生态系统韧性的评价指标
生态系统韧性理论内涵与多维分析框架
该类文献专注于生态系统韧性的科学定义、理论基础以及韧性与抵抗力、恢复力、稳定性、鲁棒性等核心概念的逻辑关系,致力于构建综合性韧性评价指标体系的理论框架。
- Trade-offs Among Resilience, Robustness, Stability, and Performance and How We Might Study Them.(B. Inouye, B. Brosi, E. L. Le Sage, M. Lerdau, 2021, Integrative and Comparative Biology)
- Unifying the concepts of stability and resilience in ecology(K. Van Meerbeek, T. Jucker, Jens‐Christian Svenning, 2020, Journal of Ecology)
- A Comprehensive Classification of Ecosystem Resilience Assessment Methods: Frameworks, Approaches, and Models(S. Ghazinoory, Asieh Bakhtiar, Atiyeh Safardoust, 2026, Environmental and Sustainability Indicators)
- Resilience in the Studies of Biodiversity-Ecosystem Functioning.(A. Mori, 2016, Trends in Ecology & Evolution)
- A review of measuring ecosystem resilience to disturbance(C Yi, N Jackson, 2021, Environmental Research Letters)
- Toward convergence in social-ecological systems resilience assessment: A systematic review and conceptual framework(Hamid Balali, Craig R Allen, F. Ward, Gholamreza Eslamifar, Alexander Fernald, 2026, Ecological Indicators)
- Ecological resilience: what to measure and how(V Dakos, S Kéfi, 2022, Environmental Research Letters)
- Advancing our understanding of ecological stability.(S. Kéfi, Virginia Domínguez-García, I. Donohue, C. Fontaine, Élisa Thébault, V. Dakos, 2019, Ecology Letters)
- How do ecological resilience metrics relate to community stability and collapse?(C. Roberts, D. Twidwell, D. Angeler, Craig R Allen, 2019, Ecological Indicators)
- Navigating the complexity of ecological stability.(I. Donohue, H. Hillebrand, J. Montoya, Owen L. Petchey, S. Pimm, M. Fowler, K. Healy, A. Jackson, M. Lurgi, Deirdre McClean, Nessa E. O’Connor, Eoin J. O’Gorman, Qiang Yang, 2016, Ecology Letters)
- A quantitative framework for assessing ecological resilience.(Didier L. Baho, C. Allen, A. Garmestani, Hannah B. Fried‐Petersen, S. E. Renes, L. Gunderson, D. Angeler, 2017, Ecology and Society)
- An exploratory framework for the empirical measurement of resilience(GS Cumming, G Barnes, S Perz, M Schmink, 2005, Ecosystems)
- Ecological Resilience—In Theory and Application(L. Gunderson, 2000, Annual Review of Ecology and Systematics)
- Toward a Generalizable Framework of Disturbance Ecology Through Crowdsourced Science(E. Graham, C. Averill, B. Bond‐Lamberty, J. Knelman, S. Krause, A. Peralta, A. Shade, A. P. Smith, Susan J. Cheng, Nicolas Fanin, C. Freund, P. Garcia, S. Gibbons, Marc Warwick Van Goethem, Marouen Ben Guebila, J. Kemppinen, Robert Nowicki, J. Pausas, S. Reed, Jennifer D. Rocca, A. Sengupta, D. Sihi, Marie Simonin, M. Słowiński, S. Spawn, I. Sutherland, J. Tonkin, Nathan I. Wisnoski, S. Zipper, 2021, Frontiers in Ecology and Evolution)
- Assess ecosystem resilience: Linking response and effect traits to environmental variability(M. Sterk, G. Gort, A. Klimkowska, J. Ruijven, A. Teeffelen, G. Wamelink, 2013, Ecological Indicators)
- Biodiversity, resilience and the stability of evolutionary systems.(P. Nosil, J. Feder, Z. Gompert, 2021, Current Biology)
- Quantifying resilience(DG Angeler, CR Allen, 2016, Journal of Applied Ecology)
- Ecological dynamic regimes: A key concept for assessing ecological resilience(M. Sánchez-Pinillos, V. Dakos, S. Kéfi, 2024, Biological Conservation)
- Resilience and the reliability of spectral entropy to assess ecosystem stability(W. de Keersmaecker, S. Lhermitte, L. Tits, O. Honnay, B. Somers, P. Coppin, 2018, Global Change Biology)
- Disturbance theory for ecosystem ecologists: A primer(Christopher M. Gough, Brian Buma, A. Jentsch, K. Mathes, R. Fahey, 2024, Ecology and Evolution)
- RESILIENCE MEASUREMENT AND CONCEPTUAL FRAMEWORKS: A REVIEW OF THE LITERATURE(Elena Serfilippi, Gayatri Ramnath, 2018, Annals of Public and Cooperative Economics)
- A multidimensional stability framework enhances interpretation and comparison of carbon cycling response to disturbance(K. Mathes, Yang Ju, Callie L Kleinke, C. Oldfield, G. Bohrer, B. Bond‐Lamberty, C. Vogel, K. Dorheim, C. Gough, 2021, Ecosphere)
- The Impact of Spatial and Temporal Dimensions of Disturbances on Ecosystem Stability(Yuval R. Zelnik, Jean‐François Arnoldi, Michel Loreau, 2018, Frontiers in Ecology and Evolution)
- ORF, an operational framework to measure resilience in social–ecological systems: the forest case study(Francisco Lloret, Pilar Hurtado, J. Espelta, L. Jaime, Laura Nikinmaa, Marcus Lindner, Jordi Martínez-Vilalta, 2024, Sustainability Science)
- How to measure ecosystem stability? An evaluation of the reliability of stability metrics based on remote sensing time series across the major global ecosystems(W. Keersmaecker, S. Lhermitte, O. Honnay, J. Farifteh, B. Somers, P. Coppin, 2014, Global Change Biology)
- Perspectives for ecosystem management based on ecosystem resilience and ecological thresholds against multiple and stochastic disturbances(Takehiro Sasaki, Takuya Furukawa, Y. Iwasaki, M. Seto, A. Mori, 2015, Ecological Indicators)
基于遥感监测与空间分析的量化评估方法
这类文献侧重于利用卫星遥感(如Landsat, MODIS)、地理信息系统及景观仿真模型,构建针对区域生态系统韧性的动态监测与定量化评估指标,强调空间异质性和大尺度分析。
- Quantifying large‐scale ecosystem stability with remote sensing data(H. White, Willson Gaul, D. Sadykova, Lupe León-Sánchez, P. Caplat, M. Emmerson, J. Yearsley, 2020, Remote Sensing in Ecology and Conservation)
- Reduced ecosystem resilience quantifies fine‐scale heterogeneity in tropical forest mortality responses to drought(Donghai Wu, G. Vargas, J. Powers, N. McDowell, J. Becknell, Daniel Pérez‐Aviles, D. Medvigy, Yanlan Liu, G. Katul, J. Calvo-Alvarado, A. Calvo-Obando, A. Sánchez-Azofeifa, Xiangtao Xu, 2021, Global Change Biology)
- Remotely sensed resilience of tropical forests(J. Verbesselt, Nikolaus Umlauf, M. Hirota, M. Holmgren, E. V. Nes, M. Herold, A. Zeileis, M. Scheffer, 2016, Nature Climate Change)
- Quantifying spatial resilience(C. Allen, D. Angeler, G. Cumming, C. Folke, D. Twidwell, D. Uden, 2016, Journal of Applied Ecology)
- Spatially Explicit Assessment of Ecosystem Resilience: An Approach to Adapt to Climate Changes(Haiming Yan, J. Zhan, Bingxi Liu, Wei Huang, Zhihui Li, 2014, Advances in Meteorology)
- Remote Sensing-Based Analysis of the Coupled Impacts of Climate and Land Use Changes on Future Ecosystem Resilience: A Case Study of the Beijing–Tianjin–Hebei Region(Jingyuan Ni, Fang Xu, 2025, Remote Sensing)
- Metrics and Models for Quantifying Ecological Resilience at Landscape Scales(S. Cushman, K. McGarigal, 2019, Frontiers in Ecology and Evolution)
- Emerging resilience metrics in an intensely managed ecological system(Nikolaos Toumasis, Dan W Simms, W. Rust, Jim Harris, John R. White, Joanna Zawadzka, Ronald Corstanje, 2024, Ecological Engineering)
- Exploring the ecosystem resilience concept with land surface model scenarios(Hugo Tameirão Seixas, N. A. Brunsell, Elisabete Caria Moraes, Gabriel de Oliveira, Guilherme Mataveli, 2021, Ecological Modelling)
- Optimizing zoning for ecological management in alpine region by combining ecosystem service supply and demand with ecosystem resilience.(Zhenqing Ji, Songbing Zou, Wenyong Zhang, Fei Song, Tenggang Yuan, Baorong Xu, 2024, Journal of Environmental Management)
- An indicator-based approach for assessing marine ecosystem resilience(L. Flensborg, Aurore Maureaud, D. N. Bravo, M. Lindegren, 2023, ICES Journal of Marine Science)
- Quantifying resilience of multiple ecosystem services and biodiversity in a temperate forest landscape(E. Cantarello, A. Newton, Philip A. Martin, P. Evans, A. Gosal, M. Lucash, 2017, Ecology and Evolution)
- Resilience and regime shifts in a marine biodiversity hotspot(P. Vasilakopoulos, D. Raitsos, E. Tzanatos, C. Maravelias, 2017, Scientific Reports)
- Use of landscape simulation modeling to quantify resilience for ecological applications(R. Keane, R. Loehman, Lisa M. Holsinger, D. Falk, P. Higuera, S. Hood, P. Hessburg, 2018, Ecosphere)
- Enhancing the resilience of ecosystem services under extreme events in socio-hydrological systems: A spatio-temporal analysis(Massoud Behboudian, Sara Anamaghi, N. Mahjouri, R. Kerachian, 2023, Journal of Cleaner Production)
- Multi-criteria assessment of the resilience of ecological function areas in China with a focus on ecological restoration(Yiyan Zhang, Yongjun Yang, Zanxu Chen, Shaoliang Zhang, 2020, Ecological Indicators)
- A globally applicable indicator of the capacity of terrestrial ecosystems to retain biological diversity under climate change: The bioclimatic ecosystem resilience index(S. Ferrier, T. Harwood, C. Ware, A. Hoskins, 2020, Ecological Indicators)
- Remote Sensing and Modeling of Coral Reef Resilience(A. Knudby, S. Pittman, J. Maina, G. Rowlands, 2014, Coastal Research Library)
- Remote sensing diagnosis of ecosystem resilience dynamics in agricultural heritage landscapes(Qing Xiang, Chunjuan Wang, Haiping Zhu, Hui Wu, Mengyan Jia, 2025, npj Heritage Science)
- Satellite remote sensing to monitor mangrove forest resilience and resistance to sea level rise(Clare Duncan, H. Owen, J. Thompson, H. Koldewey, J. Primavera, N. Pettorelli, 2018, Methods in Ecology and Evolution)
