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Soil nitrous oxide (N2O) emissions and potato yield were evaluated under 0, 90, and 120 kg N ha−1 fertilizer rates and two planting dates, at productive and degraded fields in the Fraser Valley delta. During the growing season, N2O emissions were comparable among N fertilizer rates. Following November rainfall, N2O emissions increased by three times with 120 kg N ha−1. In the degraded field, yield did not respond to the increasing N fertilizer rates. These findings suggest that lower N fertilizer rates, especially in fields with degraded soils, can lower N2O emissions from British Columbia potato production.

We studied the recovery of tree- and stand-level carbon (C) storage in a lodgepole pine (Pinus contorta Dougl. ex Loud. var. latifolia Engelm.) forest in northern British Columbia that experienced substantial (∼83%) mortality in 2006–2007 (total loss by 2013 = 86%) during a severe mountain pine beetle (MPB; Dendroctonus ponderosae Hopkins, 1902) infestation. Earlier work suggested that this forest recovered positive annual C storage 3 years after attack based on eddy covariance measurements. We sought to confirm these results by examining C storage in surviving pine trees using tree core analysis. Average growth release of surviving lodgepole pine trees was 392% (range of –53% to 2326%) compared with mean decadal growth prior to MPB attack. Nearly 97% of trees underwent a growth release, considerably higher than the 15%–75% reported for lodgepole pine in previous studies. Mean annual stem C storage of the surviving trees in this study was highly correlated (r = 0.88) with 10 years of annual net ecosystem productivity estimates made using the eddy covariance technique, indicating that surviving lodgepole pine remain an important part of C recovery after MPB attack. Mean annual stem C storage was also highly correlated (r = 0.92) with the cumulative percentage of downed stems per hectare at the site, suggesting that increased availability of resources is likely assisting the growth release.

International audience; Evergreen conifer forests are the most prevalent land cover type in North America. Seasonal changes in the color of evergreen forest canopies have been documented with near-surface remote sensing, but the physiological mechanisms underlying these changes, and the implications for photosynthetic uptake, have not been fully elucidated. Here, we integrate on-the-ground phenological observations, leaf-level physiological measurements, near surface hyperspectral remote sensing and digital camera imagery, towerbased CO 2 flux measurements, and a predictive model to simulate seasonal canopy color dynamics. We show that seasonal changes in canopy color occur independently of new leaf production, but track changes in chlorophyll fluorescence, the photochemical reflectance index, and leaf pigmentation. We demonstrate that at winter-dormant sites, seasonal changes in canopy color can be used to predict the onset of canopy-level photosynthesis in spring, and its cessation in autumn. Finally, we parameterize a simple temperature-based model to predict the seasonal cycle of canopy greenness, and we show that the model successfully simulates interannual variation in the timing of changes in canopy color. These results provide mechanistic insight into the factors driving seasonal changes in evergreen canopy color and provide opportunities to monitor and model seasonal variation in photosynthetic activity using color-based vegetation indices.

Understanding the feedback of ecosystem carbon uptake on climate change at temporal and spatial scales is crucial for developing ecosystem models. Previous studies have focused on the role of spring and autumn phenology in regulating carbon sequestration in forest stands, but few on the impact of physiological status in summer. However, plant accumulated the most carbon in summer compared with spring and autumn, therefore, it is of great significance to explore the role of summer phenological metrics on the variability of carbon sequestration. Using 514 site-years of flux data obtained at 40 FLUXNET sites including three forest ecosystems (i.e. evergreen needleleaf forest (ENF), deciduous broadleaf forest (DBF) and mixed forest (MF)) in Europe and North America, we compared the potential of physiological and phenological metrics of Gross Primary Production (GPP) and Ecosystem Respiration (RECO) in explaining the interannual and spatial variability (IAV and SV) of forest net ecosystem production (NEP). In view of the better performance of physiological metrics, we developed the maximum carbon uptake index (MCUI), which integrated the physiology metrics of photosynthesis and respiration in summer, and further explored its ability in explaining the IAV and SV of NEP. The results suggest that the MCUI had a better ability than respiration-growth length ratio (RGR) in predicting NEP for all three forest types. The interpretation of MCUI based on meteorological variables illustrated that the controlling meteorological factors of MCUI differed substantially among ecosystems. The summer shortwave radiation had the greatest influence on MCUI at DBF sites, while the soil water content played an important but opposite role at ENF and DBF sites, and no significant meteorological driver was found at MF sites. The higher potential of MCUI in explaining IAV and SV of NEP highlights the importance of summer physiology in controlling the forest carbon sequestration, and further confirms the significant role of peak plant growth in regulating carbon cycle of forest ecosystems. Understanding the drivers of peak plant growth is therefore of a great significance for further improving the precious of ecosystem model in the future. ISSN:1470-160X ISSN:1872-7034

Compared to the well-known drivers of spatial variability in gross primary productivity (GPP), the relative importance of climatic variables, soil properties and plant traits to the spatial variability in net ecosystem exchange of CO2 between terrestrial ecosystem and atmosphere (NEE) is poorly understood. We used principal component regression to analyze data from 147 eddy flux sites to disentangle effects of climatic variables, soil properties and plant traits on the spatial variation in annual NEE and its components (GPP and ecosystem respiration (RE)) across global forests and grasslands. Our results showed that the largest unique contribution (proportion of variance only explained by one class of variables) to NEE variance came from climatic variables for forests (24%-30%) and soil properties for grasslands (41%-54%). Specifically, mean annual precipitation and potential evapotranspiration were the most important climatic variables driving forest NEE, whereas available soil water capacity, clay content and cation exchange capacity mainly influenced grassland NEE. Plant traits showed a small unique contribution to NEE in both forests and grasslands. However, leaf phosphorus content strongly interacted with soil total nitrogen density and clay content, and these combined factors represented a major contribution for grassland NEE. For GPP and RE, the majority of spatial variance was attributed to the common contribution of climate, soil and plant traits (50% - 62%, proportion of variance explained by more than one class of variables), rather than their unique contributions. Interestingly, those factors with only minor influences on GPP and RE variability (e.g., soil properties) have significant contributions to the spatial variability in NEE. Such emerging factors and the interactions between climatic variables, soil properties and plant traits are not well represented in current terrestrial biosphere models, which should be considered in future model improvement to accurately predict the spatial pattern of carbon cycling across forests and grasslands globally.

