Long-term ecosystem nitrogen limitation from foliar δ15 N data and a land surface model.

The effect of nutrient availability on plant growth and the terrestrial carbon sink under climate change and elevated CO2 remains one of the main uncertainties of the terrestrial carbon cycle. This is partially due to the difficulty of assessing nutrient limitation at large scales over long periods of time. Consistent declines in leaf nitrogen (N) content and leaf δ15 N have been used to suggest that nitrogen limitation has increased in recent decades, most likely due to the concurrent increase in atmospheric CO2 . However, such data sets are often not straightforward to interpret due to the complex factors that contribute to the spatial and temporal variation in leaf N and isotope concentration. We use the land surface model (LSM) QUINCY, which has the unique capacity to represent N isotopic processes, in conjunction with two large data sets of foliar N and N isotope content. We run the model with different scenarios to test whether foliar δ15 N isotopic data can be used to infer large-scale N limitation and if the observed trends are caused by increasing atmospheric CO2 , changes in climate or changes in sources and magnitude of anthropogenic N deposition. We show that while the model can capture the observed change in leaf N content and predict widespread increases in N limitation, it does not capture the pronounced, but very spatially heterogeneous, decrease in foliar δ15 N observed in the data across the globe. The addition of an observation-based temporal trend in isotopic composition of N deposition leads to a more pronounced decrease in simulated leaf δ15 N. Our results show that leaf δ15 N observations cannot, on their own, be used to assess global-scale N limitation and that using such a data set in conjunction with an LSM can reveal the drivers behind the observed patterns.

Whole-plant optimality predicts changes in leaf nitrogen under variable CO2 and nutrient availability.

Vegetation nutrient limitation is essential for understanding ecosystem responses to global change. In particular, leaf nitrogen (N) is known to be plastic under changed nutrient limitation. However, models can often not capture these observed changes, leading to erroneous predictions of whole-ecosystem stocks and fluxes. We hypothesise that an optimality approach can improve representation of leaf N content compared to existing empirical approaches. Unlike previous optimality-based approaches, which adjust foliar N concentrations based on canopy carbon export, we use a maximisation criterion based on whole-plant growth, and allow for a lagged response of foliar N to this maximisation criterion to account for the limited plasticity of this plant trait. We test these model variants at a range of Free-Air CO2 Enrichment and N fertilisation experimental sites. We show that a model based solely on canopy carbon export fails to reproduce observed patterns and predicts decreasing leaf N content with increased N availability. However, an optimal model which maximises total plant growth can correctly reproduce the observed patterns. The optimality model we present here is a whole-plant approach which reproduces biologically realistic changes in leaf N and can thereby improve ecosystem-level predictions under transient conditions.

Satellite chlorophyll fluorescence measurements reveal large-scale decoupling of photosynthesis and greenness dynamics in boreal evergreen forests.

Mid-to-high latitude forests play an important role in the terrestrial carbon cycle, but the representation of photosynthesis in boreal forests by current modelling and observational methods is still challenging. In particular, the applicability of existing satellite-based proxies of greenness to indicate photosynthetic activity is hindered by small annual changes in green biomass of the often evergreen tree population and by the confounding effects of background materials such as snow. As an alternative, satellite measurements of sun-induced chlorophyll fluorescence (SIF) can be used as a direct proxy of photosynthetic activity. In this study, the start and end of the photosynthetically active season of the main boreal forests are analysed using spaceborne SIF measurements retrieved from the GOME-2 instrument and compared to that of green biomass, proxied by vegetation indices including the Enhanced Vegetation Index (EVI) derived from MODIS data. We find that photosynthesis and greenness show a similar seasonality in deciduous forests. In high-latitude evergreen needleleaf forests, however, the length of the photosynthetically active period indicated by SIF is up to 6 weeks longer than the green biomass changing period proxied by EVI, with SIF showing a start-of-season of approximately 1 month earlier than EVI. On average, the photosynthetic spring recovery as signalled by SIF occurs as soon as air temperatures exceed the freezing point (2-3 °C) and when the snow on the ground has not yet completely melted. These findings are supported by model data of gross primary production and a number of other studies which evaluated in situ observations of CO2 fluxes, meteorology and the physiological state of the needles. Our results demonstrate the sensitivity of space-based SIF measurements to light-use efficiency of boreal forests and their potential for an unbiased detection of photosynthetic activity even under the challenging conditions interposed by evergreen boreal ecosystems.

