Projecting the dynamics of managed forests over the coming few decades under strongly changing management and climatic drivers is a considerable challenge. In the past 20-30 years, dynamic forest growth models have increasingly been used to simulate the development of managed forests, whereas forest gap models have been used since nearly 40 years to study the dynamics of (mostly) unmanaged forests.
In our group there is significant experience with evaluating and using forest growth models, and with the development, evaluation and use of forest gap models. Over the past few years, we were working on increasing the local accuracy of the forest gap model ForClim, which led to a less general applicability of the model at other sites. In the last year, we have however made significant progress towards further increasing the local accuracy of the model while at the same time regaining the general applicability (along a strong gradient of temperature and precipitation in Europe) of the previous model versions. The latest version of ForClim, V2.9.6, appears to have a local accuracy that is at least as high as that of modern forest growth models.
The ultimate objective of this particular project is to simulate the anticipated future development of selected forest stands under varying scenarios of management and climatic change, with the aim of identifying suitable adaptation strategies. To this end, a forest management submodel was recently implemented in the gap model ForClim, which will now be subjected to further, rigorous tests against long-term data from forest trials. Possible model failures will thusly be detected and the formulation of those parts of the model that are found to be insufficient will be improved. Other forest trial data will then be used for a systematic model validation before model application.
The project is embedded in the Cost Action FP0603 and is financed by the Swiss State Secretariat for Education and Research. The goal of the Cost Action is to optimize established forest growth models for the use as decision support tools in forestry on stand level. Special emphasis is put on their ability to correctly and realistically simulate multifunctional sustainable forest management and adaptive management under climatic change. It is also a goal to promote user friendliness in forest growth models, so that they may in future also be used outside of science.
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