

Assessment of Suitable Habitat of the Demoiselle Crane (Anthropoides virgo) in the Wake of Climate Change: A Study of Its Wintering Refugees in Pakistan

The inevitable impacts of climate change have reverberated across ecosystems and caused substantial global biodiversity loss. Climate-induced habitat loss has contributed to range shifts at both species and community levels. Given the importance of identifying suitable habitats for at-risk species, it is imperative to assess potential current and future distributions, and to understand influential environmental factors. Like many species, the Demoiselle crane is not immune to climatic pressures. Khyber Pakhtunkhwa and Balochistan provinces in Pakistan are known wintering grounds for this species. Given that Pakistan is among the top five countries facing devastating effects of climate change, this study sought to conduct species distribution modeling under climate change using data collected during 4 years of field surveys. We developed a Maximum Entropy distribution model to predict the current and projected future distribution of the species across the study area. Future habitat projections for 2050 and 2070 were carried out using two representative concentration pathways (RCP 4.5 and RCP 8.5) under three global circulation models, including HADGEM2-AO, BCC-CSM1-1, and CCSM4. The most influential factors shaping Demoiselle Crane habitat suitability included the temperature seasonality, annual mean temperature, terrain ruggedness index, and human population density, all of which contributed significantly to the suitability (81.3%). The model identified 35% of the study area as moderately suitable (134,068 km2) and highly suitable (27,911 km2) habitat for the species under current climatic conditions. Under changing climate scenarios, our model predicted a major loss of the species’ current suitable habitat, with shrinkage and shift towards western–central areas along the Pakistan–Afghanistan boarder. The RCP 8.5, which is the extreme climate change scenario, portrays particularly severe consequences, with habitat losses reaching 65% in 2050 and 85% in 2070. This comprehensive study provides useful insights into the Demoiselle Crane habitat’s current and future dynamics in Pakistan.

Potential current and future distribution for Aedes aegypti and Aedes albopictus in Colombia: important disease vectors

AbstractInvasive mosquitoes, Aedes aegypti (African) and Aedes albopictus (Asian), serve as global vectors for diseases such as dengue, Zika, and chikungunya, and they are currently present in Colombia. Consequently, the aim of this study was to assess the potential geographic distribution of these A. aegypti and A. albopictus vectors under both present and future environmental conditions in Colombia. To achieve this, a dataset was compiled using global records for each species, with those from Colombia being used for model validation. These records, in conjunction with layers of bioclimatic variables, were incorporated into ecological niche models. Predictions of potential distribution were made with the Maxent algorithm, using the Wallace EcoMod application for current conditions and the Java MaxEnt software for future projections, which represented three climate change scenarios (SSP245, SSP370, and SSP585) for two time periods (2041–2060 and 2081–2100). Additionally, niche overlap was calculated, and the suitable habitat range and population at risk in Colombia were quantified for current predictions. It is suggested that both species share ideal areas in the country with an overlap of 0.85, covering over 70% of the country's territory and reaching altitudes higher than 2,500 m, potentially affecting at least 45% of the population. In the future for both species it is estimated that, with increasing temperatures, the potential distribution could decrease, but they could invade areas with altitudes above 3,500 m (colder). It is concluded that, currently, A. aegypti and A. albopictus could have similar geographic distribution in Colombia and that, in the following years, climate change could lead to latitudinal and altitudinal variations in the distribution areas of these vectors.

Predicting the current and future distributions of Pinus merkusii in Southeast Asia under climate change

Abstract. Sulton MN, Aurina DM, Muhammad F, Fadzilah FPA, Hanun Z, Indrawan M, Budiharta S, Supriatna J, Nursamsi I, Setyawan AD. 2024. Predicting the current and future distributions of Pinus merkusii in Southeast Asia under climate change. Biodiversitas 25: 1135-1143. Pinus merkusii Jungh. Et de Vriese is a native pine species of Southeast Asia with primary distribution in Indonesia, especially in the mountainous areas of northern Sumatra. The P. merkusii has an important role in the forest ecosystem including maintaining ecosystem stability, reducing soil erosion, and providing habitat for various types of flora and fauna. Climate change is expected to affect the growth, development and distribution of plants, so this study aims to predicting the current dan future distribution of P. merkusii in Southeast Asia under climate change. We used Maxent and Geographic Information System (GIS), which incorporated bioclimatic, edaphic, and UVB radiation variables, to predict the suitable areas of P. merkusii under current and future climate scenarios (RCP 2.6, RCP 4.5, RCP 6.0, and RCP 8.5) and three time periods (2030, 2050, and 2080). Our findings indicate that compared to current, there will be an increase of suitable areas for P. merkusii in 2030 across all climate scenarios with RCPs 2.6, 4.5, 6.0, and 8.5 represent 9.53%, 9.66%, 9.73%, and 9.91% of Southeast Asia terrestrial area, respectively. In 2050, such increase will continue under all climate scenarios with RCP 4.5 has the largest proportion of suitable area (10.39%). However, in 2080, the suitable areas are likely to reduce compared with 2050 with RCPs 2.6, 4.5, 6.0, and 8.5 have a percentage of 9.21%, 9.69%, 10.29%, and 9.81%, respectively. Our predictions showed that there will be a geographical shift of suitable area of P. merkusii into higher elevation and latitude, migrating east and northeast. Our findings about the potential future distribution of P. merkusii might be used as a reference for cultivation according to predicted suitable areas in the future.