- Establishing forest resilience indicators in the hilly red soil region of southern China from vegetation greenness and landscape metrics using dense Landsat time series(Meiling Liu, Xiangnan Liu, Ling Wu, Yibo Tang, Yu Li, Yaqi Zhang, L. Ye, Biyao Zhang, 2021, Ecological Indicators)
- Assessing Terrestrial Ecosystem Resilience using Satellite Leaf Area Index(Jinhui Wu, S. Liang, 2020, Remote Sensing)
- Ecosystem Resilience Monitoring and Early Warning Using Earth Observation Data: Challenges and Outlook(S. Bathiany, R. Bastiaansen, A. Bastos, Lana L. Blaschke, J. Lever, S. Loriani, Wanda De Keersmaecker, Wouter Dorigo, Milutin Milenković, Cornelius Senf, Taylor Smith, J. Verbesselt, Niklas Boers, 2024, Surveys in Geophysics)
- Comprehensive Assessment Indicator of Ecosystem Resilience in Central Asia(Xuemei Fan, Xingming Hao, Haichao Hao, Jingjing Zhang, Yuanhang Li, 2021, Water)
- Using Remote Sensing to Quantify Vegetation Change and Ecological Resilience in a Semi-Arid System(X. Cui, Cerian Gibbes, J. Southworth, P. Waylen, 2013, Land)
- Evaluating post-disaster ecosystem resilience using MODIS GPP data(Amy E. Frazier, C. Renschler, S. Miles, 2013, International Journal of Applied Earth Observation and Geoinformation)
生物多样性与生态功能驱动的机制研究
这些文献重点探究物种多样性、功能冗余及生态系统服务在维持生态韧性中的关键作用,研究生物组分变化如何影响系统的稳定性,并将其量化为具体的韧性指标。
- Partitioning species contributions to ecological stability in disturbed communities(Charlotte Kunze, Dominik Bahlburg, P. Urrutia‐Cordero, M. Striebel, E. Kelpsiene, S. Langenheder, Ian Donohue, H. Hillebrand, 2024, Ecological Monographs)
- Biodiversity increases and decreases ecosystem stability(Frank Pennekamp, Mikael Pontarp, Andrea Tabi, F. Altermatt, R. Alther, Y. Choffat, E. A. Fronhofer, P. Ganesanandamoorthy, A. Garnier, J. Griffiths, S. Greene, Katherine Horgan, Thomas M. Massie, E. Mächler, G. Palamara, M. Seymour, Owen L. Petchey, 2018, Nature)
- Patterns and drivers of biodiversity–stability relationships under climate extremes(H. D. De Boeck, J. Bloor, J. Kreyling, J. Ransijn, I. Nijs, A. Jentsch, M. Zeiter, 2018, Journal of Ecology)
- Determinants of ecosystem stability in a diverse temperate forest(J. Dolezal, P. Fibich, J. Altman, J. Lepš, S. Uemura, Koichi Takahashi, T. Hara, 2020, Oikos)
- No positive effects of biodiversity on ecological resilience of lake ecosystems(Haojie Su, YanLing Li, Misha Zhong, Ruijing Ma, Jianfeng Chen, Qingyang Rao, Yuhao Feng, Suhui Ma, Jun Chen, Haijun Wang, Erik Jeppesen, Ping Xie, 2024, The Innovation Geoscience)
- Ecosystem Resistance and Resilience after Dry and Wet Events across Central Asia Based on Remote Sensing Data(Jie Zou, Jianli Ding, Shuai Huang, Bohua Liu, 2023, Remote Sensing)
- Special feature: measuring components of ecological resilience in long-term ecological datasets(A. Seddon, 2021, Biology Letters)
- Meta-analysis on pulse disturbances reveals differences in functional and compositional recovery across ecosystems.(H. Hillebrand, Charlotte Kunze, 2020, Ecology Letters)
- The influence of landscape composition and configuration on crop yield resilience(John W. Redhead, Tom H. Oliver, Ben A. Woodcock, Richard F. Pywell, 2020, Journal of Applied Ecology)
- Does functional redundancy affect ecological stability and resilience? A review and meta‐analysis(Christopher R. Biggs, L. Yeager, D. Bolser, C. Bonsell, Angelina M. Dichiera, Zhenxin Hou, Spencer R. Keyser, A. J. Khursigara, Kaijun Lu, Arley F. Muth, Benjamin Negrete, B. Erisman, 2020, Ecosphere)
- Linking ecological resilience and ecosystem services to inform spatial conservation planning(Zhuangzhuang Wang, Bojie Fu, Xutong Wu, Shuai Wang, Junze Zhang, Liwei Zhang, L. Jiao, Hao Wang, Yingjie Li, Ying Luo, 2026, Communications Earth & Environment)
- Multiple facets of biodiversity drive the diversity–stability relationship(D. Craven, N. Eisenhauer, W. Pearse, Y. Hautier, F. Isbell, C. Roscher, M. Bahn, C. Beierkuhnlein, G. Bönisch, N. Buchmann, Chaeho Byun, J. Catford, B. Cerabolini, J. Cornelissen, J. Craine, E. Luca, A. Ebeling, J. Griffin, A. Hector, J. Hines, A. Jentsch, J. Kattge, J. Kreyling, V. Lanta, N. Lemoine, S. Meyer, V. Minden, V. Minden, V. Onipchenko, H. W. Polley, P. Reich, J. Ruijven, B. Schamp, Melinda D. Smith, Nadejda A. Soudzilovskaia, D. Tilman, A. Weigelt, B. Wilsey, P. Manning, 2018, Nature Ecology & Evolution)
- Peeking at ecosystem stability: making use of a natural disturbance experiment to analyze resistance and resilience.(H. Bruelheide, U. Luginbühl, 2009, Ecology)
- Disturbance-driven changes in the variability of ecological patterns and processes.(J. Fraterrigo, J. Rusak, 2008, Ecology Letters)
区域生态管理与社会-生态系统实证评估
此类文献通过特定案例分析(森林、旱区、农田等),探讨韧性评估指标在生态修复、防火规划、土地利用及社会-生态系统管理决策中的实际应用。
- Ecosystems resilience assessment of forest and grassland subjected to ecological drought(Yu Han, Yanping Qu, Tianliang Jiang, Xuejun Zhang, Juan Lyu, Xiaoling Su, 2025, Ecological Indicators)
- Operationalizing Ecological Resilience Concepts for Managing Species and Ecosystems at Risk(J. Chambers, C. Allen, S. Cushman, 2019, Frontiers in Ecology and Evolution)
- Assessment of ecosystem resilience in Central Asia(Jingxiu Qin, Xingming Hao, D. Hua, Haichao Hao, 2021, Journal of Arid Environments)
- A framework for measuring the effects of disturbance in restoration projects(Ebony L. Cowan, R. Standish, B. Miller, N. Enright, J. B. Fontaine, 2021, Restoration Ecology)
- A landscape index of ecological integrity to inform landscape conservation(K. McGarigal, B. Compton, E. Plunkett, William V. DeLuca, J. Grand, Eduard Ene, S. Jackson, 2018, Landscape Ecology)
- Ecological Recovery and Resilience in Environmental Risk Assessments at the European Food Safety Authority(T. Brock, F. Bigler, G. Frampton, C. Hogstrand, R. Luttik, F. Martin-Laurent, C. Topping, W. van der Werf, A. Rortais, 2018, Integrated Environmental Assessment and Management)
- Incorporating resilience and cost in ecological restoration strategies at landscape scale(M Stefanes, JM Ochoa-Quintero, F de Oliveira Roque, 2016, Ecology and …)
- Evaluation of ecosystem resilience in Yulin, China(刘小平 Liu Xiaoping, 李鹏 Li Peng, 任宗萍 Ren Zongping, 苗滋耀 Miao Ziyao, 张. Z. Jun, 刘晓军 Liu Xiaojun, 李占斌 Li Zhanbin, 王甜 Wang Tian, 2016, Acta Ecologica Sinica)
- Quantifying disturbance effects on ecosystem services in a changing climate(L. Dee, Steve J. Miller, Kate J. Helmstedt, K. S. Boersma, Stephen Polasky, Peter B. Reich, 2025, Nature Ecology & Evolution)
- Quantification of the ecological resilience of drylands using digital remote sensing(RA Washington-Allen, RD Ramsey, NE West, 2008, Ecology and …)
- Towards a Comparable Quantification of Resilience.(Johannes Ingrisch, M. Bahn, 2018, Trends in Ecology & Evolution)
- Spatial resilience: integrating landscape ecology, resilience, and sustainability(G. Cumming, 2011, Landscape Ecology)
- Evaluating pathways to social and ecological landscape resilience(Eric S. Abelson, Keith A. Reynolds, A. White, J. Long, Charles J. Maxwell, P. Manley, 2022, Ecology and Society)
- Drought risk assessment considering ecosystem resilience: A case study in the Huang-Huai-Hai Plain, China(Xiaoliang Shi, Yan Zhang, Hao Ding, Yuanqi Yang, Jiajun Chen, Mengqi Shi, Fei Chen, 2023, Ecological Indicators)
- An indicator framework for assessing agroecosystem resilience(JF Cabell, M Oelofse, 2012, Ecology and Society)
- Construction of ecological security pattern and assessment of ecological resilience based on ecosystem services: A case study of Changsha-Zhuzhou-Xiangtan urban …(Z Sun, S Wang, B Chen, 2024, Acta Ecologica Sinica)
- Multi-ecosystem services networks: A new perspective for assessing landscape connectivity and resilience(Rachel D. Field, L. Parrott, 2017, Ecological Complexity)
- Estimating resilience across landscapes(GD Peterson, 2002, Conservation Ecology)
- Measuring resilience and recovery(S. Platt, Daniel M. Brown, M. Hughes, 2016, International Journal of Disaster Risk Reduction)
关于生态系统韧性评价指标的研究已形成一套多层次的体系,主要涵盖:韧性理论内涵的界定与多维框架构建;利用遥感及空间数据进行的时空动态定量化监测;探究生物多样性与功能多样性对韧性影响的机制分析;以及将韧性度量应用于区域管理与社会-生态系统韧性决策支持的实证评估。这四个维度的整合体现了韧性评价从抽象概念向具体可操作性指标及管理工具转化的趋势。
总计85篇相关文献
The ecosystems in the arid inland areas of Central Asia are fragile and severely degraded. Understanding and assessing ecosystem resilience is a challenge facing ecosystems. Based on the net primary productivity (NPP) data estimated by the CASA model, this study conducted a quantitative analysis of the ecosystem’s resilience and comprehensively reflected its resilience from multiple dimensions. Furthermore, a comprehensive resilience index was constructed. The result showed that plain oasis’s ecosystem resilience is the highest, followed by deserts and mountainous areas. From the perspective of vegetation types, the highest resilience is artificial vegetation and the lowest is forest. In warm deserts, the resilience is higher in shrubs and meadows and lower in grassland vegetation. High coverage and biomass are not the same as the strong adaptability of the ecosystem. Moderate and slightly inelastic areas mainly dominate the ecosystem resilience of the study area. The new method is easy to use. The evaluation result is reliable. It can quantitatively analyze the resilience latitude and recovery rate, a beneficial improvement to the current ecosystem resilience evaluation.