Outbreaks of leaf-feeding Lepidopteran insects substantially weaken the quality of forest trees and strongly affect the ecosystem functions of plant photosynthesis and carbon uptake. The narrow phenological time window of leaf out about ten days, during which Lepidopteran larvae feed on high nutrient newly flushed leaves, may change the insect community and outbreak dynamics by determining the survival rate of larvae. The Chinese pine Caterpillar (Dendrolimus tabulaeformis Tsai et Liu) infestation of the northern Chinese pine (Pinus tabulaeformis) forest in China is a major concern, and accurately modeling the day of insect occurrence (DIO) in the spring remains challenging. With continuous in-situ observed insect activities of 20 plots and satellite and meteorological observations from 1983 to 2014, we found a strong synchronization (r = 0.54, p = 0.001) between the satellite-based vegetation spring phenology, i.e. the green-up day (GUD), and DIO of the pine caterpillar over time. We used partial least squares regression and ridge regression models, and identified that monthly preseason air temperature, wind speed, specific humidity, and downward radiation were key environmental cues that awakened the overwintering pine caterpillars. After removing the collinearity of multiple variables, we showed that the dimensionality reduction-based regression models substantially improved the accuracy of DIO modeling than commonly used models, such as interval and degree-day models. In particular, including GUD significantly enhanced the predictive strength of the models increasing the coefficient of determination (R 2) by 17.1% and consequently a decrease of 16.5% in the root mean square error. We further showed that evapotranspiration changed the environmental moisture content, which indirectly affected the activities of insects. Our results revealed a useful linkage between spring leaf development and insect occurrence, and therefore are of great importance for the large-scale monitoring of pest outbreaks with future remote sensing observations.

Extensive revegetation and conservation programs have been initiated in semiarid desert areas in northern China for over 10 years. However, our knowledge on how drought affects the desert ecosystem carbon (C) and water exchanges is limited. Based on eddy covariance measurements, we evaluated the effect of spring and summer droughts on ecosystem C and water exchanges over a semiarid Artemisia ordosica shrubland in Northwest China for 2014–2016. Over the 3 years, the ecosystem was a weak source of C (40 ± 32 g C m−2 y−1) (mean ± standard deviation) with evapotranspiration (ET) of 310 ± 65 mm y−1. Annual net ecosystem production was − 76, − 25 and − 18 g C m−2 y−1 and water use efficiency (WUE) [gross ecosystem production (GEP)/ET] was 0.92, 1.14 and 1.09 g C kg−1 H2O in 2014, 2015 and 2016, respectively, indicating greater C loss and suppressed WUE in 2014. We found that GEP, Re and ET were significantly suppressed in year 2014 when a severe spring drought occurred, as compared to the year 2016 with summer droughts. The differences in C and water fluxes between years 2014 and 2016 were greater than those between years 2015 and 2016, although the ecosystem suffered a severe summer drought in 2015. Interannual differences in GEP were likely due to differences in leaf area index and canopy conductance, both of which were decreased by drought. Our results indicated that spring drought appears to be more critical to the C balance than summer drought in this semiarid shrubland. This suggested that under future climate change with more variable precipitation and frequent droughts expected in northern China, the timing of drought may be critical to the C and water balances.

Ecosystem respiration is a major component of the global terrestrial carbon cycle and is strongly influenced by temperature. The global extent of the temperature-ecosystem respiration relationship, however, has not been fully explored. Here, we test linear and threshold models of ecosystem respiration across 210 globally distributed eddy covariance sites over an extensive temperature range. We find thresholds to the global temperature-ecosystem respiration relationship at high and low air temperatures and mid soil temperatures, which represent transitions in the temperature dependence and sensitivity of ecosystem respiration. Annual ecosystem respiration rates show a markedly reduced temperature dependence and sensitivity compared to half-hourly rates, and a single mid-temperature threshold for both air and soil temperature. Our study indicates a distinction in the influence of environmental factors, including temperature, on ecosystem respiration between latitudinal and climate gradients at short (half-hourly) and long (annual) timescales. Such climatological differences in the temperature sensitivity of ecosystem respiration have important consequences for the terrestrial net carbon sink under ongoing climate change.The authors test for temperature dependency of ecosystem respiration rates across globally distributed eddy covariance sites, revealing consistent temperature thresholds where ecosystem metabolism changes.

Globally, soils store two to three times as much carbon as currently resides in the atmosphere, and it is critical to understand how soil greenhouse gas (GHG) emissions and uptake will respond to ongoing climate change. In particular, the soil‐to‐atmosphere CO2 flux, commonly though imprecisely termed soil respiration (R S), is one of the largest carbon fluxes in the Earth system. An increasing number of high‐frequency R S measurements (typically, from an automated system with hourly sampling) have been made over the last two decades; an increasing number of methane measurements are being made with such systems as well. Such high frequency data are an invaluable resource for understanding GHG fluxes, but lack a central database or repository. Here we describe the lightweight, open‐source COSORE (COntinuous SOil REspiration) database and software, that focuses on automated, continuous and long‐term GHG flux datasets, and is intended to serve as a community resource for earth sciences, climate change syntheses and model evaluation. Contributed datasets are mapped to a single, consistent standard, with metadata on contributors, geographic location, measurement conditions and ancillary data. The design emphasizes the importance of reproducibility, scientific transparency and open access to data. While being oriented towards continuously measured R S, the database design accommodates other soil‐atmosphere measurements (e.g. ecosystem respiration, chamber‐measured net ecosystem exchange, methane fluxes) as well as experimental treatments (heterotrophic only, etc.). We give brief examples of the types of analyses possible using this new community resource and describe its accompanying R software package., Here we describe the lightweight, open source COSORE (COntinuous SOil REspiration) database and software. COSORE focuses on automated, continuous and long‐term greenhouse gas flux datasets, and is intended to serve as a community resource for earth sciences, climate change syntheses and model evaluation.

