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Habitat surrounding the inactive Continental Mine in northern Idaho, USA, supports bear (Ursus arctos, Ursus americanus), moose (Alces alces), elk (Cervus elaphus), woodland caribou (Rangifer tarandus caribou), and abundant mule (Odocoileus hemionus) and white-tailed deer (Odocoileus virginianus). Tailings on the mining site were capped and remediated in 2003 to reduce environmental exposure of surrounding soil and sediments of Blue Joe Creek, downslope of the mine. Before capping, the mean Pb concentration in deer pellets collected on-site was 920 mg/kg of Pb (dry wt). This exposure, if chronic, would be comparable to an exposure that could be lethal to cattle or horses. Surprisingly, the mean pellet Pb concentration of 950 mg/kg in 2004 was as high as it was before remediation, and it was related to a high rate of soil ingestion. Mean soil content of the pellets collected from the capped site in 2004 was 22% dry weight, estimated from the acid-insoluble ash, a marker of soil ingestion. Clumps of sand and bits of rock were observed inside some of the pellets, and Pb concentrations in the pellets were correlated (p < 0.05) with soil content. Although terrestrial risk assessments generally estimate exposure from diets and from incidentally ingested soil, the deer at this site were directly ingesting contaminated soil or mining waste. The mean Pb concentration of this ingested soil was estimated as 6,700 mg/kg and the maximum as 25,000 mg/kg, well above the Pb concentrations measured in the remediated cap. The deer seemed to be ingesting soil or mining waste from one or more small but highly contaminated sources located beyond the remediated cap. [ABSTRACT FROM AUTHOR]

To improve estimates of the state and change in C pools due to changes in land use in tropical forests of Africa, we combined spatially explicit estimates of biomass C density, obtained by modelling in a geographical information system (GIS), with new data on the area of forests (woody formations with a minimum of 10% crown cover) reported at subnational units for 1980 and 1990 by the Food and Agriculture Organization (FAO). Estimates of the biomass C densities for grass/shrub savannas were also included using a simple model based on precipitation. The total C pool in above– and below–ground forests and grass/shrub savannas of Africa for 1980 was 50.8 Pg (10[sup 15]g), with aboveground forest biomass accounting for 75% of the total, below–ground forest biomass for 21%, and grass/shrub savannas for 4%. Area weighted mean biomass C densities were about 180 Mg ha[sup –1] for lowland moist forests, 82 Mg ha[sup –1] for all forests, and 6 Mg ha[sup –1] for grass savannas. The total change in the aboveground forest C pool for the decade 1980–90 due to changes in land cover and use was estimated to be a decrease of 6.6 Pg C. Of this total, 43% was due to deforestation and 57% due to biomass reduction by other human activities. Six countries, mostly in central Africa, accounted for more than 73% of the total change in the C pool. The difference between state and change of C pool estimates made at the subnational scale and those made at the national scale proved to be insignificant across the region as a whole (2% for pools and – 1% for change in pool) but potentially important to individual countries (from + 36% to – 39% for pools and from + 43% to – 57% for change in pool). The differences between the two approaches may reflect a better match of the areas being deforested with the biomass C density of forests being cleared. [ABSTRACT FROM AUTHOR]

Forest ecosystem models are an important tool for estimating carbon pools and fluxes in the terrestrial biosphere. Models can provide dynamic estimates through time and can predict the results of changes inforest management practices or changes in the forest ecosystem resulting from natural disturbances. Vegetation and landcover regions identified through unsupervised classification of Global Vegetation Index(GVI) data provide an appropriate ecosystem and species description for model input parameters. The timing and magnitude of photosynthesis as indicated by NDVI observed from four year average monthly GVI composites were used to identify 42 distinct regions of the former Soviet Union (FSU) . These regions represent areas of similar vegetation and land cover at a higher level of spatial detail and with more thorough species description than provided by available continental scalethematic maps. The image classes provide a consistent framework of vegetation and land-cover information across the FSU. Qualitative comparison on a pixel-by-pixel basis with detailed topographic maps and other data showed that, in general, despite the widely acknowledged problems with GVI, surface conditions were well identified by the GVI classification, The image class descriptions for the continental scaleanalysis required a supplemental description of the species specificto regional ecosystems before they could be used as a forest ecosystem model input parameter. Model predictions for carbon pools in test sites located in the Amur region of Russia compared well to carbon estimates made using other techniques. While GVI-based image classes appear to be appropriate for continental scale analysis, there is stilla need to validate the GVI classification approach using higher resolution remote sensing data and field investigations. [ABSTRACT FROM AUTHOR]