Local consumers are the first line to control biological invasions: a case of study with the whelk Stramonita haemastoma (Gastropoda: Muricidae)
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The increasing spread of invasive species in the Mediterranean Sea determines several alterations in local food webs, changing the feeding habits of native organisms. The whelk Stramonita haemastoma is a widespread Mediterranean gastropod that consumes bivalves, barnacles and limpets. Previous studies showed a shift in its diet from the bivalve Mytilaster minimus to the invasive mussel Brachidontes pharaonis, presumably due to a higher energy gain. Here we tested whelks’ preference among natives and a novel prey, calculating the profitability ratio, and integrating those results with biochemical analysis on prey tissues and the routine metabolism of the whelks. Further, we used the scaled functional response as a theoretical tool to describe whelk ability to obtain energy from their environment by using four different prey species: B. pharaonis, Mytilus galloprovincialis, M. minimus and Patella caerulea. Whelks evidenced a Type II functional response for all prey, while Brachidontes displayed a lower attack rate and a higher handling time. Stramonita showed a greater preference for Brachidontes, that resulted as the prey with the higher energetic content, and the second most profitable after Patella. This suggests that the higher energy gain is behind the change in the predator’s diet, with possible effects on its energy budget.
KeywordsInvasive species Functional response Gastropod Mussels Stramonita haemastoma Brachidontes pharaonis
PRIN TETRIS 2010 Grant (n. 2010PBMAXP_003) funded to Gianluca Sarà by the Italian Minister of Research and University (MIUR) supported this research. We thank Dr. Francesca Ape for her help in the biochemical analysis of prey and Anna Lossmann for the English fine tuning. The authors declare no competing financial interests.
AG and GS conceived the idea and led the writing, AG and MM carried out all experiments in mesocosms, AG & AR performed modelling work and analysed output data, SM provided grant funds for AG while GS provided lab facilities at DISTEM and research funds.
- Anderson, M. J., 2001. A new method for non-parametric multivariate analysis of variance. Austral Ecology 26: 32–46.Google Scholar
- Basedow, T., 1994. Analysis of shells on beaches and rocky coasts of Europe: new findings on nutritional and population ecology of predatory marine gastropods (Muricidae and Naticidae). Zoologische Beiträge NF 36: 29–48.Google Scholar
- Bolker, B.M. & R Development Core Team, 2014. bbmle: Tools for General Maximum Likelihood Estimation. R package version 1.0.16. http://CRAN.R-project.org/package=bbmle. Accessed 06/01/2016.
- Dick, J. T., K. Gallagher, S. Avlijas, H. C. Clarke, S. E. Lewis, S. Leung, D. Minchin, J. Caffrey, M. E. Alexander, C. Maguire, C. Harrod, N. Reid, N. R. Haddaway, K. D. Farnsworth, M. Penk & A. Ricciardi, 2013. Ecological impacts of an invasive predator explained and predicted by comparative functional responses. Biological Invasions 15: 837–846.CrossRefGoogle Scholar
- Dodd, J. A., J. T. Dick, M. E. Alexander, C. MacNeil, A. M. Dunn & D. C. Aldridge, 2014. Predicting the ecological impacts of a new freshwater invader: functional responses and prey selectivity of the ‘killer shrimp’, Dikerogammarus villosus, compared to the native Gammarus pulex. Freshwater Biology 59: 337–352.CrossRefGoogle Scholar
- Hassell, M. P., 1978. The Dynamics of Arthropod Predator-prey Systems. Princeton University Press, Princeton.Google Scholar
- Juliano, S. A., 2001. Nonlinear curve fitting: predation and functional response curves. In Scheiner, S. M. & J. Gurevitch (eds.), Design and Analysis of Ecological Experiments, 2nd ed. Oxford University Press, Oxford: 178–196.Google Scholar
- Krebs, J. R. & N. B. Davies, 1993. An Introduction to Behavioural Ecology. Blackwell Scientific Publication, Oxford.Google Scholar
- Paterson, R. A., T. A. Jaimie, J. T. A. Dick, D. W. Pritchard, M. Ennis, M. J. Hatcher & A. M. Dunn, 2015. Predicting invasive species impacts: a community module functional response approach reveals context dependencies. Journal of Animal Ecology 84: 453–463.CrossRefPubMedPubMedCentralGoogle Scholar
- Pritchard, D.W., 2014. Frair: functional response analysis in R. R package version 0.4. http://CRAN.R-project.org/package=frair. Accessed 06/01/2016.
- R Core Team, 2015. R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna.Google Scholar
- Rilov, G., 1999. The whelk Stramonita haemastoma in the eastern Mediterranean rocky littoral: biotic and abiotic perspectives. Ph.D. dissertation, Tel-Aviv University.Google Scholar
- Safriel, U. N., A. Gilboa, & T. Felsenburg, 1980. Distribution of rocky intertidal mussels in the Red Sea coasts of Sinai, the Suez Canal and the Mediterranean coast of Israel, with special reference to recent colonizers. Journal of Biogeography 39–62.Google Scholar
- Schoener, T. W., 1986. Mechanistic approaches to community ecology: a new reductionism. Integrative and Comparative Biology 26: 81–106.Google Scholar
- Seyhan, K., E. R. Mazlum, H. Emiral, S. Engin & S. Demirhan, 2003. Diel feeding periodicity, gastric emptying, and estimated daily food consumption of whelk (Rapana venosa) in the south eastern Black Sea (Turkey) marine ecosystem. Indian Journal of Marine Sciences 32: 249–251.Google Scholar
- Smith, D.J., 1983. Chemoattraction of the southern oyster drill Thais haemastoma towards the oyster Crassostrea virginica, as a function of temperature and salinity. M. SC. thesis, Louisiana State University, Baton Rouge, Louisiana.Google Scholar
- Terborgh, J., 2010. Trophic Cascades: Predators, Prey, and the Changing Dynamics of Nature. Island Press, Washington, DC.Google Scholar
- Underwood, A. J., 1997. Experiments in ecology: their logical design and interpretation using analysis of variance. Cambridge University Press, Cambridge.Google Scholar
- Winberg, G.G., 1971. Symbols, units and conversion factors in study of freshwaters productivity. International Biological Program: 23 pp.Google Scholar