Ecological Indicators最新文献_第4页

Pronounced trends in vegetation phenology responses to flash droughts across China (2003−2023) 中国植被物候对突发性干旱响应的显著趋势（2003 ~ 2023年）

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

Ecological Indicators

Pub Date : 2026-01-01 DOI: 10.1016/j.ecolind.2025.114578

Tao Sun , Xinhua Zhang , Yujie Cai , Chun Yang , Zhurui Gao , He Meng , Jiannan Zhang , Yijun Guo , Tsetan Sam

Flash droughts develop rapidly and reach severe levels within a short time, which can significantly impact vegetation phenology. Quantifying vegetation responses to pre-season flash droughts is crucial for evaluating their ecological impacts, yet the mechanisms and temporal dynamics remain unclear. To address this gap, we introduced two metrics (

A_{SOS}

and

A_{EOS}

) representing anomalies in the start (SOS) and end (EOS) of the growing season to quantify phenological responses to pre-season flash droughts. Based on multi-source soil moisture and MODIS NDVI data, we systematically analyzed the response of vegetation phenology to flash drought and its temporal changes in China from 2003 to 2023. Partial correlation analysis was applied to assess the contributions of flash drought characteristics, climatic factors, and hydrological conditions to the interannual variability of vegetation phenological responses to flash droughts. Results show that 49.1% of pre-SOS flash droughts caused SOS advancement, with the advancement decreasing by 0.075 days/year (p < 0.01). In contrast, 61.5% of pre-EOS flash droughts caused EOS advancement, and 38.5% caused delay, with both effects increasing by 0.063 and 0.062 days/year, respectively (both p < 0.01). These trends vary across hydroclimatic regions. The declining SOS response is likely driven by slower flash drought onset speeds, while enhanced EOS responses are mainly attributed to higher drought-period temperatures. This study elucidates the temporal evolution and dominant drivers of phenological responses to pre-season flash droughts, providing insights into ecosystem adaptation strategies under future climate change.

突发性干旱发展迅速，在短时间内达到严重程度，对植被物候有显著影响。定量植被对季前突发性干旱的响应是评估其生态影响的关键，但其机制和时间动态尚不清楚。为了解决这一差距，我们引入了代表生长期开始（SOS）和结束（EOS）异常的两个指标（ASOS和AEOS），以量化对季前突发性干旱的物候响应。基于多源土壤水分和MODIS NDVI数据，系统分析了2003 - 2023年中国植被物候对突发性干旱的响应及其时间变化。采用偏相关分析方法，研究了突发性干旱特征、气候因子和水文条件对植被物候响应年际变化的影响。结果表明，49.1%的突发性干旱导致了SOS提前，提前期减少了0.075天/年（p < 0.01）。相比之下，EOS前期闪旱导致EOS提前的占61.5%，导致EOS延迟的占38.5%，二者分别增加0.063天和0.062天/年（p均为0.01）。这些趋势因水文气候区而异。SOS响应的下降可能是由干旱发生速度变慢造成的，而EOS响应的增强主要归因于干旱期温度的升高。本研究阐明了季前突发性干旱物候响应的时间演变和主要驱动因素，为未来气候变化下的生态系统适应策略提供了见解。

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引用次数: 0

Multi-scale supply-demand security assessment of water-energy-food related ecosystem services from an interaction perspective 基于交互作用视角的水-能-粮生态系统服务多尺度供需安全评价

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

Ecological Indicators

Pub Date : 2026-01-01 DOI: 10.1016/j.ecolind.2025.114584

Zifeng Yuan , Min Cao , Min Chen , Guonian Lü , Yan Liu , Wentong Yang , Hanjie Ni

