TREPAR-1100; No. of Pages 1

Letter

FishPEST: an innovative software suite for fish parasitologists Giovanni Strona1 and Kevin D. Lafferty2 1

Department of Biotechnology and Biosciences, University of Milano-Bicocca, Milano, Italy U.S. Geological Survey, Western Ecological Research Center, Marine Science Institute, University of California, Santa Barbara, CA 93106, USA

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Fish Parasite Ecology Software Tool (FishPEST) integrates fish parasite information from scientific literature, internet databases and museum collections with phylogenetic, biogeographical and ecological host data coming from Fishbase (http://fishbase.org). FishPEST is a dynamic web-based system using the open source scripting language Python [1] and the Python-based web framework Django [2]. Users do not need to download software and are free to use FishPEST without fee or login. FishPEST has three sections, namely Parasite Niche Modeler (PaNic), Parasite Co-occurrence Modeler (PaCo) and Parasite List Generator (PaL). PaL creates lists of known parasites per host, lists of known hosts per parasite and lists of host/parasite records. PaL is innovative in its input and output. It allows users to filter the internal database according to parasite (taxon, area of distribution) and host features (phylogeny, habitat, ecology), making it easy to test biogeographic, co-evolutionary and ecological hypotheses. Additionally, PaL can create presence– absence matrices to be used for further analyses. PaL provides basic statistical information for each generated list. Although there are many ways to generate lists of known parasites or hosts, it has, as yet, not been possible to systematically propose probable lists of parasites or hosts. PaNic generates a list of probable hosts for a parasite [3], whereas PaCo generate lists of probable parasites for a host (G. Strona and K.D. Lafferty, unpublished). These tools are based on complex and flexible algorithms. FishPEST uses an internal database including more than 16 000 validated host/parasite records for the

Acanthocephala, Cestoda, Monogenea, Nematoda and Trematoda. The host–parasite records of the FishPEST internal database derive from a much bigger list containing more than 64 000 host–parasite online records, which was reduced to a quarter during the validation process. The fact that we were able to validate only 25% of the collected data emphasizes the need for a comprehensive, peer-reviewed archive of host–parasite records. FishPEST aims to be that archive and also offers researchers a rich set of statistical tools for analyzing host/parasite relationships. Researchers can easily upload their peer-reviewed records to FishPEST. FishPEST was designed to be easy. Although it is a powerful tool for researchers, its user-friendly interface makes it possible for a non-specialist to quickly obtain useful information, allowing an occasional user to hypothesize what is going on in a home aquarium or helping a fish farmer to protect stocks from potential diseases. FishPEST can be accessed at http://purl.oclc.org/fishpest. References 1 van Rossum, G. and de Boer, J. (1991) Interactively testing remote servers using the Python programming language. CWI Q. 4, 283–303 2 Holovaty, A. and Kaplan-Moss, J. (2009) The Definitive Guide to Django: Web Development Done Right, Apress 3 Strona, G. and Lafferty, K. How to catch a parasite: Parasite Niche Modeller (PaNic) meets Fishbase. Ecography DOI: 10.1111/j.16000587.2012.07439.x.

1471-4922/$ – see front matter ß 2012 Elsevier Ltd. All rights reserved. doi:10.1016/j.pt.2012.02.001 Trends in Parasitology xx (2012) 1

Corresponding author: Strona, G. ([email protected]).

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