Testing and recommending methods for fitting size spectra to data

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dc.contributor.authorEdwards, A.M.
dc.contributor.authorRobinson, J.P.W.
dc.contributor.authorPlank, M.J.
dc.contributor.authorBaum, J.K.
dc.contributor.authorBlanchard, J.L.
dc.date.accessioned2019-10-15T23:40:44Z
dc.date.available2019-10-15T23:40:44Z
dc.date.issued2016en
dc.description.abstractSummary 1. The size spectrum of an ecological community characterises how a property, such as abundance or biomass, varies with body size. Size spectra are often used as ecosystem indicators of marine systems. They have been fitted to data from various sources, including groundfish trawl surveys, visual surveys of fish in kelp forests and coral reefs, sediment samples of benthic invertebrates and satellite remote-sensing of chlorophyll. 2. Over the past decades several methods have been used to fit size spectra to data. We document eight such methods, demonstrating their commonalities and differences. Seven methods use linear regression (of which six require binning of data), while the eighth uses maximum likelihood estimation. We test the accuracy of the methods on simulated data. 3. We demonstrate that estimated size-spectrum slopes are not always comparable between the seven regression-based methods because such methods are not estimating the same parameter. We find that four of the eight tested methods can sometimes give reasonably accurate estimates of the exponent of the individual size distribution (which is related to the slope of the size spectrum). However, sensitivity analyses find that maximum likelihood estimation is the only method that is consistently accurate, and the only one that yields reliable confidence intervals for the exponent. 4. We therefore recommend the use of maximum likelihood estimation when fitting size spectra. To facilitate this we provide documented R code for fitting and plotting results. This should provide consistency in future studies and improve the quality of any resulting advice to ecosystem managers. In particular, the calculation of reliable confidence intervals will allow proper consideration of uncertainty when making management decisions.en
dc.identifier.citationEdwards, A.M., Robinson, J.P.W., Plank, M.J., Baum, J.K., Blanchard, J.L. (2016) Testing and recommending methods for fitting size spectra to data. Methods in Ecology and Evolution, (early access online).en
dc.identifier.doihttps://doi.org/10.1111/2041-210X.12641
dc.identifier.urihttp://hdl.handle.net/10092/17432
dc.language.isoen
dc.publisherUniversity of Canterbury. Mathematics and Statisticsen
dc.rights.urihttps://hdl.handle.net/10092/17651
dc.subjectindividual size distributionen
dc.subjectecosystem indicatorsen
dc.subjectecosystem approach to fisheriesen
dc.subjectbiomass size spectrumen
dc.subjectabundance size spectrumen
dc.subjectbounded power-law distributionen
dc.subjecttruncated Pareto distributionen
dc.subject.anzsrcFields of Research::30 - Agricultural, veterinary and food sciences::3005 - Fisheries sciences::300502 - Aquaculture and fisheries stock assessmenten
dc.titleTesting and recommending methods for fitting size spectra to dataen
dc.typeJournal Articleen
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