Public defence in Forestry Industry Production Systems: Magnus Persson
Thesis title:
Evaluating thinning practices and assessment methods for improved management in coniferous production forests in southern Sweden
Third-cycle subject area:
Forestry Industry Production Systems
Faculty:
Faculty of Technology
Date:
Friday 4 November 2022 at 10:00
Place for thesis:
House N, N1017, Växjö
External reviewer:
Professor Lauri Mehtätalo, Natural Resources Institute Finland (LUKE), Finland
Examining committee:
Professor Lars Eklundh, Lunds University
Professor Annika Kangas, Natural Resources Institute Finland (LUKE), Finland
Professor Jari Hynynen, Natural Resources Institute Finland (LUKE), Finland
Suppleant:
Professor Johan Fransson, Forest and Wood Technology, Linnaeus University
Chairperson:
Professor Johanna Witzell, Forestry and Wood Technology, Linnaeus University
Supervisor:
Professor Johan Bergh, Forestry and Wood Technology, Linnaeus University
Assistant supervisor:
Docent Emma Holmström, Sveriges lantbruksuniversitet Docent Johan Sonesson, Skogforsk Dr. Magnus Petersson, Södra skogsägarna
Examiner:
Professor Stergios Adamopoulos, Forestry and Wood Technology, Linnaeus University
Spikning:
Friday 14 October 2022 at 14:00 at University Library, Växjö
Abstract
Much of our knowledge about coniferous production stands and associated silvicultural guidelines are based on field experiments which naturally have been established in rather small, homogenous management units. The assumingly large gradient in within-stand variation in practical forestry complicates an efficient use of the guidelines. The aim of the thesis is to evaluate within-stand variation at first thinning: its extent, its various effects on silviculture and its importance for future stand development. Also, to explore the utility of the optical satellite system Sentinel-2 for monitoring thinning and classifying tree species.
The survey showed an unprecedented within-stand variation before thinning for various stand attributes, but the observed thinning operations did not reduce the within-stand variation in any of the attributes. The stands were also thinned heavily (Paper I). The thinning detection model (Paper II) based on Sentinel-2 satellite imagery, separated unthinned, lightly thinned and heavily thinned sample plots with a moderate overall accuracy of 62% (kappa of 0.34). Also, annual volume growth after thinning was estimated with a root mean squared error (RMSE) of 1.8 m3 ha-1 y-1 (relative RMSE: 24%). The thinning regime were optimized (Paper III) based on the within-stand variation before thinning using the Heureka system, but no benefits in terms of stand economy or mean annual increment was found as compared to conventional stand-level thinning. Despite the non-significant results, high-resolution maps are probably needed anyway to support forest workers in thinning operations as the observed stands were heavily thinned. The dominant tree species on pixel level was classified over a large forest holding (Paper IV) using Sentinel-2 with a high overall accuracy of 88.2 %. This illustrate the usefulness of Sentinel-2 and that a practical implementation is feasible.
I conclude that there is overall a lot to gain from basing decisions on the within-stand variation and in the implementation of silviculture. The Sentinel-2 system proved its relevance for practical forestry, since monitoring of thinning response, thinning detection and tree species maps will reduce uncertainties for the management of planted forest.
Zoom link:
https://lnu-se.zoom.us/j/65766335091?pwd=THpDMFkvU0hvbUhIaWh4UW9RekhRdz09
Passcode: 881297
Meeting ID: 657 6633 5091