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Carlzon, Sebastian, 2022. Validation of basal area growth functions for larch in Heureka DSS. Second cycle, A2E. Alnarp: SLU, Southern Swedish Forest Research Centre



Larch is getting more common in Sweden. This highlights the need of reliable growth models for
larch species in Heureka DSS. Precise and accurate growth models are essential for long-term forest
planning. The risk of using under- or overpredicted basal area growth in forest planning is that longterm
projections could get more and more imprecise over time. This could, in turn, lead to
suboptimal forest management and decision-making, leading to non-optimal choice of tree-species,
early- or late timing of silvicultural treatments and ultimately to economic loss. The aim of this
thesis was to validate Heureka’s basal area growth function for Siberian larch (Larix sibirica),
European larch (Larix decidua) and hybrid larch (Larix x eurolepis). To validate the growth
function, field trials of larch from all over Sweden were used to compare basal area growth
prediction errors between Heureka predicted growth and basal area measured in the field. A sample
of plots were also chosen for simulation in Heureka StandWise for further analysis of basal area,
height and volume growth. Age-related prediction errors along with ground vegetation type were
tested and compared for the Heureka basal area function.
The results showed that basal area growth of Siberian larch was underpredicted at early age and
overpredicted at old age, regardless of vegetation type. European larch basal area growth was neither
under- nor overpredicted for the vegetation types but showed random error at young age. Basal area
growth of Hybrid larch showed a general underpredicted with vegetation type bilberry while no such
trend was seen for vegetation type no field vegetation. Heureka simulations showed a slightly higher
underpredicted basal area growth than predictions from the growth function. This could be explained
by that the predicted growth gets more imprecise over time or due to a too small sample size. There
are possibilities to increase the precision of Heureka’s growth predicted where one strategy would
be to develop and apply species specific growth models in Heureka DSS.

Main title:Validation of basal area growth functions for larch in Heureka DSS
Authors:Carlzon, Sebastian
Supervisor:Nilsson, Urban
Examiner:Trubins, Renats
Volume/Sequential designation:UNSPECIFIED
Year of Publication:2022
Level and depth descriptor:Second cycle, A2E
Student's programme affiliation:SY001 Forest Science - Master's Programme 300 HEC
Supervising department:(S) > Southern Swedish Forest Research Centre
Keywords:validation, Heureka, Larix, Larix sibirica, Larix sukaczewii, Larix decidua, Larix x eurolepis, Siberian larch, European larch, hybrid larch, growth model validation, Heureka DSS, basal area growth
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Subject. Use of subject categories until 2023-04-30.:Forestry production
Deposited On:01 Sep 2022 05:59
Metadata Last Modified:02 Sep 2022 01:05

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