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.

Will Dalbergia species survive climate change? Predicting the potential future distribution of threatened species in Madagascar

Many species of Dalbergia, the source of highly prized rosewood, are threatened with extinction, a situation compounded by climate change. Accurate estimates of how suitable habitat will be impacted by global change are needed to inform their sustainable management. We selected five commercially exploited species endemic to humid eastern Madagascar (D. baronii, D. louvelii, D. maritima, D. normandii, and D. orientalis) to explore the potential value of species distribution modeling for understanding factors influencing their current distributions and estimating future patterns of suitable habitat, using MaxEnt and locality information for 715 taxonomically and spatially validated occurrences. Eight bioclimatic variables were used for modeling; projections were made under three scenarios for climate change and two for CO2 emissions. The distribution of each of the five species is primarily influenced by precipitation seasonality. Their potential geographical range is predicted to decrease by 2100 (-5% to -33%) under the optimistic CO2 scenario (RCP 2.6) except for a slight expansion of D. normandii (+2%), and by -14% to -58% under the pessimistic scenario (RCP 8.5). Our results show that suitable habitat will likely decrease with climate change, even within protected areas. They provide valuable information for future application of IUCN Red List criterion A to exploited species with fragmented distributions, targeting ex-situ conservation and management, and guiding restoration, reforestation, and other actions to establish and reinforce Dalbergia populations in areas where they are more likely to persist during climate change over the present century and beyond.

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.

Plant pathogen infection risk and climate change in the Nordic and Baltic countries

Climate change and global warming are already affecting food production, and the impact is predicted to intensify in the future. Previous studies have been based on global data and have provided general information about climate change effects on food production. Regional high-resolution data are, however, needed to evaluate the effect of future scenarios of climate change to support strategic and tactical planning to safeguard food production. Here, we provide results on the future potential distribution range of fungal plant pathogens in the Nordic and Baltic countries. This is done using regional climate model data at 12.5 km horizontal resolution. The temperature dependent infection risk and species richness are calculated using data for 80 plant pathogens. Within the region the studied pathogens will in most cases thrive more and be more abundant in a warmer climate; leading to a longer infection risk season and the introduction of new pathogens. This applies to all emissions scenarios, even though the effects are stronger with high emissions. Our results indicate that plant diseases will increase, and this will negatively affect crop production and food security.

Distribution and conservation of the narrow sub-endemic shrub, Lonicera paradoxa in Pamir-Alay, Central Asia

Abstract. Daminova N, Nosirov S, Akbarov F, Tojibaev K, Temirov E. 2024. Distribution and conservation of the narrow sub-endemic shrub, Lonicera paradoxa in Pamir-Alay, Central Asia. Biodiversitas 25: 439-448. Lonicera paradoxa Pojark. (Lonicera ser. Alpigenae Pojark. ex A.Byalt) is a shrub with a geographically limited range. This species is included in the national red book lists of Uzbekistan, Kyrgyzstan, and Tajikistan and is considered one of the rare species in danger of extinction in nature. The species grows in a significant elevation from 1600 to 3200 m on the Northern slopes of the Alay Range, Central Asia. In this study, we investigated the geographic distribution of L. paradoxa based on scientific literature, herbarium data collections, and field surveys. We then modeled the current and potential future geographic distribution using Maxent. We also conducted a propagation study for its conservation under laboratory and greenhouse conditions. Our fieldwork in 2021-2022 found new records of L. paradoxa in Uzbekistan and Kyrgyzstan. We calculated the Extent of Occurrence (EOO) and Area of Occupancy (AOO) of the species, which were 5.08 km2 (VU) and 28 km2 (EN), respectively. Therefore, based on the IUCN Red List and Criteria, we recommend the conservation status of L. paradoxa as endangered (EN) in categories B2 ab (ii, iii, iv) + D. Our modeling prediction suggested that compared to the current, suitable habitat of L. paradoxa to reduce significantly in the future with very suitable habitats are expected to expand to the south and high mountain areas. For the first time, the conservation measures of L. paradoxa were carried out at the Tashkent Botanical Garden. The conducted research made it possible to preserve L. paradoxa in ex-situ conditions. The results of this research can be helpful in determining and planning measures for the protection of L. paradoxa in the territory of the Kyrgyz and Tajikistan Republics, both now and in the future.

