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Site-Level Modelling Comparison of Carbon Capture by Mixed-Species Forest and Woodland Reforestation in Australia.

Authors :
Kramer, Koen
Bennett, Lauren T.
Borelle, Remi
Byrne, Patrick
Dettman, Paul
England, Jacqueline R.
Heida, Hielke
Galama, Ysbrand
Haas, Josephine
van der Heijden, Marco
Pykoulas, Anna
Keenan, Rodney
Krishnan, Vithya
Lindorff, Helena
Paul, Keryn I.
Nooijen, Veronica
van Veen, Jeroen
Versmissen, Quinten
Asjes, Arnout
Source :
Forests (19994907); Jun2024, Vol. 15 Issue 6, p990, 21p
Publication Year :
2024

Abstract

Large areas of Australia's natural woodlands have been cleared over the last two centuries, and remaining woodlands have experienced degradation from human interventions and anthropogenic climate change. Restoration of woodlands is thus of high priority both for government and society. Revegetation of deforested woodlands is increasingly funded by carbon markets, with accurate predictions of site-level carbon capture an essential step in the decision making to restore. We compared predictions of carbon in above-ground biomass using both the IPCC Tier 2 modelling approach and Australia's carbon accounting model, FullCAM, to independent validation data from ground-based measurements. The IPCC Tier 2 approach, here referred to as the FastTrack model, was adjusted to simulate carbon capture by mixed-species forests for three planting configurations: direct seeding, tubestock planting, and a mix thereof. For model validation, we collected data on above-ground biomass, crown radius, and canopy cover covering an age range of 9–35 years from 20 plantings (n = 6044 trees). Across the three planting configurations, the FastTrack model showed a bias of 2.4 tC/ha (+4.2% of the observed mean AGB), whilst FullCAM had a bias of −24.6 tC/ha (−42.9% of the observed mean AGB). About two-thirds of the error was partitioned to unsystematic error in FastTrack and about one-quarter in FullCAM, depending on the goodness-of-fit metric assessed. Model bias differed strongly between planting configurations. For the FastTrack model, we found that additional canopy cover data estimated from satellite images obtained at different years can improve the carbon capture projections. To attain the highest accuracy of carbon projection at the site level, we recommend using a model with parameters calibrated for the specific planting configuration using local representative data. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
19994907
Volume :
15
Issue :
6
Database :
Complementary Index
Journal :
Forests (19994907)
Publication Type :
Academic Journal
Accession number :
178156201
Full Text :
https://doi.org/10.3390/f15060990