Ensuring supply-demand security of the water-energy-food (WEF) nexus is vital for balancing socio-economic development and natural ecosystems. However, existing studies often focus on single-scale assessments within individual units and overlook cross-regional interactions. To address this gap, this study develops a multi-scale framework integrating ecosystem services (ESs) as a common lens to capture both intra-regional supply-demand balances and inter-regional interactions. Taking the Yangtze River Delta (YRD) as a case study, we quantified the supply and demand for water yield (WY), carbon sequestration (CS), and food provision (FP) in 2000, 2010, and 2020 using the InVEST model, remote sensing products, and socio-economic statistics. By applying the supply-demand index (SDI), coupling coordination degree (CCD) model, gravity model, and network analysis, we evaluated WEF supply-demand security across provincial, municipal, and county scales. The framework revealed four coupling types that combine intra-regional supply-demand status with inter-regional network importance. Results show that mismatches were widespread, with many units exhibiting strong internal provisioning but limited external interactions. These imbalances became more pronounced at finer scales, as county-level analysis revealed structural divergences often masked in provincial summaries. These insights underscore the utility of the framework in diagnosing cross-scale imbalances and in guiding regionally tailored, multi-level policy responses for improving WEF-Nexus related ESs security.

确保水-能源-粮食关系的供需安全对于平衡社会经济发展和自然生态系统至关重要。然而，现有的研究往往侧重于单个单位内的单一尺度评估，而忽视了跨区域的相互作用。为了解决这一差距，本研究开发了一个整合生态系统服务（ESs）的多尺度框架，作为捕捉区域内供需平衡和区域间相互作用的共同视角。以长江三角洲为例，利用InVEST模型、遥感产品和社会经济统计数据，量化了2000年、2010年和2020年长江三角洲的产水量（WY）、碳固存（CS）和粮食供应（FP）的供求关系。运用供需指数（SDI）、耦合协调度（CCD）模型、引力模型和网络分析，对世界经济论坛在省、市、县三个尺度上的供需安全进行了评价。该框架揭示了将区域内供需状况与区域间网络重要性相结合的四种耦合类型。结果表明，不匹配是普遍存在的，许多单位表现出强大的内部供应，但有限的外部相互作用。这些不平衡在更细的尺度上变得更加明显，因为县级分析显示，结构性差异往往被省级总结所掩盖。这些见解强调了该框架在诊断跨尺度失衡和指导地区量身定制的多层次政策应对方面的效用，以改善世界经济论坛- nexus相关的ESs安全。

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引用次数: 0

Spatial agglomeration of cultural ecosystem services of peri-urban rural landscapes—A cross-site analysis of six megacities in the YREB 城郊乡村景观文化生态系统服务的空间集聚——以长江经济带6个特大城市为例

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

Ecological Indicators

Pub Date : 2026-01-01 DOI: 10.1016/j.ecolind.2025.114561

Ting Zhou, Qiao'an Chen, Siying Lv, Xinli Ke

The spatial agglomeration of cultural ecosystem services (CES) in the rural landscape increases farmers' income by resource sharing and cost reduction, as well as improve consumers' recreational experiences from one-stop consumption. Relevant studies have explored the CES agglomeration regarding agricultural recreation and rural tourism, while little is known about the CES of peri-urban rural landscape. This study investigates the spatial agglomeration of peri-urban rural CES in six typical megacities in the Yangtze River Economic Belt. The result reveals three agglomeration patterns of CES of peri-urban rural landscape, namely, “suburban pattern” (Chongqing and Nanjing), “exurban pattern” (Chengdu and Shanghai) and “even pattern” (Changsha and Wuhan). The GeoDetector model indicates that, the agglomeration of CES depends more on demographic and cultural characteristics, especially high-quality scenic spots as well as historical and cultural villages. Landscape characteristic and market accessibility were not found important in shaping the CES agglomeration as other studies found, which may be related to the peri-urban location advantage. Among all the five rural CES types, a higher agglomeration is more related to Agricultural Experience and Leisure Sightseeing, while less to Distinctive Dinning, Traditional Homestay, and Educational Exploration. Moreover, CES agglomeration is more likely to occur where CES types are diverse compared to homogeneous. This study concludes that, the agglomeration pattern of CES in the rural landscape varies along the urban-rural gradient as well as between different CES types. The findings provide evidence for improving the spatial agglomeration of CES in the rural landscape in the peri-urban megacities.

