Salmon stocks and fisheries in England and Wales, 2001. Preliminary assessment prepared for ICES, April 2002

This report presents a preliminary assessment of the state of salmon stocks and fisheries in England and Wales in 2001 to assist ICES in providing scientific advice to NASCO and to provide early feedback to fishery managers and anglers. The chief indicators of the state o f salmon stocks are normally the catches taken by rod and net fisheries. However, in 2001 angling was affected by the outbreak of foot and mouth disease (FMD), which restricted angling opportunities and access to rod fisheries in many parts of the country for lengthy periods. It is impossible to quantify the impact that FMD had on rod catches, although these were undoubtedly significantly reduced; net fisheries were unaffected by FMD. The declared salmon catch for 2001 (including those fish released alive by anglers) is provisionally estimated at 209 tonnes, representing some 57,000 fish, and comprising 153 tonnes (-43,000 fish) by nets and fixed engines and 56 tonnes (-14,000 fish) by rods. For direct comparison with previous years, it should be noted that the declared catch prior to the issue of a second reminder was about 49 tonnes (see below). An estimated 26 tonnes (43%) of the rod catch was released alive. These figures do not take account of catches of salmon which go unreported (including those taken illegally), and it is estimated that there may have been a total of 33 tonnes of additional fish caught in 2001; approximately 15% of all fish killed.

A historical review of the shad fisheries of North America

A review of the relative productivity and value of the shad fisheries of North America as reflected in recorded commercial catches. A review of reasons for the decline that are biological and socioeconomic. Factors that have been held responsible are: pollution; destruction or impairment of spawning and nursery areas; overfishing; hydroelectric and canal dams; natural fluctuations in abundance. Natural catastrophes, parasites, and predators are not considered important in causing the decrease in commercial production. Attempts to rehabilitate the fisheries by various means of stocking artificially-reared fry and pond-reared fingerling shad, appear to have failed in every instance. Introduction of shad fry on the Pacific Coast has resulted in a major fishery. The most significant program is a controlled catch management plan, operating at this time [1953] only in Maryland.

Effects of El Niño–Southern Oscillation events on catches of Bigeye Tuna (Thunnus obesus) in the eastern Indian Ocean off Java

The effects of El Niño–Southern Oscillation events on catches of Bigeye Tuna (Thunnus obesus) in the eastern Indian Ocean (EIO) off Java were evaluated through the use of remotely sensed environmental data (sea-surface-height anomaly [SSHA], sea-surface temperature [SST], and chlorophyll a concentration), and Bigeye Tuna catch data. Analyses were conducted for the period of 1997–2000, which included the 1997–98 El Niño and 1999–2000 La Niña events. The empirical orthogonal function (EOF) was applied to examine oceanographic parameters quantitatively. The relationship of those parameters to variations in catch distribution of Bigeye Tuna was explored with a generalized additive model (GAM). The mean hook rate was 0.67 during El Niño and 0.44 during La Niña, and catches were high where SSHA ranged from –21 to 5 cm, SST ranged from 24°C to 27.5°C, and chlorophyll-a concentrations ranged from 0.04 to 0.16 mg m–3. The EOF analysis confirmed that the 1997–98 El Niño affected oceanographic conditions in the EIO off Java. The GAM results indicated that SST was better than the other environmental factors (SSHA and chlorophyll-a concentration) as an oceanographic predictor of Bigeye Tuna catches in the region. According to the GAM predictions, the highest probabilities (70–80%) for Bigeye Tuna catch in 1997–2000 occurred during oceanographic conditions during the 1997–98 El Niño event.

Influence of soak time and fish accumulation on catches of reef fishes in a multispecies trap survey

Catch rates from fishery-independent surveys often are assumed to vary in proportion to the actual abundance of a population, but this approach assumes that the catchability coefficient (q) is constant. When fish accumulate in a gear, the rate at which the gear catches fish can decline, and, as a result, catch asymptotes and q declines with longer fishing times. We used data from long-term trap surveys (1990–2011) in the southeastern U.S. Atlantic to determine whether traps saturated for 8 reef fish species because of the amount of time traps soaked or the level of fish accumulation (the total number of individuals of all fish species caught in a trap). We used a delta-generalized-additive model to relate the catch of each species to a variety of predictor variables to determine how catch was influenced by soak time and fish accumulation after accounting for variability in catch due to the other predictor variables in the model. We found evidence of trap saturation for all 8 reef fish species examined. Traps became saturated for most species across the range of soak times examined, but trap saturation occurred for 3 fish species because of fish accumulation levels in the trap. Our results indicate that, to infer relative abundance levels from catch data, future studies should standardize catch or catch rates with nonlinear regression models that incorporate soak time, fish accumulation, and any other predictor variable that may ultimately influence catch. Determination of the exact mechanisms that cause trap saturation is a critical need for accurate stock assessment, and our results indicate that these mechanisms may vary considerably among species.

