Abstract
Detailed models have the potential to reveal important processes underlying patterns in data. However, model fitting depends on the availability of sufficient data, and the results obtained from the models depend on detailed assumptions. In a recent paper, Matthiopoulos et al. fitted Bayesian state space models to a limited dataset and attempted to explain the recent trajectory of the harbour seal population in the Moray Firth, in northern Scotland. They went on to suggest that the results could help explain recent declines in other nearby populations. This Comment describes the implications of understating the uncertainty that the model required for convergence, questions the robustness of the results, highlights the differences between the areas, and cautions against extrapolating across these populations. The distinction between models that can be fitted to a dataset and those that provide useful information about the systems that generated the data is also considered.
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Härkönen T, Harding KC, Heide-Jorgensen MP (2002) Rates of increase in age-structured populations: a lesson from the European harbour seals. Can J Zool 80:1498–1510
Lonergan M, Duck CD, Thompson D, Mackey BL, Cunningham L, Boyd IL (2007) Using sparse survey data to investigate the declining abundance of British harbour seals. J Zool 271:261–269
Lonergan M, Thompson D, Thomas L, Duck C (2011) An approximate Bayesian method applied to estimating the trajectories of four British grey seal (Halichoerus grypus) populations from pup counts. J Mar Biol 597424. doi:10.1155/2011/597424
Lonergan M, Duck C, Moss S, Morris C, Thompson D (2013) Rescaling of aerial survey data with information from small numbers of telemetry tags to estimate the size of a declining harbour seal population. Aquat Conserv Mar Freshw Ecosyst 23:135–144
Matthiopoulos J, Cordes L, Mackey B, Thompson D, Duck C, Smout S, Caillat M, Thompson P (2013) State-space modelling reveals proximate causes of harbour seal population declines. Oecologia 13:1–12
Newman KB, Fernandez C, Thomas L, Buckland ST (2009) Monte Carlo inference for state-space models of wild animal populations. Biometrics 65(2):572–583
Patterson TA, Thomas L, Wilcox C, Ovaskainen O, Matthiopoulos J (2008) State space models of individual animal movement. Trends Ecol Evol 23:87–94
Reijnders PJH, Brasseur SMJM, Tougaard S, Siebert U, Borchardt T, Stede M (2010) Population development and status of harbour seals (Phoca vitulina) in the Wadden Sea. NAMMCO Sci Publ 8:95–106
SCOS (2012) Scientific advice on matters related to the management of seal populations: 2012. Report by the NERC Special Committee on Seals. http://www.smru.st-and.ac.uk/documents/1199.pdf
Taylor BL, Martinez M, Gerrodette T, Barlow J, Hrovat YN (2007) Lessons from monitoring trends in abundance of marine mammals. Mar Mammal Sci 23:157–175
Thompson D, Bexton S, Brownlow A, Wood D, Patterson T, Pye K, Lonergan M, Milne R (2010) Report on recent seal mortalities in UK waters caused by extensive lacerations. http://www.smru.st-and.ac.uk/documents/366.pdf
Thompson D, Lonergan M, Duck C (2005) Population dynamics of harbour seals Phoca vitulina in England: monitoring growth and catastrophic declines. J Appl Ecol 42:638–648
Thompson D, Duck CD, Lonergan ME (2010) The status of harbour seals (Phoca vitulina) in the United Kingdom. NAMMCO Sci Publ 8:117–128
Wood SN (2006) Generalized additive models: an introduction with R. Chapman & Hall, Boca Raton
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Communicated by Helene Marsh.
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Lonergan, M. Modelling beyond data is uninformative: a comment on “State-space modelling reveals proximate causes of harbour seal population declines” by Matthiopoulos et al.. Oecologia 175, 1063–1067 (2014). https://doi.org/10.1007/s00442-014-2970-2
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DOI: https://doi.org/10.1007/s00442-014-2970-2