Modeling carbon dynamics in two adjacent spruce forests with different soil conditions in Russia

International audienceNet ecosystem carbon exchange (NEE) were measured with eddy covariance method for two adjacent forests located at the southern boundary of European taiga in Russia in 1999?2004. The two spruce forests shared similar vegetation composition but differed in soil conditions. The wet spruce forest (WSF) possessed a thick peat layer (60 cm) with a high water table seasonally close to or above the soil surface. The dry spruce forest (DSF) had a relatively thin organic layer (5 cm) with a deep water table (>60 cm). The measured NEE fluxes (2000 and ?1440 kg C ha?1 yr?1 for WSF and DSF, respectively) indicated that WSF was a source while DSF a sink of atmospheric carbon dioxide during the experimental years. A process-based model, Forest-DNDC, was employed in the study to interpret the observations. The modeled NEE fluxes were 1800 and ?2200 kg C ha?1 yr?1 for WSF and DSF, respectively, which were comparable with the observations. The modeled data indicated that WSF and DSF had similar rates of photosynthesis and plant autotrophic respiration but differed in soil heterotrophic respiration. The simulations resulted in a hypothesis that the water table fluctuation at WSF could play a key role in determining the negative C balance in the ecosystem. A sensitivity test was conducted by running Forest-DNDC with varied water table scenarios for WSF. The results proved that the NEE fluxes from WSF were highly sensitive to the water table depth. When the water table dropped, the length of flooding season became shorter and more organic matter in the soil profile suffered from rapid decomposition that converted the ecosystem into a source atmospheric C. The conclusion from this modeling study could be applicable for a wide range of wetland and forest ecosystems that have accumulated soil organic C while face hydrological changes under certain climatic or land-use change scenarios

Global Lagrangian atmospheric dispersion model

The Global Lagrangian Atmospheric Dispersion Model (GLADIM) is described. GLADIM is based on the global trajectory model, which had been developed earlier and uses fields of weather parameters from different atmospheric reanalysis centers for calculations of trajectories of air mass that include trace gases. GLADIM includes the parameterization of turbulent diffusion and allows the forward calculation of concentrations of atmospheric tracers at nodes of a global regular grid when a source is specified. Thus, GLADIM can be used for the forward simulation of pollutant propagation (volcanic ash, radionuclides, and so on). Working in the reverse direction, GLADIM allows the detection of remote sources that mainly contribute to the tracer concentration at an observation point. This property of Lagrangian models is widely used for data analysis and the reverse modeling of emission sources of a pollutant specified. In this work we describe the model and some results of its validation through a comparison with results of a similar model and observation data

partitioning of ecosystem respiration in a paludified shallow peat spruce forest in the southern taiga of european russia

Soil, tree stems, and ecosystem carbon dioxide fluxes were measured by chambers and eddy covariance methods in a paludified shallow-peat spruce forest in the southern taiga of European Russia (Tver region, 56 N 33 E) during the growing seasons of 2002‐2012. The site was established in 1998 as part of the EUROSIBERIAN CARBONFLUX project, an international field experiment examining atmosphere‐biosphere interaction in Siberia and European Russia. In all years the observed annual cumulative net ecosystem flux was positive (the forest was a source of carbon to the atmosphere). Soil and tree stem respiration was a significant part of the total ecosystem respiration (ER) in this paludified shallow-peat spruce forest. On average, 49% of the ER came from soil respiration. We found that the soil fluxes exhibited high seasonal variability, ranging from 0.7 to 10 mol m 2 s 1 . Generally, the soil respiration depended on the soil temperature and ground water level. In drought conditions, the soil respiration was low and did not depend on temperature. The stem respiration of spruces grew intensively in May, had permanently high values from June to the end of September, and in October it dramatically decreased. The tree stem respiration in midsummer was about 3‐5 mol m 2 s 1 for dominant trees and about 1‐2 mol m 2 s 1 for subdominant trees. The respiration of living tree stems was about 10‐20% of the ER

Ecosystem transpiration and evaporation: Insights from three water flux partitioning methods across FLUXNET sites

