Search Results (123)

The tufted deer (Elaphodus cephalophus), a Near-Threatened (NT) species endemic to China and Myanmar, requires robust genetic data for effective conservation. However, the genetic landscape of key populations, such as those in Chongqing, remains poorly understood. This study aimed to comprehensively evaluate the genetic diversity, population structure, gene flow, and demographic history of tufted deer across this critical region. We analyzed mitochondrial DNA (mtDNA) from 46 non-invasively collected fecal samples from three distinct populations: Jinfo Mountain (JF, n = 13), Simian Mountain (SM, n = 21), and the Northeastern Mountainous region (NEM, n = 12). Genetic variation was assessed using the cytochrome b (Cyt b) and D-loop regions, with analyses including F_st, gene flow (N_m), neutrality tests, and Bayesian Skyline Plots (BSP). Our results revealed the highest genetic diversity in the SM population, establishing it as a genetic hub. In contrast, the JF population exhibited the lowest diversity and significant genetic differentiation (>0.23) from the SM and NEM populations, indicating profound isolation. Gene flow was substantial between SM and NEM but severely restricted for the JF population. Demographic analyses, including BSP, indicated a long history of demographic stability followed by a significant expansion beginning in the Middle to Late Pleistocene. We conclude that the SM/NEM metapopulation serves as the genetic core for the species in this region, while the highly isolated JF population constitutes a distinct and vulnerable Management Unit (MU). This historical demographic expansion is likely linked to climatic and environmental changes during the Pleistocene, rather than recent anthropogenic factors. These findings underscore the urgent need for a dual conservation strategy: targeted management for the isolated JF population and the establishment of ecological corridors to connect the Jinfo Mountain and Simian Mountain populations, ensuring the long-term persistence of this unique species. Full article

Leeches hold significant medical and pharmaceutical value for antithrombotic treatments, yet their genetic diversity patterns remain poorly understood. We performed population genetic analyses on seven Hirudinaria manillensis populations from southern China using mitochondrial protein-coding genes (MitPCGs). Complete sequences of all 13 MitPCGs were obtained from 74 individuals. Haplotype diversity exhibited a logarithmic relationship with the gene length (R² = 0.858, p < 0.001), while nucleotide diversity showed a near-perfect alternating low-high pattern (Z = 2.938, p = 0.003). Concatenated sequence analyses indicated high haplotype diversity (>0.5) and low nucleotide diversity (<0.005) across all populations, suggesting a historical bottleneck followed by rapid expansion and mutation accumulation. The haplotype network, haplotype phylogenetics, and genetic structure analyses revealed moderate genetic differentiation across populations, dividing them into three clades: a basal Yunnan population (YNHH), sub-basal Guangxi populations (GXGG, GXLZ, and GXYL), and distal Guangdong/Hainan populations (GDMM, GDZJ, and HNDA). Analysis of historical population demography revealed five phases from ancient to recent times (P1–5): growth, prolonged stability, rapid decline, rapid growth, and secondary decline. These phases correlate strongly with past climatic events, demonstrating that glacial–interglacial cycles profoundly impacted the leech’s effective population size. This study provides a key scientific basis for H. manillensis resource conservation and utilization. Full article

The Beijing–Tianjin–Hebei (BTH) region is one of China’s most water-scarce yet economically vital areas, facing increasing challenges due to climate change and intensive human activities. This study develops an integrated Water–Food–Energy–Ecology (WFEE) simulation and regulation model to assess the system’s stability under coordinated development scenarios and extreme climate stress. A 500-year precipitation series was reconstructed using historical drought and flood records combined with wavelet analysis and machine learning models (Random Forest and Support Vector Regression). Results show that during the reconstructed historical megadrought (1633–1647), with average precipitation anomalies reaching −20% to −27%, leading to a regional water shortage rate of 16.9%, food self-sufficiency as low as 44.7%, and a critical reduction in ecological river discharge. Under future recommended scenario with enhanced water conservation, reclaimed water reuse, and expanded inter-basin transfers, the region could maintain a water shortage rate of 2.6%, achieve 69.3% food self-sufficiency, and support ecological water demand. However, long-term water resource degradation could still reduce food self-sufficiency to 62.9% and ecological outflows by 20%. The findings provide insights into adaptive water management, highlight the vulnerability of highly coupled systems to prolonged droughts, and support regional policy decisions on resilience-oriented water infrastructure planning. Full article

