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Atmospheric inversions use measurements of atmospheric CO2 gradients to constrain regional surface fluxes. Current inversions indicate a net terrestrial CO2 sink in China between 0.16 and 0.35 PgC/yr. The uncertainty of these estimates is as large as the mean because the atmospheric network historically contained only one high altitude station in China. Here, we revisit the calculation of the terrestrial CO2 flux in China, excluding emissions from fossil fuel burning and cement production, by using two inversions with three new CO2 monitoring stations in China as well as aircraft observations over Asia. We estimate a net terrestrial CO2 uptake of 0.39–0.51 PgC/yr with a mean of 0.45 PgC/yr in 2006–2009. After considering the lateral transport of carbon in air and water and international trade, the annual mean carbon sink is adjusted to 0.35 PgC/yr. To evaluate this top-down estimate, we constructed an independent bottom-up estimate based on ecosystem data, and giving a net land sink of 0.33 PgC/yr. This demonstrates closure between the top-down and bottom-up estimates. Both top-down and bottom-up estimates give a higher carbon sink than previous estimates made for the 1980s and 1990s, suggesting a trend towards increased uptake by land ecosystems in China.

article i nfo We describe a pragmatic approach for evaluating the spatial representativeness of flux tower measurements based on footprint climatology modeling analyses of land cover and remotely sensed vegetation indices. The approach was applied to the twelve flux sites of the Canadian Carbon Program (CCP) that include grassland, wetland, and temperate and boreal forests across an east-west continental gradient. The spatial variation within the footprint area was evaluated by examining the spatial structure of Normalized Difference Vegeta- tion Index (NDVI) and land cover using geostatistical analyses of frequency distribution, variogram and win- dow size. The results show that at most sites (i) the percentages of the target vegetation functional type (dominant land cover) observed by the CCP towers were higher than 60%; (ii) to some extent, most of the CCP sites presented anisotropically distributed patterns of NDVI in the 90% annual footprint climatology area; and (iii) the land surface heterogeneity within the flux footprint area differed among sites. Overall, the forest sites had larger fine-scale spatial variation than the grassland and wetland sites. The coniferous bo- real forest sites had greater spatial variability than the two wetland sites and a coniferous temperate forest site. We conclude that the combination of footprint modeling, semivariogram and window size techniques, together with moderate spatial resolution remotely-sensed image data, is a pragmatic approach for assessing the spatial representativeness of flux tower measurements.

The effects of climatic factors and vegetation type on evapotranspiration (E) and water use efficiency (WUE) were analyzed using tower-based eddy-covariance (EC) data for nine mature forest sites, two peatland sites and one grassland site across an east–west continental-scale transect in Canada during the period 2003–2006. The seasonal pattern of E was closely linked to growing-season length and rainfall distribution. Although annual precipitation (P) during the observation period was highly variable among sites (250−1450 mm), minimum annual E was not less than 200 mm and was limited to 400−500 mm where annual P exceeded 700 mm. Site-specific interannual variability in E could be explained by either changes in total P or variations in solar irradiance. A highly positive linear correlation was found between monthly mean values of E and net radiation (Rn) at the grassland site (AB-GRL), the two peatland sites (AB-WPL and ON-EPL), and only one of the forest sites (coastal Douglas-fir, BC-DF49) whereas a hysteretic relationship at the other forest sites indicated that E lagged behind the typical seasonal progression of Rn. Results of a cross-correlation analysis between daily (24-h) E and Rn revealed that site-specific lag times were between 10 and 40 days depending on the lag of vapour pressure deficit (D) behind Rn and the decoupling coefficient, Ω. There was significant seasonal variation in daytime mean dry-foliage Priestley–Taylor α with maxima occurring in the growing season at all sites except BC-DF49 where it was relatively constant (∼0.55) throughout all years. Annual means of daytime dry-foliage α mostly ranging between 0.5 and 0.7 implied stomatal limitation to transpiration. Increasing D significantly decreased canopy conductance (gc) at the forest sites but had little effect at the peatland and grassland sites, while variation in soil water content caused only minor changes in gc. At all sites, a strong linear correlation between monthly mean values of gross primary production (GPP) and E resulted in water use efficiency being relatively constant. While at most sites, WUE was in the range of 2.6–3.6 g C kg−1 H2O, the BC-DF49 site had the highest WUE of the twelve sites with values near 6.0 g C kg−1 H2O. Of the two peatland sites, AB-WPL, a western treed fen, had a significantly higher WUE (∼3.0 g C kg−1 H2O) than ON-EPL, an eastern ombrotrophic bog (∼1.8 g C kg−1 H2O), which was related to peatland productivity and plant functional type.

This study investigated how nitrogen (N) fertilization with 200 kg N ha � 1 of urea affected ecosystem carbon (C) sequestration in the first-postfertilization year in a Pacific Northwest Douglas-fir (Pseudotsuga menziesii) stand on the basis of multiyear eddy-covariance (EC) and soil-chamber measurements before and after fertilization in combination with ecosystem modeling. The approach uses a data-model fusion technique which encompasses both model parameter optimization and data assimilation and minimizes the effects of interannual climatic perturbations and focuses on the biotic and abiotic factors controlling seasonal C fluxes using a prefertilization 9-year-long time series of EC data (1998–2006). A process-based ecosystem model was optimized using the half-hourly data measured during 1998–2005, and the optimized model was validated using measurements made in 2006 and further applied to predict C fluxes for 2007 assuming the stand was not fertilized. The N fertilization effects on C sequestration were then obtained as differences between modeled (unfertilized stand) and EC or soil-chamber measured (fertilized stand) C component fluxes. Results indicate that annual net ecosystem productivity in the first-post-N fertilization year increased by � 83%, from 302 � 19 to 552 � 36 g m � 2 yr � 1 , which resulted primarily from an increase in annual gross primary productivity of � 8%, from 1938 � 22 to 2095 � 29 g m � 2 yr � 1 concurrent with a decrease in annual ecosystem respiration (Re )o f� 5.7%, from 1636 � 17 to 1543 � 31 g m � 2 yr � 1 . Moreover, with respect to respiration, model results showed that the fertilizer-induced reduction in Re (� 93 g m � 2 yr � 1 ) principally resulted from the decrease in soil respiration Rs (� 62 g m � 2 yr � 1 ).

