Validation of a new spatially explicit process-based model (HETEROFOR) to simulate structurally and compositionally complex forest stands in eastern North America
<p>Process-based forest growth models with spatially explicit representation are relevant tools 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...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2023-03-01
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| Series: | Geoscientific Model Development |
| Online Access: | https://gmd.copernicus.org/articles/16/1661/2023/gmd-16-1661-2023.pdf |
| Summary: | <p>Process-based forest growth models with spatially explicit representation
are relevant tools 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 and are often calibrated for a very limited
number of species and rarely for 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 (HETEROgeneous FORest), 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 Quebec. Using data from the forest
inventory of Quebec, 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 of the calibration
and evaluation datasets showed the robustness of the model performance in
predicting individual-tree growth. The model reproduced correctly the 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 vertically and horizontally heterogeneous structures. The model also showed a good ability
to reproduce BAI at the stand level, both for monospecific (bias of
<span class="inline-formula">−</span>3.7 %; Pearson's <span class="inline-formula"><i>r</i>=0</span>.55) and multi-species stands (bias of <span class="inline-formula">−</span>9.1 %;
Pearson's <span class="inline-formula"><i>r</i>=0</span>.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 Quebec and to test new forestry practices under
future climate scenarios.</p> |
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| ISSN: | 1991-959X 1991-9603 |