Removing observational noise from fisheries-independent time series data using ARIMA models

Abundance indices derived from fishery-independent surveys typically exhibit much higher interannual variability than is consistent with the within-survey variance or the life history of a species. This extra variability is essentially observation noise (i.e. measurement error); it probably reflects environmentally driven factors that affect catchability over time. Unfortunately, high observation noise reduces the ability to detect important changes in the underlying population abundance. In our study, a noise-reduction technique for uncorrelated observation noise that is based on autoregressive integrated moving average (ARIMA) time series modeling is investigated. The approach is applied to 18 time series of finfish abundance, which were derived from trawl survey data from the U.S. northeast continental shelf. Although the a priori assumption of a random-walk-plus-uncorrelated-noise model generally yielded a smoothed result that is pleasing to the eye, we recommend that the most appropriate ARIMA model be identified for the observed time series if the smoothed time series will be used for further analysis of the population dynamics of a species.

The measurement error in marine survey catches: the bottom trawl case

We have formulated a model for analyzing the measurement error in marine survey abundance estimates by using data from parallel surveys (trawl haul or acoustic measurement). The measurement error is defined as the component of the variability that cannot be explained by covariates such as temperature, depth, bottom type, etc. The method presented is general, but we concentrate on bottom trawl catches of cod (Gadus morhua). Catches of cod from 10 parallel trawling experiments in the Barents Sea with a total of 130 paired hauls were used to estimate the measurement error in trawl hauls. Based on the experimental data, the measurement error is fairly constant in size on the logarithmic scale and is independent of location, time, and fish density. Compared with the total variability of the winter and autumn surveys in the Barents Sea, the measurement error is small (approximately 2–5%, on the log scale, in terms of variance of catch per towed distance). Thus, the cod catch rate is a fairly precise measure of fish density at a given site at a given time.

Identification and measurement of fatty acids, amino acids in roe of tuna fish (Thunnus tonggol) and its TVB and peroxide value during cold storage

The first aim of this research was to identify fatty acids, amino acids composition of Thunnus tonggol roe and their changes during cold storage (-18'C). The second aim was to determine the changes of moisture, protein, fat and ash contents of the roe during one year cold storage (-18'C). 60 samples of longtail tuna (Thunnus tonggol) ovaries were randomly collected form Bandar-e-Abbas landings. The samples were frozen at-30'C and kept in cold store at -18'C for one year. According to a time table, the samples were examined for identification of fatty acids, amino acids, moisture, protein, fat, ash, peroxide and T.V.N. and their changes were evaluated during this time. The results showed that 26 fatty acids were identified. The unsaturated fatty acids (UFA) and saturated fatty acids (SFA) were 62.33 and 37.6%, respectively, in fresh roe. So that, DHA (C22:6) and oleic acid (C18:1) had high amounts (24.79 and 21.88%) among the UFA and palmitic acid (C16:0) was the most content (22.75%) among the SFA. The PUFA/SFA was 0.91. Also, 17 amino acids were identified that essential amino acids (EAA) and nonessential amino acids (NE) were 10478 and 7562 mg/100g, respectively, and E/NE was 1.38. Among the EAA and NE, lysine (2110mg/100g) and aspartic acid (1924 mg/100g) were the most contents. Also, results showed that moisture, ash, protein and fat contents were 72.74, 1.8, 19.88 and 4.53%, respectively, in fresh roe. The effects of freezing and cold storage on the roes showed that UFA and SFA contents have reached to 49.83 and 48.07%, respectively, at the end of cold storage. It indicated that these compounds change to each other during frozen storage. Also, n-3 and n-6 series of fatty acids were 32.75 and 1.61% in fresh roe. But their contents decreased to 22.96 and 1.25% at the end of period. Among the fatty acids, 22:6 and C16:0 had the most changes. The changes of fatty acids were significantly at 95% level except for C15:1, C18:3(n-3) and C20:4(n-6). All of the amino acids decreased in frozen storage and their changes were significantly (P<0.05). EAA was 7818 mg/100g and E/NE was 1.27 at the end of storage period. Among the amino acids, leucine and lysine had the most changes. Moisture, ash, protein and fat contents were 70.13, 1.82, 19.4 and 6.51%, respectively, at the end of storage period. The peroxide value and T.V.N. increased during storage. So that, their contents have reached to 5.86 mg/kg and 26.37 mg/100 g, respectively, at the end of frozen storage. The best shelf life of Thunnus tonggol roe was 6 or 7 months, because of lipid oxidation and increasing of peroxide.