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Simple Summary: The pepper weevil, Anthonomus eugenii Cano, stands out as a particularly destructive pest, causing substantial losses in Capsicum pepper production. Therefore, accurately identifying its distribution is crucial for effective monitoring and prevention strategies under climate warming scenarios. Using MaxEnt modeling and ArcGIS, this study mapped current and future suitable habitats for the pepper weevil in China under four climate scenarios from 2030 to 2090. The findings indicated that while the pest currently occupies 28.47% of China's area, future climate changes could lead to reduced suitable habitats, except in certain scenarios, with shifts towards southwestern regions expected. Our findings offer crucial insights for early monitoring and managing of A. eugenii populations, as well as for choosing suitable sites for pepper cultivation that are free from pest infestations. The pepper weevil, Anthonomus eugenii Cano, 1894 (Coleoptera: Curculionidae), poses a significant threat to pepper cultivation, causing extensive crop damage and economic losses. While numerous studies have addressed its occurrence, biology, and control methods, less attention has been given to how climate change might alter its distribution. This research utilized the optimized MaxEnt model to project the current and future habitat suitability of the pepper weevil under four distinct climate scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) for the periods spanning the 2030s to 2090s. Optimal model performance was achieved with a regularization multiplier of two and a feature combination of QHP, yielding high predictive accuracy with mean testing AUC values of 0.921. The analysis identified annual mean temperature (Bio1) and precipitation of the coldest quarter (Bio19) as the primary environmental factors influencing the pest's distribution. Currently, in China, suitable habitats for A. eugenii encompass an area of 273.74 × 104 km2 or 28.47% of the nation's territory, predominantly located in central, eastern, southern, and southwestern regions. Future projections suggest that suitable areas are expected to shrink across various scenarios, barring increases in specific instances like SSP126-2050s, SSP245-2070s, and SSP370-2050s, with shifts towards southwestern regions. This investigation deepens our comprehension of agricultural pest dynamics under climate change and supports the formulation of preemptive management strategies to safeguard agricultural productivity. [ABSTRACT FROM AUTHOR]

Simple Summary: Melioidosis is a zoonotic disease caused by Burkholderia pseudomallei. To explore the global animal melioidosis risk distribution and its dynamic response under future climate scenarios, we collected details about the occurrence sites of animal melioidosis and the Burkholderia pseudomallei occurrence sites in contaminated air, soil and water. Maximum entropy (MaxEnt) was used to establish the melioidosis risk model. The results show that under current bioclimatic conditions, animal melioidosis high-risk regions are concentrated between 30° S and 30° N, with particularly high levels of risk in Central America, the northern part of South America, and eastern and southern India, among others. With future climate change, the risk regions in most countries are expected to expand, and new epidemic zones will emerge at higher northern latitudes. However, some areas may experience a contraction of risk regions. This study provides a basis for global melioidosis surveillance and offers effective early warning measures, which can help reduce losses in risk areas. Melioidosis is a zoonotic disease that is caused by Burkholderia pseudomallei, which is a serious public health and safety risk. In order to explore the global animal melioidosis risk distribution and its dynamic response to future climate scenarios, we collected global data about reported animal incidence sites. Data regarding the density of Burkholderia pseudomallei in the environment were created by collecting and sorting information about the Burkholderia pseudomallei occurrence sites in contaminated air, soil, and water. Combined with bioclimatic variables, the maximum entropy (MaxEnt) niche was modeled for global animal melioidosis. The findings indicate that under current bioclimatic conditions, global animal melioidosis risk regions are concentrated between 30° S and 30° N, with high-risk areas being mainly in Central America, the northern part of South America, and eastern and southern India, among others. Most countries will expand their risk regions under future climatic scenarios. Melioidosis risk expanding towards higher northern latitudes has led to new epidemic areas. In addition, the melioidosis risk area will contract in some areas. Therefore, we have provided a basis for global melioidosis surveillance and propose feasible strategies for prevention and control in high-risk regions, which will help countries to carry out targeted surveillance and prevention to reduce risks and losses. [ABSTRACT FROM AUTHOR]

Copyright of Acta Prataculturae Sinica is the property of Acta Prataculturae Sinica Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Hylurgus ligniperda (Fabricius) is an important pest that attacks Pinus species in China. It impacts the vitality of local pine vegetation, reduces the ability to prevent windbreak and sand fixation, and causes ecological loss. MaxEnt and ArcGIS are used to predict and analyze the changes in suitable distribution areas of H. ligniperda under current and future climate scenarios, based on 12 climate factor datasets and 1,001 field distribution data points for this pest. The environmental variables used significantly influence the potential distribution of H. ligniperda. Highly suitable areas of this beetle are located in western Europe, central Asia, and the southeastern regions of Oceania, with sporadic occurrences across North America, South America, and Africa. Highly suitable areas in China occur across the east, central south, and southwest regions. There is a significant increase in the high and medium suitability areas, while the area of low suitability decreases under the 4 future climate scenarios (SSP126, SSP245, SSP370, and SSP585). The suitable distribution area for H. ligniperda shows an overall trend of moving northwestward. The purpose of this current study is to provide important theoretical support for the prevention and management of this pest by predicting and analyzing suitable distribution areas under current and future climate scenarios. Graphical Abstract [ABSTRACT FROM AUTHOR]

The Argentine shortfin squid Illex argentinus is an economically important short-lived species widely distributed in the southwest Atlantic Ocean. The abundance and distribution of I. argentinus are associated with climate change and environmental fluctuations. The potential distribution of I. argentinus was modeled with various environmental variables including sea surface temperature (SST), sea surface height (SSH), chlorophyll a, sea surface salinity (SSS), net primary productivity (NPP), mixed layer depth (MLD), eddy kinetic energy (EKE), and photosynthetically active radiation (PAR) using the maximum entropy (MaxEnt) approach during the peak fishing seasons (January–April). The habitat suitability index (HSI) was defined as the probability of species emergence from the MaxEnt model and the area of HSI≥0.6 was regarded as suitable. Results indicate that the predicted habitat correlated with the actual fishing position, with similar trends in the percentages of suitable habitats and catch per unit effort (CPUE) of I. argentinus from January to April. Moreover, SST, SSH, PAR, and MLD were identified critical environmental variables for the distribution of I. argentinus. In addition, the median of preferred ranges of the critical environmental variables were concentrated within the suitable habitats of I. argentinus. The Area under the Receiver Operating Characteristic Curve (AUC) was greater than 0.96 for all four months. Variations in latitudinal and longitudinal gravity centers (LATG and LONG) of fishing effort were consistent with latitudinal and longitudinal gravity centers (LATG_H and LONG_H) of the HSI. Our findings suggest that the MaxEnt model is an effective tool to predict the potential distribution of I. argentinus. Meanwhile, SST, SSH, PAR, and MLD should be given with more extensive attention in predicting the potential distribution of I. argentinus, as they are important environmental indicators that can help decision-makers search for the fishing ground of I. argentinus in the Southwest Atlantic. [ABSTRACT FROM AUTHOR]

Constructing ecological networks in urban areas improves ecosystem stability and biodiversity protection. However, most studies focus on optimizing ecological environments through objective assessments, often neglecting species diversity. This study developed a biodiversity grading framework for the Jianghan Plain using species observation and ecosystem diversity data. Supported by ArcGIS, ecological sources were identified via MSPA and graded using the Guidelines and MaxEnt model. The MCR model was used to simulate connectivity barriers between ecological sources and calculate the minimum cumulative resistance distance, thereby generating corridors and ultimately constructing a hierarchical biodiversity conservation network for the Jianghan Plain. Our findings indicated the following: (1) The Jianghan Plain hosts 21 major ecological sources, primarily natural water bodies at the plain's edge, which can be classified into five primary and 16 secondary sources based on biodiversity grades. (2) The recessive corridors, comprising 10 primary and 95 secondary ones, are mainly concentrated in the central Jianghan Plain, with primary corridors located centrally and westward, characterized by a large overall span. (3) Changhu Lake and Honghu Lake, two critical water bodies with high-quality habitats and significant biodiversity, were identified as key ecological nodes from the ecological sources, bridging and guiding the central and southern corridors. (4) Based on the ecological network distribution and key nodes and corridors, a "three zones, three belts, and two points" strategy was proposed for optimizing the Jianghan Plain's ecological network. This study provides a novel framework and theoretical support for regional habitat, biodiversity conservation, and sustainable development. [ABSTRACT FROM AUTHOR]

