Ecology Letters, (2002) 5: 86±94 REPORT Co-occurrence of ectoparasites of marine ®shes: a null model analysis Abstract Nicholas J. Gotelli1 We used null model analysis to test for nonrandomness in the structure of metazoan and Klaus Rohde2 ectoparasite communities of 45 species of marine ®sh. Host species consistently 1Department of Biology, supported fewer parasite species combinations than expected by chance, even in analyses University of Vermont, that incorporated empty sites. However, for most analyses, the null hypothesis was not Burlington, Vermont 05405, rejected, and co-occurrence patterns could not be distinguished from those that might USA. arise by random colonization and extinction. We compared our results to analyses of 2 School of Biological Sciences, presence±absence matrices for vertebrate taxa, and found support for the hypothesis University of New England, that there is an ecological continuum of community organization. Presence±absence Armidale, NSW 2351, Australia. matrices for small-bodied taxa with low vagility and/or small populations (marine E-mail: [email protected] ectoparasites, herps) were mostly random, whereas presence±absence matrices for large- bodied taxa with high vagility and/or large populations (birds, mammals) were highly structured. Metazoan ectoparasites of marine ®shes fall near the low end of this continuum, with little evidence for nonrandom species co-occurrence patterns. Keywords Species co-occurrence, ectoparasite communities, niche saturation, competitive interactions, null model analysis, presence±absence matrix Ecology Letters (2002) 5: 86±94 community patterns, reinforcing previous conclusions that INTRODUCTION these parasites live in largely unstructured assemblages Parasite communities are model systems for tests of (Rohde 1979, 1989, 1992, 1993, 1994, 1998a,b, 1999; Rohde community structure because community boundaries are et al. 1998; Morand et al. 1999). We compared our results to discrete and replicate communities of the same host species null model analyses of other taxa (Gotelli & McCabe, in can be collected (Holmes & Price 1986). Holmes & Price press) and found that co-occurrence patterns of marine ®sh (1986) suggested that parasite communities fall between ectoparasites were more random and unstructured than extremes of interactive and isolationist communities. Inter- co-occurrence patterns of birds and of mammals. These active communities are characterized by dense populations, comparisons suggest that patterns of animal community frequent colonization and strong species interactions, structure re¯ect an ecological continuum: animals with little whereas isolationist communities are characterized by low vagility and/or small individual or population size live in population densities and weak species interactions. Kennedy largely empty niche space and are less subject to structuring et al. (1986) hypothesized that helminth communities mechanisms (competition, facilitation, heterogeneity in infec- associated with endotherms are more highly structured than tion) than animals that are large or live in large populations those associated with ectotherms. with much vagility and are closer to saturation (Rohde 1980). However, it is dif®cult to test such generalizations because there are few taxa for which comprehensive data sets are available that can be compared with standardized METHODS analysis. Metazoan ectoparasites of marine ®shes are one of Parasite sampling these groups (Rohde et al. 1995). In this study, we analysed with null models (Gotelli & Graves 1996) a set of presence± Parasite occurrence data from the head and gills of 45 absence matrices for ectoparasites of 45 marine ®sh host ®sh species were used for this study (Table 1; for details species. These analyses revealed little evidence for nonrandom see Rohde et al. 1995; Kleeman 1996). Almost all Ó2002 Blackwell Science Ltd/CNRS Table 1 Signi®cance test results for ®sh parasite presence±absence matrices. Number of Number of Number of Checker Checker C-score C-score Combo Combo V-ratio Host species parasite species hosts occupied hosts ®xed±®xed ®xed±eq ®xed±®xed ®xed±eq ®xed±®xed ®xed±eq ®xed±eq Zeus faber 3 2213nsnsnsnsnsnsns Trigla lucerna 4 2825nsnsnsnsnsnsns Trichiurus lepturus 4 6046nsnsnsnsnsnsns Syngnathus griselineatus 4 103 61 ns ns ns ns ns ns ns Siganus lineatus 14 16 16 ns ns ns ns ns ns ns Seriola lalandi 4 2121nsnsSAnsnsA Sebastes pinniger 4 2422nsnsnsnsSSSns Sebastes maliger 4 2828nsnsnsnsnsnsns Sebastes ¯avidus 3 22 8 ns ns ns ns ns ns ns Sebastes brevispinnis 3 2424nsnsnsnsnsnsns Sebastes alutus 4 3232nsnsnsnsnsnsns Scomberoides tol 6 2323nsnsnsnsnsnsns Scomber scombrus 3 8362nsnsnsnsnsnsA Scomber japonicus 6 9855nsnsnsAAnsnsA Rhabdosargus sarba 5 7752nsnsnsAAnsnsAA Prionotus