Improving the formulation of tree growth and succession in a spatially explicit landscape model

Long-term forest landscape dynamics are determined by a set of driving forces including large-scale natural disturbances, land-use, the physical environment, and stand-scale succession processes. Landscape models have an important role as tools for synthesizing existing information and making projections of possible future vegetation dynamics on large spatial scales. However, current landscape models cannot readily be used to study: (1) the change from weakly to strongly disturbed landscapes; (2) the impact of changing climatic parameters on landscape-scale dynamics; and (3) the effects of such changes on vegetation structure. Using European mountain forests as a case study, this paper focuses on improving the well-established LANDIS landscape model so that it can be applied to study these research questions.We integrated a simple tree succession sub-model in LANDIS, which incorporates quantitative descriptions of forest structure, and included sub-models to capture the influences of competition as well as climatic and edaphic parameters on tree population dynamics.The new model was subjected to a number of quantitative tests against measured data. It accurately predicted the altitudinal distribution of vegetation properties under managed as well as unmanaged conditions in the Dischma valley (Switzerland), and it provided realistic and accurate patterns of vegetation recovery following wind disturbance events, in spite of the very simple model formulations.To demonstrate the utility of the added detail, we applied the model in scenario mode under a range of changes in climatic and disturbance parameters, assuming a continuation of the current management regime. The simulations showed that the various driving forces have quite different effects on different species, and that their combined effect differs from one scenario to the next. Notably, there are few models that integrate forest growth and succession with disturbance dynamics in a semi-mechanistic manner. Our version of LANDIS achieves this integration based on simple concepts and methods that do not require many parameter estimates. We conclude that the new model has the potential to provide an integrated picture of the impacts of both direct and indirect effects of climate change on forest landscape dynamics.