Canadian Forest Service Publications
Detecting compensatory growth in silviculture trials – Empirical evidence from three case studies across Canada. 2022. Li, C.; Barclay, H.; Huang, S.; Roitberg, B.; Lalonde, R.; Thiffault, N. Frontiers in Plant Science 13:907598, 15p.
Issued by: Laurentian Forestry Centre
Catalog ID: 40729
Availability: PDF (download)
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Compensatory growth (CG) appears common in biology and is defined as accelerated growth after experiencing a period of unfavorable conditions. It usually leads to an increase in biomass that may eventually equal or even surpass that of sites not experiencing disturbance. In forestry, with sufficient time the stand volume lost in a disturbance such as a thinning operation could match or even exceed those from undisturbed sites, respectively called exact and overcompensation. The forest sector could benefit from enhanced productivity and associated ecosystem services such as carbon storage through overcompensation. Therefore, detection of CG in different types of forests becomes important for taking advantage of it in forest management. However, compensatory growth has not been reported widely in forestry, partially due to the paucity of long-term observations and lack of proper indicators. Legacy forest projects can provide a suitable data source, though they may be originally designed for other purposes. Three case studies representing different data structures of silviculture trials are investigated to evaluate if compensatory growth is common in forest stands. Our results showed that compensatory growth occurred in all three cases, and thus suggested that the compensatory growth might indeed be common in forest stands. We found that the relative growth (RG) can serve as a universal indicator to examine stand-level compensatory growth in historical long-term silviculture datasets. When individual tree-based measurements are available, both volume and value-based indicators can be used in detecting compensatory growth, and lumber value-based indicators could be more sensitive in detecting overcompensation