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Mangroves along the Colombian Caribbean and Pacific coasts are vital ecosystems with numerous environmental, economic, and social benefits. Their dense root systems act as natural buffers, safeguarding coastlines from storms and preserving aquifer integrity. Additionally, mangroves are pivotal in mitigating climate change by efficiently storing carbon, absorbing up to 10 times more than terrestrial ecosystems. Government decision-makers face the challenge of balancing economic development with environmental preservation when approving infrastructure projects. Quantifying the monetary value of mangroves is crucial for assessing potential impacts on these ecosystems. This study used Sentinel-2 composites to train a random forest classifier, identifying and quantifying a total mangrove area of 2756.84 km2 in Colombia by 2020. This information was later used to assess the carbon storage in mangroves for the same year. The estimated value was 96,351.66 ± 13,632.63 kt or 353,610.59 ± 50,031.78 kt CO2. Ultimately, we evaluated two contingents on the mangrove extent: one depicting their disappearance and the other illustrating their growth. These findings underscore the critical importance of mangroves and highlight the need for their conservation and sustainable management to achieve emissions reduction goals by 2030.
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Blanco-Libreros, J. F., Ortiz-Acevedo, L. F., & Urrego, L. E. (2015). Reservorios de biomasa aérea y de carbono en los manglares del golfo de Urabá (Caribe colombiano). Actualidades Biológicas, 37(103), 131-141.
Blanco-Libreros, J. F., & Álvarez-León, R. (2019). Mangroves of Colombia revisited in an era of open data, global changes, and socio-political transition: Homage to Heliodoro Sánchez-Páez. Revista de la Academia Colombiana de Ciencias Exactas, Físicas y Naturales, 43(166), 84-97.
Bunting, P., Rosenqvist, A., Hilarides, L., Lucas, R. M., Thomas, N., Tadono, T., Worthington, T. A., Spalding, M., Murray, N. J., & Rebelo, L.-M. (2022). Global mangrove extent change 1996-2020: Global mangrove watch version 3.0. Remote Sensing, 14(15), 3657. https://doi.org/10.3390/rs14153657
Castellanos-Galindo, G. A., Kluger, L. C., Camargo, M. A., Cantera, J., Pineda, J. E. M., Blanco-Libreros, J. F., & Wolff, M. (2021). Mangrove research in Colombia: Temporal trends, geographical coverage and research gaps. Estuarine and Shelf Science, 248, 106799.
Colombia: CO2 country profile. (n.d.). https://ourworldindata.org/co2/country/colombia (Accessed: November 29, 2023).
Gupta, K., Mukhopadhyay, A., Giri, S., Chanda, A., Majumdar, S. D., Samanta, S., Mitra, D., Samal, R. N., Pattnaik, A. K., & Hazra, S. (2018). An index for discrimination of mangroves from non-mangroves using Landsat 8 OLI imagery. Methods X, 5, 1129-1139.
Howard, J., Hoyt, S., Isensee, K., Telszewski, M., & Pidgeon, E. (2014). Coastal blue carbon: Methods for assessing carbon stocks and emissions factors in mangroves, tidal salt marshes, and seagrasses. Conservation International, Intergovernmental Oceanographic Commission of UNESCO, International Union for Conservation of Nature.
IGAC, Instituto de Hidrología, von Humboldt, I. A., Invemar, Instituto de Investigaciones Científicas-Sinchi, & Instituto de Investigaciones Ambientales del Pacífico. (2007). Ecosistemas continentales, costeros y marinos de Colombia. Imprenta Nacional de Colombia.
Maurya, K., Mahajan, S., & Chaube, N. (2021). Remote sensing techniques: mapping and monitoring of mangrove ecosystem—a review. Complex & Intelligent Systems, 7, 2797-2818.
Leal, M., & Spalding, M. D. (Eds.). (2022). El estado de los manglares del mundo 2022. Global Mangrove Alliance.
Mcleod, E., Chmura, G. L., Bouillon, S., Salm, R., Bjôrk, M., Duarte, C. M., Lovelock, E. C., Schlesinger, W. H., & Silliman, B. R. (2011). A blueprint for blue carbon: toward an improved understanding of the role of vegetated coastal habitats in sequestering CO2. Frontiers in Ecology and the Environment, 9(10), 552-560.
