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Pantropical distribution of short-rotation woody plantations: spatial probabilities under current and future climate

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Abstract

Short-rotation woody plantations (SRWPs) play a major role in climate change mitigation and adaptation plans, because of their high yields of woody biomass and fast carbon storage. However, their benefits, trade-offs and growing-success are heavily location-dependent. Therefore, spatial data on the distribution of SRWPs are indispensable for assessing current distribution, trade-offs with other uses and potential contributions to climate mitigation. As current global datasets lack reliable information on SRWPs and full global mapping is difficult, we provide a consistent and systematic approach to estimate the spatial distribution of SRWPs in (sub-)tropical biomes under current and future climate. We combined three advanced methods (maximum entropy, random forest and multinomial regression) to evaluate spatially explicit probabilities of SRWPs. As inputs served a large empirical dataset on SRWP observations and 17 predictor variables, covering biophysical and socio-economic conditions. SRWP probabilities varied strongly between regions, and might not be feasible in major parts of (sub-)tropical biomes, challenging the feasibility of global mitigation plans that over-rely on tree plantations. Due to future climatic changes, SRWP probabilities decreased in many areas, particularly pronounced in higher emission scenarios. This indicates a negative feedback with higher emissions resulting in less mitigation potential. Less suitable land for SRWPs in the future could also result in fewer wood resources from these plantations, enhancing pressure on natural forests and hampering sustainability initiatives that use wood-based alternatives. Our results can help adding a more nuanced treatment of mitigation options and forest management in research on biodiversity and land use change.

Original languageEnglish
Article number28
Pages (from-to)1-22
Number of pages22
JournalMitigation and Adaptation Strategies for Global Change
Volume28
Issue number5
Early online date25 May 2023
DOIs
Publication statusPublished - Jun 2023

Bibliographical note

Funding Information:
K.S., Z.M. and P.V. would like to thank the European Commission for funding through the European Research Council under the European Union's Seventh Framework Programme project ID 311819 (GLOLAND). Part of the research was conducted during the Young Scientist Summer Program at the International Institute for Applied Systems Analysis. We gratefully acknowledge financial support from the German IIASA association. Additionally, we would like to thank Olga Danylo for the help with the machine learning approach and all IIASA researchers that gave feedback during the YSSP and at the final YSSP colloquium.

Funding Information:
K.S., Z.M., P.V.: European Commission through the European Research Council under the European Union's Seventh Framework Programme project ID 311819 (GLOLAND); Financial support from German IIASA association during Young Scientist Summer Program.

Publisher Copyright:
© 2023, The Author(s).

Funding

K.S., Z.M. and P.V. would like to thank the European Commission for funding through the European Research Council under the European Union's Seventh Framework Programme project ID 311819 (GLOLAND). Part of the research was conducted during the Young Scientist Summer Program at the International Institute for Applied Systems Analysis. We gratefully acknowledge financial support from the German IIASA association. Additionally, we would like to thank Olga Danylo for the help with the machine learning approach and all IIASA researchers that gave feedback during the YSSP and at the final YSSP colloquium. K.S., Z.M., P.V.: European Commission through the European Research Council under the European Union's Seventh Framework Programme project ID 311819 (GLOLAND); Financial support from German IIASA association during Young Scientist Summer Program.

FundersFunder number
European Commission
Seventh Framework Programme
European Research Council
IIASA association
International Institute for Applied Systems Analysis
Seventh Framework Programme311819

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 13 - Climate Action
      SDG 13 Climate Action
    2. SDG 15 - Life on Land
      SDG 15 Life on Land

    Keywords

    • Forest management
    • Land use modelling
    • Land-based climate change mitigation
    • Spatial probability mapping
    • Tree plantations

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