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Open AccessArticle

New 1 km Resolution Datasets of Global and Regional Risks of Tree Cover Loss

1
Betty and Gordon Moore Center for Science, Conservation International, 2011 Crystal Drive Suite 600, Arlington, VA 22202, USA
2
Clark Labs, Clark University, Worcester, MA 01610, USA
3
Monteverde Institute, Apdo 69-6665, Monteverde, Puntarenas 60109, Costa Rica
*
Author to whom correspondence should be addressed.
Received: 31 October 2018 / Revised: 6 December 2018 / Accepted: 4 January 2019 / Published: 10 January 2019
(This article belongs to the Special Issue Monitoring Land Cover Change: Towards Sustainability)
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Abstract

Despite global recognition of the social, economic and ecological impacts of deforestation, the world is losing forests at an alarming rate. Global and regional efforts by policymakers and donors to reduce deforestation need science-driven information on where forest loss is happening, and where it may happen in the future. We used spatially-explicit globally-consistent variables and global historical tree cover and loss to analyze how global- and regional-scale variables contributed to historical tree cover loss and to model future risks of tree cover loss, based on a business-as-usual scenario. Our results show that (1) some biomes have higher risk of tree cover loss than others; (2) variables related to tree cover loss at the global scale differ from those at the regional scale; and (3) variables related to tree cover loss vary by continent. By mapping both tree cover loss risk and potential future tree cover loss, we aim to provide decision makers and donors with multiple outputs to improve targeting of forest conservation investments. By making the outputs readily accessible, we anticipate they will be used in other modeling analyses, conservation planning exercises, and prioritization activities aimed at conserving forests to meet national and global climate mitigation targets and biodiversity goals. View Full-Text
Keywords: land change modeling; tree cover loss; REDD+; Sustainable Development Goals; tree cover loss projections land change modeling; tree cover loss; REDD+; Sustainable Development Goals; tree cover loss projections
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Hewson, J.; Crema, S.C.; González-Roglich, M.; Tabor, K.; Harvey, C.A. New 1 km Resolution Datasets of Global and Regional Risks of Tree Cover Loss. Land 2019, 8, 14.

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