The utility of otolith weight as a predictor of age in the emperor Lethrinus mahsena and other tropical fish species

This study examines the potential use of otolith weight as a proxy for age in the lethrinid Lethrinus mahsena from different sites in the tropical Indian Ocean: the banks of Seychelles, Mauritius and British Indian Ocean Territory (BIOT, Chagos Archipelago). The reliability of age–frequency distributions and individual ages estimated using otolith weight–age relationships was examined through comparison with those estimated through the standard method of ageing using otolith increments. Two other methods for estimating age–frequencies using age-slicing via an estimated growth curve were also examined; these used growth curves estimated by a length-based method (ELEFAN), or by fitting directly to length-at-age data (an ‘age-based’ method). Age-slicing using length-based growth parameters failed to produce reliable age–frequencies, due to inaccuracies in the growth parameter estimates. The use of age-based growth parameter estimates improved the results of age-slicing, however, age–frequencies remained significantly different from those obtained from ageing using otolith increments in two locations. The use of otolith weight–age relationships resulted in estimated age–frequency distributions that in all locations were not significantly different from those assessed through otolith increment counts. In contrast, L. mahsena otolith weight–age relationships could not be used to estimate individual ages accurately, due to the level of overlap in otolith weight between age classes. Where otolith increments are routinely used to age commercial fish species, the fact that otolith weight–age relationships could not be used to age individuals accurately may limit its application. However, where routine ageing of individuals through otolith increments is considered impractical, for instance because of its cost, the use of otolith weight–age relationships to derive catch age–frequencies represents a viable alternative approach. With this in mind, this study has also demonstrated that there is the potential to use otolith weight–age relationships for five other species caught around the Seychelles, following the validation of their otolith increments.     

Towards an ultimate explanation for mixed‐species shoaling

The formation of social groups has important impacts on fitness for many animal species, with differences in group compositions resulting in a range of fitness outcomes for individuals. Recent interest in mixed‐species grouping, which extends from a large body of literature invested in understanding single‐species grouping, highlights novel complexities of group formation which relate to phenotypic, behavioural and physiological differences that naturally exist between species. Among fishes, mixed‐species shoaling is a common form of social grouping behaviour displayed across a range of marine and freshwater ecosystems. Research explaining mixed‐species shoaling shows some overlap with explanations for single‐species shoaling; however, it also demonstrates that distinct differences between species give rise to unique cost‐benefit trade‐offs which need to be incorporated into conceptual models of mixed‐species shoaling behaviour. Unique predation related trade‐offs may arise from inefficiency of the confusion effect, variation in vigilance between species and unequal species‐preferences shown by predators, whilst unique foraging‐related trade‐offs may arise from diet partitioning, variations in foraging behaviour and differences in competitive abilities between species. We review the literature on fitness outcomes associated with mixed‐species shoaling and present a new theoretical framework to explain the cost‐benefit trade‐offs for individuals within mixed‐species shoals. The framework incorporates both trade‐offs arising from differences between species and those arising from group size, the former having been largely ignored due to a focus on single‐species shoaling. Our framework is designed to inform future research striving to explain mixed‐species shoaling behaviour.     

Weight–length relationships of 33 demersal fish species from Azores archipelago

Weight–length relationships are presented for 33 fish species of Azores archipelago. This work is the first reference on weight–length parameters of 16 species. Samples were collected between the years of 1999 and 2003 using longline at depths ranging from a few meters to 1200 m. The parameters of a and b of the equation W = aL^b were estimated. The b values of the species caught ranged from 2.701 for Lepidopus caudatus to 3.677 for Centroscymnus crepidater. Whenever possible, the b values for the species obtained both in this study and some of the previously reported in the Portuguese waters were compared.     

Turbidity related to shrimp size in tanks with soil substrate

Water turbidity was monitored daily during a 63-day growth trial with juvenile Penaeus vannamei in indoor laboratory tanks. The tanks contained a 2.5 cm layer of soil substrate collected from 14 ponds representing five shrimp farms in Texas. A linear regression model relating turbidity to estimated shrimp length accounted for 49–83% of the total variation in turbidity for the 14 soil groups. For averages of daily turbidity and shrimp length over the 14 soil groups, the linear regression model yielded an r² = 0.92. Turbidity increased with shrimp length (75–135 mm), apparently because the elevated locomotory or feeding activity of the larger shrimp increased the suspension of soil particles. These results suggest the potential of using water turbidity as a tool for estimating shrimp biomass in ponds.     

