Data from: Does one model fit all? patterns of beech mortality in natural forests of three European regions

Large uncertainties characterize forest development under global climate change. Although recent studies have found widespread increased tree mortality, the patterns and processes associated with tree death remain poorly understood, thus restricting accurate mortality predictions. Yet, projections of future forest dynamics depend critically on robust mortality models, preferably based on empirical data rather than theoretical, not well-constrained assumptions. We developed parsimonious mortality models for individual beech (Fagus sylvatica) trees and evaluated their potential for incorporation in Dynamic Vegetation Models (DVMs). We used inventory data from nearly 19′000 trees from unmanaged forests in Switzerland, Germany and Ukraine, representing the largest dataset used to date for calibrating such models. Tree death was modelled as a function of size and growth, i.e., stem diameter (dbh) and relative basal area increment (relBAI), using generalized logistic regression accounting for unequal re-measurement intervals. To explain the spatial and temporal variability in mortality patterns, we considered a large set of environmental and stand characteristics. Validation with independent datasets was performed to assess model generality. Our results demonstrate strong variability in beech mortality that was independent of environmental or stand characteristics. Mortality patterns in Swiss and German strict forest reserves were dominated by competition processes as indicated by J-shaped mortality over tree size and growth. The Ukrainian primeval beech forest was additionally characterized by windthrow and a U-shaped size-mortality function. Unlike the mortality model based on Ukrainian data, the Swiss and German models achieved good discrimination and acceptable transferability when validated against each other. We thus recommend these two models to be incorporated and examined in DVMs. Their mortality predictions respond to climate change via tree growth, which is sufficient to capture the adverse effects of water availability and competition on the mortality probability of beech under current conditions.

全球气候变化背景下，森林动态发展过程中存在极大不确定性。尽管近期研究已发现树木死亡现象普遍加剧，但与之相关的死亡模式与过程仍未得到充分阐释，这限制了树木死亡率的精准预测。然而，未来森林动态的预测高度依赖可靠的死亡率模型，这类模型最好基于实证数据构建，而非依赖理论层面且约束性不足的假设。我们针对欧洲山毛榉（Fagus sylvatica）单株树木构建了简约死亡率模型，并评估了其纳入动态植被模型（Dynamic Vegetation Models, DVMs）的可行性。我们使用了来自瑞士、德国与乌克兰无经营森林中近19000株树木的清查数据，这是迄今为止用于校准此类模型的最大规模数据集。我们以树木尺寸与生长状况——即胸径（dbh）和相对基面积增长量（relBAI）——为自变量，采用考虑复测间隔不均的广义逻辑回归对树木死亡事件进行建模。为阐释死亡模式的时空变异特征，我们纳入了大量环境与林分特征作为考量因素。我们通过独立数据集开展验证以评估模型的通用性。研究结果显示，山毛榉死亡率存在显著变异，且该变异与环境或林分特征无关。瑞士与德国严格森林保护区内的树木死亡模式以竞争过程为主导，表现为树木尺寸与生长量对应的死亡率呈J型分布。乌克兰原始山毛榉林则额外表现出以风倒干扰为主的特征，且其尺寸-死亡率函数呈U型分布。与基于乌克兰数据构建的死亡率模型不同，瑞士与德国的模型在互相验证时展现出良好的区分度与可接受的迁移性。因此我们建议将这两款模型纳入动态植被模型并开展进一步检验。其死亡率预测可通过树木生长响应气候变化，足以在当前环境下捕捉水分可获得性与竞争过程对山毛榉死亡概率的负面影响。