Ecological Indicators最新文献_第10页

Spatiotemporal variation in carbon sequestration in the forest ecosystem of Hainan Island over a 30-year period and its driving factors 30年海南岛森林生态系统固碳时空变化及其驱动因素

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.2025.114587

Zhihao Pi , Xinyi Liu , Yuan Wei , Xu Wang , Zhuo Zang , Xiqiang Song

Tropical forest ecosystems are critical for global carbon cycling, yet long-term spatiotemporal dynamics of their carbon sequestration and driving mechanisms remain unclear in island ecosystems—particularly for Hainan Island, China's largest tropical forest stronghold. This knowledge gap limits the formulation of targeted forest carbon management strategies to achieve national“dual carbon”goals. To fill this gap, we analyzed the spatiotemporal variation in forest ecosystem carbon sequestration on Hainan Island from 1990 to 2020 and its driving factors, using 30 m land use data, 1 km resolution NDVI/meteorological/human activity data, and field-measured carbon density data as inputs. Methodologically, we integrated the InVEST model, Local Moran's I, and geographic detector techniques.Model accuracy was validated through multiple approaches: (1) The 30 m land use data showed >90 % overall classification accuracy; (2) Forest area derived from land use data was highly consistent with the 2021 Hainan Forest Resource Survey; (3) Carbon storage results overlapped with regional studies with a relative difference < 5 %.Our results showed that: (1) Land use changed substantially—forested land decreased by 3.62 %, agricultural land expanded by 5.27 %, and urbanized land increased by 4.01 % annually; (2) Forest carbon sequestration exhibited a “double-peak” trend, with five stages of change closely linked to forestry policies; (3) Spatially, carbon sequestration showed significant clustering, with high values in central mountainous regions and low values in coastal areas; (4) NDVI, elevation, and slope were the dominant drivers, and the nonlinear enhancement effect of NDVI and elevation had the strongest synergistic impact.This study not only clarifies the long-term dynamics and driving mechanisms of forest carbon sequestration on Hainan Island but also provides a scientific basis for optimizing tropical island forest carbon management and supporting the achievement of national carbon neutrality goals.

热带森林生态系统对全球碳循环至关重要，但在岛屿生态系统中，其碳封存的长期时空动态及其驱动机制尚不清楚，特别是在中国最大的热带森林据点海南岛。这种知识差距限制了制定有针对性的森林碳管理战略以实现国家“双碳”目标。为了填补这一空白，利用30 m土地利用数据、1 km分辨率NDVI/气象/人类活动数据和野外实测碳密度数据，分析了1990 - 2020年海南岛森林生态系统碳汇的时空变化及其驱动因素。在方法上，我们集成了InVEST模型、Local Moran’s I和地理检测器技术。通过多种方法验证了模型的精度：①30 m土地利用数据总体分类精度为90%；(2)土地利用数据得到的森林面积与2021年海南省森林资源调查结果高度一致；(3)碳储量研究结果与区域研究结果重叠，相对差异达5%。结果表明：(1)土地利用变化明显，林地面积年均减少3.62%，农用地面积年均增加5.27%，城市化用地年均增加4.01%；(2)森林固碳呈“双峰”趋势，其变化阶段与林业政策密切相关；③从空间上看，碳汇呈显著的集聚性，中部山区高，沿海地区低；(4) NDVI、高程和坡度是主要驱动因子，且NDVI和高程的非线性增强效应协同作用最强。本研究不仅阐明了海南岛森林固碳的长期动态和驱动机制，而且为优化热带岛屿森林碳管理，支持国家碳中和目标的实现提供了科学依据。

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引用次数: 0

Passive acoustic monitoring predicts higher avian diversity metrics than traditional bird surveys across multiple Australian bioregions 被动声学监测预测的鸟类多样性指标比传统的鸟类调查在多个澳大利亚生物区域更高

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

Ecological Indicators

Pub Date : 2025-12-19 DOI: 10.1016/j.ecolind.2025.114533

Brendan Doohan , Sebastian Hoefer , Slade Allen-Ankins , Vesla Nilsen , Lin Schwarzkopf