Biscayne Bay commercial pink shrimp, Farfantepenaeus duorarum, fisheries, 1986-2005

The Biscayne Bay bait (1986–2005) and food (1989–2005) fisheries for pink shrimp were examined using dealer-reported individual vessel-trip landings data, separated by waterbody code to represent only catches from Biscayne Bay. Annual landings varied little during the 1980’s and early 1990’s, and landings of the bait shrimp fishery exceeded those of the food shrimp fishery. The number of trips and landings in both fisheries increased from the late 1990’s through 2002 and food shrimp landings exceeded landings of bait shrimp; landings in both fisheries decreased sharply in 2003. Landings in both fisheries increased in 2004 and 2005, but the increase in food shrimp landings was stronger. Annual catch per trip was much lower in the bait fishery than the food fishery. Each fishery exploited shrimp of a different size. The bait fishery targeted shrimp less than 19 mm carapace length (CL), whereas the food fishery caught shrimp greater than 19 mm CL. We compared monthly bait shrimp catch per unit of effort (CPUE) from the fishery to an estimate of shrimp density from a fishery-independent sampling effort over a 3-yr period and found a strong statistical relationship with the density estimate lagged by 3 mo. The relationship supported the use of bait shrimp fishery CPUE as an index of abundance in upcoming assessments of the effect of a massive water-management-based ecosystem restoration project on pink shrimp in Biscayne Bay. Project implementation will affect freshwater inflows to the bay and salinity patterns. An abundance index with a lengthy pre-implementation history that can be carried into the operational phase of the restoration project will be invaluable in assessing project effects and protecting an important fishery resource of Biscayne Bay. The bait shrimp fishery can provide a continuing index of shrimp abundance from late 1986 forward.

Marine Fisheries Stock Assessment Improvement Plan: report of the National Marine Fisheries Service National Task Force for Improving Fish Stock Assessments

This report argues for greatly increased resources in terms of data collection facilities and staff to collect, process, and analyze the data, and to communicate the results, in order for NMFS to fulfill its mandate to conserve and manage marine resources. In fact, the authors of this report had great difficulty defining the "ideal" situation to which fisheries stock assessments and management should aspire. One of the primary objectives of fisheries management is to develop sustainable harvest policies that minimize the risks of overfishing both target species and associated species. This can be achieved in a wide spectrum of ways, ranging between the following two extremes. The first is to implement only simple management measures with correspondingly simple assessment demands, which will usually mean setting fishing mortality targets at relatively low levels in order to reduce the risk of unknowingly overfishing or driving ecosystems towards undesirable system states. The second is to expand existing data collection and analysis programs to provide an adequate knowledge base that can support higher fishing mortality targets while still ensuring low risk to target and associated species and ecosystems. However, defining "adequate" is difficult, especially when scientists have not even identified all marine species, and information on catches, abundances, and life histories of many target species, and most associated species, is sparse. Increasing calls from the public, stakeholders, and the scientific community to implement ecosystem-based stock assessment and management make it even more difficult to define "adequate," especially when "ecosystem-based management" is itself not well-defined. In attempting to describe the data collection and assessment needs for the latter, the authors took a pragmatic approach, rather than trying to estimate the resources required to develop a knowledge base about the fine-scale detailed distributions, abundances, and associations of all marine species. Thus, the specified resource requirements will not meet the expectations of some stakeholders. In addition, the Stock Assessment Improvement Plan is designed to be complementary to other related plans, and therefore does not duplicate the resource requirements detailed in those plans, except as otherwise noted.

