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Prediction of macrozoobenthic species distribution in the Korean Saemangeum tidal flat based on a logistic regression model of environmental parameters
Authors:Jongseong Ryu  Hae-Cheol Kim  Jong Seong Khim  Yong Hoon Kim  Jinsoon Park  Daeseok Kang  Jin Hwan Hwang  Chang-Hee Lee  Chul-Hwan Koh
Institution:(1) Office of Policy Research, Korea Ocean Research and Development Institute (KORDI), PO Box 29, Ansan, 425-600, Republic of Korea;(2) I. M. Systems Group at Environmental Modeling Center, National Centers for Environmental Prediction, NOAA, Camp Springs, MD 20746, USA;(3) Division of Environmental Science and Ecological Engineering, Korea University, Seoul, 136-713, Republic of Korea;(4) Applied Science Associates, South Kingstown, RI 02879, USA;(5) School of Earth and Environmental Sciences, Seoul National University, Seoul, 151-742, Republic of Korea;(6) Department of Ecological Engineering, Pukyong National University, Busan, 608-737, Republic of Korea;(7) Department of Civil and Environmental Engineering, Dongguk University, Seoul, 100-715, Republic of Korea;(8) Department of Environmental Engineering and Biotechnology, Myongji University, Yongin, Gyeonggi-do, 449-728, Republic of Korea;
Abstract:This study aims to contribute to the development of heuristic statistical models, which are able to predict benthic macrofaunal responses to environmental gradients in coastal areas, such as tidal flats. Ecological response surfaces were derived for 15 intertidal macrobenthic species, using logistic regression based on three separate environmental parameters (shore level, mud content, and organic content) measured on the tidal flats of the Saemangeum estuary, Korea. The presence/absence of the 15 intertidal macrofauna was accurately predicted from each separate environmental factor in the environmental models, with a prediction accuracy of ~65–92%. Subsequently, geographical comparison was made between the mapped probability surfaces and maps of observed species occurrence. The results indicated that the models developed for different species exhibited a wide variety of functional forms, highlighting potential variability in species response to changes in habitat conditions, even for closely associated species with a similar trophic type. Our modeling approach was capable of predicting macrobenthic species distributions with a relatively high degree of accuracy, although the ecological processes controlling intertidal macrobenthic distribution could not be fully determined. Overall, good agreement between modeling results and field observations, with relatively high concordance regardless of target species, emphasized that such an approach would be of practical use in terms of ecosystem approach to tidal flat management.
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