Tree mortality submodels drive simulated long‐term forest dynamics

A new study of dynamic vegetation models finds that tree mortality is one of the most uncertain processes when it comes to assessing forest response to climate change.

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Tree mortality models
Simulation of basal area (m2/ha) by the eight stand-scale models at the respective sites for 200 years into the future (with the exception of 4C, for which the simulation was ended in the year 2100 in all cases). “Moderate” climate change: change of annual mean temperature <3 °C. Photo: Giorgio Vacchiano

Models are pivotal for assessing future forest dynamics under the impacts of changing climate and management practices, incorporating representations of tree growth, mortality, and regeneration. Quantitative studies on the importance of mortality submodels are scarce. The study evaluates 15 dynamic vegetation models (DVMs) regarding their sensitivity to different formulations of tree mortality under different degrees of climate change.

The set of models comprised eight DVMs at the stand scale, three at the landscape scale, and four typically applied at the continental to global scale. Some incorporate empirically derived mortality models, and others are based on experimental data, whereas still others are based on theoretical reasoning. Each DVM was run with at least two alternative mortality submodels. Model behavior was evaluated against empirical time series data, and then, the models were subjected to different scenarios of climate change. Most DVMs matched empirical data quite well, irrespective of the mortality submodel that was used.

However, mortality submodels that performed in a very similar manner against past data often led to sharply different trajectories of forest dynamics under future climate change. Most DVMs featured high sensitivity to the mortality submodel, with deviations of basal area and stem numbers on the order of 10–40% per century under current climate and 20–170% under climate change. The sensitivity of a given DVM to scenarios of climate change, however, was typically lower by a factor of two to three.

Sensitivity index for basal area (left column, panels a & c) and stem numbers (right column, panels b & d) for the eight stand-scale models, extending over 200 simulation years. Note the logarithmic scale of the y- axis. The horizontal grey line indicates a sensitivity index of 0.1. Top row (a,b): sensitivity to mortality formulations under different scenarios of climate change. Bottom row (c,d): sensitivity to climate change using different mortality formulations.  Photo: Giorgio Vacchiano.

The study concludes that (1) mortality is one of the most uncertain processes when it comes to assessing forest response to climate change, and (2) more data and a better process understanding of tree mortality are needed to improve the robustness of simulated future forest dynamics. The research paper highlights that comparing several alternative mortality formulations in DVMs provides valuable insights into the effects of process uncertainties on simulated future forest dynamics. 

REFERENCED ARTICLE

Bugmann, H., Seidl, R., Hartig, F., Bohn, F., Brůna, J., Cailleret, M., François, L., Heinke, J., Henrot, A.‐J.,Hickler, T., Hülsmann, L., Huth, A., Jacquemin, I., Kollas, C., Lasch‐Born, P., Lexer, M. J., Merganič, J.,Merganičová, K., Mette, T., Miranda, B. R., Nadal‐Sala, D., Rammer, W., Rammig, A., Reineking, B., Roedig, E., Sabaté, S., Steinkamp, J., Suckow, F., Vacchiano, G., Wild, J., Xu, C., and Reyer, C. P. O.. 2019. Tree mortality submodels drive simulated long‐term forest dynamics: assessing 15 models from the stand to global scale. Ecosphere 10( 2):e02616.