Fish lost at sea: the effect of soak time on pelagic longline catches

Our analyses of observer records reveal that abundance estimates are strongly influenced by the timing of longline operations in relation to dawn and dusk and soak time— the amount of time that baited hooks are available in the water. Catch data will underestimate the total mortality of several species because hooked animals are “lost at sea.” They fall off, are removed, or escape from the hook before the longline is retrieved. For example, longline segments with soak times of 20 hours were retrieved with fewer skipjack tuna and seabirds than segments with soak times of 5 hours. The mortality of some seabird species is up to 45% higher than previously estimated. The effects of soak time and timing vary considerably between species. Soak time and exposure to dusk periods have strong positive effects on the catch rates of many species. In particular, the catch rates of most shark and billfish species increase with soak time. At the end of longline retrieval, for example, expected catch rates for broadbill swordfish are four times those at the beginning of retrieval. Survival of the animal while it is hooked on the longline appears to be an important factor determining whether it is eventually brought on board the vessel. Catch rates of species that survive being hooked (e.g. blue shark) increase with soak time. In contrast, skipjack tuna and seabirds are usually dead at the time of retrieval. Their catch rates decline with time, perhaps because scavengers can easily remove hooked animals that are dead. The results of our study have important implications for fishery management and assessments that rely on longline catch data. A reduction in soak time since longlining commenced in the 1950s has introduced a systematic bias in estimates of mortality levels and abundance. The abundance of species like seabirds has been over-estimated in recent years. Simple modifications to procedures for data collection, such as recording the number of hooks retrieved without baits, would greatly improve mortality estimates.

Estimation of bycatch in shrimp trawl fisheries: a comparison of estimation methods using field data and simulated data

Bycatch, or the incidental catch of nontarget organisms during fi shing operations, is a major issue in U.S. shrimp trawl fisheries. Because bycatch is typically discarded at sea, total bycatch is usually estimated by extrapolating from an observed bycatch sample to the entire fleet with either mean-per-unit or ratio estimators. Using both field observations of commercial shrimp trawlers and computer simulations, I compared five methods for generating bycatch estimates that were used in past studies, a mean-per-unit estimator and four forms of the ratio estimator, respectively: 1) the mean fish catch per unit of effort, where unit effort was a proxy for sample size, 2) the mean of the individual fish to shrimp ratios, 3) the ratio of mean fish catch to mean shrimp catch, 4) the mean of the ratios of fish catch per time fished (a variable measure of effort), and 5) the ratio of mean fish catch per mean time fished. For field data, different methods used to estimate bycatch of Atlantic croaker, spot, and weakfish yielded extremely different results, with no discernible pattern in the estimates by method, geographic region, or species. Simulated fishing fleets were used to compare bycatch estimated by the fi ve methods with “actual” (simulated) bycatch. Simulations were conducted by using both normal and delta lognormal distributions of fish and shrimp and employed a range of values for several parameters, including mean catches of fish and shrimp, variability in the catches of fish and shrimp, variability in fishing effort, number of observations, and correlations between fish and shrimp catches. Results indicated that only the mean per unit estimators provided statistically unbiased estimates, while all other methods overestimated bycatch. The mean of the individual fish to shrimp ratios, the method used in the South Atlantic Bight before the 1990s, gave the most biased estimates. Because of the statistically significant two- and 3-way interactions among parameters, it is unlikely that estimates generated by one method can be converted or corrected to estimates made by another method: therefore bycatch estimates obtained with different methods should not be compared directly.

Does the size of subsamples taken from multispecies trawl catches affect estimates of catch composition and abundance?

Although subsampling is a common method for describing the composition of large and diverse trawl catches, the accuracy of these techniques is often unknown. We determined the sampling errors generated from estimating the percentage of the total number of species recorded in catches, as well as the abundance of each species, at each increase in the proportion of the sorted catch. We completely partitioned twenty prawn trawl catches from tropical northern Australia into subsamples of about 10 kg each. All subsamples were then sorted, and species numbers recorded. Catch weights ranged from 71 to 445 kg, and the number of fish species in trawls ranged from 60 to 138, and invertebrate species from 18 to 63. Almost 70% of the species recorded in catches were “rare” in subsamples (less than one individual per 10 kg subsample or less than one in every 389 individuals). A matrix was used to show the increase in the total number of species that were recorded in each catch as the percentage of the sorted catch increased. Simulation modelling showed that sorting small subsamples (about 10% of catch weights) identified about 50% of the total number of species caught in a trawl. Larger subsamples (50% of catch weight on average) identified about 80% of the total species caught in a trawl. The accuracy of estimating the abundance of each species also increased with increasing subsample size. For the “rare” species, sampling error was around 80% after sorting 10% of catch weight and was just less than 50% after 40% of catch weight had been sorted. For the “abundant” species (five or more individuals per 10 kg subsample or five or more in every 389 individuals), sampling error was around 25% after sorting 10% of catch weight, but was reduced to around 10% after 40% of catch weight had been sorted.