Total Gross Primary Production Research Articles

Modeling the impacts of urbanization on watershed-scale gross primary productivity and tradeoffs with water yield across the conterminous United States

The objective of this study was to examine the impacts of urbanization on gross primary productivity (GPP) and the interactions between carbon and water fluxes, including precipitation, evapotranspiration (ET), and water yield (Q). A water-centric ecosystem model, Water Supply Stress Index model (WaSSI) that operates at the 12-digit (81,900 watersheds) Hydrologic Unit Code (HUC) scale for the conterminous United States (CONUS) during 2000–2010, 2000–2050, and 2000–2100 was used. Linear regression and causal-based models were then applied to identify key factors controlling urbanization impact on GPP. Simulations of GPP patterns compared favorably with a global, 0.05-degree product of solar-induced chlorophyll fluorescence (SIF). We found that total CONUS GPP declined from 8.68PgCyr−1 in 2000, to 8.54PgCyr−1 in 2010, to 8.36PgCyr−1 in 2050, and to 8.13PgCyr−1 in 2100. Total GPP decreased from 6.81PgCyr−1 to 6.26PgCyr−1 for those watersheds affected by urbanization (~55,000). Total CONUS Q increased from 2.03 × 106 million m3 yr−1 in 2000, to 2.04 × 106 million m3 yr−1 in 2010, to 2.06 × 106 million m3 yr−1 in 2050, and 2.09 × 106 million m3 yr−1 in 2100, while Q increased from 1.68 × 106 million m3 yr−1 to 1.74 × 106 million m3 yr−1 for urbanized watersheds alone (~55,000). Although total CONUS ΔGPP was less than 0.55PgCyr−1, or <8%, large changes (ΔGPP >300 g C m−2 yr−1) were found in 245, 1984, and 5655 of the 81,900 watersheds by 2010, 2050 and 2100, respectively. Overall, the impacts of urbanization on GPP in the CONUS were influenced by background climate, previous land cover characteristics, and the magnitudes of land use change. Effective integrated watershed management that attempts to minimize the negative ecological and environmental impacts of urbanization must consider regional hydrologic differences and fit local climatic and watershed conditions.

Impact of aerosols on terrestrial gross primary productivity in North China using an improved boreal ecosystem productivity simulator with satellite-based aerosol optical depth

ABSTRACTAtmospheric aerosols can alter the direct and diffuse components of global solar radiation, which further influences terrestrial gross primary productivity (GPP) via photosynthesis. To investigate the impact of aerosols on GPP, GPP is modeled using the Boreal Ecosystem Productivity Simulator (BEPS) under two aerosol scenarios (S1& S2) over cropland and grassland ecosystems in the highly polluted North China. In S1, the aerosol-effect is not considered and an original empirical method is used when estimating direct and diffuse solar radiation in BEPS. In S2, BEPS is improved by a new empirical method which incorporates the impact of aerosols using the remote sensing-based aerosol optical depth (AOD). Results suggest that aerosols can reduce GPP of the sunlit leaves by decreasing direct solar radiation, but increase GPP of the shaded leaves by increasing diffuse solar radiation. The impact of aerosols on GPP is more significant over the cropland ecosystem (p < 0.05) with a more complex canopy structure during the peak period of the growing season. Furthermore, an AOD value of 0.3–0.6 with a diffuse fraction (the fraction of diffuse solar radiation in global solar radiation) around 30-40% can largely increase total GPP over the cropland ecosystem. The study improves the accuracy of GPP modeling using BEPS by highlighting the aerosol-effect on GPP via solar radiation over highly polluted regions.Abbreviations: gross primary productivity (GPP); aerosol optical depth (AOD); boreal ecosystem productivity simulator (BEPS)

Seasonality of leaf area index and photosynthetic capacity for better estimation of carbon and water fluxes in evergreen conifer forests