Peatlands and forests cover large areas of the boreal biome and are critical for global climate regulation. They also regulate regional climate through heat and water vapour exchange with the atmosphere. Understanding how land-atmosphere interactions in peatlands differ from forests may therefore be crucial for modelling boreal climate system dynamics and for assessing climate benefits of peatland conservation and restoration. To assess the biophysical impacts of peatlands and forests on peak growing season air temperature and humidity, we analysed surface energy fluxes and albedo from 35 peatlands and 37 evergreen needleleaf forests-the dominant boreal forest type-and simulated air temperature and vapour pressure deficit (VPD) over hypothetical homogeneous peatland and forest landscapes. We ran an evapotranspiration model using land surface parameters derived from energy flux observations and coupled an analytical solution for the surface energy balance to an atmospheric boundary layer (ABL) model. We found that peatlands, compared to forests, are characterized by higher growing season albedo, lower aerodynamic conductance, and higher surface conductance for an equivalent VPD. This combination of peatland surface properties results in a similar to 20% decrease in afternoon ABL height, a cooling (from 1.7 to 2.5 degrees C) in afternoon air temperatures, and a decrease in afternoon VPD (from 0.4 to 0.7 kPa) for peatland landscapes compared to forest landscapes. These biophysical climate impacts of peatlands are most pronounced at lower latitudes (similar to 45 degrees N) and decrease toward the northern limit of the boreal biome (similar to 70 degrees N). Thus, boreal peatlands have the potential to mitigate the effect of regional climate warming during the growing season. The biophysical climate mitigation potential of peatlands needs to be accounted for when projecting the future climate of the boreal biome, when assessing the climate benefits of conserving pristine boreal peatlands, and when restoring peatlands that have experienced peatland drainage and mining.

Land-cover change exerts more influence on soil respiration in boreal and temperate regions than climate change., Soil respiration (Rs) represents the largest flux of CO2 from terrestrial ecosystems to the atmosphere, but its spatial and temporal changes as well as the driving forces are not well understood. We derived a product of annual global Rs from 2000 to 2014 at 1 km by 1 km spatial resolution using remote sensing data and biome-specific statistical models. Different from the existing view that climate change dominated changes in Rs, we showed that land-cover change played a more important role in regulating Rs changes in temperate and boreal regions during 2000–2014. Significant changes in Rs occurred more frequently in areas with significant changes in short vegetation cover (i.e., all vegetation shorter than 5 m in height) than in areas with significant climate change. These results contribute to our understanding of global Rs patterns and highlight the importance of land-cover change in driving global and regional Rs changes.

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)

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.

The Quest Carbon Capture and Storage (CCS) project in Alberta, Canada, is a fully integrated project, as it involves the capture, transport, injection, storage of CO2, and a measurement, monitoring and verification (MMV) program. The MMV program has two key objectives: a) to ensure containment and b) to ensure conformance. Prior to the start of CO2 injection at the end of August 2015, a number of projects were undertaken to gather data from various domains, namely the atmosphere, biosphere, hydrosphere and geosphere, to provide input to the Quest MMV program. The focus of this paper is on monitoring activities undertaken in relation to the atmosphere and biosphere domains. Activities undertaken across the Quest sequestration lease area (SLA) included an eddy covariance system, soil gas probes, soil flux chambers, and walk-over surveys. In conclusion, understanding the spatial and temporal variability of CO2 levels prior to start of CO2 injection represents an important activity of a CCS MMV program. It provides technical input to the development of such a program, but also provides knowledge for communication to and awareness of project stakeholders (e.g. landowners) regarding CO2 levels within the atmosphere and biosphere across a SLA.

Nitrogen (N) fertilization of forests for increasing carbon sequestration and wood volume is expected to influence soil greenhouse gas (GHG) emissions, especially to increase N2O emissions. As biochar application is known to affect soil GHG emissions, we investigated the effect of biochar application, with and without N fertilization, to a forest soil on GHG emissions in a controlled laboratory study. We found that biochar application at high (10%) application rates increased CO2 and N2O emissions when applied without urea-N fertilizer. At both low (1%) and high biochar (10%) application rates CH4 consumption was reduced when applied without urea-N fertilizer. Biochar application with urea-N fertilization did not increase CO2 emissions compared to biochar amended soil without fertilizer. In terms of CO2-eq, the net change in GHG emissions was mainly controlled by CO2 emissions, regardless of treatment, with CH4 and N2O together accounting for less than 1.5% of the total emissions.

Phenology plays a fundamental role in regulating photosynthesis, evapotranspiration, and surface energy fluxes and is sensitive to climate change. The global mean surface air temperature data indicate a global warming hiatus between 1998 and 2012, while its impacts on global phenology remains unclear. Here we use long-term satellite and FLUXNET records to examine phenology trends in the northern hemisphere before and during the warming hiatus. Our results based on the satellite record show that the phenology change rate slowed down during the warming hiatus. The analysis of the long-term FLUXNET measurements, mainly within the warming hiatus, shows that there were no widespread advancing (or delaying) trends in spring (or autumn) phenology. The lack of widespread phenology trends partly led to the lack of widespread trends in spring and autumn carbon fluxes. Our findings have significant implications for understanding the responses of phenology to climate change and the climate-carbon feedbacks., A global warming hiatus occurred during 1998 and 2012 but its effects on phenology are unclear. Here the authors examine the trends in spring and autumn phenology in the northern hemisphere and the effects of the warming hiatus and show that phenology change rate in the northern hemisphere slowed down during the warming hiatus.

