土壤碳
生物量(生态学)
环境科学
土壤科学
环境化学
土壤水分
限制
生态学
饱和(图论)
化学
生物
数学
机械工程
组合数学
工程类
作者
Matthew E. Craig,Melanie A. Mayes,Benjamin N. Sulman,Anthony P. Walker
摘要
Abstract Increasing soil organic carbon (SOC) storage is a key strategy to mitigate rising atmospheric CO 2 , yet SOC pools often appear to saturate, or increase at a declining rate, as carbon (C) inputs increase. Soil C saturation is commonly hypothesized to result from the finite amount of reactive mineral surface area available for retaining SOC, and is accordingly represented in SOC models as a physicochemically determined SOC upper limit. However, mineral‐associated SOC is largely microbially generated. In this perspective, we present the hypothesis that apparent SOC saturation patterns could emerge as a result of ecological constraints on microbial biomass—for example, via competition or predation—leading to reduced C flow through microbes and a reduced rate of mineral‐associated SOC formation as soil C inputs increase. Microbially explicit SOC models offer an opportunity to explore this hypothesis, yet most of these models predict linear microbial biomass increases with C inputs and insensitivity of SOC to input rates. Synthesis of 54 C addition studies revealed constraints on microbial biomass as C inputs increase. Different hypotheses limiting microbial density were embedded in a three‐pool SOC model without explicit limits on mineral surface area. As inputs increased, the model demonstrated either no change, linear, or apparently saturating increases in mineral‐associated and particulate SOC pools. Taken together, our results suggest that microbial constraints are common and could lead to reduced mineral‐associated SOC formation as input rates increase. We conclude that SOC responses to altered C inputs—or any environmental change—are influenced by the ecological factors that limit microbial populations, allowing for a wider range of potential SOC responses to stimuli. Understanding how biotic versus abiotic factors contribute to these patterns will better enable us to predict and manage soil C dynamics.
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