Search Results (119)

Prunus sibirica L. is a key ecological and economic tree species in northern China that is threatened by habitat degradation due to climate change and human activities. To address the gaps of incomplete historical dynamics and lack of conservation integration in existing studies, we integrated MaxEnt and Zonation v4.0 to predict its suitable habitat across five periods (LIG to 2090s) and three CMIP6 SSP scenarios, identifying key drivers and priority conservation zones. The model showed high prediction accuracy (mean AUC > 0.9). Results indicated that Human Footprint (HFP), Precipitation Seasonality (Bio15), Annual Mean Temperature (Bio1), Elevation (ELEV), and Mean Temperature of the Coldest Quarter (Bio11) were the key environmental factors (cumulative contribution 91.4%), with Bio1, Bio15, Temperature Seasonality (Bio4), and HFP confirmed as major drivers (AUC > 0.8) via jackknife test. Spatiotemporally, the species’ suitable habitat contracted from the Last Interglacial to the Last Glacial Maximum and expanded to the current total suitable area of 506,620.1 km². Under future SSP scenarios, suitable habitats expanded continuously under SSP126 and SSP245 but showed a “first expansion then contraction” trend under SSP585, with a persistent northeastward migration of the habitat centroid. The vertical (altitudinal) distribution of P. sibirica showed a trend of moving to higher elevations under future warming scenarios, especially in the SSP585 scenario. High-priority conservation zones are concentrated in northern China with insufficient existing protection. It is emphasized that this study contributes to improving the adaptive capacity and genetic characterization of P. sibirica almond populations to future climate. Full article

We propose a two-level theory that connects Lin-equation-based dynamical coarse-graining of the turbulence cascade with an information-theoretic selection principle in logarithmic wavenumber space. This framework places the dissipation-range spectral shape on a verifiable logical basis rather than on ad hoc fitting. At the first (dynamical) level, we formulate an autonomous conservative Fokker–Planck equation for the normalized density and probability current. Under sufficient boundary decay and a strictly positive effective diffusion, the sign-reversed Kullback–Leibler divergence is shown to be a Lyapunov functional, yielding a rigorous H-theorem and fixing the arrow of time in scale space. At the second (selection) level, the dissipation range is treated as a stationary boundary-value problem for an open system by introducing a killing term for an unnormalized scale density. A WKB (Liouville–Green) analysis restricts the admissible tail to a stretched-exponential form and links the tail exponent to the high-wavenumber scaling of the effective diffusion. The exponential prefactor is fixed by dissipation-rate consistency, and the remaining degree of freedom is determined by one-dimensional Kullback–Leibler minimization (Hyper-MaxEnt) against a globally constructed reference distribution. The resulting exponent range is validated against the high-resolution DNS spectra reported in the literature. Full article

Mikania micrantha is one of the most detrimental invasive plant species in the southeastern coastal region of China. To accurately predict the invasion pattern of Mikania micrantha and offer guidance for production practices, it is essential to determine its precise location and the driving factors. Therefore, a design of the wavelet convolution and dynamic feature fusion module was studied, and WaveEdgeNet was proposed. This model has the abilities to deeply extract image semantic features, retain features, perform multi-scale segmentation, and conduct fusion. Moreover, to quantify the impact of human and natural factors, we developed a novel proximity factor based on land use data. Additionally, a new feature selection framework was applied to identify driving factors by analyzing the relationships between environmental variables and Mikania micrantha. Finally, the MaxEnt model was utilized to forecast its potential future habitats. The results demonstrate that WaveEdgeNet effectively extracts image features and improves model performance, attaining an MIoU of 85% and an overall accuracy of 98.62%, outperforming existing models. Spatial analysis shows that the invaded area in 2024 was smaller than that in 2023, indicating that human intervention measures have achieved some success. Furthermore, the feature selection framework not only enhances MaxEnt’s accuracy but also cuts down computational time by 82.61%. According to MaxEnt modeling, human disturbance, proximity to forests, distance from roads, and elevation are recognized as the primary factors. In the future, we will concentrate on overcoming the seasonal limitations and attaining the objective of predicting the growth and reproduction of kudzu before they happen, which can offer a foundation for manual intervention. This study lays a solid technical foundation and offers comprehensive data support for comprehending the species’ dispersal patterns and driving factors and for guiding environmental conservation. Full article