Abstract The context of rapid global environmental change underscores the pressing necessity to investigate the environmental factors and high-risk areas that contribute to the occurrence of brucellosis. In this study, a maximum entropy (MaxEnt) model was employed to analyze the factors influencing brucellosis in the Aksu Prefecture from 2014 to 2023. A distributed lag nonlinear model (DLNM) was employed to investigate the lagged effect of meteorological factors on the occurrence of brucellosis. A total of 17 environmental factors were identified as affecting the distribution of brucellosis to varying degrees. The largest contributing was the normalized difference vegetation index (NDVI), followed by gross domestic product (GDP), and then meteorological factors such as average temperature, average relative humidity, and average wind speed. The receiver operating characteristic (ROC) curve demonstrated that the MaxEnt model exhibited a high degree of predictive efficacy, with an area under the curve (AUC) value of 0.921. The impact of high temperature (25℃ with a 2-month lag, RR = 3.130, 95% CI 1.642 ~ 5.965), low relative humidity (28% with a 2.5-month lag, RR = 1.795, 95% CI 1.298 ~ 2.483), and low wind speed (1.9 m/s with a 0-month lag, RR = 2.408, 95% CI 1.360 ~ 4.264) are the most significant meteorological factors associated with the incidence of brucellosis. The trends in the impact of extreme meteorological conditions on the spread of brucellosis were found to be generally consistent. Stratified analyses indicated that males were more affected by meteorological factors than females. The prevalence of brucellosis is influenced by a range of socio-economic and meteorological factors, and a multifaceted approach is necessary to prevent and control brucellosis.

Cultivation is advocated as a solution for the sustainable exploitation of medicinal plants. Understanding environmental factors influencing plant species distribution will eliminate the indiscriminate introduction of medicinal plants to inappropriate cultivation regions. This study investigated environmental conditions for the distribution of Artemisia afra and mapped out potential areas for its cultivation in South Africa. Soil samples were collected for analysis in the Free State Province in South Africa. To identify suitable environmental conditions for the natural distribution of A. afra, the South African National Botanical Institute database and physically collected Global Positioning System points were used in a maximum entropy model. Monthly long-term average interpolated weather surfaces were used to estimate the effect of climate change on future climate suitability for A. afra distribution. Sixty-one percent of soil samples from different A. afra populations were clay loam soils with a slightly acidic to neutral pH. The carbon source utilization, Shannon Weaver Index, and species richness were positively correlated with one group of fourteen soil samples, and species evenness was positively correlated with the second group, consisting of four samples. Climate change will only affect the distribution of A. afra in the very long term. The current study provides critical information for identifying suitable cultivation areas for A. afra while supporting conservation efforts from an ecological point of view.

Abstract The eco-industry is an effective path to achieve ecological and economic sustainable development. However, the role played by Rosa roxburghii Tratt (R. roxburghii) industry in karst desertification control still needs to be determined. In this study, we predict the suitability probability and driving variables of R. roxburghii's distribution through a Maximum Entropy model, combining climate, population, vegetation, and soil data, and conducted a sample plot survey in a high-suitability area to explore the role of the R. roxburghii industry in ecological services by using adjacent non-R. roxburghii patches as comparisons. The results showed that South China Karst, with its simultaneous rain and heat climate characteristics, was the most suitable area for the industrialization of R. roxburghii in the world. In South China Karst, the area of no, low, medium, and high suitability zones for R. roxburghii was 4.2 × 105, 6.12 × 105, 4.64 × 105, and 4.42 × 105 km2, respectively, and population distribution was the dominant variable controlling its distribution. The net primary productivity, soil conservation, water conservation, mean species abundance, and aboveground biomass of the R. roxburghii monoculture plot in the high-suitability area were significantly lower than those of adjacent non-R. roxburghii lands and forest patches. Furthermore, the monoculture had higher trade-offs between provision, regulation, and support service. This study found that the monoculture of R. roxburghii industry, dominated by human activities, failed to improve ecological services and exacerbated the trade-offs between services. Therefore, future karst desertification control still needs to follow the agroforestry development path.

Introduction: Astragali Radix is the dried root of Astragalus mongoliae or Astragalus membranaceus, a leguminous plant. Since ancient times, Astragali Radix has been widely used in Chinese traditional Chinese medicine. As people become more health-conscious, the market demand for Astragali Radix grows and its popularity is increasing in the international market. As an important medicinal plant, the growth of Astragali Radix is strongly influenced by environmental conditions. In order to meet the market demand for high quality Astragali Radix herbs, it is necessary to search and find areas suitable for the growth of Astragali Radix. Methods: In this study, we assessed the potential impacts of climate change on the distribution of the Chinese medicinal plant Astragali Radix using the maximum entropy (MaxEnt) model in combination with a geographic information system(GIS). Distribution data and environmental variables were analyzed to predict suitable areas for Astragali Radix under the SSP126, SSP245 and SSP585 scenario for current and future (2041-2060, 2061-2080, 2081-2100). Jackknife is used to assess the importance of environmental variables, and environmental variables with a model contribution greater than 5% were considered to be the main drivers. Results: The results showed that the current area of suitable area for Astragali Radix is 188.41 km2, and the three climate scenarios show an increasing trend in the future, with a maximum of 212.70 km2. North China has always been the main suitable area, while the area of suitable area in Southwest China is decreasing, and Xinjiang will be developed as a new suitable area in the future. Annual precipitation (41.6%), elevation (15.9%), topsoil calcium carbonate (14.8%), annual mean temperature (8.3%), precipitation seasonality (8%) and topsoil pH (6%) contributed more to the model and were the main environmental influences on the distribution of Astragali Radix. In addition, the centroids of the suitable areas shifted northward under all three climate scenarios, indicating a migratory response to global warming. Discussion: Our study found that suitable area of Astragali Radix has been expanding for most of the time in each period of the three climate scenarios compared with the current situation. In the future, humans can focus on enhancing the cultivation techniques of Astragali Radix in these suitable areas. This study provide a scientific basis for the development of planting strategies and spatial distribution management of Astragali Radix. It helps to optimize the selection of planting areas and resource conservation of Chinese herbs. [ABSTRACT FROM AUTHOR]

Simple Summary: To investigate the effects of air pollutants and bioclimatic variables on tuberculosis in domestic ruminants, we simulated the risk distribution of tuberculosis in cattle, buffaloes, sheep, and goats in China using the maximum entropy ecological niche model, and evaluated the effects of environmental factors. The risk factors that most significantly influenced the prevalence of tuberculosis were the nitrogen dioxide (NO2) level, mean temperature of the coldest quarter, cattle distribution density, sheep distribution density, ozone (O3) level, and precipitation of the driest month. The predicted map of tuberculosis risk in cattle, buffaloes, sheep, and goats indicated that the high-risk regions were mainly distributed in South, North, East, and Northwest China. The findings of this study provide a valuable reference for the prevention and control of tuberculosis in cattle, buffaloes, sheep, and goats in China. Tuberculosis is a zoonotic chronic respiratory infectious disease caused by the Mycobacterium tuberculosis complex. The outbreak and epidemic of tuberculosis can seriously threaten human and veterinary health. To investigate the effects of environmental factors on tuberculosis in domestic ruminants, we collected data regarding the prevalence of tuberculosis in cattle, buffaloes, sheep, and goats in China (1956–2024) from publicly published literature and available databases. We identified the key risk factors among six major air pollutants and 19 bioclimatic variables; simulated the risk distribution of tuberculosis in cattle, buffaloes, sheep, and goats in China using the maximum entropy ecological niche model; and evaluated the effects of environmental factors. The area under the curve of the model was 0.873 (95% confidence interval, 0.851–0.895). The risk factors that most significantly influenced the prevalence of tuberculosis were the nitrogen dioxide (NO2) level, mean temperature of the coldest quarter, cattle distribution density, sheep distribution density, ozone (O3) level, and precipitation of the driest month. The predicted map of tuberculosis risk in cattle, buffaloes, sheep, and goats indicated that the high-risk regions were mainly distributed in South, North, East, and Northwest China. Improved surveillance is needed in these high-risk areas, and early preventive measures must be implemented based on the risk factors identified to reduce the future prevalence of tuberculosis in cattle, buffaloes, sheep, and goats. [ABSTRACT FROM AUTHOR]

