Precipitation Of Wettest Month Research Articles

Habitat suitability modeling of mosquito species in Faiyum Governorate, Egypt, using GIS

BackgroundThe life cycle and geographic range of mosquitoes are profoundly influenced by weather conditions. In Faiyum Governorate, Egypt, researchers looked at over 42 different mosquito breeding areas in the wild. Culex pipiens, Culex antennatus, Culex perexiguus, Culex theileri, Anopheles multicolor, Anopheles sergentii, Ochlerotatus caspius, Culiseta longiareolata, and Uranotaenia unguiculata, were all represented among the collected mosquito larvae. Using Maxent, we identified the most important bioclimatic factors affecting habitat appropriateness for each species. In order to determine the link between a species’ habitat appropriateness and bioclimatic factors, the computer builds response curves for each bioclimatic factor. All species risk maps, species richness maps, and individual species maps were generated with a Software that build interactive web maps (ArcGIS 10.3).ResultsEach mosquito species’ range was impacted by four bioclimatic factors. The most influential factors were those linked to temperature and precipitation. Culex antennatus, Culex perexiguus, Culex pipiens, and Ochlerotatus caspius responded best to temperature-related factors. Precipitation of wettest month (bio 13) was effective in four species (Anopheles multicolor, Culex antennatus, Culex perexiguus, and Culex pipiens).ConclusionAreas in the north and west of El-Fayoum district (Zawyat El-Karadsah, Beni-Saleh, and Monshat Abd-Allah), in Tamiya in Kafr Mahfouz, in the south of Abshway, especially in Tobhar, in the north of Atssa, in the south and center of Sinnuris have been identified as high-risk areas and more susceptible to mosquito-borne diseases.

Climate-driven mitochondrial selection in lacertid lizards.

The mitochondrion, which is an intracellular organelle responsible for most of the energy-producing pathways, can have its genome targeted for climate-driven selection. However, climate-driven mitochondrial selection remains a sparsely studied area in reptiles. Here, we reported the complete mitochondrial genome sequence of a lacertid lizard (Takydromus intermedius) and used mitogenomes from 54 species of lacertid lizards to study their phylogenetic relationships and to identify the mitochondrial genes under positive selection by climate. The length of the complete mitochondrial genome sequence of T. intermedius was 17,713 bp, which was within the range of lengths (17,224-18,943) ever reported for Takydromus species. The arrangement of mitochondrial genes in T. intermedius was the same as in other congeneric species. The 54 lacertid species could be divided into three geographically and climatically different clades. We identified three mitochondrial genes (ATP6, ATP8, and ND3) under positive selection by climate, and found that isothermality, temperature seasonality, precipitation of wettest month, and precipitation seasonality were the most important climatic variables contributing to the gene selection.

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

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

Potential Global Distribution of Paracoccus marginatus, under Climate Change Conditions, Using MaxEnt.

The papaya mealybug, Paracoccus marginatus, is an invasive pest species found all over the world. It is native to Mexico and Central America, but is now present in more than 50 countries and regions, seriously threatening the economic viability of the agricultural and forestry industry. In the current study, the global potential distribution of P. marginatus was predicted under current and future climatic conditions using MaxEnt. The results of the model assessment indicated that the area under the curve of the receiver operating characteristic ( ROC-AUC) was 0.949, while the TSS value was 0.820. The results also showed that the three variables with the greatest impact on the model were min temperature of coldest month (bio6), precipitation of wettest month (bio13), and precipitation of coldest quarter (bio19), with corresponding contributions of 46.8%, 31.1%, and 13.1%, respectively. The results indicated that the highly suitable areas were mainly located in tropical and subtropical regions, including South America, southern North America, Central America, Central Africa, Australia, the Indian subcontinent, and Southeast Asia. Under four climate scenarios in the 2050s and 2070s, the area of suitability will change very little. Moreover, the results showed that the area of suitable areas in 2070s increased under all four climate scenarios compared to the current climate. In contrast, the area of suitable habitat increases from the current to the 2050s under the SSP370 and SSP585 climate scenarios. The current study could provide a reference framework for the future control and management of papaya mealybug and other invasive species.