International audience; In the version of this Letter originally published, there were errors in Fig. 1a. The sites denoted purple were described in the legend as `Pday>0.05 & Pnight>0.05', but should have been labelled `Pdaynight>0.05'. The sites denoted green were described in the legend as `Pday>0.05 & Pnight>0.05', but should have been labelled `Pday>0.05 & Pnightday>0.05 & Pnight>0.05', but should have been labelled `Pdaynight

It is critical to have long-term carbon dioxide (CO2) flux observations in forest ecosystems to understand how changing climate can affect forest carbon (C) stocks and CO2 exchange between forests and the atmosphere. In this study, fifteen years (2002–2016) of continuous eddy-covariance flux and climate measurements in an intermediate-aged Douglas-fir stand on the east coast of Vancouver Island, Canada, were analyzed. First, the eddy covariance-measured CO2 fluxes were partitioned into gross primary production and ecosystem respiration using two artificial neural networks. Second, the responses of net ecosystem production, gross primary production and ecosystem respiration to interannual climate variability, including five El Nino-Southern Oscillation events, were determined. Three hyper-parameters (number of layers, hidden units, and batch size) of each artificial neural network were set by Bayesian optimization using sequential model-based optimization while the remaining hyper-parameters were taken from the literature. The first artificial neural network was fitted using only nighttime CO2 flux data and applied to estimate nighttime and daytime ecosystem respiration values, and the second one was used to gap-fill gross primary production values. In addition, a predictor analysis was done to investigate the most influential predictors (i.e., environmental variables) within seasons and years. When applied to half-hourly data, the ecosystem respiration model had an R2 of 0.43, whereas the gross primary production model had an R2 of 0.80. The stand was a moderate C sink (average net ecosystem production of 118 ± 404 g C m−2 year−1) during the entire study period, except for the years 2002–2006 when the stand was a moderate C source. The mean annual values of gross primary production and ecosystem respiration were 1649 ± 157 g C m−2 year−1 and 1531 ± 410 g C m−2 year−1, respectively. Our analysis showed that soil temperature was the most important predictor for the ecosystem respiration model, and photosynthetically active irradiance was the most important predictor for the gross primary production model. However, during dry periods in late summer, soil moisture became the most important predictor. Interannual variability of net ecosystem production was only slightly affected by annual total precipitation, mean soil temperature and mean air temperature. Instead, it depended on spring mean air temperature (start of the growing season), summer total precipitation (indicative of water deficiency) and mean summer air temperature. El Nino and La Nina events generally resulted in lower and higher annual net ecosystem production, respectively.

This study examined the response of carbon (C) sequestration and evapotranspiration (ET) to nitrogen (N) fertilization during the four post-fertilization years (2007–2010) in a Pacific Northwest chronosequence of three Douglas-fir stands 61, 22 and 10 yr old in 2010 (DF49, HDF11 and HDF00, respectively). An artificial neural network (ANN) for time series analysis was employed to identify and estimate the complex nonlinear relationships between C and water exchanges and environmental variables. To test the performance of the ANN model, it was trained against multi-year monthly climate variables and EC-measured C and water fluxes for 1998–2004 and the trained model was then verified using data obtained in 2005 and 2006. The optimized model which showed high reliability (linear regression analysis: for C and water fluxes, R2 > 0.93, slope = 0.96–0.99, p < 0.000) was then used to calculate the C and water fluxes for 2007–2010 assuming the three stands were not fertilized. The calculated C and water fluxes (for non-fertilized conditions) were compared with the measured fluxes (for fertilized conditions) to quantify the effects of fertilization during the post-fertilization four years. Results showed that N fertilization increased gross primary productivity of all three stands in all four years with the largest absolute increases in the 10 yr-old stand (HDF00) followed by the 22 yr-old stand (HDF11). Ecosystem respiration increased in all four years at HDF00, but decreased over the last three years at HDF88, and over all four years in the 61 yr-old stand (DF49). As a result, fertilization increased the net ecosystem productivity of all three stands with the average increase being the largest at HDF88 followed by DF49. In addition, fertilization caused a small increase in annual ET in all four years at DF49; a small increase in the first year and a decrease in the next three years at HDF88; and no consistent effect at HDF00. Consequently, fertilization exerted only a small impact on water use efficiency in the oldest stand (DF49) but a significant increase in the two younger stands (HDF00 and HDF88). Furthermore, N fertilization increased light use efficiency in all three stands, especially in the 10 yr-old stand.

Plant phenology is a sensitive indicator of climate change1–4 and plays an important role in regulating carbon uptake by plants5–7. Previous studies have focused on spring leaf-out by daytime temperature and the onset of snow-melt time8,9, but the drivers controlling leaf senescence date (LSD) in autumn remain largely unknown10–12. Using long-term ground phenological records (14,536 time series since the 1900s) and satellite greenness observations dating back to the 1980s, we show that rising pre-season maximum daytime (Tday) and minimum night-time (Tnight) temperatures had contrasting effects on the timing of autumn LSD in the Northern Hemisphere (> 20° N). If higher Tday leads to an earlier or later LSD, an increase in Tnight systematically drives LSD to occur oppositely. Contrasting impacts of daytime and night-time warming on drought stress may be the underlying mechanism. Our LSD model considering these opposite effects improved autumn phenology modelling and predicted an overall earlier autumn LSD by the end of this century compared with traditional projections. These results challenge the notion of prolonged growth under higher autumn temperatures, suggesting instead that leaf senescence in the Northern Hemisphere will begin earlier than currently expected, causing a positive climate feedback. Rising pre-season daytime and night-time temperatures have contrasting effects on the timing of autumn-leaf senescence date in the Northern Hemisphere. Diurnal differences in drought stress may be the underlying mechanism.