Post-settlement growth and mortality of brackishwater clam Corbicula japonica in the Kiso estuaries, central Japan

Different cohorts of Corbicula japonica benthic individuals (from new settlers just after larval settlement up to recruits with 12-mm shell length and more) in the Kiso estuaries, Japan were separated based on temporal changes in shell length histograms. The post-settlement growth and mortality were examined for cohorts that were successful in fishery recruitment. Three growth models (Logistic, Gompertz and ALOG) were fitted to the growth data on average shell lengths of different cohorts, the best-fitting growth model varied depending on cohort and further on cohorts that were grouped according to estuary and to either overwintering or non-overwintering. Mortality rates were estimated based on regression models fitted separately to the data on temporal changes in the log-transformed density against sampling dates of individuals before and after fishery recruitment (i.e. attaining 12-mm shell length). For most cohorts, however, there was no significant difference in mortality rates between individuals before and after fishery recruitment, although significant differences were detected in initial densities between individuals of these two groups. It may be suggested that daily mortality rate after fishery recruitment was compensated with fishery mortality, so that total mortality rate was not different between individuals of these two groups.     

The selectivity for cod (Gadus morhua L.) in two experimental trammel-nets and one gillnet

The present study analyses the selectivity for cod in two trammel-nets (three-wall nets) and one gillnet (single-wall net) used during an experimental cod fishery conducted monthly from october 1985 to December 1988 in a Norwegian fjord. It is part of a cod enhancement experiment conducted in the fjord. The three nets were grouped and utilized to sample the wild cod population. In addition, the gillnet and one trammel-net were utilized to sample a tagged group of cod with a known length composition. Relative selectivity curves were estimated indirectly for the two trammel-nets by comparing the catches of each length class within the length range 18–58 cm. Absolute selectivity curves were estimated directly for the gillnet and one trammel-net for the length range 15.0–22.0 cm. These were utilized to verify the indirectly estimated curves. The trammel-net selectivity curves obtained were used to provide an estimate for the true length-frequency distribution of cod in the fjord. Finally, it was tested whether a group of the three nets may be utilized as a unit effort to provide approximate random samples from the population.     

Cluster analysis of linear model coefficients under contiguity constraints for identifying spatial and temporal fishing effort patterns

For fisheries management purposes, it is essential to take into account spatial and seasonal characteristics of fishing activities to allow a reliable assessment of fishing impact on resource. This paper presents a novel technique for describing spatial and temporal patterns in fishing effort. The spatial and seasonal fishing activity patterns of the French trawler fleet in the Celtic Sea during the period 1991–1998 were analysed by modelling fishing effort (fishing time) with generalised linear models. The linear model for fishing effort included fixed effects for both spatial (statistical rectangles) and temporal units (months). In addition, spatial correlations in any given month were modelled by an exponentially decreasing function. Temporal correlations were included using the previous month's fishing effort for a given spatial unit as predictor. A method based on cluster analysis of estimated model coefficients of spatial or temporal fixed effects is proposed for identifying groups of similar spatial and temporal units. A contiguity constraint is imposed in the clustering algorithm, ensuring that only neighbouring spatial units or consecutive temporal units are grouped. The cluster analysis identified 22 spatial and 9 temporal groups. Winter and spring months stood out as being more variable than the remaining months. Spatial groups were of varying size, and generally larger offshore. The proposed method is generic and could for example be used to analyse temporal and spatial patterns in catch or catch rate data.     

铜仁锦江日本沼虾形态性状对体重的回归分析

随机抽取贵州铜仁锦江河段的日本沼虾(Macrobrachium nipponense)46尾(雌雄各50%),对其体长、头胸甲长、胸高、胸宽、尾长、额剑上刺数、额剑下刺数和体重等16个性状进行测量。采用逐步回归法分析体重与形态性状的关系。结果表明,日本沼虾群体的3个性状、雌性群体的1个性状、雄性群体的2性状与体重的相关系数达到了极显著水平(P0.01)或显著水平(P0.05),是影响体重的主要指标;影响雄性群体体重的主要形态性状为头胸甲长和头胸甲高,影响雌性群体体重的主要形态性状为体长,建立的最优多元回归方程也显著不同,Y=-3.368+0.114X2-0.009X4+0.172X11,Y♀=-1.921+0.086X2,Y♂=-3.178+0.120X3+0.243X5(Y为体重,X2为体长,X3为头胸甲长,X4为头胸甲宽,X5为头胸甲高,X11尾肢宽外);逐步回归法分析为日本沼虾的选种和育种提供理想的测度指标与参考模型。     