乡村景观文化生态系统服务的空间集聚通过资源共享和成本降低提高了农民的收入，同时从一站式消费提升了消费者的娱乐体验。相关研究对农业游憩和乡村旅游的消费空间集聚进行了探索，但对城郊乡村景观的消费空间集聚研究甚少。本文以长江经济带6个典型特大城市为研究对象，对城郊农村消费消费空间集聚进行了研究。结果表明，城郊乡村景观消费空间集聚模式有三种，即“近郊格局”（重庆和南京）、“近郊格局”（成都和上海）和“均匀格局”（长沙和武汉）。GeoDetector模型表明，CES的集聚更多地依赖于人口和文化特征，特别是高质量的景区和历史文化村落。景观特征和市场可达性对CES集聚的影响不像其他研究那样重要，这可能与城郊区位优势有关。五种消费消费类型中，农业体验和休闲观光的集聚度较高，特色餐饮、传统民宿和教育探索的集聚度较低。此外，消费电子产品类型的多样性比同质性更容易发生消费电子产品集聚。研究结果表明，农村景观消费空间集聚格局在城乡梯度和不同消费空间类型之间存在差异。研究结果为改善城市周边特大城市农村景观的CES空间集聚提供了依据。

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引用次数: 0

Unraveling large-scale spatial patterns and key drivers of heavy metals uptake by plants 揭示植物对重金属吸收的大尺度空间格局和关键驱动因素

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

Ecological Indicators

Pub Date : 2026-01-01 DOI: 10.1016/j.ecolind.2025.114576

Nana Zhou , Tao Hu , Mengting Wu , Chongchong Qi , Liyuan Chai , Zhang Lin

Heavy metals (HMs) contamination of soils is a critical environmental issue of global concern. HMs transfer from soil to plants is a key pathway for human exposure to soil HMs. Quantifying soil HMs uptake by plants, represented by the soil-to-root transfer coefficient (TC), is crucial for evaluating soil HMs risk and designing phytoremediation strategies. However, large-scale evaluations using laboratory-based techniques are impractical owing to their time-consuming and labor-intensive nature. In this study, a random forest model achieved the highest accuracy among seven machine learning algorithms using a compiled global dataset and enabling the first-ever spatial prediction of soil HMs uptake by plant roots. Extensive reliability and uncertainty analyses were performed to ensure model robustness across diverse environmental settings. Soil pH (35.0 % ± 2.7 %), HMs content (16.1 % ± 1.8 %), and organic carbon (OC, 9.4 % ± 0.9 %) were identified as key drivers of TC. Low pH significantly increased HMs uptake, while high OC levels enhanced bioavailability. Spatial prediction distribution of HMs uptake by plant roots across European soils revealed hotspots in Italy and Austria that were co-driven by HMs content and TC values. These results offer important insights into the spatial patterns of HMs uptake and their underlying drivers, facilitating the identification of contamination hotspots and guiding effective strategies for health risk mitigation and phytoremediation.

土壤重金属污染是全球关注的重大环境问题。土壤微生物向植物转移是人类接触土壤微生物的重要途径。以土壤-根转移系数（TC）为代表的植物对土壤有机质的吸收是评价土壤有机质风险和制定植物修复策略的重要依据。然而，使用基于实验室的技术进行大规模评价是不切实际的，因为它们费时费力。在这项研究中，随机森林模型使用编译的全球数据集在7种机器学习算法中实现了最高的精度，并首次实现了植物根系对土壤hm吸收的空间预测。进行了广泛的可靠性和不确定性分析，以确保模型在不同环境设置中的稳健性。土壤pH值（35.0%±2.7%）、HMs含量（16.1%±1.8%）和有机碳（OC, 9.4%±0.9%）是影响土壤温度的主要因素。低pH显著增加HMs吸收，而高OC水平提高生物利用度。植物根系对土壤有机质吸收的空间预测分布显示，意大利和奥地利是土壤有机质含量和TC值共同驱动的热点地区。这些结果为研究土壤中有机污染物吸收的空间格局及其潜在驱动因素提供了重要见解，有助于识别污染热点，并指导有效的健康风险缓解和植物修复策略。

