The Marine Spatial Classification and the Identification of Priority Conservation Areas (PCAs) for Marine Biodiversity Conservation - A Case Study of the Offshore China

Journal Article

Title: The Marine Spatial Classification and the Identification of Priority Conservation Areas (PCAs) for Marine Biodiversity Conservation - A Case Study of the Offshore China
Publication Date:
November 01, 2015
Journal: Ocean & Coastal Management
Volume: 116
Pages: 224-236
Publisher: Elsevier

Document Access

Website: External Link

Citation

Hao, H.; Bin, C.; Jinlan, L. (2015). The Marine Spatial Classification and the Identification of Priority Conservation Areas (PCAs) for Marine Biodiversity Conservation - A Case Study of the Offshore China. Ocean & Coastal Management, 116, 224-236.
Abstract: 

In order to effectively use limited funds and resources for conservation of biodiversity, the most valuable areas and contents have to be identified. Therefore, it is essential to identify the priority conservation areas (PCAs) and to explore the maximum conservation benefits for biodiversity conservation. The Convention on Biological Diversity (CBD) recommends that countries should conduct ‘Ecologically or Biologically Significant Marine Areas (EBSAs) identification’, and adopt a scheme of using scientific criteria to identify the EBSAs, but in China Offshore Areas, this kind of work almost does not exist. This paper focuses on the method and application of PCAs identification in Offshore China. The first step is to carry out marine spatial classification according to biogeographical factors, and then to discuss the PCAs identification in regard to marine biodiversity in species, community and ecosystem levels, finally to take Offshore China as a case study. Through marine spatial classification, Offshore China is divided into 5 biological regions by climate and geography differences, and 12 ecological regions by typical, ecological and administrative factors, and 98 biogeographical units by biogeographical factors. As a result, among 98 geographical units, 43 units are identified as PCAs, 31 units are PCAs at focal level, 16 units are PCAs at community level, and 15 units are PCAs at ecosystem level.

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