Pushing the envelope : empirical growth models for forests at change

Sammanfattning

Global climatic change has local impacts. By extending the empirical forest growth model for single trees PrognAus with a climate-sensitive module for basal area increment we forecast single-layered stands of Scots Pine (Pinus sylvestris L.), Oak (Quercus spp.), and their mixture to show latitudinally ordered decreases in standing volume in the year 2100 (paper I). The forecast decreases were more severe for Scots Pine stand types than for Oak stand types; more severe between the historical reference and RCP 4.5 than the additional stress imposed by the RCP 8.5 scenario for the Oak stand type, whilst Scots Pine experienced a decrease of the same magnitude as between the historical reference and RCP 4.5; and more severe at lower latitudes than for higher latitudes. To investigate high-resolution spatiotemporal trends, we trained a static reduced model (SRM) on the forecast stands and their climatic data (paper II). We simulated the period 2018-2100 at 30-arcsecond resolution across Europe for all stand types to compare to the period 1923-2005. The Scots Pine stand type was predicted to experience substantial decreases in gross volume production relative to the historical scenario under the future scenarios RCP 4.5 and RCP 8.5. The gross volume production of the Oak stand type was predicted to decrease in northern Europe but increase in some regions of central and southern Europe. In contrast, paper III develops a proxy for the site productivity of mixed coniferous forests based on repeat airborne laser scanning which is compared to derived values for soil moisture. Our proxy for site productivity showed a weak decline with increasing soil moisture, although variation was large. In paper IV, we present preliminary results of the potential in using high-density repeated airborne laser scanning for short-term predictions of volume increment in individual trees of Norway Spruce (Picea abies (L.) H. Karst).

Nyckelord

climate change; growth; Norway Spruce; Scots Pine; Oak; productivity; remote sensing; LiDAR; site index

Publicerad i

Acta Universitatis Agriculturae Sueciae
2024, nummer: 2024:97
Utgivare: Swedish University of Agricultural Sciences

SLU författare

• Vigren, Carl

  • Institutionen för skoglig resurshushållning, Sveriges lantbruksuniversitet
    

UKÄ forskningsämne

Fysisk geografi
Skogsvetenskap
Miljövetenskap

Publikationens identifierare

• DOI: https://doi.org/10.54612/a.7qt3hgmn6k
• ISBN: 978-91-8046-424-6
• eISBN: 978-91-8046-432-1

Permanent länk till denna sida (URI)

https://res.slu.se/id/publ/132428