MEPS Marine Ecology Progress Series Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsTheme Sections MEPS 316:69-83 (2006) - doi:10.3354/meps316069 Predicting macrofaunal species distributions in estuarine gradients using logistic regression and classification systems J. Ellis1,*, T. Ysebaert2, T. Hume3, A. Norkko3, T. Bult4, P. Herman2, S. Thrush3, J. Oldman3 1Crydium Group Ltd, 10 Linden Place, St John’s, Newfoundland A1B 2S8, Canada 2Netherlands Institute of Ecology, Centre for Estuarine and Coastal Ecology, PO Box 140, 4400 AC Yerseke, The Netherlands 3National Institute of Water and Atmospheric Research, PO Box 11-115, Hamilton, New Zealand 4Netherlands Institute for Fisheries Research, PO Box 68 1970 AB, IJmuiden, The Netherlands *Email: jellis.ca@gmail.com ABSTRACT: There is a growing need to predict ecological responses to long-term habitat change. However, statistical models for marine soft-substratum ecosystems are limited, and consequently there is a need for the development of such models. In order to assess the utility of statistical modelling approaches for predicting likely changes in species distributions under varying environmental conditions, we tested the utility of logistic modelling and classification approaches. We successfully developed models relating the presence/absence of common intertidal macrofauna to changing environmental variables such as sediment characteristics, depth/elevation, tidal currents and wind-wave (i.e. wind-generated wave activity) disturbance. The final model for each species contained between 1 and 6 variables, where the percentage correctly predicted was moderate to high, ranging from 59 to 97%. We were also able to identify relationships between higher level variables such as estuary type, basin morphometry and catchment-draining processes in driving macrobenthic community composition; however, we were unable to fully test the utility of the classification approach due to differences in the scale at which the macrobenthic data was collected and the scale of the higher level physical variables. These models were developed and tested using data that covered a range of environmental conditions in 5 estuaries in New Zealand. Such broad-scale statistical models play a critical role in our understanding of the likely effects of large-scale habitat change. However, a greater understanding of the fine-scale mechanistic controls on species distributions such as life-history characteristics, density information and biotic interactions would potentially lead to the development of more sensitive models. KEY WORDS: Logistic regression · Statistical modelling · Classification systems · Benthic macrofauna · Sedimentation · Estuary · Macroecology · New Zealand Full text in pdf format PreviousNextExport citation RSS - Facebook - Tweet - linkedIn Cited by Published in MEPS Vol. 316. Online publication date: July 03, 2006 Print ISSN: 0171-8630; Online ISSN: 1616-1599 Copyright © 2006 Inter-Research.
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