The eco-industry is an effective path to achieve ecological and economic sustainable development. However, the role played by Rosa roxburghii Tratt (R. roxburghii) industry in karst desertification control still needs to be determined. In this study, we predict the suitability probability and driving variables of R. roxburghii's distribution through a Maximum Entropy model, combining climate, population, vegetation, and soil data, and conducted a sample plot survey in a high-suitability area to explore the role of the R. roxburghii industry in ecological services by using adjacent non-R. roxburghii patches as comparisons. The results showed that South China Karst, with its simultaneous rain and heat climate characteristics, was the most suitable area for the industrialization of R. roxburghii in the world. In South China Karst, the area of no, low, medium, and high suitability zones for R. roxburghii was 4.2 × 105, 6.12 × 105, 4.64 × 105, and 4.42 × 105 km2, respectively, and population distribution was the dominant variable controlling its distribution. The net primary productivity, soil conservation, water conservation, mean species abundance, and aboveground biomass of the R. roxburghii monoculture plot in the high-suitability area were significantly lower than those of adjacent non-R. roxburghii lands and forest patches. Furthermore, the monoculture had higher trade-offs between provision, regulation, and support service. This study found that the monoculture of R. roxburghii industry, dominated by human activities, failed to improve ecological services and exacerbated the trade-offs between services. Therefore, future karst desertification control still needs to follow the agroforestry development path. [ABSTRACT FROM AUTHOR]

Cultivation is advocated as a solution for the sustainable exploitation of medicinal plants. Understanding environmental factors influencing plant species distribution will eliminate the indiscriminate introduction of medicinal plants to inappropriate cultivation regions. This study investigated environmental conditions for the distribution of Artemisia afra and mapped out potential areas for its cultivation in South Africa. Soil samples were collected for analysis in the Free State Province in South Africa. To identify suitable environmental conditions for the natural distribution of A. afra, the South African National Botanical Institute database and physically collected Global Positioning System points were used in a maximum entropy model. Monthly long-term average interpolated weather surfaces were used to estimate the effect of climate change on future climate suitability for A. afra distribution. Sixty-one percent of soil samples from different A. afra populations were clay loam soils with a slightly acidic to neutral pH. The carbon source utilization, Shannon Weaver Index, and species richness were positively correlated with one group of fourteen soil samples, and species evenness was positively correlated with the second group, consisting of four samples. Climate change will only affect the distribution of A. afra in the very long term. The current study provides critical information for identifying suitable cultivation areas for A. afra while supporting conservation efforts from an ecological point of view. [ABSTRACT FROM AUTHOR]

Ginkgo biloba L. was named by Carl Linnaeus in 1771; a "living fossil" with immense medicinal and conservation value, it is a nationally first-class protected wild plant. However, many Ginkgo populations are under threat from habitat destruction, human exploitation, and over-harvesting, which have limited their numbers and range. Using an optimized MaxEnt model in R, this study analyzed Ginkgo distribution points and 22 ecological factors in China to explore the key environmental factors affecting its geographical distribution. The study also predicted the spatial distribution patterns and centroid changes of potential suitable areas under three different carbon emission pathways: current conditions, 2021–2040 (2030s), 2041–2060 (2050s), and 2061–2080 (2070s). The findings are as follows: (1) The optimal combination of model parameters (RM = 3.2, FC = LPH) reduced model complexity and overfitting and achieved very high prediction accuracy with an optimized AUC value of 0.928. (2) The key environmental factors influencing Ginkgo growth include precipitation in the driest month (20–175 mm), minimum temperature in the coldest month (−4 to 3 °C), precipitation in the hottest quarter (450–2500 mm), and a temperature seasonal variation deviation greater than 580. (3) Under the three future climate scenarios (SSP126, SSP245, and SSP585), the potential suitable habitat area for Ginkgo in China was increased, with the distribution range migrating to higher latitudes, Under the three different development models, the total suitable area followed this order: SSP126 > SSP245 > SSP585. Highly and moderately suitable areas are concentrated in the Yangtze River Basin. This study is highly significant for the ecological protection of Ginkgo, aiding in the rational planning of potential suitable areas, enhancing the monitoring of key conservation areas, and developing effective protection strategies in a timely manner. [ABSTRACT FROM AUTHOR]

This paper utilized methods such as the MaxEnt model and ArcGIS, selected 47 actual planting points of Brassica juncea var. tumida and 20 environmental impact factors, and combined with the data of three future climate scenarios introduced by CMIP6 to predict the suitable climate areas of Brassica juncea var. tumida in Chongqing in the 2050s (2041−2060) and 2070s (2061−2080), providing a scientific reference for the planning and layout of Brassica juncea var. tumida planting in Chongqing. The results showed that the MaxEnt model provided excellent predictions. The cumulative contribution of dominant factors reached as high as 88.3%, including precipitation of the wettest month, annual precipitation, altitude, mean temperature of the coldest season, annual mean temperature and temperature annual range. The threshold of those factors was 178−185mm, 1170−1225mm, 100−380m, 7.8−9.0℃, 17.5−18.6℃ and 27.6−28.6℃, respectively. Under current conditions, Brassica juncea var. tumida had 11.6% of the suitable areas, including 1422 km² of the highly suitable area and 1.7% were in Fuling, Fengdu, and Zhongxian. Under the SSP1−2.6, SSP2−4.5 and SSP5−8.5 climate scenarios, in the 2050s the suitable areas amounted to 11.0%, 11.4% and 11.2%, respectively, and in the 2070s the suitable areas amounted to 10.8%, 10.6% and 9.6%. Future climate change will have adversely affect the planting and development of Brassica juncea var. tumida. To reduce these adverse effects, suitable planting areas should be selected. [ABSTRACT FROM AUTHOR]

Climate change can significantly impact the ecological suitability and diversity of species. Pyrethrum tatsienense, a critically endangered species in China, requires a thorough understanding of its habitat distribution and the environmental factors that affect it in the context of climate change. The Maxent algorithm was used to examine the key factors influencing the distribution of P. tatsienense in China, using data from 127 species occurrences and environmental variables from the Last Interglacial (LIG), Last Glacial Maximum (LGM), Mid‐Holocene (MH), current, and future scenarios. The Maxent model was optimized utilizing the R package ENMeval, providing the most accurate predictions for suitable habitats across various scenarios. Results show that suitable regions for P. tatsienense encompass approximately 15.02% (14.42 × 105 km2) of China, predominantly on the Qinghai‐Tibetan Plateau. The mean UV‐B of the highest month (UVB3: 39.7%), elevation (elev: 28.7%), and the warmest season of precipitation (Bio18: 17.4%) are the major limiting factors for suitable habitat. The optimal species distribution ranges are identified as > 7500 J m−2 day−1 for UVB3, 2700–5600 m for elev, and 150–480 mm for Bio18. Predictions for the historical climate indicate the presence of refugia at the junction of Sichuan, Tibet, and Qinghai. The MH predictions show an increase in climatic suitability for P. tatsienense compared to the LIG and LGM, with an expansion of suitable areas westward. Future climate change scenarios indicate that the potential suitable habitat for P. tatsienense is expected to increase with increasing radiative forcing, with higher latitude regions becoming new marginally suitable habitats. However, predicted environmental changes in western Tibet may drive the loss of highly suitable habitats in the future. These findings enhance our understanding of how environmental factors impact the habitat suitability of P. tatsienense and provide valuable insights for developing effective management and conservation strategies for this important species. [ABSTRACT FROM AUTHOR]