We apply and compare three widely applicable methods for estimating ecosystem transpiration (T) from eddy covariance (EC) data across 251 FLUXNET sites globally. All three methods are based on the coupled water and carbon relationship, but they differ in assumptions and parameterizations. Intercomparison of the three daily T estimates shows high correlation among methods (R between .89 and .94), but a spread in magnitudes of T/ET (evapotranspiration) from 45% to 77%. When compared at six sites with concurrent EC and sap flow measurements, all three EC‐based T estimates show higher correlation to sap flow‐based T than EC‐based ET. The partitioning methods show expected tendencies of T/ET increasing with dryness (vapor pressure deficit and days since rain) and with leaf area index (LAI). Analysis of 140 sites with high‐quality estimates for at least two continuous years shows that T/ET variability was 1.6 times higher across sites than across years. Spatial variability of T/ET was primarily driven by vegetation and soil characteristics (e.g., crop or grass designation, minimum annual LAI, soil coarse fragment volume) rather than climatic variables such as mean/standard deviation of temperature or precipitation. Overall, T and T/ET patterns are plausible and qualitatively consistent among the different water flux partitioning methods implying a significant advance made for estimating and understanding T globally, while the magnitudes remain uncertain. Our results represent the first extensive EC data‐based estimates of ecosystem T permitting a data‐driven perspective on the role of plants’ water use for global water and carbon cycling in a changing climate.We acknowledge insightful discussions with Dario Papale and apologize for having a cappuccino after lunch. We further acknowledge Ulrich Weber for preparing the cappuccino. M.G. acknowledges funding by Swiss National Science Foundation project ICOS‐CH Phase 2 20FI20_173691. L.Š. was supported by the Ministry of Education, Youth and Sports of the Czech Republic within the CzeCOS program, grant number LM2015061, and by SustES‐Adaptation strategies for sustainable ecosystem services and food security under adverse environmental conditions (CZ.02.1.01/0.0/0.0/16_019/0000797). G.W. acknowledges support by the Austrian National Science Fund (FWF, project I03859) and the Province of South Tyrol (“Cycling of carbon and water in mountain ecosystems under changing climate and land use”). R.P. was supported by grants CGL2014‐55883‐JIN, RTI2018‐095297‐J‐I00 (Spain), and by a Humboldt Research Fellowship for Experienced Researchers (Germany). This work used eddy covariance data acquired and shared by the FLUXNET community, including these networks: Ameri‐Flux, AfriFlux, AsiaFlux, CarboAfrica, CarboEuropeIP, CarboItaly, CarboMont, ChinaFlux, Fluxnet‐Canada, GreenGrass, ICOS, KoFlux, LBA, NECC, OzFlux‐TERN, TCOS‐Siberia, and USCCC. The ERA‐Interim reanalysis data are provided by ECMWF and processed by LSCE. The FLUXNET eddy covariance data processing and harmonization was carried out by the European Fluxes Database Cluster, AmeriFlux Management Project, and Fluxdata project of FLUXNET, with the support of CDIAC and ICOS Ecosystem Thematic Center, and the OzFlux, ChinaFlux, and AsiaFlux offices. Open access funding enabled and organized by Projekt DEAL

Influence of Spring and Autumn Phenological Transitions on Forest Ecosystem Productivity

We use eddy covariance measurements of net ecosystem productivity (NEP) from 21 FLUXNET sites (153 site-years of data) to investigate relationships between phenology and productivity (in terms of both NEP and gross ecosystem photosynthesis, GEP) in temperate and boreal forests. Results are used to evaluate the plausibility of four different conceptual models. Phenological indicators were derived from the eddy covariance time series, and from remote sensing and models. We examine spatial patterns (across sites) and temporal patterns (across years); an important conclusion is that it is likely that neither of these accurately represents how productivity will respond to future phenological shifts resulting from ongoing climate change. In spring and autumn, increased GEP resulting from an ¿extra¿ day tends to be offset by concurrent, but smaller, increases in ecosystem respiration, and thus the effect on NEP is still positive. Spring productivity anomalies appear to have carry-over effects that translate to productivity anomalies in the following autumn, but it is not clear that these result directly from phenological anomalies. Finally, the productivity of evergreen needleleaf forests is less sensitive to phenology than is productivity of deciduous broadleaf forests. This has implications for how climate change may drive shifts in competition within mixed-species stands.JRC.H.5-Land Resources Managemen

Winter respiratory C losses provide explanatory power for net ecosystem productivity

