Data

The unrealised potential of agroforestry (climate mitigation potential analysis)

The University of Queensland
Dr Simon Hart (Aggregated by) Dr Wilma J. Blaser Hart (Aggregated by)
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.48610/dda018c&rft.title=The unrealised potential of agroforestry (climate mitigation potential analysis)&rft.identifier=RDM ID: abf4b441-07f4-4545-b59d-7f295858e826&rft.publisher=The University of Queensland&rft.description=This dataset is part of a larger collection supporting the analysis in Becker et al., Nature Sustainability (2025) on the climate mitigation potential of cocoa agroforestry in West Africa. It includes the R code and processed data used to estimate aboveground carbon stocks under different agroforestry adoption scenarios, and supports the reproducibility of the scenario analysis presented in the study.&rft.creator=Dr Simon Hart&rft.creator=Dr Wilma J. Blaser Hart&rft.date=2025&rft.coverage=1.152408,10.419051 -7.548764,10.419051 -7.548764,4.276688 1.152408,4.276688 1.152408,10.419051&rft_rights= https://guides.library.uq.edu.au/deposit-your-data/license-reuse-data-agreement&rft_subject=eng&rft_subject=Sustainable agricultural development&rft_subject=Agriculture, land and farm management&rft_subject=AGRICULTURAL, VETERINARY AND FOOD SCIENCES&rft_subject=Agroforestry&rft_subject=Forestry sciences&rft_subject=Deep learning&rft_subject=Machine learning&rft_subject=INFORMATION AND COMPUTING SCIENCES&rft.type=dataset&rft.language=English Access the data
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[email protected]
School of the Environment

Full description

This dataset is part of a larger collection supporting the analysis in Becker et al., Nature Sustainability (2025) on the climate mitigation potential of cocoa agroforestry in West Africa. It includes the R code and processed data used to estimate aboveground carbon stocks under different agroforestry adoption scenarios, and supports the reproducibility of the scenario analysis presented in the study.

Issued: 2025

This dataset is part of a larger collection

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Subjects
Agricultural, Veterinary and Food Sciences | Agriculture, Land and Farm Management | Agroforestry | Deep Learning | Forestry Sciences | Information and Computing Sciences | Machine Learning | Sustainable Agricultural Development | eng |

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Identifiers
ACN 633 798 857