Yin Xiwei
Department of Forest Resources, University of Minnesota, Saint Paul, MN 55108, USA e-mail:
Oecologia. 1999 Oct;121(1):81-98. doi: 10.1007/s004420050909.
The decay rate of forest woody debris (WD) is a key missing link for a quantitative understanding of forest carbon dynamics and the global carbon budget. This paper reports an attempt to synthesize the available information into a unifying and testable numerical model pertinent to the analysis and projection of WD decay in field conditions. The model is rooted in an integrative theory that depicts decay as a process of substrate quality degradation along with feedback responses of microbial activity. It is parameterized through regression analysis against 112 data cases of stem and branch WD decay in North America, and then is evaluated against 132 additional data cases for stem and branch WD, and 75 data cases for root WD decay. The root mean square errors of both the fitted and the projected WD decay rates are about 14% of the means of respective data sets. Aided by peripheral algorithms, the model solves WD decay with data requirements limited to (1) tree species, and (2) air temperature and precipitation in January and July for forested sites, plus (3) latitude and elevation for deforested sites. The mathematical and physical implications of the model by its component functions and as a whole are generally supported by independent evidence from the literature where available. Those implications include: (1) the observed decay rate is lower when defined by density loss than by mass loss, when inferred from chronosequence survey than from population monitoring, or when estimated with specimens with end-coating than without coating; (2) the initial quality of WD differs between Abies/Picea and other species among conifers, or along the gradients of shade tolerance and normal stem slenderness among the deciduous trees; (3) the basic microbial growth rate (the rate at a WD quality of unity) increases with ambient temperature but decreases along the gradients of July precipitation-to-potential evapotranspiration ratio and January precipitation under forested conditions; and (4) WD decay may be accelerated or hampered after canopy removal, depending on local air humidity. The model further suggests that the lower of substrate quality and the basic microbial growth rate exerts a proportionally greater constraint on the decay rate, so the difference in WD decay by substrate and site narrows as the substrate quality degrades over time. Thus, a 2°C warming in air temperature would accelerate stem WD decay by 9-55% across the data sites for the 1st year, but only 1-14% by year 100.
森林木质残体(WD)的分解速率是定量理解森林碳动态和全球碳预算的关键缺失环节。本文报告了一项将现有信息综合成一个统一且可检验的数值模型的尝试,该模型适用于野外条件下WD分解的分析和预测。该模型基于一种综合理论,将分解描述为底物质量降解以及微生物活动反馈响应的过程。它通过对北美112个树干和树枝WD分解数据案例进行回归分析来进行参数化,然后针对另外132个树干和树枝WD数据案例以及75个树根WD分解数据案例进行评估。拟合和预测的WD分解速率的均方根误差约为各自数据集均值的14%。在周边算法的辅助下,该模型求解WD分解时的数据需求仅限于:(1)树种;(2)森林地区1月和7月的气温和降水量,以及(3)砍伐森林地区的纬度和海拔。该模型的组成函数及其整体的数学和物理意义在现有文献的独立证据中总体上得到了支持。这些意义包括:(1)当用密度损失定义时,观察到的分解速率低于用质量损失定义时;从年代序列调查推断时低于从种群监测推断时;用有末端涂层的标本估计时低于没有涂层的标本;(2)针叶树中冷杉/云杉与其他树种之间,或落叶树中耐荫性和正常树干细长度梯度上,WD的初始质量存在差异;(3)基本微生物生长速率(WD质量为1时的速率)随环境温度升高而增加,但在森林条件下沿7月降水量与潜在蒸散量之比和1月降水量梯度降低;(4)树冠去除后,WD分解可能会加速或受阻,这取决于当地空气湿度。该模型进一步表明,底物质量和基本微生物生长速率越低,对分解速率的限制作用就越大,因此随着底物质量随时间降解,不同底物和地点的WD分解差异会缩小。因此,气温升高2°C将使数据站点的树干WD分解在第1年加速9 - 55%,但到第100年仅加速1 - 14%。