This study compares six evapotranspiration ET products for Canada’s landmass, namely, eddy covariance EC measurements; surface water budget ET; remote sensing ET from MODIS; and land surface model (LSM) ET from the Community Land Model (CLM), the Ecological Assimilation of Land and Climate Observations (EALCO) model, and the Variable Infiltration Capacity model (VIC). The ET climatology over the Canadian landmass is characterized and the advantages and limitations of the datasets are discussed. The EC measurements have limited spatial coverage, making it difficult for model validations at the national scale. Water budget ET has the largest uncertainty because of data quality issues with precipitation in mountainous regions and in the north. MODIS ET shows relatively large uncertainty in cold seasons and sparsely vegetated regions. The LSM products cover the entire landmass and exhibit small differences in ET among them. Annual ET from the LSMs ranges from small negative values to over 600 mm across the landmass, with a countrywide average of 256 ± 15 mm. Seasonally, the countrywide average monthly ET varies from a low of about 3 mm in four winter months (November–February) to 67 ± 7 mm in July. The ET uncertainty is scale dependent. Larger regions tend to have smaller uncertainties because of the offset of positive and negative biases within the region. More observation networks and better quality controls are critical to improving ET estimates. Future techniques should also consider a hybrid approach that integrates strengths of the various ET products to help reduce uncertainties in ET estimation.

Nitrogen (N) enrichment of biochar from both inorganic and organic waste N sources has the potential to add economic and environmental value through its use as a slow release N fertilizer. We investigated the sorption of N by, and its release from, biochar made at pyrolysis temperatures of 400, 500 and 600 °C from three feedstocks: poultry litter (PL with a carbon (C) to N ratio (C:N) of 14), softwood chips of spruce-pine-fir (SPF with a C:N of 470), and a 50:50 mixture of PL and SPF (PL/SPF). The prepared biochars were enriched with ammonium nitrate (AN) and urea ammonium nitrate (UAN). PL biochars had the lowest C content (50-56% C), but the highest pH (9.3-9.9), electrical conductivity (EC, 780-960 dS m(-1)), cation exchange capacity (CEC, 40-46 cmol kg(-1)), and N content (3.3-4.5%). While N content and hydrogen (H) to C atomic ratio (H:C) decreased with increasing pyrolysis temperature irrespective of the feedstock used, both pH and EC slightly increased with pyrolysis temperature for all feedstocks. The PL and SPF biochars showed similar H:C and also similar N sorption and N release at all pyrolysis temperatures. These biochars sorbed up to 5% N by mass, irrespective of the source of N. However, PL/SPF biochar performed poorly in sorbing N from either AN or UAN. Biochar H:C was found to be unrelated to N sorption rates, suggesting that physical adsorption on active surfaces was the main mechanism of N sorption in these biochars. There were minor differences between N sorbed from NO3-N and NH4-N among different biochars. Very small amounts of sorbed N (0.2-0.4 mg N g(-1) biochar) was released when extracted with 1 M KCl solution, indicating that the retained N was strongly held in complex bonds, more so for NH4-N because the release of NO3-N was 3-4 times greater than that of NH4-N. NH4-N sorption far exceeded the effective CEC of the biochars, thereby suggesting that most of the sorption may be due to physical entrapment of NH4(+) in biochar pores. The results of this study suggest that biochar can be used to remove excess N from poultry and dairy manure and be a good mitigation option for reducing N leaching and gaseous losses.

Land-surface models use different formulations of stomatal conductance and plant hydraulics, and it is unclear which type of model best matches the observed surface-atmosphere water flux. We use the North American Carbon Program data set of latent heat flux (LE) measurements from 25 sites and predictions from 9 models to evaluate models' ability to resolve subdaily dynamics of transpiration. Despite overall good forecast at the seasonal scale, the models have difficulty resolving the dynamics of intradaily hysteresis. The majority of models tend to underestimate LE in the prenoon hours and overestimate in the evening. We hypothesize that this is a result of unresolved afternoon stomatal closure due to hydrodynamic stresses. Although no model or stomata parameterization was consistently best or worst in terms of ability to predict LE, errors in model-simulated LE were consistently largest and most variable when soil moisture was moderate and vapor pressure deficit was moderate to limiting. Nearly all models demonstrate a tendency to underestimate the degree of maximum hysteresis which, across all sites studied, is most pronounced during moisture-limited conditions. These diurnal error patterns are consistent with models' diminished ability to accurately simulate the natural hysteresis of transpiration. We propose that the lack of representation of plant hydrodynamics is, in part, responsible for these error patterns.

Hybrid poplar (HP) is an important fast-growing crop with the potential to provide a reliable supply of biomass for the pulp and bioenergy industries while also sequestering carbon (C) in the soil. We used the eddy-covariance technique to measure CO 2 , water vapor and sensible heat fluxes above a three-year-old HP plantation on high productivity land near St Albert, Alberta. Measurements showed that the annual C balance of the plantation shifted from a C source of about 1.54 Mg C ha −1 y −1 in the 2nd year (2010) to a C sink of 0.80 Mg C ha −1 y −1 in the 3rd year (2011). Water use or evapotranspiration ( E ) for 1 June – 31 October increased from 272 mm in 2010 to 321 mm in 2011, and exceeded the respective values of total precipitation of 251 mm and 298 mm for the same period. Annual E in 2010 of 364 mm was less than annual precipitation of 398 mm. In 2011, annual E (442 mm) exceeded annual P (411 mm) by 31 mm; it also exceeded the annual plantation water use E wb , estimated using a water balance method assuming no drainage from the root zone, by 40 mm. However, both courses of cumulative E and E wb closely followed cumulative P . Monthly E increased with increasing net radiation and gross primary productivity. Growing season mean albedo increased from 0.16 in 2010 to 0.21 in 2011 and was consistent with the increase in broadband NDVI. Values of albedo during winter months (November–April) exceeded 0.80. The results suggested that as the plantation grows, growing season albedo, annual C sequestration, and annual water use will increase with the possibility that the latter may exceed annual precipitation. This emphasizes the need to study the long-term sustainability of HP plantations in relation to annual P and its temporal distribution, especially when HP plantations will likely be established on large contiguous areas to supply biomass feedstock for the expanding pulp and bioenergy industries in Western Canada.

