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Heatwaves have significant effects on ecosystems and human populations. Human habitability is impacted severely as human exposure to heatwaves is projected to increase. Future risk of heatwaves has demonstrated the need of effective measures for adaptation to persistent hot temperature extremes and ambitious mitigation to limit further increases in heatwave severity.At local scales, forest management could be a potential approach of modifying surface energy budget and in this way alleviating heatwave impacts. In this study, open-site, below-canopy, and above-canopy climatic conditions from 4 different sites during the time period 1997-2020 in the Netherlands were compared to investigate canopy functions of affecting above-canopy macroclimate and as a thermal insulator to regulate understory microclimate and land surface ecology. Using high-resolution sub-daily data sets from Loobos, in which water vapor and heat fluxes were measured every half an hour by a combination of eddy covariance flux measurements and a profile system, we analysed temperatures at three levels of Loobos (23.5m, 7.5m, and soil litter layer) of the same profile and compared them with those measured at open sites in De bilt and Deleen.Heatwave periods are defined as a sequence of at least five days during which the daily maximum temperature exceeds the climatological mean over the reference period 1997-2010 by at least 5 °C. During heatwave periods, the cooling effects of the canopy on surface temperatures are stronger compared to normal periods while the canopy may aggravate the temperature above it during certain hours. By contrast, temperature differences are higher during normal times than heatwave periods when considering temperature buffer effects of canopy on understory climate (7.5m).Further study on heat fluxes, Bowen ratio, and canopy effects on heat stress during normal conditions and heatwaves will be conducted as well. Relative humidity will be incorporated in measuring heat stress to reflect real conditions living bodies experience.

The triple oxygen isotope signature Δ17O in atmospheric CO2 is a potential tracer for gross primary production (GPP). However, interpretation of Δ17O in atmospheric CO2 is complicated by the contributions from respired CO2, isotopic exchange with soil and ocean water, and the release of CO2 by fossil fuel combustion and biomass burning. We studied Δ17O in CO2 at the ecosystem level, which is the domain that integrates the contributions from vegetation and soil to the atmospheric signal. We report for the first time the observed diurnal variation of Δ17O in CO2, measured from air samples collected on 15-16 August 2019 at the mid-latitude pine forest Loobos (ICOS L2 ecosystem site). We also measured the isotopic signatures δ13C and δ18O in CO2 close to the surface (at 0.5 m height, inside the canopy) and from the top of the tower (1-2 m above the canopy). To support the interpretation of the measurements, we used a land-atmosphere model that satisfactorily reproduces the diurnal variability of the interaction between leaf/canopy and the convective boundary layer using mixed-layer theory assumptions (CLASS). Also, we used the global atmospheric transport model TM5 to (1) quantify the contribution of different sources that affect Δ17O in CO2 at Loobos; and (2) extend our analysis of the diurnal cycle to the global scale. Our methodology demonstrates the added value of isotope measurements at ICOS ecosystem and tall-tower sites, and how to integrate meteorological and ecological observations from the canopy up to the atmospheric boundary layer. This study contributes to our ongoing effort of creating an overview of different methods for quantifying photosynthesis from a top-down perspective (concentration-based methods and remote sensing) in a review paper for which we are open to other contributions.

The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-flled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the frst time in this paper. In addition, 206 of these sites are for the frst time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible., European Union (EU), United States Department of Energy (DOE)