We describe an approach for evaluating the representativeness of eddy covariance flux measurements and assessing sensor location bias (SLB) based on footprint modelling and remote sensing This approach was applied to the 12 main sites of the Fluxnet-Canada Research Network (FCRN)/Canadian Carbon Program (CCP) located along an east-west continental-scale transect covering grassland forest and wetland biomes For each site monthly and annual footprint climatologies e monthly or annual cumulative footprints) were calculated using the Simple Analytical Footprint model on Eulerian coordinates (SAFE) The resulting footprint climatologies were then overlaid on to Images of the Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) derived from LANDSAT Thematic Mapper (TM) imagery which were used as surrogates of land surface fluxes to estimate SLB Results indicate that (i) the sizes of annual footprint climatology Increased exponentially with increasing cumulative footprint percentages and for a given percentage of footprint climatology the footprint areas were significantly different among the sites Typically the 90% annual footprint climatology areas varied from 1 1 km(2) to 5 0 km(2) (ii) using either NDVI or EVI as the flux surrogate the SLB was less than 5% for most sites with respect to the reference area of interest (A(r)) at 90% annual footprint climatology (scenario A) and a circular area with radius of 1 km centred at the individual tower (scenario B) with several exceptions (iii) the SLB decreased with increasing size of footprint climatology for all sites for both scenarios A and B (iv) out of 12 eight flux towers represented most of the ecosystem surrounding the towers for an area of 0 3 km(2) up to 10 km(2) with a satisfactorily low bias of

This study analyzes 9 years of eddy-covariance (EC) data carried out in a Pacific Northwest Douglas-fir (Pseudotsuga menzesii) forest (58-year old in 2007) on the east coast of Vancouver Island, Canada, and characterizes the seasonal and interannual variability in net ecosystem productivity (NEP), gross primary productivity (GPP), and ecosystem respiration (Re) and primary climatic controls on these fluxes. The annual values (± SD) of NEP, GPP and Re were 357 ± 51, 2124 ± 125, and 1767 ± 146 g C m−2 yr−1, respectively, with ranges of 267–410, 1592–2338, and 1642–2071 g C m−2 yr−1, respectively. Spring to early summer (March–June) accounted for more than 80% of annual NEP while late spring to early autumn (May–August) was mainly responsible for its interannual variability (∼80%). The major drivers of interannual variability in annual carbon (C) fluxes were annual and spring mean air temperatures (Ta) and water deficiency during late summer and autumn (July–October) when this Douglas-fir forest growth was often water-limited. Photosynthetically active radiation (Q), and the combination of Q and soil water content (θ) explained 85% and 91% of the variance of monthly GPP, respectively; and 91% and 96% of the variance of monthly Re was explained by Ta and the combination of Ta and θ, respectively. Annual net C sequestration was high during optimally warm and normal precipitation years, but low in unusually warm or severely dry years. Excluding 1998 and 1999, the 2 years strongly affected by an El Nino/La Nina cycle, annual NEP significantly decreased with increasing annual mean Ta. Annual NEP will likely decrease whereas both annual GPP and Re will likely increase if the future climate at the site follows a trend similar to that of the past 40 years.

We describe pragmatic and reliable methods to examine the influence of patch-scale heterogeneities on the uncertainty in long-term eddy-covariance (EC) carbon flux data and to scale between the carbon flux estimates derived from land surface optical remote sensing and directly derived from EC flux measurements on the basis of the assessment of footprint climatology. Three different aged Douglas-fir stands with EC flux towers located on Vancouver Island and part of the Fluxnet Canada Research Network were selected. Monthly, annual and interannual footprint climatologies, unweighted or weighted by carbon fluxes, were produced by a simple model based on an analytical solution of the Eulerian advection-diffusion equation. The dimensions and orientation of the flux footprint depended on the height of the measurement, surface roughness length, wind speed and direction, and atmospheric stability. The weighted footprint climatology varied with the different carbon flux components and was asymmetrically distributed around the tower, and its size and spatial structure significantly varied monthly, seasonally and inter-annually. Gross primary productivity (GPP) maps at 10-m resolution were produced using a tower-mounted multi-angular spectroradiometer, combined with the canopy structural information derived from airborne laser scanning (Lidar) data. The horizontal arrays of footprint climatology were superimposed on the 10-m-resolution GPP maps. Monthly and annual uncertainties in EC flux caused by variations in footprint climatology of the 59-year-old Douglas-fir stand were estimated to be approximately 15-20% based on a comparison of GPP estimates derived from EC and remote sensing measurements, and on sensor location bias analysis. The footprint-variation-induced uncertainty in long-term EC flux measurements was mainly dependent on the site spatial heterogeneity. The bias in carbon flux estimates using spatially-explicit ecological models or tower-based remote sensing at finer scales can be estimated by comparing the footprint-weighted and EC-derived flux estimates. This bias is useful for model parameter optimizing. The optimization of parameters in remote-sensing algorithms or ecosystem models using satellite data will, in turn, increase the accuracy in the upscaled regional carbon flux estimation.