Technological advances over the last two decades have seen a large uptake in passive acoustic monitoring (PAM) to supplement traditional biodiversity surveys. To address the growing backlog of acoustic recordings these projects create, multispecies acoustic classifiers are now widely used in favour of manually processing data. Despite the uptake of these technologies, the efficacy of these recognisers needs to be evaluated to ensure they are detecting levels of diversity and community structure similar to traditional surveys. This study compared metrics of avian diversity across eastern Australia, between traditional bird surveys (both dawn, and dawn + nocturnal), and PAM processed using BirdNET, a widely used multi-species classifier. On average, PAM and multi-species classifiers returned higher values for all assessed diversity metrics (Species Richness, Chao2 estimators, Petchey's Functional Diversity, Rao's Q and Phylogenetic Distance), however traditional surveys supplemented with nocturnal surveys returned intermediate values. The efficacy of classifiers varied considerably across the study locations, with the number of incorrect identifications in the tropics substantially higher than those in temperate areas. Both methodologies failed to detect certain taxonomic groups, some threatened species, and detected significantly different avian communities. While these results provide a promising outlook for the future of PAM, it underscores the importance of maintaining traditional surveys as part of biodiversity monitoring, and relying on skilled ornithologists to ensure recorded acoustic data is appropriately interrogated. Furthermore, this study cautions against relying solely on automated classifiers in regions where training data for models is depauperate, such as Australia's tropical and subtropical woodlands.

在过去二十年的技术进步中，被动声监测（PAM）被广泛采用，以补充传统的生物多样性调查。为了解决这些项目产生的不断增长的声学记录积压问题，多物种声学分类器现在广泛用于手动处理数据。尽管采用了这些技术，但需要评估这些识别器的有效性，以确保它们能够检测到与传统调查类似的多样性水平和社区结构。本研究比较了澳大利亚东部的鸟类多样性指标，在传统的鸟类调查（黎明，黎明+夜间）和使用广泛使用的多物种分类器BirdNET处理的PAM之间进行了比较。平均而言，PAM和多物种分类器在所有评估的多样性指标（物种丰富度、Chao2估计值、Petchey's功能多样性、Rao's Q和系统发育距离）中返回较高的值，而传统调查补充夜间调查返回的值为中间值。分类器的功效在不同的研究地点差异很大，热带地区的错误识别数量明显高于温带地区。这两种方法都未能检测到某些分类类群和一些濒危物种，并且检测到明显不同的鸟类群落。虽然这些结果为PAM的未来提供了一个充满希望的前景，但它强调了将传统调查作为生物多样性监测的一部分的重要性，并依靠熟练的鸟类学家来确保记录的声学数据得到适当的询问。此外，该研究警告说，在模型训练数据不足的地区，如澳大利亚的热带和亚热带林地，不要仅仅依赖自动分类器。

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引用次数: 0

Defining habitat scenarios to integrate non-target arthropod relevance into landscape-based environmental risk assessment: A proof of concept 定义栖息地情景，将非目标节肢动物相关性纳入基于景观的环境风险评估：概念验证

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

Ecological Indicators

Pub Date : 2025-12-18 DOI: 10.1016/j.ecolind.2025.114548

Daniel Paredes , Leo Bürger , Artur Sarmento , Grzegorz Sowa , António Alves da Silva , Fernando Alvárez , Alessio Ippolito , Steven Droge , Andreas Focks , Lorraine Maltby , Louise Wipfler , Jose Paulo Sousa

Environmental risk assessment of plant protection products increasingly requires methods that incorporate the complexity of agricultural landscapes and the roles of non-target arthropods in ecosystem service provision. However, existing approaches often lack spatial specificity and fail to support the development of targeted and ecologically meaningful protection goals. This study presents a proof-of-concept method designed to assess the relevance of non-target arthropods families across agricultural habitat scenarios, serving as a step toward more spatially explicit and biodiversity-sensitive environmental risk assessment frameworks. Using high-resolution landscape data from seven European countries, we randomly generated 29,500 agricultural landscapes across nine major crops and grouped them into four habitat scenarios categories based on crop diversity and the proportion of natural habitat. We used a bibliographic dataset covering 30 representative non-target arthropods families as a proxy to estimate family-level relevance scores for each habitat scenario, based on the proportion of land use types and literature-derived occurrence data. The results from this first application are exploratory and serve to evaluate the method's operational structure and scalability. They are not intended as definitive ecological patterns but rather illustrate how the proposed habitat scenario framework can be applied to generate relevance estimates. Future work should focus on validating outputs with empirical biodiversity data, integrating functional traits such as mobility and pesticide sensitivity, and expand habitat representation. Beyond its conceptual value, the framework provides a practical tool to identify relevant arthropod families within specific habitat scenarios, supporting targeted mitigation and integrated pest management strategies. It thus links functional biodiversity with regulatory decision-making to define measurable protection goals and align environmental risk assessment with the ecosystem services framework.