To improve our understanding of the global carbon balance and its representation in terrestrial biosphere models, we present here a first dual-species application of the CarbonTracker Data Assimilation System (CTDAS). The system's modular design allows for assimilating multiple atmospheric trace gases simultaneously to infer exchange fluxes at the Earth surface. In the prototype discussed here, we interpret signals recorded in observed carbon dioxide (CO2) along with observed ratios of its stable isotopologues 13CO2∕12CO2 (δ13C). The latter is in particular a valuable tracer to untangle CO2 exchange from land and oceans. Potentially, it can also be used as a proxy for continent-wide drought stress in plants, largely because the ratio of 13CO2 and 12CO2 molecules removed from the atmosphere by plants is dependent on moisture conditions.The dual-species CTDAS system varies the net exchange fluxes of both 13CO2 and CO2 in ocean and terrestrial biosphere models to create an ensemble of 13CO2 and CO2 fluxes that propagates through an atmospheric transport model. Based on differences between observed and simulated 13CO2 and CO2 mole fractions (and thus δ13C) our Bayesian minimization approach solves for weekly adjustments to both net fluxes and isotopic terrestrial discrimination that minimizes the difference between observed and estimated mole fractions.With this system, we are able to estimate changes in terrestrial δ13C exchange on seasonal and continental scales in the Northern Hemisphere where the observational network is most dense. Our results indicate a decrease in stomatal conductance on a continent-wide scale during a severe drought. These changes could only be detected after applying combined atmospheric CO2 and δ13C constraints as done in this work. The additional constraints on surface CO2 exchange from δ13C observations neither affected the estimated carbon fluxes nor compromised our ability to match observed CO2 variations. The prototype presented here can be of great benefit not only to study the global carbon balance but also to potentially function as a data-driven diagnostic to assess multiple leaf-level exchange parameterizations in carbon-climate models that influence the CO2, water, isotope, and energy balance.

The following authors were omitted from the original version of this Data Descriptor: Markus Reichstein and Nicolas Vuichard. Both contributed to the code development and N. Vuichard contributed to the processing of the ERA-Interim data downscaling. Furthermore, the contribution of the co-author Frank Tiedemann was re-evaluated relative to the colleague Corinna Rebmann, both working at the same sites, and based on this re-evaluation a substitution in the co-author list is implemented (with Rebmann replacing Tiedemann). Finally, two affiliations were listed incorrectly and are corrected here (entries 190 and 193). The author list and affiliations have been amended to address these omissions in both the HTML and PDF versions. © 2021, This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply.

Monitoring urban–industrial emissions is often challenging because observations are scarce and regional atmospheric transport models are too coarse to represent the high spatiotemporal variability in the resulting concentrations. In this paper we apply a new combination of an Eulerian model (Weather Research and Forecast, WRF, with chemistry) and a Gaussian plume model (Operational Priority Substances – OPS). The modelled mixing ratios are compared to observed CO2 and CO mole fractions at four sites along a transect from an urban–industrial complex (Rotterdam, the Netherlands) towards rural conditions for October–December 2014. Urban plumes are well-mixed at our semi-urban location, making this location suited for an integrated emission estimate over the whole study area. The signals at our urban measurement site (with average enhancements of 11 ppm CO2 and 40 ppb CO over the baseline) are highly variable due to the presence of distinct source areas dominated by road traffic/residential heating emissions or industrial activities. This causes different emission signatures that are translated into a large variability in observed ΔCO : ΔCO2 ratios, which can be used to identify dominant source types. We find that WRF-Chem is able to represent synoptic variability in CO2 and CO (e.g. the median CO2 mixing ratio is 9.7 ppm, observed, against 8.8 ppm, modelled), but it fails to reproduce the hourly variability of daytime urban plumes at the urban site (R2 up to 0.05). For the urban site, adding a plume model to the model framework is beneficial to adequately represent plume transport especially from stack emissions. The explained variance in hourly, daytime CO2 enhancements from point source emissions increases from 30 % with WRF-Chem to 52 % with WRF-Chem in combination with the most detailed OPS simulation. The simulated variability in ΔCO : ΔCO2 ratios decreases drastically from 1.5 to 0.6 ppb ppm−1, which agrees better with the observed standard deviation of 0.4 ppb ppm−1. This is partly due to improved wind fields (increase in R2 of 0.10) but also due to improved point source representation (increase in R2 of 0.05) and dilution (increase in R2 of 0.07). Based on our analysis we conclude that a plume model with detailed and accurate dispersion parameters adds substantially to top–down monitoring of greenhouse gas emissions in urban environments with large point source contributions within a ∼ 10 km radius from the observation sites.