Copyright of Marine Fisheries: Jurnal Teknologi & Manajemen Perikanan Laut is the property of IPB University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Ecology & Rural Environment is the property of Journal of Ecology & Rural Environment Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Climate change is becoming an important driver of biodiversity loss by altering the habitat, distribution and interspecific relationships of species. Japanese yew (Taxus cuspidata) is a first class protected plant in China, which has important ecological significance and occupies a certain position in the feeding habit of wapiti (Cervus elaphus) and Siberian roe deer (Capreolus pygargus). Due to human and animal damage, the number of Japanese yew has gradually decreased. Therefore, understanding the potential distribution of Japanese yew and the suitable areas for deer to browse on it under climate change will help to further protect these three species in Northeast China, especially migrate to more suitable areas in different scenarios in the future. From July 2021 to July 2024, we collected the information of species distribution and the variables associated with the species' ecological limits in Muling National Nature Reserve to cross-reflect the current and future distribution and feeding area of the two species to assess each other's impacts with Maximum entropy model (MaxEnt). The results showed that under the SSP2-4.5 and SSP5-8.5 scenarios, feeding pressure, driest quarter precipitation (BIO17) and seasonal temperature variation coefficient (BIO4) were the main variables affecting the distribution of Japanese yew, and the driest quarter precipitation (BIO17) and annual precipitation (BIO12) were the main variables affecting wapiti and Siberian roe deer foraging them. Under SSP2-4.5 and SSP5-8.5 scenarios, the suitable area of Japanese yew and the feeding area of the two species of deer gradually decreased from 2041 to 2100. Compared with wapiti, Siberian roe deer has a greater impact on the distribution range of Japanese yew, and the suitable feeding area is wider. It is expected that the potential centroid of Japanese yew, wapiti and Siberian roe deer will migrate to higher latitudes in the future. These findings provide a scientific basis for the reserve to develop relevant measures and plans and effectively protect the three species. [ABSTRACT FROM AUTHOR]

The electronic, magnetic and optical properties of the double perovskites Ca2NiOsO6 and Fe-doped derivative were calculated using the full potential linearized augmented plane wave technique through the GGA + U with PBE exchange correlation functionals. The calculations show that both of the systems are half-metallic with Fe-doped system as a ferromagnet, whereas the undoped system shows the ferrimagnetic ordering. Additionally, the study is extended for calculating the Mott parameters through dynamical mean field theory (DMFT) with the maximum entropy model (MEM). It is found that the MIT model parameters (U, β) for Ca2NiOsO6 and Ca2Fe 0. 5 0 Ni 0. 5 0 OsO6 systems are (5.7 eV, 6.0 (eV) − 1 ) and (6.0 eV, 6.0 (eV) − 1 ), respectively. Furthermore, the calculations agree with optical Drude peak analysis. The optical conductivity, reflectivity, absorptivity, ELOSS function, dielectric function refractive index and sum-rule are also explored in relation to the photoinduced behaviors of the materials. [ABSTRACT FROM AUTHOR]

Simple Summary: Giant water bugs play an important role as top predators in wetland ecosystems, helping to control freshwater snails and mosquitoes. In this study, we used MaxEnt models to predict how climate change might affect the distribution of two Korean species, Appasus japonicus and Diplonychus esakii. Our findings suggest that A. japonicus may lose habitat and shift northward, while D. esakii is expected to expand its range, potentially causing occupancy turnover between the two species. The range shifts of the two species are primarily driven by different factors—elevation for A. japonicus and annual mean temperature for D. esakii. This research helps us understand how climate change could affect two giant water bugs and supports efforts to manage and conserve wetland ecosystems in South Korea. Giant water bugs (Hemiptera: Belostomatidae) are top predators in wetland ecosystems, serving as biological indicators of the health of lentic ecosystems and as effective biological control agents for freshwater snails and mosquitoes. This study aimed to predict the current and future distribution of two Korean giant water bugs, Appasus japonicus and Diplonychus esakii, under three climate change scenarios, contributing to the sustainable management of wetland ecosystems in South Korea. Using MaxEnt models, we employed seven climatic and three non-climatic variables to investigate the habitat preferences and distribution patterns of the species. The results revealed that A. japonicus is likely to experience a northward range contraction due to climate change, while D. esakii is predicted to expand its distribution northward without losing its current range. These responses may lead to occupancy turnover between the two species, potentially driving reassembly in aquatic organism community. Elevation was the primary factor influencing the distribution of A. japonicus, whereas annual mean temperature was the most informative variable for D. esakii, both factors derived under the current climate conditions. These findings suggest that both species are highly sensitive to climate change, with potential range shifts toward higher latitudes and elevations. This study provides insights into how climate change could impact two giant water bugs, thereby supporting future efforts to manage and conserve wetland ecosystems in this country. [ABSTRACT FROM AUTHOR]

Simple Summary: Insect declines have been linked to rising temperatures and aridification due to global climate change. These declines impact ecosystems, as many flowering plants rely on insect pollinators like bees for reproduction. However, desert organisms, which are well-adapted to hot and arid conditions, may respond differently to environmental changes compared to those in non-desert environments. In this study, we estimate the overlapping suitable habitat for the desert pallid bee (Centris pallida) and three of its host plants—the desert ironwood (Olneya tesota), blue palo verde (Parkinsonia florida), and yellow palo verde (Parkinsonia microphylla)—under current and forecasted climate conditions using maximum entropy modeling (MaxEnt). MaxEnt creates predictions of where a species is most likely to reside in novel or known areas based on the environmental variables at locations of observed occurrences. We found that C. pallida and its host plants may exhibit resilience to warming temperatures from a moderate increase in greenhouse gasses as projected by climate models, resulting in a slight northern expansion of suitable habitats shifted to higher average altitudes where all four species may exist. This study might serve as a reference for future modeling studies and insight into the resilience of desert-dwelling pollinators. Wild bees are vital for the pollination of native plants and crops, providing essential ecosystem services. Climate change is known to impact biodiversity and species distributions, but insects adapted to desert ecosystems may exhibit unique physiological, behavioral, and evolutionary responses. The desert pallid bee (C. pallida), a solitary bee native to the arid southwestern United States and northern Mexico, primarily forages on yellow palo verde (P. microphylla), blue palo verde (P. florida), and desert ironwood (O. tesota). This study used MaxEnt to estimate the current and projected geographical overlap of suitable habitats for C. pallida and its host plants. Here, we used MaxEnt to estimate the current and forecasted overlapping geographically suitable habitat of C. pallida with all three host plants. We forecasted potential environmentally suitable areas for each species to the year 2040 using the current distribution model and climate projections with moderate CO2 levels. We found a continued spatial alignment in the suitable area of the bee and its host plants with a 70% increase in the range overlap area, though shifted to higher average altitudes and a slight northern expansion. These findings may provide insight to stakeholders on the conservation needs of desert-dwelling pollinators. [ABSTRACT FROM AUTHOR]

