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)

The integrated approach of water hyacinth control on Lake Kainji: with special regard to the design, construction and installation of a water hyacinth barrier across the River Niger

This document lists the undesirable effects of water hyacinth (Eichhornia crassipes) on fisheries in Lake Kainji (Nigeria) and the integrated Water Hyacinth Control Programme in its ongoing fisheries management and development activities on the lake. Special regard is given to the design, construction and installation of a water hyacinth barrier across the River Niger. (PDF contains 44 pages)

The Coastal Barrier Island Network (CBIN): Future management strategies for barrier islands

Barrier islands are ecosystems that border coastal shorelines and form a protective barrier between continental shorelines and the wave action originating offshore. In addition to forming and maintaining an array of coastal and estuarine habitats of ecological and economic importance, barrier island coastlines also include some of the greatest concentrations of human populations and accompanying anthropogenic development in the world. These islands have an extremely dynamic nature whereby major changes in geomorphology and hydrology can occur over short time periods (i.e. days, hours) in response to extreme episodic storm events such as hurricanes and northeasters. The native vegetation and geological stability of these ecosystems are tightly coupled with one another and are vulnerable to storm-related erosion events, particularly when also disturbed by anthropogenic development. (PDF contains 4 pages)

The use of otolith morphology to indicate the stock structure of common coral trout (Plectropomus leopardus) on the Great Barrier Reef, Australia

We investigated the use of otolith morphology to indicate the stock structure of an exploited serranid coral reef fish, Plectropomus leopardus, on the Great Barrier Reef (GBR), Australia. Otoliths were measured by traditional one-and two-dimensional measures (otolith length, width, area, perimeter, circularity, and rectangularity), as well as by Fourier analysis to capture the finer details of otolith shape. Variables were compared among four regions of the GBR separated by hundreds of kilometers, as well as among three reefs within each region, hundreds of meters to tens of kilometers apart. The temporal stability in otolith structure was examined by comparing two cohorts of fully recruited four-year-old P. leopardus collected two years before and two years after a signif icant disturbance in the southern parts of the GBR caused by a large tropical cyclone in March 1997. Results indicated the presence of at least two stocks of P. leopardus, although the structure of each stock varied depending on the cohort considered. The results highlight the importance of incorporating data from several years in studies using otolith morphology to discriminate temporary and possibly misleading signals from those that indicate persistent spatial structure in stocks. We conclude that otolith morphology can be used as an initial step to direct further research on groups of P. leopardus that have lived at least a part of their life in different environments.

Patterns of growth, mortality, and size of the tropical damselfish Acanthochromis polyacanthus across the continental shelf of the Great Barrier Reef

Age-based analyses were used to demonstrate consistent differences in growth between populations of Acanthochromis polyacanthus (Pomacentridae) collected at three distance strata across the continental shelf (inner, mid-, and outer shelf) of the central Great Barrier Reef (three reefs per distance stratum). Fish had significantly greater maximum lengths with increasing distance from shore, but fish from all distances reached approximately the same maximum age, indicating that growth is more rapid for fish found on outer-shelf reefs. Only one fish collected from inner-shelf reefs reached >100 mm SL, whereas 38−67% of fish collected from the outer shelf were >100 mm SL. The largest age class of adult-size fish collected from inner and mid-shelf locations comprised 3−4 year-olds, but shifted to 2-year-olds on outer-shelf reefs. Mortality schedules (Z and S) were similar irrespective of shelf position (inner shelf: 0.51 and 60.0%; mid-shelf: 0.48 and 61.8%; outer shelf: 0.43 and 65.1%, respectively). Age validation of captive fish indicated that growth increments are deposited annually, between the end of winter and early spring. The observed cross-shelf patterns in adult sizes and growth were unlikely to be a result of genetic differences between sample populations because all fish collected showed the same color pattern. It is likely that cross-shelf variation in quality and quantity of food, as well as in turbidity, are factors that contribute to the observed patterns of growth. Similar patterns of cross-shelf mortality indicate that predation rates varied little across the shelf. Our study cautions against pooling demographic parameters on broad spatial scales without consideration of the potential for cross-shelf variabil