Comparing three indices of catch per unit effort using Bayesian geostatistics

In assessing a fish stock, indices based on catch per unit effort (CPUE) are frequently used. Estimates of three indices of catch per unit effort were compared here (CPUE₁, CPUE₂ and CPUE₃), considering the fitting of two models: (i) a bivariate geostatistical model for catch and effort; (ii) a bivariate model where catch and effort were considered spatially independent. For comparing the estimates of the three indices after the fitting of the two models, catch and effort data were simulated in different scenarios. The simulation study showed that, in general, the estimates of CPUE₁ expressed by the ratio of the means of catch and effort, present better results for different scenarios and that the estimates from (i) are better than (ii), mainly when there is a correlation between catch and effort and an additional spatial correlation.     

Incorporating spatial autocorrelation into the general linear model with an application to the yellowfin tuna (Thunnus albacares) longline CPUE data

Catch-per-unit-effort (CPUE) data have often been used to obtain a relative index of the abundance of a fish stock by standardizing nominal CPUE using various statistical methods. The theory underlying most of these methods assumes the independence of the observed CPUEs. This assumption is invalid for a fish population because of their spatial autocorrelation. To overcome this problem, we incorporated spatial autocorrelation into the standard general linear model (GLM). We also incorporated into it a habitat-based model (HBM), to reflect, more effectively, the vertical distributions of tuna. As a case study, we fitted both the standard-GLM and spatial-GLM (with or without HBM) to the yellowfin tuna CPUE data of the Japanese longline fisheries in the Indian Ocean. Four distance models (Gaussian, exponential, linear and spherical) were examined for spatial autocorrelation. We found that the spatial-GLMs always produced the best goodness-of-fit to the data and gave more realistic estimates of the variances of the parameters, and that HBM-based GLMs always produced better goodness-of-fit to the data than those without. Of the four distance models, the Gaussian model performed the best. The point estimates of the relative indices of the abundance of yellowfin tuna differed slightly between standard and spatial GLMs, while their 95% confidence intervals from the spatial-GLMs were larger than those from the standard-GLM. Therefore, spatial-GLMs yield more robust estimates of the relative indices of the abundance of yellowfin tuna, especially when the nominal CPUEs are strongly spatially autocorrelated.     

CPUE standardisation and the construction of indices of stock abundance in a spatially varying fishery using general linear models

Construction of annual indices of stock abundance based on catch and effort data remains central to many fisheries’ assessments. While the use of more advanced statistical methods has helped catch rates to be standardised against many explanatory variables, the changing spatial characteristics of most fisheries data sets provide additional challenges for constructing reliable indices of stock abundance. After reviewing the use of general linear models to construct indices of annual stock abundance, potential biases which can arise due to the unequal and changing nature of the spatial distribution of fishing effort are examined and illustrated through the analysis of simulated data. Finally, some options are suggested for modelling catch rates in unfished strata and for accounting for the uncertainties in the stock and fishery dynamics which arise in the interpretation of spatially varying catch rate data.     

Remedies for pseudoreplication

Pseudoreplication is the failure of a statistical analysis to properly incorporate the true structure of randomness present in the data. It has been well documented and studied in the ecological literature but has received little attention in the fisheries literature. Avoiding pseudoreplication in analyses of fisheries data can be difficult due to the complexity of the statistical procedures required. However, recent developments in statistical methodology are decreasing the extent to which pseudoreplication has to be tolerated. Seven examples are given here, beginning with simple design-based remedies and progressing to more challenging examples including the model-based remedies of mixed-effects modelling, generalized linear mixed models, state-space models, and geostatistics.     

Growth standards for nine North American fish species

Abstract  Standard methods for comparing population characteristics within and among fish populations greatly enhance communications among fisheries scientists, improve the efficiency of data analysis, and provide insight that helps guide management actions. Although standard methods are available for comparing some fish population characteristics (e.g. length structure, body condition), similar methods are lacking for comparing growth. The purpose of this study was to provide standards (i.e. percentiles and a standard growth model) for nine ecologically and recreationally important fish species. Percentile distributions of mean back-calculated length at age were estimated using data obtained from the published literature and from data solicited from state and federal agencies throughout North America. Percentiles of growth were estimated for bluegill, Lepomis macrochirus Rafinesque, common carp, Cyprinus carpio Linnaeus, flathead catfish, Pylodictis olivaris (Rafinesque), largemouth bass, Micropterus salmoides (Lacepède), sauger, Sander canadensis (Griffith & Smith), smallmouth bass, Micropterus dolomieu Lacepède, white bass, Morone chrysops (Rafinesque) and yellow perch, Perca flavescens (Mitchill). Standard growth models (i.e. von Bertalanffy models) were developed for these species and for channel catfish, Ictalurus punctatus (Rafinesque). These results provide tools that will help scientists compare growth of fishes across North America.     