Mejía-Rentería, J. C., Castellanos-Galindo, G. A., Cantera-Kintz, J. R., & Hamilton, S. E. (2018). A comparison of Colombian Pacific mangrove extent estimations: Implications for the conservation of a unique Neotropical tidal forest. Estuarine, Coastal and Shelf Science, 212, 233-240.
Ministerio de Ambiente y Desarrollo Sostenible de Colombia. (2022). Bosques, biodiversidad y servicios ecosistémicos, ecosistemas estratégicos, manglares. https://lc.cx/rBKjLL (Accedido el 28 de octubre de 2023).
Moreno-Muñoz, A. S. (2022). Evaluación de almacenamiento de carbono azul en el ecosistema de manglar del pacífico nariñense [Tesis de Maestría]. Facultad de Ingeniería y Administración, Universidad Nacional de Colombia, Palmira, Colombia.
Mutanga, O., & Kumar, L. (2019). Google Earth Engine applications. Remote Sensing, 11(5), 591. https://doi.org/10.3390/rs11050591
Palacios-Peñaranda, M. L., Cantera-Kintz, J. R., & Peña-Salamanca, E. J. (2019). Carbon stocks in mangrove forests of the Colombian Pacific. Estuarine, Coastal and Shelf Science, 227, 106299.
Perdomo-Trujillo, L. V., Mancera-Pineda, J. E., Medina-Calderón, J. H., Sánchez-Núñez, D. A., & Schnetter, M. L. (2021). Effect of restoration actions on organic carbon pools in the lagoon—Delta Ciénaga Grande de Santa Marta, Colombian Caribbean. Water, 13(9), 1297.
Pérez, J. U., & Giraldo, L. E. U. (2009). Gestión ambiental de los ecosistemas de manglar. Aproximación al caso colombiano. Gestión y Ambiente, 12(2), 57-71.
Pham, T. D., Ha, N. T., Saintilan, N., Skidmore, A., Phan, D. C., Le, N. N., Viet, H. L., Takeuchi, W., & Friess, D. A. (2023). Advances in earth observation and machine learning for quantifying blue carbon. Earth-Science Reviews, 243, 104501.
Pham, T. D., Yokoya, N., Bui, D. T., Yoshino, K., & Friess, D. A. (2019). Remote sensing approaches for monitoring mangrove species, structure, and biomass: Opportunities and challenges. Remote Sensing, 11(3), 230.
Rouse, J. W., Haas, R. H., Schell, J. A., & Deering, D. W. (1974). Monitoring vegetation systems in the great plains with erts. NASA Special Publications, 351(1), 309.
Sánchez-Páez, H., Álvarez-León, R., Guevara-Mancera, O. A., & Ulloa-Delgado, G. (2000). Lineamientos estratégicos para la conservación y uso sostenible de los manglares de Colombia. Proyecto. PD, 171, 91.
Selvaraj, J. J., & Pérez, B. E. G. (2023). An enhanced approach to mangrove forest analysis in the Colombian Pacific Coast using optical and SAR data in Google Earth Engine. Remote Sensing Applications: Society and Environment, 30, 100938.
Shi, T., Liu, J., Hu, Z., Liu, H., Wang, J., & Wu, G. (2016). New spectral metrics for mangrove forest identification. Remote Sensing Letters, 7(9), 885-894.
Snedaker, S. C., & Snedaker, J. G. (1984). The mangrove ecosystem: research methods. Unesco.
Total greenhouse gas emissions, kt of CO2 equivalent, - Colombia. (n.d.). https://data.worldbank.org/indicator/EN.ATM.GHGT.KT.CE?end=2020&locations=CO&name_desc=true&start=1990&view=chart
Tran, T. V., Reef, R., & Zhu, X. (2022). A review of spectral indices for mangrove remote sensing. Remote Sensing, 14(19), 4868.
What is blue carbon? (n.d.). https://www.thebluecarboninitiative.org/about
Xu, H. (2006). Modification of normalized difference water index (NDWI) to enhance open water features in remotely sensed imagery. International Journal of Remote Sensing, 27(14), 3025-3033.
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