Ancient temple complexes in China’s mountainous landscapes exemplify a profound synthesis of environmental adaptation and cultural expression. This research investigates the spatial logic underlying the Wudang Mountain temple complex—a UNESCO World Heritage site—through integrated geospatial analysis of environmental factors. Using GIS-based modeling, GeoDetector, and regression analysis, we systematically assess how terrain, hydrology, climate, vegetation, and soil conditions collectively influenced site selection. The results reveal a clear hierarchical clustering pattern, with dense temple cores in the southwestern highlands, ridge-aligned belts, and a dominant southwest–northeast orientation that reflects intentional alignment with mountain ridgelines. Temples consistently occupy zones with moderate thermal, hydrological, and vegetative stability while avoiding geotechnical extremes such as lowland humidity or unstable slopes. Regression analysis confirms that site preferences vary across temple types, with soil pH, porosity, and bulk density emerging as significant influencing factors, particularly for cliffside temples. These findings suggest that ancient temple planning was not merely a passive response to sacred geography but a deliberate process that actively considered terrain, climate, soil, and other environmental factors. While environmental constraints strongly shaped spatial decisions, cultural and symbolic considerations also played an important role. This research deepens our understanding of how environmental factors influenced the formation of historical landscapes and offers theoretical insights and ecologically informed guidance for the conservation of mountain cultural heritage sites. Full article

Tropical peatlands store approximately 105 gigatons of carbon (GtC), serving as vital long-term carbon sinks, yet remain critically underrepresented in climate policy. Indonesia peatlands contain 57GtC—the largest tropical peatland carbon stock in the Asia–Pacific. However, decades of drainage, fires, and lax enforcement practices have degraded vast peatland areas, turning them from carbon sinks into emission sources—as evidenced by the 1997 and 2015 peatland fires which emitted 2.57 Gt CO₂eq and 1.75 Gt CO₂eq, respectively. Using system theory validated against historical data (1997–2023), we develop a causal loop model revealing three interconnected feedback loops driving irreversible collapse: (1) drainage–desiccation–oxidation, where water table below −40 cm triggers peat oxidation (2–5 cm subsistence) and fires; (2) fire–climate–permafrost, wherein emissions intensify radiative forcing, destabilizing monsoons and accelerating Arctic permafrost thaw (+15% since 2000); and (2) economy–governance failure, perpetuated by palm oil’s economic dominance and slack regulatory oversight. To break these vicious cycles, we propose a precautionary framework featuring IoT-enforced water table (≤40 cm), reducing emissions by 34%, legally protected “Global Climate Stabilization Zones” for peat domes (>3 m depth), safeguarding 57 GtC, and ASEAN transboundary enforcement funded by a 1–3% palm oil levy. Without intervention, annual emissions may reach 2.869 GtCO₂e by 2030 (Nationally Determined Contribution’s business-as-usual scenario). Conversely, rewetting 590 km²/year aligns with Indonesia’s FOLU Net Sink 2030 target (−140 Mt CO₂e) and mitigates 1.4–1.6 MtCO₂ annually. We conclude that integrating peatlands as irreplaceable climate infrastructure into global policy is essential for achieving Paris Agreement goals and SDGs 13–15. Full article

This study investigates the spatiotemporal distribution and evolution of traditional villages in southern Jiangsu Province, China. By integrating historical documents, remote sensing images, and socio-economic statistics, we have applied standard geographic information system (GIS) methods, including kernel density estimation, nearest neighbor analysis, and standard deviation ellipse analysis, to examine the patterns and driving forces behind village formation and transformation. The findings are as follows: (1) The spatial distribution of the villages exhibits a spatial pattern of “peripheral agglomeration and central decline,” with a nearest neighbor index value of 0.84 (z = −2.52, p < 0.05), indicating a significantly clustered distribution. Kernel density analysis revealed high-density zones along the southwestern coast of Taihu Lake and southeastern Dianshan Lake. (2) From the Song to the Qing Dynasty, village migration followed three sequential phases, “stabilizing near water → avoiding risks around water → adapting inland,” showing strong spatiotemporal linkages to climate change and warfare. (3) The density of the villages showed a significant negative correlation with the per capita GDP (Moran’s I = −0.69, p < 0.05; 0.69, p < 0.01) and was positively correlated with the proportion of primary industry. These findings highlight the spatial resilience characteristics of traditional villages under combined natural and socio-economic pressures and provide a theoretical foundation for regional heritage conservation and rural revitalization strategies. Full article

