Methods for predicting Sitka spruce natural regeneration presence and density in the UK
Simone Bianchi (1) , Sophie Hale (2), James Gibbons (1)
iForest - Biogeosciences and Forestry, Volume 12, Issue 3, Pages 279-288 (2019)
doi: https://doi.org/10.3832/ifor2888-012
Published: May 23, 2019 - Copyright © 2019 SISEF
Research Articles
Abstract
Natural regeneration is crucial for silvicultural approaches based on the continuous presence of a forest cover, or Continuous Cover Forestry (CCF). Sitka spruce (Picea sitchensis) is the main commercial species in the United Kingdom (UK), and its potential for CCF has been demonstrated in various studies. However, there are no quantitative models available to predict its natural regeneration in the country. We describe models for Sitka spruce seedlings presence and density under canopy cover in the UK forests, to be used as a substitution of a regeneration survey. Using a natural regeneration dataset comprised of 340 plots, a Generalized Linear Mixed Model (GLMM) was calibrated to estimate the likelihood of regeneration presence at plot level. Seedling density was simulated in a subsequent step using only the subset of data with regeneration presence (138 plots): we compared methods based on GLMMs calibrated to the observed seedling density, and the simple generation of random numbers similar in distribution to the observed values. We validated the models with a cross-validation method using the calibration dataset and with an independent dataset of 78 plots collected in forests already in the process of transformation to CCF. The best GLMM for regeneration presence included age of the plantation, time after last thinning, favourable ground cover and basal area. After the cross-validation, 73% of the plots were correctly estimated (76% for presence of regeneration and 71% for the absence). After the independent validation process, 82% of the plots were correctly estimated, although 100% for presence of regeneration and only 12% for the absence. Both methods for estimating seedling density had a poor performance, both with the cross-validation and independent validation. The results showed that the tools here described are appropriate for estimating regeneration presence in traditional Sitka spruce plantations. However, alternative methods are required for forests already in an advanced stage of transformation to CCF systems.
Keywords
Sitka Spruce, Natural Regeneration, Regeneration Occurrence, Logistic Modelling, Seedling Density
Authors’ Info
Authors’ address
James Gibbons 0000-0002-0083-9872
School of Environment, Natural Resources and Geography, Bangor University, Bangor, Gwynedd (UK)
Northern Research Station, Forest Research, Roslin, Midlothian (UK)
Corresponding author
Paper Info
Citation
Bianchi S, Hale S, Gibbons J (2019). Methods for predicting Sitka spruce natural regeneration presence and density in the UK. iForest 12: 279-288. - doi: 10.3832/ifor2888-012
Academic Editor
Gianfranco Minotta
Paper history
Received: Jun 07, 2018
Accepted: Mar 18, 2019
First online: May 23, 2019
Publication Date: Jun 30, 2019
Publication Time: 2.20 months
Copyright Information
© SISEF - The Italian Society of Silviculture and Forest Ecology 2019
Open Access
This article is distributed under the terms of the Creative Commons Attribution-Non Commercial 4.0 International (https://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
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