Estimating relative abundance from catch and effort data, using neural networks

We develop and test a method to estimate relative abundance from catch and effort data using neural networks. Most stock assessment models use time series of relative abundance as their major source of information on abundance levels. These time series of relative abundance are frequently derived from catch-per-unit-of-effort (CPUE) data, using general linearized models (GLMs). GLMs are used to attempt to remove variation in CPUE that is not related to the abundance of the population. However, GLMs are restricted in the types of relationships between the CPUE and the explanatory variables. An alternative approach is to use structural models based on scientific understanding to develop complex non-linear relationships between CPUE and the explanatory variables. Unfortunately, the scientific understanding required to develop these models may not be available. In contrast to structural models, neural networks uses the data to estimate the structure of the non-linear relationship between CPUE and the explanatory variables. Therefore neural networks may provide a better alternative when the structure of the relationship is uncertain. We use simulated data based on a habitat based-method to test the neural network approach and to compare it to the GLM approach. Cross validation and simulation tests show that the neural network performed better than nominal effort and the GLM approach. However, the improvement over GLMs is not substantial. We applied the neural network model to CPUE data for bigeye tuna (Thunnus obesus) in the Pacific Ocean.

An Evaluation of the area stratification used for sampling tunas in the eastern Pacific Ocean and implications for estimating total annual catches

The Inter-American Tropical Tuna Commission (IATTC) staff has been sampling the size distributions of tunas in the eastern Pacific Ocean (EPO) since 1954, and the species composition of the catches since 2000. The IATTC staff use the data from the species composition samples, in conjunction with observer and/or logbook data, and unloading data from the canneries to estimate the total annual catches of yellowfin (Thunnus albacares), skipjack (Katsuwonus pelamis), and bigeye (Thunnus obesus) tunas. These sample data are collected based on a stratified sampling design. I propose an update of the stratification of the EPO into more homogenous areas in order to reduce the variance in the estimates of the total annual catches and incorporate the geographical shifts resulting from the expansion of the floating-object fishery during the 1990s. The sampling model used by the IATTC is a stratified two-stage (cluster) random sampling design with first stage units varying (unequal) in size. The strata are month, area, and set type. Wells, the first cluster stage, are selected to be sampled only if all of the fish were caught in the same month, same area, and same set type. Fish, the second cluster stage, are sampled for lengths, and independently, for species composition of the catch. The EPO is divided into 13 sampling areas, which were defined in 1968, based on the catch distributions of yellowfin and skipjack tunas. This area stratification does not reflect the multi-species, multi-set-type fishery of today. In order to define more homogenous areas, I used agglomerative cluster analysis to look for groupings of the size data and the catch and effort data for 2000–2006. I plotted the results from both datasets against the IATTC Sampling Areas, and then created new areas. I also used the results of the cluster analysis to update the substitution scheme for strata with catch, but no sample. I then calculated the total annual catch (and variance) by species by stratifying the data into new Proposed Sampling Areas and compared the results to those reported by the IATTC. Results showed that re-stratifying the areas produced smaller variances of the catch estimates for some species in some years, but the results were not significant.

An evaluation of mark and recapture techniques for estimating tigerfish biomass in Lake Kariba

The effectiveness of 2 mark and recapture techniques was evaluated using tiger fish, Hydrocynus vittatus. The 2 techniques used were: tagging with a plastic tag and fluorescent spray marking. While the tagging method resulted as the logical method to use within the constraints of the tiger fish study, it cannot be considered completely reliable for the estimation of population size in Lake Kariba.

Estimating the abundance of clustered and cryptic marine macro-invertebrates in the Galápagos with particular reference to sea cucumbers

Estimating the abundance of marine macro-invertebrates is complicated by a variety of factors: 1) human factors, such as diver efficiency and diver error; and 2) biological factors, such as aggregation of organisms, crypsis, and nocturnal emergence behavior. Diver efficiency varied according to the detectability of an organism causing under-estimation of density by up to 50% in some species. All common species were aggregated at scales from 10-50 m. Transects need to be long enough to transcend the scale of patchiness to improve accuracy. Some species of sea urchins and sea cucumbers (pepinos) which are cryptic by day emerged at night so that daytime censuses underestimated their abundance by up to 10 times. In the sea cucumber fishery, estimates of abundance need to be made at the scale of the population, i.e. at hundreds of km. A strategy for this is proposed.

