The Effects of Salinity, Temperature, and Food on the Growth and Reproductive Output of Polydora nuchalis Woodick, 1953

Polydora nuchalis Woodwick, 1953 (Polychaeta: Spionidae) is a protandric hermaphrodite commonly inhabiting intertidal mud flats in southern California. The species exhibits lecithotrophic larval development and adelphophagia. Reproduction of P. nuchalis was monitored for a year at four sites: Catalina Harbor, San Gabriel River, Huntington Harbour, and Malibu Lagoon. Females deposited from 11 to 31 egg capsules in their tubes, with up to 230 eggs per capsule. An average of 3% of the eggs developed into larvae: the remaining were nurse eggs serving as food for the developing larvae. Reproductive output was quantified by determining the number and size of larvae and nurse eggs for individual capsules. Significant differences among the four populations were found for all the quantified variables. In addition, two size classes of nurse eggs were found to exist in capsules from all of the sites. Egg capsules were found throughout the year at San Gabriel River, but none were found during the winter months at the remaining three sites. Size/frequency data for juveniles and adults of the Catalina Harbor population indicate an annual cycle of recruitment. The laboratory experiment consisted of a 3 x 3 x 2 £actor1al design with replication testing the effects of temperature, salinity, and food supply on growth and reproduction of P. nuchalis. Increasing temperature resulted in significantly increased survivorship, growth rates, and percentage reproduction. It also produced a significant decrease in the size of the nurse eggs and the volume of food per larva. The number of egg capsules was maximum at the intermediate temperature. Increasing the salinity resulted in significant increases in survivorship and Class I nurse egg size. Increaaing food availability produced a significant increase in the percentage of worms reproducing. The interactive effect of salinity and £ood level produced significant changes in the number of larvae per capsule and the number of nurse eggs per capsule. However, the number of nurse eggs per larva did not differ significantly among the experimental treatment groups. (PDF contains 129 pages)

User’s Guide to ADMB2R: A Set of AD Model Builder Output Routines Compatible with the R Statistics Language

ADMB2R is a collection of AD Model Builder routines for saving complex data structures into a file that can be read in the R statistics environment with a single command.1 ADMB2R provides both the means to transfer data structures significantly more complex than simple tables, and an archive mechanism to store data for future reference. We developed this software because we write and run computationally intensive numerical models in Fortran, C++, and AD Model Builder. We then analyse results with R. We desired to automate data transfer to speed diagnostics during working-group meetings. We thus developed the ADMB2R interface to write an R data object (of type list) to a plain-text file. The master list can contain any number of matrices, values, dataframes, vectors or lists, all of which can be read into R with a single call to the dget function. This allows easy transfer of structured data from compiled models to R. Having the capacity to transfer model data, metadata, and results has sharply reduced the time spent on diagnostics, and at the same time, our diagnostic capabilities have improved tremendously. The simplicity of this interface and the capabilities of R have enabled us to automate graph and table creation for formal reports. Finally, the persistent storage in files makes it easier to treat model results in analyses or meta-analyses devised months—or even years—later. We offer ADMB2R to others in the hope that they will find it useful. (PDF contains 30 pages)

User’s Guide to C2R: A Set of C Language Output Routines Compatible with the R Statistics Language

C2R is a collection of C routines for saving complex data structures into a file that can be read in the R statistics environment with a single command.1 C2R provides both the means to transfer data structures significantly more complex than simple tables, and an archive mechanism to store data for future reference. We developed this software because we write and run computationally intensive numerical models in Fortran, C++, and AD Model Builder. We then analyse results with R. We desired to automate data transfer to speed diagnostics during working-group meetings. We thus developed the C2R interface to write an R data object (of type list) to a plain-text file. The master list can contain any number of matrices, values, dataframes, vectors or lists, all of which can be read into R with a single call to the dget function. This allows easy transfer of structured data from compiled models to R. Having the capacity to transfer model data, metadata, and results has sharply reduced the time spent on diagnostics, and at the same time, our diagnostic capabilities have improved tremendously. The simplicity of this interface and the capabilities of R have enabled us to automate graph and table creation for formal reports. Finally, the persistent storage in files makes it easier to treat model results in analyses or meta-analyses devised months—or even years—later. We offer C2R to others in the hope that they will find it useful. (PDF contains 27 pages)