Modelling habitat suitability for Moringa oleifera and Moringa stenopetala under current and future climate change scenarios

Moringa oleifera Lam and Moringa stenopetala (Baker f.) Cufod are being widely promoted as multipurpose trees across the tropics for their nutritional, medicinal and soil health benefits. Different parts of these species are edible, have therapeutic values and their seeds are used for water purification. Although the two species are similar in many ways, they have contrasting distributions. However, their current promotion is not guided by adequate knowledge of the suitability of the target areas. Information is also scanty on the suitability of habitats for these species under the current and future climate change scenarios. Therefore, the objective of this study was to predict the habitat suitability of M. oleifera and M. stenopetala under current and future climate change scenarios using an ensemble of models assuming four shared socio-economic pathways, namely, SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 for 2050 and 2070. The results suggest that areas that are highly suitable for M. oleifera will increase by 0.1% and 3.2% under SSP1-2.6 to SSP5-8.5 by 2050, respectively. By 2070, the area suitable for M. oleifera would likely decrease by 5.4 and 10.6% under SSP1-2.6 and SSP5-8.5 scenarios, respectively. The habitat that is highly suitable for M. stenopetala was predicted to increase by 85–98% under SSP3-7.0 and SSP5-8.5 scenarios by 2050 and by 2070, while suitable areas could increase by up to 143.6% under SSP5-8.5. The most influential bioclimatic variables for both species were mean diurnal temperature range, mean temperature of driest quarter, precipitation of wettest month, and isothermality. Additionally, soil pH, elevation and water holding capacity were influential variables in the distribution of M. oleifera, while soil pH, soil salinity and slope were influential in M. stenopetala distribution. This study has provided baseline information on the current distribution and possible future habitat suitability, which will be helpful to guide formulation of good policies and practices for promoting Moringa species outside their current range.

Predicting the Potential Geographical Distribution of Rhodiola L. in China under Climate Change Scenarios

Rhodiola L. has high nutritional and medicinal value. Little is known about the properties of its habitat distribution and the important eco-environmental factors shaping its suitability. Rhodiola coccinea (Royle) Boriss., Rhodiola gelida Schrenk, Rhodiola kirilowii (Regel) Maxim., and Rhodiola quadrifida (Pall.) Fisch. et Mey., which are National Grade II Protected Plants, were selected for this research. Based on high-resolution environmental data for the past, current, and future climate scenarios, we modeled the suitable habitat for four species by MaxEnt, evaluated the importance of environmental factors in shaping their distribution, and identified distribution shifts under climate change scenarios. The results indicate that the growth distribution of R. coccinea, R. kirilowii, and R. quadrifida is most affected by bio10 (mean temperature of warmest quarter), bio3 (isothermality), and bio12 (annual precipitation), whereas that of R. gelida is most affected by bio8 (mean temperature of wettest quarter), bio13 (precipitation of wettest month), and bio16 (precipitation of wettest quarter). Under the current climate scenario, R. coccinea and R. quadrifida are primarily distributed in Tibet, eastern Qinghai, Sichuan, northern Yunnan, and southern Gansu in China, and according to the 2070 climate scenario, the suitable habitats for both species are expected to expand. On the other hand, the suitable habitats for R. gelida and R. kirilowii, which are primarily concentrated in southwestern Xinjiang, Tibet, eastern Qinghai, Sichuan, northern Yunnan, and southern Gansu in China, are projected to decrease under the 2070 climate scenario. Given these results, the four species included in our study urgently need to be subjected to targeted observation management to ensure the renewal of Rhodiola communities. In particular, R. gelida and R. kirilowii should be given more attention. This study provides a useful reference with valuable insights for developing effective management and conservation strategies for these four nationally protected plant species.

Prediction of the potentially suitable areas of Leonurus japonicus in China based on future climate change using the optimized MaxEnt model.

