Estimating natural interstage egg mortality of Atlantic mackerel (Scomber scombrus) and horse mackerel (Trachurus trachurus) in the Northeast Atlantic using a stochastic model
Portilla, E. and McKenzie, E. and Beare, D. and Reid, D.G. (2007) Estimating natural interstage egg mortality of Atlantic mackerel (Scomber scombrus) and horse mackerel (Trachurus trachurus) in the Northeast Atlantic using a stochastic model. Canadian Journal of Fisheries and Aquatic Sciences, 64 (12). pp. 1656-1668. ISSN 1205-7533 (https://doi.org/10.1139/F07-128)
Full text not available in this repository.Request a copyAbstract
Egg mortality is a key parameter for understanding early life histories of fish. Small variations in estimated mortality cause large differences on adult fish biomass estimates. Therefore, the assumption of a constant egg mortality rate may be misleading. Here, we show how to estimate mortality rates for the individual egg stages of Atlantic mackerel (Scomber scombrus) and horse mackerel (Trachurus trachurus) from triennial surveys conducted since 1977. We use a standard, continuous-time Markov process model that combines the numbers of eggs sampled in each stage with experimental data on egg stage duration (dependent on water temperature). This is the first attempt to study mortality among egg stages in such detail and the first comprehensive effort to estimate horse mackerel egg mortality in the Northeast Atlantic. The results include detailed descriptions of spatial-temporal dependencies in mortality. The daily egg mortality rates estimated are ˜0.56·day[sup-1] for Atlantic mackerel (far higher than suggested in the literature) and 0.54-day[sup-1] for horse mackerel. Although it was not possible to estimate stage 1 egg mortality directly, the results suggest high mortality in the first stage. This might lead to underestimation of fish biomass when assessed traditionally by egg survey data alone.
-
-
Item type: Article ID code: 10317 Dates: DateEventDecember 2007PublishedSubjects: Science > Mathematics > Probabilities. Mathematical statistics Department: Faculty of Science > Mathematics and Statistics > Statistics and Modelling Science
Faculty of Science > Mathematics and StatisticsDepositing user: Strathprints Administrator Date deposited: 16 Nov 2011 16:30 Last modified: 11 Nov 2024 09:01 URI: https://strathprints.strath.ac.uk/id/eprint/10317