植保产品的环境风险评估越来越需要结合农业景观的复杂性和非目标节肢动物在生态系统服务提供中的作用的方法。然而，现有的方法往往缺乏空间特异性，无法支持制定有针对性和生态意义的保护目标。本研究提出了一种概念验证方法，旨在评估非目标节肢动物科在农业栖息地情景中的相关性，为建立更具空间明确性和生物多样性敏感性的环境风险评估框架迈出了一步。利用来自7个欧洲国家的高分辨率景观数据，我们随机生成了9种主要作物的29,500个农业景观，并根据作物多样性和自然栖息地的比例将其分为4个栖息地情景类别。基于土地利用类型的比例和文献来源的发生数据，我们使用了一个涵盖30个代表性非目标节肢动物科的书目数据集作为代理，来估计每个栖息地情景的科级相关性得分。第一个应用程序的结果是探索性的，用于评估该方法的操作结构和可伸缩性。它们的目的不是作为确定的生态格局，而是说明拟议的生境情景框架如何适用于产生相关性估计。未来的工作应侧重于利用经验生物多样性数据验证产出，整合流动性和农药敏感性等功能特征，并扩大栖息地代表性。除了其概念价值之外，该框架还提供了一个实用工具，可在特定栖息地情景中确定相关节肢动物科，支持有针对性的缓解和综合虫害管理战略。因此，它将功能性生物多样性与监管决策联系起来，以确定可衡量的保护目标，并使环境风险评估与生态系统服务框架保持一致。

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引用次数: 0

Plant life forms shape phosphorus dynamics and rhizosphere microbial communities under gradient nutrient loadings 植物生命形态在梯度养分负荷下影响磷动态和根际微生物群落

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

Ecological Indicators

Pub Date : 2025-12-18 DOI: 10.1016/j.ecolind.2025.114558

Xiaowen Ma , Weicheng Yu , Wanxin Guo , Wenhao Xiong , Feng Li , Zhengmiao Deng , Yonghong Xie

Phosphorus (P) cycling at the sediment-water interface is a critical driver of eutrophication, yet the roles of aquatic macrophytes of different life forms and their associated rhizosphere microbial communities remain poorly understood. Here, we established three aquatic macrophyte-water-sediment mesocosms involving the submerged Vallisneria natans, rooted floating-leaf Nymphoides peltata, and emergent Typha angustifolia under gradient nutrient loadings to examine the mobility of phosphorus in aquatic macrophyte-water-sediment systems. Results showed life form-specific and phenology-dependent patterns in biomass accumulation, P uptake, P diffusion fluxes, and sediment P fractions. V. natans exhibited a hump-shaped biomass and P uptake trajectory, and effectively suppressed P release from pore water with higher microbial diversity under high nutrient loading. N. peltata exhibits a more conservative strategy, enhancing phosphorus retention within sediments while exerting limited control over sediment-water phosphorus exchange. T. angustifolia consistently sequestered P through extensive belowground organs, with maximal uptake under medium nutrient loading. Compared with the simpler and less stable network of V. natans, T. angustifolia supported a more complex and resilient rhizosphere microbial network. Microbial key taxa showed the close correlations with phosphorus properties of macrophyte-water-sediment systems. These findings emphasize the importance of integrating plant functional traits, phenology, and microbial feedbacks to explain P cycling in wetlands, offering mechanistic insights for optimizing plant-based strategies in eutrophication control and ecological restoration.