The recent mountain pine beetle (MPB) outbreak has had an impact on the carbon (C) cycling of lodgepole pine forests in British Columbia. This study examines how partial harvesting as a forest management response to MPB infestation affects the net ecosystem production (NEP) of a mixed conifer forest (MPB-09) in Interior BC. MPB-09 is a 70-year-old stand that was partially harvested in 2009 after it had been attacked by MPB. Using the eddy-covariance technique, the C dynamics of the stand were studied over two years and compared to an adjacent clear-cut (MPB-09C) over the summertime. The annual NEP at MPB-09 increased from −108 g C m−2 in 2010 to −57 g C m−2 in 2011. The increase of NEP was due to the associated increase in annual gross ecosystem photosynthesis (GEP) from 812 g C m−2 in 2010 to 954 g C m−2 in 2011, exceeding the increase in annual respiration (Re) from 920 g C m−2 to 1011 g C m−2 during the two years. During the four month period between June and September 2010, NEP at MPB-09C was −103 g C m−2, indicating high C losses in the clear-cut. MPB-09 was a C sink during the growing season of both years, increasing from 9 g C m−2 in 2010 to 47 g C m−2 in 2011. The increase of NEP in the partially harvested stand amounted to a recovery corresponding to a 26% increase in the maximum assimilation rate in the second year. This study shows that retaining the healthy residual forest can result in higher C sequestration of MPB-attacked stands compared to clear-cut harvesting.

Nitrogen (N) fertilization of forests for increasing carbon sequestration and wood volume is expected to influence soil greenhouse gas (GHG) emissions, especially to increase N

International audience; Light use efficiency (LUE) models are widely used to simulate gross primary production (GPP). However, the treatment of the plant canopy as a big leaf by these models can introduce large uncertainties in simulated GPP. Recently, a two-leaf light use efficiency (TL-LUE) model was developed to simulate GPP separately for sunlit and shaded leaves and has been shown to outperform the big-leaf MOD17 model at six FLUX sites in China. In this study we investigated the performance of the TL-LUE model for a wider range of biomes. For this we optimized the parameters and tested the TL-LUE model using data from 98 FLUXNET sites which are distributed across the globe. The results showed that the TL-LUE model performed in general better than the MOD17 model in simulating 8 day GPP. Optimized maximum light use efficiency of shaded leaves (epsilon(msh)) was 2.63 to 4.59 times that of sunlit leaves (epsilon(msu)). Generally, the relationships of epsilon(msh) and epsilon(msu) with epsilon(max) were well described by linear equations, indicating the existence of general patterns across biomes. GPP simulated by the TL-LUE model was much less sensitive to biases in the photosynthetically active radiation (PAR) input than the MOD17 model. The results of this study suggest that the proposed TL-LUE model has the potential for simulating regional and global GPP of terrestrial ecosystems, and it is more robust with regard to usual biases in input data than existing approaches which neglect the bimodal within-canopy distribution of PAR.

Understanding feedbacks of ecosystem carbon sequestration to climate change is an urgent step in developing future ecosystem models. Using 187 site-years of flux data observed at 24 sites covering three plant functional types (i.e. evergreen forests (EF), deciduous forests (DF) and non-forest ecosystems (NF) (e.g., crop, grassland, wetland)) in North America, we present an analysis of both interannual and spatial relationships between annual net ecosystem production (NEP) and phenological indicators, including the flux-based carbon uptake period (CUP) and its transitions, degree-day-derived growing season length (GSL), and spring and autumn temperatures. Diverse responses were acquired between annul NEP and these indicators across PFTs. Forest ecosystems showed consistent patterns and sensitivities in the responses of annual NEP to CUP and its transitions both interannually and spatially. The NF ecosystems, on the contrary, exhibited different trends between interannual and spatial relationships. The impact of CUP onset on annual NEP in NF ecosystems was interannually negative but spatially positive. Generally, the GSL was observed to be a likely good indicator of annual NEP for all PFTs both interannually and spatially, although with relatively moderate correlations in NF sites. Both spring and autumn temperatures were positively correlated with annual NEP across sites while this potential was greatly reduced temporally with only negative impacts of autumn temperature on annual NEP in DF sites. Our analysis showed that DF ecosystems have the highest efficiency in accumulating NEP from warmer spring temperature and prolonged GSL, suggesting that future climate warming will favor deciduous species over evergreen species, and supporting the earlier observation that ecosystems with the greatest net carbon uptake have the longest GSL.

We seek to understand how biophysical factors such as soil temperature (Ts), soil moisture (theta), and gross primary production (GPP) influence CO2 fluxes across terrestrial ecosystems. Recent advancements in automated measurements and remote-sensing approaches have provided time series in which lags and relationships among variables can be explored. The purpose of this study is to present new applications of continuous measurements of soil CO2 efflux (F0) and soil CO2 concentrations measurements. Here we explore how variation in Ts, theta, and GPP (derived from NASA's moderate-resolution imaging spectroradiometer [MODIS]) influence F0 and soil CO2 production (Ps). We focused on seasonal variation and used continuous measurements at a daily timescale across four vegetation types at 13 study sites to quantify: (1) differences in seasonal lags between soil CO2 fluxes and Ts, theta, and GPP and (2) interactions and relationships between CO2 fluxes with Ts, theta, and GPP. Mean annual Ts did not explain annual F0 and Ps among vegetation types, but GPP explained 73% and 30% of the variation, respectively. We found evidence that lags between soil CO2 fluxes and Ts or GPP provide insights into the role of plant phenology and information relevant about possible timing of controls of autotrophic and heterotrophic processes. The influences of biophysical factors that regulate daily F0 and Ps are different among vegetation types, but GPP is a dominant variable for explaining soil CO2 fluxes. The emergence of long-term automated soil CO2 flux measurement networks provides a unique opportunity for extended investigations into F0 and Ps processes in the near future.