… may be useful for policy makers and ecosystem resource … Here, we review the methods of assessing resilience and … actively quantify resilience, or were about non-ecosystem resilience, …
Marine ecosystems are under threat from a range of human pressures, notably climate change, overexploitation, and habitat destruction. The resulting loss of species and biodiversity can cause abrupt and potentially irreversible changes in their structure and functioning. Consequently, maximizing resilience has emerged as a key concept in conservation and management. However, despite a well-developed theory, there is an urgent need for a framework that can quantify key components promoting resilience by accounting for the role of biodiversity. In this study, we applied an indicator-based approach to assess the potential resilience of marine ecosystems using the North Sea as an illustrative case study. More specifically, we quantified and compared multiple indicators of ecological resilience, estimated based on high-resolution monitoring data on marine demersal fish species, combined with information on ecological traits. Our results show a pronounced spatial structuring of indicators, including both similarities and differences among individual metrics and indicators. This implies that high resilience cannot be achieved by maximizing all individual aspects of resilience, simply because there seems to be inherent trade-offs between these components. Our framework is generic and is therefore applicable to other systems and can inform spatial planning and management.
… effect on resilience. Due to … the resilience of the system. In this way this study argues to further develop a response-and-effect framework to understand and assess ecosystem resilience. …
… Ecosystem resilience is essential for sustaining ecosystems in the face of increasingly … ecological drought events, enhancing temporal resolution, and refining model fitting for resilience …
Abstract Climate change has a profound impact on ecosystem stability. Recent studies still have insufficient understanding of the response of vegetation to climate change, especially the response of vegetation to short-term climate anomalies. Based on normalized difference vegetation index (NDVI) and the meteorological data, this study conducted a quantitative assessment of the ecosystem resilience and resistance and analyzed the relationship between resistance, resilience and land cover. Furthermore, a new method was developed to identify ecologically fragile regions. The result showed that the resilience and resistance of the Central Asia ecosystem to short-term climate change are generally low. The relationship between resistance, resilience and vegetation cover was nonlinear. If there were too many or too few trees, the stability of the ecosystem was compromised. Ecologically fragile areas were found in transition areas from vegetation to non-vegetation. This study helps to better understand and quantify vegetation resilience and resistance while explicitly taking short-term climate anomalies into account. The results provide more detailed guidelines for strengthening ecosystem management.
… assess ecological resilience empirically. More specifically, we briefly review the concept of resilience … Then, we review an approach based on ecological dynamic regimes and temporal …
… Taking departure in the theory of resilience in social-ecological systems, we present an … of 13 such indicators, which, when identified in an agroecosystem, suggest that it is resilient and …
The ecosystem resilience plays a key role in maintaining a steady flow of ecosystem services and enables quick and flexible responses to climate changes, and maintaining or restoring the ecosystem resilience of forests is a necessary societal adaptation to climate change; however, there is a great lack of spatially explicit ecosystem resilience assessments. Drawing on principles of the ecosystem resilience highlighted in the literature, we built on the theory of dissipative structures to develop a conceptual model of the ecosystem resilience of forests. A hierarchical indicator system was designed with the influencing factors of the forest ecosystem resilience, including the stand conditions and the ecological memory, which were further disaggregated into specific indicators. Furthermore, indicator weights were determined with the analytic hierarchy process (AHP) and the coefficient of variation method. Based on the remote sensing data and forest inventory data and so forth, the resilience index of forests was calculated. The result suggests that there is significant spatial heterogeneity of the ecosystem resilience of forests, indicating it is feasible to generate large-scale ecosystem resilience maps with this assessment model, and the results can provide a scientific basis for the conservation of forests, which is of great significance to the climate change mitigation.
As the Earth system is exposed to large anthropogenic interferences, it becomes ever more important to assess the resilience of natural systems, i.e., their ability to recover from natural and human-induced perturbations. Several, often related, measures of resilience have been proposed and applied to modeled and observed data, often by different scientific communities. Focusing on terrestrial ecosystems as a key component of the Earth system, we review methods that can detect large perturbations (temporary excursions from a reference state as well as abrupt shifts to a new reference state) in spatio-temporal datasets, estimate the recovery rate after such perturbations, or assess resilience changes indirectly from stationary time series via indicators of critical slowing down. We present here a sequence of ideal methodological steps in the field of resilience science, and argue how to obtain a consistent and multi-faceted view on ecosystem or climate resilience from Earth observation (EO) data. While EO data offers unique potential to study ecosystem resilience globally at high spatial and temporal scale, we emphasize some important limitations, which are associated with the theoretical assumptions behind diagnostic methods and with the measurement process and pre-processing steps of EO data. The latter class of limitations include gaps in time series, the disparity of scales, and issues arising from aggregating time series from multiple sensors. Based on this assessment, we formulate specific recommendations to the EO community in order to improve the observational basis for ecosystem resilience research.
Quantitative approaches to measure and assess resilience are needed to bridge gaps between science, policy and management. In this paper, we revisit definitions of resilience and suggest a quantitative framework for assessing ecological resilience sensu Holling (1973). Ecological resilience as an emergent ecosystem phenomenon can be decomposed into complementary attributes (scales, adaptive capacity, thresholds and alternative regimes) that embrace the complexity inherent to ecosystems. Quantifying these attributes simultaneously provides opportunities to move from the assessment of specific resilience within an ecosystem towards a broader measurement of its general resilience. We provide a framework, based on testable hypotheses, which allows assessment of complementary attributes of ecological resilience. By implementing the framework in adaptive approaches to management, inference and modeling, key uncertainties can be reduced incrementally over time and learning about the general resilience of dynamic ecosystems maximized. Such improvements are needed because uncertainty about global environmental change impacts and their effects on resilience is high. Improved resilience assessments will ultimately facilitate an optimized use of limited resources for management.
… indicators to measure the response of ecosystems to climate change, the spatial difference of ecosystem resilience will also affect the accuracy of regional drought risk assessment. In …
Abstract Population growth and rapid economic development have led to serious and widespread negative ecological impacts, so the world is faced with the task of ecological recovery. China, in particular, is carrying out a nationwide land improvement and ecological restoration campaign. The spatial distribution of ecological resilience needs to be fully considered in the planning of these projects. However, most current ecological assessments lack a focus on resilience. Based on selected resilience principles, this paper constructs an assessment indicator system for national-scale ecological resilience, evaluates the level of ecological resilience of 1,434 ecological function areas in China and discusses the layout of ecological restoration projects throughout the country. The main conclusions are as follows: (1) In China, the level of ecological resilience varies widely based on location. Generally, it shows high levels of ecological resilience occur in the south and low in the north. The resilience index ranged from 0 to 0.585. The natural condition index is the most important indicator affecting resilience. (2) China's existing ecological restoration projects are mostly distributed in areas with low levels of resilience. Restorative ecological engineering is not directly related to the distribution of resilience but is affected by the level of resilience. (3) The levels of China's resilience has a negative relationship with ecological sensitivity and ecological vulnerability level. Constructing a national-scale resilience assessment index system based on resilience criteria can effectively reveal the overall pattern of national-scale resilience. This study can provide reference for the ecological restoration planning, assessment, and adaptive management on a national level.