The larvae and damage symptoms of Cnaphalocrocis medinalis and Cnaphalocrocis patnalis exhibit a high degree of similarity, which often leads to confusion between the two species. This has posed challenges for research on their population dynamics and the development of effective control measures. To better understand their morphological and damage characteristics, population dynamics, species identification based on COI gene fragments, and potential future distribution, a searchlight trap monitoring program was conducted for C. medinalis and its closely related species C. patnalis across four sites in Longhua, Haitang, and Yazhou districts in Hainan Province from 2021 to 2023. The MaxEnt model was utilized to predict the potential global distribution of both species, incorporating known occurrence points and climate variables. The trapping results revealed that both species reached peak abundance between April and June, with a maximum of 1500 individuals captured in May at Beishan Village, Haitang District. Interannual population fluctuations of both species generally followed a unimodal pattern. Genetic analyses revealed distinct differences in the mitochondrial COI gene fragment, confirming that C. medinalis and C. patnalis are closely related yet distinct species. The population peak of C. patnalis occurred slightly earlier than that of C. medinalis, and its field damage was more severe. Infestations during the booting to heading stages of rice significantly reduced seed-setting rates and overall yield. Model predictions indicated that large areas of southern Eurasia are suitable for the survival of both species, with precipitation during the wettest month identified as the primary environmental factor shaping their potential distributions. At present, moderately and highly suitable habitats for C. medinalis account for 2.50% and 2.27% of the global land area, respectively, whereas those for C. patnalis account for 2.85% and 1.19%. These results highlight that climate change is likely to exacerbate the damage caused by both rice leaf-roller pests, particularly the emerging threat posed by C. patnalis. Overall, this study provides a scientific basis for invasion risk assessment and the development of integrated management strategies targeting the combined impacts of C. medinalis and C. patnalis. Full article

In struggling against invasive species ravaging riverscape ecosystems, gaps in dispersal pathway knowledge and fragmented approaches across scales have long stalled effective riparian management worldwide. To reduce these limitations and enhance invasion management strategies, selecting appropriate alien species as models for in-depth pathway analysis is essential. Alternanthera philoxeroides (Mart.) Griseb. (alligator weed) emerges as an exemplary model species, boasting an invasion record of around 120 years spanning five continents worldwide, supported by genetic evidence of repeated introductions. In addition, the clonal reproduction of A. philoxeroides supports swift establishment, while its amphibious versatility allows occupation of varied riparian environments, with spread driven by natural water-mediated dispersal (hydrochory) and human-related vectors at multiple scales. Thus, leveraging A. philoxeroides, this review proposes a comprehensive multi-scale framework, which integrates monitoring with remote sensing, environmental DNA, Internet of Things, and crowdsourcing for real-time detection. Also, the framework can further integrate, e.g., MaxEnt (Maximum Entropy Model) for climatic suitability and mechanistic simulations of hydrodynamics and human-mediated dispersal to forecast invasion risks. Furthermore, decision-support systems developed from the framework can optimize controls like herbicides and biocontrol, managing uncertainties adaptively. At the global scale, the dispersal paradigm can employ AI-driven knowledge graphs for genetic attribution, multilayer networks, and causal inference to trace pathways and identify disruptions. Based on the premise that our multi-scale framework can bridge invasion ecology with riverscape management using A. philoxeroides as a model, we contend that the implementation of the proposed framework tackles core challenges, such as sampling biases, shifting environmental dynamics, eco–evolutionary interactions using stratified sampling, and adaptive online algorithms. This methodology is purposed to offer scalable tools for other aquatic invasives, evolving management from reactive measures to proactive, network-based approaches that effectively interrupt dispersal routes. Full article

