Important Environmental Variables Research Articles

Potential distribution of Detarium microcarpum under different climate change scenarios in Burkina Faso

Climate change and human activities are major drivers influencing species distribution, posing significant challenges for woody species that provide essential ecosystem goods and services. Therefore, a thorough understanding of climate impacts on species distribution is crucial for more effective management. This study aims to assess the effect of climate change on the current and future distribution of Detarium microcarpum. This study was conducted in Burkina Faso. The maximum entropy (MaxEnt) approach was used to simulate the current and future distributions of the species. The future distribution of the species was assessed through four global climate models: HadGEM3-GC3.1-LL, ACCESS-CM2, CNRM-CM6-1 and MIROC6 under two Shared Socioeconomic Pathways (SSPs) scenarios, SSP2-4.5 and SSP5-8.5 at the horizons 2061–2080 and 2081–2100. The area under the curve (AUC ˃ 0.80) and True Skill Statistic (TSS=0.7) revealed a high level of prediction for the current and future scenarios. The results showed that the mean temperature of the Wettest Quarter (bio8) and Isothermality (bio3) were the most important environmental variables which affect D. microcarpum distribution. The results show that the current suitability area for the species covers 65.6 % of the country area with respectively high suitability (36.73 %) and low suitability (29.16 %). Based on the outcomes of the prediction, the high suitable areas for D. microcarpum conservation will decrease on average by 5,92 % of their current area under future climate change, regardless of the scenario and model used, except for the MIROC6 model under the SSP5-8.5 scenario, which will increase its current area from 0.56 % to 1.7 %. The result of this study underscores the significant effect of the future climate on the suitable area of D. microcarpum. Specific actions should be taken to ensure the suitable conservation of this valuable multipurpose species.

Identification of Potential Future Areas for Sustainable Cashew (Anacardium occidentale L.) Nut Production in Togo Using the Maxent Model

Understanding present and potential habitats is critical for developing climate-resilient cashew-growing techniques and sustainable management strategies. This study aims to identify the existing distribution of Anacardium occidentale L. in Togo and anticipates the possible impact of climate change on its habitat distribution by 2050 using two global circulation models (HadGEM3-GC3.1-L and MIROC6) and two shared socioeconomic paths (SSP245 and SSP585). The maximum entropy algorithm, 2538 species occurrence records, and a set of seventeen (17) climatic and soil variables were used. The findings revealed that soil, followed by annual precipitation (bio12) and temperature seasonality (bio4), are the most important environmental variables influencing cashew distribution in Togo. According to the present model, 78.92% of Togo's topography is very favourable to sustainable cashew-growing practices. According to the MOROC6 Model, very favourable cashew nut production areas will be decreased to 5.24% in the SSP 245 scenario and altogether disappear with the SSP585 scenario by 2050. However, for the HadGEM3-GC3.1-L model by 2050, the areas of sustainable cashew nut production in Togo will be reduced to 3.71% and 0.26% respectively for the SSP245 and 585 scenarios. In short, the results of this study, which was carried out for the first time in Togo, point out the need to put in place a strategy for the conservation and sustainable cultivation of cashew trees in Togo.

Homogeneous earthworm communities in Southern Ontario

Earthworms are key organisms of soil ecosystems, however, the determinants of the structure and distribution of earthworm communities and their relationships with agricultural practices are not well-studied in Canada. We sampled earthworm communities from four different habitat types along a disturbance gradient: agricultural crop land, forest around crop fields (buffers), recently restored natural grassland, and forests from conservation areas. As most species living in Canada are considered exotic and because of the recent colonization of Canadian soils by mostly European species after the extinction of the native species due to the glaciation of North America during the Pleistocene, we hypothesized that the impact of agricultural practices will be similar to what is observed in Europe: for example, crop habitat showing lowest abundance, richness, and proportion of epigeic and anecic species, due to lesser soil organic matter content and higher soil disturbance. We also hypothesized that important soil variables would be associated with these habitat differences. For each habitat we sampled earthworms using a combination of two methods (quantitative + qualitative) at three replicate sites, for two years between May and July together with important environmental variables. We found lower density and diversity of earthworms in crop habitat and proportionally more epigeic species than expected. Contrary to our predictions, forest-buffer earthworm communities were more similar to crop than to forest habitats, and soil environmental variables could not explain the variations in the spatial distribution of earthworm communities. In fact, our results revealed a more homogeneous distribution of the species diversity across the habitat gradient at local scales in Southern Ontario. This was mainly associated with spatial factors, probably due to historical extinction-colonization events of earthworms in Canada and the high invasive potential of the species currently present.

