Forecasting the effects of bioclimatic characteristics and climate change on the potential distribution of Colophospermum mopane in southern Africa using Maximum Entropy (Maxent)

Predicting suitable habitat for the endangered tree Ormosia microphylla in China

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

Assessment of suitable cultivation region for Pepino (Solanum muricatum) under different climatic conditions using the MaxEnt model and adaptability in the Qinghai-Tibet plateau

Pepino (Solanum muricatum), a member of the Solanaceae family originating from South America, is cultivated globally. However, the cultivation range and suitable habitat of Pepino have not been extensively studied, which hampers the further development of its cultivation industry. Therefore, we aimed at enrich and expand the planting scope of Pepino. Currently, the main cultivation areas of Pepino in China are the Yunnan-Guizhou Plateau and the Loess Plateau, where the altitude is above 1000 m. In this study, ArcGIS combined with the MaxEnt model was used for prediction, whose area under curve value was 0.949. The main climatic factors affecting the distribution of Pepino are temperature seasonality, annual means temperature, mean temperature of the coldest quarter, elevation, isothermality, and the climate factors, and their cumulative contribution rate of 87.6%. Pepino's main potential distribution areas are located in Yunnan-Guizhou Plateau, Yunnan Province, Hexi Corridor of Loess Plateau, and low altitude areas of Qinghai-Tibet Plateau. The main distribution ranges from 1000 to 2000 m above sea level, and the total suitable area accounts for 20.09% of China's total land area. The prediction results reveal an expanded potential area for Pepino, with no significant migration in the central region of the main potential distribution area by 2050 and 2070. No studies have been conducted on the open-area cultivation of Pepino in northern China. Our findings revealed that the yield and quality in the four experimental sites and final actual cultivation conditions were consistent with the predicted results of MaxEnt. The yiel d per plant in Xunhua and Minhe was significantly different from that in Xining, which was low, and that in Minhe was the highest. Overall, the fruit quality in the Xining region was the lowest among the three regions, which was related to the climatic differences in each region. These results align with the predicted outcomes, indicating that Xining is the least suitable area. Further, these data verify the accuracy of the prediction results. The climate data of the four regions were analyzed simultaneously to elucidate the influence of different climate conditions on the growth of Pepino. Our findings are of considerable significance for introducing characteristic horticultural crops in the Qinghai-Tibet Plateau and using the MaxEnt model to predict the cultivation range of crops.

Climate change decouples dominant tree species in African savannas

To understand how two dominant African savanna trees will continue to respond to climate changes, we examined their regeneration niche and adult tree distributions. Specifically, we wanted to (1) determine if distributional patterns were shifting, (2) predict future distributions under different climate change scenarios and (3) evaluate the realism of predicted future distributions. We randomly placed 40 grids into 6 strata across a climate gradient in the kingdom of Eswatini. Within these grids, we sampled adult and seedling marula (Scelerocarya birrea) and knobthorn (Senegalia nigrecens) trees and used the data to model their abundance. Next, we quantified shifts in distributional patterns (e.g., expansion or contraction) by measuring the current and projected areas of overlap between seedling and adult trees. Finally, we predicted future distributions of abundance based on predicted climate conditions. We found knobthorn seedlings within a small portion of the adult distribution, suggesting it was unlikely to track climate changes. Alternatively, finding marula seedlings on and beyond one edge of the adult distribution, suggested its range would shift toward cooler climates. Predicted future distributions suggest suitable climate for both species would transition out of savannas and into grasslands. Future projections (2041-2070) appeared consistent with observed distributions of marula, but knobthorn predictions were unrealistic given the lack of evidence for regeneration outside of its current range. The idiosyncratic responses of these species to climate change are likely to decouple these keystone structures in the coming decades and are likely to have considerable cascading effects including the potential rearrangement of faunal communities.

Predicting the changes in suitable habitats for six common woody species in Central Asia

Climate change over the past decades has significantly altered global hydrothermal conditions and caused an evident shift in species distribution. Predicting species distribution patterns and identifying their influencing factors will be essential in developing coping strategies to prevent species extirpation and extinction. Yet, environmental factors affecting the distribution of woody species in Central Asia remain largely unknown. Here, I used the MaxEnt model to predict the current distributions and future distribution under three SSP-RCP scenarios of six common woody species in Central Asia. The results indicated a good performance of the MaxEnt model. Precipitation of driest month and annual mean temperature were the dominant factors affecting species distribution. For the species with wide ecological niches, i.e., Acer negundo and Rosa chinensis, the suitable areas showed an evident expansion trend under future scenarios. In addition, a trend toward higher elevation was found for the species that grew at high altitudes (1600-3200 m). However, the average elevation of suitable area for A. negundo and R. chinensis firstly increased but then decreased under future scenarios. Even though the areas with high species diversity increased from 0.59% under the current situation to 0.82% and 0.81% under ssp245 in 2021-2040 and 2041-2060, respectively, species diversity showed an apparent loss in parts of the northwest and southeast areas under ssp370 and ssp585. This study can guide susceptible habitat protections under climate change.