沉积物-水界面的磷循环是富营养化的关键驱动因素，但不同生命形式的水生植物及其相关根际微生物群落的作用仍然知之甚少。在此，我们建立了三个水生植物-水-沙生态系统，包括在梯度养分负荷下的沉水水草、有根浮叶水草和急生叶假丝蒲，以研究水生植物-水-沙系统中磷的流动性。结果表明，生物量积累、磷吸收、磷扩散通量和沉积物磷组分具有生命形式特异性和物候依赖性。在高养分负荷条件下，水草生物量和磷吸收呈驼峰状，微生物多样性较高，能有效抑制孔隙水中磷的释放。N. peltata表现出更保守的策略，增强沉积物中的磷保留，同时对沉积物-水磷交换施加有限的控制。黄叶参通过广泛的地下器官吸收磷，在中等营养负荷下吸收最多。与简单且不稳定的根际微生物网络相比，刺叶根际微生物网络更复杂、更有弹性。微生物关键类群与大型植物-水-沉积物系统的磷特性密切相关。这些发现强调了整合植物功能性状、物候和微生物反馈来解释湿地磷循环的重要性，为优化植物为基础的富营养化控制和生态恢复策略提供了机制见解。

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引用次数: 0

Wetland restoration enhances soil carbon sequestration in lake ecosystems: Integrating multi-source remote sensing and optimized ensemble machine learning to map soil organic carbon density 湿地恢复增强湖泊生态系统土壤固碳：结合多源遥感和优化集成机器学习绘制土壤有机碳密度

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

Ecological Indicators

Pub Date : 2025-12-18 DOI: 10.1016/j.ecolind.2025.114551

Lin Tian , Weiyu Huang , Geng Cui , Xin Huang , Feifan Cui , Yinying Wei , Chuangjia Zhao , Shouzheng Tong , Ao Wang

Lake wetlands play essential roles in flood regulation, water purification, and biodiversity, and restoring degraded wetlands can enhance their carbon-sink capacity. However, knowledge regarding the spatial patterns, temporal dynamics, and key drivers of soil organic carbon density (SOCD) in restored wetlands is limited. This study integrated multi-source remote sensing and machine-learning approaches to map SOCD in a restored lake wetland and to assess its spatiotemporal evolution from 2000 to 2023. Results showed that soil depth, soil physicochemical properties, and near-infrared spectral features were the major drivers of SOCD variability. Among nine models tested, CatBoost achieved the highest accuracy under random five-fold cross-validation (R² = 0.49 ± 0.06; MAE = 6.78 ± 0.58 MgC·ha⁻¹; RMSE = 9.30 ± 1.17 MgC·ha⁻¹; RPIQ = 1.56 ± 0.17), whereas the RF model performed most robustly under spatially grouped cross-validation(R² = 0.41 ± 0.16, MAE = 7.45 ± 0.33 MgC·ha⁻¹; RMSE = 9.76 ± 0.64 MgC·ha⁻¹; RPIQ = 1.48 ± 0.24), demonstrating the advantage of ensemble learning in capturing spatial heterogeneity. Spatially, SOCD decreased from the upland to the lakeshore zones. Temporally, SOCD declined from 2004 to 2017 due to water-level fluctuations and aquaculture disturbance, with high-SOCD areas shrinking by 38.34 km². Following the “Return-Aquaculture-to-Wetland” restoration project launched in 2017, SOCD recovered markedly, reaching a two-decade maximum in 2022 (high-SOCD area: 125.54 km²; regional mean: 47.60 MgC·ha⁻¹). These findings provide a scientific basis for wetland carbon-stock assessments and ecological-restoration monitoring and demonstrate the potential of combining multi-source remote sensing and machine learning for large-scale SOCD mapping.

湖泊湿地在洪水调节、水体净化和生物多样性等方面具有重要作用，恢复退化湿地可以增强其碳汇能力。然而，关于恢复湿地土壤有机碳密度（SOCD）的空间格局、时间动态和关键驱动因素的认识有限。本研究采用多源遥感与机器学习相结合的方法，绘制了2000 - 2023年湖泊湿地土壤有机碳的时空演变特征。结果表明，土壤深度、土壤理化性质和近红外光谱特征是土壤SOCD变化的主要驱动因素。在9个模型测试,CatBoost实现最高精度下随机5倍交叉验证(R2 = 0.49±0.06;美= 6.78±0.58 MgC·哈−1;RMSE = 9.30±1.17 MgC·哈−1;RPIQ = 1.56±0.17),而空间下的射频模型表现最强劲的分组交叉验证(R2 = 0.41±0.16,美= 7.45±0.33 MgC·哈−1;RMSE = 9.76±0.64 MgC·哈−1;RPIQ = 1.48±0.24),展示整体学习的优势在捕捉空间异质性。从空间上看，SOCD由高地向湖滨区递减。在时间上，由于水位波动和养殖干扰，2004 - 2017年SOCD呈下降趋势，高SOCD面积缩小38.34 km2。继2017年启动的“返养殖回湿地”恢复项目后，SOCD显著恢复，并在2022年达到20年来的最大值（高SOCD面积：125.54 km2；区域平均值：47.60 MgC·ha−1）。这些研究结果为湿地碳储量评估和生态恢复监测提供了科学依据，并展示了多源遥感与机器学习相结合用于大规模SOCD制图的潜力。

