4.7 Article

Is the benthic index AMBI impervious to seasonality and data transformations while evaluating the ecological status of an anthropized monsoonal estuary?

期刊

OCEAN & COASTAL MANAGEMENT
卷 186, 期 -, 页码 -

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.ocecoaman.2019.105080

关键词

Multivariate analyses; Macrobenthos; Tropical estuary; Ecological group; India

资金

  1. Council of Scientific and Industrial Research (CSIR), India

向作者/读者索取更多资源

Benthic indices are a potential measure of a system's ecological quality status. It is vital for an efficient index to distinguish the anthropogenic effects from the natural stress associated with seasonality, especially in complex ecosystems such as the tropical monsoonal estuaries. AZTI's Marine Biotic Index (AMBI), one of the most successful indices, relies on the distribution of soft-bottom macrobenthic communities into five different ecological groups (EGs) according to their sensitivity to stress. The AMBI was employed in the anthropized Ulhas estuary (India) to test its vulnerability to seasonality. Also it was endeavored in this study to test whether data transformations enhanced the efficiency of AMBI. AMBI values obtained during monsoon failed to distinguish between differently impacted stations in the major stretch of the estuary due to the uniformly dominant occurrence of Namalycastis ouanaryensis, an EG IV species with affinity for low salinity. The AMBI successfully evaluated the status of the estuary during the non-monsoonal seasons whereas it failed to perform well during the monsoon as it either underestimated or overestimated the ecological quality status of >55% of the stations. The results obtained by averaging the AMBI scores of the non-monsoonal seasons gave an accurate ecological status of the estuary. A good level of agreement between all the applied transformations implied that the data transformations did not improve the AMBI efficiency. Conversely, AMBI based on untransformed data indicated a stronger correlation with the contamination proxies than those derived from various data transformations.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据