Leonurus japonicus Houtt. is a traditional Chinese medicinal plant with high medicinal and edible value. Wild L. japonicus resources have reduced dramatically in recent years. This study predicted the response of distribution range of L. japonicus to climate change in China, which provided scientific basis for the conservation and utilization. In this study, 489 occurrence points of L. japonicus were selected based on GIS technology and spThin package. The default parameters of MaxEnt model were adjusted by using ENMeva1 package of R environment, and the optimized MaxEnt model was used to analyze the distribution of L. japonicus. When the feature combination in the model parameters is hing and the regularization multiplier is 1.5, the MaxEnt model has a higher degree of optimization. With the AUC of 0.830, our model showed a good predictive performance. The results showed that L. japonicus were widely distributed in the current period. The maximum temperature of warmest month, the min temperature of coldest month, the precipitation of wettest month, the precipitation of driest month, and altitude were the main environmental factors affecting the distribution of L. japonicus. Under the three climate change scenarios, the suitable distribution area of L. japonicus will range shift to high latitudes, indicating that the distribution of L. japonicus has a strong response to climate change. The regional change rate is the lowest under the SSP126-2090s scenario and the highest under the SSP585-2090s scenario.

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

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

Epigenetic architecture of Pseudotaxus chienii: Revealing the synergistic effects of climate and soil variables.

Whether conifers can withstand environmental changes especially temperature fluctuations has been controversial. Epigenetic analysis may provide new perspectives for solving the issue. Pseudotaxus chienii is an endangered gymnosperm species endemic to China. In this study, we have examined the genetic and epigenetic variations in its natural populations aiming to disentangle the synergistic effects of climate and soil on its population (epi)genetic differentiation by using amplified fragment length polymorphism (AFLP) and methylation-sensitive AFLP (MSAP) techniques. We identified 23 AFLP and 26, 7, and 5 MSAP outliers in P. chienii. Twenty-one of the putative adaptive AFLP loci were found associated with climate and/or soil variables including precipitation, temperature, K, Fe, Zn, and Cu, whereas 21, 7, and 4 MSAP outliers were significantly related to precipitation of wettest month (Bio13), precipitation driest of month (Bio14), percent tree cover (PTC), and soil Fe, Mn, and Cu compositions. Total precipitation and precipitation in the driest seasons were the most influential factors for genetic and epigenetic variation, respectively. In addition, a high full-methylation level and a strong correlation between genetic and epigenetic variation were detected in P. chienii. Climate is found of greater importance than soil in shaping adaptive (epi)genetic differentiation, and the synergistic effects of climate and climate-soil variables were also observed. The identified climate and soil variables should be considered when applying ex situ conservation.

Spatial variability and climate response characteristics of chemical components of Tussilago farfara L.

Tussilago farfara L. is a typical habitat-dominated herbal medicine. In this work, for evaluating the effect of ecological environment on its quality, an integrated approach based on chemical composition and maximum entropy (MaxEnt) model was developed. 52 batches of T. farfara were collected by field survey from different origins in Gansu Province and their HPLC fingerprints were established. 19 common peaks were specified and subjected to principal component analysis and orthogonal partial least squares-discriminant analysis. The result indicated the quality varied with the origins and the common peaks 12, 6, 9, 14, 19, and 1 was the key to distinguish their quality. The MaxEnt model consisting of 205 occurrence records and 14 environmental variables was constructed and used to predict the potential distribution of T. farfara in Gansu Province. The prediction results showed that the current suitable habitat area of T. farfara was about 94,547.03 km2, accounting for 22.2% of the total area of Gansu Province, and showed a trend of increasing and then decreasing with time under future climate scenarios. Moreover, the dominant factors affecting its distribution were specified as min temperature of coldest month, precipitation of wettest month, precipitation seasonality, mean diurnal range and elevation. Eventually, the correlation model between chemical composition and environmental variables was established, based on which a quality zoning map of T. farfara was drawn. The obtained results would provide a scientific reference for the conservation and utilization of wild resources and the selection of planting site of T. farfara.

