| Abstrakt: |
Dynamic forest models are a key tool to better understand, assess, and project decadal‐ to centennial‐scale forest dynamics. Despite their success, many questions regarding appropriate model formulations remain unresolved, and few models have found widespread application, for example, across a whole continent. We aimed to scrutinize the representation of ecological processes in dynamic forest models so as to rigorously test core assumptions underlying forest dynamics and the consistency of their interplay, taking the ForClim model as a case study. We developed a set of alternative representations for the main ecological processes, that is, tree establishment, growth, and mortality, and light extinction through the canopy, based on diverse sources of empirical data. We applied a pattern‐oriented modeling (POM) approach to test all combinations of the standard and alternative formulations (>500 model versions) against a comprehensive set of patterns for diverse model applications across a wide range of site conditions. We found that adapting one process in isolation can improve model performance for one specific application. However, the best model versions typically included more than one alternative formulation. Importantly, the best version for an individual application was generally not the best across multiple applications, emphasizing the varying influences of ecological processes. We conclude that the behavior and performance of complex models should not be analyzed for a few specific applications only. Rather, multiple applications, system states, and dynamics of interest should be scrutinized across a wide range of site conditions. This allows for avoiding overfitting and detecting and eliminating structural shortcomings and parameterization problems. We thus propose to make use of the ever‐increasing data availability and the POM framework to challenge the core processes of dynamic models in a holistic manner. For model applications, we propose that a set of alternative formulations (ensemble simulations) should be used to quantify the impacts of structural uncertainty, rather than to rely on the projections from one single model version. [ABSTRACT FROM AUTHOR] |
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