The application of ecological stoichiometry to plant–microbial–soil organic matter transformations

分解者 生态化学计量学 生态系统 营养循环 生物地球化学 生态学 土壤有机质 环境科学 植物凋落物 陆地生态系统 生物地球化学循环 垃圾箱 土壤水分 食物网 土壤生物学 营养物 生物
作者
Sophie Zechmeister‐Boltenstern,Katharina Keiblinger,Maria Mooshammer,Josep Peñuelas,Andreas Richter,Jordi Sardans,Wolfgang Wanek
出处
期刊:Ecological Monographs [Wiley]
卷期号:85 (2): 133-155 被引量:1134
标识
DOI:10.1890/14-0777.1
摘要

Elemental stoichiometry constitutes an inherent link between biogeochemistry and the structure and processes within food webs, and thus is at the core of ecosystem functioning. Stoichiometry allows for spanning different levels of biological organization, from cellular metabolism to ecosystem structure and nutrient cycling, and is therefore particularly useful for establishing links between different ecosystem compartments. We review elemental carbon : nitrogen : phosphorus (C:N:P) ratios in terrestrial ecosystems (from vegetation, leaf litter, woody debris, and dead roots, to soil microbes and organic matter). While the stoichiometry of the plant, litter, and soil compartments of ecosystems is well understood, heterotrophic microbial communities, which dominate the soil food web and drive nutrient cycling, have received increasing interest in recent years. This review highlights the effects of resource stoichiometry on soil microorganisms and decomposition, specifically on the structure and function of heterotrophic microbial communities and suggests several general patterns. First, latitudinal gradients of soil and litter stoichiometry are reflected in microbial community structure and function. Second, resource stoichiometry may cause changes in microbial interactions and community dynamics that lead to feedbacks in nutrient availability. Third, global change alters the C:N, C:P, and N:P ratios of primary producers, with repercussions for microbial decomposer communities and critical ecosystem services such as soil fertility. We argue that ecological stoichiometry provides a framework to analyze and predict such global change effects at various scales.
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