A generalized linear mixed model analysis of a multi-vessel fishery resource survey

A generalized linear mixed model (GLMM) that treats year and spatial cell as fixed effects while treating vessel as a random effect is used to examine fishing power among chartered industry-based vessels and a research trawler, the FRV Miller Freeman, for bottom trawl surveys on the upper continental slope of U.S. West coast. A Bernoulli distribution is used to model the probability of a non-zero haul and the gamma distribution to model the non-zero catch rates of four groundfish species. The use of vessel as a random effect allows the data for the various vessels to be combined and a single continuous time-series of biomass indices to be developed for stock assessment purposes. The GLMMs fit the data reasonably well. Among the different models examined, the GLMM incorporating a random vessel × year effect had the smallest ΔAIC and was thus chosen as the best model. Also, estimated random effects coefficients associated with the industry-based vessels and the FRV Miller Freeman for each year suggests that these vessels can be assumed to be from a common random effects distribution. These results suggest that combining data from the chartered industry-based vessels and from the research trawler may be appropriate to develop indices of abundance for stock assessment purposes. Finally, an evaluation of variances associated with abundance indices from the different models indicate that analyzing these data as a fixed effect GLM may underestimate the level of variability due to ignoring the grouped nature of tows within vessels. As such, use of a mixed model approach with vessel as a random effect is a reasonable approach to developing abundance indices and their variances.     

西北太平洋北方拟黵乌贼耳石外部形态特性分析

根据2018年9—11月我国鱿钓船在西北太平洋采集的339尾北方拟黵乌贼样本,对其耳石外形生长特征进行了研究。结果发现,北方拟黵乌贼具有长窄的吻区和宽大的翼区。主成分分析表明,耳石总长(TSL)、吻侧区长(RLL)、侧区长(LDL)、翼区长(WL)和最大宽度(MW)可以作为北方拟黵乌贼耳石外形变化的特征因子。协方差分析表明,MW、LDL和WL与胴长的关系存在性别间显著性差异,TSL和RLL则不存在显著性差异;MW、RLL、TSL、LDL和WL与体质量的关系均存在性别间显著性差异。AIC (Akaike’s information criterion)分析表明,TSL、RLL与胴长的生长关系最适合用线性函数表示,雄性个体的MW、LDL和雌雄个体的WL与胴长的关系最适合用幂函数表示,而雌性个体的LDL则最适合用指数函数表示。雄性个体的LDL和MW与体质量的关系最适合用指数函数表示,雌性个体的LDL、MW和TSL最适合用线性函数表示,而其余特征参数则均最适合用幂函数表示。随着胴长增加,耳石绝对尺寸都逐渐增大,但耳石的形态结构比例基本不变:背区、侧区、吻侧区、翼区的长度与耳石总长之比基本保持一致,分别为35.66%、55.84%、75.23%和85.82%左右。     

Sublethal effects and safe levels of carbon dioxide in seawater for Atlantic salmon postsmolts (Salmo salar L.): ion regulation and growth

Atlantic salmon (Salmo salar L.) postsmolts (0.17–0.26 kg) were exposed to four different levels of carbon dioxide partial pressure for 43 days in an open flow system: 0.6 mm Hg (control), 4.9 mm Hg (low), 12 mm Hg (medium), and 20 mm Hg (high). The water temperature was 15–16°C and the salinity 34‰. In the low carbon dioxide group (P_CO2=4.9 mm Hg; 10.6 mg/l), no significant differences were found in blood parameters (haematocrit, plasma chloride and plasma sodium) or in growth parameters (weight, length and condition factor) when compared to the control group. After 43 days, the mean plasma chloride concentration for the medium group (P_CO2=12 mm Hg; 26 mg/l) was significantly reduced, while weight and condition factor were slightly, although not significantly, lowered. For the high carbon dioxide group (P_CO2=20 mm Hg; 44 mg/l) plasma sodium and plasma pH were significantly increased and plasma chloride, oxygen consumption, weight, length and condition factor were significantly reduced at the end of exposure. There was no mortality in the control group or in the low carbon dioxide group. The mortalities in the medium and high carbon dioxide groups were 1.1 and 4.3%, respectively. Nephrocalsinosis was not observed in any of the groups. The results of the present investigation indicate that the CO₂ concentration of the low group may represent a safe level for Atlantic salmon postsmolts when the temperature is 15–16°C and the oxygen level is 6–7 mg/l. Further studies are required.     