We present a modelling framework for fossil fuel CO2 emissions in an urban environment, which allows constraints from emission inventories to be combined with atmospheric observations of CO2 and its co-emitted species CO, NOx, and SO2. Rather than a static assignment of average emission rates to each unit-area of the urban domain, the fossil fuel emissions we use are dynamic: they vary in time and space in relation to data that describe or approximate the activity within a sector, such as traffic density, power demand, 2 m temperature (as proxy for heating demand), and sunlight and wind speed (as proxies for renewable energy supply). Through inverse modelling, we optimize the relationships between these activity data and the resulting emissions of all species within the dynamic fossil fuel emission model, based on atmospheric mole fraction observations. The advantage of this novel approach is that the optimized parameters (emission factors and emission ratios, N = 44) in this dynamic model (a) vary much less over space and time, (b) allow a physical interpretation of mean and uncertainty, and (c) have better defined uncertainties and covariance structure. This makes them more suited to extrapolate, optimize, and interpret than the gridded emissions themselves. The merits of this approach are investigated using a pseudo-observation-based ensemble Kalman filter inversion setup for the Dutch Rijnmond area at 1 × 1 km resolution. We find that the dynamic fossil fuel model approximates the gridded emissions well (annual mean differences

Potato is an increasingly important crop in Ethiopia. The Gamo Highlands are one of the large potential potato producing regions in Ethiopia. The growing conditions are different from those in the temperate regions, where most of the agronomical expertise on potato has been developed. The influence of environmental conditions on the crop in the Gamo Highlands is poorly understood. We conducted field trials with eight potato cultivars in six locations and during two seasons. The canopy cover (CC) and plant height (PH) were measured with high temporal resolution and tuber yields were assessed as well. The experiments were conducted near our newly installed weather stations at different elevations. CC and PH were strongly correlated with temperature sum (Tsum). Tuber yields differed among elevations and cultivars. Nevertheless, these differences were poorly explained by environmental variables. We also found that no single cultivar performed best at all elevations. The number of branches was a predictor of yield, suggesting that radiation interception was limiting tuber growth. Tuber yield was optimal when the number of days to crop maturity was around 100&ndash, 110 days. We conclude that Tsum is a predictor of crop growth, but environmental variables poorly explain yield variations, which calls for further investigation.

We present a new methodology, which we call Single Pair of Observations Technique with Eddy Covariance (SPOT-EC), to estimate regional-scale surface fluxes of 222Rn from tower-based observations of 222Rn activity concentration, CO2 mole fractions and direct CO2 flux measurements from eddy covariance. For specific events, the regional (222Rn) surface flux is calculated from short-term changes in ambient (222Rn) activity concentration scaled by the ratio of the mean CO2 surface flux for the specific event to the change in its observed mole fraction. The resulting 222Rn surface emissions are integrated in time (between the moment of observation and the last prior background levels) and space (i.e. over the footprint of the observations). The measurement uncertainty obtained is about ±15 % for diurnal events and about ±10 % for longer-term (e.g. seasonal or annual) means. The method does not provide continuous observations, but reliable daily averages can be obtained. We applied our method to in situ observations from two sites in the Netherlands: Cabauw station (CBW) and Lutjewad station (LUT). For LUT, which is an intensive agricultural site, we estimated a mean 222Rn surface flux of (0.29 ± 0.02) atoms cm−2 s−1 with values > 0.5 atoms cm−2 s−1 to the south and south-east. For CBW we estimated a mean 222Rn surface flux of (0.63 ± 0.04) atoms cm−2 s−1. The highest values were observed to the south-west, where the soil type is mainly river clay. For both stations good agreement was found between our results and those from measurements with soil chambers and two recently published 222Rn soil flux maps for Europe. At both sites, large spatial and temporal variability of 222Rn surface fluxes were observed which would be impractical to measure with a soil chamber. SPOT-EC, therefore, offers an important new tool for estimating regional-scale 222Rn surface fluxes. Practical applications furthermore include calibration of process-based 222Rn soil flux models, validation of atmospheric transport models and performing regional-scale inversions, e.g. of greenhouse gases via the SPOT 222Rn-tracer method.

Severe droughts in the Northern Hemisphere cause widespread decline of agricultural yield, reduction of forest carbon uptake, and increased CO2 growth rates in the atmosphere. Plants respond to droughts by partially closing their stomata to limit their evaporative water loss, at the expense of carbon uptake by photosynthesis. This trade-off maximizes their water-use efficiency, as measured for many individual plants under laboratory conditions and field experiments. Here we analyze the 13C/12C stable isotope ratio in atmospheric CO2 (reported as δ13C) to provide new observational evidence of the impact of droughts on the water-use efficiency across areas of millions of km2 and spanning one decade of recent climate variability. We find strong and spatially coherent increases in water-use efficiency along with widespread reductions of net carbon uptake over the Northern Hemisphere during severe droughts that affected Europe, Russia, and the United States in 2001-2011. The impact of those droughts on water-use efficiency and carbon uptake by vegetation is substantially larger than simulated by the land-surface schemes of six state-of-the-art climate models. This suggests that drought induced carbon-climate feedbacks may be too small in these models and improvements to their vegetation dynamics using stable isotope observations can help to improve their drought response.

