Ecological Indicators最新文献_第3页

Evaluation and diagnosis of water resource carrying capacity in the middle reaches of the Heihe River under SEEA-W perspective SEEA-W视角下黑河中游水资源承载力评价与诊断

IF 7 2区环境科学与生态学 Q1 ENVIRONMENTAL SCIENCES

Ecological Indicators

Pub Date : 2026-02-01 DOI: 10.1016/j.ecolind.2026.114656

Jiangzhe Han , Zongxing Li , Xiaohong Deng , Huiwenqing Fan , Yixuan Wang

Water scarcity poses a significant challenge to sustainable development in arid regions, necessitating the adoption of advanced and interpretable methodologies for assessing water resource carrying capacity (WRCC). This study constructs a dynamic ‘Production-Supply-Use-Consumption-Emission’ (PSUCE) system based on the System of Environmental-Economic Accounting for Water (SEEA-W). It proposes the TOPSIS-XGBoost-SHAP-PDP (TOPSIS-XSP) integrated approach to evaluate WRCC in the middle reaches of the Heihe River (MRHR) from 2003 to 2023. The TOPSIS model reveals a ‘fluctuating increase-peak decline’ trend: carrying capacity reached Level IV (basic capacity) in 2019 before declining due to drought and structural constraints. Key obstacles include agricultural water use efficiency (C10), domestic sewage discharge (C20), and Sewage Reuse Rate (C23). SHAP analysis further elucidated the positive contributions of C10 and C23 alongside the significant negative impact of C22 (total emissions). PDP analysis revealed non-linear relationships and critical thresholds: agricultural water conservation exhibits diminishing marginal returns beyond a specific efficiency level. At the same time, WRCC declines sharply when pollutant emissions exceed 84 million m³. These findings demonstrate that the mixed methods approach effectively combines macro-level trend diagnostics with explanatory insights into mechanism drivers, providing a robust foundation for addressing water management challenges through adaptive efficiency improvements, pollution control, and structural water allocation strategies.

缺水对干旱地区的可持续发展构成重大挑战，因此必须采用先进和可解释的方法来评估水资源承载能力。本研究在水环境经济核算体系（SEEA-W）的基础上构建了一个动态的“生产-供应-使用-消费-排放”（PSUCE）系统。提出了2003 - 2023年黑河中游WRCC的topsis - xgboost - shape - pdp （TOPSIS-XSP）综合评价方法。TOPSIS模型显示了一种“波动的增加-峰值下降”趋势：承载力在2019年达到第四级（基本能力），然后由于干旱和结构性限制而下降。主要障碍包括农业用水效率（C10）、生活污水排放量（C20）和污水回用率（C23）。SHAP分析进一步阐明了C10和C23的积极贡献以及C22（总排放量）的显著负面影响。PDP分析揭示了农业节水的非线性关系和临界阈值：超过特定效率水平，农业节水的边际收益递减。同时，当污染物排放量超过8400万m3时，WRCC急剧下降。这些发现表明，混合方法方法有效地将宏观趋势诊断与机制驱动的解释性见解结合起来，为通过适应性效率提高、污染控制和结构性水资源分配策略解决水资源管理挑战提供了坚实的基础。

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引用次数: 0

Invertebrates' metabolic responses to climate warming scenarios in the Adriatic Sea 亚得里亚海无脊椎动物对气候变暖情景的代谢反应

IF 7 2区环境科学与生态学 Q1 ENVIRONMENTAL SCIENCES

Ecological Indicators

Pub Date : 2026-02-01 DOI: 10.1016/j.ecolind.2026.114622

Milad Shokri , Ludovico Lezzi , Mario Ciotti , Fabio Vignes , Parisa Taban , Vanessa Marrocco , Victoria Alabi , Dolapo Olatoye , Alexandra Nicoleta Muresan , Paola Forni , Teodoro Semeraro , Elisa Anna Fano , Alberto Basset