Evaluation of bioelectrical impedance analysis and Fulton’s condition factor as nonlethal techniques for estimating short-term responses in postsmolt Atlantic salmon (Salmo salar) to food availabili

We evaluated measures of bioelectrical impedance analysis (BIA) and Fulton’s condition factor (K) as potential nonlethal indices for detecting short-term changes in nutritional condition of postsmolt Atlantic salmon (Salmo salar). Fish reared in the laboratory for 27 days were fed, fasted, or fasted and then refed. Growth rates and proximate body composition (protein, fat, water) were measured in each fish to evaluate nutritional status and condition. Growth rates of fish responded rapidly to the absence or reintroduction of food, whereas body composition (% wet weight) remained relatively stable owing to isometric growth in fed fish and little loss of body constituents in fasted fish, resulting in nonsignificant differences in body composition among feeding treatments. The utility of BIA and Fulton’s K as condition indices requires differences in body composition. In our study, BIA measures were not significantly different among the three feeding treatments, and only on the final day of sampling was K of fasted vs. fed fish significantly different. BIA measures were correlated with body composition content; however, wet weight was a better predictor of body composition on both a content and concentration (% wet weight) basis. Because fish were growing isometrically, neither BIA nor K was well correlated with growth rate. For immature fish, where growth rate, rather than energy reserves, is a more important indicator of fish condition, a nonlethal index that reflects shortterm changes in growth rate or the potential for growth would be more suitable as a condition index than either BIA measures or Fulton�

An evaluation of the effects of blue crab (Callinectes sapidus) behavior on the efficacy of crab pots as a tool for estimating population abundance

Crab traps have been used extensively in studies on the population dynamics of blue crabs to provide estimates of catch per unit of effort; however, these estimates have been determined without adequate consideration of escape rates. We examined the ability of the blue crab (Callinectes sapidus) to escape crab pots and the possibility that intraspecific crab interactions have an effect on catch rates. Approximately 85% of crabs that entered a pot escaped, and 83% of crabs escaped from the bait chamber (kitchen). Blue crabs exhibited few aggressive behavioral interactions in and around the crab pot and were documented to move freely in and out of the pot. Both the mean number and size of crabs caught were significantly smaller at deeper depths. Results from this study show that current estimates of catch per unit of effort may be biased given the high escape rate of blue crabs documented in this study. The results of this paper provide a mechanistic view of trap efficacy, and reveal crab behavior in and around commercial crab pots.

Incorporating fishery observer data into an integrated catch-at-age and multiyear tagging model for estimating mortality rates and abundance

Tagging experiments are a useful tool in fisheries for estimating mortality rates and abundance of fish. Unfortunately, nonreporting of recovered tags is a common problem in commercial fisheries which, if unaccounted for, can render these estimates meaningless. Observers are often employed to monitor a portion of the catches as a means of estimating reporting rates. In our study, observer data were incorporated into an integrated model for multiyear tagging and catch data to provide joint estimates of mortality rates (natural and f ishing), abundance, and reporting rates. Simulations were used to explore model performance under a range of scenarios (e.g., different parameter values, parameter constraints, and numbers of release and recapture years). Overall, results indicated that all parameters can be estimated with reasonable accuracy, but that fishing mortality, reporting rates, and abundance can be estimated with much higher precision than natural mortality. An example of how the model can be applied to provide guidance on experimental design for a large-scale tagging study is presented. Such guidance can contribute to the successful and cost-effective management of tagging programs for commercial fisheries.

