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)

Precision of age determination of northern offshore spotted dolphins.

We investigated within- and between-reader precision in estimating age for northern offshore spotted dolphins and possible effects on precision from the sex and age-class of specimens. Age was estimated from patterns of growth layer groups i n the dentine and cementum of the dolphins' teeth. Each specimen was aged at least three times by each of two persons. Two data samples were studied. The first comprised 800 of each sex from animals collected during 1973-78. The second included 45 females collected during 1981. There were significant, generally downward trends through time in the estimates from multiple readings of the 1973-78 data. These trends were slight, and age distributions from last readings and mean estimates per specimen appeared to be homogeneous. The largest factor affecting precision in the 1973-78 data set was between-reader variation. In light of the relatively high within-reader precision (trends considered), the consistent between-reader differences suggest a problem of accuracy rather than precision for this series. Within-reader coefficients of variation averaged approximately 7% and 11%. Pooling the data resulted i n an average coefficient of variation near 16%. Within- and between-reader precision were higher for the 1981 sample, and the data homogeneous over both factors. CVs averaged near 5% and 6% for the two readers. These results point to further refinements in reading the 1981 series. Properties of the 1981 sample may be partly responsible for greater precision: by chance there were proportionately fewer older dolphins included, and preparation and selection criteria were probably more stringent. (PDF contains 35 pages.)

Studies on the condition factor of the Sierra Leone mangrove oyster (Crassostrea tulipa)

Sierra Leone is a tropical country where water temperatures are high throughout the year. Consequently the local oysters tend to spawn the year round, with one or two spawning peaks. The condition of such tropical oysters may not be as high as those oyesters in temperate countries since the stored glycogen is regularly utilized to form gonads. A high condition factor value indicates that the oysters have accumulated glycogen and or gonads, whereas a low condition factor value indicates that the oysters have spawned and are in the process of accumulating glycogen, which may later be utilized for gonad development. In oyster culture, condition factor studies may be supported by plankton and oyster spat settlement studies in the culture area. These studies give an indication of when oyster larvae and spat settlement are at their peak values. In Sierra Leone studies of the plankton and spat settlement are undertaken every week throughout the year. Conditions factor is obtained from the ratio weight of dry (oyster) meat x 1000/internal volume. Detailed condition factor values are shown in relation to salinity at two stations. Condition factor declines with reducing salinity, which principally occurs during the rainy season. The best times to collect spat are May to June and September to October

Oyster spat set on natural clutch in the Maryland portion of the Chesapeake Bay (1939 - 1975)

Basically this report is an attempt to document trends in oyster recruitment since 1939 and to relate those trends to the actual oyster harvest throughout the Maryland portion of the Chesapeake Bay. It is also hoped that the data as well as the charts compiled in this report will serve as a reference to aid in future studies on Chesapeake Bay oysters. A few if the major biological factors that affect the natural reproduction of the oyster and environmental degradations that may possibly affect oyster reproduction or harvest in the Chesapeake Bay are also briefly discussed. (PDF contains 32 pages)