INIA, CSIC, Madrid, Spain.
Glob Chang Biol. 2022 Jul;28(14):4342-4358. doi: 10.1111/gcb.16172. Epub 2022 Apr 13.
Forest disturbances such as drought, fire, and logging affect the forest carbon dynamics and the terrestrial carbon sink. Forest mortality after disturbances creates uncertainties that need to be accounted for to understand forest dynamics and their associated C-sink. We combined data from permanent resampling plots and biomass oriented dendroecological plots to estimate time series of annual woody biomass growth (ABI) in several forests. ABI time series were used to benchmark a vegetation model to analyze dynamics in forest productivity and carbon allocation forced by environmental variability. The model implements source and sink limitations explicitly by dynamically constraining carbon allocation of assimilated photosynthates as a function of temperature and moisture. Bias in tree-ring reconstructed ABI increased back in time from data collection and with increasing disturbance intensity. ABI bias ranged from zero, in open stands without recorded mortality, to over 100% in stands with major disturbances such as thinning or snowstorms. Stand leaf area was still lower than in control plots decades after heavy thinning. Disturbances, species life-history strategy and climatic variability affected carbon-partitioning patterns in trees. Resprouting broadleaves reached maximum biomass growth at earlier ages than nonresprouting conifers. Environmental variability and leaf area explained much variability in woody biomass allocation. Effects of stand competition on C-allocation were mediated by changes in stand leaf area except after major disturbances. Divergence between tree-ring estimated and simulated ABI were caused by unaccounted changes in allocation or misrepresentation of some functional process independently of the model calibration approach. Higher disturbance intensity produced greater modifications of the C-allocation pattern, increasing error in reconstructed biomass dynamics. Legacy effects from disturbances decreased model performance and reduce the potential use of ABI as a proxy to net primary productivity. Trait-based dynamics of C-allocation in response to environmental variability need to be refined in vegetation models.
森林干扰,如干旱、火灾和采伐,会影响森林碳动态和陆地碳汇。干扰后的森林死亡率会产生不确定性,需要加以考虑,以了解森林动态及其相关的碳汇。我们结合了永久性重采样样地和生物质导向的树木年代学样地的数据,以估算几个森林的年度木质生物量生长(ABI)时间序列。ABI 时间序列用于基准植被模型,以分析环境变异性强制下的森林生产力和碳分配动态。该模型通过动态地将同化的光合产物的碳分配作为温度和水分的函数来限制源和汇,从而明确地实现源和汇的限制。树木年轮重建的 ABI 偏差随着时间的推移从数据收集开始增加,并随着干扰强度的增加而增加。ABI 偏差的范围从零(在没有记录死亡率的开阔林分中)到 100%以上(在经历过严重干扰的林分中,如疏伐或暴风雪)。重度疏伐后几十年,林分的叶面积仍低于对照样地。干扰、物种生活史策略和气候变异性影响了树木的碳分配模式。萌生阔叶树种在比非萌生针叶树种更早的年龄达到最大生物量生长。环境变异性和叶面积解释了木质生物量分配的很大变异性。除了在重大干扰之后,林分竞争对 C 分配的影响是通过林分叶面积的变化来调节的。树木年轮估计和模拟 ABI 之间的差异是由分配中未被考虑到的变化或某些功能过程的错误表示引起的,而与模型校准方法无关。较高的干扰强度会导致 C 分配模式发生更大的变化,从而增加重建生物量动态的误差。干扰的遗留效应会降低模型性能,并降低将 ABI 作为净初级生产力代理的潜在用途。需要在植被模型中进一步完善对环境变异性的 C 分配的基于特征的动态。