Abstract
Mangroves are highly productive forest ecosystems recognized for several ecosystem services like carbon sequestration and coastal protection that can help in climate change adaptation and mitigation. Globally, mangrove forests have decreased and have become fragmented, especially in Southeast Asia where conversion to aquaculture ponds (AP) was the major driver of loss. When disturbed, mangroves can naturally recolonize their habitat. However, documentation and assessment of natural mangrove recolonization in former AP are largely unreported. Hence, in this study, we developed a methodology that detected and mapped mangroves in AP in Panguil Bay, southern Philippines. Using Landsat data and Google Earth Engine (GEE), we analyzed spatiotemporal mangrove distribution and extent in AP from 1993 to 2020. In general, the increase in mangrove cover was directly correlated to the decrease in AP. However, different rates and patterns of mangrove colonization in different periods were observed. Mangrove-recolonized ponds (MRPs) were ca. 25% (10.24 km2) of the total mangrove area (40.20 km2) in 2020. To our knowledge, this study showed the first map** of mangrove recolonization in AP in the Philippines. The developed methodology used open access Landsat data on a cloud-based processing platform, which can be replicated in other regions for large-scale mangrove scenario planning and policy-making. Upscaling the developed methodology can provide national-level MRP information that can be used for evaluating the success of mangrove rehabilitation programs.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Achanta R, Susstrunk S (2017) Superpixels and polygons using simple non-iterative clustering. In: 2017 IEEE conference on computer vision and pattern recognition (CVPR), pp 4895–4904. https://doi.org/10.1109/CVPR.2017.520
Asian Development Bank (ADB) (1999) Program performance audit report on the fisheries sector program (loans 971-PHI[SF]/972-PHI) in the Philippines. http://www.adb.org.ph
Avtar R, Navia M, Sassen J, Fujii M (2021) Assessment of changes in mangrove ecosystems in the Ba and Rewa deltas, Fiji, and their impacts using information from multiple sources. Coast Eng J 63(3). https://doi.org/10.1080/21664250.2021.1932332. https://www.tandfonline.com/doi/full/10.1080/21664250.2021.1932332
Azanza RV, Aliño PM, Cabral RB, Juinio-Meñez MA, Pernia EM, Mendoza RU, Siriban CS (2017) Valuing and managing the Philippines’ marine resources toward a prosperous ocean-based blue economy. Public Policy 18:1–26
Baloloy AB, Blanco AC, Sta. Ana RRC, Nadaoka K (2020) Development and application of a new mangrove vegetation index (MVI) for rapid and accurate mangrove map**. ISPRS J Photogramm Remote Sens 166:95–117. https://doi.org/10.1016/j.isprsjprs.2020.06.001
Boco SR, Metillo EB, Papa RDS (2014) Abundance, size and symbionts of Catostylus sp. Medusae (Scyphozoa, Rhizostomeae) in Panguil Bay, northern Mindanao, Philippines. Philipp J Syst Biol 8:19
Bryan-Brown DN, Connolly RM, Richards DR, Adame F, Friess DA, Brown CJ (2020) Global trends in mangrove forest fragmentation. Sci Rep 10(1):1–8
Climate Change Commission (2021) Republic of the Philippines Nationally Determined Contribution communicated to the UNFCCC on 15 April 2021. https://www4.unfccc.int/sites/ndcstaging/PublishedDocuments/Philippines%20First/Philippines%20-%20NDC.pdf
dos Reis-Neto AS, Meireles AJA, Cunha-Lignon M (2019) Natural regeneration of the mangrove vegetation on abandoned salt ponds in Ceará, in the semi-arid region of northeastern Brazil. Diversity 11(2):27. https://doi.org/10.3390/d11020027
Duke NC (2001) Gap creation and regenerative processes driving diversity and structure of mangrove ecosystems. Wetl Ecol Manag 9(3):267–279. https://doi.org/10.1023/A:1011121109886