Changes in soil bacterial community diversity and its network stability under different grazing intensities in plateau rangelands

Grassland degradation is a significant ecological challenge, it changes the grassland environment, including the structure of soil microbial communities. Grazing is a critical factor in this process, yet the impact of different grazing intensities on soil bacterial communities, particularly in unique environments like the Qinghai-Tibet Plateau, remains poorly understood. This study utilized a full-length 16 S rRNA gene sequencing technology combined with environmental factors to assess the impacts of the Holba sheep grazing on soil bacterial community diversity in Zhongba County, Shigatse City, Qinghai-Tibet Plateau. The specific aim was to explore the changes in soil bacterial community diversity and stability under contrasting grazing intensities: prohibited grazing, light grazing, moderate grazing, and heavy grazing. The results showed that grazing activities significantly altered the diversity of bacterial communities, particularly under light and heavy grazing. The spatial dissimilarity in soil bacterial communities was mainly driven by species turnover (i.e., species replacement), which was more pronounced under heavy grazing. The number of keystone species increased with the grazing intensity of the bacterial co-occurrence network. Under heavy grazing, bacterial communities showed the highest number of keystone species and the community stability. Environmental factors such as exchangeable magnesium (EM), soil available kalium (SAK), and soil pH were the most important environmental variables impacting changes in bacterial community structure by influencing community α-diversity and stability. This study enhances our understanding of the response mechanisms of soil microbial communities to grazing intensities and other environmental stresses in grassland ecosystems. In addition, this study also provides important references and guidance for microbial diversity research in extreme environments. These findings are crucial for promoting the sustainable management and conservation of grassland ecosystems in climatically harsh areas such as the Qinghai-Tibet Plateau.

Prediction of Chinese suitable habitats of Panax notoginseng under climate change based on MaxEnt and chemometric methods

Notoginseng saponin R1; ginsenosides Rg1, Re, Rb1, and Rd; the sum of the five saponins; and underground-part fresh weight (UPFW) of single plants were used as quality evaluation indices for Panax notoginseng (Burk.) F. H. Chen (P. notoginseng). Comprehensive evaluation of P. notoginseng samples from 30 production areas was performed using that MaxEnt model. Spatial pattern changes in suitable P. notoginseng habitats were predicted for current and future periods (2050s, 2070s, and 2090s) using SSP126 and SSP585 models. The results revealed that temperature, precipitation, and solar radiation were important environmental variables. Suitable habitats were located mainly in Yunnan, Guizhou, and Sichuan Provinces. The distribution core of P. notoginseng is predicted to shift southeast in the future. The saponin content decreased from the southeast to the northwest of Yunnan Province, which was contrary to the UPFW trend. This study provides the necessary information for the protection and sustainable utilization of P. notoginseng resources, and a theoretical reference for its application in the quality evaluation of Chinese medicinal products.

Genetic variability and population structure of two sympatric cownose rays Rhinoptera (Myliobatiformes, Rhinopteridae) in the Western Atlantic Ocean

Cownose rays Rhinoptera bonasus and R. brasiliensis, are species distributed along the coastal waters from eastern United States, Gulf of Mexico to Brazil. This study represents the most extensive evaluation to date of the genetic diversity and population genetic structure of R. bonasus across its distribution, and it is the first to investigate the population genetics of R. brasiliensis. We analyzed sequences of COI and Cytb genes for Rhinoptera bonasus (COI: 230, Cytb: 108) and R. brasiliensis (COI: 181, Cytb: 105) to investigate the genetic diversity and their relationship with environmental variables, genetic structure, as well as demographic parameters. We found that benthic temperature and current velocity were the most important environmental variables in genetic diversity. The global population structure reveals the presence of significant population genetic structure in both species. Bayesian clusters in BAPS were consistent with the segregation pattern observed for haplotype networks based on COI and Cytb markers for both species, which may respond to philopatry and temperature. These results will further improve management and conservation efforts for theses species of ecological and economic importance.