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引用次数: 0

Suggestions for extending, expanding, and integrating passive acoustic monitoring programs 对无源声监测项目的延伸、扩展和整合的建议

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

Ecological Indicators

Pub Date : 2025-12-17 DOI: 10.1016/j.ecolind.2025.114549

Connor M. Wood

Passive acoustic monitoring (PAM) has entered the ecological mainstream, and further growth is likely. How can the growth of PAM be guided for maximum research and conservation impact? I offer suggestions for how terrestrial PAM programs can proactively plan for extension (growth over time), expansion (growth over space and/or species surveyed), and integration (growth in the number of teams involved, leading to synthesis of data from multiple programs). The three modes of growth are independent, though expansion in space is usually predicated on concurrent extension. Key points include: (1) hardware and recording choices are critical because they irrevocably define the limits of the audio dataset, the characteristics of the audio, and the sampling unit itself; (2) analysis software is less critical because audio can be reanalyzed with new tools; (3) long-term planning for the retention of experienced personnel (e.g., via pathways for professional advancement) and database development (e.g., building a streamlined bioacoustics pipeline with purpose-built output files) are important; and (4) the interpersonal aspects of multi-project syntheses are likely to be critical to integration, though statistical challenges (not addressed at length herein) may also be formidable without careful planning. Careful growth of passive acoustic monitoring programs can lead to new insights for ecology and conservation; under-planned growth can lead to wasted resources and missed opportunities – steep costs in an era of limited resources and rapid change.

被动声监测（PAM）已进入生态主流，并有可能进一步发展。如何引导PAM的发展，以获得最大的研究和保护影响？我就陆地PAM项目如何主动规划扩展（随时间增长）、扩展（随空间和/或所调查物种的增长）和整合（参与团队数量的增长，导致来自多个项目的数据的综合）提出了建议。这三种增长模式是独立的，尽管空间的扩展通常基于并发扩展。关键点包括：(1)硬件和录音选择至关重要，因为它们不可逆转地定义了音频数据集、音频特征和采样单元本身的限制；(2)分析软件不那么重要，因为音频可以用新的工具重新分析；(3)为保留经验丰富的人员（例如，通过专业晋升途径）和数据库开发（例如，建立一个具有专用输出文件的流线型生物声学管道）进行长期规划是重要的；(4)多项目综合的人际关系方面可能对集成至关重要，尽管统计方面的挑战（在这里没有详细说明）如果没有仔细的计划也可能是可怕的。被动声学监测项目的精心发展可以为生态和保护带来新的见解；计划不足的增长可能导致资源浪费和错失机会——在一个资源有限、变化迅速的时代，这是高昂的成本。

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引用次数: 0

Seasonal migration of flood risk: Multi-ecosystem threshold triggering and adaptive management 洪水风险的季节性迁移：多生态系统阈值触发与适应性管理