A new remote-sensing-based land surface model, named ecosystem–atmosphere simulation scheme (EASS), is introduced in this paper. The principle motivation for formulating EASS is to provide realistic partition of energy fluxes at regional scales as well as consistent estimates of carbon assimilation rates. EASS has the following characteristics: (i) satellite data are used to describe the spatial and temporal information on vegetation, and in particular, we use a foliage clumping index (˝) in addition to leaf area index to characterize the effects of three-dimensional canopy structure on radiation, energy and carbon fluxes; (ii) energy and water exchanges and carbon assimilation in the soil–vegetation–atmosphere system are fully coupled and are simulated simultaneously; (iii) the energy and carbon assimilation fluxes are calculated with stratification of sunlit and shaded leaves to avoid shortcomings of the “big-leaf” assumption. Model experiments shows that the simulation realism and accuracy by the new strategy are enhanced about 9–14% compared with the “big-leaf model”. Moreover, ˝ is useful for accurate separation of sunlit and shaded leaves in the canopy. The accuracy in simulation of energy and carbon fluxes increase about 5–8% by considering the effects of ˝ on the radiation interception and the separation of sunlit and shaded leaves; (iv) snow and soil simulations are emphasized by including a flexible and multiple layer scheme. EASS has been tested and validated against multiple-year observed data at several sites. EASS is proved to be overall successful in capturing variations in energy fluxes, canopy and soil temperatures, and soil moisture over diurnal, synoptic, seasonal and inter-annual temporal scales.

Accurate estimation of temporal and spatial variations in photosynthetic discrimination of 13C is critical to carbon cycle research. In this study, a combined ecosystem-boundary layer isotope model, which was satisfactorily validated against intensive campaign data, was used to explore the temporal variability of carbon discrimination in response to environmental driving factors in a boreal ecosystem in the vicinity of Fraserdale Tower, Ontario, Canada (49 degrees 52'30''N, 81 degrees 34'12''W). A 14 year (1990-1996 and 1998-2004) hourly CO2 concentration and meteorological record measured on this tower was used for this purpose. The 14 year mean yearly diurnal amplitude of canopy-level discrimination Delta(canopy) was computed to be 2.8 +/- 0.5 per thousand, and the overall diurnal cycle showed that the greatest Delta(canopy) values occurred at dawn and dusk, while the minima generally appeared in mid-afternoon. The average annual Delta(canopy) varied from 18.3 to 19.7 per thousand with the 14 year average of 19 +/- 0.4 per thousand. The overall seasonality of Delta(canopy) showed a gradually increasing trend from leaf emergence in May-September and with a slight decrease at the end of the growing season in October. Delta(canopy) was negatively correlated to vapour pressure deficit and air temperature across hourly to decadal timescales. A strong climatic control on stomatal regulation of ecosystem isotope discrimination was found in this study.

Land surface models (LSMs) need to be coupled with atmospheric general circulation models (GCMs) to adequately simulate the exchanges of energy, water, and carbon between the atmosphere and terrestrial surfaces. The heterogeneity of the land surface and its interaction with temporally and spatially varying meteorological conditions result in nonlinear effects on fluxes of energy, water, and carbon, making it challenging to scale these fluxes accurately. The issue of up-scaling remains one of the critical unsolved problems in the parameterization of subgrid-scale fluxes in coupled LSM and GCM models. A new distributed LSM, the Ecosystem–Atmosphere Simulation Scheme (EASS) was developed and coupled with the atmospheric Global Environmental Multiscale model (GEM) to simulate energy, water, and carbon fluxes over Canada’s landmass through the use of remote sensing and ancillary data. Two approaches (lumped case and distributed case) for handling subgrid heterogeneity were used to evaluate the effect of land-cover heterogeneity on regional flux simulations based on remote sensing. Online runs for a week in August 2003 provided an opportunity to investigate model performance and spatial scaling issues. Comparisons of simulated results with available tower observations (five sites) across an east–west transect over Canada’s southern forest regions indicate that the model is reasonably successful in capturing both the spatial and temporal variations in carbon and energy fluxes, although there were still some biases in estimates of latent and sensible heat fluxes between the simulations and the tower observations. Moreover, the latent and sensible heat fluxes were found to be better modeled in the coupled EASS–GEM system than in the uncoupled GEM. There are marked spatial variations in simulated fluxes over Canada’s landmass. These patterns of spatial variation closely follow vegetation-cover types as well as leaf area index, both of which are highly correlated with the underlying soil types, soil moisture conditions, and soil carbon pools. The surface fluxes modeled by the two up-scaling approaches (lumped and distributed cases) differ by 5%–15% on average and by up to 15%–25% in highly heterogeneous regions. This suggests that different ways of treating subgrid land surface heterogeneities could lead to noticeable biases in model output.

