A parsimonious modular approach to building a mechanistic belowground carbon and nitrogen model

被引:38
作者
Abramoff, Rose Z. [1 ,2 ,3 ]
Davidson, Eric A. [4 ]
Finzi, Adrien C. [1 ,2 ]
机构
[1] Boston Univ, Dept Biol, 5 Cummington St, Boston, MA 02215 USA
[2] Boston Univ, PhD Program Biogeosci, Boston, MA 02215 USA
[3] Lawrence Berkeley Natl Lab, Climate & Ecosyst Sci Div, Climate Sci Dept, Berkeley, CA USA
[4] Univ Maryland, Appalachian Lab, Ctr Environm Sci, Frostburg, MD USA
基金
美国国家科学基金会;
关键词
microbial modeling; soil decomposition; microbial physiology; stoichiometry; C efflux; heterotrophic respiration; SOIL ORGANIC-MATTER; MICHAELIS-MENTEN KINETICS; EARTH SYSTEM MODELS; N-P STOICHIOMETRY; TEMPERATE FORESTS; THEORETICAL-MODEL; MICROBIAL PHYSIOLOGY; SENSITIVITY-ANALYSIS; LITTER MANIPULATION; CLIMATE-CHANGE;
D O I
10.1002/2017JG003796
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Soil decomposition models range from simple empirical functions to those that represent physical, chemical, and biological processes. Here we develop a parsimonious, modular C and N cycle model, the Dual Arrhenius Michaelis-Menten-Microbial Carbon and Nitrogen Phyisology (DAMM-MCNiP), that generates testable hypotheses regarding the effect of temperature, moisture, and substrate supply on C and N cycling. We compared this model to DAMM alone and an empirical model of heterotrophic respiration based on Harvard Forest data. We show that while different model structures explain similar amounts of variation in respiration, they differ in their ability to infer processes that affect C flux. We applied DAMM-MCNiP to explain an observed seasonal hysteresis in the relationship between respiration and temperature and show using an exudation simulation that the strength of the priming effect depended on the stoichiometry of the inputs. Low C:N inputs stimulated priming of soil organic matter decomposition, but high C:N inputs were preferentially utilized by microbes as a C source with limited priming. The simplicity of DAMM-MCNiP's simultaneous representations of temperature, moisture, substrate supply, enzyme activity, and microbial growth processes is unique among microbial physiology models and is sufficiently parsimonious that it could be incorporated into larger-scale models of C and N cycling. Plain Language Summary Microorganisms that grow in the soil, like bacteria and fungi, affect how much carbon resides in the soil and how much is released to the atmosphere as CO2. Mathematical models used to make climate change predictions often struggle to capture the activity of soil microbes in realistic ways. This study uses well-established descriptions of water and temperature effects on soil microbes to predict rate of carbon and nitrogen cycling in the soil. Our new model reproduces the changing relationship between temperature and microbial respiration during the growing season. We also show using a theoretical addition of root secretions that the microbial response depends on the nitrogen content of the added plant material. This model is simple and based on well defined physical and biological properties, and could be developed to model microbial activity at larger scales.
引用
收藏
页码:2418 / 2434
页数:17
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