Scientific Journal Of King Faisal University
Basic and Applied Sciences

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Scientific Journal of King Faisal University / Basic and Applied Sciences

The Effectiveness of the Metric Index of Biological Integration Using the Principal Component Analysis to Assess the Environment of Marshes Al-Chybayish in Dhi Qar, Iraq

(Ali Taha Yaseen, Falah Maaruf Mutlak and Abdullah Najem Abood)

Abstract

Biological monitoring and evaluation have gained a substantial ground because they provide a mechanism to evaluate the condition of water bodies directly and analyse the causes of their degradation. This then leads to the ability to define the measurements in order to achieve conservation goals or environmental restoration and evaluate the effectiveness of management decisions. Fish were used as bioindicators for the environmental assessment using the Index of Biological Integration (IBI). The effectiveness of the metrics used in the index was tested using principal components analysis (PCA). With the aim of studying the water quality of Chybayish marshes, the efficiency of the fourteen metrics elected in this paper were checked by an eigenvalue extracted from the PCA technique. 22 species of freshwater fish including 14 native species and eight exotic species were caught. The index was divided into three groups: the first was characterised by the abundance of native species with considerable values of the index of richness and monthly abundance, and the second group was comprised of the tolerant species and the percentage of the exotic species, whereas the omnivore and herbivore species occupied the third group. The value of the index reached 47.44%, and the marshes of Al-Chybayish were classified within the range of moderate environments. PCA technique showed the effectiveness and the contribution percentages of index metrics of the IBI. This tool has helped to better explain the potential factors that affect water quality, and thus helped with reliable management of water resources.

KEYWORDS
bioindicators, fish assemblage, fish environment, multivariate technique, water

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