In order to test two hypotheses: (i) that carbon (C) and energy exchanges between terrestrial ecosystems and the atmosphere are closely constrained by soil water availability, and (ii) that vegetation is able to optimize soil water uptake from different soil layers; two model simulations were conducted. The Boreal Ecosystem Productivity Simulator (BEPS) model was run to simulate an aspen forest in Saskatchewan, Canada during the period 1997–2004. In Simulation 1, the effect of soil water availability in different soil layers on stomatal conductance was weighted only by root fraction. In Simulation 2, the influence of soil water availability in different soil layers on stomatal conductance was weighted according to both the root fraction and soil water availability, in order to allow easier access of roots to soil layers containing more water. Comparison against measured fluxes showed that Simulation 2 was an improvement over Simulation 1 in predicting C, water and energy fluxes at different time scales in dry years. In Simulation 1, the daytime C and water fluxes were underestimated during the transition from adequate to insufficient soil water content in the upper layers. In this run, the model captured 92, 79 and 91% of the daily variances in gross primary productivity (GPP), net ecosystem productivity (NEP), and ecosystem respiration ( R e ) during 1997–2004. In Simulation 2, the daily variances of GPP, NEP, and R e explained by the model increased to 93, 82 and 92%, respectively. In Simulation 1, the annual NEP was considerably underestimated in the dry years and years with dry periods, with a root mean square error (RMSE) of 45 g C m −2 year −1 ( n = 8) from 1997 to 2004. In Simulation 2, the RMSE value of simulated annual NEP was reduced to 14 g C m −2 year −1 , a relatively small value compared with the average NEP of 157 g C m −2 year −1 during 1997–2004. This suggested that the ability of plant roots to extract water from deep soil layers is critical for the forest to maintain growth when surface layers dried out. Our model results showed that NEP was very sensitive to water conditions at this site. In wet years, heterotrophic respiration was enhanced and NEP was reduced.

Stable isotopes of CO2 contain unique information on the biological and physical processes that exchange CO2 between terrestrial ecosystems and the atmosphere. In this study, we developed an integrated modeling system to simulate dynamics of stable carbon isotope of CO2, as well as moisture, energy, and momentum, between a boreal forest ecosystem and the atmosphere, as well as their transport/mixing processes through the convective boundary layer (CBL), using remotely sensed surface parameters to characterize the surface heterogeneity. It has the following characteristics: (i) it accounts for the influences of the CBL turbulent mixing and entrainment of the air aloft; (ii) it scales individual leaf-level photosynthetic discrimination up to the whole canopy (Δcanopy) through the separation of sunlit and shaded leaf groups; (iii) it has the capacity to examine the detailed interrelationships among plant water-use efficiency, isotope discrimination, and vapor pressure deficit; and (iv) it has the potential to investigate how an ecosystem discriminates against 13C at various time and spatial scales. The monthly mean isotopic signatures of ecosystem respiration (i.e. δ13CR) used for isotope flux calculation are retrieved from the nighttime flask data from the intensive campaigns (1998–2000) at 20 m level on Fraserdale tower, and the data from the growing season in 1999 are used for model validation. Both the simulated CO2 mixing ratio and δ13C of CO2 at the 20 m level agreed with the measurements well in different phases of the growing season. On a diurnal basis, the greatest photosynthetic discrimination at canopy level (i.e. Δcanopy) occurred early morning and late afternoon with a varying range of 10–26‰. The diurnal variability of Δcanopy was also associated with the phases of growing season and meteorological variables. The annual mean Δcanopy in 1999 was computed to be 19.58‰. The monthly averages of Δcanopy varied between 18.55‰ and 20.84‰ with a seasonal peak during the middle growing season. Because of the strong opposing influences of respired and photosynthetic fluxes on forest air (both CO2 and 13CO2) on both the diurnal and seasonal time scales, CO2 was consistently enriched with the heavier 13C isotope (less negative δ13C) from July to October and depleted during the remaining months, whereas on a diurnal basis, CO2 was enriched with the heavier 13C in the late afternoon and depleted in early morning. For the year 1999, the model results reveal that the boreal ecosystem in the vicinity of Fraserdale tower was a small sink with net uptake of 29.07 g 12C m−2 yr−1 and 0.34 g 13C m−2 yr−1.

In this study we use a modified version of the ecosystem model Boreal Ecosystem Productivity Simulator (BEPS) to simulate gross primary productivity (GPP) derived from measured CO2 flux at the Takayama site, which is characterized by a broadleaf deciduous secondary forest. The period of simulation is from 1998 to 2002. The performance of the model is assessed in its ability to reproduce seasonal and inter-annual variations in the derived GPP. Given appropriate vegetation parameters and meteorological conditions for the site, we find that the model can simulate seasonal changes and inter-annual variability of GPP that are in close agreement with those derived from the eddy covariance CO2 flux measurements. Estimated annual GPPs (in gC m−2) are 1171 (1998), 1024 (1999), 1274 (2000), 1200 (2001), and 1243 (2002). (Positive GPP is defined as ecosystem assimilation of CO2.) Although the inter-annual variability of the seasonal cycle and its upward trend are simulated relatively well, the model tends to overestimate GPP, particularly from 2000 to 2002 when the measured leaf area index (LAI) during the growing season was relatively high. Furthermore, due to certain missing phenological mechanisms in the model, it tends to overestimate photosynthetic absorption during the latter half of the growing season. Also, the model does not resolve the understory of dense evergreen dwarf bamboo at the site, thus failing to catch the start of photosynthetic activity by the understory before the leaf emergence of the woody component takes place in the spring. Results indicate that the observed inter-annual variability in GPP at the Takayama site has been influenced mostly by changes in LAI.

