Preprints
https://doi.org/10.5194/gmd-2022-268
https://doi.org/10.5194/gmd-2022-268
Submitted as: model evaluation paper
23 Nov 2022
Submitted as: model evaluation paper | 23 Nov 2022
Status: this preprint is currently under review for the journal GMD.

Validation of a new spatially-explicit process-based model (HETEROFOR) to simulate structurally and compositionally complex stands in eastern North-America

Arthur Guignabert1, Quentin Ponette1, Frédéric André1, Christian Messier2,3, Philippe Nolet2,3, and Mathieu Jonard1 Arthur Guignabert et al.
  • 1Earth and Life Institute, Université catholique de Louvain, Louvain-la-Neuve, Belgium
  • 2Centre d'Étude de la Forêt, Université du Québec à Montréal, Montréal, QC, Canada
  • 3Institut des Sciences de la Forêt Tempérée, Université du Québec en Outaouais, Ripon, QC, Canada

Abstract. Process-based forest growth models with spatially explicit representation are a relevant tool to investigate innovative silviculture practices and/or climate change effects because they are based on key ecophysiological processes and account for the effects of local competition for resources on tree growth. Such models are rare, often calibrated for a very limited number of species and rarely in mixed and/or uneven-aged stands, and none are suitable for the temperate forests of Québec. The aim of this study was to calibrate and evaluate HETEROFOR, a process-based and spatially explicit model based on resource sharing, for 23 functionally diverse tree species in forest stands with contrasting species compositions and environmental conditions in southern Québec. Using data from the forest inventory of Québec, we evaluated the ability of HETEROFOR to predict the short-term growth (5–16 years) of these species at the tree and stand levels, and the long-term dynamics (120 years) of red and sugar maple stands. The comparison between the prediction quality for the calibration and evaluation datasets showed the robustness of the model performance in predicting individual tree growth. The model reproduced correctly individual basal area increment (BAI) of the validation dataset with a mean Pearson’s correlation coefficient of 0.56 and a mean bias of 18 %. Our results also highlighted that considering tree position is of importance for predicting individual tree growth most accurately in complex stands with both vertical and horizontal heterogeneous structure. The model also showed a good ability to reproduce BAI at the stand level, both for monospecific (bias of -3.7 %, Pearson’s r = 0.55) and multi-species stands (bias of -9.1 %, Pearson’s r = 0.62). Long-term simulations of red maple and sugar maple showed that HETEROFOR was able to accurately predict the growth (basal area and height) and mortality processes from the seedling stage to the mature stand. Our results suggest that HETEROFOR is a reliable option to simulate forest growth in southern Québec and test new forestry practices under future climate scenarios.

Arthur Guignabert et al.

Status: open (until 18 Jan 2023)

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Arthur Guignabert et al.

Data sets

Validation of a new spatially-explicit process-based model (HETEROFOR) to simulate structurally and compositionally complex stands in Eastern North-America : Dataset Arthur Guignabert, Quentin Ponette, Frédéric André, Christian Messier, Philippe Nolet, Mathieu Jonard https://doi.org/10.5281/zenodo.7225303

Arthur Guignabert et al.

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Short summary
Spatially explicit and process-based models are useful to test innovative forestry practices under changing and uncertain conditions. However, their larger use is often limited by the restricted range of species and stand structures they can reliably account for. We therefore calibrated and evaluated such a model, HETEROFOR, for 23 species across southern Québec. Our results showed that the model is robust and can predict accurately both individual tree growth and stand dynamics in this region.