The genus Dysosma, a group of perennial herbaceous plants with significant medicinal value and a relatively narrow ecological niche, is potentially at risk due to the combined pressures of habitat degradation and climate change. As their habitats continue to degrade, all species of this genus have been included in the National Key Protected Wild Plants List (Category II). Investigating the impacts of climate change on the distribution of Dysosma resources is vital for their sustainable utilization. In this study, the potential distribution dynamics of seven Dysosma species under current and three future climate scenarios (SSP126, SSP245, SSP585) were quantified using 534 occurrence points and 25 environmental variables in a MaxEnt model, accompanied by the ecological niche overlap index (Schoener’s D), dynamic metrics (relative change rate [RCR], change intensity [CI], stability index [SI], spatial displacement rate [SDR]), and centroid migration analysis. The results indicated that (1) areas of high habitat suitability were consistently concentrated in the mountainous and hilly regions of southwestern Guizhou, Chongqing, and Hubei, with the minimum temperature of the coldest month (Bio6) and the mean diurnal temperature range (Bio2) being identified as the primary driving factors. (2) The future suitable habitat areas remained highly stable overall (SI > 97.89%), though dynamic changes varied across scenarios. Under SSP126, only slight fluctuations were observed, with an average CI of approximately 3.78% and RCR ranging from −0.46% to 1.97%. Under the SSP245 scenario, suitable habitat areas showed a continuous, slight expansion (RCR = 0.45% to 1.54%), whereas under the high-emission SSP585 scenario, a typical “mid-term expansion–late-term contraction” pattern was observed, with RCR shifting from positive (1.32%, 1.44%) to negative (−0.92%). The SI reached its lowest value of 97.89% in the late term, and the spatial displacement rate increased, signaling a reorganization of the distribution pattern. (3) High ecological niche differentiation was observed within the genus, with the highest overlap index being only 0.562, and approximately one-third of species pairs exhibiting completely non-overlapping niches. (4) Dysosma tsayuensis, a niche-specialist species, exhibited a distribution that was highly dependent on the annual mean ultraviolet-B radiation (UVB, contribution rate 52.9%), displaying an adaptation strategy markedly different from that of conservative species. (5) Centroid analysis indicated that, although the overall centroid remained stable in Guizhou, the presence of niche-specialist species under the high-emission SSP585 scenario resulted in migration paths opposite to those observed under other scenarios. The findings reveal the potential vulnerability and differential response patterns of Dysosma species under rapid climate warming, thereby providing a scientific basis for targeted conservation, in situ and ex situ conservation strategies, and population restoration. Full article

We develop a data-driven framework for analyzing how scientific concepts evolve through their empirical in-text frequency distributions in large text corpora. For each concept, the observed distribution is paired with a maximum entropy equilibrium reference, which takes a generalized Boltzmann form determined by two measurable statistical moments. Using data from more than 500,000 physics papers (about 13,000 concepts, 2000–2018), we reconstruct the temporal trajectories of the associated MaxEnt parameters and entropy measures, and we identify two characteristic regimes of concept dynamics, stable and driven, separated by a transition point near criticality. Departures from equilibrium are quantified using a residual-information measure that captures how much structure a concept exhibits beyond its equilibrium baseline. To analyze temporal change, we adapt the Hatano–Sasa and Esposito–Van den Broeck decomposition to discrete time and separate maintenance-like contributions from externally driven reorganization. The proposed efficiency indicators describe how concepts sustain or reorganize their informational structure under a finite representational capacity. Together, these elements provide a unified and empirically grounded description of concept evolution in scientific communication, based on equilibrium references, nonequilibrium structure, and informational work. Full article

