New 1 km Resolution Datasets of Global and Regional Risks of Tree Cover Loss
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...
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doaj-1a3cd19f84f24849b442b2acc5b62de72020-11-25T02:48:14ZengMDPI AGLand2073-445X2019-01-01811410.3390/land8010014land8010014New 1 km Resolution Datasets of Global and Regional Risks of Tree Cover LossJennifer Hewson0Stefano C. Crema1Mariano González-Roglich2Karyn Tabor3Celia A. Harvey4Betty and Gordon Moore Center for Science, Conservation International, 2011 Crystal Drive Suite 600, Arlington, VA 22202, USAClark Labs, Clark University, Worcester, MA 01610, USABetty and Gordon Moore Center for Science, Conservation International, 2011 Crystal Drive Suite 600, Arlington, VA 22202, USABetty and Gordon Moore Center for Science, Conservation International, 2011 Crystal Drive Suite 600, Arlington, VA 22202, USABetty and Gordon Moore Center for Science, Conservation International, 2011 Crystal Drive Suite 600, Arlington, VA 22202, USADespite 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.http://www.mdpi.com/2073-445X/8/1/14land change modelingtree cover lossREDD+Sustainable Development Goalstree cover loss projections |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Jennifer Hewson Stefano C. Crema Mariano González-Roglich Karyn Tabor Celia A. Harvey |
spellingShingle |
Jennifer Hewson Stefano C. Crema Mariano González-Roglich Karyn Tabor Celia A. Harvey New 1 km Resolution Datasets of Global and Regional Risks of Tree Cover Loss Land land change modeling tree cover loss REDD+ Sustainable Development Goals tree cover loss projections |
author_facet |
Jennifer Hewson Stefano C. Crema Mariano González-Roglich Karyn Tabor Celia A. Harvey |
author_sort |
Jennifer Hewson |
title |
New 1 km Resolution Datasets of Global and Regional Risks of Tree Cover Loss |
title_short |
New 1 km Resolution Datasets of Global and Regional Risks of Tree Cover Loss |
title_full |
New 1 km Resolution Datasets of Global and Regional Risks of Tree Cover Loss |
title_fullStr |
New 1 km Resolution Datasets of Global and Regional Risks of Tree Cover Loss |
title_full_unstemmed |
New 1 km Resolution Datasets of Global and Regional Risks of Tree Cover Loss |
title_sort |
new 1 km resolution datasets of global and regional risks of tree cover loss |
publisher |
MDPI AG |
series |
Land |
issn |
2073-445X |
publishDate |
2019-01-01 |
description |
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. |
topic |
land change modeling tree cover loss REDD+ Sustainable Development Goals tree cover loss projections |
url |
http://www.mdpi.com/2073-445X/8/1/14 |
work_keys_str_mv |
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