Forecasting daily total pollen concentrations on a global scale.

There is evidence that global anthropogenic climate change may be impacting floral phenology and the temporal and spatial characteristics of aero-allergenic pollen. Given the extent of current and future climate uncertainty, there is a need to strengthen predictive pollen forecasts. The study aims to use CatBoost (CB) and deep learning (DL) models for predicting the daily total pollen concentration up to 14 days in advance for 23 cities, covering all five continents. The model includes the projected environmental parameters, recent concentrations (1, 2 and 4 weeks), and the past environmental explanatory variables, and their future values. The best pollen forecasts include Mexico City (R2(DL_7) ≈ .7), and Santiago (R2(DL_7) ≈ .8) for the 7th forecast day, respectively; while the weakest pollen forecasts are made for Brisbane (R2(DL_7) ≈ .4) and Seoul (R2(DL_7) ≈ .1) for the 7th forecast day. The global order of the five most important environmental variables in determining the daily total pollen concentrations is, in decreasing order: the past daily total pollen concentration, future 2 m temperature, past 2 m temperature, past soil temperature in 28-100 cm depth, and past soil temperature in 0-7 cm depth. City-related clusters of the most similar distribution of feature importance values of the environmental variables only slightly change on consecutive forecast days for Caxias do Sul, Cape Town, Brisbane, and Mexico City, while they often change for Sydney, Santiago, and Busan. This new knowledge of the ecological relationships of the most remarkable variables importance for pollen forecast models according to clusters, cities and forecast days is important for developing and improving the accuracy of airborne pollen forecasts.

Maxent Predictive Species Distribution Models and Model Accuracy Assessment for Two Species of Psilochalcis Kieffer (Hymenoptera: Chalcididae) Occurring in the Eastern Great Basin of Utah, USA

Two species of Psilochalcis wasps (P. minuta and P. quadratis) were recently described from Utah’s eastern Great Basin. The extent of their known distributions is extremely limited, based on few data points. We developed species distribution models (SDMs) using Maxent modeling software for each Psilochalcis species to identify areas of probable suitable habitat for targeted collecting to improve our knowledge of their distributions. We used six occurrence data points for P. minuta and eight occurrence data points for P. quadratis, along with ten environmental variables as inputs into the Maxent modeling software. Model-predicted areas with a potential suitable habitat value greater than 0.69 were mapped using ArcGIS Pro to help select locations for model accuracy assessment. Employing Malaise traps, eighteen sites were sampled to evaluate each SDM’s ability to predict the occurrence of Psilochalcis species. Psilochalcis minuta occurred at eight of nine juniper-dominated sample sites that were predicted as having high suitability by the model for this species. Likewise, P. quadratis occurred at two of four cheatgrass-dominated sample sites predicted by the model. Psilochalcis minuta occurred at three of nine sampled sites that were not predicted by the model, and P. quadratis occurred at seven of fourteen non-predicted sites. The Maxent SDM results yielded an AUC value of 0.70 and p-value of 0.02 for P. minuta and 0.68 and 0.02. for P. quadratis. These results were reflected in our model accuracy assessment. Of the selected environmental variables, aspect, historic fire disturbance, and elevation yielded the greatest percent contributions to both species’ models. Sympatric distributions were observed for P. minuta and P. quadratis. Elevation, vegetation type, NDVI, and soil type are the most important environmental variables in differentiating areas of optimal suitable habitat for the two species.

Distribution patterns of Phytoseiulus persimilis in response to climate change.

