Age determination manual of the Alaska Fisheries Science Center Age and Growth Program

The Age and Growth Program at the Alaska Fisheries Science Center is tasked with providing age data in order to improve the basic understanding of the ecology and fisheries dynamics of Alaskan fish species. The primary focus of the Age and Growth Program is to estimate ages from otoliths and other calcified structures for age-structured modeling of commercially exploited stocks; however, the program has recently expanded its interests to include numerous studies on topics ranging from age estimate validation to the growth and life history of non-target species. Because so many applications rely upon age data and particularly upon assurances as to their accuracy and precision, the Age and Growth Program has developed this practical guide to document the age determination of key groundfish species from Alaskan waters. The main objective of this manual is to describe techniques specific to the age determination of commercially and ecologically important species studied by the Age and Growth Program. The manual also provides general background information on otolith morphology, dissection, and preparation, as well as descriptions of methods used to measure precision and accuracy of age estimates. This manual is intended not only as a reference for age readers at the AFSC and other laboratories, but also to give insight into the quality of age estimates to scientists who routinely use such data.

A robust Bayesian two-sample test for detecting intervals of differential gene expression in microarray time series.

Understanding the regulatory mechanisms that are responsible for an organism's response to environmental change is an important issue in molecular biology. A first and important step towards this goal is to detect genes whose expression levels are affected by altered external conditions. A range of methods to test for differential gene expression, both in static as well as in time-course experiments, have been proposed. While these tests answer the question whether a gene is differentially expressed, they do not explicitly address the question when a gene is differentially expressed, although this information may provide insights into the course and causal structure of regulatory programs. In this article, we propose a two-sample test for identifying intervals of differential gene expression in microarray time series. Our approach is based on Gaussian process regression, can deal with arbitrary numbers of replicates, and is robust with respect to outliers. We apply our algorithm to study the response of Arabidopsis thaliana genes to an infection by a fungal pathogen using a microarray time series dataset covering 30,336 gene probes at 24 observed time points. In classification experiments, our test compares favorably with existing methods and provides additional insights into time-dependent differential expression.

National Centers for Coastal Ocean Science Coastal Ecosystem Assessment Program: a manual of methods

Environmental managers strive to preserve natural resources for future generations but have limited decision-making tools to define ecosystem health. Many programs offer relevant broad-scale, environmental policy information on regional ecosystem health. These programs provide evidence of environmental condition and change, but lack connections between local impacts and direct effects on living resources. To address this need, the National Oceanic and Atmospheric Administration/National Ocean Service (NOAA/NOS) Cooperative Oxford Laboratory (COL), in cooperation with federal, state, and academic partners, implemented an integrated biotic ecosystem assessment on a sub-watershed 14-digit Hydrologic Unit Code (HUD) scale in Chesapeake Bay. The goals of this effort were to 1) establish a suite of bioindicators that are sensitive to ecosystem change, 2) establish the effects of varying land-use patterns on water quality and the subsequent health of living resources, 3) communicate these findings to local decision-makers, and 4) evaluate the success of management decisions in these systems. To establish indicators, three sub-watersheds were chosen based on statistical analysis of land-use patterns to represent a gradient from developed to agricultural. The Magothy (developed), Corsica (agricultural), and Rhode (reference) Rivers were identified. A random stratified design was developed based on depth (2m contour) and river mile. Sampling approaches were coordinated within this structure to allow for robust system comparisons. The sampling approach was hierarchal, with metrics chosen to represent a range from community to cellular level responses across multiple organisms. This approach allowed for the identification of sub-lethal stressors, and assessment of their impact on the organism and subsequently the population. Fish, crabs, clams, oysters, benthic organisms, and bacteria were targeted, as each occupies a separate ecological niche and may respond dissimilarly to environmental stressors. Particular attention was focused on the use of pathobiology as a tool for assessing environmental condition. By integrating the biotic component with water quality, sediment indices, and land- use information, this holistic evaluation of ecosystem health will provide management entities with information needed to inform local decision-making processes and establish benchmarks for future restoration efforts.

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.