The unprecedented climate warming is profoundly altering marine life. Metabolic rate, a key organismal trait, serves as an ecological indicator of species' responses to the temperature-driven impacts of climate change, across levels of biological organisation from individuals to ecosystems. Understanding and predicting the temperature responses of metabolic rate is thus urgent for guiding effective policy and conservation efforts, particularly in the semi-enclosed Adriatic Sea, which has recently experienced pronounced changes in invertebrate populations and community composition. Here, we aimed to assess how the standard metabolic rate (SMR) of invertebrate species in the Adriatic Sea responds to temperature changes and to project its change under various IPCC climate emission scenarios by 2100. We measured the individual SMRs of nine invertebrate species collected from locations spanning the southern to northern Adriatic Sea, across two acclimation temperature levels. Relative to theoretical expectations, our findings indicated shallower scaling of SMR with body size (with an overall scaling exponent of 0.50), and lower temperature dependence (with an activation energy of 0.35 eV). We further showed that species in the Adriatic Sea are projected to experience an increase in their metabolic rate ranging from an average 7.8% under the most optimistic Representative Concentration Pathway RCP2.6, to 27.3% under the more severe climate change scenario RCP8.5, with the highest increases expected in the northern area in Gulf of Trieste. Overall, despite lower-than-theoretically expected metabolic temperature dependence in aquatic invertebrates, empirical estimates combined with spatial climate projections indicate that warming will elevate energetic demands throughout the Adriatic Sea, with disproportionately stronger impacts in the northern basin.

前所未有的气候变暖正在深刻地改变着海洋生物。代谢率是一个关键的生物特征，是物种对气候变化的温度驱动影响的反应的生态指标，从个体到生态系统的生物组织水平都是如此。因此，了解和预测代谢率的温度响应对于指导有效的政策和保护工作是迫切的，特别是在半封闭的亚得里亚海，最近经历了无脊椎动物种群和群落组成的显著变化。在此，我们旨在评估亚得里亚海无脊椎动物的标准代谢率（SMR）如何响应温度变化，并预测其在2100年不同IPCC气候排放情景下的变化。我们测量了从亚得里亚海南部到北部收集的9种无脊椎动物的个体smr，跨越了两个驯化温度水平。与理论预期相比，我们的研究结果表明SMR随体型的标度较浅（总体标度指数为0.50），温度依赖性较低（活化能为0.35 eV）。研究进一步表明，亚得里亚海物种的代谢率在最乐观的代表性浓度路径RCP2.6下平均增加7.8%，在更严重的气候变化情景RCP8.5下增加27.3%，其中的里雅斯特湾北部地区的增加幅度最大。总体而言，尽管水生无脊椎动物的代谢温度依赖性低于理论预期，但结合空间气候预测的经验估计表明，变暖将提高整个亚得里亚海的能量需求，对北部盆地的影响更大。

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引用次数: 0

Flying above fragility: Remote sensing and field samplings unveil microcrustacean patterns in ephemeral ponds 在脆弱之上飞行：遥感和实地取样揭示了短暂池塘中的微甲壳类动物模式

IF 7 2区环境科学与生态学 Q1 ENVIRONMENTAL SCIENCES

Ecological Indicators

Pub Date : 2026-01-23 DOI: 10.1016/j.ecolind.2026.114655

Livia Benedini , Giulia Cesarini , Davide Taurozzi , Virginia Iorio-Merlo , Francesco Simone Mensa , Massimiliano Scalici

Temporary ponds (TPs) are ephemeral freshwater habitats that undergo seasonal drying, creating harsh and highly dynamic environments. Microcrustaceans are key biological components of TPs since they play a crucial role in ecosystem dynamics. The main objective of this study is to test an innovative approach that combines field sampling with modern remote sensing technologies to: (i) investigate the temporal variation of microcrustacean communities and the influence of hydroperiod length and pond area in three coastal temporary ponds (TpA, TpB, TpC) and (ii) assess the hydroperiod length using unmanned aerial vehicles (UAVs). Overall, eight microcrustacean families were identified. In TpA, five families were recorded, whereas six families were documented in both TpB and TpC exhibiting diverse feeding strategies. Our observations suggest that the presence and relative abundance of taxa in the ponds significantly changed over time. We observed statistically significant similarities in TpB and TpC communities, with a Jaccard similarity coefficient of 0.833 in January, whereas the comparison between these communities and TpA did not show the same level of similarity. We also found a positive correlation between pond size and Shannon diversity index (Spearman: rho = 0.607, p < 0.01), indicating that an increase in pond area corresponded to greater microcrustacean diversity. Furthermore, our analyses revealed that temporal variability plays a more prominent role than spatial heterogeneity (transect and sub-transect) in explaining the observed biodiversity patterns. Our findings highlight the effectiveness of analyzing temporary environments through a multi-methodological approach that can be replicated over time and internationally adopted.

