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Recognition of co-existence pattern of salt marshes and mangroves for littoral forest restoration
Institution:1. School of Resources, Environment and Materials, Guangxi University, 530004 Nanning, China;2. State Key Laboratory of Pollution Control and Resources Reuse, School of the Environment, Nanjing University, Nanjing 210023, China;1. Programa de Pós-Graduação em Sensoriamento Remoto, Universidade Federal do Rio Grande do Sul, 91501-970, Porto Alegre, Brazil;2. Centro Polar e Climático, Instituto de Geociências, Universidade Federal do Rio Grande do Sul, 91501-970, Porto Alegre, Brazil;3. Departamento de Geografia, Instituto de Geociências, Universidade Federal do Rio Grande do Sul, 91501-970, Porto Alegre, Brazil;4. Centro de Estudos Geográficos, Instituto de Geografia e Ordenamento do Território, Universidade de Lisboa, 1600-276, Lisboa, Portugal;5. Instituto Federal de Educação, Ciência e Tecnologia do Rio Grande do Sul – Campus Porto Alegre, 90030-040, Porto Alegre, Brazil;6. Departamento de Geociências, Universidade Federal de Santa Maria, 97105-900, Santa Maria, Brazil;1. School of Surveying and Built Environment, University of Southern Queensland, Toowoomba, Queensland 4350, Australia;2. Future Regions Research Centre, Federation University Australia, Churchill, Victoria 3842, Australia;1. School of Technology, Beijing Forestry University, 100083 Beijing, China;2. BFU Research Center for Biodiversity Intelligent Monitoring, 100083 Beijing, China;3. Key Laboratory of Forestry Equipment and Automation National Forestry and Grassland Administration, 100083 Beijing, China;1. Instituto Tecnologico Metropolitano, Grupo de Maquinas inteligentes y reconocimiento de patrones, Medellín, Antioquia, Colombia;2. Universidad EAFIT, Medellín, Antioquia, Colombia
Abstract:Climate-change driven sea level rise causes a increase in salinity in coastal wetlands accelerating the alteration of the species composition. It triggers the gradual extinction of species, particularly the mangrove population which is intolerant of excessive salinity. Thus despite being crucial to a wide range of ecosystem services, mangroves have been identified as a vulnerable coastal biome. Hence restoration strategy of mangroves is undergoing rigorous research and experiments in literature at an interdisciplinary level. From a data-driven perspective, analysis of mangrove occurrence data could be the key to comprehend and predict mangrove behavior along different environmental parameters, and it could be important in formulating management strategy for mangrove rehabilitation and restoration. As salt marshes are the natural salt-accumulating halophytes, mitigating excessive salinity could be achieved by incorporating salt-marshes in mangrove restoration activities. This study intends to find a novel restoration strategy by assessing the frequent co-existence status of salt marshes, with the mangroves, and mangrove associates in different zones of degraded mangrove patches for species-rich plantation. To achieve this, we primarily design a novel methodological framework for the practice of knowledge discovery concerning the coexistence pattern of salt marshes, mangroves, and mangrove associates along with environmental parameters using a data mining paradigm of association rule mining. The proposed approach has the capability to uncover underlying facts and forecast likely facts that could automate the study in the field of ecological research to comprehend the occurrence of inter-species relationships. Our findings are based on published data gathered on the Sundarban Mangrove Forest, one of the world’s most important littoral forests. The existing literature reinforces the findings that include all the sets of frequently co-occurring mangroves, their associates, and salt marshes along the salinity gradient of coastal Sundarbans. A detailed understanding of the occurrence patterns of all these, along with the environmental variables, would be able to promote decision-making strategy. This framework is effective for both academia and stakeholders, especially the foresters/ conservation planners, to regulate the spread of salt marshes and the restoration of mangroves as well.
Keywords:Salt marsh and mangrove  Co-occurrence  Prediction  Data mining model  Rule mining  SPSS validation
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