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The usual model for censored survival analysis requires the assumption that censoring of observations arises only due to causes unrelated to the lifetime under consideration. It is easy to envision situations in which this assumption is unwarranted, and in which use of the Kaplan-Meier estimator and associated techniques will lead to unreliable analyses.
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Management of birds often requires analysis of collections of estimates. We describe a hierarchical modeling approach to the analysis of these data, in which parameters associated with the individual species estimates are treated as random variables, and probability statements are made about the species parameters conditioned on the data. A Markov-Chain Monte Carlo (MCMC) procedure is used to fit the hierarchical model. This approach is computer intensive, and is based upon simulation. MCMC allows for estimation both of parameters and of derived statistics. To illustrate the application of this method, we use the case in which we are interested in attributes of a collection of estimates of population change. Using data for 28 species of grassland-breeding birds from the North American Breeding Bird Survey, we estimate the number of species with increasing populations, provide precision-adjusted rankings of species trends, and describe a measure of population stability as the probability that the trend for a species is within a certain interval. Hierarchical models can be applied to a variety of bird survey applications, and we are investigating their use in estimation of population change from survey data.
As a low-lying peninsula surrounded by water, Florida faces tough decisions about long-range planning and development strategies to address impacts of climate change. In 2007, the Intergovernmental Panel on Climate Change (IPCC) stated there is strong evidence that global average sea level will rise by ? to 2 feet in the next century due to continued thermal expansion and melting of ice on land.
In many biological studies of water quality, a diversity index is calculated in 'bits per individual' by using Shannon's Approximation to Brillouin's Formula. Difficulties associated with such use of Shannon's Formula and its associated parameters are discussed. Recent research has indicated that diversity indexes can be improved if (a) biological sample collection and analysis are standardized prior to use for among various aquatic systems diversity indexes and their associated parameters, (b) the diversity index is measured in 'sits per individual' rather than the presently used unit of 'bits per individual,' and (c) the equation e=(H - H(min)/(H(max) - H(min)) is used to evaluate the uniformity of distribution of individuals among species in a sample where e equals relative evenness. Relative evenness, a ratio, is an expression in which Brillouin's and Shannon's Equations are not arbitrarily mixed. Values of diversity indexes using Brillouin and Shannon Formulas, both in bits and sits per individual, and relative evenness are given for 16 hypothetical samples.
A technique has been developed to separate and extract spectral-reflectivity variations and topographic informaiton from multispectral images. The process is a completely closed system employing only the image data and can be applied to any digital multispectral data set. -from Authors
As a part of the Geological Survey's program of releasing water data to the public, two large-scale computerized systems are maintained. The National Water Data Storage and Retrieval System was developed to provide more effective and efficient management of data-releasing activities and provides for the processing, storage, and retrieval of surface-water, ground-water and water-quality data. Another service available is providing assistance to users of water data to identify, locate, and acquire needed data. This service is provided by the National Water Data Exchange, which has the mission to identify sources of water data and to provide the connection between those who acquire and those who use water data.
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[No abstract available]