Comparing and evaluating process‐based ecosystem model predictions of carbon and water fluxes in major European forest biomes - Pablo Morales; Martin T. Sykes; I. Colin Prentice; Pete Smith; Benjamin Smith; Harald Bugmann; Bärbel Zierl; Pierre Friedlingstein; Nicolas Viovy; Santi Sabaté; Anabel Sánchez; Eduard Pla; et al. (Global Change Biology, 2005)
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 h ). 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.