Abstract

Abstract Advances in dynamic ecosystem modelling have made a number of different approaches to vegetation dynamics possible. Here we compare two models representing contrasting degrees of abstraction of the processes governing dynamics in real vegetation. Model (a) (GUESS) simulates explicitly growth and competition among individual plants. Differences in crown structure (height, depth, area and LAI) influence relative light uptake by neighbours. Assimilated carbon is allocated individually by each plant to its leaf, fine root and sapwood tissues. Carbon allocation and turnover of sapwood to heartwood in turn govern height and diameter growth. Model (b) (LPJ) incorporates a ‘dynamic global vegetation model’ (DGVM) architecture, simulating growth of populations of plant functional types (PFTs) over a grid cell, integrating individual‐level processes over the proportional area (foliar projective cover, FPC) occupied by each PFT. Individual plants are not simulated, but are replaced by explicit parameterizations of their growth and interactions. The models are identical in their representation of core physiological and biogeochemical processes. Both also use the same set of PFTs, corresponding to the major woody plant groups in Europe, plus a grass type. When applied at a range of locations, broadly spanning climatic variation within Europe, both models successfully predicted PFT composition and succession within modern natural vegetation. However, the individual‐based model performed better in areas where deciduous and evergreen types coincide, and in areas subject to pronounced seasonal water deficits, which would tend to favour grasses over drought‐intolerant trees. Differences in model performance could be traced to their treatment of individual‐level processes, in particular light competition and stress‐induced mortality. Our results suggest that an explicit individual‐based approach to vegetation dynamics may be an advantage in modelling of ecosystem structure and function at the resolution required for regional‐ to continental‐scale studies.

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