The foraging strategies of sympatric ungulates with similar ecological niches are important for understanding ecological niche differentiation, resource utilization, competition, and coexistence and for understanding the ecological impacts on plant communities in the ecosystem. The behavior of the wapiti (Cervus elaphus) and Siberian roe deer (Capreolus pygargus) foraging on Japanese yew (Taxus cuspidata) has affected its succession and renewal in the northeastern forests of China, which has become an urgent problem for the relevant departments. This study analyzed the foraging strategies of the wapiti and Siberian roe deer on Japanese yew from July 2021 to January 2024 using field investigations and infrared camera monitoring in the Muling National Nature Reserve, Heilongjiang Province, China. It was found that the wapiti and Siberian roe deer have different foraging strategies in terms of time, space, and behavior. Temporally, they both preferred to forage for the saplings of the Japanese yew during the winter season, the degree of overlap in foraging rhythms was medium (Dhat1 = 0.67), and the diurnal foraging activity index (DRAI) of the wapiti was larger than that of the Siberian roe deer. Spatially, the suitable foraging habitat of the Siberian roe deer was twice that of the wapiti, and their overlap was low in the location and direction of saplings and the distance of the seed tree. Behaviorally, the foraging intensity of the wapiti was high, and that of Siberian roe deer was low. Foraging reduced the average primary branch height, number of new branches, and length of lateral branches of saplings, and the influence of the wapiti was significantly greater than that of the Siberian roe deer. This study provides a scientific basis for solving the conservation and management problems of the deer animals foraging on Japanese yew and contributes to further understanding of the competition‐coexistence mechanism of sympatric species. [ABSTRACT FROM AUTHOR]

Ephedra sinica (E. sinica) holds significant economic and medicinal importance and is predominantly found in arid areas. Due to the limitations of environmental variables, growth habits, and human activities, the production and suitability areas of E. sinica have significantly decreased, especially in the five northwestern provinces of China. In this study, 212 distribution points of E. sinica and 40 environmental variables were obtained to project the habitat suitability of E. sinica under different emission scenarios in the future. It identified precipitation in the wettest month, monthly mean of the diurnal temperature difference, and solar radiation intensity in April and July as the primary environmental factors affecting the suitability of E. sinica in the region. The areas of high, medium, and low suitability in the region cover 103,000 km2, 376,500 km2, and 486,800 km2. Under future scenarios, the suitability areas from 2021 to 2100 will decrease by 20%, with high suitability areas decreasing by 65% to 85% particularly. With comprehensive environmental variables, the suitability areas of E. sinica from 2021 to 2100 are projected, filling the gap in the projection of E. sinica suitability areas in the five northwestern provinces of China over long time period. The suitability areas show a significant decreasing trend. This research provides valuable insights into the suitability areas and crucial environmental factors, offering theoretical support for future protection and management efforts for E. sinica. [ABSTRACT FROM AUTHOR]

China's rare and endangered bamboo species belonging to the Indocalamus genus, specifically Indocalamus decorus Q. H. Dai, Indocalamus hirsutissimus Z. P. Wang & P. X. Zhang, and Indocalamus pedalis (Keng) P. C. Keng, possess notable value in biodiversity conservation and have significant potential for use in landscape design. Using an enhanced MaxEnt model, this study forecasted shifts in the species' potential range under four separate climate scenarios (SSP1-RCP2.6, SSP2-RCP4.5, SSP3-RCP7.0, and SSP5-RCP8.5), considering both the historical period (1970–2000, referred to as "the current period") and upcoming timeframes (2021–2040, 2041–2060, 2061–2080, and 2081–2100). The analysis disclosed that the present total potential habitat area for these species is approximately 251.79 × 104 km2, with high, medium, and low suitability areas occupying 0.15 × 104 km2, 125.39 × 104 km2, and 126.26 × 104 km2, respectively. The minimum temperature of the coldest month emerged as the critical determinant of their potential habitat distribution. Expected climate changes are likely to increase the suitable habitat for these species, although areas with low suitability might slightly diminish, with Guizhou and Chongqing showing the least impact. The distribution centers of suitable habitats for the three plant species consistently exhibit a westward shift under various climate scenarios. These results contribute valuable insights for the spatial distribution, continuous monitoring, sustainable management, and ex situ conservation in response to climate change. [ABSTRACT FROM AUTHOR]

Michelia lacei W.W. Smith, a magnolia species categorized as Endangered on the IUCN Red List, is subject to severe disturbance. We carried out field surveys and a review of literature records to present a detailed description of the current status of M. lacei. We then predicted the potential distribution of M. lacei under different climatic scenarios based on 60 occurrence records (53 recorded during our field surveys and 7 earlier records) and 19 bioclimatic variables from the WorldClim database. We selected 18 locations and four bioclimatic variables for model training. Temperature seasonality and annual temperature range were the most influential variables for predicting the potential distribution of the species. We used MaxEnt to model distribution under current climate conditions and four Shared Socioeconomic Pathway scenarios in four future time periods to determine the effects of future climate change on the habitat suitable for the species. We predict areas of moderately and highly suitable habitat will gradually decrease over time. We recommend increased in situ and ex situ conservation efforts to mitigate this habitat decline and protect populations of M. lacei.

Abstract As an important fishery resource and endangered species, studying the habitat of Coilia nasus (C. nasus) is highly significant. This study used fishery survey data from southern Zhejiang coastal waters from 2016 to 2020, employing a maximum entropy model (MaxEnt) to map the habitat distribution of C. nasus. Model performance was evaluated using two metrics: the area under the curve (AUC) of the receiver operating characteristic curve for the training and test sets and true skill statistics (TSS). This study aimed to predict the habitat distribution of C. nasus and explore how environmental variables influence habitat suitability. The results indicated that the models for each season had strong predictive performance, with AUC values above 0.8 and TSS values exceeding 0.6, indicating that they could accurately predict the presence of C. nasus. In the study area, C. nasus was primarily found in brackish or marine waters near bays and coastal islands. Among all environmental factors, salinity (S) and bottom temperature (BOT) had the highest correlations with habitat distribution, although these correlations varied across seasons. The findings of this study provide empirical evidence and a reference for the conservation and management of C. nasus and for the designation of its protected areas.

To reveal the response of flue-cured tobacco suitable planting regions in Yunnan Province to climate change， the distribution characteristics of flue-cured tobacco suitable planting regions in Yunnan Province under contemporary climate conditions were studied by using maximum entropy （MaxEnt） model， which was based on the measured distribution data of flue-cured tobacco in Yunnan Province and the relevant environmental variable data.Furthermore， the change of suitable planting areas for flue-cured tobacco in Yunnan under future climate change conditions was analyzed.The results showed： （1） According to order of contribution of environmental variables to Yunnan flue-cured tobacco cultivation， the dominant environmental variables affecting Yunnan order of contribution of environmental variables to Yunnan flue-cured tobacco cultivation cultivation were， in order， the average precipitation in May， the average temperature in the hottest season， the classification of soil texture， and the content of soil carbonate.The cumulative contribution rate of such four items reached 80.9%， and the overall impact of climate variables on planting flue-cured tobacco in Yunnan is higher than that of soil variables.（2） In the current conditions， the suitable planting regions of flue-cured tobacco in Yunnan Province are mainly in Qujing， Kunming， Chuxiong， Zhaotong， Dali， Baoshan， Linchang， eastern Yuxi， northcentral Honghe， northwest Wenshan， also scattered in southern Lijiang and central Pu’er.The total suitable area is 23.82×106 hm2， accounting for 60.44% of the land area of Yunnan province.（3） Under the RCP4.5 and RCP8.5 emission scenarios， the area of suitable planting areas of flue-cured tobacco showed an increasing trend in different degrees， increasing to 28.28×106 hm2 and 26.09×106 hm2， respectively， accounting for 71.76% and 66.19% of the total area of the province.The displacement of the center of mass （geometric center） of the total suitable planting area along the easterly-northerly direction， and this displacement was mainly caused by the migration of the centroids in the highly suitable planting regions.