Climate change threatens the distribution of major woody species and ecosystem services provision in southern Africa

In southern Africa, woody vegetation provides essential ecological, regulation, and cultural ecosystem services (ES), yet many species and ecosystems are increasingly threatened by climate change and land-use transformations. We investigated the effect of climate change on the distribution of eight species in 18 countries in southern Africa, covering 36% of the continent. We proposed a loser/winner ranking of the species based on the changes in land climatic suitability within their historical distribution and future gains and losses of suitable areas. We interpreted these findings in terms of changes in key ES (timber, food, and energy) provision and identified hotspots of ES provision decline. We used species presence data from the Global Biodiversity Information Facility, climatic data from the AfriClim dataset, and the MaxEnt algorithm to project the changes in species-specific land climatic suitability. Among the eight investigated species, the baseline suitability range of Mopane (Colophosperm mopane) was least affected by climate change. At the same time, the area of its future distribution was projected to double, rendering it a regional winner. Another two species, manketti (Schinziophyton rautanenii) and leadwood (Combretum imberbe) showed high future gains too; however, the impact on their baseline suitability range differed between the climatic scenarios. The baseline range of African rosewood (Guibourtia coleosperma) declined entirely, and the future gains were negligible, rendering the species a regional loser. The effect of climate change was particularly severe on timber-producing species (four out of eight species), while species providing food (four species) and energy (four species) were affected less. Our projections portrayed distinct hotspot and coldspot areas, where climatic suitability for multiple species was concurrently projected to decline or persist. This assessment can inform spatially targeted adaptation and conservation actions and strategies, which are currently lacking in many African regions.

Assessment of Climate Change and Land Use Effects on Water Lily (Nymphaea L.) Habitat Suitability in South America

Many aquatic species have restricted dispersal capabilities, making them the most vulnerable organisms to climate change and land use change patterns. These factors deplete Nymphaea species’ suitable habitats, threatening their populations and survival. In addition, the species are poorly documented, which may indicate how scarce they are or will become. Members of Nymphaea are ecologically important as well as having cultural and economic value, making them of conservation interest. Therefore, using the maximum entropy (MaxEnt) approach, climatic variables, land use, and presence points were modeled for seven Nymphaea species in South America, using three general circulation models (CCSM4, HADGEM2-AO, and MIROC5) and in two representative concentration pathways (RCPs 4.5 and 8.5) and two scenarios (2050 and 2070). Our results indicated that mean diurnal range (bio2), precipitation of the wettest month (bio13), temperature seasonality (bio15), and land use (dom_lu) were the main influencing factors. For all species, suitable areas were concentrated east of Brazil, and they were variable in northern parts of the continent. Besides, inconsistent expansion and contraction of suitable habitats were noticed among the species. For example, N. amazonum, N. rudgeana, and N. lasiophylla future habitat expansions declined and habitat contraction increased, while for N. ampla and N. jamesoniana, both future habitat expansion and contraction increased, and for N. pulchella and N. rudgeana it varied in the RCPs. Moreover, the largest projected suitable habitats were projected outside protected areas, characterized by high human impacts, despite our analysis indicating no significant change between protected and unprotected areas in suitable habitat change. Finally, understanding how climate change and land use affect species distribution is critical to developing conservation measures for aquatic species.

Mapping the habitat suitability of Ottelia species in Africa

Understanding the influence of environmental covariates on plant distribution is critical, especially for aquatic plant species. Climate change is likely to alter the distribution of aquatic species. However, knowledge of this change on the burden of aquatic macroorganisms is often fraught with difficulty. Ottelia, a model genus for studying the evolution of the aquatic family Hydrocharitaceae, is mainly distributed in slow-flowing creeks, rivers, or lakes throughout pantropical regions in the world. Due to recent rapid climate changes, natural Ottelia populations have declined significantly. By modeling the effects of climate change on the distribution of Ottelia species and assessing the degree of niche similarity, we sought to identify high suitability regions and help formulate conservation strategies. The models use known background points to determine how environmental covariates vary spatially and produce continental maps of the distribution of the Ottelia species in Africa. Additionally, we estimated the possible influences of the optimistic and extreme pessimistic representative concentration pathways scenarios RCP 4.5 and RCP 8.5 for the 2050s. Our results show that the distinct distribution patterns of studied Ottelia species were influenced by topography (elevation) and climate (e.g., mean temperature of driest quarter, annual precipitation, and precipitation of the driest month). While there is a lack of accord in defining the limiting factors for the distribution of Ottelia species, it is clear that water-temperature conditions have promising effects when kept within optimal ranges. We also note that climate change will impact Ottelia by accelerating fragmentation and habitat loss. The assessment of niche overlap revealed that Ottelia cylindrica and O . verdickii had slightly more similar niches than the other Ottelia species. The present findings identify the need to enhance conservation efforts to safeguard natural Ottelia populations and provide a theoretical basis for the distribution of various Ottelia species in Africa.