Accurate predictions of net ecosystem productivity (NEPc) of forest ecosystems are essential for climate change decisions and requirements in the context of national forest growth and greenhouse gas inventories. However, drivers and underlying mechanisms determining NEPc (e.g., climate and nutrients) are not entirely understood yet, particularly when considering the influence of past periods. Here we explored the explanatory power of the compensation day (cDOY)defined as the day of year when winter net carbon losses are compensated by spring assimilationfor NEPc in 26 forests in Europe, North America, and Australia, using different NEPc integration methods. We found cDOY to be a particularly powerful predictor for NEPc of temperate evergreen needleleaf forests (R-2=0.58) and deciduous broadleaf forests (R-2=0.68). In general, the latest cDOY correlated with the lowest NEPc. The explanatory power of cDOY depended on the integration method for NEPc, forest type, and whether the site had a distinct winter net respiratory carbon loss or not. The integration methods starting in autumn led to better predictions of NEPc from cDOY then the classical calendar method starting 1 January. Limited explanatory power of cDOY for NEPc was found for warmer sites with no distinct winter respiratory loss period. Our findings highlight the importance of the influence of winter processes and the delayed responses of previous seasons' climatic conditions on current year's NEPc. Such carry-over effects may contain information from climatic conditions, carbon storage levels, and hydraulic traits of several years back in time.Peer reviewe

Carbon-nitrogen interactions in European forests and semi-natural vegetation - Part 2: Untangling climatic, edaphic, management and nitrogen deposition effects on carbon sequestration potentials

The effects of atmospheric nitrogen deposition (N$_{dep}$) on carbon (C) sequestration in forests have often been assessed by relating differences in productivity to spatial variations of N$_{dep}$ across a large geographic domain. These correlations generally suffer from covariation of other confounding variables related to climate and other growth-limiting factors, as well as large uncertainties in total (dry+wet) reactive nitrogen (N$_{r}$) deposition.We propose a methodology for untangling the effects of N$_{dep}$ from those of meteorological variables, soil water retention capacity and stand age, using a mechanistic forest growth model in combination with eddy covariance CO$_{2}$ exchange fluxes from a Europe-wide network of 22 forest flux towers. Total N$_{r}$ deposition rates were estimated from local measurements as far as possible. The forest data were compared with data from natural or semi-natural, non-woody vegetation sites. The response of forest net ecosystem productivity to nitrogen deposition (dNEP= dN$_{dep}$) was estimated after accounting for the effects on gross primary productivity (GPP) of the co-correlates by means of a meta-modelling standardization procedure, which resulted in a reduction by a factor of about 2 of the uncorrected, apparent dGPP/dN$_{dep}$ value. This model-enhanced analysis of the C and N$_{dep}$ flux observations at the scale of the European network suggests a mean overall dNEP/dN$_{dep}$ response of forest lifetime C sequestration to N$_{dep}$ of the order of 40–50 g C per g N, which is slightly larger but not significantly different from the range of estimates published in the most recent reviews. Importantly, patterns of gross primary and net ecosystem productivity versus N$_{dep}$ were non-linear, with no further growth responses at high N$_{dep}$ levels (N$_{dep}$ >2.5–3 gNm$^{-2}$ yr$^{-1}$) but accompanied by increasingly large ecosystem N losses by leaching and gaseous emissions. The reduced increase in productivity per unit N deposited at high N$_{dep}$ levels implies that the forecast increased N$_{r}$ emissions and increased Ndep levels in large areas of Asia may not positively impact the continent’s forest CO$_{2}$ sink. The large level of unexplained variability in observed carbon sequestration efficiency (CSE) across sites further adds to the uncertainty in the dC/dN response

The effect of assimilating satellite derived soil moisture in SiBCASA on simulated carbon fluxes in Boreal Eurasia

Boreal Eurasia is a region where the interaction between droughts and the carbon cycle may have significant impacts on the global carbon cycle. Yet the region is extremely data sparse with respect to meteorology, soil moisture and carbon fluxes as compared to e.g. Europe. To better constrain our vegetation model SiBCASA, we increase data usage by assimilating two streams of satellite derived soil moisture. We study if the assimilation improved SiBCASA's soil moisture and its effect on the simulated carbon fluxes. By comparing to unique in situ soil moisture observations, we show that the passive microwave soil moisture product did not improve the soil moisture simulated by SiBCASA, but the active data seem promising in some aspects. The match between SiBCASA and ASCAT soil moisture is best in the summer months over low vegetation. Nevertheless, ASCAT failed to detect the major droughts occurring between 2007 and 2013. The performance of ASCAT soil moisture seems to be particularly sensitive to ponding, rather than to biomass. The effect on the simulated carbon fluxes is large, 5-10% on annual GPP and TER, and tens of percent on local NEE, and 2% on area-integrated NEE, which is the same order of magnitude as the inter-annual variations. Consequently, this study shows that assimilation of satellite derived soil moisture has potentially large impacts, while at the same time further research is needed to understand under which conditions the satellite derived soil moisture improves the simulated soil moisture