Modelling the Spatial Structure of White Spruce Plantations and Their Changes after Various Thinning Treatments

Abstract

Research Highlights: The spatial distribution of trees results from several ecological processes that can be difficult to measure. We applied a point process modelling approach that uses the diameter and species of neighbouring trees to represent inter-tree interactions through repulsive and attractive processes. Thinning treatments slightly influence the tree spatial distribution of trees in white spruce plantations. Integrating this “spatialiser” into growth models could help improve stand simulations following various thinning treatments over larger areas and longer periods. It could also allow for the use of spatially explicit models when tree position is not available. Background and Objectives: Tree spatial patterns result from several ecological processes and have important implications in forest ecology and management. The use of spatial information can significantly improve our understanding of forest structures. However, this implies intensive field work that is rarely integrated into forest inventories. The aims of this study were to develop a spatial distribution simulator of trees in white spruce plantations and to evaluate the influence of thinning treatments. Materials and Methods: A point process modelling approach was used to represent inter-tree interactions through repulsive and attractive process in white spruce (Picea glauca (Moench) Voss) plantations in eastern Quebec, Canada, that had been commercially thinned five years ago. Balsam fir (Abies balsamea (L.) Mill.) and hardwoods together can represent 30–40% of the basal area of these plantations. Results: The diameter and species of each tree’s two closest neighbours were found to be the most important predictors in explaining the observed distances between trees. Despite the short period since thinning treatments, results showed that the treatment had slight significant effects on tree interactions. However, their impact on the global spatial distribution of stands is quite limited. Conclusions: Using only a few readily-available variables (species and diameter of trees), this “spatialiser” will make it possible to assign spatial coordinates to trees and generate realistic stand spatial structures even after various silvicultural treatments.

Simulation model in determining forestry and plantation circumstances

“…The most significant predictor tree in clarifying the observed distance between the found trees is the diameter and species of the two closest neighbors. Since the treatment of singering, in a short period of outcomes showed that the action had little substantial effect on the interaction of trees [20].…”

A Novel Model to evaluate Spatial Structure in Thinned Conifer- Broadleaved Mixed Natural Forests

“…Different nascent forest management methods now meet the demands for sustainable development of forest ecosystems, among which domestic and foreign mixed thinning is the most common (Fulé et al, 2012;Hartley, 2002;Huuskonen et al, 2021;Kolström et al, 2011;Spathelf P, 2015). This management method not only maintains stable forest diversity, reduces pests and diseases, maintains forest self-regulation, enhances self-recovery (Knoke et al, 2008), improves the forest environment (Li et al, 2021), but also affects forest non-spatial structure (Horner et al, 2010), forest spatial structure (Duchateau et al, 2021;Ye et al, 2018), species diversity in the forest understory, and understory plant regeneration. These complementary effects optimize the functioning of the forest ecosystem.…”

Modeling Forest Stand Dynamics, Growth and Yield

“…This Special Issue is comprised of eight papers with authors from 11 countries in Asia, Australasia, Europe, North America, and South America. The compilation begins with a paper on modeling tree growth using forest inventory data [1], which is followed by a presentation on modeling spatial structure changes in white spruce plantations after thinning [2]. A non-destructive method for tree pith location based on terrestrial laser scanning is described in the next paper [3].…”