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引用次数: 0

The explicit-implicit interactive transition measurement and zoning research framework of cultivated land and construction land: A case study of Shandong section of the Yellow River Basin 耕地与建设用地显性-隐性交互过渡测度与区划研究框架——以黄河流域山东段为例

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

Ecological Indicators

Pub Date : 2026-01-01 DOI: 10.1016/j.ecolind.2025.114555

Jian Liu , Yong Yang , Ailing Wang , Linyao Chen , Xue Chen , Ziqi Meng

Urbanization reshaped quantity, structure, and functions of cultivated land (CUL), while transforming demand and efficiency of construction land (COL). These changes drive both cultivated land utilization transition (CULT) and construction land utilization transition (COLT). The study innovatively develops the explicit-implicit interactive transition measurement and zoning research framework of CUL and COL. The CUL's implicit morphology specifically focuses on agricultural production function, while COL's is conceptualized as a complex integrating spatial agglomeration, intensive construction, and economic concentration. The study integrates carbon storage for CUL functionality and carbon emission intensity for COL intensity, achieving a comprehensive evaluation system. This county-level study targets Shandong section of the Yellow River Basin—a key CUL protection and high-quality development zone—addressing strategic priorities through finer-scale analysis. It investigates explicit-implicit interactive transition characteristics of CULT and COLT from 2000 to 2020 and innovatively implements interactive transition zoning. Results showed faster CUL loss in Jinan's urban core and northeastern Yellow River Delta, with more pronounced COL expansion in central and northeastern compared to western regions. CUL functionality rose significantly during 2015–2020, and COL intensity improved markedly during 2010–2015. The explicit-implicit interactive transition trended toward optimization for CULT, while COLT attained both transitional and optimized states. Strong CUL-COL explicit transition correlations occurred in southwestern plains. CUL functionality and COL intensity showed moderate coupling coordination. Based on these findings, interactive transition zoning informed regulatory strategies, supporting food security and land resource optimization.

城市化重塑了耕地的数量、结构和功能，同时改变了建设用地的需求和效率。这些变化推动了耕地利用转型和建设用地转型。本研究创新性地构建了城市群与城市群的显-隐交互过渡测度与区划研究框架。城市群的隐式形态侧重于农业生产功能，而城市群的隐式形态则是空间集聚、集约化建设和经济集中度相结合的综合体。本研究将CUL功能的碳储量与COL强度的碳排放强度相结合，形成综合评价体系。本次县域研究以黄河流域山东段为研究对象，通过更精细的尺度分析，确定战略重点。研究了2000 - 2020年CULT和COLT的外显-内隐交互过渡特征，并创新性地实现了交互过渡分区。结果表明，济南城市核心和黄河三角洲东北部的城市平均城市寿命损失更快，中部和东北部的城市平均城市寿命扩张比西部地区更为明显。2015-2020年CUL功能性显著上升，2010-2015年COL强度显著改善。CULT的外显-内隐交互过渡倾向于优化状态，COLT同时达到了过渡状态和优化状态。西南平原出现了较强的CUL-COL显式过渡相关。CUL功能与COL强度呈中等耦合协调。基于这些发现，互动式过渡区划为监管战略提供了信息，支持粮食安全和土地资源优化。

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引用次数: 0

Fine root trait networks reveal plant adaptation strategies across arid habitats and life forms in northwest China 细根性状网络揭示了西北干旱生境和生命形式下植物的适应策略

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

Ecological Indicators

Pub Date : 2026-01-01 DOI: 10.1016/j.ecolind.2025.114596

Hongyong Wang , Jing Ma , Yiming Chen , Tingting Xie , Furong Niu , Cai He , Yonghua Zhao , Jie Yang , Lishan Shan