Potential Distribution of the Asiatic Black Bear in Khangchendzonga National Park, Sikkim Eastern Himalaya using MaxEnt Modeling

Habitat assessment and mapping are major functional keys in the need species conservation concern. The study aimed to understand the possible distribution of Asiatic Black bear (Ursus thibetanus) in the Khangchendzonga National Park. Sign survey, camera trapping, and trail monitoring were used to collect the presence-only data. In this analysis, we used Maximum Entropy Modeling and ArcGIS to determine the variable's contribution to the species distribution and presence. In total, 63 presence data were obtained, and out of 23 environmental variables we used only 15 different environmental variables due to multicollinearity. The ROC results show that variable consistency was excellent (mean AUC=0.941). The variables like Bio-14(Precipitation of driest month), Bio-2(Mean diurnal range (mean of monthly max temp - min temp)), Bio-13(Precipitation of wettest month), aspect and LULC were the critical factors for the distribution of U.thibetanus. The major distribution of U.thibetanus was found in the broadleaved, coniferous forest and grassland patches in the core area. The temperate zone is most preferred as compared to the sub-alpine and alpine zone by U.thibetanus. The distributional area accounts for 360.32km2, representing 20.19% of the whole core area of Khangchendzonga National Park. Large areas of distribution were predicted outside of the core areas, i.e. buffer and transition areas of Khangchendzonga National Park. This study offers valuable findings and data which can be used in future research and conservation management plans in and around Khangchendzonga National Park to mitigate human-bear interaction.

Climatic adaptation explains responses to Pleistocene oscillations and diversification in European vipers

AbstractAimAllopatric speciation is the primary mode of diversification in the Mediterranean Basin. However, the contribution of climatic adaptation during this process is contradictory. In this work, we investigate the eco‐evolutionary processes that drove diversification in this region, using European vipers as a case study. We describe the climatic requirements of different lineages to compare their responses to the Pleistocene climatic oscillations and tackle the evolutionary mechanisms underlying their diversification.LocationEurasia and North Africa.TaxonEuropean vipers (genus Vipera).MethodsWe used ecological niche modelling (ENM) to identify the climatic requirements of 24 Vipera lineages and infer past range dynamics associated with their diversification during the Pleistocene. To test whether climatic niches varied across lineages, we calculated the phylogenetic signal of different climatic variables and examined the relationship with phylogenetic relatedness. To investigate climatic niche evolution and test for phylogenetic niche conservatism (PNC), we quantified pairwise niche overlap in sister phylogenetic units under a 3D hypervolume approach.ResultsENM identified temperature annual range, precipitation of wettest month and precipitation of driest quarter as the most important climatic variables related to the distribution of most lineages, validating Pelias clade as cold‐adapted, and Vipera 1 and Vipera 2 as warm‐adapted clades. Projections to past conditions varied among clades, with Pelias and Vipera 1 having more similar responses, while Vipera 2 exhibited greater variability. We found significant phylogenetic signal in one temperature‐related and two humidity‐related climatic variables and detected high complexity in ecological niche evolution across the phylogeny, both rejecting the hypothesis of PNC.Main ConclusionsClimatic adaptation played a significant role in driving diversification among European vipers. Cold‐adapted and warm‐adapted lineages presented similar climatic requirements and remarkable responses to Pleistocene stages, resulting in an intricate pattern of niche divergence along the phylogeny that favours local adaptation rather than PNC.

Species distribution models of Brant's oak (Quercus brantii Lindl.): The impact of spatial database on predicting the impacts of climate change

Investigating the correlation between environmental variables and species distribution should be performed using data acquired from appropriate spatial scales to meet adaptive management requirements in a changing environment. This research aimed to model the influence of climate change on the spatial distribution of Brant’s oak (Quercus brantii Lindl.) via presence data acquired from local (Ilam province, western Iran), regional (Zagros ecoregion), and global (whole distribution extent of Brant’s oak) extents. To project the potential habitat of Brant's oak, general circulation models (CCSM4, HADGEM2-ES, BCC-CSM1–1 and GISS-E2-R) under the 2.6 and 8.5 representative concentration pathways (RCP) for 2050 and 2070 were used. To model the distribution of Brant’s oak, artificial neural network (ANN), random forest (RF), generalized linear model (GLM), and maximum entropy (MaxEnt) were compared. To validate the models, random-holdback cross-validation, whereby 80% of the data was randomly selected to calibrate the model and the remaining 20% was used to validate the models, was carried out. The results revealed that enhancing the modeling extent increased the accuracy of the model; hence, a model trained using the global dataset performed better than local and regional datasets. In all three geographical extents, RF and MaxEnt had the best performance in modeling the spatial distribution range of Brant’s oak. The main predictors of Brant’s oak distribution were different in local, regional, and global models. The mean temperature of driest quarter (bio9), at the local extent; precipitation of wettest month (bio13), at the regional extent; and temperature annual range (bio7), at the global extent were the most important climatic variables. The findings also indicated that the potential habitat of Brant’s oak will decline in the future under climate change scenarios (i.e., RCP 2.6 and RCP 8.5) and across all three geographical extents compared to the current habitat. Using the findings of this study, it is possible to identify the suitable habitats of Brant's oak forests with more certainty and take measures to manage and protect them.