The biological control agent Phytoseiulus persimilis is a commercialized specialist predator of two agricultural pest mite species Tetranychus urticae and Tetranychus evansi. Biocontrol of these pest species by P. persimilis has achieved success in biological control in some areas. However, the lack of precise information about the influence of global climate change on the worldwide distribution of this biocontrol agent hampers international efforts to manage pest mites with P. persimilis. With 276 occurrence records and 19 bioclimatic variables, this study investigated the potential global distribution of P. persimilis. The results demonstrated that the Maximum Entropy (MaxEnt) model performed well, with the area under the curve being 0.956, indicating the high accuracy of this model. Two variables, the minimum temperature of the coldest month (Bio_6) and precipitation of the coldest quarter (Bio_19) were the most important environmental variables that influenced the distribution of P. persimilis, contributing more than 30% to the model, respectively. The suitable area currently occupies 21.67% of the world's land area, spanning latitudes between 60°S and 60°N. Under shared socio-economic pathway (SSP) 5-8.5 (high-carbon emissions), the low suitable area would increase by 1.31% until the 2050s. This study successfully identified that south-eastern China, parts of countries in the Mediterranean coastal regions, including Libya, Algeria, Portugal, Spain, and France, are climatically favorable regions for P. persimilis, providing valuable information about the potential areas where it can be effectively exploited as biocontrol agents in classical biological control programs to manage pest spider mites environmentally friendly. © 2024 Society of Chemical Industry.

Spatiotemporal pattern and suitable areas analysis of equine influenza in global scale (2005-2022).

Equine influenza (EI) is a severe infectious disease that causes huge economic losses to the horse industry. Spatial epidemiology technology can explore the spatiotemporal distribution characteristics and occurrence risks of infectious diseases, it has played an important role in the prevention and control of major infectious diseases in humans and animals. For the first time, this study conducted a systematic analysis of the spatiotemporal distribution of EI using SaTScan software and investigated the important environmental variables and suitable areas for EI occurrence using the Maxent model. A total of 517 occurrences of EI from 2005 to 2022 were evaluated, and 14 significant spatiotemporal clusters were identified. Furthermore, a Maxent model was successfully established with high prediction accuracy (AUC = 0.920 ± 0.008). The results indicated that annual average ultraviolet radiation, horse density, and precipitation of the coldest quarter were the three most important environmental variables affecting EI occurrence. The suitable areas for EI occurrence are widely distributed across all continents, especially in Asia (India, Mongolia, and China) and the Americas (Brazil, Uruguay, USA, and Mexico). In the future, these suitable areas will expand and move eastward. The largest expansion is predicted under SSP126 scenarios, while the opposite trend will be observed under SSP585 scenarios. This study presents the spatial epidemiological characteristics of EI for the first time. The results could provide valuable scientific insights that can effectively inform prevention and control strategies in regions at risk of EI worldwide.

Exploring the Dynamics of Trade in Developing Countries: A Panel ARDL Analysis of Renewable Electricity, Labor Force, and Economic Factors

This study looks at how important economic, environmental, and labour force variables interact with trade dynamics in emerging nations. The study examines the relationship between trade and renewable power generation, labour force participation, and economic indicators throughout the period from 2000 to 2023 using a panel Autoregressive Distributed Lag (ARDL) approach. With the exception of CO2 emissions, which show a negative correlation, the results show a strong positive association between trade and the variables under investigation. These results highlight the significance of sustainable economic development methods in promoting trade growth in poor countries and throw insight on the intricate processes influencing trade patterns.

Quantifying the spatial nonstationary response of environmental factors on purse seine tuna vessel fishing

To investigate the spatial and temporal patterns of environmental factors influencing the activity of purse seine tuna fishing vessels, data on fishing efforts of purse seine tuna fleets and environmental factors in the Western and Central Pacific Ocean (WCPO) from 2015 to 2020 were utilized to develop a geographically weighted regression (GWR) model. The results showed that fishing activity was primarily concentrated in the area between 140°E and 175°W, and between 10°S and 5°N. The GWR model showed excellent fitting performance and was suitable for correlation analysis. The environmental factors had a significant spatially heterogeneous effect on the fishing activity of purse seine tuna fishing vessels. The sea surface temperature, primary productivity at 200 m depth, and dissolved oxygen below the surface had the greatest spatially heterogeneous effect and are important environmental variables influencing the activity of purse seine tuna vessels in the WCPO. This study provides new methods for exploring the spatial distribution of fishing vessel activity to support science-based conservation and management.