Current and future potential distribution of Culex (Melanoconion) (Diptera: Culicidae) of public health interest in the Neotropics.

Anthropogenic activities are altering ecosystem stability and climate worldwide, which is disturbing and shifting arbovirus vector distributions. Although the overall geographic range of some epidemiologically important species is recognized, the spatiotemporal variation for other species in the context of climate change remains poorly understood. Here we predict the current potential distribution of 9 species of Culex (Melanoconion) based on an ecological niche modeling (ENM) approach and assess spatiotemporal variation in future climate change in the Neotropics. The most important environmental predictors were the mean temperature of the warmest season (27 °C), precipitation during the driest month (50 mm), and precipitation during the warmest season (>200 mm). The best current model for each species was transferred to the future general circulation model IPSL-CM6A-LR, using 2 shared socioeconomic pathway scenarios (ssp1-2.6, ssp5-8.5). Under both scenarios of climatic change, an expansion of suitable areas can be observed followed by a strong reduction for the medium-long future under the worst scenario. The multivariate environmental similarity surface analysis indicated future novel climates outside the current range. However, none of the species would occur in those areas. Even if many challenges remain in improving methods for forecasting species responses to global climate change and arbovirus transmission, ENM has strong potential to be applied to the geographic characterization of these systems. Our study can be used for the monitoring of Culex (Melanoconion) species populations and their associated arboviruses, contributing to develop region-specific public health surveillance programs.

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.

Prediction of suitable areas and division of key monitoring zones for Solidago canadensis in Guizhou Province, China

Comprehending invasive alien species’ potential habitat area and spread trend are of great importance for effective prevention and control strategy and prevention of spread. However, previous studies have mainly been based on large regional scales (national or global level). Research on the smaller regional scale of ecologically fragile karst makes the prevention and control measures more feasible and targeted, it is of great significance to protect mountainous region species diversity and maintain national nature reserves. In this study, based on the distribution point data of Solidago canadensis in Guizhou Province and environmental factors, Pearson correlation analysis and contribution rate analysis of environmental factors were carried out by SPSS and knife cutting method, and current and future potential distribution vector maps were obtained by MaxEnt model, and then imported into ArcGIS for reclassification and visualization. The results show that, (1) the main drivers of S canadensis distribution were precipitation changes and human activities, the total contribution rate more than 70%; (2) S canadensis occurrence probability initially increased, and then decreased with increased precipitation variables, and increased rapidly initially, then gradually with increasing human footprint; (3) under current climate conditions, S canadensis suitable area is 8.13 × 104 km2, with the highly suitable area concentrated in Guiyang, east of Bijie, Zunyi, Anshun and Qiannan. Under climate conditions of the 2050s, the suitable area drops slightly to 8.00 × 104 km2, mainly in the west and north of Zunyi, Anshun and other areas reduced. Under climate conditions of the 2070s, the suitable area expands to 8.31 × 104 km2, it expands in the adjacent areas of Anshun, Qiannan and Qianxinan and the junction of Zunyi, Tongren, Qiannan and Qiandongnan. And move toward the south within the study area; (4) finally, using the spatial optimization software ZONATION, according to the landscape loss proportion curve, the key monitoring area of 79,857 km2 was obtained, including a primary monitoring area mainly distributed in Guiyang, east of Bijie, northeast of Anshun and northwest of Qiannan, a secondary monitoring area mainly outside the primary monitoring area, and a third-level monitoring area widely distributed in Zunyi, Tongren, Qiannan, west of Qiandongnan and Anshun and east of Bijie. Linking our results with this specie’s invasive power, we thus recommended to increase the prevention and control sites in the first-level monitoring area, and continue to pay attention to the risk of the southward spread of this species.