Environmental predictors may change at fine scale habitat suitability modelling: implications for conservation of Kashmir musk deer in three protected areas of Uttarakhand, India.

The Kashmir musk deer (Moschus cupreus, hereafter KMD) is one of the top conservation priority species which is facing population decline due to poaching, habitat loss, and climate change. Therefore, the long-term survival and viability of KMD populations in their natural habitat require conservation and management of suitable habitats. Hence, the present study attempted to assess the suitable habitat of KMD in three protected areas (PAs) of the Western Himalayan region of Uttarakhand using the Maxent modelling algorithm. Our results suggest that Kedarnath wildlife sanctuary (KWLS) possesses the maximum highly suitable habitats (22.55%) of KMD, followed by Govind Pashu Vihar National Park & Sanctuary (GPVNP&S; 8.33%) and Gangotri National Park (GNP; 5%). Among the environmental variables, altitude was the major contributing factor governing the distribution of KMD in KWLS. In contrast, human footprint in GPVNP&S and precipitation in GNP were the major contributing factors governing the distribution of KMD in these respective PAs. The response curve indicated that habitats with less disturbance falling in the altitudinal zone of 2000-4000m were the most suitable habitat range for the distribution of KMD in all three PAs. However, in the case of GNP suitable habitat of KMD increases with an increase in the value of variables bio_13 (precipitation of wettest month). Further, based on our results, we believe that the predictors of suitable habitat change are site specific and cannot be generalized in the entire distribution range of the species. Therefore, the present study will be helpful in making proper habitat management actions at fine scale for the conservation of KMD.

Climate and topography controls on soil water-stable aggregates at regional scale: Independent and interactive effects

Detailed information on the variability of soil–water stable aggregates (WSA) is critical for soil management practices, ecosystem services and soil erosion. Topography and climate are two of the most important factors influencing WSA variability at the regional to global scales, especially when soil management, agricultural practices, and soil types are similar, yet few studies have examined their independent and interactive effects on WSA. This work was conducted in the karst region of southwest China to investigate the influence of climatic and topographic variables on WSA variability at the regional scale. A total of 569 topsoil samples (0–20 cm) were collected by random sampling under long-term continuous mono-cropping of tobacco in March 2021. Classical statistics, semivariogram, recursive feature elimination (RFE) algorithm, random forest (RF), and GeoDetector were applied to investigate the relationships between WSA variability and several environmental factors, including 6 topographic, 11 temperature-, and 8 precipitation-related variables. Classical statistics showed that the mean WSA content was 51.67%, varying between 40.84% and 64.05%. Semivariogram analysis revealed the strong spatial autocorrelation of WSA (nugget effect = 10.09%). Based on the REF results, both RF modelling and GeoDetector identified 5 climatic variables, namely isothermality (BIO3), annual precipitation (BIO12), precipitation of wettest month (BIO13), precipitation of driest month (BIO14), and precipitation seasonality (BIO15), which dominated WSA variability at the regional scale. Moreover, the linear and non-linear fits of the key variables to WSA showed that BIO3, BIO12, BIO13, and BIO14 presented highly significantly negative correlations (p < 0.01) with WSA, whereas BIO15 had a highly significantly positive correlation (p < 0.01). The Spearman correlation coefficients of BIO3, BIO12, BIO13, BIO14, and BIO15 with WSA were 0.32, 0.44, 0.3, 0.37, and 0.41, respectively (p < 0.01). The interactive effects between topography and the five key climatic variables could facilitate the interpretation of individual variables for WSA variability. The dominant climatic factors of WSA variability changed along different topographical locations. Overall, this study identifies climatic (mainly precipitation) variables that dominated WSA variability at the regional scale and defines the interactive effects of these variables with topography on WSA variability. The results of this work contribute to explaining the complex causes of soil aggregate stability at large scale and provide clues to the management of soil security under climate change.

