Cholho Song , Chul-Hee Lim , Hyun-Ah Choi , Whijin Kim , Donguk Han , Mary Tahu Paia , Hyeon Kwon Ahn , Sangin Kang , Woo-Kyun Lee
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引用次数: 0
Abstract
The Solomon Islands requested technical assistance from the Climate Technology Centre and Network (CTCN) to plan Integrated Coastal Zone Management (ICZM). Mangrove ecosystems, which connect terrestrial and ocean ecosystems in the coastal zone, are considered key management targets within ICZM in the Solomon Islands. However, limited spatial data resources for ecological planning of mangrove ecosystems pose a significant challenge to developing effective ICZM. A citizen science approach was employed to map mangrove distribution and related ecosystem services to address this limitation. This study organized a participatory workshop to collect local knowledge about mangrove distribution, which was then compared with established global mangrove distribution datasets. The local knowledge obtained through citizen science was digitized and converted into a hexagonal spatial framework to develop a decision-support map. Each hexagon was assigned a score from 1 to 3 based on the overlap between local and global data, reflecting mangrove density and the priority of ecosystem services. Out of 17,743 hexagons, 1283 were identified as areas with mangrove distribution and ecosystem services, with 363, 569, and 351 hexagons assigned scores of 1, 2, and 3, respectively. The highest-priority areas (score 3), characterized by dense mangrove presence and essential ecosystem services, were primarily located along the coasts of Malaita and Guadalcanal, suggesting their significance for ICZM planning. This study highlights the value of citizen science in supporting ICZM, particularly in data-scarce regions. It demonstrates how integrating local perspectives with global datasets can contribute to more effective and inclusive coastal management in the Solomon Islands.
期刊介绍:
The journal Ecological Informatics is devoted to the publication of high quality, peer-reviewed articles on all aspects of computational ecology, data science and biogeography. The scope of the journal takes into account the data-intensive nature of ecology, the growing capacity of information technology to access, harness and leverage complex data as well as the critical need for informing sustainable management in view of global environmental and climate change.
The nature of the journal is interdisciplinary at the crossover between ecology and informatics. It focuses on novel concepts and techniques for image- and genome-based monitoring and interpretation, sensor- and multimedia-based data acquisition, internet-based data archiving and sharing, data assimilation, modelling and prediction of ecological data.