Michelia lacei W.W. Smith, a magnolia species categorized as Endangered on the IUCN Red List, is subject to severe disturbance. We carried out field surveys and a review of literature records to present a detailed description of the current status of M. lacei. We then predicted the potential distribution of M. lacei under different climatic scenarios based on 60 occurrence records (53 recorded during our field surveys and 7 earlier records) and 19 bioclimatic variables from the WorldClim database. We selected 18 locations and four bioclimatic variables for model training. Temperature seasonality and annual temperature range were the most influential variables for predicting the potential distribution of the species. We used MaxEnt to model distribution under current climate conditions and four Shared Socioeconomic Pathway scenarios in four future time periods to determine the effects of future climate change on the habitat suitable for the species. We predict areas of moderately and highly suitable habitat will gradually decrease over time. We recommend increased in situ and ex situ conservation efforts to mitigate this habitat decline and protect populations of M. lacei. [ABSTRACT FROM AUTHOR]

This study predicted the potential habitats of Monochamus alternatus, a known vector of Bursaphelenchus xylophilus, utilizing its occurrence points and environmental variables—ecoclimatic indices and terrain variables. SSP2-4.5 and SSP5-8.5 scenarios were applied to predict the potential habitat under climate change. We secured the 20,514 occurrence points of Monochamus alternatus among the points with geographic coordinates of PWD-affected trees (2017–2022). The maximum entropy model (MaxEnt) and ensemble model (ensemble) were used to identify and compare the variability of potential habitats in the baseline period, near future, intermediate future, and distant future. At the outset, both the MaxEnt and the ensemble models showed a high model fit, and the ensemble was judged to be relatively superior. Next, both models showed that the habitat will expand northward according to climate change scenarios. Finally, the binary maps were superimposed to examine the differences between individual and multiple models; both models showed similar distributions in the baseline period and near future. Nonetheless, MaxEnt tended to overestimate expansion in the intermediate and far future. In the future, it is expected that the accuracy and reliability of forecasts can be improved by building optimized models to reduce uncertainty by supplementing field data and collaborating with model experts. [ABSTRACT FROM AUTHOR]

Turkey is the leading producer of pine honey worldwide, accounting for 90% of global production, largely due to the presence of Marchalina hellenica populations. However, in recent years, devastating forest fires have caused substantial damage to Pinus brutia forests and M. hellenica populations, leading to a dramatic decline in pine honey production areas. The urgency for early intervention procedures against forest fires and relocation of M. hellenica populations to other P. brutia forests has become apparent. A comprehensive assessment of 25 criteria was conducted to investigate the thresholds and behaviors of each criterion, which play a vital role in the distribution of M. hellenica, using the maximum entropy model (MaxEnt). To evaluate the impact of forest fires on the distribution of M. hellenica, the potential locations of pine honey production areas were determined for 2022. Furthermore, the susceptibility of forest fires was modeled for all pine honey production months. The findings revealed that forest fires have destroyed 384.9 km2 (12.8% of the total pine honey production area), predominantly in August and September, with the most severe damage in Marmaris (156 km2) and significant impacts in Ula, Köyceğiz, and Milas. The analysis facilitates the estimation of new areas suitable for M. hellenica and pine honey production while providing valuable insights into strategies for mitigating forest fires and formulating proactive protection protocols. [ABSTRACT FROM AUTHOR]

Introduction: Mangroves are an important component of coastal ecosystems, and determining the spatial dispersion of prevalent mangrove species and the most suitable land-use source for mangrove growth is of great importance for judicious restoration and effective conservation approaches. Maximum entropy (MaxEnt) models are well suited for this task; however, the default parameterization such models for distribution prediction has limitations and may produce results with low accuracy, requiring elucidation of useful parameter settings. Further, a focus on predicting only the mangrove distribution is insufficient for mangrove restoration, and clarification of suitable habitats is required. Here, we examined the geographical distribution of six mangrove species in Beihai, China (Aricennia marina, Aegiceras corniculatum, Kandelia obovata, Rhizophora stylosa, Bruguiera gymnorrhiza, and Acanthus ilicifolius). Methods: We used the ENMTools tool to select 16 variables from environmental factors, including bioclimate, terrain, sediment type, land-use classification, and sea-surface salinity and temperature. Using the selected variables and mangrove distribution data, a MaxEnt model optimized using the "kuenm" package in R was used to establish a mangrove prediction distribution model for Beihai City. Transition analyses of land-use types within suitable zones further clarified their current and potential functional roles. Results and discussion: The spatial occurrences of A. marina, A. corniculatum, and K. obovata were strongly driven by topographical features, those of R. stylosa and B. gymnorrhiza mostly depended on bioclimatic variables, and that of A. ilicifolius was driven mostly by edaphic conditions, notably the substrate type. The predicted optimal suitable area for mangrove growth in Beihai City was 50.76km2, of which 55.04% are currently officially protected. Unprotected areas suitable for mangrove growth were mainly located in Lianzhou Bay, Tieshangang Bay, Dafengjiang, and Xicun Port. The majority of these regions were derived from land-use transitions from wetlands and aquaculture ponds to forested ecosystems. We suggest that careful development of selected wetland ecosystems and transmutation of aquaculture ponds into forested landscapes are crucial for effective mangrove restoration. Our results will assist in selecting suitable species for mangrove restoration sites and improving mangrove restoration efficiency. [ABSTRACT FROM AUTHOR]

Energy landscape analysis is a data‐driven method to analyse multidimensional time series, including functional magnetic resonance imaging (fMRI) data. It has been shown to be a useful characterization of fMRI data in health and disease. It fits an Ising model to the data and captures the dynamics of the data as movement of a noisy ball constrained on the energy landscape derived from the estimated Ising model. In the present study, we examine test–retest reliability of the energy landscape analysis. To this end, we construct a permutation test that assesses whether or not indices characterizing the energy landscape are more consistent across different sets of scanning sessions from the same participant (i.e. within‐participant reliability) than across different sets of sessions from different participants (i.e. between‐participant reliability). We show that the energy landscape analysis has significantly higher within‐participant than between‐participant test–retest reliability with respect to four commonly used indices. We also show that a variational Bayesian method, which enables us to estimate energy landscapes tailored to each participant, displays comparable test–retest reliability to that using the conventional likelihood maximization method. The proposed methodology paves the way to perform individual‐level energy landscape analysis for given data sets with a statistically controlled reliability. [ABSTRACT FROM AUTHOR]

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Nicotiana tabacum L. (tobacco) has extremely high economic value, medicinal value, scientific research value and some other uses. Though it has been widely cultivated throughout the world, classification and change of its suitable habitats is not that clear, especially in the context of global warming. In order to achieve rational cultivation and sustainable development of tobacco, current (average from 1970-2000) and future (2070, average from 2061-2080) potential suitable habitats of Nicotiana tabacum L. were forecasted with MaxEnt model and ArcGIS platform based on 854 occurrence data and 22 environmental factors in this study. The results revealed that mean temperature of warmest quarter (bio10), annual precipitation (bio12), solar radiation in September (Srad9), and clay content (CLAY) were the four decisive environment variables for the distribution of Nicotiana tabacum L. Under current climate conditions, suitable habitats of Nicotiana tabacum L. were mainly distributed in south-central Europe, south-central North America, most parts of South America, central Africa, south and southeast Asia, and southeast coast of Australia, and only 13.7% of these areas were highly suitable. By the year 2070, suitable habitats under SSP1-2.6, SSP3-7.0, and SSP5-8.5 climate scenarios would all increase with the largest increase found under SSP3-7.0 scenario, while suitable habitats would reduce under SSP2-4.5 climate scenario. Globally, the center of mass of suitable habitats would migrate to southeast to varying degrees within Libya under four different climate scenarios. The emergence of new habitats and the disappearance of old habitats would all occur simultaneously under each climate scenario, and the specific changes in each area, combined with the prediction results under current climate conditions, will provide an important reference for the adjustment of agronomic practices and rational cultivation of Nicotiana tabacum L. both currently and in the future. [ABSTRACT FROM AUTHOR]