Projected Effects of Climate Change on Species Range of Pantala flavescens, a Wandering Glider Dragonfly.

Dragonflies are sensitive to climate change due to their special habitat in aquatic and terrestrial environments, especially Pantala flavescens, which have extraordinary migratory abilities in response to climate change on spatio-temporal scales. At present, there are major gaps in the documentation of insects and the effects of climatic changes on the habitat and species it supports. In this study, we model the global distribution of a wandering glider dragonfly, P. flavescens, and detected the important environmental factors shaping its range, as well as habitat shifts under historical and future warming scenarios. The results showed a global map of species ranges of P. flavescens currently, including southern North America, most of South America, south-central Africa, most of Europe, South, East and Southeast Asia, and northern Oceania, in total, ca. 6581.667 × 104 km2. BIO5 (the max temperature of warmest month) and BIO13 (the precipitation of wettest month) greatly explained its species ranges. The historic refugia were identified around the Great Lakes in the north-central United States. Future warming will increase the total area of suitable habitat and shift the type of suitable habitat compared to the current distribution. The habitat suitability of P. flavescens decreased with elevation, global warming forced it to expand to higher elevations, and the habitat suitability of P. flavescens around the equator increased with global warming. Overall, our study provides a global dynamic pattern of suitable habitats for P. flavescens from the perspective of climate change, and provides a useful reference for biodiversity research and biological conservation.

Identification of potential cultivation areas for centelloside-specific elite chemotypes of Centella asiatica (L.) using ecological niche modeling

Centella asiatica (L.) is used in the treatment of neuropsychiatric disorders, gastro-intestinal problems, and wound healing in the Ayurveda system of medicine. The species is well-known for its rich triterpenoid centellosides constituents, which are extensively used in the preparation of various pharmaceutical and cosmetic products. Identification of elite chemotypes based on bioactive marker contents, characterizing their climatic niches, and delineating the potential areas of cultivation for bioactive compound-based elite germplasms, can help large-scale commercial cultivation of C. asiatica with targeted bioactive compounds. We quantified four bioactive compounds i.e., madecassoside, asiaticoside, madecassic acid, and asiatic acid in 109 samples of C. asiatica collected from different phyto-geographical regions of India using HPTLC. Ecological niche modeling (ENM) was used to identify the major climatic factors associated with high metabolite content, and also predict the potential areas of cultivation where the contents are expected to be highest for each bio-marker based elite chemotypes. The contents of asiatic acid, madecassic acid, asiaticoside and madecassoside varied between 0.02–3.2 %, 0.02–3.06 %, 0.018–4.3 %, and 0.01–4.8 %, respectively. Several samples from Western Ghats and Deccan Plateau were identified as elite chemotypes with high centelloside contents. The individual metabolite-specific ENM revealed that temperature annual range, annual precipitation, precipitation of wettest month, precipitation seasonality, and precipitation of coldest quarter were the dominant climatic factors associated with high contents of centellosides. Areas with high climatic suitability for production of the selected four metabolites were restricted to the Western Ghats, Northeast India, Eastern Himalaya, and Western Himalaya. Such areas identified through ENM should be suitable for commercial cultivation of chemotypes with specific metabolite contents. The protocol established in this study would help sustainable availability of metabolite-specific Quality Raw Material (QRM) and Quality Planting Materials (QPM) for the industry in respect of other medicinal plants as well.

