caa a22 4500 445893052 CHVBK 20180317145622.0 cr unu---uuuuu 170323e20110701xx s 000 0 eng 10.1007/s10750-011-0673-9 doi (NATIONALLICENCE)springer-10.1007/s10750-011-0673-9 Prediction of marine species distribution from presence-absence acoustic data: comparing the fitting efficiency and the predictive capacity of conventional and novel distribution models [Elektronische Daten] [A. Palialexis, S. Georgakarakos, I. Karakassis, K. Lika, V. Valavanis] The accurate representation of species distribution derived from sampled data is essential for management purposes and to underpin population modelling. Additionally, the prediction of species distribution for an expanded area, beyond the sampling area can reduce sampling costs. Here, several well-established and recently developed habitat modelling techniques are investigated in order to identify the most suitable approach to use with presence-absence acoustic data. The fitting efficiency of the modelling techniques are initially tested on the training dataset while their predictive capacity is evaluated using a verification set. For the comparison among models, Receiver Operating Characteristics (ROC), Kappa statistics, correlation and confusion matrices are used. Boosted Regression Trees (BRT) and Associative Neural Networks (ASNN), which are both within the machine learning category, outperformed the other modelling approaches tested. Springer Science+Business Media B.V., 2011 Species distribution models nationallicence Species distribution predictions nationallicence Habitat modelling nationallicence Models comparison nationallicence Geostatistics nationallicence Spatial autocorrelation nationallicence Palialexis A. Department of Biology, University of Crete, Vassilika Vouton, P.O. Box 2208, 71 409, Heraklion, Crete, Greece aut Georgakarakos S. Department of Marine Sciences, University of the Aegean, University Hill, 81 100, Mytilini, Lesvos, Greece aut Karakassis I. Department of Biology, University of Crete, Vassilika Vouton, P.O. Box 2208, 71 409, Heraklion, Crete, Greece aut Lika K. Department of Biology, University of Crete, Vassilika Vouton, P.O. Box 2208, 71 409, Heraklion, Crete, Greece aut Valavanis V. Marine GIS Lab, Hellenic Centre for Marine Research, P.O. Box 2214, 71 003, Heraklion, Crete, Greece aut Hydrobiologia Springer Netherlands 670/1(2011-07-01), 241-266 0018-8158 670:1<241 2011 670 10750 https://doi.org/10.1007/s10750-011-0673-9 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s10750-011-0673-9 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Palialexis A. Department of Biology, University of Crete, Vassilika Vouton, P.O. Box 2208, 71 409, Heraklion, Crete, Greece aut NATIONALLICENCE 700 1- Georgakarakos S. Department of Marine Sciences, University of the Aegean, University Hill, 81 100, Mytilini, Lesvos, Greece aut NATIONALLICENCE 700 1- Karakassis I. Department of Biology, University of Crete, Vassilika Vouton, P.O. Box 2208, 71 409, Heraklion, Crete, Greece aut NATIONALLICENCE 700 1- Lika K. Department of Biology, University of Crete, Vassilika Vouton, P.O. Box 2208, 71 409, Heraklion, Crete, Greece aut NATIONALLICENCE 700 1- Valavanis V. Marine GIS Lab, Hellenic Centre for Marine Research, P.O. Box 2214, 71 003, Heraklion, Crete, Greece aut NATIONALLICENCE 773 0- Hydrobiologia Springer Netherlands 670/1(2011-07-01), 241-266 0018-8158 670:1<241 2011 670 10750 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer