凋落物分解主场效应及其土壤生物驱动

凋落物分解主场效应是指凋落物具有在其生长的栖息地比在别的生境分解更快的特征,土壤生物的特化作用被认为是主场效应的产生机理.主场效应是除基质质量和物理化学环境外控制凋落物分解的重要因子,可影响模拟精度的8％.凋落物分解主场效应驱动机制的深入研究对促进分解模型中纳入生物因子,提高区域尺度模拟精度具有重要作用.虽然时间和基质质量可导致主场效应强度变化,但不能全面解释主场效应强度差异特别是负效应的产生.通过分析凋落物分解过程中土壤生物的作用机理,指出凋落物分解主场效应的土壤生物驱动可能包括土壤微生物的调节性适应,土壤动物的后期插入以及物理化学环境的间接影响.为深入了解主场效应土壤生物驱动机制,更好地模拟凋落物分解过程,提出延长凋落物分解交互移置实验时间,拓展实验空间,结合室内模拟分析和构建分解模型等方法与途径.

Home-field advantage of litter decomposition and its soil biological driving mechanism: a review

Decomposition has been studied for decades due to its significance in understanding nutrient cycling and carbon sequestration processes. The current study identified the three interacting factors that control decomposion: the physicochemical environment, litter quality, and decomposer organisms. Exsiting biogeochemical models that that are derived by local cliamte and little quality parameters can explain about 70% of the variation in litter decomposition. However, the role of soil organisms has been largely ignored in these models that assume the functions of soil organisms are mainly controlled by temperature, moisture and litter quality. Recent studies suggest that leaf litters tend to decompose more rapidly in the habitat from which it was derived (i.e. home) than in other habitats (i.e. new home away from its origion), this phenomena has been termed as the home-field advantage (HFA ) in litter decomposition. In contrast to plant growth, leaf litter-soil feedbacks are expected to consistently cause positive feedback at a home habitat resulting in faster litter decay. This is because 1) leaf litter from different plant species often varies considerably in structure and chemical composition; and 2) leaf litter inputs are a major source of nutrients and energy for soil biota that access decomposed litter. Thus, competition among soil biota for accessing nutrients may create a selective pressure for organisms that are efficient at breaking down litter derived locally resulting in HFA.. Unique soil biota developed in the litter derived from the orgional ecosystem has been regarded as the reason for this phenomenon. quantifying HFA is more complex than a simply comparison between the decomposition rates for a litter type at its home site and an away site, because differences in environmental contitions between the sites could also influence decomposition. The method originally developed for evaluating home-site effects in sports allows the HFA to be calculated for each of the litters separately in fully reciprocal transplants experiment of three or more litter species. Existing literature suggests there is a large amount of variation in HFA among reciprocal transplants between different tree species. Differences in litter traits could explain some of these variations, but it is apparent that other factors influence the relationship given the initially large HFA observed in field and laboratory experiments, as well as periods of home-field disadvantage. Thus we need a better understanding of the drivers of HFA and how soil biota are involved in order to address this potential problem in how we model decomposition. Based on the review about the rules of soil organisms on litter decompositon, three mechanisms are considered to reveal the soil biological drive of HFA: soil microorganism adjustability has a weakening effect on the HFA, soil animals' late entry can lead to different HFA intensity, including a disadvantage of home decomposition, environmental climatic conditions have indirect effects on HFA, especially under soil water stress.Integrating these using an ecosystem approach helps to elucidate the effects of soil organism on the HFA of litter decomposition, and interpret the causes of different intensity, especially negative effect of HFA. In order to clearly understand the effects of soil organisms on HFA, long term reciprocal litter transplant experiments, including in-situ and laboratory, should be established across a large geographic and climatic gradient. Based on the effects of soil organisms on HFA, mathematical models of litter decomposition should incorporate with biological factors. This is especially important for global ecosystems that are used for understaing climate change effects on carbon and nutrient cycles.