… for assessing resilience are … resilience differ in various respects, and the main purpose of this study is to identify and classify different approaches to ecosystem resilience assessment for …
Abstract An important element of the Convention on Biological Diversity’s Aichi Target 15 – i.e. to enhance “ecosystem resilience … through conservation and restoration” – remains largely unaddressed by existing indicators. We here develop an indicator addressing just one of many possible dimensions of ecosystem resilience, by focusing on the capacity of ecosystems to retain biological diversity in the face of ongoing, and uncertain, climate change. The Bioclimatic Ecosystem Resilience Index (BERI) assesses the extent to which a given spatial configuration of natural habitat will promote or hinder climate-induced shifts in biological distributions. The approach uses existing global modelling of spatial turnover in species composition within three broad biological groups (plants, invertebrates and vertebrates) to scale projected changes in composition under a plausible range of climate scenarios. These projections serve as filters through which to analyse the configuration of habitat observed at a given point in time (e.g. for a particular year) – represented as a grid in which cells are scored in terms of habitat condition. BERI is then calculated, for each cell in this grid, as a function of the connectedness of that cell to areas of natural habitat in the surrounding landscape which are projected to support a similar composition of species under climate change to that currently associated with the focal cell. All analyses are performed at 30-arcsecond grid resolution (approximately 1 km cells at the equator). Results can then be aggregated to report on status and trends for any desired set of reporting units – e.g. ecoregions, countries, or ecosystem types. We present example outputs for the Moist Tropical Forest Biome, based on a habitat-condition time series derived from the Global Forest Change dataset. We also describe how BERI is now being extended to cover all biomes (forest and non-forest) across the entire terrestrial surface of the planet.
… of disturbances on natural systems, the need to operationalize ecological resilience for assessing and managing ecological systems is greater than ever. However, operationalizing …
… %,and79.7% of the total area had ecosystem resilience values greater than 0.4, respectively. In … Therefore, when the value of ecosystem resilience maintained steady growth in the Yulin …
… to confer ecosystem resilience, such as … ecosystem resilience for each context and to examine how we can manage and conserve them. The second is the identification of ecological …
… The concept of social-ecological resilience holds promise for … be measured in a given study of resilience. In this paper we present a framework for opera tionalizing resilience concepts. …
… of specific resilience measures.Rather than proposing new metrics, this study offers a unifying framework to guide more consistent, theoretically grounded SES resilience assessments …
… definitions, models, and measurement frameworks. Originating in the physical sciences, ideas of resilience are not easily adaptable to human socio-ecological settings. The social …
Resilience is commonly addressed when dealing with the sustainable planning and management of social–ecological systems, but we lack a unified framework for its quantitative assessment and application. We present an operational resilience framework (ORF) based on recognizing and relating several elements: system variables (e.g., ecosystem services), disturbances and stressors acting at given spatiotemporal scales, a reference state, and metrics comparing the observed system variables to the reference state. These elements fit into a rationale aimed at identifying resilience predictors suitable to be managed and co-drivers which describe non-manageable context, reflecting the mechanisms involved in resilience. By a systematic search of the presence of the ORF concepts in 453 empirical studies assessing resilience, we corroborate that ORF can be applied to studies on forest social–ecological systems. This literature survey shows that ORF elements are commonly recognized, although the logical narrative relating them is not always explicit, particularly in socioeconomic-focused studies. We advocate that the proposed ORF allows to standardize the terminology and to frame and measure resilience, allowing sounder comparisons and better-supported recommendations for the improvement of resilience in social–ecological systems, particularly in forest systems.
An explicit link between the abiotic environment, the biotic components of ecosystems, and resilience to disturbance across multiple scales is needed to operationalize the concept of ecological resilience. To accomplish this, managers must be able to measure the ecological resilience of current conditions and project resilience under future scenarios of landscape change. The goal of this paper is to present metrics and describe a process for using geospatial data, landscape pattern analysis and landscape dynamic simulation modeling to evaluate ecosystem resilience at management scales. The dynamic equilibria of species abundances, community structure, and landscape patterns that are produced under a given combination of abiotic conditions, such as topography, soils, and climate, can form a foundation to define desired conditions and measure resistance and resilience. The degree of forcing required to push the system from this dynamic range is a measure of resistance, and the rate of return to the dynamic range after the perturbation is a measure of the resilience and recovery of the system. Several tools from the field of landscape ecology are useful in defining the dynamic range of an ecosystem under natural regulation and to measure the forcing required to drive departure and the rate of recovery. Simulation models provide means to quantify the expected range of species abundance, community structure and landscape patterns under a variety of scenarios, including the natural disturbance regime, current disturbance regime, and possible future regimes under alternative management and climate scenarios. Landscape pattern analysis and multivariate trajectory analysis provide a means to quantify conditions and change vectors relative to this desired range. Together this combination of tools provides a means to define the conditions of a desired state for an ecosystem, to quantify the degree of resistance and resilience of the system to perturbation, and to measure and monitor the departure from the range of natural variability in the system dynamics.
… In 1973, CS Holling introduced the word resilience into the ecologicalliterature as a way of helping to understand the non-linear dynamics observedin ecosystems. Ecological resilience …
Ecological resilience has become a focal concept in ecosystem management. Palaeoecological records (i.e. the sub-fossil remains preserved in sediments) are useful archives to address ecological resilience since they can be used to reconstruct long-term temporal variations in ecosystem properties. The special feature presented here includes nine new papers from members and associates of the PAGES EcoRe3 community. The papers build on previous work in palaeoecology to investigate, identify and compare components of ecosystem resilience on centennial to millennial timescales. There are four key messages that can be summarized from the findings of papers within the special feature: (i) multi-proxy studies reveal insights into the presence and mechanisms of alternative states; (ii) transitions between alternative states may not necessarily be abrupt; (iii) components of ecological resilience can be identified in long-term ecological data and (iv) the palaeoecological record can also provide insights into factors influencing the resilience of ecosystem functioning. Overall, these papers demonstrate the importance of using long-term ecological records for addressing questions related to the theoretical framework provided by ecological resilience.
… stability metrics within confidence limits. Based on these confidence limits, other studies dealing with specific ecosystem … that monitor ecosystem stability against climate disturbances. …
Ecosystems constantly face disturbances which vary in their spatial and temporal features, yet little is known on how these features affect ecosystem recovery and persistence, i.e., ecosystem stability. We address this issue by considering three ecosystem models with different local dynamics, and ask how their stability properties depend on the spatial and temporal properties of disturbances. We measure the spatial dimension of disturbances by their spatial extent while controlling for their overall strength, and their temporal dimension by the average frequency of random disturbance events. Our models show that the return to equilibrium following a disturbance depends strongly on the disturbance's extent, due to rescue effects mediated by dispersal. We then reveal a direct relation between the temporal variability caused by repeated disturbances and the recovery from an isolated disturbance event. Although this could suggest a trivial dependency of ecosystem response on disturbance frequency, we find that this is true only up to a frequency threshold, which depends on both the disturbance spatial features and the ecosystem dynamics. Beyond this threshold the response changes qualitatively, displaying spatial clusters of disturbed regions, causing an increase in variability, and even a system-wide collapse for ecosystems with alternative stable states. Thus, spanning the spatial dimension of disturbances is a way to probe the underlying dynamics of an ecosystem. Furthermore, considering spatial and temporal dimensions of disturbances in conjunction is necessary to predict ecosystem responses with dramatic ecological consequences, such as regime shifts or population extinction.
… and predict the effects of disturbances on the overall stability of ecosystems. If the science of … They must employ stability metrics that do not require strong equilibrium assumptions (eg …
Abstract The concept of ecological resilience (the amount of disturbance a system can absorb before collapsing and reorganizing) holds potential for predicting community change and collapse—increasingly common issues in the Anthropocene. Yet neither the predictions nor metrics of resilience have received rigorous testing. The cross-scale resilience model, a leading operationalization of resilience, proposes resilience can be quantified by the combination of diversity and redundancy of functions performed by species operating at different scales. Here, we use 48 years of sub-continental avian community data aggregated at multiple spatial scales to calculate resilience metrics derived from the cross-scale resilience model (i.e., cross-scale diversity, cross-scale redundancy, within-scale redundancy, and number of body mass aggregations) and test core predictions inherent to community persistence and change. Specifically, we ask how cross-scale resilience metrics relate community stability and collapse. We found low mean cross-correlation between species richness and cross-scale resilience metrics. Resilience metrics constrained the magnitude of community fluctuations over time (mean species turnover), but resilience metrics but did not influence variability of community fluctuations (variance in turnover). We show shifts in resilience metrics closely predict community collapse: shifts in cross-scale redundancy preceded abrupt changes in community composition, and shifts in cross-scale diversity synchronized with abrupt changes in community composition. However, we found resilience metrics only weakly relate to maintenance of particular species assemblages over time. Our results distinguish ecological resilience from ecological stability and allied concepts such as elasticity and resistance: we show communities may fluctuate widely yet still be resilient. Our findings also differentiate the roles of functional redundancy and diversity as metrics of resilience and reemphasize the importance of considering resilience metrics from a multivariate perspective. Finally, we support the contention that ecological stability is nested within ecological resilience: stability predicts the behavior of systems within an ecological regime, and resilience predicts the maintenance of regimes and behavior of systems collapsing into alternative regimes.
Ecosystems worldwide are experiencing a range of natural and anthropogenic disturbances, many of which are intensifying as global change accelerates. Ecological responses to those disturbances are determined by both the vulnerabilities of species and their interspecific interactions. Understanding how individual species contribute to the (in‐)stability of an aggregated community property, or function, is fundamental to ecological management and conservation. Here, we present a framework to identify species contributions to stability based on their absolute and relative responses to disturbances. Using simulations, we show that these two dimensions enable identification of (de‐)stabilizing species and reveal that competitive dominance determines the magnitude of both absolute and relative contributions to stability. Applying our framework to empirical data from a multi‐site mesocosm experiment showed that species contributions varied among treatments, sites, and seasons. Despite this dependency on both biotic and abiotic contexts, species contributions were generally constrained by their relative dominance in undisturbed conditions. Rare species contributed positively to stability, while dominant species contributed negatively, indicating compensatory dynamics. Our framework offers an important step toward a more mechanistic understanding of ecological stability based on species performance.
