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National-scale datasets systematically underestimate vegetation recovery in Australian carbon farming projects

National-scale datasets systematically underestimate vegetation recovery in Australian carbon farming projects

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Authors

Tim Moore, Andrew O'Reilly-Nugent , Kenneth Clarke, Cathleen Waters

Abstract

Limiting global warming below 2 degrees C requires nature-based climate solutions which are expected to supply more than a third of cost-effective climate mitigation by 2030. Regenerating native forests under the Australian Government’s Australian Carbon Credit Unit (ACCU) program are delivering large-scale carbon storage across approximately 3.4 million hectares. Projects using the Human Induced regeneration (HIR) method3 25 aim to restore native forests through improved land management, generating ACCUs that underpin both legislated emissions reduction and voluntary decarbonisation targets. Scientific rigour and transparency must underpin the integrity of the ACCU program. Constructive critiques of carbon crediting programs allow refinement over time, strengthening climate action. However, flawed analyses can undermine investment decisions and diminish real outcomes when it impacts critical policy decisions. Macintosh et al. (2024; https://doi.org/10.1038/s43247-024-01313-x) contend that HIR activities are having limited influence on changes in woody vegetation cover in Australia. Macintosh analysed the National Forest and Sparse Woody Vegetation Dataset (NFSWVD) and, elsewhere, Woody Cover Fraction (WCF) to compare vegetation trends between credited HIR areas and adjacent comparison areas. Here, we show their assessment relies on two flawed assumptions: 1. that publicly available, national-scale datasets can accurately detect and quantify vegetation cover at the scale of individual projects, and 2. that adjacent comparison areas represent valid experimental controls. We provide high quality reference data, collected on HIR projects as standard practice, as empirical evidence that these national-scale datasets systematically underestimate regeneration success on HIR projects, and are therefore not fit for purpose as used by Macintosh. We also demonstrate that Macintosh' s experimental design undermines and does not support their stated conclusions.

DOI

https://doi.org/10.32942/X2CW5W

Subjects

Environmental Monitoring

Keywords

Dates

Published: 2025-06-10 23:40

Last Updated: 2025-06-10 23:40

License

CC BY Attribution 4.0 International

Additional Metadata

Language:
English

Conflict of interest statement:
The authors receive financial remuneration for administering carbon farming projects and monitoring their performance.