Catch-per-unit-effort and biological parameters from the Massachusetts coastal lobster (Homarus americanus) resource: Description and trends

Acomprehensive description of the Massachusetts coastal lobster (Homarus americanus) resou,rce was obtained by sampling commercial catches coastwide at sea and at dealerships between 1981 and 1986. Acommercial lobster sea-sampling program, wherein six coastal regions were sampled monthly, with an areal and temporal data weighting design, was the primary source of data. An improved index of catch per trap haul/set-over-day was generated by modeling the relationship between catch and immersion time and standardizing effort. This 6-year time-series of mean annual catch rates tracked closely the landings trend for territorial waters. During the study period there was a gradual increase in indices of exploitation and total annual mortality which corresponded to a gradual decline in mean carapace length of marketable lobster. The frequency of culls escalated from 10.0% in 1981 to 20.9% in 1986, while the percentage of lobster found dead in traps was consistently less than 1%. The sex ratio (%F:%M) was significantly different from 50:50 and approximated a 60:40 relationship during the study period. Male and female weight-length relationships were significantly different. Females weighed more than males at smaller sizes and less than males at larger sizes. A north-south clinal trend was evident wherein lobster north of Cape Cod weighed less at length than those from regions south of Cape Cod. Functional size-maturity relationships were developed for female lobster by staging cement gland development. Proportions mature at size represent more realistic values than those obtained by analyses of percent of females ovigerous. Regional variation occurred in most of the parameters studied. Three lobster groups, differing in major population descriptors, are defined by our data.(PDF file contains 28 pages.)

Quantifying the impact of environmental variables upon catch-per-unit-effort of the Blue Shark Prionace glauca in the Western English Channel

The effect of environmental variables on blue shark Prionace glauca catch per unit effort (CPUE) in a recreational fishery in the western English Channel, between June and September 1998–2011, was quantified using generalized additive models (GAMs). Sea surface temperature (SST) explained 1·4% of GAM deviance, and highest CPUE occurred at 16·7° C, reflecting the optimal thermal preferences of this species. Surface chlorophyll a concentration (CHL) significantly affected CPUE and caused 27·5% of GAM deviance. Additionally, increasing CHL led to rising CPUE, probably due to higher productivity supporting greater prey biomass. The density of shelf-sea tidal mixing fronts explained 5% of GAM deviance, but was non-significant, with increasing front density negatively affecting CPUE. Time-lagged frontal density significantly affected CPUE, however, causing 12·6% of the deviance in a second GAM and displayed a positive correlation. This outcome suggested a delay between the evolution of frontal features and the subsequent accumulation of productivity and attraction of higher trophic level predators, such as P. glauca.

Quantifying the impact of environmental variables upon catch-per-unit-effort of the Blue Shark Prionace glauca in the Western English Channel

The effect of environmental variables on blue shark Prionace glauca catch per unit effort (CPUE) in a recreational fishery in the western English Channel, between June and September 1998–2011, was quantified using generalized additive models (GAMs). Sea surface temperature (SST) explained 1·4% of GAM deviance, and highest CPUE occurred at 16·7° C, reflecting the optimal thermal preferences of this species. Surface chlorophyll a concentration (CHL) significantly affected CPUE and caused 27·5% of GAM deviance. Additionally, increasing CHL led to rising CPUE, probably due to higher productivity supporting greater prey biomass. The density of shelf-sea tidal mixing fronts explained 5% of GAM deviance, but was non-significant, with increasing front density negatively affecting CPUE. Time-lagged frontal density significantly affected CPUE, however, causing 12·6% of the deviance in a second GAM and displayed a positive correlation. This outcome suggested a delay between the evolution of frontal features and the subsequent accumulation of productivity and attraction of higher trophic level predators, such as P. glauca.

Population biology of Uca thayeri Rathbun, 1900 (Brachyura, Ocypodidae) in a subtropical South American mangrove area: Results from transect and catch-per-unit-effort techniques

The population biology of Uca thayeri was studied in a subtropical mangrove in Ubatuba, State of São Paulo, Brazil. Two sampling techniques were used: transect sampling and catch-per-unit-effort. Size frequency distribution, sex-ratio, and reproductive period were analysed. For juvenile crabs (CW < 4.6 mm), the transect procedure was most efficient, while ovigerous females were most collected during the capture effort. Males were most numerous in the transect technique, while in the catch-per-unit-effort there was no difference between sexes. The species showed a different size frequency distribution for each sampling procedure. The reproduction of U. thayeri is seasonal, being more pronounced in the warmer months of the year. However, juveniles occurred all over the year, although more numerous in the colder months. The success of the species in reproductive activity and the constant colonization of the area can be attributed to the availability of food resources and differential occupation of the habitat by ovigerous females.

Catch-per-unit-effort: which estimator is best?