Validation of a method for estimating realized annual fecundity in a multiple spawner, the long-snouted seahorse (Hippocampus guttulatus), using underwater visual census

The long-snouted seahorse (Hippocampus guttulatus) (Cuvier, 1829), was used to validate the pre-dictive accuracy of three progressively realistic models for estimating the realized annual fecundity of asyn-chronous, indeterminate, multiple spawners. Underwater surveys and catch data were used to estimate the duration of the reproductive season, female spawning frequency, male brooding frequency, and batch fecun-dity. The most realistic model, a generalization of the spawning fraction method, produced unbiased estimates of male brooding frequency (mean ±standard deviation [SD]=4.2 ±1.6 broods/year). Mean batch fecundity and realized annual fecundity were 213.9 (±110.9) and 903.6 (±522.4), respectively. However, females prepared significantly more clutches than the number of broods produced by males. Thus, methods that infer spawning frequency from patterns in female egg production may lead to significant overestimates of realized annual fecundity. The spawning fraction method is broadly applicable to many taxa that exhibit parental care and can be applied nondestructively to species for which conservation is a concern.

Comparison of survey methods for estimating abundance of harbor seals (Phoca vitulina) in glacial fjords

The importance of glacial ice habitats to harbor seals (Phoca vitulina) in Alaska has become increasingly apparent. However, enumerating harbor seals hauled out on ice in glacial fjords has been difficult. At Johns Hopkins Inlet in Glacier Bay, Alaska, we compared a shore-based counting method to a large-format aerial photography method to estimate seal abundance. During each aerial survey, shore-based observers simultaneously counted seals from an observation post. Both survey methods incurred errors in double-counting and missing seals, especially when ice movements caused seals to drift between survey zones. Advantages of shore-based counts included the ability to obtain multiple counts for relatively little cost, distinguish pups from adults, and to distinguish mobile seals from shadows or glacial debris of similar size. Aerial photography provided a permanent record of each survey, allowing both a reconciliation of counts in overlapping zones and the documentation of the spatial distribution of seals and ice within the fjord.

Estimating species and size composition of rockfishes to verify targets in acoustic surveys of untrawlable areas

Rockfish (Sebastes spp.) biomass is difficult to assess with standard bottom trawl or acoustic surveys because of their propensity to aggregate near the seafloor in highrelief areas that are inaccessible to sampling by trawling. We compared the ability of a remotely operated vehicle (ROV), a modified bottom trawl, and a stereo drop camera system (SDC) to identify rockfish species and estimate their size composition. The ability to discriminate species was highest for the bottom trawl and lowest for the SDC. Mean lengths and size distributions varied among the gear types, although a larger number of length measurements could be collected with the bottom trawl and SDC than with the ROV. Dusky (S. variabilis), harlequin (S. variegatus), and northern rockfish (S. polyspinis), and Pacific ocean perch (S. alutus) were the species observed in greatest abundance. Only dusky and northern rockfish regularly occurred in trawlable areas, whereas these two species and many more occurred in untrawlable areas. The SDC was able to resolve the height of fish off the seafloor, and some of the rockfish species were observed only near the seafloor in the acoustic dead zone. This finding is important, in that fish found exclusively in the acoustic dead zone cannot be assessed acoustically. For these species, methods such as bottom trawls, long-lines, or optical surveys using line transect or area swept methods will be the only adequate means to estimate the abundance of these fishes. Our results suggest that the selection of appropriate methods for verifying targets will depend on the habitat types and species complexes to be examined.

Evaluating methods for estimating rare events with zero-heavy data: a simulation model estimating sea turtle bycatch in the pelagic longline fishery

Estimating rare events from zero-heavy data (data with many zero values) is a common challenge in fisheries science and ecology. For example, loggerhead sea turtles (Caretta caretta) and leatherback sea turtles (Dermochelys coriacea) account for less than 1% of total catch in the U.S. Atlantic pelagic longline fishery. Nevertheless, the Southeast Fisheries Science Center (SEFSC) of the National Marine Fisheries Service (NMFS) is charged with assessing the effect of this fishery on these federally protected species. Annual estimates of loggerhead and leatherback bycatch in a fishery can affect fishery management and species conservation decisions. However, current estimates have wide confidence intervals, and their accuracy is unknown. We evaluate 3 estimation methods, each at 2 spatiotemporal scales, in simulations of 5 spatial scenarios representing incidental capture of sea turtles by the U.S. Atlantic pelagic longline fishery. The delta-log normal method of estimating bycatch for calendar quarter and fishing area strata was the least biased estimation method in the spatial scenarios believed to be most realistic. This result supports the current estimation procedure used by the SEFSC.