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

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...

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Bibliographic Details
Published in:	Forests Vol. 15; no. 6; p. 990
Main Authors:	Koen Kramer, Lauren T. Bennett, Remi Borelle, Patrick Byrne, Paul Dettman, Jacqueline R. England, Hielke Heida, Ysbrand Galama, Josephine Haas, Marco van der Heijden, Anna Pykoulas, Rodney Keenan, Vithya Krishnan, Helena Lindorff, Keryn I. Paul, Veronica Nooijen, Jeroen van Veen, Quinten Versmissen, Arnout Asjes
Format:	Journal Article
Language:	English
Published:	MDPI AG 01-06-2024
Subjects:	above-ground biomass carbon capture projection carbon sequestration environmental plantings revegetation woodland restoration
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Summary:	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.
ISSN:	1999-4907
DOI:	10.3390/f15060990