临时池塘（TPs）是短暂的淡水栖息地，经历季节性干燥，创造了严酷和高度动态的环境。微甲壳类动物在生态系统动力学中起着至关重要的作用，是TPs的关键生物组成部分。本研究的主要目的是测试一种将野外采样与现代遥感技术相结合的创新方法，以：(i)调查三个沿海临时池塘（TpA, TpB, TpC）的微甲壳类动物群落的时间变化以及水期长度和池塘面积的影响；（ii）利用无人机（uav）评估水期长度。总共鉴定出8个微甲壳类动物科。在TpA中记录了5个科，而在TpB和TpC中记录了6个科，表现出不同的摄食策略。我们的观察表明，随着时间的推移，池塘中分类群的存在和相对丰度发生了显著变化。1月份，TpB和TpC群落的Jaccard相似系数为0.833，而TpA与TpB群落的相似性不高。我们还发现池塘大小与Shannon多样性指数呈正相关（Spearman: rho = 0.607, p < 0.01），表明池塘面积的增加对应着更大的微甲壳类生物多样性。此外，我们的分析表明，在解释观察到的生物多样性格局方面，时间变异比空间异质性（样带和亚样带）更为突出。我们的研究结果强调了通过多方法方法分析临时环境的有效性，这种方法可以随着时间的推移而被复制并在国际上采用。

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引用次数: 0

Nutrient stoichiometry and limitations shift as cyanobacterial inoculation-induced biocrusts develop 随着蓝藻接种诱导的生物结壳的发展，营养化学计量学和限制发生了变化

IF 7 2区环境科学与生态学 Q1 ENVIRONMENTAL SCIENCES

Ecological Indicators

Pub Date : 2026-01-23 DOI: 10.1016/j.ecolind.2026.114634

Lu Chen , Xinwen Xu , Matthew A. Bowker , Longkat A. Gufwan , Li Wu , Shubin Lan

Cyanobacterial inoculation has been recognized as a promising strategy for promoting the development of biological soil crusts (biocrusts) and combating desertification. However, the long-term shifts in enzyme dynamics, nutrient limitations, and stoichiometric balance during induced biocrust development remain poorly understood. In this study, we quantified changes of carbon (C), nitrogen (N) and phosphorus (P) contents, corresponding stoichiometric ratios, and enzyme activities in both biocrusts and subsurface layers soil at long-term restoration sites in the Qubqi Desert, where cyanobacteria were inoculated approximately two decades ago. The induced biocrust communities underwent a clear successional trajectory, from shifting sand to cyanobacteria- and finally to moss-dominated types, accompanied by substantial increases in organic carbon (SOC), total nitrogen (TN), total phosphorus (TP), and the major stoichiometric ratios (C: N, C: P, and N: P) in both biocrusts and subsurface soils. Vector analysis of enzyme activities revealed a shift in microbial nutrient demand along with induced-biocrust development, from N limitation to P limitation or co-limitation of C and P, while the subsurface soils remained N limited. Assessments of stoichiometric imbalance between biocrust and subsurface soils indicated a growing vertical nutrient stratification and decoupling with increasingly pronounced C: P and N: P imbalances as induced biocrust development progressed, suggesting increased P demand and unique P-related metabolic processes within developed biocrusts. Our findings highlight that cyanobacterially induced biocrusts not only enrich soil fertility and alter nutrient limitations but also create vertical heterogeneity in soil stoichiometry. All these findings underscore the importance of understanding P cycling within biocrust ecosystems to support the long-term stability and sustainability of biocrust-based desert soil restoration practices.

