Validation of a spatial model for the estimation of biomass and carbon storage in the clean shaft in the mangroves of the Gulf of Mexico
DOI :
https://doi.org/10.5902/1980509890104Mots-clés :
NDVI, Sentinel-2A, Remote sensing, ConservationRésumé
Mangroves are tropical and subtropical coastal ecosystems that play a crucial role in protection against erosion and sea level rise, as well as being important in mitigating climate change by storing large amounts of biomass and carbon. To estimate biomass and carbon storage in mangroves, using field and remote sensing methods. An inventory was carried out at 24 monitoring sites within the UMA, each with 30 x 10 m plots. Dasometric variables such as diameter at breast height and tree height were measured using measuring tapes and altimeters. Biomass was estimated using allometric equations specific to each mangrove species, and carbon content was calculated using a biomass-to-carbon conversion factor of 0.48. The vegetation index NDVI, obtained from images from the Sentinel 2A satellite, was used to assess vegetation health at the different sites. At site 3, L. racemosa had the highest average aboveground biomass (127.08 Mg ha-1), while site 18 had the lowest (8.18 Mg ha-1). For A. germinans, site 7 had the highest biomass (129.03 Mg ha-1), and site 5 the lowest (4.23 Mg ha-1). For R. mangle, site 21 had an average aboveground biomass of 53.88 Mg ha-1. NDVI values ranged from 0.68 to 0.88, being higher in areas of robust growth and lower in areas with less developed vegetation. The study validates a spatial model for estimating biomass and carbon storage in mangroves in the Gulf of Mexico, demonstrating the effectiveness of allometric equations and the use of NDVI as a tool to assess ecosystem health.
Téléchargements
Références
APARECIDA DOS REIS, A. et al. Temporal stability of stratifications using different dendrometric variables and geostatistical interpolation. Ciência Florestal, v. 32, n. 1, 2022. DOI: https://doi.org/10.5902/1980509843274
ARIFANTI, V. B. et al. Contributions of mangrove conservation and restoration to climate change mitigation in Indonesia. Global Change Biology, v. 28, n. 15, p. 4523–4538, 2022. DOI: https://doi.org/10.1111/gcb.16216
AYE, W. N.; TONG, X.; TUN, A. W. Species diversity, biomass and carbon stock assessment of Kanhlyashay Natural Mangrove Forest. Forests, v. 13, n. 7, p. 1013, 2022. DOI: https://doi.org/10.3390/f13071013
BARBOSA-RAMOS, J. C. et al. Índices de vegetação na diagnose nutricional de povoamentos híbridos de Eucalyptus urophylla ST Blake. Ciência Florestal, v. 33, n. 2, 2023. DOI: https://doi.org/10.5902/1980509865702
BAUTISTA-OLIVAS, A. I. et al. Aerial biomass and carbon sequestration in mangroves in the arid zone of northwestern Mexico: Bahía del Tóbari and estero El Sargento, Sonora. Revista Chapingo Serie Ciencias Forestales y del Ambiente, v. 24, n. 3, p. 387-403, 2018. DOI: https://doi.org/10.5154/r.rchscfa.2018.02.020
CHAVE, J. et al. Tree allometry and improved estimation of carbon stocks and balance in tropical forests. Oecologia, v. 145, p. 87-99, 2005. DOI: https://doi.org/10.1007/s00442-005-0100-x
CUENCA-OCAY, G. Mangrove ecosystems’ role in climate change mitigation. Davao Research Journal, v. 12, n. 2, p. 72-75, 2019. DOI: https://doi.org/10.59120/drj.v12i2.168
FROMARD, F. et al. Structure, above-ground biomass and dynamics of mangrove ecosystems: new data from French Guiana. Oecologia, v. 115, n. 1, p. 39-53, 1998. DOI: https://doi.org/10.1007/s004420050489
HERNÁNDEZ, M. E.; JUNCA-GÓMEZ, D. Carbon stocks and greenhouse gas emissions (CH4 and N2O) in mangroves with different vegetation assemblies in the central coastal plain of Veracruz Mexico. Science of The Total Environment, v. 741, p. 140276, 2020. DOI: https://doi.org/10.1016/j.scitotenv.2020.140276
KAUFFMAN, J. B.; DONATO, D. C.; ADAME, M. F. Protocol for the measurement, monitoring and reporting of mangrove structure, biomass and carbon stocks. Bogor: CIFOR, 2013. (Vol. 117).