While low-to-moderate resolution gridded climate data are suitable for climate-impact modeling at global and ecosystems levels, spatial analyses conducted at local scales require climate data with increased spatial accuracy. This is particularly true for research focused on the evaluation of adaptive forest management strategies. In this study, we developed an application, ClimateAP, to generate scale-free (i.e., specific to point locations) climate data for historical (1901–2015) and future (2011–2100) years and periods. ClimateAP uses the best available interpolated climate data for the reference period 1961–1990 as baseline data. It downscales the baseline data from a moderate spatial resolution to scale-free point data through dynamic local elevation adjustments. It also integrates and downscales the historical and future climate data using a delta approach. In the case of future climate data, two greenhouse gas representative concentration pathways (RCP 4.5 and 8.5) and 15 general circulation models are included to allow for the assessment of alternative climate scenarios. In addition, ClimateAP generates a large number of biologically relevant climate variables derived from primary monthly variables. The effectiveness of the local downscaling was determined based on the strength of the local linear regression for the estimate of lapse rate. The accuracy of the ClimateAP output was evaluated through comparisons of ClimateAP output against observations from 1805 weather stations in the Asia Pacific region. The local linear regression explained 70%–80% and 0%–50% of the total variation in monthly temperatures and precipitation, respectively, in most cases. ClimateAP reduced prediction error by up to 27% and 60% for monthly temperature and precipitation, respectively, relative to the original baselines data. The improvements for baseline portions of historical and future were more substantial. Applications and limitations of the software are discussed.

Understanding how the dynamics of vegetation growth respond to climate change at different temporal and spatial scales is critical to projecting future ecosystem dynamics and the adaptation of ecosystems to global change. In this study, we investigated vegetated growth dynamics (annual productivity, seasonality and the minimum amount of vegetated cover) in China and their relations with climatic factors during 1982–2011, using the updated Global Inventory Modeling and Mapping Studies (GIMMS) third generation global satellite Advanced Very High Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (NDVI) dataset and climate data acquired from the National Centers for Environmental Prediction (NCEP). Major findings are as follows: (1) annual mean NDVI over China significantly increased by about 0.0006 per year from 1982 to 2011; (2) of the vegetated area in China, over 33% experienced a significant positive trend in vegetation growth, mostly located in central and southern China; about 21% experienced a significant positive trend in growth seasonality, most of which occurred in northern China (>35°N); (3) changes in vegetation growth dynamics were significantly correlated with air temperature and precipitation (p < 0.001) at a region scale; (4) at the country scale, changes in NDVI was significantly and positively correlated with annual air temperature (r = 0.52, p < 0.01) and not associated with annual precipitation (p > 0.1); (5) of the vegetated area, about 24% showed significant correlations between annual mean NDVI and air temperature (93% positive and remainder negative), and 12% showed significant correlations of annual mean NDVI with annual precipitation (65% positive and 35% negative). The spatiotemporal variations in vegetation growth dynamics were controlled primarily by temperature and secondly by precipitation. Vegetation growth was also affected by human activities; and (6) monthly NDVI was significantly correlated with the preceding month’s temperature and precipitation in western, central and northern China. The effects of a climate lag of more than two months in southern China may be caused mainly by the abundance of precipitation. These findings suggest that continuing efforts to monitor vegetation changes (in situ and satellite observations) over time and at broad scales are greatly needed, and are critical for the management of ecosystems and adapting to global climatic changes. It is likewise difficult to predict well future vegetation growth without linking these observations to mechanistic terrestrial ecosystem processes models that integrate all the satellite and in situ observations.

The updated Global Inventory Modeling and Mapping Studies (GIMMS) third generation global satellite Advanced Very High Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (NDVI) dataset provides very detailed global information on the state of vegetation from 1982 to 2011. Using these data we investigated the changes in the vegetation photosynthetic activity in the Asia-Pacific (AP) (including Australia, South East Asia, China, and the Pacific Coast of North America) region, by discerning gradual changes into two key metrics: 1) the cumulative annual NDVI in each year and 2) the seasonality or variance in that index. We then assessed changes using break and turning points using three statistical models (least-square linear, expanded paired-consecutive linear and piecewise regression models). We found that the AP region overall experienced increasing NDVI from 1982 through 2011 with an average rate of 530 x 10(-4) NDVI yr(-1) (0.13% yr(-1)). The annual NDVI increased from 1982 at a faster rate of 26.14 x 10(-4) NDVI yr-1 (0.65% yr(-1)) until a break in the trend after 1991 (after that the trend reduced to 5.78 x 10(-4) NDVI yr(-1)). In the Asia-Australia (AA) subarea of the AP, vegetation greening slowly increased at 8.71 x 10(-4) NDVI yr(-1) before 2003 and then increased to 28.30 x 10(-4) NDVI yr(-1) after 2003. In contrast, in the North America (NA) subarea NDVI rapidly increased initially at 18.72 x 10(-4) NDVI yr(-1) before 1992 and then marginally increased (3.96 x 10(-4) NDVI yr(-1)) after 1992. The turning points were found to be 2008 and 1987 for the AA and NA subareas respectively. Analysis of monthly NDVI data showed that the trends were positive for most of the months of the study period, particularly during the growing season. Geospatial analyses demonstrated that cumulative annual NDVI and the variance or seasonality across the large AP region varied across the different subareas. As well, we found evidence for different spatial patterns of the NDVI changes with strong spatial heterogeneity in the patterns of the break and turning points. This suggests complex and nonlinear responses of vegetation photosynthetic activity to regional climatic changes and other drivers. (C) 2014 Elsevier Inc. All rights reserved.