The Gamo Highlands in Ethiopia are characterized by complex topography and lakes. These modulate the mesoscale and synoptic scale weather systems. In this study, we analyzed the temporal and spatial variations in weather as function of topography and season and their impact on potato crop growth. To determine how crop growth varies with elevation, we installed a network of six automatic weather stations along two transects. It covers a 30-km radius and 1800-m elevation difference. We conducted a potato field experiment near the weather stations. We used the weather observations as input for a crop model, GECROS. Data analysis showed large differences between weather in February and May. February is more dominated by mesoscale circulations. The averaged February diurnal patter shows a strong east to southeast lake breezes and, at night, weak localized flows driven by mountain density flows. In contrast, in May, the synoptic flow dominates, interacting with the mesoscale flows. The GECROS model satisfactorily predicted the elevational gradient in crop yield. Model sensitivity experiments showed that belg-averaged precipitation distribution gave the highest yield, followed by exchanging May weather observations with April.

Severe droughts in the Northern Hemisphere cause a widespread decline of agricultural yield, the reduction of forest carbon uptake, and increased CO2 growth rates in the atmosphere. Plants respond to droughts by partially closing their stomata to limit their evaporative water loss, at the expense of carbon uptake by photosynthesis. This trade-off maximizes their water-use efficiency (WUE), as measured for many individual plants under laboratory conditions and field experiments. Here we analyse the C-13/C-12 stable isotope ratio in atmospheric CO2 to provide new observational evidence of the impact of droughts on the WUE across areas of millions of square kilometres and spanning one decade of recent climate variability. We find strong and spatially coherent increases in WUE along with widespread reductions of net carbon uptake over the Northern Hemisphere during severe droughts that affected Europe, Russia and the United States in 2001-2011. The impact of those droughts on WUE and carbon uptake by vegetation is substantially larger than simulated by the land-surface schemes of six state-of-the-art climate models. This suggests that drought-induced carbon-climate feedbacks may be too small in these models and improvements to their vegetation dynamics using stable isotope observations can help to improve their drought response.

Monitoring urban-industrial emissions is often challenging, because observations are scarce and regional atmospheric transport models are too coarse to represent the high spatiotemporal variability in the resulting concentrations. In this paper we apply a new combination of a Eulerian model (WRF with chemistry) and a Gaussian plume model (OPS). The modelled mixing ratios are compared to observed CO2 and CO mole fractions at four sites along a transect from an urban-industrial complex (Rotterdam, Netherlands) towards rural conditions for October–December 2014. Urban plumes are well-mixed at our semi-urban location, making this location suited for an integrated emission estimate over the whole study area. The signals at our urban measurement site (with average enhancements of 11 ppm CO2 and 40 ppb CO over the baseline) are highly variable due to the presence of distinct source areas dominated by road traffic/residential heating emissions or industrial activities. This causes different emission signatures that are translated into a large variability in observed ΔCO : ΔCO2 ratios, which can be used to identify dominant source types. We find that WRF-Chem is able to represent synoptic variability in CO2 and CO (e.g. the median CO2 mixing ratio is 9.7 ppm (observed) against 8.7 ppm (modelled)) , but it fails to reproduce the hourly variability of daytime urban plumes at the urban site (R2 up to 0.05). For the urban site, a plume model should be added to the model framework to adequately represent plume transport especially from stack emissions. The explained variance in hourly, daytime CO2 enhancements from point source emissions increases from 30 % with WRF-Chem to 52 % with WRF-Chem in combination with the most detailed OPS simulation. The simulated variability in ΔCO : ΔCO2 ratios decreases drastically from 1.5 to 0.6 ppb ppm−1 which agrees better with the observed standard deviation of 0.4 ppb ppm−1. This is partly due to improved wind fields (increase in R2 of 0.10), but also due to improved point source representation (increase in R2 of 0.05) and dilution (increase in R2 of 0.07). Based on our analysis we conclude that a plume model with detailed and accurate dispersion parameters is inevitable for top-down monitoring of greenhouse gas emissions in urban environments with large point source contributions within a ~ 10 km radius from the observation sites.

