Dead Again: Predictions of repeat tree die-off under hotter droughts confirm mortality thresholds for a dryland conifer species

Tree die-off, driven by extreme drought and exacerbated by a warming climate, is occurring rapidly across every wooded continent - threatening carbon sinks and other ecosystem services provided by forests and woodlands. Forecasting the spatial patterns of tree die-off in response to drought is a priority for the management and conservation of forested ecosystems under projected future hotter and drier climates. Several drought-related metrics have recently been proposed to predict the mortality threshold (i.e., tipping point) for Pinus edulis, a model tree species in many studies of drought-induced tree die-off. To improve future capacity to forecast tree mortality, we used a severe drought in 2018 across the southwestern United States as a natural experiment. We compared the ability of published mortality thresholds derived from four drought metrics (the Forest Drought Severity Index, the Standardized Precipitation Evapotranspiration Index, and raw values of precipitation and vapor pressure deficit) to predict areas of P. edulis die-off following extreme drought. Using aerial detection surveys of tree mortality in combination with gridded climate data, we calculated the agreement between these four proposed thresholds and the presence and absence of regional-scale tree die-off. Overall, such thresholds tended to over predict the spatial extent of tree die-off across the landscape, yet some retain moderate skill in discriminating between areas that experienced and did not experience tree die-off. Area under the curve (AUC) of these thresholds ranged from 0.51 to 0.71, sensitivity (true-positive rate) ranged from 0.54 to 0.86, and specificity (true-negative rates) ranged from 0.16 to 0.73. We highlight that empirically derived climate thresholds may be a useful forecasting tool to identify vulnerable areas to drought induced die-off, allowing for targeted responses to future droughts and improved management of at-risk areas.极端干旱驱动、气候变暖加剧的林木枯亡（Tree die-off）事件正快速席卷所有覆盖森林的大陆，威胁着森林与林地所提供的碳汇及其他生态系统服务。在未来气候预计更热更干燥的背景下，预测干旱引发的林木枯亡空间格局，是森林生态系统管理与保护的优先事项。近期已有多项干旱相关指标被提出，用于预测二针松（Pinus edulis）的死亡阈值（即临界点）——该树种是诸多干旱诱导林木枯亡研究中的模式树种。为提升未来林木死亡预测能力，我们以2018年美国西南部发生的严重干旱作为自然实验。我们对比了基于四项干旱指标推导得到的已发表死亡阈值的预测能力，这四项指标分别为：森林干旱严重性指数（Forest Drought Severity Index）、标准化降水蒸散指数（Standardized Precipitation Evapotranspiration Index），以及降水与水汽压亏缺（vapor pressure deficit）的原始观测值，用于预测极端干旱后二针松的枯亡区域。我们结合林木枯亡航空探测调查数据与网格化气候数据，计算了这四项提出的阈值与区域尺度林木枯亡发生与否的吻合程度。总体而言，此类阈值往往会高估区域内林木枯亡的空间范围，但部分阈值仍具备中等区分能力，可识别发生与未发生林木枯亡的区域。这些阈值的受试者工作特征曲线下面积（Area under the curve, AUC）介于0.51至0.71之间，灵敏度（true-positive rate）介于0.54至0.86之间，特异度（true-negative rate）介于0.16至0.73之间。我们强调，基于经验推导得到的气候阈值可作为实用的预测工具，用于识别易受干旱诱导枯亡影响的区域，从而为未来干旱制定针对性应对措施，并优化风险区域的管理工作。