Leaf area index (LAI), defined as one half the total leaf area per unit ground area, and Vcmax, representing the maximal carboxylation rate of leaves, are two most significant parameters used in most Terrestrial Biosphere Models (TBMs). The ability of TBMs to simulate gross primary productivity (GPP) and evapotranspiration (ET) for evergreen needle-leave forests (ENF) can be significantly hampered by uncertainties in LAI and Vcmax. Remotely sensed (RS) LAI for ENF is generally underestimated in winter, early spring and late autumn. Although constant Vcmax throughout the growing season is often used in TBMs for GPP and ET modeling, it could vary significantly under leaf aging and stressed conditions. There were recent studies that apply seasonal leaf chlorophyll constraints on GPP modeling for croplands and deciduous forests, but little attention is given to the influence of the seasonality of either LAI or Vcmax on GPP or ET estimations for the ENF biome. In this study, we pay special attention to this biome, with the purpose of investigating if the representations of seasonal LAI and Vmax variations are essential in TBMs. To serve this purpose, the University of Toronto LAI product Version 2 was corrected for its seasonal variation using leaf lifespan and in-situ measurements at eight ENF sites in Canada. Seasonal Vcmax variation was derived from the MERIS Terrestrial Chlorophyll Index (MTCI) through downscaling it to the leaf level using a scheme with a general vertical nitrogen distribution within the canopy. Leaf chlorophyll content (LCC) is thus derived from MTCI and converted to Vcmax using empirical equations. Four model cases with and without considerations of the seasonal LAI and Vcmax variations were tested and compared. Validation against eddy covariance measurements indicates that the case with both LAI and Vcmax variations produced the highest R2, lowest root mean square error (RMSE) and lowest mean absolute error (MAE) for both GPP and ET simulations, and thus outperforms all other cases without considering the variations or with consideration of one of the variations only. In this best case, the simulated daily GPP yields R2 of 0.91, RMSE of 0.91 g C m−2 and MAE of 0.65 g C m−2, while the simulated daily ET yields R2 of 0.8, RMSE of 0.52 mm and MAE of 0.34 mm. Most improvements were found in spring and autumn. Not only the correlations between the seasonal trajectories of model simulation and observation were improved, but also the annual total GPP and ET were more accurately estimated. The smallest mean absolute relative bias to eddy covariance measurements is 9% for GPP and 15% for ET, both were found in the best case. Moreover, improvements in GPP were more pronounced than in ET. Our results highlight the significance of considering both seasonal structural and physiological characteristics of leaves in TBMs. Considering the important role that evergreen coniferous forests play in global terrestrial ecosystems, global simulations of GPP and ET in space and time can benefit from the proper representation of seasonal variations in canopy structure and leaf physiology as represented by LAI and Vcmax, respectively.

The 2012 Flash Drought Threatened US Midwest Agroecosystems

In the summer of 2012, the US Midwest, the most productive agricultural region in the world, experienced the most intense and widespread drought on record for the past hundred years. The 2012 drought, characterized as ‘flash drought’, developed in May with a rapid intensification afterwards, and peaked in mid-July. ~76% of crop region and 60% of grassland and pasture regions have been under moderate to severe dry conditions. This study used multiple lines of evidences, i.e., in-situ AmeriFlux measurements, spatial satellite observations, and scaled ecosystem modeling, to provide independent and complementary analysis on the impact of 2012 flash drought on the US Midwest vegetation greenness and photosynthesis carbon uptake. Three datasets consistently showed that 1) phenological activities of all biomes advanced 1–2 weeks earlier in 2012 compared to the other years of 2010-2014; 2) the drought had a more severe impact on agroecosystems (crop and grassland) than on forests; 3) the growth of crop and grassland was suppressed from June with significant reduction of vegetation index, sun-induced fluorescence (SIF) and gross primary production (GPP), and did not recover until the end of growing season. The modeling results showed that regional total GPP in 2012 was the lowest (1.76 Pg C/yr) during 2010–2014, and decreased by 63 Tg C compared with the other-year mean. Agroecosystems, accounting for 84% of regional GPP assimilation, were the most impacted by 2012 drought with total GPP reduction of 9%, 7%, 6%, and 29% for maize, soybean, cropland, and grassland, respectively. The frequency and severity of droughts have been predicted to increase in future. The results imply the importance to investigate the influences of flash droughts on vegetation productivity and terrestrial carbon cycling.

Modeling phenological controls on carbon dynamics in dryland sagebrush ecosystems

