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Biogenic emission algorithms predict that oak forests account for ~ 70 % of the total European isoprene budget. Yet the isoprene emission potentials that underpin these model estimates are calculated from a very limited number of leaf-level observations and hence are highly uncertain. Increasingly, micrometeorological techniques such as eddy covariance are used to measure whole-canopy fluxes directly, from which isoprene emission potentials can be calculated. Here, we review five observational datasets of isoprene fluxes from a range of oak forests in the UK, Italy and France. We outline procedures to correct the measured net fluxes for losses from deposition and chemical flux divergence, which were found to be on the order of 5–8 % and 4–5 %, respectively. The corrected observational data were used to derive isoprene emission potentials at each site in a two-step process. Firstly, six commonly used emission algorithms were inverted to back out time series of isoprene emission potential, and then an average isoprene emission potential was calculated for each site with an associated uncertainty. We used these data to assess how the derived emission potentials change depending upon the specific emission algorithm used and importantly, on the particular approach adopted to derive an average site specific emission potential. Our results show that isoprene emission potentials can vary by up to a factor of four depending on the specific algorithm used and whether or not it is used in a big-leaf or canopy environment model format. When using the same algorithm, the calculated average isoprene emission potential was found to vary by as much as 34 % depending on how the average was derived. In order to best replicate the observed fluxes we propose a new weighted average method whereby the isoprene emission potential is calculated as the average of all flux observations divided by the average activity factor (γ) of the emission algorithm. This approach ensures that modelled fluxes always have the same average as the measurements. Using this new approach, with version 2.1 of the Model for Emissions of Gases and Aerosols from Nature (MEGAN), we derive new ecosystem-scale isoprene emission potentials for the five measurement sites, Alice Holt, UK (10 500 ± 2500 µg m−2 h−1), Bosco Fontana, Italy (1610 ± 420 µg m−2 h−1), Castelporziano, Italy (43 ± 10 µg m−2 h−1), Ispra, Italy (7590 ± 1070 µg m−2 h−1) and the Observatoire de Haute Provence, France (7990 ± 1010 µg m−2 h−1). Ecosystem-scale isoprene emission potentials were then extrapolated to the leaf-level and compared to previous leaf-level measurements for Quercus robur and Quercus pubescens, two species thought to account for 50 % of the total European isoprene budget. The literature values agreed closely with emission potentials calculated using the G93 algorithm, which were 85 ± 75 µg g−1 h−1 and 78 ± 25 µg g−1 h−1 for Q. robur and Q. pubescens respectively. By contrast, emission potentials calculated using the G06 algorithm, the same algorithm used in a previous study to derive the European budget, were significantly lower, which we attribute to the influence of past light and temperature conditions. Adopting these new G06 specific emission potentials for Q. robur (55 ± 24 µg g−1 h−1) and Q. pubescens (47 ± 16 µg g−1 h−1) reduced the projected European budget by ~ 17 %. Our findings demonstrate that calculated isoprene emission potentials vary considerably depending upon the specific approach used in their calculation. Therefore, it is our recommendation that the community now adopt a standardised approach to the way in which micrometeorological flux measurements are corrected and used to derive isoprene, and other biogenic VOC, emission potentials. Modellers who use derived emission potentials should pay particular attention to the way in which an emission potential was derived and ensure that the algorithm they are using, and the implementation thereof, is consistent with that used to derive the emission potential. Our results show that, in the worst cases, failure to account for this may result in modelled fluxes that differ from observations by up to a factor of four.