Plant trait network analysis offers a powerful approach to quantifying the complex relationships among traits by capturing their topological structure, providing new insights into ecological topics such as phenotypic integration and adaptive trade-offs. However, the links between fine root trait network structure and habitats or life forms remain understudied, particularly in arid regions where ecological vulnerability is pronounced. This study constructed a trait network model based on ten fine root traits measured across 25 species (11 shrubs and 14 herbs) from arid regions in northwestern China, revealing how life form and arid habitats jointly shape network structure. The results revealed that arid habitats and life form significantly shape the fine root trait network structure in desert plants. In drier regions, shrub trait networks become loosely assembled from more modules, with specific root area, root carbon and phosphorus ratio, and root nitrogen and phosphorus ratio as hub traits, forming a hybrid adaptation dominated by conservative strategies while maintaining efficient nutrient acquisition. Conversely, herbs adopt a highly integrated and modular network structure, with root diameter and root nitrogen and phosphorus ratio as hub traits, forming a resource strategy focused on acquisition while incorporating defensive mechanisms. Our findings offer new insights into desert plant adaptation strategies through the lens of trait network architecture, which is key to predicting plant responses to environmental change.

植物性状网络分析通过捕获它们的拓扑结构，为量化性状之间的复杂关系提供了强有力的方法，为表型整合和适应性权衡等生态学主题提供了新的见解。然而，细根性状网络结构与生境或生命形式之间的联系仍未得到充分研究，特别是在生态脆弱性明显的干旱地区。本研究基于中国西北干旱区25种植物（11种灌木和14种草本植物）的10个根系精细性状，构建了一个性状网络模型，揭示了生命形式和干旱生境如何共同塑造网络结构。结果表明，干旱生境和生活方式对荒漠植物根系细性状网络结构具有重要影响。在干旱地区，灌木性状网络由更多的模块松散地组合起来，以特定根面积、根碳磷比和根氮磷比为中心性状，在保持养分高效获取的同时，形成以保守策略为主的杂交适应。相反，草本植物采用高度集成化、模块化的网络结构，以根径和根氮磷比为枢纽性状，形成了以获取为主、兼有防御机制的资源策略。我们的研究结果通过性状网络结构为荒漠植物适应策略提供了新的见解，这是预测植物对环境变化响应的关键。

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引用次数: 0

Detecting nonlinearity in natural population time series with classical and proxy indicators 用经典指标和代理指标检测自然种群时间序列的非线性

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

Ecological Indicators

Pub Date : 2026-01-01 DOI: 10.1016/j.ecolind.2025.114600

Meng Gao , Yutong Yang , Haoyang Gao , Yueqi Wang

Ecosystem dynamics are inherently nonlinear due to complex inter- and intraspecific interactions, which drive the complex population dynamics observed in nature. The nonlinearity in empirical population time series manifests in diverse patterns and can be detected using a variety of methods. In this study, multiple nonlinearity detection methods were systematically applied to empirical population time series from two major databases—the Living Planet Database (LPD) and the Global Population Dynamics Database (GPDD). The methodological framework encompassed three primary approaches: (1) classical statistical tests and forecasting methods that directly analyze time series nonlinearities; (2) machine learning methods that classify time series based on time series morphologies; and (3) the calculation of Early Warning Signals (EWS) as proxies for nonlinearity. First, the classical methods effectively identified nonlinear trends, periodicity, and serial dependence, despite the low concordance (Fleiss’ Kappa: 0.156 and 0.225) among the six test methods. Subsequent application of four machine learning models to a subset of LPD series demonstrated their dual capability to not only detect nonlinearity but also classify series into distinct morphological categories (e.g., monotonic, U-shaped, multimodal). Lastly, extending the nonlinear analysis to higher-order phenomena, EWS indicators were computed for GPDD series, revealing tipping points in 95 series and underscoring the common occurrence of regime shifts in ecosystems. Our findings collectively affirm that complex nonlinear phenomena are pervasive in population time series. This study highlights the complementary value of classical statistical tests, machine learning classification, and EWS indicators in characterizing ecological nonlinearity. These results underscore the utility of dynamical systems theory and multivariate methodological approaches for detecting and interpreting nonlinear patterns and critical transitions in natural population dynamics.

