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)

Resource management of dynamic coastal environments using synoptic measures from remote sensing

In addition to providing vital ecological services, coastal areas of North Carolina provide prized areas for habitation, recreation, and commercial fisheries. However, from a management perspective, the coasts of North Carolina are highly variable and complex. In-water constituents such as nutrients, suspended sediments, and chlorophyll a concentration can vary significantly over a broad spectrum of time and space scales. Rapid growth and land-use change continue to exert pressure on coastal lands. Coastal environments are also very vulnerable to short-term (e.g., hurricanes) and long-term (e.g., sea-level rise) natural changes that can result in significant loss of life, economic loss, or changes in coastal ecosystem functioning. Hence, the dynamic nature, effects of human-induced change over time, and vulnerability of coastal areas make it difficult to effectively monitor and manage these important state and national resources using traditional data collection technologies such as discrete monitoring stations and field surveys. In general, these approaches provide only a sparse network of data over limited time and space scales and generally are expensive and labor-intensive. Products derived from spectral images obtained by remote sensing instruments provide a unique vantage point from which to examine the dynamic nature of coastal environments. A primary advantage of remote sensing is that the altitude of observation provides a large-scale synoptic view relative to traditional field measurements. Equally important, the use of remote sensing for a broad range of research and environmental applications is now common due to major advances in data availability, data transfer, and computer technologies. To facilitate the widespread use of remote sensing products in North Carolina, the UNC Coastal Studies Institute (UNC-CSI) is developing the capability to acquire, process, and analyze remotely sensed data from several remote sensing instruments. In particular, UNC-CSI is developing regional remote sensing algorithms to examine the mobilization, transport, transformation, and fate of materials between coupled terrestrial and coastal ocean systems. To illustrate this work, we present the basic principles of remote sensing of coastal waters in the context of deriving information that supports efficient and effective management of coastal resources. (PDF contains 4 pages)

Dynamics of bigeye (Thunnus obesus) and yellowfin (T. albacares) tuna in Hawaii’s pelagic fisheries: analysis of tagging data with a bulk transfer model incorporating size-specific attrition

Tag release and recapture data of bigeye (Thunnus obesus) and yellowfin tuna (T. albacares) from the Hawaii Tuna Tagging Project (HTTP) were analyzed with a bulk transfer model incorporating size-specific attrition to infer population dynamics and transfer rates between various fishery components. For both species, the transfer rate estimates from the offshore handline fishery areas to the longline fishery area were higher than the estimates of transfer from those same areas into the inshore fishery areas. Natural and fishing mortality rates were estimated over three size classes: yellowfin 20–45, 46–55, and ≥56 cm and bigeye 29–55, 56–70, and ≥71 cm. For both species, the estimates of natural mortality were highest in the smallest size class. For bigeye tuna, the estimates decreased with increasing size and for yellowfin tuna there was a slight increase in the largest size class. In the Cross Seamount fishery, the fishing mortality rate of bigeye tuna was similar for all three size classes and represented roughly 12% of the gross attrition rate (includes fishing and natural mortality and emigration rates). For yellowfin tuna, fishing mortality ranged between 7% and 30%, the highest being in the medium size class. For both species, the overall attrition rate from the entire fishery area was nearly the same. However, in the specific case of the Cross Seamount fishery, the attrition rate for yellowfin tuna was roughly twice that for bigeye. This result indicates that bigeye tuna are more resident at the Seamount than yellowfin tuna, and larger bigeye tunas tend to reside longer than smaller individuals. This may result in larger fish being more vulnerable to capture in the Seamount fishery. The relatively low level of exchange between the Sea-mount and the inshore and longline fisheries suggests that the fishing activity at the Seamount need not be of great management concern for either species. However, given that the current exploitation rates are considered moderate (10–30%), and that Seamount aggregations of yellowfin and bigeye tuna are highly vulnerable to low-cost gear types, it is recommended that further increases in fishing effort for these species be monitored at Cross Seamount.