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

Ecological Indicators

Pub Date : 2025-12-17 DOI: 10.1016/j.ecolind.2025.114557

Xiaoxu Liu , Xiaomin Liu , Tingxi Liu , Miao Yu , Yaotian Yang

To gain a deeper understanding of the evolving characteristics of floods across different ecosystems and their meteorological driving conditions, in this study, a transferable, all-season, multi-ecosystem methodology for setting meteorological threshold warnings for floods of various magnitudes is established. An in-depth analysis of the differences in evolving flood characteristics and driving conditions between ecosystems that have been intensely disturbed by human activities and natural/seminatural systems is conducted. A flood management measure is proposed, which draws on the ecological resilience of forest and grassland systems. We emphasize that the philosophy of flood control should shift from hard-defence to adaptive governance. In the Yellow River Basin, the universal driving factors of floods are precipitation, humidity, and sunshine, with atmospheric pressure requiring additional consideration in water bodies and wetlands. Winter floods are most sensitive to sunshine percentage and precipitation, whereas floods in spring, summer, and autumn are primarily driven by humidity and sunshine hours. Since 1985, flood risk in the Yellow River Basin has entered a phase of persistent intensification. This intensification has accelerated across the entire basin in the 21st century and has reached 4–57 times the average rate of increase. Flood severity will continually rise throughout the basin. In this study, the peak flood months for each ecosystem are identified, with the most significant increases in flood momentum observed in January and September. The traditional summer-and-autumn flood season boundary has extended into winter and spring, indicating that flood risk in the Yellow River Basin has broken through traditional seasonal patterns and is intensifying across all seasons and multiple ecosystems. Human activities could increase flood risk. However, agricultural and settlement systems, which are entirely human-dominated, have the potential to mitigate floods in the long term through sustained management. Deserts are the most prone to triggering floods, grasslands carry the hidden danger of long-term persistent increases in flood risk, and floods in water bodies and wetlands are prone to evolving into high-intensity events. The research findings provide decision-makers with actionable pathways for flood early warning and adaptive management.

为了更深入地了解洪水在不同生态系统的演变特征及其气象驱动条件，本研究建立了一种可转移的、全季节的、多生态系统的不同震级洪水气象阈值预警设置方法。深入分析了受人类活动强烈干扰的生态系统与自然/半自然系统在洪水特征和驱动条件演变方面的差异。提出了一种利用森林和草地系统生态恢复力的洪水管理措施。我们强调，防洪理念应从硬防御转向适应性治理。在黄河流域，洪水的普遍驱动因子是降水、湿度和日照，水体和湿地需要额外考虑大气压力。冬季洪水对日照率和降水最为敏感，春、夏、秋汛期洪水主要受湿度和日照时数的影响。1985年以来，黄河流域洪水风险进入持续加剧阶段。在21世纪，这种加剧在整个盆地加速，达到了平均增长率的4-57倍。整个流域的洪水严重程度将持续上升。在本研究中，确定了各生态系统的洪峰月份，其中1月和9月的洪水动量增加最为显著。传统的夏秋汛期边界向冬春汛期延伸，表明黄河流域洪水风险已经突破了传统的季节格局，并在各季节和多个生态系统中不断加剧。人类活动可能会增加洪水风险。然而，完全由人类主导的农业和定居系统，通过持续的管理，有可能在长期内减轻洪水。沙漠最容易引发洪水，草原存在洪水风险长期持续增加的隐患，水体和湿地的洪水容易演变成高强度事件。研究结果为决策者提供了洪水预警和适应性管理的可操作路径。

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引用次数: 0

Contribution of moss crusts to soil multifunctionality in karst ecosystems under extreme climate conditions 极端气候条件下喀斯特生态系统苔藓结皮对土壤多功能性的贡献

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

Ecological Indicators

Pub Date : 2025-12-17 DOI: 10.1016/j.ecolind.2025.114546

Wei Zheng , Qian Wu , Xun Duan , Jiaxin Lai , Wende Yan , Jinshui Wu

Frequent extreme climate events globally threaten ecosystem services and functions, particularly in fragile regions. As one of the vital “ecosystem engineers” and “living skin”, mosses have been demonstrated to impact soil biogeochemical cycles markedly, yet their role in shaping the soil multifunctionality of fragile regions under extreme climates remains unclear. A one-year in-situ field experiment was conducted to simulate the effect of moss crust on soil multifunctionality in intense karst rocky desertification regions under extreme drought and heavy precipitation. Compared with bare soil, the moss crust significantly enhanced soil multifunctionality, with increases of 44.0 %, 32.7 %, and 54.8 % in extreme drought, ambient precipitation, and heavy precipitation conditions, respectively. This was primarily attributed to moss crust promoting the related variable on soil carbon cycling, such as improving β-1,4-glucosidase and microbial biomass carbon under extreme climate conditions. Furthermore, moss crust reduced the dependency of soil on precipitation by boosting above-ground biomass and modulating microbes to enhance soil multifunctionality. Collectively, this finding underscores the critical role of moss crusts in sustaining soil multifunctionality of vulnerable ecosystems under extreme climate contexts, and provides new insights into soil protection. However, the limited biomass input of moss crusts and the potential imbalance in nitrogen fraction conversion are critical issues that require careful consideration. Accordingly, combining moss crusts with diverse vegetation restoration approaches may be an effective strategy for ecological restoration and carbon sequestration enhancement in fragile ecosystems affected by climate change.

