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Droughts reduce gross primary production (GPP) and ecosystem respiration (Reco), contributing to most of the inter-annual variability in terrestrial carbon sequestration. In seasonally dry climates (Mediterranean), droughts result from reductions in annual rainfall and changes in rain seasonality. We compared carbon fluxes measured by the eddy covariance technique in three contrasting ecosystems in southern Portugal: an evergreen oak woodland (savannah-like) with ca.~21% tree crown cover, a grassland dominated by herbaceous annuals and a coppiced short-rotation eucalyptus plantation. During the experimental period (2003–2006) the eucalyptus plantation was always the strongest sink for carbon: net ecosystem exchange rate (NEE) between −861 and −399 g C m−2 year−1. The oak woodland and the grassland were much weaker sinks for carbon: NEE varied in the oak woodland between −140 and −28 g C m−2 year−1 and in the grassland between −190 and +49 g C m−2 year−1. The eucalyptus stand had higher GPP and a lower proportion of GPP spent in respiration than the other systems. The higher GPP resulted from high leaf area duration (LAD), as a surrogate for the photosynthetic photon flux density absorbed by the canopy. The eucalyptus had also higher rain use efficiency (GPP per unit of rain volume) and light use efficiency (the daily GPP per unit incident photosynthetic photon flux density) than the other two ecosystems. The effects of a severe drought could be evaluated during the hydrological-year (i.e., from October to September) of 2004–2005. Between October 2004 and June 2005 the precipitation was only 40% of the long-term average. In 2004–2005 all ecosystems had GPP lower than in wetter years and carbon sequestration was strongly restricted (less negative NEE). The grassland was a net source of carbon dioxide (+49 g C m−2 year−1). In the oak woodland a large proportion of GPP resulted from carbon assimilated by its annual vegetation component, which was strongly affected by the shortage of rain in winter. Overall, severe drought affected more GPP than Reco leading to the deterioration of NEE. Although the rain-use efficiency of the eucalyptus plantation increased in the dry year, this was not the case of evergreen oak woodland, which rain-use efficiency was not influenced by drought. Recovery after drought alleviation, i.e., beginning with heavy rain in October 2005, was fully accomplished in 2006 in the oak woodland and grassland, but slow in the eucalyptus plantation.

Soil respiration in drought prone regions is highly dependent on the precipitation regime and soil moisture conditions, which are expected to change in a global warming context. In the present study we used an extensive collection of field chamber measurements of soil respiration ( R s ) from forest and grassland sites of centre and south of Portugal distributed over a 10 year period. This data were summarized and analysed with the objective to describe seasonal variability of R s as affected by soil moisture ( H s ) and soil temperature ( T s ). A Bayesian framework was used to test the effectiveness of soil bioclimatic models in estimating R s on a daily and monthly time step. R s seasonality was similar between sites, reaching a maximum in spring and autumn and a minimum in the dry season (July–September). No differences were observed for R s between sites with different standing biomass or soil carbon stocks either on an annual or seasonal timescale. H s , and not T s , was the driving factor of R s during most of the year. T s drove R s response only above certain H s limits: 10% for forest sites and 15% for grassland sites leading to a Q 10 of 2.01, 1.61 and 1.31 for closed forests, open forests and grasslands, respectively. The Bayesian analysis showed that models using H s as an independent variable performed better than models driven by T s alone. Monthly estimates of R s in grasslands can be predicted by simple climatic models based on H s but none of them was suitable for forest ecosystems, stressing the need for a process-based approach. This study adds to the evidence that H s controls R s fluxes for Mediterranean ecosystems and should always be taken into account for extrapolation purposes.

Summary Mediterranean evergreen oak woodlands of southern Portugal (montados) are savannah-type ecosystems with a widely sparse tree cover, over extensive grassland. Therefore, ecosystem water fluxes derive from two quite differentiated sources: the trees and the pasture. Partitioning of fluxes according to these different sources is necessary to quantify overall ecosystem water losses as well as to improve knowledge on its functional behaviour. In southern Iberia, these woodlands are subjected to recurrent droughts. Therefore, reaction/resilience to water stress becomes an essential feature of vegetation on these ecosystems. Long-term tree transpiration was recorded for 6 years from a sample of holm oak (Quercus ilex ssp. rotundifolia) trees, using the Granier sap flow method. Ecosystem transpiration was measured by the eddy covariance technique for an 11-month period (February to December 2005), partly coincident with a drought year. Pasture transpiration was estimated as the difference between ecosystem (eddy covariance) and tree (sap flow) transpiration. Pasture transpiration stopped during the summer, when the surface soil dried up. In the other seasons, pasture transpiration showed a strong dependence on rainfall occurrence and on top soil water. Conversely, trees were able to maintain transpiration throughout the summer due to the deep root access to groundwater. Q. ilex trees showed a high resilience to both seasonal and annual drought. Tree transpiration represented more than half of ecosystem transpiration, in spite of the low tree density (30 trees ha−1) and crown cover fraction (21%). Tree evapotranspiration was dominated by transpiration (76%), and interception loss represented only 24% of overall tree evaporation.

