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•Flux partitioning infers gross primary productivity and ecosystem respiration.•Algorithms conceptualise ecosystem respiration to result from a single source.•The phase-shift between ...air and soil temperature results in hysteresis.•A single-source model of ecosystem respiration results in biased estimates.
So-called CO2 flux partitioning algorithms are widely used to partition the net ecosystem CO2 exchange into the two component fluxes, gross primary productivity and ecosystem respiration. Common CO2 flux partitioning algorithms conceptualise ecosystem respiration to originate from a single source, requiring the choice of a corresponding driving temperature. Using a conceptual dual-source respiration model, consisting of an above- and a below-ground respiration source each driven by a corresponding temperature, we demonstrate that the typical phase shift between air and soil temperature gives rise to a hysteresis relationship between ecosystem respiration and temperature. The hysteresis proceeds in a clockwise fashion if soil temperature is used to drive ecosystem respiration, while a counter-clockwise response is observed when ecosystem respiration is related to air temperature. As a consequence, nighttime ecosystem respiration is smaller than daytime ecosystem respiration when referenced to soil temperature, while the reverse is true for air temperature. We confirm these qualitative modelling results using measurements of day and night ecosystem respiration made with opaque chambers in a short-statured mountain grassland. Inferring daytime from nighttime ecosystem respiration or vice versa, as attempted by CO2 flux partitioning algorithms, using a single-source respiration model is thus an oversimplification resulting in biased estimates of ecosystem respiration. We discuss the likely magnitude of the bias, options for minimizing it and conclude by emphasizing that the systematic uncertainty of gross primary productivity and ecosystem respiration inferred through CO2 flux partitioning needs to be better quantified and reported.
The modification of the surface radiation and energy balance in urban areas causes the temperatures in these areas to exceed those of the surrounding countryside. It has thus been suggested that ...urban environments may serve as field laboratories for studying the effects of a warming climate on biota in a space-for-time substitution. Here we investigated changes in the timing of plant phenology and temperature across study sites that differed in the degree of urbanization using publicly available pan-European datasets for the period 1981-2010. We found a significant advancement in the phenological phases of leaf development, flowering and fruiting with higher degrees of urbanization, whereas a significant delay was observed for phenological phases of leaf senescence. In addition to these phenological changes, an increase in air temperature with higher degrees of urbanization was observed. This increase was largest during the periods of leaf development, flowering and fruiting and smallest during the period of leaf senescence. On the basis of these results, we show that the apparent temperature sensitivity of phenological phases to urban warming is either significantly dampened (leaf development, flowering and fruiting) or reversed (leaf senescence) compared with the temperature sensitivity inferred from temporal changes in phenology and temperature. We conclude that gradients in urbanization represent a poor analogue for the temporal changes in plant phenology, apparently owing to confounding factors associated with urbanization.
Alpine ecosystems are, similar to arctic ecosystems, characterized by a very long snow season. Previous studies investigating arctic or alpine ecosystems have shown that winter CO₂ effluxes can ...dominate the annual balance and that the timing and duration of the snow cover plays a crucial role for plant growth and phenology and might also influence the growing season ecosystem CO₂ strength and dynamics. The objective of this study was to analyze seasonal and annual CO₂ balances of a grassland site at an elevation of 2440 m a.s.l in the Swiss central Alps. We continuously measured the NEP using the eddy covariance method from June 2013 to October 2014, covering two growing seasons and one winter. We analyzed the influence of snow melt date on the CO₂ exchange dynamics at this site, because snow melt differed about 24 days between the 2 years. To this end, we employed a process-based ecosystem carbon cycling model to disentangle the co-occurring effects of growing season length, environmental conditions during the growing season, and physiological/structural properties of the canopy on the ecosystem carbon balance. During the measurement period, the site was a net sink for CO₂ although winter efflux contributed significantly to the total balance. The cumulative growing season NEP as well as mean and maximum daily CO₂ uptake rates was lower during the year with the later snow melt, and the results indicated that the differences were mainly due to differing growing season lengths.
•Rsoil is a fraction of Reco and theoretically must be lower than Reco.•Reco was not consistently higher than Rsoil from daily to annual scales.•We discuss issues with current practices influencing ...under or overestimation of Reco and Rsoil.•Flux networks need a better integration of spatial and temporal variability of Reco and Rsoil.
