生物地球化学的概念与方法──DNDC模型的发展

BIOGEOCHEMICAL CONCEPTS AND METHODOLOGIES: DEVELOPMENT OF THT DNDC MODEL

生物地球化学作为一个学科包含４个概念，即生物地球化学量、流、群和场。这４个概念从不同角度描述了生命与其环境的关系。生物地球化学量探索生命及其无机环境在元素丰度上的相似性，这种相似性决定了生命体对环境化学状态的依赖性。生物地球化学流描写化学元素在生态系统中的迁移，此迁移导致了生命体与环境间的物质和能量交换。生物地球化学群描述化学元素在迁移转化时的复杂组合关系及其生物效应。生物地球化学场是生态系统中控制生物地球化学反应的各种环境营力的总和。生物地球化学模型即是这一综合力场及其对化学元素迁移转化影响的数学描述，ＤＮＤＣ模型即基于这些概念发展起来。ＤＮＤＣ模型可用来预测陆地生态系统中碳和氮的生物地球化学行为，该模型已被一些国家用来预测农业土壤的长期肥力和温室气体排放。

Biogeochendstry, as a scientific discipline, consists of four concepts. They are biogeochemical abundance, flow, coupling and field. The four concepts interpret relationships between life and its environment but from different angles. Biogeochemical abundance explores the correlation between life and its inorganic environment (e.g., earth's crust soil, sea water etc.) in their elementary abundance, which may originate from life's evolution and determines current life's dependence on the environmental chemical status. Biogeochemical flow describes transport of chemical elements between life and its environment through which they form an interacting entity by exchanging matter and energy. Sometimes we call the elementary flow as biogeochemical cycle when the flow closes within a meaningful time span. Biogeochemical coupling answers why the chemical elements act in couple or group during their transport and transformation in ecosystems. Biogeochemical field is an assembly of the environmental forces, which determine directions and rates of all relevant biogeochemical reactions. Biogeochemical model is a mathematical expression of the forces and their effects on the elementary abundance, flow and coupling. To predict carbon (C) and nitrogen (N) biogeochemistry in terrestrial ecosystems, we developed a model, DNDC, by integrating the biogeochemical concepts into a computing framework. DNDC consists of two components for predicting effects of basic ecological drivers (e.g., climate, soil, vegetation and anthropogenic activity) on environmental factors (e.g., radiation, temperature, moisture, Eh, pH and substrate concentration gradient), and effects of the environmental factors on nitrification, denitrification and fermentation in the simulated ecosystems, respectively. Trough validations against dozens of data sets measured in cropland, grassland and forests worldwide, DNDC has demonstrated its ability in predicting C and N cycles as well as greenhouse gas emissions in a wide range of terrestrial ecosystems. DNDC has been linked to GIS databases and remote sensing din sets to scale up C and N predictions for large regions such as total croplands in the U. S. and China.