Understanding alpine plants’ survival and reproduction is crucial for their conservation in climate change. This study, based on 273 valid distribution points, utilizes the MaxEnt model to predict the potential habitat and distribution dynamics of Kobresia pygmaea under both current and future climate scenarios (SSP126, SSP245, SSP370, SSP585), while clarifying the key factors that influence its distribution. The study indicates that elevation (3527.99–6054.54 m) is the dominant factor influencing its distribution. The current suitable habitat is primarily concentrated in southern and central Tibet, northwestern Sichuan, and southern Qinghai on the Tibetan Plateau, with a total area of 1.13 × 10⁵ km², of which high- and moderate-suitability areas account for 1.76 × 10⁴ km² and 3.2 × 10⁴ km², respectively. Under future climate scenarios (2050s–2070s), the overall distribution pattern remains concentrated on the Tibetan Plateau, but the suitable area exhibits a trend of initial expansion followed by contraction. By the 2050s, the total suitable area increases across all scenarios, with the most pronounced expansion under SSP126. By the 2070s, however, the total suitable area decreases under high-emission scenarios, declining by 9.50% under SSP370 and 6.76% under SSP585, respectively. The reduction in high-suitability areas is more severe, with a maximum decline of 58.75% under SSP3-7.0. Dynamic change analysis shows that approximately 70% of the current high-suitability areas remain stable by the 2050s, with range expansion occurring under low-emission scenarios toward southeastern Tibet, northwestern Sichuan, and southern Golog in Qinghai. In contrast, habitat contraction intensifies by the 2070s, particularly under the SSP5-8.5 scenario, where the reduced area reaches 1.6 times the current high-suitability extent. Centroid shift analysis indicates that the distribution center of suitable habitats migrates northward or northeastward, with a maximum displacement of 206.51 km under the SSP1-2.6 scenario by the 2050s. The results suggest that short-term climate warming may alleviate low-temperature constraints, facilitating the upward and poleward expansion of Kobresia pygmaea into higher-elevation areas. However, prolonged and intensified warming will likely lead to degradation of core habitats, posing a significant threat to its long-term persistence. This study provides a scientific basis for the conservation of alpine ecosystems on the Tibetan Plateau and for developing adaptive management strategies under climate change. Full article

The three northeastern provinces of China are the country’s most important grain-producing region, particularly for maize, soybean, and rice, and form its largest commercial grain base. Over the past two decades, cropping structures in this region have undergone notable shifts driven by both climate change and human activities. Generating long-term, high-resolution maps of multi-crop distribution and evaluating their suitability is essential for understanding cropping dynamics, optimizing land use, and promoting sustainable agriculture. In this study, we integrated multi-source satellite imagery from Landsat and Sentinel-2 to map the distribution of rice, maize, and soybean from 2000 to 2023 using a Random Forest classifier. A crop suitability assessment framework was developed by combining a multi-criteria evaluation model with the MaxEnt model. Reliable training samples were derived by overlaying suitability evaluation results with stable crop growth areas, and environmental variables—including climate, topography, soil, hydrology, and anthropogenic factors—were incorporated into MaxEnt to assess suitability. Furthermore, the spatial consistency between actual cultivation and suitability was evaluated to identify areas of misallocated land use. The results show that: (1) the six classification maps achieved an average overall accuracy of 91.05% and a Kappa coefficient of 0.857; (2) the cultivation area of all three crops expanded, with maize showing the largest increase, followed by soybean and rice, and the dominant conversion being from soybean to maize; (3) suitability areas ranked as soybean (376,692 km²) > maize (329,056 km²) > rice (311,869 km²), with substantial spatial overlap, particularly between maize and soybean, suggesting strong competition; and (4) in 2023, highly suitable zones accounted for 57.39% of rice, 39.69% of maize, and 28.89% of soybean cultivation, indicating a closer alignment between actual distribution and suitability for rice, weaker for maize, and weakest for soybean, whose suitable zones were often displaced by rice and maize. These findings provide insights to guide farmers in optimizing crop allocation and offer a scientific basis for policymakers in designing cultivated land protection strategies in Northeast China. Full article