IntroductionAstragali Radix is the dried root of Astragalus mongoliae or Astragalus membranaceus, a leguminous plant. Since ancient times, Astragali Radix has been widely used in Chinese traditional Chinese medicine. As people become more health-conscious, the market demand for Astragali Radix grows and its popularity is increasing in the international market. As an important medicinal plant, the growth of Astragali Radix is strongly influenced by environmental conditions. In order to meet the market demand for high quality Astragali Radix herbs, it is necessary to search and find areas suitable for the growth of Astragali Radix.MethodsIn this study, we assessed the potential impacts of climate change on the distribution of the Chinese medicinal plant Astragali Radix using the maximum entropy (MaxEnt) model in combination with a geographic information system(GIS). Distribution data and environmental variables were analyzed to predict suitable areas for Astragali Radix under the SSP126, SSP245 and SSP585 scenario for current and future (2041-2060, 2061-2080, 2081-2100). Jackknife is used to assess the importance of environmental variables, and environmental variables with a model contribution greater than 5% were considered to be the main drivers.ResultsThe results showed that the current area of suitable area for Astragali Radix is 188.41 km2, and the three climate scenarios show an increasing trend in the future, with a maximum of 212.70 km2. North China has always been the main suitable area, while the area of suitable area in Southwest China is decreasing, and Xinjiang will be developed as a new suitable area in the future. Annual precipitation (41.6%), elevation (15.9%), topsoil calcium carbonate (14.8%), annual mean temperature (8.3%), precipitation seasonality (8%) and topsoil pH (6%) contributed more to the model and were the main environmental influences on the distribution of Astragali Radix. In addition, the centroids of the suitable areas shifted northward under all three climate scenarios, indicating a migratory response to global warming.DiscussionOur study found that suitable area of Astragali Radix has been expanding for most of the time in each period of the three climate scenarios compared with the current situation. In the future, humans can focus on enhancing the cultivation techniques of Astragali Radix in these suitable areas. This study provide a scientific basis for the development of planting strategies and spatial distribution management of Astragali Radix. It helps to optimize the selection of planting areas and resource conservation of Chinese herbs.

Anisodus tanguticus (Maxim.) Pascher, a distinctive medicinal plant native to the Qinghai-Tibet Plateau, China, has garnered attention due to increasing market demand. This study explores the impact of environmental factors on the distribution and levels of active compounds namely anisodamine, anisodine, and atropine within A. tanguticus. Our goal was to identify suitable cultivation areas for this plant. This study employs the maximum entropy model to simulate the suitable area of A. tanguticus under current conditions and three climate change scenarios during the 2050s and 2070s. The finding revealed that altitude, precipitation in the warmest season (Bio 18), the average annual temperature (Bio 1) exerted significant influences on the distribution of A. tanguticus. Among the environmental factors considered, temperature difference between day and night (Bio 2) had the most substantial impact on the distribution of anisodamine, temperature seasonal variation variance (Bio 4) predominantly influenced anisodine distribution, and Bio 1 had the greatest effected on the distribution of atropine. The suitable areas primarily exist in the eastern Qinghai-Tibet Plateau in China, encompassing a total area of 30.78 × 104 km2. Under the climate scenarios for the future, the suitable areas exhibit increasing trends of approximately 30.2%, 30.3%, and 39.8% by the 2050s, and 25.1%, 48.8%, and 60.1% by the 2070s. This research would provide theoretical suggestions for the protection, and cultivation management of A. tanguticus resources to face the challenge of global climate change. [ABSTRACT FROM AUTHOR]

Ephedra sinica and Ephedra intermedia are important medicinal plants and critical raw materials for ephedrine extraction in the pharmaceutical industry. Climate change will affect their distribution and quality. In our study, information on E. sinica and E. intermedia was collected through wilderness and online surveys. Using high-performance liquid chromatography, we determined the contents of ephedrine and pseudoephedrine. We then utilized the maximum entropy model to assess the potential impact of future climate on the distribution and quality of the two Ephedra. The results showed that the two Ephedra species were predominantly found in the arid and semiarid regions of northern China. The suitable habitats and quality area of E. intermedia will be severely degraded under RCP 2.6, RCP 4.5 and RCP 8.5 conditions and the results for E. sinica are the opposite. The accumulation of chemical components in E. sinica depends on the precipitation of the wettest month (Bio13) and soil sand content, while the accumulation of chemical components in E. intermedia depends on the mean temperature of the warmest quarter (Bio10) and the precipitation seasonality (Bio15). Overall, the research results provide the basis for the two high-quality Ephedra species for conservation and sustainable resource development. [ABSTRACT FROM AUTHOR]

The endangered semi-mangrove plant Heritiera littoralis occupies an overall area of less than 30 hm² in China. In this study, we employed the MaxEnt model to predict the distribution patterns of H. littoralis during the Last Glaciation Maximum, the present day, and the future. Drawing from 41 distributed records and 12 environmental factors within China, we investigated the species' potential habitats. To anticipate future scenarios, we assessed its distribution under the RCP4.5 greenhouse gas emission scenario for 2050 and 2070. As a result, four primary distribution areas emerged in Guangxi, Guangdong, Hainan, and Taiwan, signifying the main potential habitats for H. littoralis. Our findings indicate that the distribution centre of H. littoralis remains in Guangxi across the four time periods, with a projected eastward migration. By 2050, the species' habitat range is anticipated to contract, whereas, by 2070, the suitable habitat area is expected to expand. Moreover, we identify pivotal environmental factors influencing the potential distribution of H. littoralis, including precipitation of the warmest quarter (Bio 18), temperature seasonality (Bio 4), mean diurnal range (Bio 2), precipitation of the wettest month (Bio 13), and annual mean temperature (Bio 1). The outcomes of this study offer valuable data for comprehending the distribution of H. littoralis in China. Furthermore, they aid in pinpointing areas suitable for conservation management, both presently and in the future. [ABSTRACT FROM AUTHOR]

Jumbo flying squid Dosidicus gigas is widely distributed in the Eastern Pacific Ocean. It has a short-lived life cycle and tends to extremely respond to environmental and climate variability. In order to investigate the difference of the effects of environmental factors on habitat distribution of Dosidicus gigas in different regions in the Eastern Pacific Ocean, the present study developed a habitat distribution model for this squid in summer and autumn in the equator, off Peru and Chile. The fisheries data in the equatorial waters of the Pacific Ocean, the waters off Peru from 2016-2018, and the waters off Chile from 2015-2017 were used and obtained from National distant-water fisheries data center of China. Seven marine environmental factors including Sea surface temperature （SST）, Eddy kinetic energy （EKE）, Sea surface salinity （SSS）, Sea surface height （SSH）, Chlorophyll concentration （Chl. a）, Mixed layer depth （MLD）, and Dissolved oxygen concentration （DO） were considered in this study. The maximum entropy model （MaxEnt）was applied to investigate the distribution of suitable habitat for Dosidicus gigas and the differences in the effects of the environmental factors on it were examined in different seasons in different waters. The results showed that the AUC values of the maximum entropy model were higher than 0. 8 in different seasons in different areas, and the actual fishing locations coincided with the range of suitable habitats fitted by the model. The distribution of optimal habitats in the three regions was as follows: in the equatorial waters in summer, the optimal habitats were mainly distributed within the ranges of 110°W-120°W, 1°N-3°S; in autumn, the optimal habitats for Dosidicus gigas were mainly distributed within the ranges of 97°W-117°W, 1. 5°N-1. 5°S, and the distribution of suitable habitats was extended to the east from summer to autumn. In summer, the optimal habitats of Dosidicus gigas off Peru were mainly located in the range of 75°W-86°W, 15°S-20°S; in autumn, the optimal habitats of Dosidicus gigas were mainly located in the range of 75°W-84° W, 15° S-20° S, with the optimal habitats moving southeastward from summer to autumn. The optimal habitats of Dosidicus gigas in summer off Chile were mainly distributed in the range of 73°W-85°W, 20°S-30°S; in autumn, the optimal habitatswere mainly distributed in the range of 75°W-85°W, 20°S-28°S, and the overall suitable habitats moved to the northeast from summer to autumn. Based on the contribution rate of each environmental factor in the habitat model, SSH, Chl. a, SSS and SST were the important environmental factors affecting jumbo flying squid habitat in the equatorial waters; SSH, MLD, DO and SST were the important environmental factors affecting jumbo flying squid habitat in the offshore Peru, and SSH, SST, Chl. a and MLD were the important environmental factors affecting jumbo flying squid habitat in the offshore Chile. Our findings suggested that significant geographical difference was shown in the environmental factors affecting Dosidicus gigas distribution in different regions. [ABSTRACT FROM AUTHOR]