Carbon dioxide (CO2) from soil respiration is the focus of many ecosystem-atmosphere studies. However, due to the difficulty in obtaining measurements, there is a relative lack of information on the behavior of CO2 in the soil. This paper describes an accurate method that can be used in the field to measure CO2 concentration in small (10-cm) samples of soil air using an infrared gas analyzer. Measurements on samples drawn by syringe from different depths are compared to those calculated using a simple steady-state model derived from the conservation equation for soil CO2 and Fick’s law of diffusion. The study site is a second growth coastal temperate Douglas-fir forest plantation (53 yr old) located on the eastern slope of Vancouver Island, Canada. Measurements of CO2 concentrations were obtained from two locations at six soil depths between 0.02 and 1 m at various times of the year in 2000 and 2001. The vertical profiles of CO2 concentrations generally had similar shapes throughout the year although there was considerably more short-term variability in the shallow layers. Below-ground CO2 concentrations were higher during summer and decreased during the winter. Non-zero CO2 concentration gradients between the 0.5- and 1-m depths suggested some CO2 production below the 1-m depth. By matching modelled CO2 concentrations with measured values and using measured CO2 efflux, we used the model to determine the CO2 production profile. Calculations of CO2 production profiles indicated that more than 85% of the CO2 efflux from this forest soil originates at depths shallower than 30 cm. Key words: Soil carbon dioxide, CO2, soil respiration, steady-state model

A physically‐based multi‐layer numerical model is developed to determine the coupled transport of heat and water in the soil and in the soil‐atmosphere boundary layer. Using inputs of standard weather data and initial soil conditions the model is capable of predicting the surface energy balance components as well as water content and temperature profiles in the soil. It is used to predict these variables for a bare silt loam soil under two tillage treatments, viz. culti‐packed and left loose after disc‐harrowing, and the predicted results are compared with measurements. Very good agreement between the model predictions and measured evaporation and heat fluxes and soil water and temperatures for a ten‐day period shows that the model is capable of simulating the coupled transport of soil heat and soil water and their transfer across the soil surface‐atmosphere interface adequately. Model predictions were compared with those of CLASS (Canadian Land Surface Scheme). It is shown that CLASS, version 2....

Northern regions are experiencing considerable climate change affecting the state of permafrost, peat accumulation rates, and the large pool of carbon (C) stored in soil, thereby emphasizing the importance of monitoring surface C fluxes in different landform sites along a climate gradient. We studied surface net C exchange (NCE) and ecosystem respiration (ER) across different landforms (upland, peat plateau, collapse scar) in mid-boreal to high subarctic ecoregions in the Mackenzie Valley of northwestern Canada for three years. NCE and ER were measured using automatic CO2 chambers (ADC, Bioscientific LTD., Herts, England), and soil respiration (SR) was measured with solid state infrared CO2 sensors (Carbocaps, Vaisala, Vantaa, Finland) using the concentration gradient technique. Both NCE and ER were primarily controlled by soil temperature in the upper horizons. In upland forest locations, ER varied from 583 to 214 g C·m−2·year−1 from mid-boreal to high subarctic zones, respectively. For the bog and peat plateau areas, ER was less than half that at the upland locations. Of SR, nearly 75% was generated in the upper 5 cm layer composed of live bryophytes and actively decomposing fibric material. Our results suggest that for the upland and bog locations, ER significantly exceeded NCE. Bryophyte NCE was greatest in continuously waterlogged collapsed areas and was negligible in other locations. Overall, upland forest sites were sources of CO2 (from 64 g·C·m−2·year−1 in the high subarctic to 588 g C·m−2·year−1 in mid-boreal zone); collapsed areas were sinks of C, especially in high subarctic (from 27 g·C·m−2 year−1 in mid-boreal to 86 g·C·m−2·year−1 in high subarctic) and peat plateaus were minor sources (from 153 g·C·m−2·year−1 in mid-boreal to 6 g·C·m−2·year−1 in high subarctic). The results are important in understanding how different landforms are responding to climate change and would be useful in modeling the effect of future climate change on the soil C balance in the northern regions.

The application of nitrogen fertilizers to Douglas fir forests is known to raise net ecosystem productivity (NEP), but also N2O emissions, the CO2 equivalent of which may offset gains in NEP when accounting for net greenhouse gas (GHG) exchange. However, total changes in NEP and N2O emissions caused by fertilizer between times of application and harvest, while needed for national GHG inventories, are difficult to quantify except through modeling. In this study, integrated hypotheses for soil and plant N processes within the ecosystem model ecosys were tested against changes in CO2 and N2O fluxes recorded with eddy covariance (EC) and surface flux chambers for 1 year after applying 20 g N m−2 of urea to a mature Douglas fir stand in British Columbia. Parameters from annual regressions of hourly modeled versus measured CO2 fluxes conducted before and after fertilization were unchanged (b = 1.0, R2 = 0.8, RMSD = 3.4 mmol m−2 s−1), indicating that model hypotheses for soil and plant N processes did not introduce bias into CO2 fluxes modeled after fertilization. These model hypotheses were then used to project changes in NEP and GHG exchange attributed to the fertilizer during the following 10 years until likely harvest of the Douglas fir stand. Increased CO2 uptake caused modeled and EC‐derived annual NEP to rise from 443 and 386 g C m−2 in the year before fertilization to 591 and 547 g C m−2 in the year after. These gains contributed to a sustained rise in modeled wood C production with fertilization, which was partly offset by a decline in soil C attributed in the model to reduced root C productivity and litterfall. Gains in net CO2 uptake were further offset in the model by a rise of 0.74 g N m−2 yr−1 in N2O emissions during the first year after fertilization, which was consistent with one of 1.05 g N m−2 yr−1 estimated from surface flux chamber measurements. Further N2O emissions were neither modeled nor measured after the first year. At the end of the 11 year model projection, a total C sequestration of 1045 g C m−2 was attributed to the 20 g N m−2 of fertilizer. However, only 119 g C m−2 of this was sequestered in stocks that would remain on site after harvest (foliage, root, litter, soil). The remainder was sequestered as harvested wood, the duration of which would depend on use of the wood product. The direct and indirect CO2‐equivalent costs of this application, including N2O emission, were estimated to offset almost all non‐harvested C sequestration attributed to the fertilizer. An edited version of this paper was published by AGU. Copyright 2010 American Geophysical Union.