Background: Mangrove plants are a core component of coastal ecosystems, directly influencing biodiversity and shoreline stability. However, in recent years, due to the combined pressures of human activities and climate change, nearly half of the mangrove species in China are endangered and require urgent conservation measures. This study analyzed the population dynamics and stress factors affecting four rare and endangered mangrove species—Lumnitzera racemosa, Ceriops tagal, Barringtonia racemosa, and Heritiera littoralis—on the Leizhou Peninsula, providing scientific evidence for their conservation. Methods: Field surveys and plot investigations were conducted, with population dynamics and structure quantified using static life tables, survival rates, mortality rates, and disappearance curves. Additionally, the MaxEnt species distribution model and GIS technology were applied to predict the potentially suitable distribution areas. Results: The findings revealed that the population of L. racemosa exhibits an atypical pyramid structure, with few seedlings and constraining population growth potential. The C. tagal population follows an irregular pyramid structure, with abundant seedlings but fewer mature individuals, suggesting a rapid decline followed by stability. The B. racemosa population also follows an irregular pyramid structure, with many seedlings and a greater proportion of middle-aged and older individuals, facing the risk of early mortality. The H. littoralis population is also in decline, with few seedlings and a severe risk of local extinction. MaxEnt model predictions indicated that temperature is the primary environmental factor, with Area Under the Curve (AUC) values for all species exceeding 0.8, indicating strong predictive ability. The predicted potential suitable areas showed an expanded distribution range compared to current distribution points, providing valuable references for species introduction and propagation. Conclusions: This study described the population structure of the four mangrove species on the Leizhou Peninsula and assessed their primary stress factors. The results provided a theoretical basis for the conservation and restoration of endangered mangrove species and offer important guidance for developing effective conservation strategies in southern China. Full article

In recent years, ecosystems in Saudi Arabia have experienced severe degradation due to factors such as hyperaridity, overgrazing, climate change, urban expansion, and an increase in uncontrolled wildfires. Among these, wildfires have emerged as the second most significant threat to forests after urban expansion. This study aims to map wildfire susceptibility in southwestern Saudi Arabia by identifying key driving factors and evaluating the performance of several machine learning models under conditions of limited and imbalanced data. The models tested include Maxent, logistic regression, random forest, XGBoost, and support vector machine. In addition, an NDVI-based phenological approach was applied to assess seasonal vegetation dynamics and to compare its effectiveness with conventional machine learning-based susceptibility mapping. All methods generated effective wildfire risk maps, with Maxent achieving the highest predictive accuracy (AUC = 0.974). The results indicate that human activities and dense vegetation cover are the primary contributors to wildfire occurrence. This research provides valuable insights for wildfire risk assessment in data-scarce regions and supports proactive fire management strategies in non-traditional fire-prone environments. Full article

Mass-balanced compartmental systems defy classical deterministic entropy measures since both metric and topological entropy vanish in dissipative dynamics. By interpreting open compartmental systems as absorbing continuous-time Markov chains that describe the random journey of a single representative particle, we allow established information-theoretic principles to be applied to this particular type of deterministic dynamical system. In particular, path entropy quantifies the uncertainty of complete trajectories, while entropy rates measure the average uncertainty of instantaneous transitions. Using Shannon’s information entropy, we derive closed-form expressions for these quantities in equilibrium and extend the maximum entropy principle (MaxEnt) to the problem of model selection in compartmental dynamics. This information-theoretic framework not only provides a systematic way to address equifinality but also reveals hidden structural properties of complex systems such as the global carbon cycle. Full article

Assessing the suitability of human settlements is of great significance for promoting pastoral development, improving herders’ livelihoods, and advancing the construction of beautiful villages in agro-pastoral regions. Focusing on ten pastoral banners within Xilingol League, a representative pastoral region in northern China, this study employed the Google Earth Engine (GEE) platform combined with statistical datasets to evaluate settlement suitability using an optimized MaxEnt model. Fourteen key influencing factors were identified, and the spatiotemporal dynamics of settlement suitability in 2017 and 2024 were analyzed, together with predictions of suitable area distribution. The results showed that the model achieved the highest accuracy when using a linear combination of linear, quadratic, hinge, product, and threshold features with a regularization multiplier of 5.0. Suitable areas were mainly located in the southern part of the League, characterized by higher elevation, moderate temperatures, sufficient water resources, and relatively developed economies, while unsuitable areas were concentrated along the northwestern and northeastern borders with Mongolia. Spatially, settlement suitability exhibited a decreasing gradient from the southwest to the northeast. Furthermore, the dominant driving factors have gradually shifted from ecological conditions to socio-economic conditions. Overall, the suitability of pastoral human settlements in Xilingol League has continued to improve, providing new insights for suitability evaluation and spatial restructuring in pastoral regions. Full article