In this paper, an effective algorithm for optimizing the subarray of conformal arrays is proposed. The method first divides the conformal array into several first-level subarrays. It uses the X algorithm to solve the feasible solution of first-level subarray tiling and employs the particle swarm algorithm to optimize the conformal array subarray tiling scheme with the maximum entropy of the planar mapping as the fitness function. Subsequently, convex optimization is applied to optimize the subarray amplitude phase. Data results verify that the method can effectively find the optimal conformal array tiling scheme.

Ephedra sinica (E. sinica) holds significant economic and medicinal importance and is predominantly found in arid areas. Due to the limitations of environmental variables, growth habits, and human activities, the production and suitability areas of E. sinica have significantly decreased, especially in the five northwestern provinces of China. In this study, 212 distribution points of E. sinica and 40 environmental variables were obtained to project the habitat suitability of E. sinica under different emission scenarios in the future. It identified precipitation in the wettest month, monthly mean of the diurnal temperature difference, and solar radiation intensity in April and July as the primary environmental factors affecting the suitability of E. sinica in the region. The areas of high, medium, and low suitability in the region cover 103,000 km2, 376,500 km2, and 486,800 km2. Under future scenarios, the suitability areas from 2021 to 2100 will decrease by 20%, with high suitability areas decreasing by 65% to 85% particularly. With comprehensive environmental variables, the suitability areas of E. sinica from 2021 to 2100 are projected, filling the gap in the projection of E. sinica suitability areas in the five northwestern provinces of China over long time period. The suitability areas show a significant decreasing trend. This research provides valuable insights into the suitability areas and crucial environmental factors, offering theoretical support for future protection and management efforts for E. sinica.

Abstract Background Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease discovered in China in 2009. The purpose of this study was to describe the spatiotemporal distribution of SFTS and to identify its environmental influencing factors and potential high-risk areas in Shandong Province, China. Methods Data on the SFTS incidence from 2010 to 2021 were collected. Spatiotemporal scan statistics were used to identify the time and area of SFTS clustering. The maximum entropy (MaxEnt) model was used to analyse environmental influences and predict high-risk areas. Results From 2010 to 2021, a total of 5705 cases of SFTS were reported in Shandong. The number of SFTS cases increased yearly, with a peak incidence from April to October each year. Spatiotemporal scan statistics showed the existence of one most likely cluster and two secondary likely clusters in Shandong. The most likely cluster was in the eastern region, from May to October 2021. The first secondary cluster was in the central region, from May to October 2021. The second secondary cluster was in the southeastern region, from May to September 2020. The MaxEnt model showed that the mean annual wind speed, NDVI, cattle density and annual cumulative precipitation were the key factors influencing the occurrence of SFTS. The predicted risk map showed that the area of high prevalence was 28,120 km2, accounting for 18.05% of the total area of the province. Conclusions The spatiotemporal distribution of SFTS was heterogeneous and influenced by multidimensional environmental factors. This should be considered as a basis for delineating SFTS risk areas and developing SFTS prevention and control measures.

How to assess the effect of ecosystem restoration is a trending topic with all the restoration projects and ecosystem function studies in recent years. Although many studies have used different indicators and methods to evaluate ecosystem restoration effects, it needs a lot of site works to acquire the data. Low-function Platycladus orientalis forest restoration program in Beijing mountainous area has been started since 2002, in this study, the understory species of 92 plots were investigated and recorded. We assumed that the effect of ecosystem restoration would improve site conditions, especially for the soil conditions which might lead to the appearance of new species. The relationship between understory species and eleven site condition factors was elucidated by means of canonical correspondence analysis (CCA), further, specific species were chosen to represent the improvement and possible growth areas of specific species was predicted by Maximum Entropy model. Results shown that Spiraea pubescens, Deutzia parviflora, Chrysanthemum chanetii, Themeda triandra, Oplismenus undulatifolius were the main understory species which were sensitive to environmental factors, and their distribution were related to soil factors closely. The species of Spiraea pubescens, Chrysanthemum chanetii, Oplismenus undulatifolius had strong indication to soil nutrient, the appearances would happen when the comprehensive index of soil nutrient was above 81,64 and 61 respectively. The appearance of Chrysanthemum chanetii and Oplismenus undulatifolius would indicate that the soil nutrient level was in or above the range of medium, and the appearance of Spiraea pubescens would mean that the soil nutrient level was in or above the range of high in low-function Platycladus orientalis forest of Beijing mountainous area. Our study indicates that the specific species could as an indicator to reflect or evaluate the ecosystem restoration effect.

Copyright of Bulletin of Botanical Research is the property of Bulletin of Botanical Research Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Ecology & Rural Environment is the property of Journal of Ecology & Rural Environment Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The soft coral order Alcyonacea is a common coral found in the deep sea and plays a crucial role in the deep-sea ecosystem. This study aims to predict the distribution of Alcyonacea in the western Pacific Ocean using four machine learning-based species distribution models. The performance of these models is also evaluated. The results indicate a high consistency among the prediction results of the different models. The soft coral order is primarily distributed in the Thousand Islands Basin, Japan Trench, and Thousand Islands Trench. Water depth and silicate content are identified as important environmental factors influencing the distribution of Alcyonacea. The RF, Maxent, and XGBoost models demonstrate high accuracies, with the RF model exhibiting the highest prediction accuracy. However, the Maxent model outperforms the other three models in data processing. Developing a high-resolution, high-accuracy, and high-precision habitat suitability model for soft corals can provide a scientific basis and reference for China's exploration and research in the deep sea field and aid in the planning of protected areas in the high seas. [ABSTRACT FROM AUTHOR]

The purpose of this study was to analyze the characteristics of occurrence and spread of highly pathogenic avian influenza H5N1 (HPAI-H5N1) globally, understand its spatiotemporal characteristics, investigate the risk factors influencing outbreaks, and identify high-risk areas for disease occurrence. We collected the data on global poultry HPAI-H5N1 outbreaks from January 2005 to April 2023, and conducted a thorough analysis of the spatial and temporal characteristics of the disease through time series decomposition and directional distribution analysis. Additionally, an ecological niche model was established to explore the major factors influencing the occurrence of HPAI-H5N1 and to pinpoint high-risk areas. Our findings revealed that HPAI-H5N1 outbreaks were cyclical, and seasonal, exhibiting a rising trend, with a predominant northwest-southeast transmission direction. The ecological niche model highlighted that species factors and economic trade factors are critical in influencing the outbreak of HPAI-H5N1. Variables such as chicken and duck density, population density, isothermality, and road density, contributed to importantly risk of outbreaks. High-risk areas for HPAI-H5N1 occurrence were primarily identified in Europe, West Africa, Southeast Asia, and Southeast China. This study provided valuable insights into the spatial and temporal distribution characteristics and risk factors of global poultry HPAI-H5N1 outbreaks. The identification of high-risk areas provides essential information that can be used to develop more effective prevention and control policies.