Drivers of organic carbon distribution and accumulation in the northern Barents Sea

Sedimentary properties and accumulation rates on the continental shelf and in the deep sea reflect temporal oceanographic, biological and chemical processes occurring in the water column and the sediment surface. We used the radionuclides 210Pb, 226Ra, and 137Cs activities to estimate sedimentation rates during the last century at nine stations in the northern Barents Sea region. Elemental (C, N) and stable isotopic composition (δ13C, δ15N) were also analysed from the nine stations sampled in August 2018, and, for five other stations sampled in August and December 2019, and in March and May 2021. Sediment accumulation rates varied between 130 and 1 410 g m−2 y−1. The < 63 μm normalized total organic carbon (TOC63) and the total nitrogen from the sediment surface varied between 0.90–2.56 % and 0.13–0.33 %, respectively. Ice-free shelf stations had higher TOC63 and possibly fresher organic matter (high δ13C, low δ15N) than ice-covered more northern stations. The opposite trend was observed for total inorganic carbon. We found that these trends in biogeochemical parameters were spatially structured by the winter sea ice concentration and biological production differences, and exhibited a south-north separation of the Polar Front region. The low and stable organic carbon accumulation rate (1.7–13.4 g Corg m-2 y−1; ARtoc) is a function of slow sedimentation rates, and high degradation and residence time in the water column and at the sediment–water interface. Overall, the ARtoc has been stable for the past 100 years, with a slight increase from the early 1970s to the present at the shelf and slope stations. Our results highlight that spatial scales of variability of the studied sedimentary parameters are linked to spatial patterns of important environmental variables (e.g., chlorophyll-a, sea ice concentration) in the region. In contrast, no seasonal differences were observed in the sediment parameters of revisited stations, and the dated sediment geochemical profiles did not exhibit substantial longer-term variation. This means that climate-induced changes in variables that modify the sedimentary geochemistry of the environment may affect benthic community activity and structure before leaving a record in ARtoc.

Phytoplankton composition in Mediterranean confined coastal lagoons: testing the use of ecosystem metabolism for the quantification of community-related variables

Estimations of ecosystem metabolism have rarely been used to quantify productivity in structural reductionist approaches for the description of phytoplankton composition. However, estimations of ecosystem metabolism could contribute to a better understanding of the relationship between phytoplankton composition and ecosystem functioning. To examine this, we investigated the community structure of phytoplankton in a set of Mediterranean coastal lagoons (natural and artificial) during a hydrological cycle to identify the most important environmental variables determining phytoplankton species composition. The focus of the study was on the quantification of productivity-related variables using estimations of ecosystem metabolism, such as different proxies for the estimation of the production-to-biomass ratio and of the relative importance of K- and r-strategies, which are commonly used conceptually but not quantified. Our results demonstrated differences in phytoplankton composition between seasons, due to the dominant hydrological pattern of flooding confinement in the salt marsh, and between lagoons that were caused by different levels of nutrient availability. Moreover, there was a notable decrease in the production/biomass ratio and a prevalence of K-strategists with seasonal succession, as predicted by Margalef’s mandala. Thus, the results showed that estimations of ecosystem metabolism are useful for the higher frequency quantification of important ecological variables, and contribute to a better understanding of planktonic assemblages, and physical and chemical changes, in these fluctuating ecosystems.

Using DNA metabarcoding to characterize national scale diatom-environment relationships and to develop indicators in streams and rivers of the United States