频繁的全球极端气候事件威胁着生态系统服务和功能，特别是在脆弱地区。苔藓作为重要的“生态系统工程师”和“活皮肤”之一，已被证明对土壤生物地球化学循环有显著影响，但其在极端气候条件下脆弱地区土壤多功能性形成中的作用尚不清楚。通过为期一年的现场试验，模拟了极端干旱强降水条件下喀斯特石漠化地区苔藓结皮对土壤多功能性的影响。与裸地相比，苔藓结皮显著增强了土壤的多功能性，在极端干旱、环境降水和强降水条件下，苔藓结皮分别提高了44.0%、32.7%和54.8%。这主要是由于苔藓结皮在极端气候条件下促进了土壤碳循环的相关变量，如提高β-1,4-葡萄糖苷酶和微生物生物量碳。此外，苔藓结皮通过增加地上生物量和调节微生物来增强土壤的多功能性，从而降低了土壤对降水的依赖性。总的来说，这一发现强调了极端气候背景下苔藓结皮在维持脆弱生态系统土壤多功能性方面的关键作用，并为土壤保护提供了新的见解。然而，苔藓结皮有限的生物量输入和氮组分转化的潜在不平衡是需要认真考虑的关键问题。因此，将苔藓结皮与多种植被恢复方法相结合，可能是气候变化影响下脆弱生态系统生态恢复和固碳增强的有效策略。

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引用次数: 0

Comprehensive ecological effect evaluation of photovoltaic stations using entropy-weighted TOPSIS 基于熵权TOPSIS的光伏电站综合生态效应评价

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

Ecological Indicators

Pub Date : 2025-12-17 DOI: 10.1016/j.ecolind.2025.114542

Jiajia Qiao , Min Yan , Li Zhang , Li Zhou , Yongqiang Liu , Li Li , Zhijie Gao

Driven by the challenges of global warming and decarbonization, the solar photovoltaic (PV) industry has grown rapidly over recent decades. With abundant land resources and excellent solar radiation, the Xinjiang Uygur Autonomous Region (Xinjiang) has become as a key location for large-scale PV stations. Given its fragile and sensitive ecosystems, evaluating the ecological effects of PV construction is essential. This study established a multidimensional evaluation framework based on land surface, soil, meteorological, and vegetation indicators, and applied an entropy-weighted TOPSIS method to assess the ecological impacts of PV stations in Xinjiang. The results showed that (1) PV station significantly reduced land surface albedo and consequently lowered land surface temperature (LST). Although the reduction in albedo was greater in Bare PV areas, the cooling effect was slightly stronger in Veg PV due to vegetation-mediated regulation, with LST decreasing by 0.34 °C in Veg PV and 0.32 °C in Bare PV. (2) Both Veg PV and Bare PV exhibited similar ecological responses, with increases in evapotranspiration (ET), soil moisture (SM), and leaf area index (LAI), while the Enhanced Vegetation Index (EVI) showed a decreasing trend. (3) Overall, the construction of PV stations has had a positive impact on the ecosystems of Xinjiang, with Veg PV exhibiting more pronounced ecological improvements. In summary, the comparative analysis between Veg PV and Bare PV highlights the regulatory role of the underlying surface in shaping ecological outcomes, further underscoring the substantial potential of Veg PV in advancing the co-development of energy security and ecological sustainability.

近几十年来，在全球变暖和脱碳挑战的推动下，太阳能光伏（PV）产业发展迅速。新疆维吾尔自治区拥有丰富的土地资源和良好的太阳辐射，已成为大型光伏电站的重点选址。鉴于其脆弱而敏感的生态系统，评估光伏建设的生态效应至关重要。建立了基于地表、土壤、气象、植被等指标的多维评价框架，应用熵加权TOPSIS方法对新疆光伏电站生态影响进行了评价。结果表明：(1)光伏电站显著降低了地表反照率，从而降低了地表温度。尽管裸PV区反照率降低幅度更大，但由于植被介导的调节，裸PV区的降温效果略强，地表温度分别降低了0.34°C和0.32°C。(2)植被和裸地均表现出相似的生态响应，蒸散发（ET）、土壤水分（SM）和叶面积指数（LAI）均呈增加趋势，而植被增强指数（EVI）呈下降趋势。(3)总体而言，光伏电站建设对新疆生态系统产生了积极影响，其中蔬菜光伏电站的生态改善更为明显。综上所述，植物光伏和裸光伏的对比分析突出了下垫面在形成生态结果中的调节作用，进一步强调了植物光伏在促进能源安全和生态可持续性共同发展方面的巨大潜力。