High spatiotemporal resolution satellite imagery is useful for natural resource management and monitoring for land-use and land-cover change and ecosystem dynamics. However, acquisitions from a single satellite can be limited, due to trade-offs in either spatial or temporal resolution. The spatial and temporal adaptive reflectance fusion model (STARFM) and the enhanced STARFM (ESTARFM) were developed to produce new images with high spatial and high temporal resolution using images from multiple sources. Nonetheless, there were some shortcomings in these models, especially for the procedure of searching spectrally similar neighbor pixels in the models. In order to improve these modelsâ?? capacity and accuracy, we developed a modified version of ESTARFM (mESTARFM) and tested the performance of two approaches (ESTARFM and mESTARFM) in three study areas located in Canada and China at different time intervals. The results show that mESTARFM improved the accuracy of the simulated reflectance at fine resolution to some extent.

Until now, most of the early rice remains in China were found in the middle to lower reaches of the Yangtze River drainage. Recently, rice remains earlier than 8000 B.P. were found from Jiahu site (8942-7801 B.P.) in Wuyang County of Henan Province, central China. This is the earliest cultivated rice found at this latitude (33°37’N), which is far outside the current distribution of wild rice species. The discovery is of great implications. It suggests that central China may be one of the centers of early rice domestication.

Climate change inevitably leads to changes in hydrothermal circulation. However, thermal-hydrologic exchanging caused by land cover change has also undergone ineligible changes. Therefore, studying the comprehensive effects of climate and land cover changes on land surface water and heat exchanges enables us to well understand the formation mechanism of regional climate and predict climate change with fewer uncertainties. This study investigated the land surface thermal-hydrologic exchange across southern China for the next 40 years using a land surface model (ecosystem-atmosphere simulation scheme (EASS)). Our findings are summarized as follows. (i) Spatiotemporal variation patterns of sensible heat flux (H) and evapotranspiration (ET) under the land cover scenarios (A2a or B2a) and climate change scenario (A1B) are unanimous. (ii) BothHand ET take on a single peak pattern, and the peak occurs in June or July. (iii) Based on the regional interannual variability analysis,Hdisplays a downward trend (10%) and ET presents an increasing trend (15%). (iv) The annual averageHand ET would, respectively, increase and decrease by about 10% when woodland converts to the cultivated land. Through this study, we recognize that land surface water and heat exchanges are affected greatly by the future climate change as well as land cover change.

The Earth climate is a complex, interactive system, determined by a number of complex connected physical, chemical and biological processes occurring in the atmosphere, land and ocean. The terrestrial biosphere plays many pivotal roles in the coupled Earth system providing both positive and negative feedbacks to climate change (Treut et al., 2007). Terrestrial vegetation via photosynthesis converts solar energy into carbon that would otherwise reside in the atmosphere as a greenhouse gas, thereby regulating climate. Vegetation also transfers water between belowground reservoirs and the atmosphere to maintain precipitation and surface water flows.The terrestrial carbon (C) cycle is closely linked to hydrological and nutrient controls on vegetation (Betts et al., 2000; Cox et al., 2000). Understanding the coupled terrestrial C and water cycle is required to gain a comprehensive understanding of the role that terrestrial ecosystems play in the global climate change. Much progress has been made in gaining insight of the coupling processes between C and water cycles across a range of time and spatial scales (Pielke Sr, 2001; Friedlingstein et al., 2003; Seneviratne et al., 2006; Betts et al, 2007a,b; Baldocchi, 2008). Since the early 1990s, there has been an increased interest in monitoring of the CO2, water vapor and energy exchange between the atmosphere and terrestrial ecosystems by a variety of methods, such as the eddy-covariance techniques (EC), satellite and other airborne remote sensing, CO2 concentration and isotope measurements. Meanwhile, there are various kinds of models have been developed to better understanding of these processes and for largescale C and water budgeting.

The potential use of TerraSAR-X and Radarsat-2 data for soil moisture retrieval over bare agricultural areas was investigated using both empirical and semi-empirical approaches. For the empirical approach, the Support Vector Regression (SVR) model was used with two cases: (1) using only one C-band or X-band image; and (2) using a pair of C-band and X-band images jointly. For the semi-empirical approach, the modified Dubois model based on C-band and X-band SAR data was developed to estimate soil moisture content. The experiments were implemented over two bare agricultural areas, and in-situ measurements were carried out to assess the methods. The results showed that the TerraSAR-X and Radarsat-2 are suitable remote sensing tools for the estimation of surface soil moisture, with an accuracy of about 3 vol % (root mean square error, RMSE) over bare agricultural areas. Compared with the results obtained by Radarsat-2 data, TerraSAR-X data gives a slight improvement in estimating soil moisture. The accuracy of the soil moisture estimation was improved further when the two bands SAR data were used (RMSE of about 2.2 vol %) instead of only one. Moreover, the modified Dubois model showed comparable accuracy to the empirical model independent of the surface roughness.

BitTorrent (BT) is an extremely successful peer-to-peer (P2P) application providing efficient file sharing over the Internet. The ever-increasing traffic among the peers has also put unprecedented pressure to Internet Service Providers (ISPs). P2P locality has therefore been widely suggested, which explores finding local resources to optimize the cross-ISP/AS traffic. However, the ISPs would fail to reduce the cross-AS traffic if they could not control the neighbor selection of their P2P subscribers. In this paper, we examine the applicability of P2P locality through real-world measurement. We find that the widely deployed load balance trackers will greatly reduce the efficiency of traffic locality. Due to peers' random tracker selection, there is no grantee that the peers will always choose the modified trackers as we expected. To make the matter worse, some Internet trackers involve serious copyright violation and may hardly cooperate with the ISPs. Fortunately, our investigation of the AS-Tracker relationship indicates that if we carefully select the trackers during the locality deployment, most peers can still be controlled by the ISPs with relatively high probability. A machine learning based model is then proposed to quantify the similarity of trackers' peer distribution. Our trace-based simulation shows that, the similarity value can provide useful hints to enhance P2P locality. In particular, the peers are more likely to be optimized with higher probability. Moreover, the learning of tracker similarity does not require the global knowledge of Internet trackers, which can hardly be obtained by the individual ISPs.

