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

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Title: Pantropical distribution of short-rotation woody plantations: spatial probabilities under current and future climate.
Authors: Schulze, Katharina1 (AUTHOR) k.schulze.env@gmail.com, Malek, Žiga1 (AUTHOR), Schepaschenko, Dmitry2 (AUTHOR), Lesiv, Myroslava2 (AUTHOR), Fritz, Steffen2 (AUTHOR), Verburg, Peter H.1,3 (AUTHOR)
Source: Mitigation & Adaptation Strategies for Global Change. Jun2023, Vol. 28 Issue 5, p1-22. 22p.
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. [ABSTRACT FROM AUTHOR]
Copyright of Mitigation & Adaptation Strategies for Global Change is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Pantropical distribution of short-rotation woody plantations: spatial probabilities under current and future climate.
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  Data: <searchLink fieldCode="AR" term="%22Schulze%2C+Katharina%22">Schulze, Katharina</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> k.schulze.env@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Malek%2C+Žiga%22">Malek, Žiga</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Schepaschenko%2C+Dmitry%22">Schepaschenko, Dmitry</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Lesiv%2C+Myroslava%22">Lesiv, Myroslava</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Fritz%2C+Steffen%22">Fritz, Steffen</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Verburg%2C+Peter+H%2E%22">Verburg, Peter H.</searchLink><relatesTo>1,3</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Mitigation+%26+Adaptation+Strategies+for+Global+Change%22">Mitigation & Adaptation Strategies for Global Change</searchLink>. Jun2023, Vol. 28 Issue 5, p1-22. 22p.
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: 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. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Mitigation & Adaptation Strategies for Global Change is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1007/s11027-023-10066-5
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              Text: Jun2023
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