Micrometeorological measurements of methane and carbon dioxide fluxes at a municipal landfill.

Continuous and area-integrating monitoring of methane (CH4) and carbon dioxide (CO2) emissions was performed for 6 and 9 months, respectively, at a municipal landfill in Finland with the micrometeorological eddy covariance (EC) method. The mean CH4 emission from June to December was 0.53 mg m(-2) s(-1), while the CO2 emission between February and December averaged 1.78 mg m(-2) s(-1). The CH4 emissions from the summit area of the landfill, where active waste deposition was going on, were 1.7 times as high as from the slope area with a better surface cover. The variation in emissions over the source area of the measurement was high. Significant seasonal variation, linked to air and soil temperature, was only seen in the CO2 release rates. Results obtained with the EC method were comparable to those measured with closed static chambers. According to the EC measurements, the gas recovery system decreased CH4 fluxes by 69-79%. The ratio of the measured CH4 and CO2 emissions roughly indicated the route of the landfill gas emission, resembling the ratio of the gases measured in the gas wells (1.24) when the emission originated from the area with no oxidizing cover layer and being smaller when CH4 oxidation had taken place.

Nitrous oxide emissions from a municipal landfill.

The first measurements of nitrous oxide (N20) emissions from a landfill by the eddy covariance method are reported. These measurements were compared to enclosure emission measurements conducted at the same site. The average emissions from the municipal landfill of the Helsinki Metropolitan Area were 2.7 mg N m(-2) h(-1) and 6.0 mg N m(-2) h(-1) measured bythe eddy covariance and the enclosure methods, respectively. The N20 emissions from the landfill are about 1 order of magnitude higher than the highest emissions reported from Northern European agricultural soils, and 2 orders of magnitude higher than the highest emissions reported from boreal forest soils. Due to the small area of landfills as compared to other land-use classes, the total N20 emissions from landfills are estimated to be of minor importance for the total emissions from Finland. Expressed as a greenhouse warming potential (GWP100), the N2O emissions make up about 3% of the total GWP100 emission of the landfill. The emissions measured by the two systems were generally of similar magnitude, with enclosure measurements showing a high small-scale spatial variation.

Temperature dependence of leaf-level CO2 fixation: revising biochemical coefficients through analysis of leaf three-dimensional structure.

CO2 fixation in a leaf is determined by biochemical and physical processes within the boundaries set by leaf structure. Traditionally determined temperature dependencies of biochemical processes include physical processes related to CO2 exchange that result in inaccurate estimates of parameter values. A realistic three-dimensional model of a birch (Betula pendula) leaf was used to distinguish between the physical and biochemical processes affecting the temperature dependence of CO2 exchange, to determine new chloroplastic temperature dependencies for V c(max) and Jmax based on experiments, and to analyse mesophyll diffusion in detail. The constraint created by dissolution of CO2 at cell surfaces substantially decreased the CO2 flux and its concentration inside chloroplasts, especially at high temperatures. Consequently, newly determined chloroplastic V c(max) and Jmax were more temperature dependent than originally. The role of carbonic anhydrase in mesophyll diffusion appeared to be minor under representative mid-day nonwater-limited conditions. Leaf structure and physical processes significantly affect the apparent temperature dependence of CO2 exchange, especially at optimal high temperatures when the photosynthetic sink is strong. The influence of three-dimensional leaf structure on the light environment inside a leaf is marked and affects the local choice between Jmax and V c(max)-limited assimilation rates.