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      Changes and influencing factors of ecosystem resilience in China

      , , , , ,
      Environmental Research Letters
      IOP Publishing

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          Abstract

          The multifunctionality and sustainability of ecosystems are strongly dependent on their ability to withstand and recover from disturbances—that is, ecosystem resilience (ER). However, the dynamics and attributes of ER remain largely unknown, especially in China, where climatic and anthropogenic pressures are high. In this study, we evaluated spatiotemporal patterns of ER in China from 2001 to 2020 using solar-induced chlorophyll fluorescence. We estimated the relative independent importance of climate change, CO 2, and anthropogenic factors on changes in ER signals. The results showed that more than half of the ecosystems in the study area have experienced ER gain followed by ER loss during the past two decades. Before breakpoints (BPs), climate change explained 58.29% of the ER change associated with increasing precipitation. After BPs, 65.10% of the ER change was most affected by CO 2, and drought from rising temperature further deteriorated ER loss. We highlight that relationships between changes in ER and climate are spatially heterogeneous and suggest increased negative radiative effects of CO 2, associated with global warming, on ecosystem stability due to the saturated canopy photosynthesis. These findings have crucial implications for future climate change mitigation, carbon peak, and carbon neutrality targets.

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          Early-warning signals for critical transitions.

          Complex dynamical systems, ranging from ecosystems to financial markets and the climate, can have tipping points at which a sudden shift to a contrasting dynamical regime may occur. Although predicting such critical points before they are reached is extremely difficult, work in different scientific fields is now suggesting the existence of generic early-warning signals that may indicate for a wide class of systems if a critical threshold is approaching.
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            Forest disturbances under climate change

            Forest disturbances are sensitive to climate. However, our understanding of disturbance dynamics in response to climatic changes remains incomplete, particularly regarding large-scale patterns, interaction effects and dampening feedbacks. Here we provide a global synthesis of climate change effects on important abiotic (fire, drought, wind, snow and ice) and biotic (insects and pathogens) disturbance agents. Warmer and drier conditions particularly facilitate fire, drought and insect disturbances, while warmer and wetter conditions increase disturbances from wind and pathogens. Widespread interactions between agents are likely to amplify disturbances, while indirect climate effects such as vegetation changes can dampen long-term disturbance sensitivities to climate. Future changes in disturbance are likely to be most pronounced in coniferous forests and the boreal biome. We conclude that both ecosystems and society should be prepared for an increasingly disturbed future of forests.
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              Methods for Detecting Early Warnings of Critical Transitions in Time Series Illustrated Using Simulated Ecological Data

              Many dynamical systems, including lakes, organisms, ocean circulation patterns, or financial markets, are now thought to have tipping points where critical transitions to a contrasting state can happen. Because critical transitions can occur unexpectedly and are difficult to manage, there is a need for methods that can be used to identify when a critical transition is approaching. Recent theory shows that we can identify the proximity of a system to a critical transition using a variety of so-called ‘early warning signals’, and successful empirical examples suggest a potential for practical applicability. However, while the range of proposed methods for predicting critical transitions is rapidly expanding, opinions on their practical use differ widely, and there is no comparative study that tests the limitations of the different methods to identify approaching critical transitions using time-series data. Here, we summarize a range of currently available early warning methods and apply them to two simulated time series that are typical of systems undergoing a critical transition. In addition to a methodological guide, our work offers a practical toolbox that may be used in a wide range of fields to help detect early warning signals of critical transitions in time series data.
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                Author and article information

                Contributors
                Journal
                Environmental Research Letters
                Environ. Res. Lett.
                IOP Publishing
                1748-9326
                August 14 2023
                September 01 2023
                August 14 2023
                September 01 2023
                : 18
                : 9
                : 094012
                Article
                10.1088/1748-9326/acec89
                30b4b203-2fc0-459f-afb3-88fabd50895e
                © 2023

                http://creativecommons.org/licenses/by/4.0

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