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      How to develop a comprehensive Mangrove Quality Index?

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          Abstract

          Currently, the available indices to measure mangrove health are not comprehensive. An integrative ecological-socio economic index could give a better picture of the mangrove ecosystem health. This method explored all key biological, hydrological, ecological and socio-economic variables to form a comprehensive mangrove quality index. A total of 10 out of 43 variables were selected based on principal component analysis (PCA). They are aboveground biomass, crab abundance, soil carbon, soil nitrogen, number of phytoplankton species, number of diatom species, dissolved oxygen, turbidity, education level and fishing time spent by fishers. Two types of indices were successfully developed to indicate the health status viz., (1) Mangrove quality index for a specific category (MQIS i ) and, (2) Overall mangrove quality index ( MQI) to reflect the overall health status of the ecosystem. The indices for the five different categories were mangrove biotic integrity index ( M Q I S 1 ), mangrove soil index ( M Q I S 2 ), marine-mangrove index ( M Q I S 3 ), mangrove-hydrology index ( M Q I S 4 ) and mangrove socio-economic index ( M Q I S 5 ). The quality of the mangroves was classified from 1 to 5 viz. 1 (worst), 2 (bad), 3 (moderate), 4 (good), 5 (excellent). These MQI class could reflect the quality of mangrove forest which could be managed with the objective of improving its quality. Advantages of this method include:

          • PCA to select metrics from ecological-socioeconomic variables

          • Formulation of MQI based on selected metrics

          • Comprehensive index to classify mangrove ecosystem health

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          Applying remote sensing techniques to monitor shifting wetland vegetation: A case study of Danshui River estuary mangrove communities, Taiwan

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            TESTING THE FLORISTIC QUALITY ASSESSMENT INDEX AS AN INDICATOR OF WETLAND CONDITION

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              Mapping mangrove changes in the Matang Mangrove Forest using multi temporal satellite imageries

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                Author and article information

                Contributors
                Journal
                MethodsX
                MethodsX
                MethodsX
                Elsevier
                2215-0161
                20 June 2019
                2019
                20 June 2019
                : 6
                : 1591-1599
                Affiliations
                [a ]Faculty of Forestry, Universiti Putra Malaysia, 43400, UPM Serdang, Selangor, Malaysia
                [b ]Faculty of Agriculture, Universiti Putra Malaysia, 43400, UPM Serdang, Selangor, Malaysia
                [c ]Department of Statistics, Faculty of Mathematics and Natural Science, Bogor Agricultural University, Indonesia
                [d ]Laboratory of Marine Biotechnology, Institute of Bioscience, Universiti Putra Malaysia, 43400, UPM Serdang, Selangor, Malaysia
                [e ]Institute of Tropical Forestry and Forest Product (INTROP), Universiti Putra Malaysia, 43400, UPM Serdang, Selangor, Malaysia
                [f ]Department of Biological Sciences, Faculty of Science, King Abdul Aziz University, 21589, Jeddah, Saudi Arabia
                [g ]Faculty of Economics and Management, Universiti Putra Malaysia, 43400, UPM Serdang, Selangor, Malaysia
                Author notes
                [* ]Corresponding author. f_hanum@ 123456upm.edu.my
                Article
                S2215-0161(19)30171-2
                10.1016/j.mex.2019.06.014
                6612797
                31321213
                a453a20f-8f64-45af-a998-e0343765e7de
                © 2019 The Authors

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

                History
                : 17 May 2019
                : 15 June 2019
                Categories
                Environmental Science

                how to develop a comprehensive mangrove quality index?,mangrove health,pca,indicator,formulation

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