A framework and comparison response Abstract. The concept of stability is central to the study and sustainability of vital ecosystem goods and services as disturbances increase globally. While ecosystem ecologists, including carbon (C) cycling scientists, have long-considered multiple dimensions of disturbance response, our discipline lacks an agreed-upon analytical framework for characterizing multidimensional stability. Here, we advocate for the broader adoption of a standardized and normalized multidimensional stability framework for analyzing disturbance response. This framework includes four dimensions of stability: the degree of initial change in C fl uxes (i.e., resistance ); rate (i.e., resilience ) and variability (i.e., temporal stability ) of return to pre-disturbance C fl uxes; and the extent of return to pre-disturbance C fl uxes (i.e., recovery ). Using this framework, we highlight fi ndings not readily seen from analysis of absolute fl uxes, including trade-offs between initial and long-term C fl ux responses to disturbance; different overall stability pro fi les among fl uxes; and, using a pilot dataset, similar relative stability of net primary production following fi re and insect disturbances. We conclude that ecosystem ecologists ’ embrace of a unifying multidimensional stability framework as a complement to approaches focused on absolute C fl uxes could advance global change research by aiding in the novel interpretation, comprehensive synthesis, and improved forecasting of ecosystems ’ response to an increasing array of disturbances.
… Our results also suggest that stability metrics commonly used in ecology to assess … ecological stability metric (biomass-based resistance) under our climate change disturbance regime …
The concept of ecological stability occupies a prominent place in both fundamental and applied ecological research. We review decades of work on the topic and examine how our understanding has progressed. We show that our understanding of stability has remained fragmented and is limited largely to simple or simplified systems. There has been a profusion of metrics proposed to quantify stability, of which only a handful are used commonly. Furthermore, studies typically quantify one to two metrics of stability at a time and in response to a single perturbation, with some of the main environmental pressures of today being the least studied. We argue that we need to build on the existing consensus and strong theoretical foundation of the stability concept to better understand its multidimensionality and the interdependencies between metrics, levels of organisation and types of perturbations. Only by doing so can we make progress in the quantification of stability in theory and in practice, and eventually build a more comprehensive understanding of how ecosystems will respond to ongoing environmental change.
… most to the stability of species composition in a beech forest after profound disturbance, we made use … In this paper we focus on the stability of species composition in forest ecosystems. …
Abstract Understanding what regulates ecosystem functional responses to disturbance is essential in this era of global change. However, many pioneering and still influential disturbance‐related theorie proposed by ecosystem ecologists were developed prior to rapid global change, and before tools and metrics were available to test them. In light of new knowledge and conceptual advances across biological disciplines, we present four disturbance ecology concepts that are particularly relevant to ecosystem ecologists new to the field: (a) the directionality of ecosystem functional response to disturbance; (b) functional thresholds; (c) disturbance–succession interactions; and (d) diversity‐functional stability relationships. We discuss how knowledge, theory, and terminology developed by several biological disciplines, when integrated, can enhance how ecosystem ecologists analyze and interpret functional responses to disturbance. For example, when interpreting thresholds and disturbance–succession interactions, ecosystem ecologists should consider concurrent biotic regime change, non‐linearity, and multiple response pathways, typically the theoretical and analytical domain of population and community ecologists. Similarly, the interpretation of ecosystem functional responses to disturbance requires analytical approaches that recognize disturbance can promote, inhibit, or fundamentally change ecosystem functions. We suggest that truly integrative approaches and knowledge are essential to advancing ecosystem functional responses to disturbance.
Most ecosystems are affected by anthropogenic or natural pulse disturbances, which alter the community composition and functioning for a limited period of time. Whether and how quickly communities recover from such pulses is central to our understanding of biodiversity dynamics and ecosystem organisation, but also to nature conservation and management. Here, we present a meta-analysis of 508 (semi-)natural field experiments globally distributed across marine, terrestrial and freshwater ecosystems. We found recovery to be significant yet incomplete. At the end of the experiments, disturbed treatments resembled controls again when considering abundance (94%), biomass (82%), and univariate diversity measures (88%). Most disturbed treatments did not further depart from control after the pulse, indicating that few studies showed novel trajectories induced by the pulse. Only multivariate community composition on average showed little recovery: disturbed species composition remained dissimilar to the control throughout most experiments. Still, when experiments revealed a higher compositional stability, they tended to also show higher functional stability. Recovery was more complete when systems had high resistance, whereas resilience and resistance were negatively correlated. The overall results were highly consistent across studies, but significant differences between ecosystems and organism groups appeared. Future research on disturbances should aim to understand these differences, but also fill obvious gaps in the empirical assessments for regions (especially the tropics), ecosystems and organisms. In summary, we provide general evidence that (semi-)natural communities can recover from pulse disturbances, but compositional aspects are more vulnerable to long-lasting effects of pulse disturbance than the emergent functions associated to them.
… Temperature is a highly relevant disturbance owing to its importance for biological … Synchrony was assessed by a previously published metric 37 that calculates the average correlation …
… Understanding how disturbance shapes the dynamics of ecological … disturbance effects involves examining disturbance-driven … as a response to disturbance, we gain another metric of …
… of productivity could also be related to differential species responses to canopy disturbances and gap dynamics, we categorized species into sympodially branching trees with greater …
Ecological resilience is widely acknowledged as a vital attribute of successful ecosystem restoration, with potential for restoration practice to contribute to this goal. Hence, defining common metrics of resilience to naturally occurring disturbances is essential for restoration planning, efforts, and monitoring. Here, we reviewed how plant community ecologists have measured resilience of restoration projects to disturbances and propose a framework to guide measurement of restoration projects to disturbance. We found 22 studies that investigated the impact of disturbances on restoration projects, from three continents and for three disturbance types. Over half of the studies were from Australia, with the dataset biased toward fire responses of restored, or partially restored, forest ecosystems. Native plant species richness, cover, and density were common response variables. Studies varied in restoration context, design, response variables, and statistical approaches, limiting generalizations. Nonetheless we have identified several response variables that offer potential as lagging indicators (e.g. species richness) and leading indicators (e.g. recruitment) of resilience in diverse vegetation types exposed to a variety of disturbance regimes. We suggest a third set of variables, proxy measures of resilience (e.g. functional redundancy), to complement lagging and leading indicators. We conclude with a framework to guide decisions about when to use each of the three types of measures to assess resilience of restoration projects to disturbance, providing some clarity to decision‐making despite the uncertainty of changing disturbance regimes. Lastly, we invite researchers to understand the impact of disturbance on the resilience of restoration projects, rather than assume resilience.
. In light of rapid shifts in biodiversity associated with human impacts, there is an urgent need to understand how changing patterns in biodiversity impact ecosystem function. Functional redundancy is hypothesized to promote ecological resilience and stability, as ecosystem function of communities with more redundant species (those that perform similar functions) should be buffered against the loss of individual species. While functional redundancy is being increasingly quanti fi ed, few studies have linked differences in redundancy across communities to ecological outcomes. We conducted a review and meta-analysis to determine whether empirical evidence supports the asserted link between functional redundancy and ecosystem stability and resilience. We reviewed 423 research articles and assembled a data set of 32 studies from 15 articles across aquatic and terrestrial ecosystems. Overall, the mean correlation between functional redundancy and ecological stability/resilience was positive. The mean positive effect of functional redundancy was greater for studies in which redundancy was measured as species richness within functional groups (vs. metrics independent of species richness), but species richness itself was not corre-lated with effect size. The results of this meta-analysis indicate that functional redundancy may positively affect community stability and resilience to disturbance, but more empirical work is needed including more experimental studies, partitioning of richness and redundancy effects, and links to ecosystem functions.
Disturbances fundamentally alter ecosystem functions, yet predicting their impacts remains a key scientific challenge. While the study of disturbances is ubiquitous across many ecological disciplines, there is no agreed-upon, cross-disciplinary foundation for discussing or quantifying the complexity of disturbances, and no consistent terminology or methodologies exist. This inconsistency presents an increasingly urgent challenge due to accelerating global change and the threat of interacting disturbances that can destabilize ecosystem responses. By harvesting the expertise of an interdisciplinary cohort of contributors spanning 42 institutions across 15 countries, we identified an essential limitation in disturbance ecology: the word ‘disturbance’ is used interchangeably to refer to both the events that cause, and the consequences of, ecological change, despite fundamental distinctions between the two meanings. In response, we developed a generalizable framework of ecosystem disturbances, providing a well-defined lexicon for understanding disturbances across perspectives and scales. The framework results from ideas that resonate across multiple scientific disciplines and provides a baseline standard to compare disturbances across fields. This framework can be supplemented by discipline-specific variables to provide maximum benefit to both inter- and intra-disciplinary research. To support future syntheses and meta-analyses of disturbance research, we also encourage researchers to be explicit in how they define disturbance drivers and impacts, and we recommend minimum reporting standards that are applicable regardless of scale. Finally, we discuss the primary factors we considered when developing a baseline framework and propose four future directions to advance our interdisciplinary understanding of disturbances and their social-ecological impacts: integrating across ecological scales, understanding disturbance interactions, establishing baselines and trajectories, and developing process-based models and ecological forecasting initiatives. Our experience through this process motivates us to encourage the wider scientific community to continue to explore new approaches for leveraging Open Science principles in generating creative and multidisciplinary ideas.
