Karl-Heinz Frommolt, Rolf Bardeli and Michael Clausen (Eds.) Computational bioacoustics for assessing biodiversity BfN - Skripten 234 2008 Computational bioacoustics for assessing biodiversity Proceedings of the International Expert meeting on IT-based detection of bioacoustical patterns, December 7th until December 10th, 2007 at the International Academy for Nature Conservation (INA) Isle of Vilm, Germany Editors: Karl-Heinz Frommolt Rolf Bardeli Michael Clausen Cover picture: Northern part of the lake Parstein – a study site for bioacoustic monitoring (K.-H. Frommolt). The graphics in the left depict a set of features used in bioacoustic pattern recognition algorithms: spectrogram, periodicity features and a resulting automatic segmentation are plotted for the example of a Chaffinch's song (D. Wolff). Editors’ addresses: Dr. Karl-Heinz Frommolt Rolf Bardeli and Prof. Michael Clausen Museum für Naturkunde Institut für Informatik III der Humboldt-Universität zu Berlin Rheinische Friedrich-Wilhelms-Universität Bonn Invalidenstraße 43 Römerstraße 164 10115 Berlin, Germany 53117 Bonn, Germany E-Mail: [email protected] E-Mail: [email protected] Project coordinator BfN: Dr. Horst Freiberg, Federal Agency for Nature Conservation (BfN) Department Z 2.1 ”Nature Conservation Information and Geographical Information” National Focal Point CHM E-Mail: [email protected] BfN-Skripten are not available in book trade but can be downloaded in a pdf version from the internet at: http://www.bfn.de/0502_skripten.html This publication is included in the literature database “DNL-online” (www.dnl-online.de) Publisher: Bundesamt für Naturschutz (BfN) Federal Agency for Nature Conservation Konstantinstrasse 110 53179 Bonn, Germany URL: http://www.bfn.de All rights reserved by BfN The publisher takes no guarantee for correctness, details and completeness of statements and views in this report as well as no guarantee for respecting private rights of third parties. Views expressed in the papers published in this issue of BfN-Skripten are those of the authors and do not necessarily represent those of the publisher. No part of the material protected by this copyright notice may be reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying, recording or by any information storage and retrieval system without written permission from the copyright owner. Printed by the printing office of the Federal Ministry of Environment, Nature Conservation and Nuclear Safety. Printed on 100% recycled paper. Bonn, Germany 2008 Contents Introduction 5 Short term and long term bioacoustic monitoring of the marine environment. Results from NEMO ONDE experiment and way ahead 7 Pavan, G., La Manna, G. , Zardin, F. , Internullo, E., Kloeti, S., Cosentino, G., Speziale. F., Riccobene, G. & the NEMO Collaboration A perennial acoustic observatory in the Antarctic Ocean 15 Kindermann, L., Boebel, O., Bornemann, H., Burkhardt, E., Klinck, H., van Opzeeland, I., Plötz, J. & A.-M. Seibert Probabilistic evaluation of synergetic ultrasound pattern recognition for large scale bat surveys 29 Obrist, M.K., Boesch, R. & P. Flückiger Anurans, the group of terrestrial vertebrates most vulnerable to climate change: a case study with acoustic monitoring in the Iberian Peninsula 43 Márquez, R., Llusia, D., Beltrán, J.F., do Amaral, J.P. & R.G. Bowkers A decade of monitoring frog communities in Northern Australia 53 Grigg, G., McCallum, H. & A. Taylor Automated bioacoustic identification of insects for phytosanitary and ecological applications 59 Chesmore, D. From bird species to individual songs recognition: automated methods for localization and recognition in real habitats using wireless sensor networks 73 Trifa, V. M., Kirschel, A., Yao, Y., Taylor, C. & L. Girod Advantages and disadvantages of acoustic monitoring of birds – realistic scenarios for automated bioacoustic monitoring in a densely populated region 83 Frommolt, K.-H., Tauchert, K.-H. & M. Koch Bird song recognition in complex audio scenes 93 Bardeli, R., Wolff, D. & M.Clausen Techniques for bioacoustic signal detection using image processing 103 Brandes, T.S. Bioacoustic classifier system design as a knowledge engineering problem 111 Huebner, S. Computational methods in analysis of bird song complexity 125 Tanttu, J. T. & J. Turunen Automated monitoring of avian flight calls during nocturnal migration 131 Schrama, T., Poot, M., Robb, M. & H. Slabbekoorn Birds and bats: automatic recording of flight calls and their value for the study of migration 135 Hill, R. & O. Hüppop XBAT: an open-source extensible platform for bioacoustic research and monitoring 143 Figueroa, H. & M. Robbins Agenda of the meeting List of participants 3 4 Introduction From December 7 through 10, 2007, an