To improve our understanding of the global carbon balance and its representation in terrestrial biosphere models we present here a first multi-species application of the CarbonTracker Data Assimilation System (CTDAS). The system's modular design allows for assimilating multiple atmospheric trace gases simultaneously to infer exchange fluxes at the Earth surface. In the prototype discussed here we interpret signals recorded in observed carbon dioxide (CO 2 ) along with observed ratios of its stable isotopologues 13 CO 2 / 12 CO 2 (δ 13 C). The latter is in particular a valuable tracer to untangle CO 2 exchange from land and oceans. Potentially, it can also be used as a proxy for continent-wide drought stress in plants, largely because the ratio of 13 CO 2 and 12 CO 2 molecules removed from the atmosphere by plants is dependent on moisture conditions. The multi-species CTDAS system varies the net exchange fluxes of both 13 CO 2 and CO 2 in ocean and terrestrial biosphere models to create an ensemble of 13 CO 2 and CO 2 fluxes that propagates through an atmospheric transport model. Based on differences between observed and simulated 13 CO 2 and CO 2 mole fractions (and thus δ 13 C) our Bayesian minimization approach solves for weekly adjustments to both net fluxes and isotopic terrestrial discrimination that minimizes the difference between observed and estimated mole fractions. With this system we are able to estimate changes in terrestrial δ 13 C exchange on seasonal and continental scales in the Northern hemisphere where the observational network is most dense. Our results indicate a decrease in stomatal conductance on a continent-wide scale during a severe drought. These changes could only be detected after applying combined atmospheric CO 2 and δ 13 C constraints as done in this work. The additional constraints on surface CO 2 exchange from δ 13 C observations neither affected the estimated carbon fluxes, nor compromised our ability to match observed CO 2 variations. The prototype presented here can be of great benefit not only to study the global carbon balance but potentially also to function as a data driven diagnostic to assess multiple leaf-level exchange parameterizations in carbon-climate models that influence the CO 2 , water, isotope, and energy balance.

In Minda et al. [1], an error was introduced. We propose the following amendment: Figure 9, inSection 3.2.4 (Days to Maturity and Yield), should be replaced by the following updated figure [...]

Nitrogen (N) and phosphorus (P) are two dominant nutrients regulating the productivity of most terrestrial ecosystems. The growing imbalance of anthropogenic N and P inputs into the future is estimated to exacerbate P limitation on land and limit the land carbon (C) sink, so that we hypothesized that P limitation will increasingly reduce C sequestered per unit N deposited into the future. Using a global land surface model (CABLE), we simulated the effects of increased N deposition with and without P limitation on land C uptake and the fate of deposited N on land from 1901 to 2100. Contrary to our hypothesis, we found that N deposition continued to induce land C sequestration into the future, contributing to 15% of future C sequestration as opposed to 6% over the historical period. P limitation reduced the future land C uptake per unit N deposited only moderately at the global scale but P limitation increasingly caused N deposition to have net negative effects on the land C balance in the temperate zone. P limitation further increased the fraction of deposited N that is lost via leaching to aquatic ecosystems, globally from 38.5% over the historical period to 53% into the future, and up to 75% in tropical ecosystems. Our results suggest continued N demand for plant productivity but also indicate growing adverse N deposition effects in the future biosphere, not fully accounted for in global models, emphasizing the urgent need to elaborate on model representations of N and P dynamics.

