Forest biomass and its change over time have been measured at both local and large scales, an example for the latter being forest greenhouse gas inventories. Currently used methodologies to obtain stock change estimates for large forest areas are mostly based on forest inventory information as well as various factors, referred to as biomass factors, or biomass equations, which transform diameter, height or volume data into biomass estimates. However, while forest inventories usually apply statistically sound sampling and can provide representative estimates for large forest areas, the biomass factors or equations used are, in most cases, not representative, because they are based on local studies. Moreover, their application is controversial due to the inconsistent or inappropriate use of definitions involved. There is no standardized terminology of the various factors, and the use of terms and definitions is often confusing. The present contribution aims at systematically summarizing the main types of biomass factors (BF) and biomass equations (BE) and providing guidance on how to proceed when selecting, developing and applying proper factors or equations to be used in forest biomass estimation. The contribution builds on the guidance given by the IPCC (Good practice guidance for land use, land-use change and forestry, 2003) and suggests that proper application and reporting of biomass factors and equations and transparent and consistent reporting of forest carbon inventories are needed in both scientific literature and the greenhouse gas inventory reports of countries.

The concentrations (C) of several semivolatile organic compounds (SOCs) in Norway spruce needles (N) and in the local humus horizon (O) of 25 remote Austrian forest sites were used to calculate an ecosystem-oriented partition coefficient needles/humus horizon (C N /C O ). Between 66 and 78% of the compounds' variation of this quotient could be explained by each of the following physicochemical parameters: vapor pressure (p S ) and the partition coefficients n-octanol/water (K OW ), n-octanol/air (K OA ), and adsorbed/ dissolved in soil (K OC ) of the compounds. This result further underlines the usefulness of these parameters for predicting the behavior of SOCs in terrestrial ecosystems. Compounds with low p S and high K OW , K OA , and K OC show a very low C N /C O quotient, which implies a higher accumulation of these compounds in the O horizon than in the needles. The role of forest soils as sink for these SOCs is demonstrated. Alternatively, C N /C O > 1, due to higher concentrations in the needles than in the O horizon, have been shown for SOCs with comparably high p S and low K OW , K OA , and K OC . In this respect, the possible role of revolatilization of the more volatile SOCs from soils to needles is discussed. In the mineral soil layers below the O horizon, SOCs with lower K OC and better water solubility tend to be less accumulated. However, if all investigated compounds are taken into consideration, accumulation in the mineral soil layers showed no general trend in relation to the selected physicochemical parameters.

Microbial assemblages on large organic aggregates (lake snow) of Lake Constance, Germany, were analyzed with rRNA-directed fluorescent oligonucleotide probes specific for the domain Bacteria and the ␣-, ␤-, and ␥-subclasses of the class Proteobacteria. Lake snow aggregates were either collected in situ by SCUBA diving or in a sediment trap at 50 m or formed of natural lake water incubated in rolling cylinders under simulated in situ conditions. For the latter aggregates, the time course of the microbial colonization was also examined. The natural aggregates and those made in rolling cylinders were composed of the particulate organic material present in the lake and thus reflected the composition of the ambient plankton community. All types of lake snow aggregates examined were heavily colonized by microbial cells and harbored between 0.5 ؋ 10 6 and >2 ؋ 10 6 cells aggregate ؊1. Between 55 and 100% of the microbial cells stained with 4,6-diamidino-2-phenylindole (DAPI) could be visualized with the domain Bacteria-specific probe. In most samples, ␤-subclass proteobacteria dominated the microbial community, constituting 27 to 42% of total cells as counted by DAPI staining, irrespective of the composition of the aggregates. During the time course experiments with the laboratory-made aggregates, the fraction of ␤-subclass proteobacteria usually increased over time. Except for a few samples, ␣and ␥-subclass proteobacteria were far less abundant than ␤-subclass proteobacteria, constituting 11 to 25 and 9 to 33% of total cells, respectively. Therefore, we assume that a specific aggregate-adapted microbial community was established on the aggregates. Because the compositions of the microbial assemblages on natural and laboratory-made aggregates were similar, we conclude that aggregates made in rolling cylinders are a good model system with which to examine the formation and microbial colonization of macroscopic organic aggregates.

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