Promoting the Development of Astragalus mongholicus Bunge Industry in Guyang County (China) Based on MaxEnt and Remote Sensing

To provide high-quality Astragalus mongholicus Bunge to domestic and foreign markets and maintain sustainable development of the A. mongholicus industry, Firstly, we evaluated the impact of environmental factors and planting areas on the A. mongholicus industry. The maximum entropy method (MaxEnt) was utilized to simulate the suitability distribution of A. mongholicus and establish the relationship between the active component contents of A. mongholicus and ecological factors through linear regression analysis. The random forest algorithm was subsequently used to perform feature selection and classification extraction on Sentinel-2 imagery covering the study area. Furthermore, the planting, processing, and sales of A. mongholicus in Guyang County were investigated, and the roles of stakeholders in the value chains were analyzed. The results demonstrated that precipitation of the warmest quarter, minimum temperature of the coldest month, standard deviation of seasonal temperature changes, range of mean annual temperature, and mean diurnal range [mean of monthly (max temp - min temp)] were the five environmental variables that contributed the most to the growth of A. mongholicus. The most influential factor on the distribution of high-quality A. mongholicus was the mean temperature of the coldest quarter. The classification results of image features showed that the planting areas of A. mongholicus was consistent with the suitable planting areas predicted by MaxEnt, which can provide data support to the relevant departments for the macro development of the A. mongholicus industry. In the production of A. mongholicus, 10 value chains were constructed, and the study demonstrated that the behavior of stakeholders, target markets, and the selected planting area had a significant impact on the quality of A. mongholicus.

Spatial Distribution and Climate Warming Impact on Abies kawakamii Forest on a Subtropical Island

Species distribution modeling (SDM) is currently the primary tool for predicting suitable habitats for species. In this study, we used Abies kawakamii, a species endemic to Taiwan. Being the only Abies species distributed in high mountains, it acts as an ecological indicator on the subtropical island. We analyzed a vegetation map derived from remote sensing and ground surveys using SDM. The actual distribution of A. kawakamii in Taiwan has a total area of 16,857 ha distributed at an altitude of 2700–3600 m, and it often forms a monodominant forest at 3100–3600 m with the higher altitude edge as a forest line. Exploring the potential distribution of A. kawakamii through MaxEnt showed that the suitable habitat was 73,151 ha under the current climate. Under the scenarios of temperature increases of 0.5, 1.0, 1.5, and 2.0 °C, suitable habitat for A. kawakamii will gradually decrease to 70.2%, 47.1%, 30.2%, and 10.0% of this area, respectively, indicating that A. kawakamii will greatly decline under these climate warming scenarios. Fire burning disturbance may be the most significant damage to A. kawakamii at present. Although A. kawakamii has been protected by conservation areas and its natural regeneration is in good condition, it rarely has the opportunity to migrate upwards during climate warming. We suggest that in the future, research on the natural regeneration and artificial restoration of A. kawakamii should be emphasized, especially in the forest line ecotone.

Estimating the Potential Impacts of Climate Change on the Spatial Distribution of Garuga forrestii, an Endemic Species in China

Understanding how species have adapted and responded to past climate provides insights into the present geographical distribution and may improve predictions of how biotic communities will respond to future climate change. Therefore, estimating the distribution and potentially suitable habitats is essential for conserving sensitive species such as Garuga forrestii W.W.Sm., a tree species endemic to China. The potential climatic zones of G. forrestii were modelled in MaxEnt software using 24 geographic points and nine environmental variables for the current and future (2050 and 2070) conditions under two climate representative concentration pathways (RCP4.5 and RCP8.5) scenarios. The resulting ecological niche models (ENMs) demonstrated adequate internal assessment metrics, with all AUC and TSS values being >0.79 and a pROC of >1.534. Our results also showed that the distribution of G. forrestii was primarily influenced by temperature seasonality (% contribution = 12%), elevation (% contribution = 27.5%), and precipitation of the wettest month (% contribution = 35.6%). Our findings also indicated that G. forrestii might occupy an area of 309,516.2 km2 in southwestern China. We note that the species has a potential distribution in three provinces, including Yunnan, Sichuan, and Guangxi. A significant decline in species range is observed under the future worst case of high-emissions scenario (RCP8.5), with about 19.5% and 20% in 2050 and 2070, respectively. Similarly, higher elevations shift northward to southern parts of Sichuan province in 2050 and 2070. Thus, this study helps highlight the vulnerability of the species, response to future climate and provides an insight to assess habitat suitability for conservation management.