[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.

International audience; Micrometeorological measurements of nighttime ecosystem respiration can be systematically biased when stable atmospheric conditions lead to drainage flows associated with decoupling of air flow above and within plant canopies. The associated horizontal and vertical advective fluxes cannot be measured using instrumentation on the single towers typically used at micrometeorological sites. A common approach to minimize bias is to use a threshold in friction velocity, u*, to exclude periods when advection is assumed to be important, but this is problematic in situations when in-canopy flows are decoupled from the flow above. Using data from 25 flux stations in a wide variety of forest ecosystems globally, we examine the generality of a novel approach to estimating nocturnal respiration developed by van Gorsel et al. (van Gorsel, E., Leuning, R., Cleugh, H.A., Keith, H., Suni, T., 2007. Nocturnal carbon efflux: reconciliation of eddy covariance and chamber measurements using an alternative to the u*-threshold filtering technique. Tellus 59B, 397–403, Tellus, 59B, 307-403). The approach is based on the assumption that advection is small relative to the vertical turbulent flux (FC) and change in storage (FS) of CO2 in the few hours after sundown. The sum of FC and FS reach a maximum during this period which is used to derive a temperature response function for ecosystem respiration. Measured hourly soil temperatures are then used with this function to estimate respiration RRmax. The new approach yielded excellent agreement with (1) independent measurements using respiration chambers, (2) with estimates using ecosystem lightresponse curves of Fc + Fs extrapolated to zero light, RLRC, and (3) with a detailed process-based forest ecosystem model, Rcast. At most sites respiration rates estimated using the u*-filter, Rust, were smaller than RRmax and RLRC. Agreement of our approach with independent measurements indicates that RRmax provides an excellent estimate of nighttime ecosystem respiration

[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.

[1] Gross ecosystem production (GEP) can be estimated at the global scale and in a spatially continuous mode using models driven by remote sensing. Multiple studies have demonstrated the capability of high resolution optical remote sensing to accurately measure GEP at the leaf and stand level, but upscaling this relationship using satellite data remains challenging. Canopy structure is one of the complicating factors as it not only alters the strength of a measured signal depending on integrated leaf-angle-distribution and sun-observer geometry, but also drives the photosynthetic output and light-use-efficiency (ɛ) of individual leaves. This study introduces a new approach for upscaling multiangular canopy level reflectance measurements to satellite scales which takes account of canopy structure effects by using Light Detection and Ranging (LiDAR). A tower-based spectro-radiometer was used to observe canopy reflectances over an annual period under different look and solar angles. This information was then used to extract sunlit and shaded spectral end-members corresponding to minimum and maximum values of canopy-ɛ over 8-d intervals using a bidirectional reflectance distribution model. Using three-dimensional information of the canopy structure obtained from LiDAR, the canopy light regime and leaf area was modeled over a 12 km2 area and was combined with spectral end-members to derive high resolution maps of GEP. Comparison with eddy covariance data collected at the site shows that the spectrally driven model is able to accurately predict GEP (r2 between 0.75 and 0.91, p < 0.05).

regional GPP from mixing ratio measurements, we also compared the estimates of regional GPP with estimates made using eddy covariance (EC) flux measurements, although their respective source areas are different. They had similar seasonal patterns, but the regional estimates were consistently smaller than the local EC flux derived GPP throughout the growing season in 2003. These estimates of annual regional GPP were 649–664 g C m � 2 for 2003 while the EC-derived annual GPP was 819–847 g C m � 2 . The annual difference was about 20–25%. The EC flux footprint of the tower was relatively homogeneous old black spruce while the concentration footprint, which was a few orders of magnitude larger than the flux footprint, covered boreal evergreen and deciduous broadleaf forests, grassland, cropland, and lakes. Nonforested land occupied about 10–50% of the concentration footprint depending on wind direction and speed and was less productive than the black spruce forest. The discrepancies between regional and local GPP estimates reflected the differences in underlying land surfaces represented by the different footprint areas.

[1] The temporal variation of the CO 2 mixing ratio in the atmosphere at a given height results from several processes, including photosynthesis and respiration of the underlying ecosystems, the vertical mixing of the atmosphere near the surface and in the planetary boundary layer (PBL), and entrainment of the air above the PBL. Theoretically, if all atmospheric processes are modeled accurately, we can estimate the magnitude of ecosystem photosynthesis and respiration from the variations in the measured CO 2 mixing ratio. Through analyzing the CO 2 concentration measured at several heights (30 m, 122 m, and 396 m) on the Wisconsin tall tower, we demonstrate that it is possible to derive the daily carbon flux resulting from CO 2 uptake from hourly CO 2 mixing ratio data. At 30 m, the concentration-derived daily gross primary productivity (GPP) is well correlated with measured daily GPP derived from flux measurements (r 2 = 0.70), but the former was 20% larger than the latter. The correlation increased considerably for 10-day averages (r2 = 0.87). As the variations at lower heights have larger diurnal CO 2 amplitudes, the concentration-derived GPP is more accurate at lower heights. The footprint distance of CO 2 concentration during the daytime under the influence of the mixed layer is estimated to be of the order of 10 km, or a footprint area of 10 3 -10 4 km 2 , which is much larger than that of CO 2 fluxes measured using eddy covariance methods (typically 1 km 2 ). The difference in these footprint areas may partly explain the differences between these two flux estimates at the Wisconsin tower. These differences also signify the importance of retrieving flux information from the mixing ratio as it provides a means to upscale from local sites to a region.

