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Using hybrid modelling to predict basal area and evaluate effects of climate change on growth of Norway spruce and Scots nine stands

Goude, Martin and Nilsson, Urban and Mason, Euan and Vico, Giulia (2022). Using hybrid modelling to predict basal area and evaluate effects of climate change on growth of Norway spruce and Scots nine stands. Scandinavian Journal of Forest Research. 37 :1 , 59-73
[Research article]

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Abstract

When modelling forest growth, capturing the effects of climate change is needed for reliable longterm predictions and management choices. This remains a challenge because commonly used mensurational forest growth and yield models, relying on inventory data, cannot account for climate change effects. We developed hybrid physiological/mensurational basal area growth and yield models, which combine physiological response to climatic conditions and empirical relations. We included climate and site effects by replacing time with light sums of photosynthetically active radiation and modifying the latter with monthly soil water, vapour pressure deficit, temperature, and frost days. When parameterised with permanent sample plot data for Scots pine and Norway spruce across Sweden, the hybrid models could reproduce observations well, although with no increase in precision compared with time-based mensurational models. When considering different climate scenarios, a significant impact on productivity from climate change emerged. For example, a 2 degrees C warming enhanced Scots pine production by up to 14% in regions where temperatures were originally cooler and soil water deficit was low (i.e. northwest Sweden), but depressed it, up to 9%, elsewhere. Hence, climate-sensitive models that take local variations into account are necessary for accurate predictions and sustainable forest management.

Authors/Creators:Goude, Martin and Nilsson, Urban and Mason, Euan and Vico, Giulia
Title:Using hybrid modelling to predict basal area and evaluate effects of climate change on growth of Norway spruce and Scots nine stands
Series Name/Journal:Scandinavian Journal of Forest Research
Year of publishing :2022
Volume:37
Number:1
Page range:59-73
Number of Pages:15
Publisher:TAYLOR AND FRANCIS AS
ISSN:0282-7581
Language:English
Publication Type:Research article
Article category:Scientific peer reviewed
Version:Published version
Copyright:Creative Commons: Attribution-Noncommercial-No Derivative Works 4.0
Full Text Status:Public
Subjects:(A) Swedish standard research categories 2011 > 4 Agricultural Sciences > 401 Agricultural, Forestry and Fisheries > Forest Science
(A) Swedish standard research categories 2011 > 1 Natural sciences > 105 Earth and Related Environmental Sciences > Climate Research
Keywords:photosynthetically active radiation, forest modelling, boreal forests, growth and yield, long-term prediction
URN:NBN:urn:nbn:se:slu:epsilon-p-116382
Permanent URL:
http://urn.kb.se/resolve?urn=urn:nbn:se:slu:epsilon-p-116382
Additional ID:
Type of IDID
DOI10.1080/02827581.2022.2039278
Web of Science (WoS)000757178800001
ID Code:27536
Faculty:S - Faculty of Forest Sciences
NJ - Fakulteten för naturresurser och jordbruksvetenskap
Department:(S) > Southern Swedish Forest Research Centre
(NL, NJ) > Dept. of Crop Production Ecology
Deposited By: SLUpub Connector
Deposited On:12 Apr 2022 15:37
Metadata Last Modified:12 Apr 2022 15:41

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