由于复杂的种间和种内相互作用，生态系统动力学本质上是非线性的，这驱动了自然界中观察到的复杂的种群动态。经验总体时间序列的非线性表现为多种模式，可以用多种方法检测。本研究采用多种非线性检测方法，系统地分析了两个主要数据库——地球生命数据库（LPD）和全球人口动态数据库（GPDD）的经验人口时间序列。方法框架包括三种主要方法：(1)直接分析时间序列非线性的经典统计检验和预测方法；(2)基于时间序列形态学对时间序列进行分类的机器学习方法；(3)作为非线性代理的预警信号（EWS）计算。首先，尽管六种检验方法的一致性较低（Fleiss’Kappa: 0.156和0.225），但经典方法有效地识别了非线性趋势、周期性和序列依赖性。随后将四种机器学习模型应用于LPD序列的子集，证明了它们的双重能力，不仅可以检测非线性，还可以将序列分类为不同的形态类别（例如，单调，u形，多模态）。最后，将非线性分析扩展到高阶现象，计算了GPDD序列的EWS指标，揭示了95个序列的临界点，并强调了生态系统中政权转移的普遍发生。我们的研究结果共同证实了复杂的非线性现象在人口时间序列中普遍存在。本研究强调了经典统计检验、机器学习分类和EWS指标在表征生态非线性方面的互补价值。这些结果强调了动力系统理论和多元方法方法在检测和解释自然种群动态中的非线性模式和关键转变方面的效用。

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引用次数: 0

Meta-analysis and field experiments reveal the global impact of management practices on Forest soil organic carbon 荟萃分析和田间试验揭示了管理措施对森林土壤有机碳的全球影响

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

Ecological Indicators

Pub Date : 2026-01-01 DOI: 10.1016/j.ecolind.2025.114582

Yiyun Xia , Xin Chen , Taoran Sun , Jiejie Jiao , Lin Xu

Forest soil organic carbon (SOC) plays a vital role in regulating the global carbon cycle. Forest management practices significantly impact SOC stocks, yet most existing studies remain plot-scale. We conducted a global meta-analysis of harvesting, fertilization, and reforestation using controlled experimental data. Management effects were analyzed by time scale (short-term ≤5 years; long-term >5 years). Harvesting in tropical forests showed a 15.77 % decline (effect size:-0.23,p < 0.01). Short-term harvesting (≤5 years) increased SOC by 7.96 % (effect size: 0.10,p < 0.05), particularly in temperate forests (9.45 %, effect size: 0.08,p < 0.05), while long-term harvesting (>5 years) reduced SOC by 7.76 % (effect size:-0.19, p < 0.01), with tropical forests experiencing a 20.95 % decline (effect size: −0.30, p < 0.01). Fertilization in tropical forests resulted in a 6.30 % increase (effect size: 0.05 p < 0.01). Long-term fertilization in tropical forests showed an 11.24 % increase (effect size:0.11,p < 0.05), but subtropical forests experienced a 10.16 % reduction (p < 0.01). Reforestation had a weak effect on SOC, with long-term reforestation (>5 years) also showing a non-significant impact. We investigated the effects of forest management practices on SOC in subtropical Moso bamboo forests. Harvesting exhibited variable impacts: moderate harvesting significantly reduced SOC by 10.30 %, while light and heavy harvesting increased SOC by 43.24 % and 17.39 %, respectively. Fertilization consistently enhanced SOC, with light and heavy biochar applications increasing SOC by 32.91 % and 42.18 %. Our research highlights that forest management measures exert varying effects on SOC when assessed across different climate zones, underscoring the value of a cross-biome comparative perspective. Therefore, future studies on adaptive climate management should prioritize scientifically differentiated strategies to enhance forest SOC stocks effectively.

