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| Petitgas, Pierre; Renard, Didier; Desassis, Nicolas; Huret, Martin; Romagnan, Jean-baptiste; Doray, Mathieu; Woillez, Mathieu; Rivoirard, Jacques. |
| This paper presents a novel application of the geostatistical multivariate method known as min–max autocorrelation factors (MAFs) for analysing fisheries survey data in a space–time context. The method was used to map essential fish habitats and evaluate the variability in time of their occupancy. Research surveys at sea on marine fish stocks have been undertaken for several decades now. The data are time series of yearly maps of fish density, making it possible to analyse the space–time variability in fish spatial distributions. Space–time models are key to addressing conservation issues requiring the characterization of variability in habitat maps over time. Here, the variability in fisheries survey data series is decomposed in space and time to address... |
| Tipo: Text |
Palavras-chave: MAF; Space-time; Habitat; Mapping; Sardine; Bay of Biscay. |
| Ano: 2020 |
URL: https://archimer.ifremer.fr/doc/00599/71157/69915.pdf |
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