Modelling current and future potential distribution of medicinal orchids in Darjeeling eastern Himalaya

Modelling current and future potential distribution of medicinal orchids in Darjeeling eastern Himalaya

Projecting the current and potential future distribution of New Zealand’s invasive sturnids

AbstractInvasive species threaten native ecosystems, the economy and human health. Improved understanding of an invasive species’ ecological niche, and whether it has differentiated in the invasive compared to the native range, will enable better prediction of areas at risk of future invasions. Here, we characterise the ecological niche of the common myna (Acridotheres tristis) and common starling (Sturnus vulgaris), in their native range and in Aotearoa New Zealand, where they were introduced over 140 years ago. Common myna and common starling are two of the most invasive bird species in the world and are agricultural pests, competitors to native fauna and may act as disease vectors. Using biologically justified environmental variables and occurrence data, we construct ecological niche models (ENMs) using five algorithms. Based on the ENM algorithm with highest transferability, we identify key environmental variables to compare the niches of the two species in New Zealand and the native range, and between the two species in New Zealand. For both species, we find no evidence of niche divergence between New Zealand and their native range despite their long invasion history. However, we do find evidence for niche differences between the two species in New Zealand. Our future suitable habitat predictions suggest little range expansion of the already-widespread starlings in New Zealand, but large areas at risk of future myna invasion in New Zealand’s South Island. Our results support ongoing management of myna populations, especially in the South Island where the Cook strait may already provide some barrier to dispersal.

Multispectral remote sensing approach of predicting the potential distribution and evaluating the current spread of water hyacinth (Eichhornia crassipes)

The water hyacinth is categorized among the world’s top ten worst invasive plant species of aquatic ecosystems. This study assessed changes in the spatiotemporal distributions of the water hyacinth in Lake Koka and Ziway of the Upper Awash River basin during the peak growth season of the plant. Household questionnaires and key informant interviews along with Landsat images for 2013, 2017, and 2021 were collected to identify the past, present, and future potential distributions of the invasive plant in the two lakes. Household surveys and key informant interviews were prepared using the Kobo Toolbox which monitors data collection online. A total number of 413 households were sampled and the data were analyzed through descriptive statistics. For Landsat images, a supervised classification technique was applied to classify the land use classes using the maximum likelihood algorithm. The survey results showed increased water hyacinth expansion in the area since the year 2011. The water hyacinth expansion affected 285 households’ livelihoods by invading 69.0% of their farmlands which caused 97.6% food scarcity in the study districts. The results of the Landsat image indicated that the water hyacinth invasion in Lake Koka occupied 1.48% in 2013, and this increased to 7.13% in 2021, while the water body decreased from 75.94 to 69.90%, respectively. However, the area of the other vegetation is nearly identical between the years 2013–2021. Likewise, water hyacinth covered 4.66% of Lake Ziway in 2013, and this was raised to 8.42% in 2021. At Lake Ziway water hyacinth invasion affected the area of other vegetation coverage as it decreased from 16.19 to 10.67% but the area of the water body remained almost the same during the years. Between 2013 and 2025, the amount of water hyacinths increased in both Lake Koka and Lake Ziway. According to LULC data, the water hyacinth's rate of spread was 0.56% in Lake Koka and 0.95% in Lake Ziway. The results of this study revealed the signals of LULC change due to water hyacinth invasion in the Upper Awash Basin which is considered an important aspect for future water resources planning and management.

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).

MaxEnt model strategies to studying current and future potential land suitability dynamics of wheat, soybean and rice cultivation under climatic change scenarios in East Asia.

Climate change and variability are projected to alter the geographic suitability of lands for crops cultivation. Accurately predicting changes in the potential current and future land suitability distribution dynamics of wheat (Triticum aestivum), soybean (Glycine max) and rice (Oryza sativa) crops due to climate change scenarios is critical to adapting and mitigating the impacts of bioclimatic changes, and plays a significant role in securing food security in East Asia region. This study compiled large datasets of wheat, soybean and rice occurrence locations from GBIF and 19 bioclimatic variables obtained from the WorldClim database that affect crops growth. We recognized potential future suitable distribution regions for crops under the one socioeconomic pathway, (SSP585) for 2021-2040 and 2041-2060, using the MaxEnt model. The accuracy of the MaxEnt was highly significant with mean AUC values ranging from 0.833 to 0.882 for all models evaluated. The jackknife test revealed that for wheat, Bio4 and Bio12 contributed 17.6% and 12.6%, for soybean Bio10 and Bio12 contributed 15.6% and 49.5%, while for rice Bio12 and Bio14 contributed 12.9% and 36.0% to the MaxEnt model. In addition, cultivation aptitude for wheat, soybean, and rice increased in southeast China, North Korea, South Korea, and Japan, while decreasing in Mongolia and northwest China. Climate change is expected to increase the high land suitability for wheat, soybean, and rice in East Asia. Simulation results indicate an average decrease of unsuitable areas of -98.5%, -41.2% and -36.3% for wheat, soybean and rice from 2060 than that of current land suitability. In contrast, the high land suitable for wheat, soybean and rice cultivation is projected to increase by 75.1%, 68.5% and 81.9% from 2060 as compared with current. The findings of this study are of utmost importance in the East Asia region as they present an opportunity for policy makers to develop appropriate adaptation and mitigation strategies required to sustain crops distribution under future climates. Although the risks of wheat, soybean and rice cultivation may be significantly higher in the future because of high temperatures, heat waves, and droughts caused by climate change.

