The use of models to integrate information and understanding of soil C at the regional scale
The use of models to integrate information and understanding of soil C at the regional scale
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DOI：
10.1016/s0016-7061(97)00043-8
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发表时间：
1997-09
期刊：
影响因子：
6.1
通讯作者：
K. Paustian;E. Levine;W. M. Post;I. Ryzhova
中科院分区：
文献类型：
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作者：
K. Paustian;E. Levine;W. M. Post;I. Ryzhova
生态系统特性（包括土壤碳）的区域分析是一个快速发展的研究领域。区域分析用于量化现有土壤碳储量，预测土壤碳随土地利用模式变化的变化，并评估对气候变化的可能反应。此类分析所需的工具是模拟模型以及植被、土壤、地形、土地利用和气候的空间明确数据库。描述了区域分析的一般框架，该框架将模型与特定地点和空间解析的数据相结合。目前有两类模型用于区域尺度的分析：生态系统层面的模型，最初是为局部尺度的研究而设计的，以及为大陆和全球尺度的应用而开发的更聚合的“宏观尺度”模型。应用这两类模型的一个考虑因素是需要最小化与聚合信息相关的错误以应用于较粗的空间和时间尺度。对于模型输入数据，对于进入非线性模型函数的变量，例如土壤质地对有机物分解和水平衡的影响或分解生物的温度响应，聚合偏差最为严重。还需要考虑模型结构的聚合，特别是对于宏观模型。例如，仅用一两个池来表示枯枝落叶和土壤有机质可能适合表示平衡条件，但使用高度聚合模型的瞬态条件的变化率往往会被高估。来自实地调查的地理土壤数据是区域分析的关键组成部分。在土壤碳区域分析的背景下讨论了数据质量和土壤调查数据的解释问题。讨论了进一步开发数据和建模能力的领域，包括完善土壤碳图、开发土地利用和管理实践的空间数据库、在区域模型应用中使用遥感数据以及将陆地生态系统模型与全球气候模型联系起来。
Regional analysis of ecosystem properties, including soil C, is a rapidly developing area of research. Regional analyses are being used to quantify existing soil C stocks, predict changes in soil C as a function of changing landuse patterns, and assess possible responses to climate change. The tools necessary for such analyses are simulation models coupled with spatially-explicit databases of vegetation, soils, topography, landuse and climate. A general framework for regional analyses which integrates models with site-specific and spatially-resolved data is described. Two classes of models are currently being used for analyses at regional scales, ecosystem-level models, which were originally designed for local scale studies, and more aggregated “macro-scale” models developed for continental and global scale applications. A consideration in applying both classes of models is the need to minimize errors associated with aggregating information to apply to coarser spatial and temporal scales. For model input data, aggregation bias is most severe for variables which enter into non-linear model functions, such as soil textural effects on organic matter decomposition and water balance or the temperature response of decomposer organisms. Aggregation of model structure also needs to be considered, particularly for macro-scale models. For example, representations of litter and soil organic matter by only one or two pools may be suitable for representing equilibrium conditions but rates of change will tend to be overestimated for transient-state conditions using highly aggregated models. Geographic soils data, derived from field surveys, are a key component for regional analyses. Issues of data quality and interpretation of soil survey data are discussed in the context of regional analyses of soil C. Areas for further development of data and modeling capabilities, including refining soil C maps, developing spatial databases on landuse and management practices, using remotely sensed data in regional model applications, and linking terrestrial ecosystem models with global climate models, are discussed.