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)

Assessment of Atlantic Red Drum for 1999: Northern and southern regions

An assessment of the status of the Atlantic stock of red drum is conducted using recreational and commercial data from 1986 through 1998. This assessment updates data and analyses from the 1989, 1991, 1992 and 1995 stock assessments on Atlantic coast red drum (Vaughan and Helser, 1990; Vaughan 1992; 1993; 1996). Since 1981, coastwide recreational catches ranged between 762,300 pounds in 1980 and 2,623,900 pounds in 1984, while commercial landings ranged between 60,900 pounds in 1997 and 422,500 pounds in 1984. In weight of fish caught, Atlantic red drum constitute predominantly a recreational fishery (ranging between 85 and 95% during the 1990s). Commercially, red drum continue to be harvested as part of mixed species fisheries. Using available length-frequency distributions and age-length keys, recreational and commercial catches are converted to catch in numbers at age. Separable and tuned virtual population analyses are conducted on the catch in numbers at age to obtain estimates of fishing mortality rates and population size (including recruitment to age 1). In tum, these estimates of fishing mortality rates combined with estimates of growth (length and weight), sex ratios, sexual maturity and fecundity are used to estimate yield per recruit, escapement to age 4, and static (or equilibrium) spawning potential ratio (static SPR, based on both female biomass and egg production). Three virtual analysis approaches (separable, spreadsheet, and FADAPT) were applied to catch matrices for two time periods (early: 1986-1991, and late: 1992-1998) and two regions (Northern: North Carolina and north, and Southern: South Carolina through east coast of Florida). Additional catch matrices were developed based on different treatments for the catch-and-release recreationally-caught red drum (B2-type). These approaches included assuming 0% mortality (BASEO) versus 10% mortality for B2 fish. For the 10% mortality on B2 fish, sizes were assumed the same as caught fish (BASEl), or positive difference in size distribution between the early period and the later period (DELTA), or intermediate (PROP). Hence, a total of 8 catch matrices were developed (2 regions, and 4 B2 assumptions for 1986-1998) to which the three VPA approaches were applied. The question of when offshore emigration or reduced availability begins (during or after age 3) continues to be a source of bias that tends to result in overestimates of fishing mortality. Additionally, the continued assumption (Vaughan and Helser, 1990; Vaughan 1992; 1993; 1996) of no fishing mortality on adults (ages 6 and older), causes a bias that results in underestimates of fishing mortality for adult ages (0 versus some positive value). Because of emigration and the effect of the slot limit for the later period, a range in relative exploitations of age 3 to age 2 red drum was considered. Tuning indices were developed from the MRFSS, and state indices for use in the spreadsheet and FADAPT VPAs. The SAFMC Red Drum Assessment Group (Appendix A) favored the FADAPT approach with catch matrix based on DELTA and a selectivity for age 3 relative to age 2 of 0.70 for the northern region and 0.87 for the southern region. In the northern region, estimates of static SPR increased from about 1.3% for the period 1987-1991 to approximately 18% (15% and 20%) for the period 1992-1998. For the southern region, estimates of static SPR increased from about 0.5% for the period 1988-1991 to approximately 15% for the period 1992-1998. Population models used in this assessment (specifically yield per recruit and static spawning potential ratio) are based on equilibrium assumptions: because no direct estimates are available as to the current status of the adult stock, model results imply potential longer term, equilibrium effects. Because current status of the adult stock is unknown, a specific rebuilding schedule cannot be determined. However, the duration of a rebuilding schedule should reflect, in part, a measure of the generation time of the fish species under consideration. For a long-lived, but relatively early spawning, species as red drum, mean generation time would be on the order of 15 to 20 years based on age-specific egg production. Maximum age is 50 to 60 years for the northern region, and about 40 years for the southern region. The ASMFC Red Drum Board's first phase recovery goal of increasing %SPR to at least 10% appears to have been met. (PDF contains 79 pages)

Saline-saturated DMSO-EDTA as a storage medium for microbial DNA analysis from coral mucus swab samples

