Title: Spatial correlation increase in single-sensor satellite data reveals loss of Amazon rainforest resilience Show Chinese title

Title: 单传感器卫星数据中的空间相关性增加揭示了亚马逊雨林弹性的丧失

Abstract: The Amazon rainforest (ARF) is threatened by deforestation and climate change, which could trigger a regime shift to a savanna-like state. Previous work suggesting declining resilience in recent decades was based only on local resilience indicators. Moreover, previous results are potentially biased by the employed multi-sensor and optical satellite data and undetected anthropogenic land-use change. Here, we show that the spatial correlation provides a more robust resilience indicator than local estimators and employ it to measure resilience changes in the ARF, based on single-sensor Vegetation Optical Depth data under conservative exclusion of human activity. Our results show an overall loss of resilience until around 2019, which is especially pronounced in the southwestern and northern Amazon for the time period from 2002 to 2011. The demonstrated reliability of spatial correlation in coupled systems suggests that in particular the southwest of the ARF has experienced pronounced resilience loss over the last two decades. Show Chinese abstract

Abstract: 亚马逊雨林（ARF）受到森林砍伐和气候变化的威胁，这可能导致转变为类似稀树草原的状态。 以往的研究表明近几十年来弹性下降，但仅基于局部弹性指标。 此外，以前的结果可能受到所使用的多传感器和光学卫星数据以及未检测到的人类土地利用变化的影响。 在这里，我们表明空间相关性比局部估计器提供了更稳健的弹性指标，并利用它来测量亚马逊雨林的弹性变化，基于单一传感器植被光学深度数据，在保守排除人类活动的情况下进行。 我们的结果表明，直到2019年整体弹性有所丧失，特别是在2002年至2011年期间，西南部和北部亚马逊地区的弹性丧失尤为明显。 在耦合系统中空间相关性的可靠性得到证明，这尤其表明亚马逊雨林的西南部在过去二十年中经历了明显的弹性丧失。