Forests are an important component of the global carbon (C) cycle and can be net sources or sinks of CO2, thus mitigating or exacerbating the effects of anthropogenic greenhouse gas emissions. While forest productivity is often inferred from national-scale yield tables or from satellite products, forest C emissions resulting from dead organic matter decay are usually simulated, therefore it is important to ensure the accuracy and reliability of a model used to simulate organic matter decay at an appropriate scale. National Forest Inventories (NFIs) provide a record of carbon pools in ecosystem components, and these measurements are essential for evaluating rates and controls of C dynamics in forest ecosystems. In this study we combine the observations from the Swiss NFIs and machine learning techniques to quantify the decay rates of the standing snags and downed logs and identify the main controls of dead wood decay. We found that wood decay rate was affected by tree species, temperature, and precipitation. Dead wood originating from Fagus sylvatica decayed the fastest, with the residence times ranging from 27 to 54 years at the warmest and coldest Swiss sites, respectively. Hardwoods at wetter sites tended to decompose faster compared to hardwoods at drier sites, with residence times 45–92 and 62–95 years for the wetter and drier sites, respectively. Dead wood originating from softwood species had the longest residence times ranging from 58 to 191 years at wetter sites and from 78 to 286 years at drier sites. This study illustrates how long-term dead wood observations collected and remeasured during several NFI campaigns can be used to estimate dead wood decay parameters, as well as gain understanding about controls of dead wood dynamics. The wood decay parameters quantified in this study can be used in carbon budget models to simulate the decay dynamics of dead wood, however more measurements (e.g. of soil C dynamics at the same plots) are needed to estimate what fraction of dead wood is converted to CO2, and what fraction is incorporated into soil.

中文翻译：

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瑞士森林中枯木腐烂的动态

森林是全球碳（C）循环的重要组成部分，可以是CO2的净源或汇，从而减轻或加剧了人为温室气体排放的影响。虽然通常从国家级产量表或卫星产品推断森林生产力，但通常模拟死有机物质腐烂产生的森林碳排放，因此，重要的是确保用于模拟有机物质腐烂的模型的准确性和可靠性。适当的规模。国家森林清单（NFI）提供了生态系统组件中碳库的记录，这些测量对于评估森林生态系统中碳动态的速率和控制至关重要。在这项研究中，我们结合了来自瑞士NFI的观察结果和机器学习技术，以量化站立断枝和被砍伐原木的腐烂率，并确定死木腐烂的主要控制因素。我们发现木材腐烂率受树木种类，温度和降水量的影响。来自瑞士青冈（Fagus sylvatica）的枯木腐烂最快，在最热和最冷的瑞士地点的滞留时间分别为27至54年。与较干燥地点的硬木相比，较湿地点的硬木易于分解，较湿地点和较干燥地点的停留时间分别为45-92年和62-95年。源自软木树种的死木在湿润地点的停留时间最长，从58到191年不等，而在干燥地点则为78至286年。这项研究说明了如何在几次NFI活动中收集并重新测量的长期死木观测值可用于估计死木衰减参数，以及获得对死木动力学控制的了解。这项研究中量化的木材腐烂参数可用于碳预算模型中，以模拟枯木的腐烂动力学，但是需要更多的测量（例如，在同一块土地上的土壤C动力学）来估算将枯木转化成多少比例的枯木。二氧化碳，以及将什么比例掺入土壤。