The mucus surface layer of corals plays a number of integral roles in their overall health and fitness. This mucopolysaccharide coating serves as vehicle to capture food, a protective barrier against physical invasions and trauma, and serves as a medium to host a community of microorganisms distinct from the surrounding seawater. In healthy corals the associated microbial communities are known to provide antibiotics that contribute to the coral’s innate immunity and function metabolic activities such as biogeochemical cycling. Culture-dependent (Ducklow and Mitchell, 1979; Ritchie, 2006) and culture-independent methods (Rohwer, et al., 2001; Rohwer et al., 2002; Sekar et al., 2006; Hansson et al., 2009; Kellogg et al., 2009) have shown that coral mucus-associated microbial communities can change with changes in the environment and health condition of the coral. These changes may suggest that changes in the microbial associates not only reflect health status but also may assist corals in acclimating to changing environmental conditions. With the increasing availability of molecular biology tools, culture-independent methods are being used more frequently for evaluating the health of the animal host. Although culture-independent methods are able to provide more in-depth insights into the constituents of the coral surface mucus layer’s microbial community, their reliability and reproducibility rely on the initial sample collection maintaining sample integrity. In general, a sample of mucus is collected from a coral colony, either by sterile syringe or swab method (Woodley, et al., 2008), and immediately placed in a cryovial. In the case of a syringe sample, the mucus is decanted into the cryovial and the sealed tube is immediately flash-frozen in a liquid nitrogen vapor shipper (a.k.a., dry shipper). Swabs with mucus are placed in a cryovial, and the end of the swab is broken off before sealing and placing the vial in the dry shipper. The samples are then sent to a laboratory for analysis. After the initial collection and preservation of the sample, the duration of the sample voyage to a recipient laboratory is often another critical part of the sampling process, as unanticipated delays may exceed the length of time a dry shipper can remain cold, or mishandling of the shipper can cause it to exhaust prematurely. In remote areas, service by international shipping companies may be non-existent, which requires the use of an alternative preservation medium. Other methods for preserving environmental samples for microbial DNA analysis include drying on various matrices (DNA cards, swabs), or placing samples in liquid preservatives (e.g., chloroform/phenol/isoamyl alcohol, TRIzol reagent, ethanol). These methodologies eliminate the need for cold storage, however, they add expense and permitting requirements for hazardous liquid components, and the retrieval of intact microbial DNA often can be inconsistent (Dawson, et al., 1998; Rissanen et al., 2010). A method to preserve coral mucus samples without cold storage or use of hazardous solvents, while maintaining microbial DNA integrity, would be an invaluable tool for coral biologists, especially those in remote areas. Saline-saturated dimethylsulfoxide-ethylenediaminetetraacetic acid (20% DMSO-0.25M EDTA, pH 8.0), or SSDE, is a solution that has been reported to be a means of storing tissue of marine invertebrates at ambient temperatures without significant loss of nucleic acid integrity (Dawson et al., 1998, Concepcion et al., 2007). While this methodology would be a facile and inexpensive way to transport coral tissue samples, it is unclear whether the coral microbiota DNA would be adversely affected by this storage medium either by degradation of the DNA, or a bias in the DNA recovered during the extraction process created by variations in extraction efficiencies among the various community members. Tests to determine the efficacy of SSDE as an ambient temperature storage medium for coral mucus samples are presented here.

Life history and population dynamics of the finetooth shark (Carcharhinus isodon) in the northeastern Gulf of Mexico

The life history and population dynamics of the finetooth shark (Carcharhinus isodon) in the north-eastern Gulf of Mexico were studied by determining age, growth, size-at-maturity, natural mortality, productivity, and elasticity of vital rates of the population. The von Bertalanffy growth model was estimated as Lt=1559 mm TL (1–e–0.24 (t+2.07)) for females and Lt = 1337 mm TL (1–e–0.41 (t+1.39)) for males. For comparison, the Fabens growth equation was also fitted separately to observed size-at-age data, and the fits to the data were found to be similar. The oldest aged specimens were 8.0 and 8.1 yr, and theoretical longevity estimates were 14.4 and 8.5 yr for females and males, respectively. Median length at maturity was 1187 and 1230 mm TL, equivalent to 3.9 and 4.3 yr for males and females, respectively. Two scenarios, based on the results of the two equations used to describe growth, were considered for population modeling and the results were similar. Annual rates of survivorship estimated through five methods ranged from 0.850/yr to 0.607/yr for scenario 1 and from 0.840/yr to 0.590/yr for scenario 2. Productivities were 0.041/yr for scenario 1 and 0.038/yr for scenario 2 when the population level that produces maximum sustain-able yield is assumed to occur at an instantaneous total mortality rate (Z) equaling 1.5 M, and were 0.071/yr and 0.067/yr, when Z=2 M for scenario 1 and 2, respectively. Mean generation time was 6.96 yr and 6.34 yr for scenarios 1 and 2, respectively. Elasticities calculated through simulation of Leslie matrices averaged 12.6% (12.1% for scenario 2) for fertility, 47.7% (46.2% for scenario 2) for juvenile survival, and 39.7% (41.6% for scenario 2) for adult survival. In all, the finetooth shark exhibits life-history and population characteristics intermediate to those of sharks in the small coastal complex and those from some large coastal species, such as the blacktip shark (Carcharhinus limbatus).