The net ecosystem exchange (NEE) is the difference between ecosystem CO2 assimilation and CO2 losses to the atmosphere. Ecosystem respiration (Reco), the efflux of CO2 from the ecosystem to the atmosphere, includes the soil-to-atmosphere carbon flux (i.e., soil respiration; Rsoil) and aboveground plant respiration. Therefore, Rsoil is a fraction of Reco and theoretically has to be smaller than Reco at daily, seasonal, and annual scales. However, several studies estimating Reco with the eddy covariance technique and measuring Rsoil within the footprint of the tower have reported higher Rsoil than Reco at different time scales. Here, we compare four different and contrasting ecosystems (from forest to grasslands, and from boreal to semiarid) to test if measurements of Reco are consistently higher than Rsoil. In general, both fluxes showed similar temporal patterns, but Reco was not consistently higher than Rsoil from daily to annual scales across sites. We identified several issues that apply for measuring NEE and measuring/upscaling Rsoil that could result in an underestimation of Reco and/or an overestimation of Rsoil. These issues are discussed based on (a) nighttime measurements of NEE, (b) Rsoil measurements, and (c) the interpretation of the functional relationships of these fluxes with temperature (i.e., Q10). We highlight that there is still a need for better integration of Rsoil with eddy covariance measurements to address challenges related to the spatial and temporal variability of Reco and Rsoil.
Terpenoid emissions above urban areas are a complex mix of
biogenic and anthropogenic emission sources. In line with previous studies
we found that summertime terpenoid fluxes in an alpine city were ...dominated
by biogenic sources. Inter-seasonal emission measurements revealed
consistency for monoterpenes and sesquiterpenes but a large difference in
isoprene between the summers of 2015 and 2018. Standardized emission potentials
for monoterpenes and sesquiterpenes were 0.12 nmol m−2 s−1 and 3.0×10-3 nmol m−2 s−1 in 2015 and 0.11 nmol m−2 s−1
and 3.4×10-3 nmol m−2 s−1 in 2018, respectively. Observed
isoprene fluxes were almost 3 times higher in 2018 than in 2015. This
factor decreased to 2.3 after standardizing isoprene fluxes to 30 ∘C air temperature and photosynthetic active radiation (PAR) to 1000 µmol m−2 s−1. Based on emission model parameterizations, increased
leaf temperatures can explain some of these differences, but standardized
isoprene emission potentials remained higher in 2018 when a heat wave
persisted. These data suggest a higher variability of interannual isoprene
fluxes than for other terpenes. Potential reasons for the observed
differences such as emission parameterization, footprint changes, water
stress conditions, and tree trimming are investigated.
► The energy imbalance is an outstanding problem in micrometeorology. ► We hypothesize that an energy balance model provides further insights into the energy imbalance. ► We used eddy covariance ...energy flux and auxiliary data from three sites in three differing biomes. ► The energy balance model does not contain enough information to constrain the energy imbalance. ► Our approach though provides a sensible way for quality control of energy flux data.
Elucidating the causes for the energy imbalance, i.e. the phenomenon that eddy covariance latent and sensible heat fluxes fall short of available energy, is an outstanding problem in micrometeorology. This paper tests the hypothesis that the full energy balance, through incorporation of additional independent measurements which determine the driving forces of and resistances to energy transfer, provides further insights into the causes of the energy imbalance and additional constraints on energy balance closure options. Eddy covariance and auxiliary data from three different biomes were used to test five contrasting closure scenarios. The main result of our study is that except for nighttime, when fluxes were low and noisy, the full energy balance generally did not contain enough information to allow further insights into the causes of the imbalance and to constrain energy balance closure options. Up to four out of the five tested closure scenarios performed similarly and in up to 53% of all cases all of the tested closure scenarios resulted in plausible energy balance values. Our approach may though provide a sensible consistency check for eddy covariance energy flux measurements.
