Zusammenfassung: The authors sampled fishes and measured microhabitat in series of contiguous habitat units (riffles, runs, pools) in three Virginia streams. Monte Carlo simulations were used to construct hypothetical series of habitat units, then examined how number of species, similarity in relative abundances, and number of microhabitats accumulated with increasing number of habitat units (i.e., sampling effort). The curves indicated that 90% of the species present were usually found by sampling 5 to 14 habitat units (stream length of 22-67 stream widths). Estimates of species relative abundances required less sampling effort for a given accuracy than estimates of number of species. Rates of species accumulation (with effort) varied among streams and reflected discontinuity in species distributions among habitat units. Most discontinuity seemed to be due to low population density rather than to habitat selectivity. Results from an Illinois stream corroborated our findings from Virginia, and suggested that greater sampling effort is needed to characterize fish community structure in more homogeneous stream reaches.

Zusammenfassung: The characterization of an heterogeneous geological media can be approached by means of an statistical treatment of the field data. This lets us know its spatial variability behaviour, in probability terms. The algorithms presented in this work belongs to the scope of simulation of geological heterogeneous random fields. The aim of that characterization is related with the reseach studies of nuclear waste repositories in deep geological structures. Several stochastic generation algorithms are presented, based in the geostatistical regionalized variable, fractal geometry, and spectral Fourier theories. Some of them are deeply exposed here to their understanding. As a result of the paper, some comparative schemes are showed with numerical, geostatistical and spectral analysis of the implicit autorregresive generation methods.

Zusammenfassung: As the CoastWatch regional node for the Great Lakes, the Great Lakes Environmental Research Laboratory (GLERL) is working to obtain and/or develop and deliver environmental data and products for near real-time monitoring of the Great Lakes to support environmental science and decision making. In support of this goal, GLERL is providing access to near real-time and retrospective satellite observations and in-situ data for the Great Lakes to Federal, state, and local agencies and academic institutions. There are currently nearly 40 regional CoastWatch users. The goals and objectives of the Great Lakes CoastWatch Program directly support agency statutory responsibilities in estuarine and marine science, living marine resource protection, and ecosystem monitoring and management. GLERL is currently receiving an enhanced digital image product suite of 26 images including satellite derived surface-temperature, visible and near-infrared reflectance, brightness temperatures, satellite and solar zenith angle data, and cloud masks from the NOAA-12 satellite. These products are downloaded from the NOAA Ocean Products Center (OPC) via INTERNET on a daily basis and archived at GLERL. Over 32,000 image products have been received and archived since becoming the Great Lakes CoastWatch Node in 1990. GOES-8 data is also currently being received.