An ecological characterization of the marine resources of Vieques, Puerto Rico. Part I: Historical data synthesis

From the 1940s until 2003, portions of the island of Vieques, a municipality within the Commonwealth of Puerto Rico, were used by the US Navy as a base and training facility, resulting in development and zoning history that differ in comparison to other Caribbean islands. The majority of former Navy lands are now under the jurisdiction of the Department of the Interior’s Fish and Wildlife Service as a National Wildlife Refuge, while a smaller percentage of land was transferred to the Vieques municipality and the Puerto Rico Conservation Trust. An analysis of the distribution and status of the marine resources is timely in light of the recent land transfer, increases in development and tourism, and potential changes in marine zoning around the island. To meet this need, NOAA’s Biogeography Branch, in cooperation with the Office of Response and Restoration and other local and regional partners, conducted Part I of an ecological characterization to integrate historical data and research into a synthesis report. The overall objective of this report is to provide resource managers and residents a comprehensive characterization of the marine resources of Vieques to support research, monitoring, and management. For example, knowledge of the spatial distribution of physical features, habitats, and biological communities is necessary to make an informed decision of the establishment and placement of a marine protected area (MPA). The report is divided into chapters based on the physical environment (e.g., climate, geology, bathymetry), habitat types (e.g., reefs and hardbottom, seagrasses, mangroves) and major faunal groups (e.g. fish, turtles, birds). Each section includes five subsections: an overview, description of the relevant literature, methods of analysis, information on the distribution, status and trends of the particular resource, and a discussion of ecological linkages with other components of the Vieques marine ecosystem and surrounding environment. The physical environment of Vieques is similar to other islands within the Greater Antilles chain, with some distinctions. The warm, tropical climate of Vieques, mediated by the northeasterly trade winds, is characterized by a dry season (December-April) and a rainy season (May-November), the latter of which is characterized by the occasional passage of tropical cyclones. Compared to mainland Puerto Rico, Vieques is characterized by lower elevation, less annual precipitation, and higher average temperatures. The amount of annual precipitation also varies spatially within Vieques, with the western portion of the island receiving higher amounts of rainfall than further east. While the North Equatorial Current dominates the circulation pattern in the Greater Antilles region, small scale current patterns specific to Vieques are not as well characterized. These physical processes are important factors mitigating the distribution and composition of marine benthic habitats around Vieques. In general, the topography of Vieques is characterized by rolling hills. Mt. Pirata, the tallest point at 301 m, is located near the southwest coast. In the absence of island wide sedimentation measurements, information on land cover, slope, precipitation, and soil type were used to estimate relative erosion potential and sediment delivery for each watershed. While slope and precipitation amount are the primary driving factors controlling runoff, land use practices such as urban development, military activity, road construction, and agriculture can increase the delivery of pollution and sediments to coastal waters. Due to the recent land transfer, increased development and tourism is expected, which may result in changes in the input of sediments to the coastal environment.

Brevetoxin in two planktivorous fishes after exposure to Karenia brevis: implications for food-web transfer to bottlenose dolphins

Brevetoxin uptake was analyzed in 2 common planktivorous fish that are likely foodweb vectors for dolphin mortality events associated with brevetoxin-producing red tides. Fish were exposed to brevetoxin-producing Karenia brevis for 10 h under conditions previously reported to produce optimal uptake of toxin in blood after oral exposure. Striped mullet Mugil cephalus were exposed to a low dose of brevetoxin, and uptake and depuration by specific organs were evaluated over a 2 mo period. Atlantic menhaden Brevoortia tyrannus specimens were used to characterize a higher brevetoxin dose uptake into whole body components and evaluate depuration over 1 mo. We found a high uptake of toxin by menhaden, with a body to water ratio of 57 after a 10 h exposure and a slow elimination with a half life (t1/2) of 24 d. Elimination occurred rapidly from the intestine (t1/2 < 1 wk) and muscle (t1/2 ≈ 1 wk) compartments and redistributed to liver which continued to accumulate body stores of toxin for 4 wk. The accumulation and elimination characteristics of the vectoring capacity of these 2 fish species are interpreted in relation to data from the Florida Panhandle dolphin mortality event of 2004. We show that due to slow elimination rate of brevetoxin in planktivorous fish, brevetoxin-related dolphin mortality events may occur without evidence of a concurrent harmful algal bloom event.