Determining the potential distribution of Oryctes monoceros and Oryctes rhinoceros by combining machine-learning with high-dimensional multidisciplinary environmental variables

The African coconut beetle Oryctes monoceros and Asiatic rhinoceros beetle O. rhinoceros have been associated with economic losses to plantations worldwide. Despite the amount of effort put in determining the potential geographic extent of these pests, their environmental suitability maps have not yet been well established. Using MaxEnt model, the potential distribution of the pests has been defined on a global scale. The results show that large areas of the globe, important for production of palms, are suitable for and potentially susceptible to these pests. The main determinants for O. monoceros distribution were; temperature annual range, followed by land cover, and precipitation seasonality. The major determinants for O. rhinoceros were; temperature annual range, followed by precipitation of wettest month, and elevation. The area under the curve values of 0.976 and 0.975, and True skill statistic values of 0.90 and 0.88, were obtained for O. monoceros and O. rhinoceros, respectively. The global simulated areas for O. rhinoceros (1279.00 × 104 km2) were more than that of O. monoceros (610.72 × 104 km2). Our findings inform decision-making and the development of quarantine measures against the two most important pests of palms.

Predicting the distributions of Scleroderma guani (Hymenoptera: Bethylidae) under climate change in China.

The wasp Scleroderma guani is an important parasitic natural enemy of a variety of stem borers such as longicorn beetles. Studying and clarifying the suitable area of this wasp plays an important role in controlling stem borers. Based on information about the actual distribution of S. guani and on a set of environmental variables, MaxEnt niche model and ArcGIS were exploited to predict the potential distribution of this insect in China. This work simulated the geographical distribution of potential climatic suitability of S. guani in China at present and in different periods in the future. Combining the relative percent contribution score of environmental factors and the Jackknife test, the dominant environmental variables and their appropriate values restricting the potential geographical distribution of S. guani were screened. The results showed that the prediction of the MaxEnt model was highly in line with the actual distribution under current climate conditions, and the simulation accuracy was very high. The distribution of S. guani is mainly affected by bio18 (Precipitation of Warmest Quarter), bio11 (Mean Temperature of Coldest Quarter), bio13 (Precipitation of Wettest Month), and bio3 (Isothermality). The suitable habitat of S. guani in China is mainly distributed in the Northeast China Plain, North China Plain, middle‐lower Yangtze Plain, and Sichuan Basin, with total suitable area of 547.05 × 104 km2, accounting for 56.85% of China’s territory. Furthermore, under the RCP2.6, RCP4.5, and RCP8.5 climate change scenarios in the 2050s and 2090s, the areas of high, medium, and low suitability showed different degrees of change compared to nowadays, exhibiting expansion trend in the future. This work provides theoretical support for related research on pest control and ecological protection.

Development of a Methodology for the Conservation of Northern-Region Plant Resources under Climate Change

According to the guidelines of the Nagoya Protocol, species are now recognized as ‘resources’ and owned by each country, thereby emphasizing the significance of biological resources and the importance of the continuous efforts made to systematically manage them. Despite these efforts, climate change, which influences climatic factors such as temperature and precipitation, is expected to negatively impact the struggle for conservation of biological resources by affecting species’ habitats. We aimed to devise methodologies that could be utilized for the management of biological resources, especially valuable tree species, that are experiencing difficulties due to climate change. First, changes in habitat of the northern-region plant Needle fir (Abies holophylla) due to of climate change were estimated using the BIOMOD2 package in R under the RCP8.5 scenario. Second, the time period of management was estimated based on the change in habitat area over time. It is expected that 30% of the current habitat of A. holophylla will be lost by 2030 and 50% will be lost by 2042. Third, four management zones (maintenance, reduction, dispersal, and non-habitat areas) were derived by comparing habitats according to the period of management required. In this case, we compared the present and the time point at which 30% habitat loss (2030) is expected to occur. After that, the management steps that can be taken for each management zone were suggested. Our results show the impact of climate change, especially change in Bio1 (annual mean temperature) and Bio13 (precipitation of wettest month), on species distribution patterns and have potential applicability in biological resource management. We have specified the suitable point of time, area, and direction of management in this study, which will contribute to climate change management planning and policy-making. By doing so, we hope that when a management policy on biological resources is applied, by dividing the four management zones, policymakers will be able to apply a cost-efficient policy.