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Long-term ecological surveys (LTES) often exhibit strong variability among sampling dates. The use and interpretation of such interannual variability is challenging due to the combination of multiple processes involved and sampling uncertainty. Here, we analysed the interannual variability in ∼30 years of 150 species density (fish and invertebrate) and environmental observation time series in four aquatic systems (stream, river, estuary, and marine continental shelf) with different sampling efforts to identify the information provided by this variability. We tested, using two empirical methods, whether we could observe simultaneous fluctuation between detrended time series corresponding to widely acknowledged assumptions about aquatic population dynamics: spatial effects, cohort effects, and environmental effects. We found a low number of significant results (36%, 9%, and 0% for spatial, cohort, and environmental effects, respectively), suggesting that sampling uncertainty overrode the effects of biological processes. Our study does not question the relevance of LTES for detecting important trends, but clearly indicates that the statistical power to interpret interannual variations in aquatic species densities is low, especially in large systems where the degree of sampling effort is always limited. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Journal of Fisheries & Aquatic Sciences is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Canadian Journal of Fisheries & Aquatic Sciences is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Catch curves are widely used to estimate total mortality for exploited marine populations. The usual population dynamics model assumes constant recruitment across years and constant total mortality. We extend this to include annual recruitment and annual total mortality. Recruitment is treated as an uncorrelated random effect, while total mortality is modelled by a random walk. Data requirements are minimal as only proportions-at-age and total catches are needed. We obtain the effective sample size for aggregated proportion-at-age data based on fitting Dirichlet-multinomial distributions to the raw sampling data. Parameter estimation is carried out by approximate likelihood. We use simulations to study parameter estimability and estimation bias of four model versions, including models treating mortality as fixed effects and misspecified models. All model versions were, in general, estimable, though for certain parameter values or replicate runs they were not. Relative estimation bias of final year total mortalities and depletion rates were lower for the proposed random effects model compared with the fixed effects version for total mortality. The model is demonstrated for the case of blue ling ( Molva dypterygia) to the west of the British Isles for the period 1988 to 2011. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Journal of Fisheries & Aquatic Sciences is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

A simple two-stage biomass random effects population dynamics model is presented for carrying out fish stock assessments based on survey indices using no commercial catch information. Recruitment and biomass growth are modelled as random effects, reducing the number of model parameters while maintaining model flexibility. No assumptions regarding natural mortality rates are required. The performance of the method was evaluated using simulated data with emphasis on identifying parameter redundancy, which showed that the variance of the biomass growth random effect might only be estimable if large (>0.2). The full and two nested models were fitted to European anchovy (Engraulis encrasicolus) in the Bay of Biscay using two survey series. The best-fitting model had fixed biomass growth and random recruitment following a lognormal distribution. [ABSTRACT FROM AUTHOR]

Survey indices play an important role in stock assessments as they provide information on stock trends. In certain cases, large interannual variations have been observed that are unlikely to reflect true underlying stock changes but are rather outliers. When survey indices for several species appear to be outliers for the same year, the suspicion is raised that something happened during the survey of that year. This is called a year effect in survey catches. To study the potential year effect in survey catches for the French autumn groundfish survey taking place in the Bay of Biscay, several indicators for survey design and wind conditions were derived as explanatory variables, and principal component analysis was used to study the relationship between these variables. Using multiple linear regression models, we found that, on average, 20% of interannual variation in abundance indices could be explained by survey conditions for benthic species, 11% for demersal, and none for pelagic species. In contrast, survey conditions explained a smaller and decreasing part of the interannual variability in the coefficients of variations of these abundance indices and in species mean weight for benthic, demersal, and pelagic species. Thus survey indices of benthic species seemed most affected by survey design and wind conditions. [ABSTRACT FROM AUTHOR]

Discarding is an issue of increasing concern and there is a growing number of studies aiming at estimating discard amounts and characteristics. However, the sampling design and methods used in these studies generally rely on implicit assumptions. In this perspective, we examine the available evidence in favour of or refuting these assumptions. We find that (i) the assumptions most commonly used for estimating discards, namely that discards are proportional to catch or to effort, are generally not supported by the available evidence, (ii) both environmental conditions and fishing methods influence the amounts and composition of discards, but because of the huge variability, sampling stratification according to these factors might not result in any improvement of the precision of discard estimates, and (iii) many intricate factors can play a role in determining discards in a particular fishery. We conclude that assumptions should be more carefully checked prior to being taken for granted in discard studies and that more studies designed to improve knowledge of the discarding processes are needed. [ABSTRACT FROM AUTHOR]

Examines the population and community descriptors that might be used as indicators of the impact of fishing. Total mortality rates; Mean length of catch; Indicators for assemblages; Food web models.

Examines the performance of population and community indicators derived from abundance estimates for detecting the impact of fishing on the Celtic Sea groundfish community. Change in fishing mortality required to reverse population growth rate; Biodiversity index; Proportion of noncommercial species; Distribution of mean population length.