蓝藻接种已被认为是促进生物土壤结皮（生物结皮）的发展和防治荒漠化的一种有前途的策略。然而，在诱导生物结壳发育过程中，酶动力学、营养限制和化学计量平衡的长期变化仍然知之甚少。在这项研究中，我们量化了在大约20年前接种蓝藻的库布齐沙漠长期恢复点生物结皮和亚表层土壤中碳(C)、氮(N)和磷(P)含量、相应的化学计量比和酶活性的变化。诱导生物结皮群落经历了一个明显的演替轨迹，从流沙到蓝藻，最后到苔藓为主的类型，并伴随着生物结皮和地下土壤中有机碳（SOC）、全氮（TN）、全磷（TP）和主要化学计量比（C: N、C: P和N: P）的大幅增加。酶活性的载体分析显示，随着诱导生物结皮的发育，微生物养分需求发生了转变，从氮限制到磷限制或碳磷共同限制，而地下土壤仍然是氮限制。对生物硬壳和地下土壤化学计量失衡的评估表明，随着生物硬壳发育的进展，垂直养分分层和解耦日益明显，C: P和N: P失衡日益明显，这表明在发育的生物硬壳中，磷需求增加，磷相关代谢过程独特。研究结果表明，蓝藻诱导的生物结皮不仅能提高土壤肥力，改变养分限制，而且还会造成土壤化学计量的垂直异质性。所有这些发现都强调了了解生物硬壳生态系统中磷循环对支持基于生物硬壳的荒漠土壤恢复实践的长期稳定性和可持续性的重要性。

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引用次数: 0

Multi-endpoint ecophysiological indicators to assess freshwater mussel translocation success 评价淡水贻贝转运成功的多终点生态生理指标

IF 7 2区环境科学与生态学 Q1 ENVIRONMENTAL SCIENCES

Ecological Indicators

Pub Date : 2026-01-23 DOI: 10.1016/j.ecolind.2026.114649

Andreas H. Dobler , Sebastian Beggel , Michaela Tille , Paul A. Schwarzenbeck, Juergen Geist

Freshwater mussels are considered keystone fauna of aquatic ecosystems and globally declining. Translocation of mussels has been used as a conservation tool, but there is a lack of indicators for the success of such measures. This study investigated ecophysiological responses of three native mussel species (Anodonta anatina, A. cygnea, Unio pictorum) after translocations into different substitute habitats, hypothesizing that the response patterns can be used as ecological indicators for translocation success. Over 47,000 mussels were relocated from a drained reservoir to three replacement habitats: a fishpond, the pre-dam and a slow-flowing section of the river inflow of the reservoir (river Schwarzach). Mortality, growth and macromolecules (glycogen, glucose, protein, lipids) in the mussel foot tissue were measured in PIT-tagged mussels over three years. Survival rates greatly varied between habitats (0% in the Schwarzach, 38% in the fishpond, 66% in the pre-dam area). Shell growth was higher in the fishpond than in the pre-dam, and concentrations of storage compounds varied over time and between habitats. The results highlight that the combined assessment of multiple biological endpoints comprising mortality, growth and biochemical markers provides a valuable ecological indicator for assessing mussel translocation success which is crucial for improving conservation efforts. They also stress the critical importance of considering temporal patterns in assessing ecophysiological responses to stress, and the need for risk mitigation and careful habitat selection for successful translocation of freshwater mussels.

淡水贻贝被认为是水生生态系统的基石动物，在全球范围内日益减少。贻贝的易位已被用作一种保护工具，但缺乏此类措施成功的指标。本文研究了三种本地贻贝（Anodonta anatina， A. cygnea, Unio pictorum）迁移到不同替代生境后的生态生理反应，并假设这些反应模式可以作为迁移成功的生态指标。超过47,000只贻贝被从一个排水的水库重新安置到三个替代栖息地：鱼塘、大坝前和水库流入的河流慢流段（施瓦扎克河）。在三年的时间里，用pit标记的贻贝测量了贻贝足组织中的死亡率、生长和大分子（糖原、葡萄糖、蛋白质、脂质）。不同生境的成活率差异很大（施瓦扎克为0%，鱼塘为38%，坝前区为66%）。鱼塘中贝壳的生长高于坝前，储存化合物的浓度随时间和生境的不同而变化。结果表明，由死亡率、生长和生化指标组成的多个生物学终点的综合评估为评估贻贝易位成功提供了一个有价值的生态指标，这对改善贻贝的保护工作至关重要。他们还强调了在评估对压力的生态生理反应时考虑时间模式的关键重要性，以及为成功迁移淡水贻贝而减轻风险和仔细选择栖息地的必要性。