agriculture and 2 year old hybrid poplar plantation, respectively. We found that � 75% of soil respiration in the native aspen stand originated from the top 7.5–10 cm litter-fibrichumus layer. Seasonal heterotrophic and autotrophic respiration among the land uses ranged from 97 to 272 and 333 to 560 g C m � 2 , respectively, contributing up to 35% and 83% of total soil respiration, respectively. The variability in soil respiration across different land uses was explained mainly by site differences in soil temperature (88– 94%). Soil respiration followed a pronounced seasonal trend: increasing during the growing season and converging to a minimum in the fall. Soil respiration under different land uses was influenced by (1) ecosystem C stock, (2) temperature sensitivity (Q10 )o f organic matter present, and (3) organic matter decomposability as indicated by the natural abundance of d 13 C. Heterotrophic respiration was influenced by soil temperature, while autotrophic respiration was influenced by fine root biomass and nutrient (NO3 and P) availability. These results are useful in estimating potential responses of soil respiration and its components to future land management and climate change.

[1] The seasonal and interannual variability of gross ecosystem photosynthesis (Pg) and ecosystem respiration (Re), and their relationships to environmental variables and stand characteristics were used to explain the variation of eddy-covariance-measured net ecosystem productivity (FNEP) of three different-aged Douglas-fir stands located on the east coast of Vancouver Island in British Columbia, Canada. During the 9-year period, 1998–2006, which included a strong El Nino/La Nina event, the near-end-of-rotation stand (DF49, 57 years old in 2006) was a moderate carbon (C) sink for CO2 with annual FNEP ranging from 267 to 410 g C m−2 yr−1 (mean ± SD, 357 ± 51 g C m−2 yr−1). The pole/sapling stand (HDF88, 18 years old in 2006) was a weak C source (FNEP = −64 ± 75 g C m−2 yr−1), and the recently harvested stand (HDF00, 6 years old in 2006) was a large C source (FNEP = −515 ± 88 g C m−2 yr−1) during 2002–2006. Irrespective of stand age, all sites responded quite similarly to changes in environmental variables during each year. Daily total values of Pg and Re were highest in July–August in all three stands, while daily FNEP peaked during April–June at DF49, May–June at HDF88, and June–July at HDF00. Reductions in root-zone soil water content decreased both Pg and Re especially during the dry period from May to September, and this effect was more pronounced in the younger stands. Evapotranspiration and dry-foliage surface conductance also decreased with decreasing root-zone soil water content whereas water use efficiency appeared to be conservative, especially at DF49. Increasing spring temperature had a positive effect on annual Pg and Re but caused a slight decrease in annual FNEP. During the summer to autumn transition period, increases in soil water content resulted in a greater increase in Re than Pg causing a reduction in FNEP. The interannual variation in the C balance was determined mainly by the interannual variation in Re for the near-end-of-rotation stand and Pg for the two younger stands. The results indicate that regardless of the stand age, interannual variability in the C balance was mainly determined by year-to-year variability in spring temperature and water availability in late summer.

[1] This study investigated how nitrogen (N) fertilization with 200 kg N ha−1 of a 58-year-old West Coast Douglas fir stand influenced its net greenhouse gas (GHG) global warming potential (GWP) in the first year after fertilization. Effects of fertilization on GHG GWP were calculated considering changes in soil N2O emissions, measured using the static chamber technique and the soil N2O gradient technique; eddy covariance (EC) measured net ecosystem productivity (NEP); and energy requirements of fertilizer production, transport, and its aerial spreading. We found significant N2O losses in fertilized plots compared to a small uptake in nonfertilized plots. Chamber-measured N loss in the fertilized plots was about 16 kg N2O ha−1 in the first year, which is equivalent to 10 kg N ha−1 or 5% of the applied fertilizer N. Soil N2O emissions measured using the gradient technique, however, exceeded the chamber measurements by about 50%. We also compared a polymer-coated slow-release urea with regular urea and found that the former delayed N2O emissions but the year-end total loss was about the same as that from regular urea. Change in NEP due to fertilization was determined by relating annual NEP for the nonfertilized stand to environmental controls using an empirical and a process-based model. Annual NEP increased by 64%, from 326 g C m−2, calculated assuming that the stand was not fertilized, to the measured value of 535 g C m−2 with fertilization. At the end of the year, net change in GHG GWP was −2.28 t CO2 ha−1 compared to what it would have been without fertilization, thereby indicating favorable effect of fertilization even in the first year after fertilization with significant emissions of N2O.

A simple top-down model of canopy photosynthesis (P) was developed and tested in this study. The model (referred to as the Qe-MM model) is P = αQ e P max/(αQ e + P max), α and P max are quantum-use efficiency and potential P, respectively. Q e is given by Q d 0 + kQ b 0, where Q d 0 and Q b 0 are the diffuse and direct photosynthetically active radiation (PAR) incident on the canopy, respectively. Q e can be considered to be the effective incident PAR contributing to P and k is a measure of the contribution of Q b 0 to Q e. When k = 1, the Qe-MM model becomes the regular Michaelis-Menten type model of P (referred to as the MM model). A major objective of this study was to determine how well the Qe-MM model could estimate P of a 56-year-old coastal Douglas-fir stand. To this end, we parameterized the Qe-MM model using five and half years of eddy-covariance measurements of CO2 flux above the Douglas-fir stand. The Qe-MM model, with the incorporation of a function of air temperature, accounted for 74% of the variance in over 34,000 half-hourly P measurements. P estimated using the Qe-MM model had no systematic errors with respect to Q d 0. Although the Qe-MM model has only one more parameter than the MM model, it accounted for 30% more variance in P than the latter when total incident PAR exceeded 900 μmol m−2 s−1. On average, k was found to be 0.22. We show that this small value of k reflects the significant effect of the scattering of the solar beam and the fraction of light-limited sunlit leaves. We also show that the success of the Qe-MM model was due to the fact that a large fraction of the sunlit leaves were light-limited as a result of their orientation to the solar beam.