Duncan C, Primavera JH, Pettorelli N, Thompson JR, Loma RJA, Koldewey HJ (2016) Rehabilitating mangrove ecosystem services: a case study on the relative benefits of abandoned pond reversion from Panay Island, Philippines. Mar Pollut Bull 109(2):772–782. https://doi.org/10.1016/j.marpolbul.2016.05.049
Duncan C, Owen HJF, Thompson JR, Koldewey HJ, Primavera JH, Pettorelli N (2018) Satellite remote sensing to monitor mangrove forest resilience and resistance to sea level rise. Methods Ecol Evol 9(8):1837–1852. https://doi.org/10.1111/2041-210X.12923
Eastman JR, Crema SC, Sangermano F, Cunningham S, ** of aquaculture and coastal habitats in Thailand, Cambodia and Vietnam. In: Aquaculture and Coastal Habitats Report No. 1. Clark Labs
Ferrer AJG, Hopanda JC, Orquejo MQ, Moscoso ADE, Sadaba RB (2016) Reverting disused fishpond lease agreement areas to mangrove forests in region VI (Western Visayas), Philippines. In: Olewiler N, Francisco HA, Ferrer AJG (eds) Marine and coastal ecosystem valuation, institutions, and policy in Southeast Asia. Springer, Berlin, pp 201–224. https://doi.org/10.1007/978-981-10-0141-3_10
Feyisa GL, Meilby H, Fensholt R, Proud SR (2014) Automated water extraction index: a new technique for surface water map** using Landsat imagery. Remote Sens Environ 140:23–35. https://doi.org/10.1016/j.rse.2013.08.029
Garcia KB, Malabrigo PL, Gevaña DT (2014) Philippines’ mangrove ecosystem: status, threats and conservation. In: Mangrove ecosystems of Asia. Springer, New York, pp 81–94
Giri C (2016) Observation and monitoring of mangrove forests using remote sensing: opportunities and challenges. Remote Sens 8(9):783. https://doi.org/10.3390/rs8090783
Goldberg L, Lagomasino D, Thomas N, Fatoyinbo T (2020) Global declines in human-driven mangrove loss. Glob Chang Biol 26(10):5844–5855. https://doi.org/10.1111/gcb.15275
Gorelick N, Hancher M, Dixon M, Ilyushchenko S, Thau D, Moore R (2017) Google earth engine: planetary-scale geospatial analysis for everyone. Remote Sens Environ 202:18–27. https://doi.org/10.1016/j.rse.2017.06.031
Gracia A, Rangel-Buitrago N, Oakley JA, Williams AT (2018) Use of ecosystems in coastal erosion management. Ocean Coast Manage 156:277–289. https://doi.org/10.1016/j.ocecoaman.2017.07.009
Herr D, Landis E (2016) Coastal blue carbon ecosystems. Opportunities for Nationally Determined Contributions. Policy Brief. IUCN and TNC, Gland, and Washington, DC. https://portals.iucn.org/library/sites/library/files/documents/Rep-2016-026-En.pdf
Hochard JP, Hamilton S, Barbier EB (2019) Mangroves shelter coastal economic activity from cyclones. Proc Natl Acad Sci 116(25):12232–12237. https://doi.org/10.1073/pnas.1820067116
Hong HTC, Avtar R, Fujii M (2019) Monitoring changes in land use and distribution of mangroves in the southeastern part of the Mekong River Delta, Vietnam. Trop Ecol 60(4):552–565. https://doi.org/10.1007/s42965-020-00053-1
Inoue T (2018) Carbon sequestration in mangroves. In: Kuwae T, Hori M (eds) Blue carbon in shallow coastal ecosystems: carbon dynamics, policy, and implementation. Springer, Berlin, pp 73–99. https://doi.org/10.1007/978-981-13-1295-3_3
Jimenez JU, de Guzman AB, Jimenez CR, Acuna RE (2009) Panguil Bay fisheries over the decades: status and management challenges. J Environ Aquat Resour 1(1):15–31
Lewis RR (2005) Ecological engineering for successful management and restoration of mangrove forests. Ecol Eng 24(4):403–418. https://doi.org/10.1016/j.ecoleng.2004.10.003
Long J, Napton D, Giri C, Graesser J (2014) A map** and monitoring assessment of the Philippines’ mangrove forests from 1990 to 2010. J Coast Res 30(2):260–271
Macabuac MCF (2005) After the aquaculture bust: impacts of the globalized food chain on poor Philippine fishing households. Doctoral dissertation, Virginia Tech
Menéndez P, Losada IJ, Beck MW, Torres-Ortega S, Espejo A, Narayan S, Díaz-Simal P, Lange G-M (2018) Valuing the protection services of mangroves at national scale: the Philippines. Ecosyst Serv 34:24–36. https://doi.org/10.1016/j.ecoser.2018.09.005