Prediction of future potential distributions of Pinus yunnanensis varieties under climate change

Pinus yunnanensis Franch. (Pinaceae) is an important endemic tree species that serves as a critical constituent of the forest ecosystems and plays a significant role in forestry economic production in southwest China. P. yunnanensis comprises three varieties: var. yunnanensis, var. pygmaea and var. tenuifolia, with significant variation in traits, such as height and leaf size. This study aims to characterize the habitat conditions of the three varieties and predict their potential future distributions by employing MaxEnt model. Temperature seasonality (BIO4) emerged as the most influential factor affecting the distribution of var. yunnanensis; isothermally (BIO3) stands out as the most critical factor for the distribution of var. pygmaea; whereas mean annual fire occurrence (MAF) had the greatest impact on the distribution of var. tenuifolia. Under future climate conditions, the highly and moderately suitable habitats for all the three varieties are projected to decrease, while the lowly suitable habitats are projected to increase. The distribution centroids of all the three varieties are anticipated to shift to higher latitudes. Our study characterized the habitat conditions and predicted the potential future distribution of the three Pinus yunnanensis varieties, which could help the conservation and utilization of Pinus yunnanensis varieties.

An Endemic Vascular Plant Species for Türkiye, Ferulago Humilis Boiss., and Its Potential Distribution Areas

Turkey is expected to be affected considerably in future adverse climatic conditions. Plant species are one of the most vulnerable to these climatic changes. In this study, we aimed to investigate current and future potential distribution areas of Ferulago humilis Boiss., which is an endemic vascular plant species for Turkey, using CMIP5 projected to year 2070. For this purpose, we obtained occurence data (presence-only) from Global Biodiversity Information Facility (GBIF). Regarding bioclimatic data we used WorldClim dataset with 10 km2 resolution. Using both plant occurrence and bioclimatic data, we performed species distribution modelling analysis. We used two methods namely Boosted Regression Trees (BRT) and Random Forest (RF). Additionally, we used bootstrapping method as partitioning resampling for all analysis. Our analysis has showed that potential distribution areas of the species has slightly changed for the future projection. The species movement is towards slightly upwards as higher latitudes. We believe that our study shows the importance and relevance of the endemic species in the scope of species distribution models for plant conservation topics.

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.

Modeling potential distribution and above-ground biomass of Scots pine (Pinus sylvestris L.) forests in the Inner Anatolian Region, Türkiye.

Scots pine (Pinus sylvestris L.) holds a substantial position as a tree species designated for biomass energy within European forests, covering a significant part of Türkiye's forests. We used the machine learning technique, namely, maximum entropy (MaxEnt), to estimate the suitable areas for Scots pine and to investigate its potential future distribution under various climate change scenarios in Inner Anatolian Region, Türkiye. The distribution data of Scots pine was utilized, and a set of 20 variables was chosen from spectral, topographic, and bioclimatic datasets to train the MaxEnt model. A map depicting the potential distribution of Scots pine in the area was generated, and alterations in its spatial distribution under SSP2-4.5 and SSP5-8.5 climate change scenarios were predicted. The results showed that the most effective factors for the distribution of Scots pine in the region were normalized difference vegetation index (NDVI), Red band of the imagery, and Bio19 variables, and the contribution percentages were 45.6%, 18.5%, and 18.1%, respectively. Current conditions have indicated that 81.11% of the region is not suitable for Scots pine. Highly suitable areas for Scots pine constituted 0.88% of the total area in the east and southeast parts of the region. Considering the SSP2-4.5 and SSP5-8.5 scenarios, it has been determined that there may be a partial increase in highly suitable areas. The above-ground biomass (AGB) data generated based on potential distribution areas were predicted between 0.04 and 168.76 t ha-1, and the areas with dense biomass over 120 t ha-1 were identified in the west, north, and northeast parts of the region. While actual AGB of Scots pine was 6.92 MT, its potential AGB was estimated 125.93 MT in total area. The difference may well be attributed to the wide potential distribution of Scots pine stands in the area apart from the current forest lands. Nevertheless, this research contributes to the holistic management of forests and provides substantial values for formulating well-suited silvicultural interventions, developing sustainable forest management strategies, and furthering research aimed at estimating biomass reserves.