Monitoring urban-industrial emissions is often challenging, because observations are scarce and regional atmospheric transport models are too coarse to represent the high spatiotemporal variability in the resulting concentrations. In this paper we present a new combination of a Eulerian model (WRF-Chem with an urban parameterisation) and a Lagrangian transport-deposition model (OPS), demonstrating that a plume model strongly improves our ability to capture urban plume transport. This follows from a comparison to observed CO2 and CO mole fractions at four sites along a transect from an urban-industrial complex (Rotterdam, Netherlands) towards rural conditions. At the urban measurement site we find strong enhancements of up to 33.1 ppm CO2 and 84 ppb CO over the rural background concentrations. These signals are highly variable due to the presence of distinct source areas dominated by road traffic/residential heating emissions or industrial activities. This causes different emission signatures that are observed in the CO : CO2 ratios and can be well-reproduced with our framework, suggesting that top-down emission monitoring within this urban-industrial complex is feasible. Further downwind from the city, the urban plume is less frequently observed and its concentration becomes smaller and less variable, making these locations more suited for an integrated emission estimate over the whole study area. We find that WRF-Chem, although able to represent mesoscale patterns, lacks spatiotemporal detail to reproduce the timing, magnitude and variability of urban plumes at the regional background and urban sites. The implementation of the OPS plume model improves the simulation of the CO2 and CO enhancements. The bias for extreme CO2 pollution events is reduced with almost 80 % from 15.4 to 3.4 ppm, while the reproducible fraction of observed variability over 750 measurements more than doubles (to 38 %) with the use of a plume model. Therefore, we argue that a plume model with detailed and accurate dispersion parameters is crucial for top-down monitoring of greenhouse gas emissions in urban environments. Future research could benefit from assimilating observed wind fields to improve the plume representation at urban scales.

We measured the evapotranspiration from the understory vegetation and the whole ecosystem of a Siberian larch forest on the forest floor and above the forest canopy, respectively, using the eddy-covariance method, and obtained the year-to-year difference in evapotranspiration during the early (from 1st to 10th), middle(11th to 20th) and late (21th to the end) periods of month. The year-to-year differences in evapotranspiration from whole ecosystem and understory vegetation were in the range from -11.0 mm to 9.5 mm and from -2.4 mm to 4.7 mm, respectively. These values explained from 20% to 30% of monthly mean evapotranspiration, and thus significant differences were found in this site. To clarify the factor controlling the year-to-year difference in evapotranspiration, we analyzed the relationships among the year-to-year differences in evapotranspiration, radiative and advective terms of Penman–Monteith equation. As a result, due to the small value of decoupling factor of this forest, the most important factor was the year-to-year difference in the advective term. We found that the difference in vapor pressure deficit resulting in the change of the surface conductance was important for year-to-year difference in the advective term in this site.

In this study we examined ecosystem respiration (R-ECO) data from 104 sites belonging to FLUXNET, the global network of eddy covariance flux measurements. The goal was to identify the main factors involved in the variability of R-ECO: temporally and between sites as affected by climate, vegetation structure and plant functional type (PFT) (evergreen needleleaf, grasslands, etc.). We demonstrated that a model using only climate drivers as predictors of R-ECO failed to describe part of the temporal variability in the data and that the dependency on gross primary production (GPP) needed to be included as an additional driver of R-ECO. The maximum seasonal leaf area index (LAI(MAX)) had an additional effect that explained the spatial variability of reference respiration (the respiration at reference temperature T-ref=15 degrees C, without stimulation introduced by photosynthetic activity and without water limitations), with a statistically significant linear relationship (r2=0.52, P 70% of the variance for most vegetation types. Exceptions include tropical and Mediterranean broadleaf forests and deciduous broadleaf forests. Part of the variability in respiration that could not be described by our model may be attributed to a series of factors, including phenology in deciduous broadleaf forests and management practices in grasslands and croplands.

We measured evapotranspiration in an eastern Siberian boreal forest, in which the understory was cowberry and the overstory was larch, during the entire growing seasons of 2005 and 2006. We compared evapotranspiration from the understory vegetation above the forest floor E U with evapotranspiration from the whole ecosystem above the overstory canopy E O . The E U / E O ratio had a seasonal trend with a flat-bottomed U-shape during the growing season (4 May–30 September). High- E U / E O ratios at the beginning and end of the growing season were observed because larch, one of the two sources of E O , was a deciduous tree, while the understory was the evergreen cowberry. The mean daily E U values during the foliated period of larch (1 June–31 August) were 0.8 and 0.9 mm day −1 , or 51.4 and 51.8% of E O in 2005 and 2006, respectively. The understory vegetation was one of the most important components of the hydrologic cycle in this forest. A significant amount of E U was caused by plant physiological control, due to the aerodynamic conductance, which was much larger than the surface conductance, leading to a smaller decoupling coefficient. We found that 71% of E U was caused by the vapour pressure deficit above the forest floor.