Resilience is a key concept in ecology and describes the capacity of an ecosystem to maintain its state and recover from disturbances. Numerous metrics have been applied to quantify resilience over a range of ecosystems. However, the way resilience is quantified affects the degree to which different trajectories of ecosystem recovery from disturbance are represented as 'resilient', precluding a comparison of disturbance responses across ecosystems and their properties and functions. To approach a broadly comparable assessment of resilience we suggest using a bivariate framework that jointly considers the disturbance impact and the recovery rate, both normalized to the undisturbed state of a system. We demonstrate the potential of the framework for attribution and integration across the various components underlying resilience.
… This paper reports systematic attempts to measure and assess recovery after recent major … , and to assess which are more cost effective rather than detail the process of recovery after …
… When a system is perturbed but resilience is not exceeded, then the recovery can be … Resilience assessment methods also focus on the identification of thresholds (Standish et al. 2014), …
A conceptual framework was developed by a working group of the Scientific Committee of the European Food Safety Authority (EFSA) to guide risk assessors and risk managers on when and how to integrate ecological recovery and resilience assessments into environmental risk assessments (ERA). In this commentary we advocate that a systems approach is required to integrate the diversity of ecosystem services (ES) providing units, environmental factors, scales, and stressor‐related responses necessary to address the context dependency of recovery and resilience in agricultural landscapes. A future challenge in the resilience assessment remains to identify the relevant bundles of ecosystem services provided by different types of agroecosystem that need to be assessed in concert. Integr Environ Assess Manag 2018;14:586–591. © 2018 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals, Inc. on behalf of Society of Environmental Toxicology & Chemistry (SETAC)
… Our purpose was to quantify the ecological resilience of the vegetation communities of an agropastoral dryland ecosystem in response to repeated severe droughts using historical …
This research extends upon land cover change studies by incorporating methodological approaches, which are compatible with heterogeneous ecosystems, are able to link landscape changes to system processes, such as climate change, and provide potential linkages to concepts of ecological resilience. The study region in southern Africa experienced a significant climatic shift in the 1970s, resulting in drier conditions. The state of these ecosystems and their response to such climatic shock is quantified in terms of vegetation amount and heterogeneity. We monitor these characteristics pre- and post-disturbance using a Landsat image series and examine the utility of continuous characterizations of land cover for measuring ecosystem resilience. Land cover change is evaluated using a mean-variance analysis in concert with a spatial persistence analysis. This investigation indicates that although the impact of the decreased precipitation is evident in the 1980s, recovery occurred by the 1990s and 2000s. We found the continuous methodological approach used holds potential for studying heterogeneous landscapes within a resilience framework.
To fully understand ecosystem functioning under global change, we need to be able to measure the stability of ecosystem functioning at multiple spatial scales. Although a number of stability components have been established at small spatial scales, there has been little progress in scaling these measures up to the landscape. Remote sensing data holds huge potential for studying processes at landscape scales but requires quantitative measures that are comparable from experimental field data to satellite remote sensing. Here we present a methodology to extract four components of ecosystem functioning stability from satellite‐derived time series of Enhanced Vegetation Index (EVI) data. The four stability components are as follows: variability, resistance, recovery time and recovery rate in ecosystem functioning. We apply our method to the island of Ireland to demonstrate the use of remotely sensed data to identify large disturbance events in productivity. Our method uses stability measures that have been established at the field‐plot scale to quantify the stability of ecosystem functioning. This makes our method consistent with previous small‐scale stability research, whilst dealing with the unique challenges of using remotely sensed data including noise. We encourage the use of remotely‐sensed data in assessing the stability of ecosystems at a scale that is relevant to conservation and management practices.
… are complex socio-ecological systems increasingly … their ecosystem resilience remain unclear. This study combines time-series remote sensing data and analytical algorithms to quantify …
… resilience index (CRI) quantifies the … of ecological capital on the recovery of a community via an integrated CRI. We developed a measure of ecosystem resilience using remotely sensed …
Quantitative approaches to measuring and assessing terrestrial ecosystem resilience, which expresses the ability of an ecosystem to recover from disturbances without shifting to an alternative state or losing function and services, is critical and essential to forecasting how terrestrial ecosystems will respond to global change. However, global and continuous terrestrial resilience measurement is fraught with difficulty, and the corresponding attribution of resilience dynamics is lacking in the literature. In this study, we assessed global terrestrial ecosystem resilience based on the long time-series GLASS LAI product and GIMMS AVHRR LAI 3g product, and validated the results using drought and fire events as the main disturbance indicators. We also analyzed the spatial and temporal variations of global terrestrial ecosystem resilience and attributed their dynamics to climate change and environmental factors. The results showed that arid and semiarid areas exhibited low resilience. We found that evergreen broadleaf forest exhibited the highest resilience (mean resilience value (from GLASS LAI): 0.6). On a global scale, the increase of mean annual precipitation had a positive impact on terrestrial resilience enhancement, while we found no consistent relationships between mean annual temperature and terrestrial resilience. For terrestrial resilience dynamics, we observed three dramatic raises of disturbance frequency in 1989, 1995, and 2001, respectively, along with three significant drops in resilience correspondingly. Our study mapped continuous spatiotemporal variation and captured interannual variations in terrestrial ecosystem resilience. This study demonstrates that remote sensing data are effective for monitoring terrestrial resilience for global ecosystem assessment.
Urban and regional ecosystems are increasingly challenged by the compounded effects of climate change and intensive land use. In this study, a predictive assessment framework for ecosystem resilience in the Beijing–Tianjin–Hebei region was developed by integrating multi-source remote sensing data, with the aim of quantitatively evaluating the coupled effects of climate change and land use change on future ecosystem resilience. In the first stage of the study, the SD-PLUS coupled modeling framework was employed to simulate land use patterns for the years 2030 and 2060 under three representative combinations of Shared Socioeconomic Pathways and Representative Concentration Pathways (SSP1-2.6, SSP2-4.5, and SSP5-8.5). Building upon these simulations, ecosystem resilience was comprehensively evaluated and predicted on the basis of three key attributes: resistance, adaptability, and recovery. This enabled a quantitative investigation of the spatio-temporal dynamics of ecosystem resilience under each scenario. The results reveal the following: (1) Temporally, ecosystem resilience exhibited a staged pattern of change. From 2020 to 2030, an increasing trend was observed only under the SSP1-2.6 scenario, whereas, from 2030 to 2060, resilience generally increased in all scenarios. (2) In terms of scenario comparison, ecosystem resilience typically followed a gradient pattern of SSP1-2.6 > SSP2-4.5 > SSP5-8.5. However, in 2060, a notable reversal occurred, with the highest resilience recorded under the SSP5-8.5 scenario. (3) Spatially, areas with high ecosystem resilience were primarily distributed in mountainous regions, while the southeastern plains and coastal zones consistently exhibited lower resilience levels. The results indicate that climate and land use changes jointly influence ecosystem resilience. Rainfall and temperature, as key climate drivers, not only affect land use dynamics but also play a crucial role in regulating ecosystem services and ecological processes. Under extreme scenarios such as SSP5-8.5, these factors may trigger nonlinear responses in ecosystem resilience. Meanwhile, land use restructuring further shapes resilience patterns by altering landscape configurations and recovery mechanisms. Our findings highlight the role of climate and land use in reshaping ecological structure, function, and services. This study offers scientific support for assessing and managing regional ecosystem resilience and informs adaptive urban governance in the face of future climate and land use uncertainty, promotes the sustainable development of ecosystems, and expands the applicability of remote sensing in dynamic ecological monitoring and predictive analysis.
Climate change forecasts indicate that the frequency and intensity of extreme climate events will increase in the future; these changes will have important effects on ecosystem stability and function. An important arid region of the world, Central Asia has ecosystems that are extremely vulnerable to extreme weather events. However, few studies have investigated the resistance and resilience of this region’s ecosystems to extreme weather events. In this study, first, the extreme drought/wet threshold was calculated based on the 113-year (1901–2013) standardized precipitation–evapotranspiration index (SPEI); second, moderate resolution imaging spectroradiometer (MODIS) remote sensing data were applied to calculate ecosystem water use efficiency (WUE) and quantify ecosystem resistance and resilience after different extreme climate events; and finally, differences in the changes of various ecosystem types before and after climate events were assessed. The results showed the following: (1) The average SPEI was 0.073, and the thresholds of extreme wetness and drought were 0.91 and −0.67, respectively. Central Asia experienced extreme wet periods in 2002 and 2003 and a drought period in 2008. (2) Suitable wetness levels can increase the resistance of an ecosystem; however, continuous wetness reduces ecosystem resistance, as does drought. Wet areas had strong resilience after wet events, and arid areas had strong resilience after drought events. (3) During both wet and drought years, the transition between shrubland and grassland caused changes in ecosystem resistance and resilience. These findings are important for understanding the impact of future climate change on ecosystem stability.
Sensitivity of forest mortality to drought in carbon‐dense tropical forests remains fraught with uncertainty, while extreme droughts are predicted to be more frequent and intense. Here, the potential of temporal autocorrelation of high‐frequency variability in Landsat Enhanced Vegetation Index (EVI), an indicator of ecosystem resilience, to predict spatial and temporal variations of forest biomass mortality is evaluated against in situ census observations for 64 site‐year combinations in Costa Rican tropical dry forests during the 2015 ENSO drought. Temporal autocorrelation, within the optimal moving window of 24 months, demonstrated robust predictive power for in situ mortality (leave‐one‐out cross‐validation R2 = 0.54), which allows for estimates of annual biomass mortality patterns at 30 m resolution. Subsequent spatial analysis showed substantial fine‐scale heterogeneity of forest mortality patterns, largely driven by drought intensity and ecosystem properties related to plant water use such as forest deciduousness and topography. Highly deciduous forest patches demonstrated much lower mortality sensitivity to drought stress than less deciduous forest patches after elevation was controlled. Our results highlight the potential of high‐resolution remote sensing to “fingerprint” forest mortality and the significant role of ecosystem heterogeneity in forest biomass resistance to drought.