The evaluation of cloud distribution, properties, and their interaction with the radiation (longwave and shortwave) is of utmost importance for the proper assessment of future climate. Therefore, this study focuses on the Coupled Model Inter-Comparison Project Phase-6 (CMIP6) historical and future projections using the Shared Socio-Economic Pathways (SSPs) low- (ssp1–2.6), moderate- (ssp2–4.5), and high-emission (ssp5–8.5) scenarios along the South Asian region. For this purpose, a multi-model ensemble mean approach is employed to analyze the future projections in the low-, mid-, and high-emission scenarios. The cloud water content and cloud ice content in the CMIP6 models show an increase in upper and lower troposphere simultaneously in future projections as compared to ERA5 and historical projections. The longwave and shortwave cloud radiative effects at the top of the atmosphere are examined, as they offer a global perspective on radiation changes that influence atmospheric circulation and climate variability. The longwave cloud radiative effect (44.14 W/m²) and the shortwave cloud radiative effect (−73.43 W/m²) likely indicate an increase in cloud albedo. Similarly, there is an expansion of Hadley circulation (intensified subsidence) towards poleward, indicating the shifting of subtropical high-pressure zones, which can influence regional monsoon dynamics and cloud distributions. The impact of future projections on the tropospheric temperature (200–600 hPa) is studied, which seems to become more concentrated along the Tibetan Plateau in the moderate- and high-emission scenarios. This increase in the tropospheric temperature at 200–600 hPa reduces atmospheric stability, allowing stronger convection. Hence, the strengthening of convective activities may be favorable in future climate conditions. Thus, the correct representation of the model physics, cloud-radiative feedback, and the large-scale circulation that drives the Indian Summer Monsoon (ISM) is of critical importance in Coupled General Circulation Models (GCMs). Full article

This study explores advanced multivariate models that incorporate non-climatic exogenous variables for very short-term photovoltaic energy forecasting. By integrating historical energy data from multiple photovoltaic plants, the research aims to improve the prediction accuracy of a target plant while addressing critical challenges in electric power systems (EPS), such as frequency stability. Frequency stability becomes increasingly complex as renewable energy sources penetrate the grid because of their intermittent nature. To mitigate this challenge, precise forecasting of photovoltaic energy generation is essential for balancing supply and demand in real time. The performance of long short-term memory (LSTM) networks and bidirectional LSTM (BiLSTM) networks was compared over a 5 min horizon. Including energy generation data from neighboring plants significantly improved prediction accuracy compared to univariate models. Among the models, multivariate BiLSTM showed superior performance, achieving a lower root-mean-square error (RMSE) and higher correlation coefficients. Quantile regression applied to manage prediction uncertainty, providing robust confidence intervals. The results suggest that incorporating an exogenous power series effectively captures spatial correlations and enhances prediction accuracy. This approach offers practical benefits for optimizing grid management, reducing operational costs, improving the integration of renewable energy sources, and supporting frequency stability in power generation systems. Full article

Forest shelterbelts and windbreaks play a vital role in protecting ecosystems, mitigating climate change effects, and enhancing agricultural productivity. These vegetative barriers serve as effective tools for soil conservation, reducing wind and water erosion while improving soil fertility. Additionally, they contribute to biodiversity preservation by providing habitat corridors for various plant and animal species. Their role in microclimate regulation, such as temperature moderation and increased humidity retention, further enhances agricultural yields and ecosystem stability. This study examines the historical evolution, design principles, and contemporary applications of forest shelterbelts and windbreaks, drawing insights from scientific research and case studies worldwide. It highlights the economic and environmental benefits, including improved air quality, carbon sequestration, and water management, making them crucial components of sustainable land use strategies. However, challenges such as land use competition, maintenance costs, and policy constraints are also analyzed, underscoring the need for integrated approaches to their management. Through a comprehensive bibliometric analysis of the existing literature and field studies, this paper emphasizes the necessity of strategic planning, community involvement, and adaptive policies to ensure the long-term sustainability of forest shelterbelts and windbreaks. The findings contribute to a broader understanding of their role in combating environmental degradation and promoting ecological resilience in the face of ongoing climate challenges. Full article