Examining the importance of consistency in multi-vessel trawl survey design based on the U.S. west coast groundfish bottom trawl survey

Generalized linear mixed-effects models can be used to combine bottom trawl data from multiple vessels, each with a different fishing power, into a single time series of relative abundance. However, how important might it be to have a consistent set of vessels and vessel characteristics from year to year given we can model differences in fishing power among vessels? We demonstrate how changes in the suite of fishing vessels performing the survey can affect the results of the data analysis using sablefish catches in the U.S. west coast groundfish bottom trawl survey from 1998 to 2000. The results do not indicate that one must have a consistent set of vessels over time to provide useful data, but rather that there is benefit to consistency even when the survey data are analyzed using advanced statistical models. Further research should be undertaken to quantify these benefits specifically to aid in contracting and bidding of survey vessels.     

Application of support vector regression to CPUE analysis for southern bluefin tuna Thunnus maccoyii,and its comparison with conventional methods

This paper describes the catch per unit effort (CPUE) standardization using three models for data mining (support vector regression, neural network and tree regression model) and two conventional statistical methods (analysis of variance and generalized linear model) using the actual fishery data for southern bluefin tuna Thunnus maccoyii. Statistical performances of these five models were compared based on mean square error, mean absolute error and three correlation coefficients, which are measured by the difference between the observed and the corresponding predicted values. As a result, the performance of support vector regression is equivalent to (or better than) that of neural networks, and these two models are superior to the tree regression model, analysis of variance, and generalized linear model based on CPUE analyses of actual fishery data for southern bluefin tuna. We suggest a simple method for factorial analysis to extract the CPUE year trend based on the predicted values obtained from these data mining models. This method is expected to contribute markedly to reduce the difficulty of estimating the CPUE year trends by these models for data mining and should be applied to CPUE analyses because of its ease of use, general versatility and high performance .     

Pacific herring, Clupea pallasi, recruitment in the Bering Sea and north-east Pacific Ocean, II: relationships to environmental variables and implications for forecasting

Previous studies have shown that Pacific herring populations in the Bering Sea and north-east Pacific Ocean can be grouped based on similar recruitment time series. The scale of these groups suggests large-scale influence on recruitment fluctuations from the environment. Recruitment time series from 14 populations were analysed to determine links to various environmental variables and to develop recruitment forecasting models using a Ricker-type environmentally dependent spawner–recruit model. The environmental variables used for this investigation included monthly time series of the following: southern oscillation index, North Pacific pressure index, sea surface temperatures, air temperatures, coastal upwelling indices, Bering Sea wind, Bering Sea ice cover, and Bering Sea bottom temperatures. Exploratory correlation analysis was used for focusing the time period examined for each environmental variable. Candidate models for forecasting herring recruitment were selected by the ordinary and recent cross-validation prediction errors. Results indicated that forecasting models using air and sea surface temperature data lagged to the year of spawning generally produced the best forecasting models. Multiple environmental variables showed marked improvements in prediction over single-environmental-variable models.     

Climate and stock influences on the spread and locations of catches in the northeast Atlantic mackerel fishery

The poleward movements of northeast Atlantic (NEA) mackerel (Scomber scombrus) catches, possibly linked to climate change, are causing a major international disagreement over quotas. We present an analysis of spatially resolved catch data from 1977 to 2013 that shows how a northward shift is only part of the change in the fishery. There was a 30‐yr trend for declining catches per ICES rectangle (0.5° latitude by 1°‐degree longitude) until 2011–2013. Catches also moved further offshore, to areas of deeper waters. Segmented regressions suggested discontinuities in the temporal pattern of change in catch‐related variables. In particular, the number of ICES rectangles fished rose sharply around 1987. Generalized additive models (GAMs) suggest that much of the movement of fishing activity to areas of deeper water can be associated with variation in the Atlantic Multidecadal Oscillation (AMO) and the North Atlantic Oscillation (NAO). GAM models had a lower predictive error than linear or simple autoregressive models of change in catch‐related variables. Although climate indices can be linked to some of the changes in catch, it may be difficult to extrapolate future patterns in the catch: some of the GAM smoothers are non‐linear, and the oceanographic processes linked to climate index values are not homogenous across the area occupied by mackerel. A practical implication of the reported changes in catch since 1977 is that vessels are now reportedly fishing further offshore, which has implications for fuel consumption and profitability of the fishery.