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Explicit avalanche-forest feedback simulations improve the performance of a coupled avalanche-forest model

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Zurbriggen, N., Nabel, J. E. M. S., Teich, M., Bebi, P., & Lischke, H. (2014). Explicit avalanche-forest feedback simulations improve the performance of a coupled avalanche-forest model. Ecological Complexity, 17, 56-66. doi:10.1016/j.ecocom.2013.09.002.

Cite as: https://hdl.handle.net/11858/00-001M-0000-0028-1382-F
Many temperate and boreal mountain landscapes are strongly affected by snow avalanches. Forests can reduce avalanche release probability, leading to a positive feedback between forests and avalanches. The effects of this feedback, especially when influenced by changing environmental conditions, make the projection of the future developments of mountain forests and avalanches challenging. In order to study this feedback under a wide range of environmental situations, we coupled a forest landscape model with a new probabilistic avalanche module. The coupled model TREEMIG-AVAL allows yearly spatially explicit simulations of climatically driven forest dynamics, with species-specific growth, mortality, and reproduction. Simulated spatially explicit avalanche release is driven by climate, topography, forest type and density. These factors, together with additional factors increasing tree mortality, influence the strength of the positive feedback between forests and avalanches. We investigated (a) the influences of the three environmental factors temperature, slope steepness, and additional mortality on the simulated dynamics of mountain forests and avalanches, (b) the plausibility of TREEMIG-AVAL, and (c) whether the complexity of TREEMIG-AVAL could be reduced. The sensitivity of avalanche release probability to environmental changes was thus compared between TREEMIG-AVAL and two simplified model versions. The three environmental drivers had strong and often nonlinear influences on the simulated forest and avalanche dynamics. The simulated avalanche release probability showed linear to sigmoidal decreases with temperature, a peak-shaped response to slope steepness, and steep sigmoidal increases with additional mortality. However, these response shapes of avalanche release probability to each environmental factor changed along the axes of the two other factors studied. These interactions suggest that future mountain forest simulation studies should explicitly account for the influence of environmental drivers on the avalanche-forest feedback. The simulations showed that the behavior of TREEMIG-AVAL is plausible and comparable to expert knowledge and previously published literature. Moreover, large differences in the sensitivity of the avalanche release probability to the environmental factors were apparent between TREEMIG-AVAL and the simplified model versions, revealing that for plausible simulations of avalanche-prone mountain regions it is necessary to explicitly account for the avalanche-forest feedback in TREEMIG-AVAL. In particular the simulated treeline was sensitive to changes in model structure and prone to underestimation of the avalanche release probability in the simplified model versions. When the feedback is explicitly accounted for, TREEMIG-AVAL is a useful tool for simulation studies of mountain forests including spatially explicit disturbances. (C) 2013 Elsevier B.V. All rights reserved.