Recent advancements in DNA techniques, metabarcoding, and bioinformatics could help expand the use of benthic diatoms in monitoring and assessment programs by providing relatively quick and increasingly cost-effective ways to quantify diatom diversity in environmental samples. However, such applications of DNA-based approaches are relatively new, and in the United States, unknowns regarding their applications at large scales exist because only a few small-scale studies have been done. Here, we present results from the first nationwide survey to use DNA metabarcoding (rbcL) of benthic diatoms, which were collected from 1788 streams and rivers across nine ecoregions spanning the conterminous USA. At the national scale, we found that diatom assemblage structure (1) was strongly associated with total phosphorus and total nitrogen concentrations, conductivity, and pH and (2) had clear patterns that corresponded with differences in these variables among the nine ecoregions. These four variables were strong predictors of diatom assemblage structure in ecoregion-specific analyses, but our results also showed that diatom-environment relationships, the importance of environmental variables, and the ranges of these variables within which assemblage changes occurred differed among ecoregions. To further examine how assemblage data could be used for biomonitoring purposes, we used indicator species analysis to identify ecoregion-specific taxa that decreased or increased along each environmental gradient, and we used their relative abundances of gene reads in samples as metrics. These metrics were strongly correlated with their corresponding variable of interest (e.g., low phosphorus diatoms with total phosphorus concentrations), and generalized additive models showed how their relationships compared among ecoregions. These large-scale national patterns and nine sets of ecoregional results demonstrated that diatom DNA metabarcoding is a robust approach that could be useful to monitoring and assessment programs spanning the variety of conditions that exist throughout the conterminous United States.

Projections of climate-driven biogeographical changes of benthic mollusks in the Yellow Sea and East China Sea

Climate change influences the distribution of many marine species. To project the biogeographical changes of benthic mollusks in response to climate change in the Yellow Sea and East China Sea, ensemble species distribution models (SDMs) were applied. Ensemble SDMs performed well for ten of the thirteen selected benthic mollusks with environmental variables including temperature, salinity, current velocity, and depth. Six cold water mollusks, including bivalves Acila mirabilis, Ennucula niponica, Ennucula tenuis, Nuculana yokoyamai, Pendaloma otohimeae and Megayoldia japonica, were projected to contract their habitats and move northward in 2050s and 2100s under all of the RCP2.6, 4.5, 6.0 and 8.5 climate scenarios, with temperature being the most important environmental variable. Two warm water mollusks (bivalves Nucula tokyoensis and Leptomya minuta) were projected to lose their suitable habitats under future climate scenarios (all RCP scenarios), while two (the gastropod Cylichna biplicata and the bivalve Moerella hilaris) were projected to expand their habitats to the deeper water area. The most important environmental variable varied among warm water species between temperature, salinity and depth. This study will contribute to better understanding the marine species biogeographical changes under climate change, and thus we can better protect their biodiversity.

Population genetic variation and geographic distribution of suitable areas of Coptis species in China.

The rhizomes of Coptis plants have been used in traditional Chinese medicine over 2000 years. Due to increasing market demand, the overexploitation of wild populations, habitat degradation and indiscriminate artificial cultivation of Coptis species have severely damaged the native germplasms of species in China. Genome-wide simple-sequence repeat (SSR) markers were developed using the genomic data of C. chinensis. Population genetic diversity and structure of 345 Coptis accessions collected from 32 different populations were performed based on these SSRs. The distribution of suitable areas for three taxa in China was predicted and the effects of environmental variables on genetic diversity in relation to different population distributions were further analyzed. 22 primer pairs were selected as clear, stable, and polymorphic SSR markers. These had an average of 16.41 alleles and an average polymorphism information content (PIC) value of 0.664. In the neighbor-joining (N-J) clustering analysis, the 345 individuals clustered into three groups, with C. chinensis, C. chinensis var. brevisepala and C. teeta being clearly separated. All C. chinensis accessions were further divided into four subgroups in the population structure analysis. The predicted distributions of suitable areas and the environmental variables shaping these distributions varied considerably among the three species. Overall, the amount of solar radiation, precipitation and altitude were the most important environmental variables influencing the distribution and genetic variation of three species. The findings will provide key information to guide the conservation of genetic resources and construction of a core reserve for species.

Responses of Three Pedicularis Species to Geological and Climatic Changes in the Qinling Mountains and Adjacent Areas in East Asia.