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引用次数: 0

Enhancing multi-stage and multi-depth soil moisture estimation in winter wheat fields with UAV remote sensing fusion and ensemble learning strategy 基于无人机遥感融合和集成学习策略的冬小麦田多阶段、多深度土壤水分估算

IF 7 2区环境科学与生态学 Q1 ENVIRONMENTAL SCIENCES

Ecological Indicators

Pub Date : 2026-01-23 DOI: 10.1016/j.ecolind.2026.114651

Chaoyang Chu , Zonghan Ma , Ziming Li , Yaqi Hu , Tong Li , Junlin Zhao , Jiayu Li , Xinke Li , Zhenhua Wang , Wenyong Wu

Accurate estimation of soil moisture content (SMC) serves as a crucial foundation for smart irrigation implementation and precision agriculture management. However, traditional methods relying on single data sources or individual machine learning models often suffer from limited generalization ability and insufficient accuracy. To address these challenges, this study utilized Unmanned Aerial Vehicle (UAV) remote sensing to acquire multi-source data (RGB, Multispectral, and Thermal Infrared) across three critical growth stages of winter wheat. We systematically evaluated the perfor-mance of six machine learning algorithms and Stacking ensemble learning strategy for estimating SMC at different soil depths (0–60 cm). The results demonstrated that fusing multi-source data consistently enhanced SMC estimation accuracy compared to single-source data across all growth stages. Temporally, the milk-ripe stage exhibited the strongest correlation with SMC, making it the optimal phenological phase for surface moisture retrieval. During the key filling stage, the XGBoost model combined with fused data (MS + RGB + TIR) achieved the best performance for surface soil (0–20 cm) with an R² of 0.73 and RRMSE of 0.06. In contrast, the GPR model exhibited poor performance in most cases. Although estimation accuracy decreased with soil depth, the fusion approach maintained acceptable results in deeper layers (0–40 cm and 0–60 cm). Furthermore, the Stacking ensemble strategy effectively overcame the limitations of single models，the performance of combinations of different base models and secondary models varied. Specifically, the ensemble model employing Support Vector Regression (SVR) as the secondary learner yielded the highest overall accuracy (R² = 0.76, RRMSE = 0.06). These findings provide a theoretical basis and a robust technical reference for optimizing data fusion and model selection in the precision irrigation management of dryland winter wheat fields.

土壤含水量的准确估算是智能灌溉和精准农业管理的重要基础。然而，依赖单一数据源或单个机器学习模型的传统方法泛化能力有限，精度不足。为了解决这些挑战，本研究利用无人机（UAV）遥感技术获取冬小麦三个关键生育期的多源数据（RGB、多光谱和热红外）。我们系统地评估了六种机器学习算法和堆叠集成学习策略在不同土壤深度（0-60 cm）下估计SMC的性能。结果表明，在所有生长阶段，与单源数据相比，融合多源数据一致地提高了SMC估计精度。从时间上看，乳熟期与SMC的相关性最强，是提取地表水分的最佳物候期。在关键填土阶段，XGBoost模型结合融合数据（MS + RGB + TIR）对0 ~ 20 cm表层土表现最佳，R2为0.73，RRMSE为0.06。相比之下，GPR模型在大多数情况下表现不佳。虽然估算精度随土壤深度的增加而降低，但融合方法在较深层（0-40 cm和0-60 cm）保持可接受的结果。此外，叠加集成策略有效地克服了单一模型的局限性，不同基本模型和次级模型组合的性能存在差异。具体而言，采用支持向量回归（SVR）作为二级学习者的集成模型总体准确率最高（R2 = 0.76, RRMSE = 0.06）。研究结果为旱地冬小麦精准灌溉管理中数据融合和模型选择的优化提供了理论依据和可靠的技术参考。

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引用次数: 0

Negative impacts of Russian-Ukrainian war on forests are overshadowed by climate-driven vegetation greening 俄乌战争对森林的负面影响被气候驱动的植被绿化所掩盖

