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

机译:新的1 km的全球和区域树木覆盖率损失风险的分辨率数据集

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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.
机译:尽管全球范围内都认识到毁林对社会,经济和生态的影响,但世界正在以惊人的速度失去森林。决策者和捐助者为减少森林砍伐而进行的全球和区域性努力,需要以科学为依据的信息,以了解森林损失的发生地点以及未来可能发生的损失。我们使用照常使用的空间明晰的全球一致变量和全球历史树木覆盖率和损失,以照常营业的方式分析全球和区域尺度变量如何造成历史树木覆盖率损失并模拟树木覆盖率损失的未来风险场景。我们的结果表明:(1)一些生物群落的树木覆盖率比其他生物群落高; (2)全球范围内与树木覆盖率损失相关的变量与地区范围内的变量不同; (3)与树木覆盖率损失相关的变量因大陆而异。通过绘制树木覆盖率损失风险和潜在的未来树木覆盖率损失图,我们旨在为决策者和捐助者提供多种产出,以改善森林保护投资的针对性。通过使输出易于获取,我们预计它们将被用于其他建模分析,保护规划工作以及旨在保护森林以满足国家和全球减缓气候变化目标和生物多样性目标的优先活动。

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