Water vapor, energy fluxes, and environmental conditions were measured in an eastern Siberian larch forest for 7 water years, from 1998 to 2006, to understand the water-balance characteristics and interannual variation (IAV). The latent heat flux accounted for 38–67% of the sum of turbulent heat fluxes in June, July, and August, a relatively moderate fraction was compared to values measured at mid- and low latitudes. More than 70% of the annual precipitation evaporated during May to September. Annual evapotranspiration, including interception loss, was relatively steady at 169–220 mm compared with the wide range in annual precipitation (111–347 mm year −1 ). The evapotranspiration rate was 1.49–2.30 mm day −1 on a daily basis from May to September above a dry canopy. This feature is one of the remarkable characteristics of the water balance in eastern Siberian forests. The thawing depth of the permafrost has been rapidly deepening since 2004, such that the maximal thawing depth varied from 127 cm before 2003 to over 200 cm after 2004. At the same time, there was a very large increase in the moisture content of the surface soil. This increase could not be explained by the amount of annual precipitation alone and may have been due to inflow from the deeper thawing layer. The IAV of evapotranspiration was small, but the yearly evapotranspiration coefficient (the ratio of evapotranspiration to potential evaporation) ranged from 0.30 to 0.45. These results indicate that the IAV of evapotranspiration is controlled by regulation of the land surface rather than by atmospheric demand. Soil-moisture content was the most important variable among the factors determining the evapotranspiration coefficient at an interannual temporal scale. This result differs somewhat from previous satellite-based findings that air temperature was a major variable for plant activity. This difference might result from the fact that the IAV of soil water content did not correspond to that of the precipitation amount because of the presence of the permafrost. By contrast, the soil water content was strongly affected by precipitation in the previous summer.

Roughness length and zero-plane displacement over boreal, cool- and warm-temperate forests were observed and parameterised using forest structure data. Previous models for roughness length and zero-plane displacement using leaf area index and frontal area index did not describe intersite differences, and the model for zero-plane displacement did not express seasonal variations with the change of leaf area that was smaller in dense forest than in sparse forest. The observed results show that intersite differences of normalised zero-plane displacement were related to stand density, and seasonal variations were related to leaf area index at each forest, with the degree depending on stand density. From these observations, a new concept is proposed for normalised zero-plane displacement: the basal part is primarily determined by the density of stems and branches (stand density), while the seasonal variation depends on the density of leaves (leaf area index), which is limited to the residual of the basal part. Based on this concept, a new model was developed and verified to express both intersite differences and seasonal variations in observed roughness length and zero-plane displacement.

We measured sensible and latent heat fluxes (H and λE) in five forests located in boreal, cool-temperate, and warm-temperate zones of the Far East concurrently over several years to clarify their energy-consumption characteristics and the variation in and factors controlling evapotranspiration. The consumption of energy for evapotranspiration was larger at the southern sites than at the northern sites, and evapotranspiration in summer (July–August) was larger (average 2.9 mm day−1) for temperate forests than for boreal forests (average 1.7 mm day−1). Differences in energy-consumption characteristics between the forest types (e.g., deciduous vs. coniferous) were not as distinct as those by location. This inter-locational difference resulted from differing evapotranspiration restrictions caused by land-surface characteristics, rather than differing atmospheric evaporation demand.

The satellite-derived normalized difference vegetation index (NDVI), which is used for estimating gross primary production (GPP), often includes contributions from both mosses and vascular plants in boreal ecosystems. For the same NDVI, moss can generate only about one-third of the GPP that vascular plants can because of its much lower photosynthetic capacity. Here, based on eddy covariance measurements, we show that the difference in photosynthetic capacity between these two plant functional types has never been explicitly included when estimating regional GPP in the boreal region, resulting in a substantial overestimation. The magnitude of this overestimation could have important implications regarding a change from a current carbon sink to a carbon source in the boreal region. Moss abundance, associated with ecosystem disturbances, needs to be mapped and incorporated into GPP estimates in order to adequately assess the role of the boreal region in the global carbon cycle. © 2014 Macmillan Publishers Limited. All rights reserved.