We applied a site evaluation approach combining Lagrangian Stochastic footprint modelling with a quality assessment approach for eddy-covariance data to 25 forested sites of the CarboEurope-IP network. The analysis addresses the spatial representativeness of the flux measurements, instrumental effects on data quality, spatial patterns in the data quality, and the performance of the coordinate rotation method. Our findings demonstrate that application of a footprint filter could strengthen the CarboEurope-IP flux database, since only one third of the sites is situated in truly homogeneous terrain. Almost half of the sites experience a significant reduction in eddy-covariance data quality under certain conditions, though these effects are mostly constricted to a small portion of the dataset. Reductions in data quality of the sensible heat flux are mostly induced by characteristics of the surrounding terrain, while the latent heat flux is subject to instrumentation-related problems. The Planar-Fit coordinate rotation proved to be a reliable tool for the majority of the sites using only a single set of rotation angles. Overall, we found a high average data quality for the CarboEurope-IP network, with good representativeness of the measurement data for the specified target land cover types.

International audience; [1] Field-chamber measurements of soil respiration from 17 different forest and shrubland sites in Europe and North America were summarized and analyzed with the goal to develop a model describing seasonal, interannual and spatial variability of soil respiration as affected by water availability, temperature, and site properties. The analysis was performed at a daily and at a monthly time step. With the daily time step, the relative soil water content in the upper soil layer expressed as a fraction of field capacity was a good predictor of soil respiration at all sites. Among the site variables tested, those related to site productivity (e. g., leaf area index) correlated significantly with soil respiration, while carbon pool variables like standing biomass or the litter and soil carbon stocks did not show a clear relationship with soil respiration. Furthermore, it was evidenced that the effect of precipitation on soil respiration stretched beyond its direct effect via soil moisture. A general statistical nonlinear regression model was developed to describe soil respiration as dependent on soil temperature, soil water content, and site-specific maximum leaf area index. The model explained nearly two thirds of the temporal and intersite variability of soil respiration with a mean absolute error of 0.82 mumol m(-2) s(-1). The parameterized model exhibits the following principal properties: (1) At a relative amount of upper-layer soil water of 16% of field capacity, half-maximal soil respiration rates are reached. (2) The apparent temperature sensitivity of soil respiration measured as Q(10) varies between 1 and 5 depending on soil temperature and water content. (3) Soil respiration under reference moisture and temperature conditions is linearly related to maximum site leaf area index. At a monthly timescale, we employed the approach by Raich et al. [2002] that used monthly precipitation and air temperature to globally predict soil respiration (T&P model). While this model was able to explain some of the month-to-month variability of soil respiration, it failed to capture the intersite variability, regardless of whether the original or a new optimized model parameterization was used. In both cases, the residuals were strongly related to maximum site leaf areaindex. Thus, for a monthly timescale, we developed a simple T&P&LAI model that includes leaf area index as an additional predictor of soil respiration. This extended but still simple model performed nearly as well as the more detailed time step model and explained 50% of the overall and 65% of the site-to-site variability. Consequently, better estimates of globally distributed soil respiration should be obtained with the new model driven by satellite estimates of leaf area index. Before application at the continental or global scale, this approach should be further tested in boreal, cold-temperate, and tropical biomes as well as for non-woody vegetation.

We applied a site evaluation approach combining Lagrangian Stochastic footprint modeling with a quality assessment approach for eddy-covariance data to 25 forested sites of the CarboEurope-IP network. The analysis addresses the spatial representativeness of the flux measurements, instrumental effects on data quality, spatial patterns in the data quality, and the performance of the coordinate rotation method. Our findings demonstrate that application of a footprint filter could strengthen the CarboEurope-IP flux database, since only one third of the sites is situated in truly homogeneous terrain. Almost half of the sites experience a significant reduction in eddy-covariance data quality under certain conditions, though these effects are mostly constricted to a small portion of the dataset. Reductions in data quality of the sensible heat flux are mostly induced by characteristics of the surrounding terrain, while the latent heat flux is subject to instrumentation-related problems. The Planar-Fit coordinate rotation proved to be a reliable tool for the majority of the sites using only a single set of rotation angles. Overall, we found a high average data quality for the CarboEurope-IP network, with good representativeness of the measurement data for the specified target land cover types.