Under elevated atmospheric CO2 concentrations, soil carbon (C) inputs are typically enhanced, suggesting larger soil C sequestration potential. However, soil C losses also increase and progressive nitrogen (N) limitation to plant growth may reduce the CO2 effect on soil C inputs with time. We compiled a data set from 131 manipulation experiments, and used meta-analysis to test the hypotheses that: (1) elevated atmospheric CO2 stimulates soil C inputs more than C losses, resulting in increasing soil C stocks; and (2) that these responses are modulated by N. Our results confirm that elevated CO2 induces a C allocation shift towards below-ground biomass compartments. However, the increased soil C inputs were offset by increased heterotrophic respiration (Rh), such that soil C content was not affected by elevated CO2. Soil N concentration strongly interacted with CO2 fumigation: the effect of elevated CO2 on fine root biomass and -production and on microbial activity increased with increasing soil N concentration, while the effect on soil C content decreased with increasing soil N concentration. These results suggest that both plant growth and microbial activity responses to elevated CO2 are modulated by N availability, and that it is essential to account for soil N concentration in C cycling analyses. Under elevated atmospheric CO concentrations, soil carbon (C) inputs are typically enhanced, suggesting larger soil C sequestration potential. However, soil C losses also increase and progressive nitrogen (N) limitation to plant growth may reduce the CO effect on soil C inputs with time. We compiled a data set from 131 manipulation experiments, and used meta-analysis to test the hypotheses that: (1) elevated atmospheric CO stimulates soil C inputs more than C losses, resulting in increasing soil C stocks; and (2) that these responses are modulated by N. Our results confirm that elevated CO induces a C allocation shift towards below-ground biomass compartments. However, the increased soil C inputs were offset by increased heterotrophic respiration (Rh), such that soil C content was not affected by elevated CO. Soil N concentration strongly interacted with CO fumigation: the effect of elevated CO on fine root biomass and -production and on microbial activity increased with increasing soil N concentration, while the effect on soil C content decreased with increasing soil N concentration. These results suggest that both plant growth and microbial activity responses to elevated CO are modulated by N availability, and that it is essential to account for soil N concentration in C cycling analyses.

The observation of acclimation in leaf photosynthetic capacity to differences in growth irradiance has been widely used as support for a hypothesis that enables a simplification of some soil-vegetation-atmosphere transfer (SVAT) photosynthesis models. The acclimation hypothesis requires that relative leaf nitrogen concentration declines with relative irradiance from the top of a canopy to the bottom, in 1 : 1 proportion. In combination with a light transmission model it enables a simple estimate of the vertical profile in leaf nitrogen concentration (which is assumed to determine maximum carboxylation capacity), and in combination with estimates of the fraction of absorbed radiation it also leads to simple 'big-leaf' analytical solutions for canopyphotosynthesis. We tested how forests deviate from this condition in five tree canopies, including four broadleaf stands, and one needle-leaf stand: a mixed-species tropical rain forest, oak (Quercus petraea (Matt.) Liebl), birch (Betula pendula Roth), beech (Fagus sylvatica L.) and Sitka spruce (Picea sitchensis (Bong.) Carr). Each canopy was studied when fully developed (mid-to-late summer for temperate stands). Irradiance (Q, ~S^~mol m-2 s-1) was measured for 20 d using quantum sensors placed throughoutthe vertical canopy profile. Measurements were made to obtain parameters from leaves adjacent to the radiation sensors: maximum carboxylation and electron transfer capacity (Va, Ja, ~S^~mol m-2 s-1), day respiration (Rda, ~S^~mol m-2 s-1), leaf nitrogen concentration (Nm, mg g-1) and leaf mass per unit area (La, g m-2). Relative to upper-canopy values, Va declined linearly in 1 : 1 proportion with Na. Relative Va also declined linearly with relative Q, but with a significant intercept at zero irradiance (P < 0.01). This intercept was strongly related to La of the lowest leaves in each canopy (P < 0.01, rr = 0.98, n = 5). For each canopy, daily ln Q was also linearly related with ln Va (P < 0.05), and the intercept was correlated with the value for photosynthetic capacity per unit nitrogen (PUN: Va/Na, ~S^~mol g-1s-1) of the lowest leaves in each canopy (P < 0.05). Va was linearly related with La and Na (P < 0.01), but the slope of the Va : Na relationship varied widely among sites. Hence, whilst there was a unique Va : Na ratio in each stand, acclimation in Va to Q varied predictably with La of the lowest leaves in each canopy. The specific leaf area, Lm (cmr g-1), of the canopy-bottom foliage was also found to predict carboxylation capacity (expressed on a mass basis; Vm, ~S^~mol g-1 s-1) at all sites (P < 0.01). These results invalidate the hypothesis of full acclimation to irradiance, but suggest that La and Lm of the most light-limited leaves in a canopy are widely applicable indicators of the distribution of photosynthetic capacity with height in forests.