[1] Ecosystem CO2 exchange with the atmosphere and the planetary boundary layer (PBL) dynamics are correlated diurnally and seasonally. The strength of this kind of covariation is quantified as the rectifier effect, and it affects the vertical gradient of CO2 and thus the global CO2 distribution pattern. An 11-year (1990–1996, 1999–2002), continuous CO2 record from Fraserdale, Ontario (49°52′29.9″N, 81°34′12.3″W), along with a coupled vertical diffusion scheme (VDS) and ecosystem model named Boreal Ecosystem Productivity Simulator (BEPS), are used to investigate the interannual variability of the rectifier effect over a boreal forest region. The coupled model performed well (r2 = 0.70 and 0.87, at 40 m at hourly and daily time steps, respectively) in simulating CO2 vertical diffusion processes. The simulated annual atmospheric rectifier effect varies from 3.99 to 5.52 ppm, while the diurnal rectifying effect accounted for about a quarter of the annual total (22.8∼28.9%).The atmospheric rectification of CO2 is not simply influenced by terrestrial source and sink strengths, but by seasonal and diurnal variations in the land CO2 flux and their interaction with PBL dynamics. Air temperature and moisture are found to be the dominant climatic factors controlling the rectifier effect. The annual rectifier effect is highly correlated with annual mean temperature (r2 = 0.84), while annual mean air relative humidity can explain 51% of the interannual variation in rectification. Seasonal rectifier effect is also found to be more sensitive to climate variability than diurnal rectifier effect.

[1] The magnitude and spatial distribution of the carbon sink in the extratropical Northern Hemisphere remain uncertain in spite of much progress made in recent decades. Vertical CO2 diffusion in the planetary boundary layer (PBL) is an integral part of atmospheric CO2 transport and is important in understanding the global CO2 distribution pattern, in particular, the rectifier effect on the distribution [Keeling et al., 1989; Denning et al., 1995]. Attempts to constrain carbon fluxes using surface measurements and inversion models are limited by large uncertainties in this effect governed by different processes. In this study, we developed a Vertical Diffusion Scheme (VDS) to investigate the vertical CO2 transport in the PBL and to evaluate CO2 vertical rectification. The VDS was driven by the net ecosystem carbon flux and the surface sensible heat flux, simulated using the Boreal Ecosystem Productivity Simulator (BEPS) and a land surface scheme. The VDS model was validated against half-hourly CO2 concentration measurements at 20 m and 40 m heights above a boreal forest, at Fraserdale (49°52′29.9″N, 81°34′12.3″W), Ontario, Canada. The amplitude and phase of the diurnal/seasonal cycles of simulated CO2 concentration during the growing season agreed closely with the measurements (linear correlation coefficient (R) equals 0.81). Simulated vertical and temporal distribution patterns of CO2 concentration were comparable to those measured at the North Carolina tower. The rectifier effect, in terms of an annual-mean vertical gradient of CO2 concentration in the atmosphere that decreases from the surface to the top of PBL, was found at Fraserdale to be about 3.56 ppmv. Positive covariance between the seasonal cycles of plant growth and PBL vertical diffusion was responsible for about 75% of the effect, and the rest was caused by covariance between their diurnal cycles. The rectifier effect exhibited strong seasonal variations, and the contribution from the diurnal cycle was mostly confined to the surface layer (less than 300 m).

Stable isotopes of CO 2 contain unique information on the biological and physical processes that exchange CO 2 between terrestrial ecosystems and the atmosphere. Ecosystem exchange of carbon isotopes with the atmosphere is correlated diurnally and seasonally with the planetary boundary layer (PBL) dynamics. The strength of this kind of covariation affects the vertical gradient of δ 13 C and thus the global δ 13 C distribution pattern. We need to understand the various processes involved in transport/diffusion of carbon isotope ratio in the PBL and between the PBL and the biosphere and the troposphere. In this study, we employ a one-dimensional vertical diffusion/transport atmospheric model (VDS), coupled to an ecosystem isotope model (BEPS-EASS) to simulate dynamics of 13 CO 2 in the PBL over a boreal forest region in the vicinity of the Fraserdale (FRD) tower (49°52′29.9″N, 81°34′12.3″W) in northern Ontario, Canada. The data from intensive campaigns during the growing season in 1999 at this site are used for model validation in the surface layer. The model performance, overall, is satisfactory in simulating the measured data over the whole course of the growing season. We examine the interaction of the biosphere and the atmosphere through the PBL with respect to δ 13 C on diurnal and seasonal scales. The simulated annual mean vertical gradient of δ 13 C in the PBL in the vicinity of the FRD tower was about 0.25‰ in 1999. The δ 13 C vertical gradient exhibited strong diurnal (29%) and seasonal (71%) variations that do not exactly mimic those of CO 2 . Most of the vertical gradient (96.5%±) resulted from covariation between ecosystem exchange of carbon isotopes and the PBL dynamics, while the rest (3.5%±) was contributed by isotopic disequilibrium between respiration and photosynthesis. This disequilibrium effect on δ 13 C of CO 2 dynamics in PBL, moreover, was confined to the near surface layers (less than 350 m). DOI: 10.1111/j.1600-0889.2006.00213.x