No abstract

The wind damage probability (P (DAM)) in the forests in the federal state of Baden-Wuerttemberg (Southwestern Germany) was calculated using weights of evidence (WofE) methodology and a logistic regression model (LRM) after the winter storm 'Lothar' in December 1999. A geographic information system (GIS) was used for the area-wide spatial prediction and mapping of P (DAM). The combination of the six evidential themes forest type, soil type, geology, soil moisture, soil acidification, and the 'Lothar' maximum gust field predicted wind damage best and was used to map P (DAM) in a 50 x 50 m resolution grid. GIS software was utilised to produce probability maps, which allowed the identification of areas of low, moderate, and high P (DAM) across the study area. The highest P (DAM) values were calculated for coniferous forest growing on acidic, fresh to moist soils on bunter sandstone formations-provided that 'Lothar' maximum gust speed exceeded 35 m s(-1) in the areas in question. One of the most significant benefits associated with the results of this study is that, for the first time, there is a GIS-based area-wide quantification of P (DAM) in the forests in Southwestern Germany. In combination with the experience and expert knowledge of local foresters, the probability maps produced can be used as an important tool for decision support with respect to future silvicultural activities aimed at reducing wind damage. One limitation of the P (DAM)-predictions is that they are based on only one major storm event. At the moment it is not possible to relate storm event intensity to the amount of wind damage in forests due to the lack of comprehensive long-term tree and stand damage data across the study area.

Abstract. Fluxes of greenhouse gases (GHG) carbon dioxide (CO 2 ), methane (CH 4 ) and nitrous oxide (N 2 O) were measured during a two month campaign at a drained peatland forest in Finland by the eddy covariance (EC) technique (CO 2 and N 2 O), and automatic and manual chambers (CO 2 , CH 4 and N 2 O). In addition, GHG concentrations and soil parameters (mineral nitrogen, temperature, moisture content) in the peat profile were measured. The aim of the measurement campaign was to quantify the GHG fluxes during freezing and thawing of the top-soil, a time period with potentially high GHG fluxes, and to compare different flux measurement methods. The forest was a net CO 2 sink during the two months and the fluxes of CO 2 dominated the GHG exchange. The peat soil was a small sink of atmospheric CH 4 and a small source of N 2 O. Both CH 4 oxidation and N 2 O production took place in the top-soil whereas CH 4 was produced in the deeper layers of the peat, which were unfrozen throughout the measurement period. During the frost-thaw events of the litter layer distinct peaks in CO 2 and N 2 O emissions were observed. The CO 2 peak followed tightly the increase in soil temperature, whereas the N 2 O peak occurred with a delay after the thawing of the litter layer. CH 4 fluxesCorrespondence to: M. K. Pihlatie (mari.pihlatie@helsinki.fi) did not respond to the thawing of the peat soil. The CO 2 and N 2 O emission peaks were not captured by the manual chambers and hence we conclude that high time-resolution measurements with automatic chambers or EC are necessary to quantify fluxes during peak emission periods. Subcanopy EC measurements and chamber-based fluxes of CO 2 and N 2 O were comparable, although the fluxes of N 2 O measured by EC were close to the detection limit of the system. We conclude that if fluxes are high enough, i.e. greater than 5-10 µg N m −2 h −1 , the EC method is a good alternative to measure N 2 O and CO 2 fluxes at ecosystem scale, thereby minimizing problems with chamber enclosures and spatial representativeness of the measurements.

No abstract