Spatial efficiency of protected mangrove areas in Madagascar

Chao Fan; He Xu; Xiyong Hou

doi:10.1016/j.jenvman.2022.116568

Spatial efficiency of protected mangrove areas in Madagascar

J Environ Manage. 2023 Jan 1;325(Pt A):116568. doi: 10.1016/j.jenvman.2022.116568. Epub 2022 Oct 28.

Authors

Chao Fan¹, He Xu¹, Xiyong Hou²

Affiliations

¹ Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai, 264003, China; University of Chinese Academy of Sciences, Beijing, 100049, China; Key Laboratory of Coastal Environmental Processes and Ecological Remediation, Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai, 264003, China; Shandong Key Laboratory of Coastal Environmental Processes, Yantai, Shandong, 264003, PR China.
² Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai, 264003, China; Key Laboratory of Coastal Environmental Processes and Ecological Remediation, Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai, 264003, China; Shandong Key Laboratory of Coastal Environmental Processes, Yantai, Shandong, 264003, PR China. Electronic address: xyhou@yic.ac.cn.

PMID: 36419301
DOI: 10.1016/j.jenvman.2022.116568

Abstract

Protected Areas (PAs) are an important nature-based solution for mangrove conservation and rehabilitation. We evaluated spatial effectiveness of PAs for mangroves toward achieving Global Conservation Targets (GCTs). The hypothesis for this study was that PAs with different attributes have insignificant effects on mangrove conservation. We assessed the proportions of the most vulnerable mangroves inside PAs, and focused on a typical mangrove country (Madagascar). First, based on remote sensing technology and big data in Google Earth Engine (GEE), we identified the exposure location of mangroves, and determined the environmental factors significantly influencing mangrove distribution. Then, Vulnerability Assessment and Hot-Spot Analysis models were used to measure spatial vulnerability and hotspots of those values, respectively. Finally, we implemented the statistics for the most vulnerable mangroves inside PAs. It was found that: i. Mangroves were mainly abundant in west and east coasts with low latitudes, and the most typical environmental factor influencing mangrove distribution was elevation and; ii. PAs sheltered 486.18 km² (22.16%) of the most vulnerable mangroves in Madagascar. Overall, PAs in Madagascar failed to match 30% of spatial requirements proposed by GCTs (A key proportion of spatial requirements used to reverse trends in biodiversity loss). This study provides a quantitative paradigm for verifying the spatial efficiency of PAs, and will inform local decision-makers on places where mangroves are facing adaption loss to optimize mangrove conservation in future.

Keywords: Coastal area; Google earth engine; Madagascar; Mangrove; Protected areas; Vulnerability index.

MeSH terms

Biodiversity*
Madagascar
Remote Sensing Technology*