Morales Pablo, Sykes Martin T, Prentice I Colin, Smith Pete, Smith Benjamin, Bugmann Harald, Zierl Bärbel, Friedlingstein Pierre, Viovy Nicolas, Sabaté Santi, Sánchez Anabel, Pla Eduard, Gracia Carlos A, Sitch Stephen, Arneth Almut, Ogee Jerome
Centre for Geobiosphere Science, Department of Physical Geography and Ecosystems Analysis, Lund University, Sölvegatan 12, S-223 62 Lund, Sweden.
Department of Earth Sciences, University of Bristol, Wills Memorial Building, Queen's Road, Bristol BS8 1RJ, UK.
Glob Chang Biol. 2005 Dec;11(12):2211-2233. doi: 10.1111/j.1365-2486.2005.01036.x. Epub 2005 Oct 27.
Process-based models can be classified into: (a) terrestrial biogeochemical models (TBMs), which simulate fluxes of carbon, water and nitrogen coupled within terrestrial ecosystems, and (b) dynamic global vegetation models (DGVMs), which further couple these processes interactively with changes in slow ecosystem processes depending on resource competition, establishment, growth and mortality of different vegetation types. In this study, four models - RHESSys, GOTILWA+, LPJ-GUESS and ORCHIDEE - representing both modelling approaches were compared and evaluated against benchmarks provided by eddy-covariance measurements of carbon and water fluxes at 15 forest sites within the EUROFLUX project. Overall, model-measurement agreement varied greatly among sites. Both modelling approaches have somewhat different strengths, but there was no model among those tested that universally performed well on the two variables evaluated. Small biases and errors suggest that ORCHIDEE and GOTILWA+ performed better in simulating carbon fluxes while LPJ-GUESS and RHESSys did a better job in simulating water fluxes. In general, the models can be considered as useful tools for studies of climate change impacts on carbon and water cycling in forests. However, the various sources of variation among models simulations and between models simulations and observed data described in this study place some constraints on the results and to some extent reduce their reliability. For example, at most sites in the Mediterranean region all models generally performed poorly most likely because of problems in the representation of water stress effects on both carbon uptake by photosynthesis and carbon release by heterotrophic respiration (R ). The use of flux data as a means of assessing key processes in models of this type is an important approach to improving model performance. Our results show that the models have value but that further model development is necessary with regard to the representation of the some of the key ecosystem processes.
(a) 陆地生物地球化学模型（TBMs），用于模拟陆地生态系统中碳、水和氮的通量耦合；(b) 动态全球植被模型（DGVMs），该模型进一步将这些过程与取决于不同植被类型的资源竞争、建立、生长和死亡率的缓慢生态系统过程变化进行交互耦合。在本研究中，对代表这两种建模方法的四个模型——RHESSys、GOTILWA+、LPJ-GUESS和ORCHIDEE——进行了比较，并根据欧洲通量项目中15个森林站点的碳通量和水通量涡度协方差测量提供的基准进行了评估。总体而言，模型与测量值之间的一致性在不同站点间差异很大。两种建模方法各有不同优势，但在所测试的模型中，没有一个在评估的两个变量上普遍表现良好。小偏差和误差表明，ORCHIDEE和GOTILWA+在模拟碳通量方面表现更好，而LPJ-GUESS和RHESSys在模拟水通量方面表现更佳。一般来说，这些模型可被视为研究气候变化对森林碳循环和水循环影响的有用工具。然而，本研究中描述的模型模拟之间以及模型模拟与观测数据之间的各种变化来源对结果施加了一些限制，并在一定程度上降低了其可靠性。例如，在地中海地区的大多数站点，所有模型通常表现不佳，这很可能是由于水分胁迫对光合作用碳吸收和异养呼吸（R）碳释放的影响表示存在问题。使用通量数据作为评估此类模型关键过程的一种手段是提高模型性能的重要方法。我们的结果表明，这些模型具有价值，但在一些关键生态系统过程的表示方面，进一步的模型开发是必要的。