Climate change is increasingly altering ecosystems around the world and threatening biodiversity, especially species with narrow distribution ranges and a dependency on dedicated conservation practices. In Saskatchewan, Canada, the ecological significance of the genus sedge (Carex L.) from the Cyperaceae family is well recognized, yet spatially explicit forecasts of its habitats under future climate scenarios remain absent, creating a major obstacle to forward-looking conservation strategies. This study assesses the current and future habitat suitability of six sedges, including three nationally at-risk species (C. assiniboinensis, C. saximontana, C. tetanica) and three provincially rare species (C. glacialis, C. granularis, C. supina subsp. spaniocarpa). We applied the MaxEnt algorithm to model the distributions of those Carex species of conservation concern using 20 environmental predictors (19 bioclimatic variables and elevation) under baseline climate (1970–2000) and projected future scenarios for the 2030s and 2050s using SSP245 and SSP585 emission pathways. We optimized and validated models with the ENMeval package to enhance predictive reliability. Model accuracy was high (AUC = 0.88–0.99) and the results revealed a diversity of species responses: C. assiniboinensis and C. tetanica are projected to expand their suitable habitat, while C. saximontana is expected to lose high suitability areas. The distributions of C. glacialis and C. supina subsp. spaniocarpa remain restricted and relatively stable across scenarios. C. granularis is projected to have dynamic range shifts, particularly under the high-emission SSP585 scenario. Temperature-related variables were consistently the most influential predictors. These results provide critical insights into the potential impacts of climate change on Carex species of conservation concern in Canada and offer valuable guidance for prioritizing adaptive conservation planning and proactive habitat management. The diversity of species responses emphasizes the necessity of tailored conservation approaches rather than a one-size-fits-all strategy. Full article

The aim of our study is to achieve a comprehensive understanding of the global distribution of suitable habitats for Sophora alopecuroides L., as well as how these habitats might change in response to climate change. We employed the MaxEnt niche model to integrate distribution data from the Global Biodiversity Information Platform, incorporating 19 bioclimatic factors. This approach enabled us to predict the potential geographic distribution of S. alopecuroides L. worldwide under both current climatic conditions and future greenhouse gas emission scenarios. The results were visualized via ArcGIS 10.8 software. The findings indicate that currently, the suitable habitat for S. alopecuroides L. spans 12,897,100 km², with the majority situated in the arid regions of Central and Eastern Asia. The key environmental variables influencing its distribution are annual mean temperature, maximum temperature of the warmest month, precipitation of the warmest season, and mean temperature of the coldest season. For future climate projections, suitable habitats generally exhibit a shrinking trend. The most pronounced decrease is anticipated under the moderate greenhouse gas emission scenario (SSP245). However, under the high greenhouse gas emission scenario (SSP585), the suitable habitat area is projected to increase marginally by 2060. This dynamic change warning suggests that it is necessary to optimize climate adaptation strategies, strengthen ecological protection and restoration in suitable areas, so as to maintain the ecological service functions of S. alopecuroides L. in arid and semi-arid ecosystems, such as sand fixation and soil conservation, and maintain biodiversity, and provide basic guarantee for the sustainable development and utilization of its medicinal and forage resources. This study reveals the dynamic impact of climate change on the distribution of S. alopecuroides L. suitable areas, which not only provides a scientific basis for ecological restoration and S. alopecuroides L. resource protection in arid and semi-arid areas, but also has important practical significance for promoting the regional practice of the concept of sustainable development of “harmonious coexistence between man and nature.” Full article