森林土壤有机碳（SOC）在调节全球碳循环中起着至关重要的作用。森林管理实践显著影响有机碳储量，但大多数现有研究仍停留在样地尺度上。我们使用对照实验数据对采伐、施肥和再造林进行了全球荟萃分析。按时间尺度（短期≤5年，长期>；5年）分析管理效果。热带森林的采伐下降了15.77%（效应值：-0.23,p < 0.01）。短期采伐（≤5年）增加了7.96%的有机碳（效应值：0.10,p < 0.05），特别是在温带森林（9.45%，效应值：0.08,p < 0.05），而长期采伐（>；5年）减少了7.76%（效应值：-0.19,p < 0.01），热带森林减少了20.95%（效应值：- 0.30,p < 0.01）。在热带森林中，施肥使其增加6.30%（效应值：0.05 p < 0.01）。热带森林长期施肥增加了11.24%（效应值：0.11,p < 0.05），亚热带森林长期施肥减少了10.16% （p < 0.01）。复植对土壤有机碳的影响较弱，长期复植（5年）对土壤有机碳的影响也不显著。研究了不同森林经营方式对亚热带毛竹林土壤有机碳的影响。收获对土壤有机碳的影响不尽相同，中度收获显著降低土壤有机碳10.30%，轻度和重度收获分别使土壤有机碳增加43.24%和17.39%。施肥持续提高有机碳含量，轻炭和重炭分别提高了32.91%和42.18%。我们的研究强调了森林管理措施在不同气候区对有机碳的影响是不同的，强调了跨生物群系比较视角的价值。因此，未来的适应性气候管理研究应优先考虑科学的差异化策略，以有效提高森林有机碳储量。

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引用次数: 0

Automating coastal bioindicator acquisition with deep learning: crab community monitoring for enhanced wetland management 基于深度学习的沿海生物指标采集自动化：螃蟹群落监测对湿地管理的促进

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

Ecological Indicators

Pub Date : 2026-01-01 DOI: 10.1016/j.ecolind.2025.114577

Xuan Gu , Guogui Chen , César Capinha , Wenqing Wang , Xiaoyan Lu , Mao Wang

Major biodiversity changes in the Anthropocene demand enhanced monitoring of ecological communities. Notably, community-level attributes of coastal wetland ecosystem engineers, especially crabs (Brachyura), emerge as crucial ecological indicators. However, traditional expert-based surveys for such data remain labor-intensive, time-consuming, and often invasive. This creates an urgent need for an automated and efficient paradigm shift. We developed an RGB sensor-based automated framework and collected extensive image data from 17 coastal mangrove wetlands across China. This framework integrates expert knowledge with artificial intelligence via a pyramid-style annotation approach, utilizing optimized CNN models (YOLOv5/v8 and EfficientNet) for automated image processing and indicator extraction. Test results show that by integrating attention modules and improved anchors, our model achieved superior performance in crab detection, classification, carapace width measurement, biomass estimation, and burrow detection, matching or exceeding manual methods. It further captured plot-level spatial point patterns, addressing limitations of conventional manual surveys. Our local case study validated that image-extracted community metrics provide independent and essential insights for community analysis, offering a more efficient and comprehensive indicator system than traditional methods. Ecologically, this deep learning-integrated novel method provides an economical solution to expand the dimensionality and breadth of biological data. It enhances management effectiveness by (1) serving as foundational hardware-software for in-situ monitoring and automated data collection (scalable to other benthic fauna), and (2) capturing higher-dimensional community indicators and fine-scale spatial patterns to support biodiversity conservation, blue carbon sequestration, and vegetation protection.