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Comparing three indices of catch per unit effort using Bayesian geostatistics

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Estimating whole-lake fish catch per unit effort

The European standard for gillnetsampling to characterize lake fish communities stratifies sampling effort (i.e., number of nets) within depth strata. Nets to sample benthic habitats are randomly distributed throughout the lake within each depth strata. Pelagic nets are also stratified by depth, but are set only at the deepest point of the lake. Multiple authors have suggested that this design under-represents pelagic habitats, resulting in estimates of whole-lake CPUE and community composition which are disproportionately influenced by ecological conditions of littoral and benthic habitats. To address this issue, researchers have proposed estimating whole-lake CPUE by weighting the catch rate in each depth-compartment by the proportion of the volume of the lake contributed by the compartment. Our study aimed to assess the effectiveness of volume-weighting by applying it to fish communities sampled according to the European standard (CEN), and by a second whole-lake gillnetting protocol (VERT), which prescribes additional fishing effort in pelagic habitats. We assume that convergence between the protocols indicates that volume-weighting provides a more accurate estimate of whole-lake catch rate and community composition. Our results indicate that volume-weighting improves agreement between the protocols for whole-lake total CPUE, estimated proportion of perch and roach and the overall fish community composition. Discrepancies between the protocols remaining after volume-weighting maybe because sampling under the CEN protocol overlooks horizontal variation in pelagic fish communities. Analyses based on multiple pelagic-set VERT nets identified gradients in the density and biomass of pelagic fish communities in almost half the lakes that corresponded with the depth of water at net-setting location and distance along the length of a lake. Additional CEN pelagic sampling effort allocated across water depths and distributed throughout the lake would therefore help to reconcile differences between the sampling protocols and, in combination with volume-weighting, converge on a more accurate estimate of whole-lake fish communities.

Response of Catch-Per-Unit-Effort to Spatial and Environmental Factors: an Exploratory Data Analysis Using Generalized Additive Models

Understanding spatial distributions and how environmental conditions influence catch-per-unit-effort (CPUE) is important for increased fishing efficiency and sustainable fisheries management. This study investigated the relationship between CPUE, spatial factors, temperature, and depth using generalized additive models. Combinations of factors, and not one single factor, were frequently included in the best model. Parameters which best described CPUE varied by geographic region. The amount of variance, or deviance, explained by the best models ranged from a low of 29% (halibut, Charlotte region) to a high of 94% (sablefish, Charlotte region). Depth, latitude, and longitude influenced most species in several regions. On the broad geographic scale, depth was associated with CPUE for every species, except dogfish. Latitude and longitude influenced most species, except halibut (Areas 4 A/D), sablefish, and cod. Temperature was important for describing distributions of halibut in Alaska, arrowtooth flounder in British Columbia, dogfish, Alaska skate, and Aleutian skate. The species-habitat relationships revealed in this study can be used to create improved fishing and management strategies.

Distribution of catch-per-unit-of-effort and fishing effort for tuna in the Eastern Tropical Pacific Ocean by months of the year 1951-1960

ENGLISH: Comparison of physical and biological environmental factors affecting the aggregation of tunas with the success of fishing by the commercial fleets, requires that catch and effort data be examined in greater detail than has been presented in these publications. Consequently, the United States Bureau of Commercial Fisheries Biological Laboratory, San Diego, to serve the needs of its program of research on causes of variations in tuna abundance, made arrangements with the Tuna Commission to summarize these catch and effort data by month, by one-degree area, by fishing vessel size-class, for the years 1951-1960 for bait boats and 1953-1960 for purse-seiners. The present paper describes the techniques employed in summarizing these data by automatic data processing methods. It also presents the catch and effort information by months, by five-degree areas and certain combinations of five-degree areas for use by fishermen, industry personnel, and research agencies. Because of space limitations and other considerations, the one-degree tabulations are not included but are available at the Tuna Commission and Bureau laboratories. SPANISH: La comparación de los factores ambientales físicos y biológicos que afectan la agrupación del atún, con el éxito obtenido en la pesca por las flotas comerciales, requiere que los datos sobre la captura y el esfuerzo sean examinados con mayor detalle de lo que han sido presentados en estas publicaciones. En consecuencia, el Laboratorio Biológico del Buró de Pesquerías Comerciales de los Estados Unidos, situado en San Diego, a fin de llenar los requisitos de su programa de investigación sobre las causas de las variaciones en la abundancia del atún, hizo arreglos con la Comisión del Atún para sumarizar esos datos sobre la captura y el esfuerzo por meses, por áreas de un grado, por clases de tamaño de las embarcaciones de pesca durante los años 1951-1960 en lo que concierne a los barcos de carnada y durante el período 1953-1960 en lo que respecta a los barcos rederos. El presente trabajo describe la técnica empleada en la sumarización de dichos datos mediante métodos automáticos de manejo de datos. También se da aquí la información sobre la captura y el esfuerzo por meses, por áreas de cinco grados y ciertas combinaciones de áreas de cinco grados para el uso de los pescadores, del personal de la industria y de las oficinas de investigación. Por falta de espacio y otras razones, las tabulaciones de las áreas de un grado no han sido incluídos en este trabajo, pero están a la disposición de quien tenga interés en los laboratorios de la Comisión del Atún y del Buró.

Comparison between univariate and bivariate geostatistical models for estimating catch per unit of effort (cpue): A simulation study

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)