This paper analyses Poland’s participation in implementing European climate policy within the framework of the National Energy and Climate Plan (NECP), looking toward 2040. It assesses the feasibility of Poland’s commitments to the European Union’s decarbonisation targets, particularly with regard to transitioning from fossil fuels to renewable energy sources and nuclear power. The study highlights the challenges related to the speed of the energy transition, the security of electricity supply, and the competitiveness of the national economy. The study also assesses the energy mix scenarios proposed in the NECP, taking into account historical energy consumption data, economic and demographic projections, and expert analyses of energy security. It also critically examines the risks of delayed investment in nuclear and offshore wind, the potential shortfall in renewable energy infrastructure, and the need for transitional solutions, including coal and gas generation. An alternative scenario is proposed to mitigate potential energy supply shortfalls between 2035 and 2040, highlighting the role of energy storage, strategic reserves, and the maintenance of certain fossil fuel capacities. Poland’s energy policy should prioritize flexibility and synchronization with EU objectives, while ensuring economic stability and technological feasibility. The analysis underlines that the sustainable development of the national energy system requires not only alignment with European climate goals, but also a long-term balance between environmental responsibility, energy affordability, and security. Strengthening the sustainability dimension in energy policy decisions—by integrating resilience, renewability, and social acceptance—is essential to ensure a just and enduring energy transition. Full article

This study investigates the impact of climate variability on wheat production in Algeria’s semi-arid interior plains from 2014 to 2024, aiming to curb the challenges of rainfed wheat cultivation, optimize irrigation, and improve water productivity. The Soil–Water–Atmosphere–Plant (SWAP) model-driven approach refined irrigation scheduling to mitigate climate-induced losses and improve resource efficiency. Using historical climate data, soil properties, and wheat growth observations from the experimental farm of the Technical Institute for Field Crops, the SWAP model was calibrated and validated using one-factor-at-a-time sensitivity analysis, achieving a coefficient of determination (R²) of 0.93 and a Normalized Root Mean Squared Error (NRMSE) of 17.75. Two drought-based irrigation indices, Soil Moisture Drought Index (SMDI) and Crop Water Stress Index (CWSI), guided adaptive irrigation strategies, showing a significant reduction in crop failure during drought periods. Results revealed a strong link between rainfall variability and wheat yield. Adopting a 9-day irrigation interval could increase water productivity to 18.91 kg ha⁻¹ mm⁻¹, enhancing yield stability under varying climatic conditions. The SMDI approach maintained soil moisture during extreme drought, while CWSI optimized water use in normal and wet years. This study integrates SMDI and CWSI into a validated irrigation framework, offering data-driven strategies to enhance wheat production resilience. Findings support sustainable water management and provide practical insights for policymakers and farmers to refine irrigation planning and climate adaptation, contributing to long-term agricultural sustainability. Full article

Sowing date significantly affects plant growth, development, and yield, holding a crucial role in soybean cultivation. This study was conducted in the southern coastal region of Korea under recent climate change conditions to investigate the effects of five different sowing dates on climatic characteristics, growth, and yield. Compared to historical data, the southern coastal region has experienced a consistent increase in average temperature during the soybean cultivation period, along with frequent abnormal summer climate events such as concentrated heavy rainfall and monsoons. These climate changes prolonged the vegetative growth period in earlier sowings, leading to an increased risk of lodging at maturity due to vigorous vegetative growth. Furthermore, earlier sowing delayed flowering and exposed plants to longer post-flowering photoperiods, consequently reducing the number of pods. Therefore, in the southern coastal region of Korea, it is crucial to re-evaluate conventional sowing practices and establish region-specific optimal dates, with careful consideration given to postponing the soybean sowing date to late June in order to enhance yield stability and improve the feasibility of double-cropping systems by shortening the growing period. Full article