international expert meeting on IT-based detection of bioacoustic patterns was held at the facilities of the International Academy for Nature Conservation on the Isle of Vilm in the Baltic Sea. The meeting was held under the patronage of the German Federal Agency for Nature Conservation (Bundesamt für Naturschutz, BfN) in the context of a research project on bioacoustic pattern recognition. The progress in information technology during the last years, especially in the field of pattern recognition, opens up important new perspectives for the automated bioacoustic monitoring of a multitude of animal species. The idea of the meeting was to bring together specialists from all over the world, to discuss the potential of IT-based detection of bioacoustic patterns. The topics of the meeting covered both the current knowledge on acoustic pattern recognition in bioacoustic signals and the application of bioacoustic methods for purposes of the monitoring of wild animals. This publication contains expanded versions of the talks given during the meeting, giving an impression of the problems and methods in the field of algorithmic bioacoustics from scientists from Australia, the USA, Italy, Spain, Finland, Switzerland, the UK, the Netherlands and Germany. The articles cover a wide variety of animal species from insects and frogs to birds, from whales to bats. Monitoring locations reach from the densely populated centre of Europe to the out-backs of Australia, from the Mediterranean Sea to Antarctica. In the first presentation, Mapping bioacoustic phenomena over ecologically meaningful spatio-temporal scales, Christopher Clark gave a good overview of the perspective of bioacoustic monitoring for a variety of species from elephants to whales. The following presentations are all focused on different aspects of this general theme. They are characterised by either a certain species or group of species, a special study area, or are dedicated mainly to software systems or algorithms. • Gianni Pavan et al. report on Short term and long term bioacoustic monitoring of the marine environment. Recording from an underwater test site for neutrino detection, investigations into the presence and migration of marine animals in the Mediterranean revealed a more frequent and consistent presence of sperm whales than previously believed. • Lars Kindermann et al. describe a bioacoustics project in a truely adverse environment. A perennial acoustic observatory in the Antarctic Ocean consisting of hydrophones deployed under the ice shelf allows to study the acoustic repertoire of whales and seals. • Martin Obrist et al. give a Probabilistic evaluation of synergetic ultrasound pattern recognition for large scale bat surveys. Residing in the realm of ultrasound, echolocation calls show strong interspecies overlap in their signal characteristics but nevertheless species recognition is often possible on the basis of these signals. • Rafael Márquez et al. investigate the automated recording of Anurans, the group of terrestrial vertebrates most vulnerable to climate change. In a case study in the Iberian Peninsula, they compare results of an automated sound recording system with those of human listeners as tools in the study of the effect of temperature to Anuran vocalisations. • Andrew Taylor et al. look back at A decade of monitoring frog communities in northern Australia. Their focus is on both, the pattern recognition problem and the design of autonomous recording stations. The latter are designed to operate unattended in remote areas and have to be highly robust to retain operability in adverse situations such as fires and flooding. • David Chesmore discusses Automated bioacoustic identification of insects for phytosanitary and ecological applications. In particular, he uses time domain signal processing and artificial neural networks for the robust identification of taxa, concentrating on insects. He introduces the concept of time domain signal coding. 5 Among his results, he describes phytosanitary applications for quarantine insect larvae in timber. • In bioacoustics research, and especially in bioacoustical pattern recognition, everybody needs a good software infrastructure. All investigation of bioacoustic signals starts from signal processing tools such as filtering, spectrogram computation and visualisation. Harold Figueroa introduces XBAT, an open-source extensible platform for bioacoustic research and monitoring. Here, in addition to the basic tools needed by every practitioner, new tools for feature extraction, classification and visualisation can easily be implemented based on existing algorithms. Sebastian Huebner investigates Bioacoustic classifier system design as a knowledge engineering problem. His system