Nagelkerken I, Blaber SJM, Bouillon S, Green P, Haywood M, Kirton LG, Meynecke J-O, Pawlik J, Penrose HM, Sasekumar A, Somerfield PJ (2008) The habitat function of mangroves for terrestrial and marine fauna: a review. Aquat Bot 89(2):155–185. https://doi.org/10.1016/j.aquabot.2007.12.007
Newcomer ME, Kuss AJM, Ketron T, Remar A, Choksi V, Skiles JW (2014) Estuarine sediment deposition during wetland restoration: a GIS and remote sensing modeling approach. Geocarto Int 29(4):451–467. https://doi.org/10.1080/10106049.2013.798356
Osing PKA, Jondonero MA, Suson P, Guihawan J, Amparado R (2019) Species composition and diversity in a natural and reforested mangrove forests in Panguil Bay, Mindanao, Philippines. J Biodivers Environ Sci 15(3) https://innspub.net/jbes/species-composition-diversity-natural-reforested-mangrove-forests-panguil-bay-mindanao-philippines/
Otsu N (1979) A threshold selection method from gray level histograms. https://doi.org/10.1109/TSMC.1979.4310076
Primavera JH (1995) Mangroves and brackishwater pond culture in the Philippines. In: Asia-Pacific symposium on mangrove ecosystems. Springer, Dordrecht, pp 303–309
Primavera JH (2000) Development and conservation of Philippine mangroves: institutional issues. Ecol Econ 35(1):91–106
Primavera JH, Esteban JMA (2008) A review of mangrove rehabilitation in the Philippines: successes, failures and future prospects. Wetl Ecol Manag 16(5):345–358
Primavera JH, Rollon RN, Samson MS (2011) The pressing challenges of mangrove rehabilitation: pond reversion and coastal protection. Biologica 50:232
Primavera J, Yap W, Savaris J, Loma R, Moscoso A, Coching J, Montilijao C, Poingan R, Tayo I (2014) Manual on mangrove reversion of abandoned and illegal brackishwater fishpond—mangrove manual series no. 2, 1st edn. Zoological Society of London - CMRP Philippines, Inc.
Proisy C, Viennois G, Sidik F, Andayani A, Enright JA, Guitet S, Gusmawati N, Lemonnier H, Muthusankar G, Olagoke A, Prosperi J, Rahmania R, Ricout A, Soulard B, Suhardjono (2018) Monitoring mangrove forests after aquaculture abandonment using time series of very high spatial resolution satellite images: a case study from the Perancak estuary, Bali, Indonesia. Mar Pollut Bull 131:61–71. https://doi.org/10.1016/j.marpolbul.2017.05.056
Richards DR, Friess DA (2016) Rates and drivers of mangrove deforestation in Southeast Asia, 2000–2012. Proc Natl Acad Sci 113(2):344–349. https://doi.org/10.1073/pnas.1510272113
Rivera RR, Mino SA, Lapinig VT, Freitas I (2017) Population diversity of mangrove species in Panguil Bay, Philippines. J High Educ Res Discip 1(1):9–14
Salem ME, Mercer DE (2012) The economic value of mangroves: a meta-analysis. Sustainability 4(3):359–383. https://doi.org/10.3390/su4030359
Salmo SG III, Gianan ELD (2019) Post-disturbance carbon stocks and rates of sequestration: implications on “blue carbon” estimates in Philippine mangroves. Philipp Sci Lett 12:122–132
Salmo SG III, Juanico DEO (2015) An individual-based model of long-term forest growth and carbon sequestration in planted mangroves under salinity and inundation stresses. Int J Philipp Sci Technol 8(2):31–35
Salmo SG III, Lovelock C, Duke NC (2013) Vegetation and soil characteristics as indicators of restoration trajectories in restored mangroves. Hydrobiologia 720(1):1–18. https://doi.org/10.1007/s10750-013-1617-3
Salmo SG III, Malapit V, Garcia MCA, Pagkalinawan HM (2019) Establishing rates of carbon sequestration in mangroves from an earthquake uplift event. Biol Lett 15(3):20180799. https://doi.org/10.1098/rsbl.2018.0799
Samson MS, Rollon RN (2011) Mangrove revegetation potentials of brackish-water pond areas in the Philippines. In: Aquaculture and the environment – a shared destiny. IntechOpen. https://doi.org/10.5772/28222