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引用次数: 0

Early warning study on ecological risk of heavy metals in soil based on XGBoost-IER coupled model - A case study of black soil area in Jilin province 基于XGBoost-IER耦合模型的土壤重金属生态风险预警研究——以吉林省黑土区为例

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

Ecological Indicators

Pub Date : 2025-12-17 DOI: 10.1016/j.ecolind.2025.114554

Jinhui Tan , Yanan Chen , Wanying Shi , Jinying Li , Zhengshan Hou , Jiquan Zhang , Dianqi Pan , Yichen Zhang , Xue Chen

The heavy metals (HMs) content of arable soils in the black soil zone of Jilin Province has exceeded the background thresholds of the soil environment in Jilin Province, and localised contaminated areas have appeared as a result of the influence of factors such as neighbouring industrial discharges and anthropogenic activities. In this study, we innovatively combined the Extreme Gradient Boosting Algorithm (XGBoost) with the Index of Ecological Risk Early Warning (I_ER) method. We constructed the XGBoost-I_ER composite model for predicting the concentration of soil HMs (Cd, Cu, Zn, Pb, and Mn) and for ecological risk early warning assessment. This paper compares the performance of three spectral preprocessing methods (Standard Normal Variable Transform (SNV), Multivariate Scattering Correction (MSC), and Savitzky-Golay Convolutional Smoothing First-order Derivative (SG-FD)), as well as the Competitive Adaptive Re-weighted Sampling (CARS) feature selection method. The results show that SG-FD preprocessing combined with CARS feature selection can extract feature information more effectively. The XGBoost model is further compared with Least Squares Support Vector Machine (LS-SVM) and Partial Least Squares Regression (PLS), and the results show that the XGBoost model has a significant advantage in both prediction accuracy and stability. The ecological risk early warning analysis based on the model prediction shows that Cd and Zn present a moderate pollution warning in the central part of the study area, and Cu, Pb and Mn are all mildly warned; From the comprehensive I_ER, there is a heavy pollution warning area in the central and southern part of the study area (Jilin, Changchun and Siping). The ecosystem structure has suffered severe damages. The agreement between the model prediction results and the actual detection data reached: Mn (98.21 %), Cu (94.64 %), Cd (91.96 %), Pb(91.07 %), which fully verified the reliability of the method.

吉林省黑土区耕地土壤重金属含量已超过吉林省土壤环境的背景阈值，在邻近工业排放和人为活动等因素的影响下，出现了局部性污染区。在这项研究中，我们创新地将极端梯度增强算法（XGBoost）与生态风险预警指数（IER）方法相结合。我们构建了XGBoost-IER复合模型，用于预测土壤重金属（Cd、Cu、Zn、Pb和Mn）浓度和生态风险预警评估。本文比较了标准正态变量变换（SNV）、多元散射校正（MSC）和Savitzky-Golay卷积平滑一阶导数（SG-FD）三种光谱预处理方法以及竞争自适应重加权采样（CARS）特征选择方法的性能。结果表明，SG-FD预处理与CARS特征选择相结合可以更有效地提取特征信息。将XGBoost模型与最小二乘支持向量机（LS-SVM）和偏最小二乘回归（PLS）进行比较，结果表明XGBoost模型在预测精度和稳定性方面都具有显著优势。基于模型预测的生态风险预警分析表明，研究区中部Cd、Zn为中度污染预警，Cu、Pb、Mn为轻度污染预警；从综合IER来看，研究区中南部（吉林、长春、四平）存在重污染预警区。生态系统结构遭到严重破坏。模型预测结果与实际探测数据的一致性达到：Mn（98.21%）、Cu（94.64%）、Cd（91.96%）、Pb(91.07%)，充分验证了该方法的可靠性。

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引用次数: 0