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An alternative aggregate preference ranking algorithm to assess environmental effects on macrobenthic abundance in coastal water

Coastal marine waters are ranked among the most important aquatic ecosystems on earth in terms of ecological and economic significance. Since the Industrial Revolution, human activities have drastically changed coastal marine ecosystems. The development of rules and regulations to protect these ecosystems against human activities requires availability of environmental assessment standard. This necessitates the identification of the key parameters that reflect condition of the coastal water ecosystem. Macrobenthic assemblages are recognized to rapidly respond to changes in the quality of water or habitat. Therefore, it would be useful to study the population of macrobenthos and assess the influential factors on the growth of this species. This study is categorized as multidisciplinary approach which contains two perspectives, ecological and mathematical. In the ecological section, the effect of the water quality parameters (e.g. pH, temperature, dissolved oxygen and salinity) and the sediment characteristics on the macrobenthic abundance is studied. A total of 432 samples were collected and analyzed from four touristic costal locations (at various distances form the coast) of Penang National Park to investigate the spatial change of macrobenthic assemblage. In a mathematical perspective, this paper pursues a new algorithm based on the performance evaluation methods. For this purpose, first, Data Envelopment Analysis (DEA) is employed to evaluate a group of Decision Making Units (DMUs). Consequently, inputs of the mentioned DMUs are considered as alternatives (or candidates), and using a modified DEA model that is categorized as aggregating preference ranking method, the influence of inputs in efficiency of DMUs is investigated.