User’s Guide to For2R: A Module of Fortran 95 Output Routines Compatible with the R Statistics Language

For2R is a collection of Fortran routines for saving complex data structures into a file that can be read in the R statistics environment with a single command.1 For2R provides both the means to transfer data structures significantly more complex than simple tables, and an archive mechanism to store data for future reference. We developed this software because we write and run computationally intensive numerical models in Fortran, C++, and AD Model Builder. We then analyse results with R. We desired to automate data transfer to speed diagnostics during working-group meetings. We thus developed the For2R interface to write an R data object (of type list) to a plain-text file. The master list can contain any number of matrices, values, dataframes, vectors or lists, all of which can be read into R with a single call to the dget function. This allows easy transfer of structured data from compiled models to R. Having the capacity to transfer model data, metadata, and results has sharply reduced the time spent on diagnostics, and at the same time, our diagnostic capabilities have improved tremendously. The simplicity of this interface and the capabilities of R have enabled us to automate graph and table creation for formal reports. Finally, the persistent storage in files makes it easier to treat model results in analyses or meta-analyses devised months—or even years—later. We offer For2R to others in the hope that they will find it useful. (PDF contains 31 pages)

Aspects of the fishing industry and an overview of artificial reefs and fish aggregating devices for increasing fisheries output and viability in Nigeria

Aspects of the Nigerian fishing industry are outlined to explain the concept of fishing systems viability which is often influenced by a combination of factors including biological productivity, as well as technical, economic and social factors. The productivity of the aquatic environments can be increased by the construction and installation of artificial reefs and fish aggregating devices. These man-made structures provide shelters, food and breeding grounds for fin fish and shell fish. The habitat enhancement techniques are appropriate, efficient, cheap and simple strategic options for increase in fish production. Recommendations for effective utilization and long term management are outlined.

La pêche au chalut en Côte d'Ivoire. Maximum de rendement économique

This paper analyses the relations between effort and catch per unit effort of trawlers which worked in Côte d'Ivoire from Jan 1966 to Dec 1970. A fishing effort permitting to exploit fishery in the best rentability conditions is proposed.

Estimating the maximum sustainable yield of bonito (Sarda chiliensis, Scombridae) of northern Chile from monthly catch data

Monthly catch data of bonito Sarda chiliensis from northern Chile, from 1976 to 1989, were used to obtain a series of estimates of the Z-G parameter (i.e., total mortality minus the growth coefficient in weight). This series was then used to estimate a maximum sustainable yield of 4,500 t/year through a modified version of the surplus production model of J. Csirke and J. Caddy. The status of the fishery is discussed.

Estimating input demand and output supply elasticities in gillnet and seine fishing in Guimaras Strait and adjacent waters

This contribution is a summary of the results of the study conducted by the University of the Philippines in the Visayas team from November 1990 to June 1991. The purpose of this research is to estimate demand and output supply elasticities in gillnet and seine fishing in Guimaras Strait (Philippines) and adjacent waters.

Maximum likelihood estimation of mortality and growth with individual variability from multiple length-frequency data

We consider estimation of mortality rates and growth parameters from length-frequency data of a fish stock and derive the underlying length distribution of the population and the catch when there is individual variability in the von Bertalanffy growth parameter L∞. The model is flexible enough to accommodate 1) any recruitment pattern as a function of both time and length, 2) length-specific selectivity, and 3) varying fishing effort over time. The maximum likelihood method gives consistent estimates, provided the underlying distribution for individual variation in growth is correctly specified. Simulation results indicate that our method is reasonably robust to violations in the assumptions. The method is applied to tiger prawn data (Penaeus semisulcatus) to obtain estimates of natural and fishing mortality.