… Ecological resilience, the amount of disturbance that a system can withstand before it shifts … because they are amenable to remote sensing and quantification with GIS. Many other types …
Coastal ecosystems, such as mangroves, provide key ecosystem services for climate change mitigation and adaptation. However, combined anthropogenic activities and climatic change‐driven sea level rise (SLR) pose a severe threat to their global persistence, and to the continued delivery of these services. Mangrove vulnerability to SLR depends upon capacity for both resilience (landward migration) and resistance (maintained functioning with the existing distribution), which are in turn hindered by extractive activities and coastal infrastructure development. Limited landscape‐scale data availability means existing SLR vulnerability assessment frameworks lack rigorous quantification of these discrete processes. Here we develop and implement a novel multi‐product (multispectral, microwave, derived‐product) open‐access satellite remote sensing approach to assess both coastal ecosystem SLR resilience and resistance capacity in multiple mangrove sites across the world, and landscape‐level and anthropogenic factors driving these capacities. Our approach allows comparative ranking of resilience and resistance capacities across sites, based on relative observed ecosystem change (biomass, distribution) and in constraints to these two components of SLR vulnerability. We observe mostly low SLR resilience and resistance across our case study sites. Furthermore, we find that site‐specific resilience and resistance capacities and constraints can be highly incongruent, highlighting the importance of comprehensive SLR vulnerability monitoring for effective management. High within‐site variation was also detected in resilience and resistance capacities and their constraints. This underlines the importance of spatially explicit monitoring at extensive spatial scales to inform decision making. The methodology developed and repeat‐pass imagery employed adds to the remote monitoring and assessment toolkit for adaptive coastal ecosystem management under SLR, providing a new approach to inform conservation and management priority assessments in data‐deficient regions.
… However, the quantification and characterization of resilience is a … different ecosystems across the globe. In order to explore ecosystem resilience to drought, we estimated the resilience …
… More importantly, our analysis is based on additive regression models, and the sharp rise of … Although we limited our analysis to evergreen tropical forests it is possible that vegetation …
… quantify coral reef resilience across reefs. Remote sensing allows direct mapping of several ecosystem … is to operationalize our understanding of ecosystem resilience and apply it for …
. Rapid environmental changes challenge the resilience of wildlands. The western portion of the Lake Tahoe Basin in California is an important ecological and cultural hotspot that is at risk of degradation from current and future environmental pressures. Historical uses, fire suppression, and a changing climate have created forest landscape conditions at risk of drought stress, destructive fire, and loss of habitat diversity. We prospectively modeled forest landscape conditions for a period of 100 years to evaluate the efficacy of 5 unique management scenarios in achieving desired landscape conditions. Management scenarios ranged from no management other than fire suppression to applying treatments consistent with historical fire frequencies and extent (i.e., regular and broadscale biomass reduction). We developed a decision support tool to evaluate environmental and social outcomes within a single framework to provide a transparent set of costs and benefits. Results illuminated underlying mechanisms of forest resilience and provided actionable guidance to decision makers. Sixteen attributes were assessed in the model after assigning weights to each. We found that removing forest biomass across the landscape, particularly when accomplished using extensive fire-based removal techniques, led to highly favorable conditions for environmental quality and promoted overall landscape resilience. Environmental conditions resulting from extensive fire-based biomass removal also had nominal variation over time, in contrast with strategies that had less extensive and/or used physical removal techniques (e.g., mechanical thinning). Our analysis provides a transparent approach to assess large datasets with complex and interacting variables. Ultimately, we aim to provide insights into the complexities of maintaining optimal conditions and managing landscapes to promote ecosystem resilience in a changing world
… multiple ES and landscape ecological resilience. We … ecological process flows can be used to develop spatially explicit network nodes and links between multiple ES across landscapes…
… Unfortunately, ecological resilience is difficult to measure or estimate in the landscapes … approaches to resilience and estimate resilience using complex landscape simulation models. I …
… Like the stressor metrics, each resiliency metric measures resiliency from a … landscape context and ecological function, and resiliency metrics are correlated, yielding a set of metrics that …
… units of analysis and to calculate the landscape metrics. Given the extent of the studied area, … We explored the trade-off between ecological resilience and restoration cost proposing a …
Goals of fostering ecological resilience are increasingly used to guide U.S. public land management in the context of anthropogenic climate change and increasing landscape disturbances. There are, however, few operational means of assessing the resilience of a landscape or ecosystem. We present a method to evaluate resilience using simulation modeling. In this method, we use historical conditions (e.g., in North America, prior to European settlement), quantified using simulation modeling, to provide a comparative reference for contemporary conditions, where substantial departures indicate loss of resilience. Contemporary ecological conditions are compared statistically to the historical time series to create a resilience index, which can be used to prioritize landscapes for treatment and inform possible treatments. However, managing for resilience based on historical conditions is tenuous in the Anthropocene, which is characterized by rapid climate change, extensive human land use, altered disturbance regimes, and exotic species introductions. To account for the future variability of ecosystems resulting from climate and disturbance regime shifts, we augment historical simulations with simulations of ecosystem dynamics under projected climate and land use changes to assess the degree of departure from benchmark historical conditions. We use a mechanistic landscape model (FireBGCv2) applied to a large landscape in western Montana, USA, to illustrate the methods presented in this paper. Spatially explicit ecosystem modeling provides the vehicle to generate the historical and future time series needed to quantify potential resilience conditions associated with past and potential future conditions. Our methods show that given selection of a useful set of metrics, managers could use simulations like ours to evaluate potential future management
Abstract Resilience is increasingly being considered as a new paradigm of forest management among scientists, practitioners, and policymakers. However, metrics of resilience to environmental change are lacking. Faced with novel disturbances, forests may be able to sustain existing ecosystem services and biodiversity by exhibiting resilience, or alternatively these attributes may undergo either a linear or nonlinear decline. Here we provide a novel quantitative approach for assessing forest resilience that focuses on three components of resilience, namely resistance, recovery, and net change, using a spatially explicit model of forest dynamics. Under the pulse set scenarios, we explored the resilience of nine ecosystem services and four biodiversity measures following a one‐off disturbance applied to an increasing percentage of forest area. Under the pulse + press set scenarios, the six disturbance intensities explored during the pulse set were followed by a continuous disturbance. We detected thresholds in net change under pulse + press scenarios for the majority of the ecosystem services and biodiversity measures, which started to decline sharply when disturbance affected >40% of the landscape. Thresholds in net change were not observed under the pulse scenarios, with the exception of timber volume and ground flora species richness. Thresholds were most pronounced for aboveground biomass, timber volume with respect to the ecosystem services, and ectomycorrhizal fungi and ground flora species richness with respect to the biodiversity measures. Synthesis and applications. The approach presented here illustrates how the multidimensionality of stability research in ecology can be addressed and how forest resilience can be estimated in practice. Managers should adopt specific management actions to support each of the three components of resilience separately, as these may respond differently to disturbance. In addition, management interventions aiming to deliver resilience should incorporate an assessment of both pulse and press disturbances to ensure detection of threshold responses to disturbance, so that appropriate management interventions can be identified.
… Stability landscapes, in terms of ecosystem resilience, … parameterisation around equilibrium, resilience, tipping points … stability landscapes are changes that arise when an ecosystem …
Abstract Sustainable agriculture aims to produce sufficient food while minimizing environmental damage. To achieve this, we need to understand the role of agricultural landscapes in providing diverse ecosystem services and how these affect crop production and resilience, that is, maintaining yields despite environmental perturbation. We used 10 years of English wheat yield data to derive three metrics of resilience (relative yield across the time series, yield stability around a moving average and resistance to an extreme weather event) at 10 km × 10 km resolution. We used remotely sensed maps to calculate measures of landscape structure, including composition (proportions of different land cover types) and configuration (metrics of connectivity and proximity), known to affect ecosystem service delivery (e.g. control of pests by beneficial invertebrates). We then used an information‐theoretic approach to identify the best‐fitting combination of landscape structure predictors for each resilience metric, using a potential yield model to account for the effects of climate and soils. Relative yield showed a strongly positive relationship with the area of arable land. For yield stability, this relationship was evident but alongside other landscape structure variables in the best‐fitting model. No relationship with arable land was evident for resistance. Yield stability showed a strongly positive effect of proximity to semi‐natural habitats. For resistance, the best‐fitting model included positive relationships with the cover of semi‐natural habitats and proximity to semi‐natural grasslands. Synthesis and applications . Landscapes with the highest relative wheat yields did not show the highest yield stability or resistance to extreme events. As resilience metrics were derived from shorter portions of the time series, the importance of semi‐natural habitats compared to arable land increased. This is probably driven by the complex interplay between landscape structure, agricultural management and ecosystem services. These results demonstrate that measuring relative yield over time may be insufficient to capture the full effect that non‐arable components of the landscape, and the ecosystem services they deliver, have on other aspects of resilience, and that there are clear trade‐offs in managing agricultural landscapes to maximize different aspects of crop yield resilience.
… Although social–ecological resilience is generally thought to be … and ecological resilience, the two may also be in conflict. Focusing solely on ecosystems can reduce social resilience (…
Abstract Resilience is the capacity of an ecosystem to respond and recover from damage or stress. It can inherently exhibit the cycle and feedback of the disturbed ecosystem recovery process for a specified period. The current availability of dense and consistent time series of satellite images holds the promise of monitoring forest resilience. The aim of this study is to establish forest resilience indicators using dense Landsat time series and assess forest resilience in response to the maximum disturbance magnitude in the hilly red soil region, Hengyang Basin, Southern China. To achieve this, Landsat images of the study area from 1987 to 2017 were collected. Normalized Difference Vegetation Index (NDVI), i.e., proxy of forest green characteristics, number of patch (NP), average patch size (PS), patch perimeter-area ratio (PPAR) and aggregation index (AI), i.e., proxies of forest landscape metrics were calculated from Landsat images. And then elasticity (i.e., the time and rate of recovery), malleability (i.e., degree of deviation from an initial state) and trend (i.e., the pattern of change) as the indicators of forest resilience were constructed. The local space–time Moran’s I (STI) based on NDVI residual space–time Moran’s I (STI) was employed to characterize the forest disturbance and recovery process. The results revealed the following. Firstly, the STI calculated from dense time series NDVI residuals are successful at monitoring the forest disturbance recovery process, regardless of whether changes were dramatic or subtle. Secondly, the most forest disturbances (i.e., > 75%) occurred in the late 1980s and early 1990s. NDVI and landscape metrics also differed in their response to disturbances; NDVI, PPAR and AI are more malleable to disturbance than PS and NP are. Finally, approximately 40% of the disturbed forest had the strong elasticity with a short recovery time (i.e., a year). We conclude that measuring forest resilience via vegetation greenness and landscape metrics using dense time series satellite images is practical as an operational tool for policy makers, landowners, and national park managers. Moreover, insights into ecological dynamics are emerging from capturing the process showing the difference both before and after the change.
