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Mapping data gaps to estimate biomass across Brazilian Amazon forests
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Tropical forests play a fundamental role in the provision of diverse ecosystem services, such as biodiversity, climate and air quality regulation, freshwater provision, carbon cycling, agricultural support and culture. To understand the role of forests in the carbon balance, aboveground biomass (AGB) estimates are needed. Given the importance of Brazilian tropical forests, there is an urgent need to improve AGB estimates to support the Brazilian commitments under the United Nations Framework Convention on Climate Change (UNFCCC). Many AGB maps and datasets exist, varying in availability, scale and coverage. Thus, stakeholders, policy makers and scientists must decide which AGB product, dataset or combination of data to use for their particular goals. In this study, we assessed the gaps in the spatial AGB data across the Brazilian Amazon forests not only to orient the decision makers about the data that are currently available but also to provide a guide for future initiatives.
We obtained a map of the gaps in the forest AGB spatial data for the Brazilian Amazon using statistics and differences between AGB maps and a spatial multicriteria evaluation that considered the current AGB datasets. The AGB spatial data gap map represents areas with good coverage of AGB data and, consequently, the main gaps or priority areas where further biomass assessments should focus, including the northeast of Amazon State, Amapá and northeast of Pará. Additionally, by quantifying the variability in both the AGB maps and field data on multiple environmental factors, we provide valuable elements for understanding the current AGB data as a function of climate, soil, vegetation and geomorphology.
The map of AGB data gaps could become a useful tool for policy makers and different stakeholders working on National Communications, Reducing Emissions from Deforestation and Degradation (REDD+), or carbon emissions modeling to prioritize places to implement further AGB assessments. Only 0.2% of the Amazon biome forest is sampled, and extensive effort is necessary to improve what we know about the tropical forest.
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Mapping data gaps to estimate biomass across Brazilian Amazon forests
),
Abstract
Tropical forests play a fundamental role in the provision of diverse ecosystem services, such as biodiversity, climate and air quality regulation, freshwater provision, carbon cycling, agricultural support and culture. To understand the role of forests in the carbon balance, aboveground biomass (AGB) estimates are needed. Given the importance of Brazilian tropical forests, there is an urgent need to improve AGB estimates to support the Brazilian commitments under the United Nations Framework Convention on Climate Change (UNFCCC). Many AGB maps and datasets exist, varying in availability, scale and coverage. Thus, stakeholders, policy makers and scientists must decide which AGB product, dataset or combination of data to use for their particular goals. In this study, we assessed the gaps in the spatial AGB data across the Brazilian Amazon forests not only to orient the decision makers about the data that are currently available but also to provide a guide for future initiatives.
We obtained a map of the gaps in the forest AGB spatial data for the Brazilian Amazon using statistics and differences between AGB maps and a spatial multicriteria evaluation that considered the current AGB datasets. The AGB spatial data gap map represents areas with good coverage of AGB data and, consequently, the main gaps or priority areas where further biomass assessments should focus, including the northeast of Amazon State, Amapá and northeast of Pará. Additionally, by quantifying the variability in both the AGB maps and field data on multiple environmental factors, we provide valuable elements for understanding the current AGB data as a function of climate, soil, vegetation and geomorphology.
The map of AGB data gaps could become a useful tool for policy makers and different stakeholders working on National Communications, Reducing Emissions from Deforestation and Degradation (REDD+), or carbon emissions modeling to prioritize places to implement further AGB assessments. Only 0.2% of the Amazon biome forest is sampled, and extensive effort is necessary to improve what we know about the tropical forest.
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Acknowledgements
We are grateful to Luiz Aragão, Marcos Longo, Luiz Carlos Estraviz, Thelma Krug and Celso von Randow for their valuable contributions to improve this study. We want to thank Michael Keller, Marcos Longo and Maiza Nara dosSantos from the Sustainable Landscapes Project for the field and LiDAR data. For the locations of AGB data, we want to thank Niro Higuchi, Carlos Celes, Moacir Campos and Adriano Lima from INPA, Luiz Aragão from TREES, Marcus Vinicio Oliveira from Embrapa Acre and Joberto Freitas from the National Forest Service. For the AGB maps, we thank Sassan Saatchi, Alessandro Baccini, Euler Nogueira, Valerio Avitabile, and Pedro Valle. We also want to thank American Journal Experts for the English revision.
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