人类世生物多样性的重大变化要求加强对生态群落的监测。值得注意的是，海岸带湿地生态系统工程师的群落属性，尤其是蟹类（Brachyura）成为重要的生态指标。然而，对于此类数据，传统的基于专家的调查仍然是劳动密集型的、耗时的，而且往往是侵入性的。这就产生了对自动化和高效的范式转换的迫切需求。我们开发了一个基于RGB传感器的自动化框架，并收集了中国17个沿海红树林湿地的大量图像数据。该框架通过金字塔式标注方法将专家知识与人工智能相结合，利用优化的CNN模型（YOLOv5/v8和EfficientNet）进行自动图像处理和指标提取。测试结果表明，通过集成关注模块和改进锚，我们的模型在螃蟹检测、分类、壳宽测量、生物量估计和洞穴检测方面取得了优异的性能，匹配或超过了人工方法。它进一步捕获了地块级空间点格局，解决了传统手工调查的局限性。我们的本地案例研究证实，图像提取的社区指标为社区分析提供了独立和必要的见解，提供了比传统方法更有效和全面的指标体系。在生态学上，这种深度学习集成的新方法为扩展生物数据的维度和广度提供了一种经济的解决方案。它通过(1)作为原位监测和自动化数据收集（可扩展到其他底栖动物）的基础硬件软件，(2)捕获高维群落指标和精细尺度空间格局，以支持生物多样性保护、蓝碳封存和植被保护，从而提高管理效率。

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引用次数: 0

Localized assessment of urban forest structures with 3D indicators 基于三维指标的城市森林结构局部评价

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

Ecological Indicators

Pub Date : 2026-01-01 DOI: 10.1016/j.ecolind.2026.114606

Markus Münzinger , Dirk Burghardt , Martin Behnisch

Urban trees, as nature-based solutions, are crucial for climate change adaptation, biodiversity, and human well-being. Although heterogeneous vertical structures are inherent to urban spaces, decisions on tree preservation and planting often rely on 2D assessments, not accounting for the vertical dimension. This study evaluates the added value of 3D data in informing such decisions. A comprehensive analysis of localized differences between 2D and 3D urban forest structure and morphology was conducted for the cities of Amsterdam (Netherlands) and Berlin (Germany) on a 100 × 100 m grid, using spatially explicit indicators. The relationship between horizontal and vertical forest structure was assessed by analyzing mean canopy height relative to canopy coverage. While canopy height generally increased with canopy coverage, high vertical heterogeneity was observed across all urban forest structures. A quadratic regression of canopy coverage against the canopy 3D index revealed a complex, non-linear relationship, indicating vertical structure cannot be reliably predicted from horizontal data alone. Furthermore, evaluating the impact of vertical structures on the spatial relationship between trees and buildings revealed patterns linked to urban morphology. Although significant variation was observed, 2D assessments tended to indicate tree proportions up to 25 % higher than volume-based measurements in building-dominated areas, while indicating lower proportions in tree-dominated areas. Overall, the study revealed large local and site-specific differences in vertical structures that could not be inferred from 2D data. By explicitly accounting for data resolution, spatial scale and context, the added value of 3D assessments for managing the ecosystem services provided by urban trees was demonstrated.

城市树木作为基于自然的解决方案，对适应气候变化、生物多样性和人类福祉至关重要。虽然不同的垂直结构是城市空间固有的，但关于树木保护和种植的决定往往依赖于二维评估，而不是考虑垂直维度。本研究评估了3D数据在告知此类决策中的附加价值。本文以荷兰阿姆斯特丹和德国柏林为研究对象，采用空间显式指标，在100 × 100 m网格上对城市森林二维和三维结构和形态的局部差异进行了综合分析。通过分析平均冠层高度与冠层盖度的关系，评价了水平和垂直森林结构之间的关系。冠层高度总体上随冠层盖度的增加而增加，但各城市森林结构的垂直异质性均较高。冠层覆盖度与冠层三维指数的二次回归揭示了一种复杂的非线性关系，表明仅靠水平数据无法可靠地预测垂直结构。此外，通过评估垂直结构对树木和建筑之间空间关系的影响，揭示了与城市形态相关的模式。虽然观察到显著的差异，但二维评估往往表明，在建筑为主的地区，树木比例比基于体积的测量高25%，而在树木为主的地区，树木比例较低。总体而言，该研究揭示了无法从2D数据推断出的垂直结构的巨大局部和特定地点差异。通过明确考虑数据分辨率、空间尺度和背景，论证了城市树木提供的生态系统服务管理的3D评估的附加价值。

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引用次数: 0