Song AM, Dressler WH, Satizábal P, Fabinyi M (2021) From conversion to conservation to carbon: the changing policy discourse on mangrove governance and use in the Philippines. J Rural Stud 82:184–195. https://doi.org/10.1016/j.jrurstud.2021.01.008
Stuhler S, Leiterer R, Joerg P, Wulf H, Schaepman M (2016) Generating a cloud-free, homogeneous Landsat-8 mosaic of Switzerland using Google Earth Engine. https://doi.org/10.13140/RG.2.1.2432.0880
Thomas N, Lucas R, Bunting P, Hardy A, Rosenqvist A, Simard M (2017) Distribution and drivers of global mangrove forest change, 1996–2010. PLoS One 12(6):e0179302. https://doi.org/10.1371/journal.pone.0179302
Valiela I, Bowen JL, York JK (2001) Mangrove forests: one of the world's threatened major tropical environments: at least 35% of the area of mangrove forests has been lost in the past two decades, losses that exceed those for tropical rain forests and coral reefs, two other well-known threatened environments. Bioscience 51(10):807–815
van Bijsterveldt CEJ, van Wesenbeeck BK, van der Wal D, Afiati N, Pribadi R, Brown B, Bouma TJ (2020) How to restore mangroves for greenbelt creation along eroding coasts with abandoned aquaculture ponds. Estuar Coast Shelf Sci 235:106576. https://doi.org/10.1016/j.ecss.2019.106576
Wang L, Jia M, Yin D, Tian J (2019) A review of remote sensing for mangrove forests: 1956–2018. Remote Sens Environ 231:111223. https://doi.org/10.1016/j.rse.2019.111223
Wodehouse DCJ, Rayment MB (2019) Mangrove area and propagule number planting targets produce sub-optimal rehabilitation and afforestation outcomes. Estuar Coast Shelf Sci 222:91–102. https://doi.org/10.1016/j.ecss.2019.04.003
Xu H (2006) Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery. Int J Remote Sens 27(14):3025–3033. https://doi.org/10.1080/01431160600589179
Yamazaki D, Ikeshima D, Tawatari R, Yamaguchi T, O’Loughlin F, Neal JC, Sampson CC, Kanae S, Bates PD (2017) A high-accuracy map of global terrain elevations. Geophys Res Lett 44(11):5844–5853. https://doi.org/10.1002/2017GL072874
Yu Z, Di L, Rahman MS, Tang J (2020) Fishpond map** by spectral and spatial-based filtering on Google earth engine: a case study in Singra Upazila of Bangladesh. Remote Sens 12(17):2692. https://doi.org/10.3390/rs12172692
Zhu Z, Woodcock CE (2012) Object-based cloud and cloud shadow detection in Landsat imagery. Remote Sens Environ 118:83–94. https://doi.org/10.1016/j.rse.2011.10.028
Zhu Z, Wang S, Woodcock CE (2015) Improvement and expansion of the Fmask algorithm: cloud, cloud shadow, and snow detection for Landsats 4–7, 8, and sentinel 2 images. Remote Sens Environ 159:269–277. https://doi.org/10.1016/j.rse.2014.12.014
Acknowledgments
We would like to thank the Ministry of Education, Culture, Sports, Science and Technology (MEXT) Japan for the financial support. This study was also supported by the Integrated Research Program for Advancing Climate Models (TOUGOU) Grant Number JPMXD0717935498 from MEXT. We also thank the Philippine Department of Environment and Natural Resources – Region 10 and the National Map** and Resource Information Authority for providing the land cover maps used for the study.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this chapter
Cite this chapter
delos Santos, K.A., Avtar, R., Salmo, S., Fujii, M. (2022). Assessment of Mangrove Colonization of Aquaculture Ponds Through Satellite Image Analysis: Implications for Mangrove Management. In: Dasgupta, R., Hashimoto, S., Saito, O. (eds) Assessing, Map** and Modelling of Mangrove Ecosystem Services in the Asia-Pacific Region. Science for Sustainable Societies. Springer, Singapore. https://doi.org/10.1007/978-981-19-2738-6_3
Download citation
DOI: https://doi.org/10.1007/978-981-19-2738-6_3
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-19-2737-9
Online ISBN: 978-981-19-2738-6
eBook Packages: Earth and Environmental ScienceEarth and Environmental Science (R0)