Earth’s energy imbalance (EEI) is a major indicator of climate change. Its metrics are top of the atmosphere radiation imbalance (EEI TOA) and net internal heat uptake. Both EEI and temperature are expected to respond gradually to forcing on annual timescales. This expectation was tested by analyzing regime changes in the inputs to EEI TOA along with increasing ocean heat content (OHC). Outward longwave radiation (OLR) displayed rapid shifts in three observational and two reanalysis records. The reanalysis records also contained shifts in surface fluxes and temperature. OLR, outward shortwave radiation (OSR) and TOA net radiation (Net) from the CERES Energy Balanced and Filled Ed-4.2.1 (2001–2023) record and from 27 CMIP5 historical and RCP4.5 forced simulations 1861–2100, were also analyzed. All variables from CERES contained shifts but the record was too short to confirm regime changes. Contributions of OLR and OSR to net showed high complementarity over space and time. EEI TOA was −0.47 ± 0.11 W m⁻² in 2001–2011 and −1.09 ± 0.11 W m⁻² in 2012–2023. Reduced OSR due to cloud feedback was a major contributor, coinciding with rapid increases in sea surface temperatures in 2014. Despite widely varying OLR and OSR, 26/27 climate models produced stable regimes for net radiation. EEI TOA was neutral from 1861, shifting downward in the 26 reliable records between 1963 and 1995, with 25 records showing it stabilizing by 2039. To investigate heat uptake, temperature and OHC 1955/57–2023 was analyzed for regime change in the 100 m, 700 m and 2000 m layers. The 100 m layer, about one third of total heat content, was dominated by regimes. Increases became more gradual with depth. Annual changes between the 700 m layer and 1300 m beneath were negatively correlated (−0.67), with delayed oscillations during lag years 2–9. Heat uptake at depth is dynamic. These changes reveal a complex thermodynamic response to gradual forcing. We outline a complex arrangement of naturally evolved heat engines, dominated by a dissipative heat engine nested within a radiative engine. EEI is a property of the dissipative heat engine. This far-from-equilibrium natural engine has evolved to take the path of least resistance while being constrained by its maximum power limit (~2 W m⁻²). It is open to the radiative engine, receiving solar radiation and emitting scattered shortwave and longwave radiation. Steady states maximize entropy within the dissipative engine by regulating spatial patterns in surface variables that influence outgoing OLR and OSR. Regime shifts to warmer climates balance the cost of greater irreversibility with increased energy rate density. The result is the regulation of EEI TOA through a form of thermodynamic metabolism. Full article

Accurate long-term power load forecasting in the grid is crucial for supply–demand balance analysis in new power systems. It helps to identify potential power market risks and uncertainties in advance, thereby enhancing the stability and efficiency of power systems. Given the temporal and nonlinear features of power load, this paper proposes a hybrid load-forecasting model using attention mechanisms, CNN, and BiLSTM. Historical load data are processed via CEEMDAN, K-means clustering, and VMD for significant regularity and uncertainty feature extraction. The CNN layer extracts features from climate and date inputs, while BiLSTM captures short- and long-term dependencies from both forward and backward directions. Attention mechanisms enhance key information. This approach is applied for seasonal load forecasting. Several comparative experiments show the proposed model’s high accuracy, with MAPE values of 1.41%, 1.25%, 1.08% and 1.67% for the four seasons. It outperforms other methods, with improvements of 0.25–2.53 GWh² in MSE, 0.15–0.1 GWh in RMSE, 0.1–0.74 GWh in MAE and 0.22–1.40% in MAPE. Furthermore, the effectiveness of the data processing method and the impact of training data volume on forecasting accuracy are analyzed. The results indicate that decomposing and clustering historical load data, along with large-scale data training, can both boost forecasting accuracy. Full article

The Loess Plateau (LP), the cradle of Chinese civilization, has a long history of agricultural activities closely linked to ecological changes. This study addresses a fundamental question: what was the maximum sustainable cropland area threshold for the LP prior to modern soil and water conservation measures? To answer this, we analyzed the historical data to investigate changes in the cropland area and their ecological impacts over the past 4000 years, with the specific aim of examining the long-term interactions between land exploitation and the ecosystem that defined sustainable thresholds. Three key stages of cropland area development were identified: slow growth (2000–500 BC), a fluctuating phase (500 BC–1000 AD), and rapid expansion (1000–2000 AD). During the slow-growth and rapid-expansion stages, the cropland areas were estimated at 34.9 ± 23.4 and 117.9 ± 34.1 thousand km², with growth rates of 2.9 and 8.7 thousand km²/100 years, respectively, while the fluctuating period stabilized at 62.1 ± 18.1 thousand km². Population growth was the primary driver of cropland expansion (56.9%), followed by agricultural technology and policy adjustments (27%) and climate change (16.1%). Particularly over the past 1000 years, climate deterioration and a population surge due to the abolition of the poll tax accelerated cropland expansion, resulting in deforestation, intensified soil erosion specific to the LP, and frequent flooding of the lower Yellow River (YR). In contrast, during the fluctuating period, rapid social development did not lead to major ecological issues, suggesting that moderate cropland expansion can balance social development and ecological sustainability. Based on the historical conditions, without modern soil and water conservation measures, this study determined that the upper limit of the cropland area during the fluctuating period (80.2 thousand km²) is the maximum sustainable cropland area for the LP, establishing a scientific basis to guide future land-use strategies. Especially in the face of population pressure and climate deterioration, developing agriculture and adjusting policies to increase grain production will be essential to balance the ecological risks and maintenance of food security while remaining within this threshold. These findings offer insights into the agricultural history and ecological management of the LP and can serve as a reference for similar studies of other regions. Full article