KOMIYAMA, A.; POUNGPARN, S.; KATO, S. Common allometric equations for estimating the tree weight of mangroves. Journal of Tropical Ecology, v. 21, n. 4, p. 471-477, 2005. DOI: https://doi.org/10.1017/S0266467405002476
MENDOZA-CARIÑO, M. et al. Economic value of aboveground mangrove biomass carbon storage in Sonora, Mexico. Revista Chapingo Serie Ciencias Forestales y del Ambiente, v. 28, n. 3, 2022. DOI: https://doi.org/10.5154/r.rchscfa.2021.09.056
MUHSONI, F. F. et al. Comparison of different vegetation indices for assessing mangrove density using sentinel-2 imagery. International Journal of Geomate, v. 14, p. 42-51, 2018. DOI: https://doi.org/10.21660/2018.45.7177
NGUYEN, L. D. et al. Mangrove mapping and above-ground biomass change detection using satellite images in coastal areas of Thai Binh Province, Vietnam. [S. l.: s. n.], 2019. DOI: https://doi.org/10.24259/fs.v3i2.7326
OCHOA-GÓMEZ, J. G. et al. Mangrove wetland productivity and carbon stocks in an arid zone of the Gulf of California (La Paz Bay, Mexico). Forest Ecology and Management, v. 442, p. 135-147, 2019. DOI: https://doi.org/10.1016/j.foreco.2019.03.059
PEREA-ARDILA, M. A.; LEAL-VILLAMIL, J.; OVIEDO-BARRERO, F. Caracterización espectral y monitoreo de bosques de manglar con teledetección en el litoral pacífico colombiano: Bajo Baudó, Chocó. La Granja: Revista de Ciencias de la Vida, v. 34, n. 2, p. 27-44, 2021. DOI: https://doi.org/10.17163/lgr.n34.2021.02
ROMAHN DE LA VEGA, C. F.; RAMÍREZ MALDONADO, H.; TREVIÑO GARCÍA, J. L. Dendrometry. Chapingo: Universidad Autónoma Chapingo, 1994.
SANTA, V. et al. Determination of the correlation between biomass data obtained in the field and NDVI obtained by remote sensing along the Chucul stream (Pcia. Córdoba). [S. l.: s. n.], 2013.
SANTOS, H. V. V. S. S. et al. Allometric models for estimating the aboveground biomass of the mangrove Rhizophora mangle. Brazilian Journal of Oceanography, v. 65, n. 1, p. 44-53, 2017. DOI: https://doi.org/10.1590/s1679-87592017127006501
SUMARGA, E. et al. Maintaining carbon storage does not reduce fish production from mangrove-fish pond system: a case study in Coastal Area of Subang District, West Java, Indonesia. Forests, v. 13, n. 8, p. 1308, 2022. DOI: https://doi.org/10.3390/f13081308
THUY, H. L. T. T. et al. Using sentinel image data and plot survey for the assessment of biomass and carbon stock in coastal forests of Thai Binh province, Vietnam. Applied Ecology & Environmental Research, v. 18, n. 6, 2020. DOI: https://doi.org/10.15666/aeer/1806_74997514
WAHLANG, R.; CHATURVEDI, S. S. Relationship between above-ground biomass and different vegetation indices of forests of Ri-Bhoi District, Meghalaya, India. International Journal of Engineering and Technical Research, v. 9, 2020. DOI: https://doi.org/10.17577/IJERTV9IS050128
WINARSO, G. et al. Mangrove above ground biomass estimation using combination of Landsat 8 and ALOS PALSAR data. International Journal of Remote Sensing and Earth Sciences, v. 12, n. 2, p. 85-96, 2015. DOI: https://doi.org/10.30536/j.ijreses.2015.v12.a2687
Téléchargements
Publié-e
Comment citer
Numéro
Rubrique
Licence
(c) Tous droits réservés Ciência Florestal 2025
Cette œuvre est sous licence Creative Commons Attribution 4.0 International.
A CIÊNCIA FLORESTAL se reserva o direito de efetuar, nos originais, alterações de ordem normativa, ortográfica e gramatical, com vistas a manter o padrão culto da lingua, respeitando, porém, o estilo dos autores.
As provas finais serão enviadas as autoras e aos autores.
Os trabalhos publicados passam a ser propriedade da revista CIÊNCIA FLORESTAL, sendo permitida a reprodução parcial ou total dos trabalhos, desde que a fonte original seja citada.
As opiniões emitidas pelos autores dos trabalhos são de sua exclusiva responsabilidade.