The Budyko framework elegantly reduces the complex spatial patterns of actual evapotranspiration and runoff to a general function of two variables: mean annual precipitation (MAP) and net radiation. ...While the methodology has first‐order skill, departures from a globally averaged curve can be significant and may be usefully attributed to additional controls such as vegetation type. This paper explores the magnitude of such departures as detected from flux tower measurements of ecosystem‐scale evapotranspiration, and investigates their attribution to site characteristics (biome, seasonal rainfall distribution, and frozen precipitation). The global synthesis (based on 167 sites with 764 tower‐years) shows smooth transition from water‐limited to energy‐limited control, broadly consistent with catchment‐scale relations and explaining 62% of the across site variation in evaporative index (the fraction of MAP consumed by evapotranspiration). Climate and vegetation types act as additional controls, combining to explain an additional 13% of the variation in evaporative index. Warm temperate winter wet sites (Mediterranean) exhibit a reduced evaporative index, 9% lower than the average value expected based on dryness index, implying elevated runoff. Seasonal hydrologic surplus explains a small but significant fraction of variance in departures of evaporative index from that expected for a given dryness index. Surprisingly, grasslands on average have a higher evaporative index than forested landscapes, with 9% more annual precipitation consumed by annual evapotranspiration compared to forests. In sum, the simple framework of supply‐ or demand‐limited evapotranspiration is supported by global FLUXNET observations but climate type and vegetation type are seen to exert sizeable additional controls.
Key Points
Global FLUXNET data support Budyko hypothesis of surface water balance controls
Climate type, vegetation type exert additional control on evapotranspiration
Grasslands exhibit higher evaporative index than forests
•Seven light use efficiency models were compared at global eddy covariance towers.•Performance of seven models differed substantially among ecosystem types.•It is needed to improve LUE models by ...integrating impacts of diffuse radiation and reliable water stress equations.
Simulating gross primary productivity (GPP) of terrestrial ecosystems has been a major challenge in quantifying the global carbon cycle. Many different light use efficiency (LUE) models have been developed recently, but our understanding of the relative merits of different models remains limited. Using CO2 flux measurements from multiple eddy covariance sites, we here compared and assessed major algorithms and performance of seven LUE models (CASA, CFix, CFlux, EC-LUE, MODIS, VPM and VPRM). Comparison between simulated GPP and estimated GPP from flux measurements showed that model performance differed substantially among ecosystem types. In general, most models performed better in capturing the temporal changes and magnitude of GPP in deciduous broadleaf forests and mixed forests than in evergreen broadleaf forests and shrublands. Six of the seven LUE models significantly underestimated GPP during cloudy days because the impacts of diffuse radiation on light use efficiency were ignored in the models. CFlux and EC-LUE exhibited the lowest root mean square error among all models at 80% and 75% of the sites, respectively. Moreover, these two models showed better performance than others in simulating interannual variability of GPP. Two pairwise comparisons revealed that the seven models differed substantially in algorithms describing the environmental regulations, particularly water stress, on GPP. This analysis highlights the need to improve representation of the impacts of diffuse radiation and water stress in the LUE models.
Determining the spatial and temporal distribution of terrestrial gross primary production (GPP) is a critical step in closing the Earth's carbon budget. Dynamical global vegetation models (DGVMs) ...provide mechanistic insight into GPP variability but diverge in predicting the response to climate in poorly investigated regions. Recent advances in the remote sensing of solar‐induced chlorophyll fluorescence (SIF) opens up a new possibility to provide direct global observational constraints for GPP. Here, we apply an optimal estimation approach to infer the global distribution of GPP from an ensemble of eight DGVMs constrained by global measurements of SIF from the Greenhouse Gases Observing SATellite (GOSAT). These estimates are compared to flux tower data in N. America, Europe, and tropical S. America, with careful consideration of scale differences between models, GOSAT, and flux towers. Assimilation of GOSAT SIF with DGVMs causes a redistribution of global productivity from northern latitudes to the tropics of 7–8 Pg C yr⁻¹ from 2010 to 2012, with reduced GPP in northern forests (~3.6 Pg C yr⁻¹) and enhanced GPP in tropical forests (~3.7 Pg C yr⁻¹). This leads to improvements in the structure of the seasonal cycle, including earlier dry season GPP loss and enhanced peak‐to‐trough GPP in tropical forests within the Amazon Basin and reduced growing season length in northern croplands and deciduous forests. Uncertainty in predicted GPP (estimated from the spread of DGVMs) is reduced by 40–70% during peak productivity suggesting the assimilation of GOSAT SIF with models is well‐suited for benchmarking. We conclude that satellite fluorescence augurs a new opportunity to quantify the GPP response to climate drivers and the potential to constrain predictions of carbon cycle evolution.
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