Soils provide the largest terrestrial carbon store, the largest atmospheric CO 2 source, the largest terrestrial N 2 O source and the largest terrestrial CH 4 sink, as mediated through root and soil microbial processes. A change in land use or management can alter these soil processes such that net greenhouse gas exchange may increase or decrease. We measured soil-atmosphere exchange of CO 2 , N 2 O and CH 4 in four adjacent land-use systems (native eucalypt woodland, clover-grass pasture, Pinus radiata and Eucalyptus globulus plantation) for short, but continuous, periods between October 2005 and June 2006 using an automated trace gas measurement system near Albany in southwest Western Australia. Mean N 2 O emission in the pasture was 26.6 lg N m À2 h À1 , significantly greater than in the natural and managed forests (o2.0 lg N m À2 h À1 ). N 2 O emission from pasture soil increased after rainfall events (up to 100 lg N m À2 h À1 ) and as soil water content increased into winter, whereas no soil water response was detected in the forest systems. Gross nitrification through 15 N isotope dilution in all land-use systems was small at water holding capacity o30%, and under optimum soil water conditions gross nitrification ranged between o0.1 and 1.0 mg N kg À1 h À1 , being least in the native woodland/eucalypt plantation opine plantation opasture. Forest soils were a constant CH 4 sink, up to À20 lg C m À2 h À1 in the native woodland. Pasture soil was an occasional CH 4 source, but weak CH 4 sink overall (À3 lg C m À2 h À1 ). There were no strong correlations (Ro0.4) between CH 4 flux and soil moisture or temperature. Soil CO 2 emissions (35-55 mg C m À2 h À1 ) correlated with soil water content (Ro0.5) in all but the E. globulus plantation. Soil N 2 O emissions from improved pastures can be considerable and comparable with intensively managed, irrigated and fertilised dairy pastures. In all land uses, soil N 2 O emissions exceeded soil CH 4 uptake on a carbon dioxide equivalent basis. Overall, afforestation of improved pastures (i) decreases soil N 2 O emissions and (ii) increases soil CH 4 uptake.

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Linking environmental computer simulation models and geographic information systems (GIS) is now a common practice to scale up simulations of complex ecosystem processes for decision support. Unfortunately, several important issues of upscaling using GIS are rarely considered; in particular scale dependency of models, availability of input data, support of input and validation data, and uncertainty in prediction including error propagation from the GIS. We linked the biogeochemical Forest-DNDC model to a GIS database to predict growth of Eucalyptus globulus plantations at two different scales ( $ 0.045 ha plot À1 scale and $ 100 ha grid À1 scale) across Victoria, in south-eastern Australia. Results showed that Forest-DNDC was not scale dependent across the range of scales investigated. Reduced availability of input data at the larger scale may introduce severe prediction errors, but did not require adjustment of the model in this study. Differences in the support of input and validation data led to an underestimation of predictive precision but an overestimation of prediction accuracy. Increasing data support, produced a high level of prediction accuracy (¯e% ¼ À3:54%), but a medium level of predictive precision (r 2 5 0.474, ME 5 0.318) after statistical validation. GIS error contribution could be detected but was not readily or reliably quantified. In a regional case study for 2653 ha of E. globulus plantations, the linked model GIS system estimated a total standing biomass of 95 260 t C for mid-2003 and a net CO 2 balance of À45 671 t CO 2 -C yr À1 for the entire year of 2002. This study showed that regional predictions of forest growth and carbon sequestration can be produced with greater confidence after a comprehensive assessment of upscaling issues.

Versatile process-oriented ecosystem models are discussed as promising tools for the analyses of ecosystem services beyond wood yield, such as catchment water yield, sequestration of carbon and greenhouse gas balances. However, long-term yield simulation is often regarded as a weakness of such versatile models. In this context, we present a multiple response evaluation of the modular, process-based forest growth model MoBiLE-PDT based on mensurational data from 38 permanent sample plots in commercial Eucalyptus globulus plantations in Australia followed from establishment to 8 years of stand age. MoBiLE-PDT is based on the PnET-N-DNDC model and considers nitrogen availability and drought stress dynamically in dependence on tree and stand properties as well as on climate and deposition. New tree dimensions are calculated directly from carbon allocated to sapwood and mortality is derived from stand density. Towards the end of the rotation, model efficiency E was 0.58 for stand volume (m 3 ha -1 ) and 0.54 for aboveground biomass (t C ha -1 ). In a comparison with similar forest growth models evaluated against the same data only one had a better model efficiency, whereas MoBiLE-PDT was the most versatile model for the analyses of ecosystem services. Due to its modular structure, further model extensions for more ecological applications are easily possible.