Institute of Geosciences, Universität Potsdam, Potsdam, Germany.
Earth System Modelling, School of Engineering and Design, Technical University of Munich, Munich, Germany.
Nat Ecol Evol. 2023 Nov;7(11):1799-1808. doi: 10.1038/s41559-023-02194-7. Epub 2023 Sep 14.
Concerns have been raised that the resilience of vegetated ecosystems may be negatively impacted by ongoing anthropogenic climate and land-use change at the global scale. Several recent studies present global vegetation resilience trends based on satellite data using diverse methodological set-ups. Here, upon a systematic comparison of data sets, spatial and temporal pre-processing, and resilience estimation methods, we propose a methodology that avoids different biases present in previous results. Nevertheless, we find that resilience estimation using optical satellite vegetation data is broadly problematic in dense tropical and high-latitude boreal forests, regardless of the vegetation index chosen. However, for wide parts of the mid-latitudes-especially with low biomass density-resilience can be reliably estimated using several optical vegetation indices. We infer a spatially consistent global pattern of resilience gain and loss across vegetation indices, with more regions facing declining resilience, especially in Africa, Australia and central Asia.
人们担心，在全球范围内，不断发生的人为气候变化和土地利用变化可能会对植被生态系统的恢复力产生负面影响。最近的几项研究基于卫星数据，使用不同的方法框架，提出了全球植被恢复力趋势。在这里，我们通过对数据集、空间和时间预处理以及恢复力估计方法进行系统比较，提出了一种避免先前结果中存在的不同偏差的方法。然而，我们发现，无论选择哪种植被指数，使用光学卫星植被数据来估计恢复力都存在广泛的问题，尤其是在密集的热带和高纬度北方森林地区。然而，对于中纬度的大部分地区——特别是生物量密度较低的地区——使用多种光学植被指数可以可靠地估计恢复力。我们推断出了一种跨越植被指数的具有空间一致性的全球恢复力增益和损失模式，越来越多的地区面临恢复力下降的情况，尤其是在非洲、澳大利亚和中亚地区。
