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• W4310235234 abstract "Protected areas (PAs) serve as a critical strategy for protecting natural resources, conserving biodiversity, and mitigating climate change. While there is a critical need to guide area-based conservation efforts, a systematic assessment of PA effectiveness for storing carbon stocks has not been possible due to the lack of globally consistent forest biomass data. In this study, we present a new methodology utilizing forest structural information and aboveground biomass density (AGBD) obtained from the Global Ecosystem Dynamics Investigation (GEDI) mission. We compare PAs with similar, unprotected forests obtained through statistical matching to assess differences in carbon storage and forest structure. We also assess matching outcomes for a robust and minimally biased way to quantify PA efficacy. We find that all analyzed PAs in Tanzania possess higher biomass densities than their unprotected counterfactuals (24.4% higher on average). This is also true for other forest structure metrics, including tree height, canopy cover, and plant area index (PAI). We also find that community-governed PAs are the most effective category of PAs at preserving forest structure and AGBD – often outperforming those managed by international or national entities. In addition, PAs designated under more than one entity perform better than the PAs with a single designation, especially those with multiple international designations. Finally, our findings suggest that smaller PAs may be more effective for conservation, depending on levels of connectivity. Taken together, these findings support the designation of PAs as an effective means for forest management with considerable potential to protect forest ecosystems and achieve long-term climate goals." @default.
• W4310235234 created "2022-11-30" @default.
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• W4310235234 date "2023-01-01" @default.
• W4310235234 modified "2023-10-15" @default.
• W4310235234 title "Assessing protected area’s carbon stocks and ecological structure at regional-scale using GEDI lidar" @default.
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• W4310235234 doi "https://doi.org/10.1016/j.gloenvcha.2022.102621" @default.
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