IF 7 2区环境科学与生态学 Q1 ENVIRONMENTAL SCIENCES

Ecological Indicators

Pub Date : 2026-01-23 DOI: 10.1016/j.ecolind.2026.114607

Siyu Xue, Shaodong Huang, Panfei Fang, Yuying Liang, Yujie Li, Longhuan Wang, Jia Wang

Since the onset of the Russian-Ukrainian war in 2022, the negative impact on ecological environment has received widespread attention, but the mechanisms by which the coupling of war intensity and climatic factors drives forest vegetation dynamics remain unclear. This study developed the War Intensity Index (WI) using conflict point density and classified Ukraine into no war, weak war, and strong war. Utilizing Sentinel datasets through Google Earth Engine, we analyzed the multi-scale spatial-temporal changes in forest Normalized Difference Vegetation Index (NDVI) during the post-war (2022–2024) period compared to pre-war (2019–2021) across the growing season (April–October). We further employed geodetector, a valuable statistical tool for detecting the driving ability of various elements, to investigate the driving effects of four climatic factors. The results indicated that: 1) Overall forest NDVI in Ukraine increased by 5.29 %, but the average NDVI change rate decreased with increasing war intensity (6.20 % > 3.95 % > 1.54 %). 2) Precipitation and temperature were the dominant factors of NDVI, while WI exhibited weak independent explanatory power. The interactions between WI and climatic factors were stronger than WI alone but remained weaker than those among climatic factors. 3) The variability of climatic factors with longitude was more pronounced in strong war than weak war. These findings suggested that the war had a negative impact on forests in specific regions of Ukraine, but was overshadowed by climate-driven greening. The stronger explanatory power of climatic factors in strong war compared to weak war may be attributed to geographical differences in their spatial distribution.

自2022年俄乌战争爆发以来，其对生态环境的负面影响受到广泛关注，但战争强度与气候因子耦合驱动森林植被动态的机制尚不清楚。本研究利用冲突点密度发展战争强度指数（War Intensity Index， WI），将乌克兰划分为无战争、弱战争和强战争。利用Sentinel数据集，通过谷歌Earth Engine分析了战后（2022-2024）与战前（2019-2021）不同生长季节（4 - 10月）森林归一化植被指数（NDVI）的多尺度时空变化。利用地理探测器（geodetector）这一检测各种要素驱动能力的重要统计工具，研究了四种气候因子的驱动效应。结果表明：1)乌克兰森林NDVI总体增加5.29%，但平均NDVI变化率随战争强度的增加而下降（6.20% > 3.95% > 1.54%）。2)降水和温度是NDVI的主导因子，WI的独立解释力较弱。WI与气候因子之间的相互作用强于WI单独存在，但仍弱于气候因子之间的相互作用。③强战争时期气候因子随经度的变异性比弱战争时期更为明显。这些发现表明，战争对乌克兰特定地区的森林产生了负面影响，但被气候驱动的绿化所掩盖。气候因子在强战争中的解释力强于弱战争，这可能与气候因子空间分布的地理差异有关。

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引用次数: 0

A stacked machine learning approach for mapping grazing pressure on the Qinghai-Tibet Plateau: implications for sustainable pasture management 青藏高原放牧压力映射的堆叠机器学习方法：对可持续牧场管理的启示

IF 7 2区环境科学与生态学 Q1 ENVIRONMENTAL SCIENCES

Ecological Indicators

Pub Date : 2026-01-22 DOI: 10.1016/j.ecolind.2026.114631

Jianjun Chen , Qinyi Huang , Yi Sun , Yu Qin , Xinhong Li , Hucheng Li , Jiayuan Yin , Qingmin Cheng , Xiaowen Han , Haotian You , Shuhua Yi

