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首页> 外文期刊>Journal of Forestry Research >Review on the decomposition and influence factors of coarse woody debris in forest ecosystem
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Review on the decomposition and influence factors of coarse woody debris in forest ecosystem

机译:森林生态系统中粗木屑的分解及其影响因素研究进展

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摘要

Coarse woody debris (CWD) is an important and particular component of forest ecosystems and is extremely important to forest health. This review describes the decomposition process, decomposition model and influence factors. CWD decomposition is a complex and continuous process and characterizes many biological and physical processes, including biological respiration, leaching, and fragmentation. All these processes have closed relationships between each other and work synergistically. During decomposition, there are many controlling factors mainly including site conditions (temperature, humidity, and O_2/CO_2 concentration), woody substrate quality (diameter, species and compound) and organism in CWD. The decomposition rate is genp rally expresses through a constant k which indicate the percent mass, volume or density loss over time, and can be determined by long-term monitoring, chronosequence approach and the radio between input and the total mass. Now using mathematical models to simulate decomposition patterns and estimate the decomposition rate is widely applied, especially the exponential model. We brought forward that managing and utilizing for the CWD in forest was a primary objective on all forest lands. And it is should be intensified to integrate many related research subjects and to carry a comprehensive, long-term and multi-scale research which mainly focus on seven sections.
机译:粗大的木屑(CWD)是森林生态系统的重要组成部分,对森林健康极为重要。这篇综述描述了分解过程,分解模型和影响因素。 CWD分解是一个复杂而连续的过程,具有许多生物和物理过程的特征,包括生物呼吸,浸出和破碎。所有这些过程之间有着紧密的联系,并且可以协同工作。在分解过程中,有许多控制因素,主要包括场地条件(温度,湿度和O_2 / CO_2浓度),木质底物质量(直径,种类和化合物)和CWD中的生物。分解速率通常由常数k表示,常数k表示质量,体积或密度随时间损失的百分比,可以通过长期监控,时间序列方法以及输入与总质量之间的无线电来确定。现在使用数学模型来模拟分解模式并估计分解速率已被广泛应用,尤其是指数模型。我们提出,在森林中对CWD进行管理和利用是所有林地的主要目标。应加强对许多相关研究主题的整合,并进行以七部分为主的全面,长期,多尺度的研究。

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