Abstract
This study aimed to develop a practical approach to identify the priority areas with ecological significance along highly human disturbed coastal areas. Field surveys were used to assess and complement to the results of the remote sensing (RS)-based analysis. The RS-based biodiversity hotspot (BH) identification process was accomplished in three steps. The lands with native vegetation cover, including the national natural reserve lands, were first selected as the baseline BHs (BBHs). Then, after assigning resistance coefficients to each land use, the least accumulative cost (LAC) of the BBHs was calculated by distance analysis, while the normalized differential vegetation index (NDVI) from the Landsat Thematic Mapper was reclassified into 20 grades based on the Euclidean distance to the main anthropogenic sources. Finally, the RS-based BH identification was realized through the logistic calculation of LAC less than a series of thresholds and NDVI more than 10. While the field survey-based BH identification was through the logistic calculation between HM potential ecological risks of low to moderate and BHs acquired by NDVI-based integrated assessments. The results proved that RS-based analysis could be an important surrogate for necessary field surveys to manage BHs along coasts.
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Acknowledgement
This work is supported by the National 973 Key Project of Basic Science Research (no. 2012CB430400), the Natural Scientific Foundation of China (no. 41101172, 41201179), and Shanghai Universities First-class Disciplines Project of Fisheries.
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Li, N., Yang, W., Xu, L. et al. Two comparative approaches to identify the conservation priority areas impacted by heavy metals on Yellow Sea coasts. J Coast Conserv 21, 177–188 (2017). https://doi.org/10.1007/s11852-016-0488-y
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DOI: https://doi.org/10.1007/s11852-016-0488-y