The Qinling Mountains in East Asia serve as the geographical boundary between the north and south of China and are also indicative of climatic differences, resulting in rich ecological and species diversity. However, few studies have focused on the responses of plants to geological and climatic changes in the Qinling Mountains and adjacent regions. Therefore, we investigated the evolutionary origins and phylogenetic relationships of three Pedicularis species in there to provide molecular evidence for the origin and evolution of plant species. Ecological niche modeling was used to predict the geographic distributions of three Pedicularis species during the last interglacial period, the last glacial maximum period, and current and future periods, respectively. Furthermore, the distribution patterns of climate fluctuations and the niche dynamics framework were used to assess the equivalence or difference of niches among three Pedicularis species. The results revealed that the divergence of three Pedicularis species took place in the Miocene and Holocene periods, which was significantly associated with the large-scale uplifts of the Qinling Mountains and adjacent regions. In addition, the geographic distributions of three Pedicularis species have undergone a northward migration from the past to the future. The most important environmental variables affecting the geographic distributions of species were the mean diurnal range and annual mean temperature range. The niche divergence analysis suggested that the three Pedicularis species have similar ecological niches. Among them, P. giraldiana showed the highest niche breadth, covering nearly all of the climatic niche spaces of P. dissecta and P. bicolor. In summary, this study provides novel insights into the divergence and origins of three Pedicularis species and their responses to climate and geological changes in the Qinling Mountains and adjacent regions. The findings have also provided new perspectives for the conservation and management of Pedicularis species.

Maximum Entropy Analysis of Bird Diversity and Environmental Variables in Nanjing Megapolis, China

Against the background of global climate change and urbanization, the biodiversity of birds is facing unprecedented threats. In this paper, taking the Nanjing megapolis as an example, based on the distribution sites of 79 bird species and 17 environmental variables, the MaxEnt model was used to simulate the distribution of bird diversity, and the most important environmental variables were analyzed. The results show that (1) the MaxEnt model is suitable for simulation of the potential distribution of bird diversity in the Nanjing megapolis; (2) the areas with the highest bird diversity in the Nanjing megapolis were mainly distributed in the mountains and hills where the forests are located; (3) the five most important environmental variables affecting bird distribution were ranked as maximum temperature of the warmest month (MTWM) &gt; Digital Elevation Model (DEM) &gt; precipitation of the wettest month (PWM) &gt; distance to the nearest forest (DF) &gt; Fractional Vegetation Cover index (FVC), with MTWM, PWM, and DF being negatively correlated with bird diversity, whereas FVC and DEM exhibited positive correlations with bird diversity; and (4) the contribution rates of the three types of environmental variables were ranked as follows: habitat environmental variables &gt; meteorological environmental variables &gt; disturbance environmental variables. Sufficient bird habitats should be maintained in cities, and disturbances from human activities should be reduced to achieve the harmonious coexistence of humans and animals in the context of climate change and urbanization, thereby promoting sustainable development.

Global Warming Drives Expansion of Endangered Spruce Forest on the Tibetan Plateau

Global warming is critical to the distribution pattern of endangered plants; therefore, understanding the future changes in the adaptive areas of endangered spruce and driving factors on the Tibetan Plateau is of great research significance for spruce species conservation and sustainability. In this study, variations in the distribution pattern of four endangered spruce species (Picea. Balfouriana, Picea. Linzhiensis, Picea. Complanata, and Picea. Aurantiaca) on the Tibetan Plateau were predicted by the MaxEnt model, and the important environmental variables affecting its geographic distribution were analyzed. We found that under the current climate conditions, the four endangered spruce species were mainly situated in the southern and southeastern Tibetan Plateau. The mean temperature of the coldest quarter was a key environmental variable affecting the geographic distribution of four endangered spruce species, with suitable growth ranges of −9–8 °C for P. balfouriana and −6–5 °C for P. linzhiensis, P. complanata, and P. aurantiaca. Under different future climate pathways, the highly suitable habitat of four endangered spruce was mainly situated in the east, south, and southeast districts of the Tibetan Plateau. With the suitable growth range of key variables continuing to expand on the Tibetan Plateau, the area of suitable habitat for each of the four endangered spruce species increases to varying degrees. Compared with the current climate, four endangered spruce species will expand to the northwest of the Tibetan Plateau under different future climate scenarios, and the degree of expansion will increase with the increase in temperature. This study not only reveals the response of suitable habitats of four endangered spruce species to global warming, but also provides scientific insights for spruce population conservation and sustainable development.