Dense Forests in the Brazilian State of Amapá Store the Highest Biomass in the Amazon Basin

José Douglas M. da Costa, Paulo Eduardo Barni, Eleneide D. Sotta, Marcelo de J. V. Carim, Alan C. da Cunha, Marcelino C. Guedes, Perseu da S. Aparicio, Leidiane L. de Oliveira, Reinaldo I. Barbosa, Philip M. Fearnside, Henrique E. M. Nascimento and José Julio de Toledo ()
Additional contact information
José Douglas M. da Costa: Graduate Program in Environmental Sciences, Federal University of Amapá UNIFAP, Macapá 68903-419, Brazil
Paulo Eduardo Barni: Rorainópolis Campus, State University of Roraima UERR, Rorainópolis 69375-000, Brazil
Eleneide D. Sotta: Brazilian Agricultural Research Corporation EMBRAPA, Macapá 68903-197, Brazil
Marcelo de J. V. Carim: Technology Development Coordination, Research Institute of Amapá State IEPA, Macapá 68903-419, Brazil
Alan C. da Cunha: Graduate Program in Environmental Sciences, Federal University of Amapá UNIFAP, Macapá 68903-419, Brazil
Marcelino C. Guedes: Brazilian Agricultural Research Corporation EMBRAPA, Macapá 68903-197, Brazil
Perseu da S. Aparicio: Department of Forest Engineering, Amapá State University UEAP, Macapá 68900-070, Brazil
Leidiane L. de Oliveira: Institute of Water Science and Technology, Federal University of Western Pará UFOPA, Santarém 68040-255, Brazil
Reinaldo I. Barbosa: Environmental Dynamics Coordination, National Institute for the Amazon Research INPA, Manaus 69067-375, Brazil
Philip M. Fearnside: Environmental Dynamics Coordination, National Institute for the Amazon Research INPA, Manaus 69067-375, Brazil
Henrique E. M. Nascimento: Environmental Dynamics Coordination, National Institute for the Amazon Research INPA, Manaus 69067-375, Brazil
José Julio de Toledo: Graduate Program in Environmental Sciences, Federal University of Amapá UNIFAP, Macapá 68903-419, Brazil

Sustainability, 2025, vol. 17, issue 12, 1-20

Abstract: The Amazonian forests located within the Guiana Shield store above-average levels of biomass per hectare. However, considerable uncertainty remains regarding carbon stocks in this region, mainly due to limited inventory data and the lack of spatial datasets that account for factors influencing variation among forest types. The present study investigates the spatial distribution of original total forest biomass in the state of Amapá, located in the northeastern Brazilian Amazon. Using data from forest inventory plots, we applied geostatistical interpolation techniques (kriging) combined with environmental variables to generate a high-resolution map of forest biomass distribution. The stocks of biomass were associated with different forest types and land uses. The average biomass was 536.5 ± 64.3 Mg ha −1 across forest types, and non-flooding lowland forest had the highest average (619.1 ± 38.3), followed by the submontane (521.8 ± 49.8) and the floodplain (447.6 ± 45.5) forests. Protected areas represented 84.1% of Amapá’s total biomass stock, while 15.9% was in agriculture and ranching areas, but the average biomass is similar between land-use types. Sustainable-use reserves stock more biomass (40%) than integral-protection reserves (35%) due to the higher average biomass associated with well-structured forests and a greater density of large trees. The map generated in the present study contributes to a better understanding of carbon balance across multiple spatial scales and demonstrates that forests in this region contain the highest carbon stocks per hectare (260.2 ± 31.2 Mg ha −1 , assuming that 48.5% of biomass is carbon) in the Amazon. To conserve these stocks, it is necessary to go further than merely maintaining protected areas by strengthening the protection of reserves, restricting logging activities in sustainable-use areas, promoting strong enforcement against illegal deforestation, and supporting the implementation of REDD+ projects. These actions are critical for avoiding substantial carbon stock losses and for reducing greenhouse-gas emissions from this region.

Keywords: Amazon Guiana Shield; biomass mapping; carbon stock; forest inventory; kriging; land-use change; geostatistics; greenhouse gases; protected areas; REDD+ (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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