Length-weight relationships of marine fishes from the central Brazilian coast

Parameters of the length-weight relationship are presented for 85 fish species from the marine and estuarine regions of the central Brazilian coast (latitude 13° to 23° S). Three different methods were used. A non-linear iterative process using the quasi-Newton algorithm yielded a better fit for all data sets analyzed. The length-weight allometry coefficient b estimated from standard length data tended to be lower than from total length data. The difference between these estimates was significant for some species.

Length-weight relationship of marine fishes from southern Brazil

The relationship between length (L) and weight (W) was estimated for 80 species belonging to 50 families of marine fishes from the shelf and upper slope of southern Brazil (lat. 28°S - 34°S). Sample sizes (n) for different species ranged from 11 to 14 741 specimens collected from commercial landings and research surveys. The fit of the equations (W=aLb) with a and b parameters estimated from regular and functional regression (of log-transformed weight and length data) as well as from a non-linear iterative process using the quasi-Newton algorithm were compared. The non-linear method gave the most accurate estimates in terms of residual sum of squares. Differences were less than 2.3% for n>500 compared with predictive regressions and 1.5% compared with functional regressions. No difference was observed between both predictive and functional regressions. Determination coefficients (r2) increased with sample size, and the highest r2 were obtained for 50

A guide to monitoring reef fish in the National Park Service's South Florida/Caribbean Network

Reef fishes are conspicuous and essential components of coral reef ecosystems and economies of southern Florida and the United States Virgin Islands (USVI). Throughout Florida and the USVI, reef fish are under threat from a variety of anthropogenic and natural stressors including overfishing, habitat loss, and environmental changes. The South Florida/Caribbean Network (SFCN), a unit of the National Park Service (NPS), is charged with monitoring reef fishes, among other natural and cultural resources, within six parks in the South Florida - Caribbean region (Biscayne National Park, BISC; Buck Island Reef National Monument, BUIS; Dry Tortugas National Park, DRTO; Everglades National Park, EVER; Salt River Bay National Historic Park and Ecological Preserve, SARI; Virgin Islands National Park, VIIS). Monitoring data is intended for park managers who are and will continue to be asked to make decisions to balance environmental protection, fishery sustainability and park use by visitors. The range and complexity of the issues outlined above, and the need for NPS to invest in a strategy of monitoring, modeling, and management to ensure the sustainability of its precious assets, will require strategic investment in long-term, high-precision, multispecies reef fish data that increases inherent system knowledge and reduces uncertainty. The goal of this guide is to provide the framework for park managers and researchers to create or enhance a reef fish monitoring program within areas monitored by the SFCN. The framework is expected to be applicable to other areas as well, including the Florida Keys National Marine Sanctuary and Virgin Islands Coral Reef National Monument. The favored approach is characterized by an iterative process of data collection, dataset integration, sampling design analysis, and population and community assessment that evaluates resource risks associated with management policies. Using this model, a monitoring program can adapt its survey methods to increase accuracy and precision of survey estimates as new information becomes available, and adapt to the evolving needs and broadening responsibilities of park management.

Sampling design tool for ArcGIS: Instruction manual.[for ESRI ArcGIS 10.0 Service Pack 3 or higher]

The Biogeography Branch’s Sampling Design Tool for ArcGIS provides a means to effectively develop sampling strategies in a geographic information system (GIS) environment. The tool was produced as part of an iterative process of sampling design development, whereby existing data informs new design decisions. The objective of this process, and hence a product of this tool, is an optimal sampling design which can be used to achieve accurate, highprecision estimates of population metrics at a minimum of cost. Although NOAA’s Biogeography Branch focuses on marine habitats and some examples reflects this, the tool can be used to sample any type of population defined in space, be it coral reefs or corn fields.

Manual for the Sampling Design Tool for ArcGIS

The Biogeography Branch’s Sampling Design Tool for ArcGIS provides a means to effectively develop sampling strategies in a geographic information system (GIS) environment. The tool was produced as part of an iterative process of sampling design development, whereby existing data informs new design decisions. The objective of this process, and hence a product of this tool, is an optimal sampling design which can be used to achieve accurate, high-precision estimates of population metrics at a minimum of cost. Although NOAA’s Biogeography Branch focuses on marine habitats and some examples reflects this, the tool can be used to sample any type of population defined in space, be it coral reefs or corn fields.