Assessing Individual And Local Scale Forest Vulnerability To Mortality From The 2019 Extreme Drought In Central Europe

气候变化正在对全球树木和森林生态系统的健康产生重大影响。对于许多地区来说，在未来气候情景下，干旱事件的频率和强度预计会增加。因此，随着气候变暖和干旱事件变得更加频繁和强烈，预计森林生长将普遍减少，死亡事件的范围和严重程度将增加。虽然干旱事件的影响往往发生在物种分布的炎热和干燥边缘，但令人震惊的是，最近与干旱有关的物种灭绝发生在气候条件最有利的物种范围的核心区。全球植被生长模型很难预测被认为总体上适合该物种气候的地区的死亡事件，这给确定哪些森林容易受干旱影响以及这种脆弱性在不同景观和个别树木中的差异带来了相当大的挑战。为了解决这一问题，我们迫切需要来自物种分布核心区内死亡和幸存严重干旱事件的个人的详细数据。然而，预测强烈干旱事件将在何时何地发生是极具挑战性的，这使得收集这种响应性数据非常困难。2019年，一场严重的干旱事件影响了中欧的森林。2020年春，很明显，这一干旱事件在欧洲山毛榉的核心区造成了广泛但变数很大的死亡--欧洲山毛榉是欧洲大陆分布最广泛的阔叶树之一，也是关键的林业资源。中欧欧洲山毛榉森林对2019年严重干旱的非同寻常的反应，现在为我们提供了一个特殊的机会，可以更好地预测在该物种范围的核心范围内，哪些林区面临干旱事件的风险增加。通过在这一极端事件发生后在现已死亡的树木的树冠开始脱落和坍塌之前迅速采取行动，我们可以收集2019年干旱事件中死亡和幸存下来的单个树木的数据，以确定树木大小(例如直径、高度、树冠大小)、林分竞争(例如树木密度、大小分布)、历史生长模式(由树木年轮确定)和当地地形特征(例如坡度、坡向、曲率)如何影响树木对干旱导致死亡的脆弱性。我们将把详细的现场测量与同样详细的无人机捕获的高光谱和激光雷达数据以及卫星遥感数据配对，这将使我们能够从森林树冠上方评估树木健康和森林结构。有效地利用这一短暂的机会窗口来评估2019年干旱的影响，将使我们能够制定新的方法，快速评估森林健康状况，并预测大片森林的脆弱性。该项目收集的数据将使我们能够对树木易受干旱的脆弱性作出现实的当地预测，并开发遥感方法来支持这些森林健康预测的有效性。2019年中欧干旱事件后造成的情况极其罕见，因此该项目提供了一个重大机会，以推动森林健康遥感方面亟需的改进，并提供在持续气候变化下改进全球森林增长模型所需的知识和数据。

Climate change is having significant impacts on the health of trees and forest ecosystems globally. For many regions, the frequency and intensity of drought events are predicted to increase under future climate scenarios. Consequently, widespread reductions in forest growth and increases in the extent and severity of die-off events are anticipated as the climate warms and drought events become more frequent and intense. While the effects of drought events have often been observed at the hot and dry margins of species distributions, alarmingly, recent drought-linked die-off has occurred within the core area of species ranges where climatic conditions should be most favourable. Global models of vegetation growth have difficulty predicting die-off events in areas considered to be generally climatically suitable for the species, bringing considerable challenges in identifying which forests are vulnerable to droughts and how that vulnerability varies across landscapes and individual trees. To address this problem, we urgently need detailed data from individuals that die and those that survive intense drought events from within the core regions of the species distribution. However, predicting when and where intense drought events will occur is extremely challenging, making such responsive data collection very difficult. In 2019 an intense drought event impacted forests in Central Europe. In the Spring of 2020, it became clear that this drought event had caused widespread, yet highly variable die-off within the core area of the range of the European beech tree - one of the most widely distributed broadleaf trees on the continent and a key forestry resource. The extraordinary response of the European beech forests in Central Europe to the intense drought in 2019 now provides us with an exceptional opportunity to better predict which forest areas are at an increased risk to drought events within the core of this species range. By acting rapidly in the wake of this extreme event before the crowns of the now-dead trees begin to lose branches and collapse, we can collect data from individual trees that died and survived the 2019 drought event to determine how tree size (e.g. diameter, height, crown size), stand competition (e.g. tree density, size distribution), historical growth patterns (determined from tree rings), and local terrain characteristics (e.g. slope, aspect, curvature) influence the vulnerability of trees to drought-induced mortality. We will pair detailed field measurements with equally detailed drone-captured hyperspectral and LiDAR data and satellite remote sensing data that will enable us to assess tree heath and forest structure from above the forest canopy. Effectively exploiting this short window of opportunity to assess the impact of the 2019 drought will enable us to develop new approaches for the rapid assessment of forest health and to predict vulnerability across large areas of forest. The data collected in this project will allow us to make realistic local forecasts of tree vulnerability to drought and develop remote sensing methods to support the validation of these forest health forecasts. The conditions that have resulted following the drought event in Central Europe in 2019 are extremely rare and so this project provides a major opportunity to drive much needed improvements in remote sensing of forest health and deliver the knowledge and data needed to improve global models of forest growth under ongoing climate change.