Livestock grazing is one of the primary pressures on the vegetation ecology of the Qinghai-Tibet Plateau (QTP). However, its spatial distribution is highly heterogeneous due to multiple drivers, leading to localized overuse and ecological degradation. This spatial complexity underscores the urgent need for long-term grazing pressure monitoring to support sustainable pasture management. This study developed a spatiotemporal simulation framework for relative grazing pressure (RGP) using a Stacked Generalization Machine Learning (Stacking-ML) model. By integrating county-level actual livestock carrying capacity (ALCC) data with multisource variables (including terrain, vegetation indices, and human footprint indices), we quantified RGP trends in the QTP region over 20 years and evaluated their implications for grazing sustainability. The results showed that: 1) the Stacking-ML model (R² = 0.770, RMSE = 0.0015) outperformed single-algorithm models in RGP simulation, achieving high temporal consistency and spatial resolution; 2) RGP exhibited an east-west gradient, with significantly higher growth rates in the eastern QTP (p < 0.05); 3) policy interventions (e.g., grazing bans in degraded areas) effectively mitigated pressure hotspots in eastern regions. Our framework provides a scalable tool for evidence-based grassland governance, emphasizing the synergy between machine learning and policy-driven sustainability.

放牧是青藏高原植被生态的主要压力之一。但由于多种驱动因素的影响，其空间分布具有高度的异质性，导致局部性过度利用和生态退化。这种空间复杂性强调了长期放牧压力监测的迫切需要，以支持可持续的牧场管理。本研究利用堆叠泛化机器学习（Stacking-ML）模型开发了一个相对放牧压力（RGP）的时空模拟框架。通过将县域实际牲畜承载能力（ALCC）数据与多源变量（包括地形、植被指数和人类足迹指数）相结合，量化了QTP地区20年来的RGP趋势，并评估了其对放牧可持续性的影响。结果表明：1)在RGP模拟中，stack - ml模型（R2 = 0.770, RMSE = 0.0015）优于单算法模型，具有较高的时间一致性和空间分辨率；2) RGP呈东西梯度，东部地区的生长速率显著高于东部地区（p < 0.05）；3)政策干预（如在退化地区封牧）有效缓解了东部地区的压力热点。我们的框架为基于证据的草原治理提供了一个可扩展的工具，强调了机器学习和政策驱动的可持续性之间的协同作用。

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引用次数: 0

Impacts of urban expansion patterns on ecosystem service balance and equity: A case study of Yunnan's border counties, China 城市扩张模式对生态系统服务平衡与公平的影响——以云南边县为例

IF 7 2区环境科学与生态学 Q1 ENVIRONMENTAL SCIENCES

Ecological Indicators

Pub Date : 2026-01-22 DOI: 10.1016/j.ecolind.2026.114636

Xin Yang , Youyan Liu , Jianxin Jiao , Apurva Kakade , Xiaoping Jing , Jiandui Mi , Duman Imanmadi , Ermekov Farabi Kerimbaevich , Jie Gong , Ruijun Long

Understanding and addressing the challenges of ecosystem service supply-demand (ESSD) balance and spatial equity are critical for promoting sustainable development and achieving regional coordination in border regions. This study focuses on 25 border counties in Yunnan Province, examining the supply-demand dynamics of ecosystem services (ESs) under different urban expansion patterns. It employs the Gini coefficient to quantify the equity of ESSD, highlighting differences in ESSD balance and equity between port and non-port counties. The findings indicate that border counties generally exhibit an ESSD surplus, but counties with higher urbanization levels have lower ecosystem service (ES) supply. Regarding spatial equity, port counties consistently show lower equity in ES distribution compared to non-port counties, suggesting significant ecological equity challenges in port counties amid economic growth pursuits. Furthermore, certain urban expansion patterns, particularly adjacent-type expansion (e.g., infilling and edge-expansion), exacerbate ESSD imbalances and reduce spatial equity. Analysis of driving factors reveals that socioeconomic factors, especially increased urbanization rates, significantly negatively affect both the supply and equity of ESs. Based on these findings, the study recommends adopting tailored urban planning strategies that account for local characteristics, balancing the dual objectives of ecological conservation and sustainable development.