nudigula 4 6645nsnsnsnsnsnsns Platichthys stellatus 6 23 23 ns ns S ns AA AA ns Nemadactylus macropterus 6 2525nsnsnsnsnsnsns Mugil cephalus 4 5947nsnsnsSSnsnsSS Monodactylus argenteus 3 3534nsnsnsnsnsnsns Micropogon furnieri 5 3124nsnsnsAAnsnsAA Megalaspis cordyla 5 1313nsnsnsnsnsnsns Macrourus holotrachys 3 2013nsnsnsnsnsnsns Lethrinus nebulosus 15 14 14 ns ns ns ns ns ns ns Lepidotrigla argus 2 44 3 ns ns ns ns ns ns ns Lepidopsetta bilineata 6 3827nsnsnsnsnsnsns Hoplichthys haswelli 4 2623nsnsnsnsnsSns Hippoglossoides elassodon 4 4725nsnsnsnsnsnsns Herklotsichthys castelnaui 4 118 37 ns ns SS ns ns ns ns Ó Helicolenus papillosus 4 2917nsnsnsnsnsnsns Species richness measurement 2002 Blackwell Science Ltd/CNRS Girella tricuspidata 6 4422nsnsnsnsnsnsns Genypterus blacodes 3 25 20 ns ns ns A ns ns A Gasterosteus aculeatus 5 2018nsnsnsnsnsnsns Gadus morhua 3 4434nsnsnsnsnsnsns Gadus macrocephalus 4 20 16 ns ns ns A ns ns ns Damalichthys vacca 5 2120nsnsnsnsnsnsns Cymatogaster aggregata 4 40 39 ns ns ns A ns ns ns Chlorophthalmus nigripinnis 5 34 14 ns ns ns A ns ns A 87 Ó Table 1 (continued) 88 2002 Blackwell Science Ltd/CNRS N.J. Gotelli and K. Rohde Number of Number of Number of Checker Checker C-score C-score Combo Combo V-ratio Host species parasite species hosts occupied hosts ®xed±®xed ®xed±eq ®xed±®xed ®xed±eq ®xed±®xed ®xed±eq ®xed±eq Centroberyx af®nis 3 3719nsnsnsnsnsnsns Bodianus vulpinus 6 3131nsnsnsnsnsnsns Atractoscion aequidens 5 26 16 ns ns A ns S SS ns Sillago ¯indersi 4 4040nsnsnsnsnsnsns Sillago ciliata 5 4018nsnsnsnsnsnsns Lethrinus miniatus 22 41 41 ns ns SSS ns ns ns ns Lethrinus seminctus 15 14 14 ns ns ns ns ns ns ns Each row represents a different host species sampled. The ®rst three columns give the number of parasite species recorded, the number of host individuals examined, and the number of host individuals occupied by one or more parasite species. The remaining columns give the co-occurrence index used and the null model used for analysis (see text for details). The entries represent signi®cant deviations from the null hypothesis. ``S'' indicates cases in which the pattern was signi®cant segregation and less co-occurrence than expected by chance (one-tailed test). ``A'' indicates cases in which the pattern was signi®cant aggregation and more co-occurrence than expected. S or A P < 0.05; SS or AA P < 0.01; SSS or AAA P < 0.001; ns not signi®cant (P > 0.05). various experts. and Branchiura.Monopisthocotylea, Specimens were Trematoda,Copepoda, identi®ed larval by Cestoda, MonogeneaAll KR Isopoda Polyopisthocotylea, and metazoanmounted Monogenea and parasite identi®ed (forunder taxa details a see were Rohde dissected dissecting and recorded, microscope. theirunlikely. including gills Parasites and Fish were headTherefore, were examined any stained, signi®cant for brought error parasites due back to loss to of parasites the is laboratory, community patterns. presence±absence data will not necessarilyresults mask with nonrandom both sets ofabsence analyses, data suggesting that and thebank abundance use voles of data. ( analysed They obtained coexistence similar McCabe, patterns in ofpresence±absence helminth press). matrices parasiteswanted Haukisalmi to for of compare & our otheroccurrence results than quantitatively Henttonen taxa in to analysesdata, measuring (1993) of (Gotelli abundance, because and & to because there we analyse presence±absencein is data, a particular rather less hostabsence than (Simberloff (0) uncertainty & abundance Connor or 1979). presenceindividual in We (1) chose host. of measuring The aparasite particular entries species parasite in species and1987). the In each matrix such columncommunity represent a represents ecology matrix, the a and eachpresence±absence different row matrix, biogeography represents a (McCoyFor a fundamental & different unit each Heck of host studyData organization in species, we organized the data as a sediment inthat bags dropped (seeplastic off Table bags 2 the containingwere in 10% hosts used formalin. Rohde andwell-de®ned were The were locality few collected placed atspecimens parasites one immediately from time. of after Only the capture each freshly in caught host ®sh species were collected from a community. value ofdescribe how the each index is indexindices calculated and and what their is the performance expected Gotelli in in (2000) null model describes tests. ameasures the Here pattern we statistical competitively for propertiesthe structured of an variance these entire ratio.the presence±absence number Each of matrix. checkerboard indexcommunity species structure: is pairs, the the number a C-scoreWe of and single species used combinations, number four that Measuring indices community structure to quantify patterns