River ecosystems are driven by linked physical, chemical, and biological subsystems, which operate over different temporal and spatial domains. This complexity increases uncertainty in ecological forecasts, and impedes preparation for the ecological consequences of climate change. We describe a recently developed “multi-modeling” system for ecological forecasting in a 7600 km² watershed in the North American Great Lakes Basin.

Central Asia has experienced drastic socio-economic, geopolitical, and ecological transitions within the last few decades. The USSR collapse in 1991 has led to widespread changes in land cover and land use due to economic and political transformations within the region. Management practices during and after the Soviet era have intensified ecological problems and demands on resources.

This paper comprises some general issues about the natural and agricultural context in arid and semiarid Mediterranean pastures. We include most of our studies concerning to shrublands characteristics: composition, production and diversity; which have been developed in the oriental sector of Andalusia for more than 20 years. This work is concluded with some personal considerations about the changes in the land uses, mainly due to rural abandonment, and its incidence in the global change.

SWAT (Soil and Water Assessment Tool) represents a dynamic catchment modelling application that can be applied to any river basin and used to quantify the impact of land management practices on water quality over a continuous period. The objective of this study is to apply the Soil and Water Assessment Tool (SWAT) to model pathogen transport, simulate management practices affecting water quality and predict pathogen loads in Irish catchments.

Remote-sensing technology provides a powerful means for land use/land cover (LU/LC) monitoring at global and regional scales. However, it is more efficient and effective to combine remote-sensing measurements with a geographic information system (GIS) database and expert knowledge for change updating than to use remote-sensing technology alone. In this article, these different sources of information are integrated in the proposed framework, which is able to provide rapid updating of LU/LC information.

The last decade has seen a remarkable increase in the number of modeling tools available to examine future land-use and land-cover (LULC) change. Integrated modeling frameworks, agent-based models, cellular automata approaches, and other modeling techniques have substantially improved the representation of complex LULC systems, with each method using a different strategy to address complexity. However, despite the development of new and better modeling tools, the use of these tools is limited for actual planning, decision-making, or policy-making purposes.

In automatic/semiautomatic mapping of land use/cover using very high resolution remote-sensing imagery, the major challenge is that a single class of land use contains ground targets with varied spectral values, textures, geometries and spatial features. Here we present an object-oriented strategy for automatic/semiautomatic classifications of land use/cover using very high resolution remote-sensing data. The strategy consists of character detecting, object positioning and coarse classification, then refining the classification result step by step.

Estimates of forest area were obtained for the states of Indiana, Iowa, Minnesota, and Missouri in the United States using stratified analyses and observations from forest inventory plots measured in federal fiscal year 1999. Strata were created by aggregating the land cover classes of the National Land Cover Data (NLCD), and strata weights were calculated as proportions of strata pixel counts.

The land-cover/use change dynamics in Manica Province in Mozambique are analysed, based upon interpretation of LANDSAT images, to assess trends and highlight management suggestions considering current policies in place that include the ownership and participation of local communities in natural resources management and the recognition of traditional ownership systems. Applying an object-oriented approach to compare the year 2004 with 1990, one observes that land-cover/use changes are not distributed evenly in the province.

BACKGROUND: The toxic effects of ultrafine particles (UFP) are a public health concern. However, epidemiological studies on the long term effects of UFP are limited due to lacking exposure models. Given the high spatial variation of UFP, the assignment of exposure levels in epidemiological studies requires a fine spatial scale. The aim of this study was to assess the performance of a short-term measurement protocol used at a large number of locations to derive a land use regression (LUR) model of the spatial variation of UFP in Girona, Spain.

1. The role of land cover change as a significant component of global change has become increasingly recognized in recent decades. Large databases measuring land cover change, and the data which can potentially be used to explain the observed changes, are also becoming more commonly available. When developing statistical models to investigate observed changes, it is important to be aware that the chosen sampling strategy and modelling techniques can influence results. 2.