This review provides an overview and integration of the use of resilience concepts to guide natural resources management actions. We emphasize ecosystems and landscapes and provide examples of the use of these concepts from empirical research in applied ecology. We begin with a discussion of definitions and concepts of ecological resilience and related terms that are applicable to management. We suggest that a resilience-based management approach facilitates regional planning by providing the ability to locate management actions where they will have the greatest benefits and determine effective management strategies. We review the six key components of a resilience-based approach, beginning with managing for adaptive capacity and selecting an appropriate spatial extent and grain. Critical elements include developing an understanding of the factors influencing the general and ecological resilience of ecosystems and landscapes, the landscape context and spatial resilience, pattern and process interactions and their variability, and relationships among ecological and spatial resilience and the capacity to support habitats and species. We suggest that a spatially explicit approach, which couples geospatial information on general and spatial resilience to disturbance with information on resources, habitats, or species, provides the foundation for resilience-based management. We provide a case study from the sagebrush biome that illustrates the use of geospatial information on ecological and spatial resilience for prioritizing management actions and determine effective strategies.
… ecological resilience—the capacity of an ecosystem to … —with ecosystem services to identify priority areas for ecological … —Service Priority, Balanced Priority, and Resilience Priority—to …
… resilience index of 113 ecological corridors ranged from 0.0027 to 0.8002. Corridors with high resilience … corridors with low resilience were distributed in the west and north areas. The …
In order to enhance ecosystem stability and promote sustainable regional ecological, social, and economic development, it is crucial to explore the coupling relationship between ecosystem service supply and demand and the resilience of ecosystem, so as to propose scientific ecological management zones and strategies. Taking the vulnerable alpine ecosystem in Gannan Tibetan Autonomous Prefecture (Gannan Prefecture) as the study area, this paper comprehensively utilized multi-source data, grid analysis, ecosystem service supply and demand estimation model, and coupled coordination model to analyze the spatio-temporal differentiation and coordination pattern of ecosystem service supply and demand in the study area from 2000 to 2020. With the assistance of the Analytic Hierarchy Process (AHP), the ecosystem resilience index system was constructed to evaluate the regional ecological resilience. The results reveal the following: (1) In the past 20 years, the ecosystem service supply and resilience in Gannan Prefecture showed a fluctuating upward trend, and the demand continued to grow steadily. Their spatial differentiation were obvious, but the pattern remained stable. (2) There was a moderate incoordination indicated by the average coordination degree of the supply and demand coupling of ecosystem services, which rangeed between 0.3 and 0.4. (3) Gannan Prefecture was split into three ecological management zones, considering the spatial distribution of ecosystem service supply and demand, as well as resilience. Through system function monitoring and other measures, the ecological conservation zone will rely on its high resilience to support the restoration and self-sufficiency of the system, ensuring the stability and well-being of the ecosystem. The primary objectives of general protected zone includes environmental preservation, strict regulations, and the prevention of human intervention. To enhance their ecological background, key restoration zone must intensify the implementation of ecological restoration initiatives. To address the needs of the locals, strategies such as ecological compensation, optimizing the land use structure, and fostering the growth of environmentally friendly companies can be implemented simultaneously.
… life and ecosystem services (ESs), the spatio-temporal assessment of the resilience of ESs … for assessing ESs-based resilience, taking into account the seven resilience principles: a) …
Biological systems are likely to be constrained by trade-offs among robustness, resilience, and performance. A better understanding of these trade-offs is important for basic biology, as well as applications where biological systems can be designed for different goals. We focus on redundancy and plasticity as mechanisms governing some types of trade-offs, but mention others as well. Whether trade-offs are due to resource constraints or "design" constraints (i.e., structure of nodes and links within a network) will also affect the types of trade-offs that are important. Identifying common themes across scales of biological organization will require that researchers use similar approaches to quantifying robustness, resilience, and performance, using units that can be compared across systems.
… used to quantify resilience, should be interpreted as a metric for … stability and the ability to return to a stable point or trajectory only (ie, engineering resilience), whereas stability metrics …
Characterizing how ecosystems are responding to rapid environmental change has become a major focus of ecological research. The empirical study of ecological stability, which aims to quantify these ecosystem responses, is therefore more relevant than ever. Based on a historical review and bibliometric mapping of the field of ecological stability, we show that the two main schools relating to the study of stability—one focusing on systems close to their equilibrium and the other on non‐equilibrium behaviour—have developed in parallel leading to divergence in both concepts and definitions. We synthesize and expand previous frameworks and capitalize on the latest developments in the field to build towards an integrated framework by elaborating the overarching concept of ecological stability and its properties. Finally, the broad applicability of our work is demonstrated in two empirical cases. Synthesis. With rapidly changing environmental conditions, the stability of ecosystems has become a major focus of ecological research. Still, the concept of stability remains a major source of confusion and disagreement among ecologists. The conceptual framework presented here provides a basis to integrate currently diverging views on the study of ecological stability.
Various macro-evolutionary phenomena, such as long-term stability punctuated by bursts of evolution, are difficult to explain via the micro-evolutionary process of weak selection acting steadily on individual mutations. In contrast, bursts of change are expected if evolutionary systems are complex and balanced, with occasional disruption of balance. Such disruption represents the collapse of resilience, akin to the snapping of an elastic band. It can be driven by external factors, or by self-propagating feedback loops internal to a system. Thus, evolutionary resilience could help explain how evolution generates broader patterns of biodiversity. We outline evidence and tests for this hypothesis, which emphasizes the processes balancing evolution, as urged fifty years ago in ecological genetics and via modern results in a range of systems.
… biodiversity on stability during and after the extreme events are shown, assuming a limited recovery period. Resilience … quantify differences in biodiversity using trait-based metrics and (4…
Ecological resilience is critical for ecosystems to persist in the face of perturbations without shifting to a different state. Global biodiversity loss in multiple ecosystems is considered to be associated with decreasing ecological resilience and increasing the risk of ecosystem collapse. However, how temporal changes in biodiversity affect ecological resilience in natural ecosystems remains poorly elucidated. By analyzing subfossil records of diatoms, chironomids, and cladocerans from 53 lake sediment cores across the globe, we found that species richness showed an increasing trend with time, while beta diversity and ecological resilience presented a decreasing temporal trend when ecosystems are approaching the abrupt shift. Asynchronous fluctuations among species and temporal stability at species level are suggested to be the mechanisms that contribute to the maintenance of temporal community stability. We found species richness and beta diversity have positive effects on species asynchrony but negative effects on species stability. However, we found that species asynchrony and species stability had negative relationships with ecological resilience, with species richness and beta diversity overall having no positive effects on ecological resilience. We highlighted that biodiversity effects on ecological resilience are not only the role of species richness, but also the species assemblage and network complexity of species-species interactions. Our study indicates that increased species diversity and community heterogeneity may be not beneficial for the ecosystem to recover from disturbances at a lake ecosystem scale, which has great implications for the assessment of ecological resilience and predicting ecosystem collapse in future global environmental change scenarios.
… and measures of resilience currently in use make it difficult to determine whether and how biodiversity, or other system features, influence resilience. According to the resilience theory of …
… recover rapidly following disturbance (resilience), and slow species … and higher resilience, thus increasing ecosystem stability. … MNTD, therefore, is a good metric to test our hypotheses …
Complex natural systems, spanning from individuals and populations to ecosystems and social-ecological systems, often exhibit abrupt reorganizations in response to changing stressors, known as regime shifts or critical transitions. Theory suggests that such systems feature folded stability landscapes with fluctuating resilience, fold-bifurcations, and alternate basins of attraction. However, the implementation of such features to elucidate response mechanisms in an empirical context is scarce, due to the lack of generic approaches to quantify resilience dynamics in individual natural systems. Here, we introduce an Integrated Resilience Assessment (IRA) framework: a three-step analytical process to assess resilience and construct stability landscapes of empirical systems. The proposed framework involves a multivariate analysis to estimate holistic system indicator variables, non-additive modelling to estimate alternate attractors, and a quantitative resilience assessment to scale stability landscapes. We implement this framework to investigate the temporal development of the Mediterranean marine communities in response to sea warming during 1985–2013, using fisheries landings data. Our analysis revealed a nonlinear tropicalisation of the Mediterranean Sea, expressed as abrupt shifts to regimes dominated by thermophilic species. The approach exemplified here for the Mediterranean Sea, revealing previously unknown resilience dynamics driven by climate forcing, can elucidate resilience and shifts in other complex systems.
关于生态系统韧性评价指标的研究已形成一套多层次的体系,主要涵盖:韧性理论内涵的界定与多维框架构建;利用遥感及空间数据进行的时空动态定量化监测;探究生物多样性与功能多样性对韧性影响的机制分析;以及将韧性度量应用于区域管理与社会-生态系统韧性决策支持的实证评估。这四个维度的整合体现了韧性评价从抽象概念向具体可操作性指标及管理工具转化的趋势。