认识和应对生态系统服务供需平衡和空间公平的挑战，对促进边境地区可持续发展和实现区域协调具有重要意义。本文以云南省25个边境县为研究对象，研究了不同城市扩张模式下生态系统服务的供需动态。它采用基尼系数来量化社会服务发展的公平性，突出了港口县和非港口县之间社会服务发展平衡和公平性的差异。研究结果表明，边境县总体上存在生态系统服务供给过剩，但城市化水平越高的县生态系统服务供给越少。在空间公平方面，与非港口县相比，港口县在ES分布上的公平程度一直较低，这表明港口县在追求经济增长的同时面临着重大的生态公平挑战。此外，某些城市扩张模式，特别是邻接型扩张（如填充和边缘扩张），加剧了ESSD的不平衡，降低了空间公平。驱动因素分析表明，社会经济因素，特别是城市化率的提高，对社会服务的供给和公平都有显著的负面影响。基于这些发现，研究建议采用符合当地特色的城市规划策略，平衡生态保护和可持续发展的双重目标。

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引用次数: 0

Intensified seasonal droughts and carryover effects amplify negative growth anomalies in Eurasian grasslands during the past four decades 在过去40年里，季节性干旱加剧和结转效应加剧了欧亚草原的负增长异常

IF 7 2区环境科学与生态学 Q1 ENVIRONMENTAL SCIENCES

Ecological Indicators

Pub Date : 2026-01-22 DOI: 10.1016/j.ecolind.2026.114641

Nazhakaiti Anniwaer , Jiana Chen , Yanan Zhang , Weiqing Zhao , Yue He , Kai Wang , Sen Cao , Zaichun Zhu

Eurasian grasslands, among the ecosystems most vulnerable to climate change, have experienced an increasing frequency of negative extreme anomalies in vegetation growth (NEGs) in recent decades, significantly impairing their ecosystem services. Despite their ecological importance, the mechanisms driving NEGs across Eurasian grasslands remain inadequately understood. As annual ecosystems with shallow root systems that respond rapidly to climate fluctuations, grasslands require seasonal-resolution analyses that integrate both immediate and lagged effects of extreme climate events, along with the trans-seasonal growth legacy effects of previous vegetation conditions on subsequent NEGs. To address these gaps, we implemented a comprehensive multifactor coincidence analysis spanning 1982 to 2018, using long-term satellite observations and climate time series to assess these complex interactions. Our results showed that NEGs occurred approximately three times more often at seasonal than annual timescales. Specifically, spring cold extremes dominated spring NEGs over 47% of the study area, while preseason droughts drove summer and autumn NEGs in 55% and 40% of the region, with these drought effects further intensified by preseason NEGs. Notably, the spatial extent of spring NEGs driven by cold extremes shrank from 47% (1982–1996) to 39% (2004–2018), as drought conditions emerged as a more influential factor. Concurrently, the carryover effects from preseason vegetation anomalies on summer and autumn NEGs strengthened substantially over time. These findings underscore the seasonal variability of the drivers of NEGs and highlight the crucial role of biological carryover effects in shaping Eurasian grassland dynamics, offering new insights for ecosystem management and climate adaptation strategies in these important yet vulnerable regions.

欧亚草原是最易受气候变化影响的生态系统之一，近几十年来植被生长负极端异常的频率日益增加，严重损害了其生态系统服务。尽管它们具有重要的生态意义，但在欧亚草原上驱动neg的机制仍然没有得到充分的了解。作为具有浅根系统的一年生生态系统，草原对气候波动反应迅速，因此需要进行季节分辨率分析，以综合极端气候事件的即时和滞后影响，以及先前植被条件对后续neg的跨季节生长遗留影响。为了解决这些差距，我们实施了1982年至2018年的综合多因素巧合分析，使用长期卫星观测和气候时间序列来评估这些复杂的相互作用。我们的研究结果表明，阴性气候在季节时间尺度上的发生频率大约是年时间尺度的三倍。其中，春季极端寒冷天气主导了47%的春季负负气候，季前干旱天气主导了55%和40%的夏季和秋季负负气候，且季前干旱天气进一步加剧了这些干旱影响。值得注意的是，由于干旱条件成为一个更有影响力的因素，极端寒冷导致的春季负负气候的空间比例从47%（1982-1996年）减少到39%（2004-2018年）。同时，季前植被异常对夏季和秋季负气候的延续效应随着时间的推移而显著增强。这些发现强调了neg驱动因素的季节性变化，并强调了生物携带效应在塑造欧亚草原动态中的关键作用，为这些重要但脆弱地区的生态系统管理和气候适应战略提供了新的见解。

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引用次数: 0