Dryland ecosystems play an important role in determining how precipitation anomalies affect terrestrial carbon fluxes at regional to global scales. Thus, to understand how climate change may affect the global carbon cycle, we must also be able to understand and model its effects on dryland vegetation. Dynamic Global Vegetation Models (DGVMs) are an important tool for modeling ecosystem dynamics, but they often struggle to reproduce seasonal patterns of plant productivity. Because the phenological niche of many plant species is linked to both total productivity and competitive interactions with other plants, errors in how process-based models represent phenology hinder our ability to predict climate change impacts. This may be particularly problematic in dryland ecosystems where many species have developed a complex phenology in response to seasonal variability in both moisture and temperature. Here, we examine how uncertainty in key parameters as well as the structure of existing phenology routines affect the ability of a DGVM to match seasonal patterns of leaf area index (LAI) and gross primary productivity (GPP) across a temperature and precipitation gradient. First, we optimized model parameters using a combination of site-level eddy covariance data and remotely-sensed LAI data. Second, we modified the model to include a semi-deciduous phenology type and added flexibility to the representation of grass phenology. While optimizing parameters reduced model bias, the largest gains in model performance were associated with the development of our new representation of phenology. This modified model was able to better capture seasonal patterns of both leaf area index (R2 = 0.75) and gross primary productivity (R2 = 0.84), though its ability to estimate total annual GPP depended on using eddy covariance data for optimization. The new model also resulted in a more realistic outcome of modeled competition between grass and shrubs. These findings demonstrate the importance of improving how DGVMs represent phenology in order to accurately forecast climate change impacts in dryland ecosystems.

An in situ study of production from diel oxygen modelling, oxygen exchange, and electron transport rate in the kelp Ecklonia radiata

Macroalgal forests provide the foundation for most shallow reef ecosystems in temperate environments; hence tools for accurately measuring primary productivity are integral for ecosystem management. This study compares estimates of production/potential production in an Ecklonia radiata kelp forest in Tasmania, Australia, using diel oxygen gross primary production (GPP) models, benthic exchange chambers, and electron transport rate in photosystem II measured using PAM fluorometry. Two approaches to modelling GPP show good fit with environmental dissolved oxygen (DO), with gross oxygen production of the kelp bed ranging between ~0-20 for one model and ~0-8 µmol O2 m-2 s-1 for the other, with total daily GPP (±SE) of 464 ± 28 and 347 ± 7 mmol O2 m-2, respectively. The oxygen production rate of E. radiata in benthic chambers ranged between 0 and 9.6 µmol O2 m-2 s-1, with total daily production as 204 ± 13 mmol O2 m-2, half that estimated from modelling DO. The peak value for maximum relative electron transport rate was 49 µmol e- m-2 s-1 at PAR of 208 µmol m-2 s-1. Oxygen evolution from benthic chambers and electron transport rates from PAM fluorometry were well correlated; however, the latter may overestimate oxygen production. Water column DO can measure GPP of the benthic communities; however, additional measurements/more sophisticated models may be necessary. Benthic exchange chambers and PAM fluorometry can potentially estimate the contribution of E. radiata to total daily production provided that the measurements can be calibrated with other methods to obtain actual productivity. Additionally, upscaling requires reliable biomass estimates.

Quantifying Climate Change and Ecological Responses within the Yangtze River Basin, China

The interactions between climate change and vegetation have a significant impact on the dynamics of the global carbon cycle. Based on the observed meteorological data from 1961 to 2013 and the temperature and precipitation data simulated by various climate models (simulations phase 5 of the Climate Model Intercomparison Project dataset), this paper analyzes the temperature and precipitation changes of the Yangtze River Basin (YRB) and finds that they are a similar trend, that is, the temperature presents a significant upward trend (R2 = 0.49, p &lt; 0.01), and the variation trend of precipitation is not significant (R2 = 0.01). Specifically, based on observed meteorological data, the annual mean temperature increased significantly and the area of increasing temperature accounted for 99.94% of the total region (p &lt; 0.05); however, there was no significant change in annual precipitation. Ecological indicators (normalized difference vegetation index (NDVI); enhanced vegetation index (EVI); leaf area index (LAI); gross primary production (GPP); and net primary production (NPP)) of the YRB showed an increasing trend, and annual NDVI, annual EVI, LAI, annual total GPP and annual total NPP increased at respective rates of 0.002 yr−1, 0.001 yr−1, 0.07 m2m−2decade−1, 9 TgCyr−1yr−1, and 6 TgCyr−1yr−1, respectively. Correlation analysis between temperature/precipitation and NDVI/EVI/LAI/GPP/NPP was used to determine the relationships between climatic parameters and ecological indicators. Specifically, the temperature is significantly positively correlated with annual NDVI (R2 = 0.37, p &lt; 0.05), with annual mean LAI (R2 = 0.35, p &lt; 0.05) and with annual GPP (R2 = 0.37, p &lt; 0.05). In addition, there is a moderate positive correlation between mean EVI and mean growing season air temperature (R2 = 0.24); annual mean air temperature is a moderate positive correlation with annual NPP (R2 = 0.28). Our findings confirm that temperature is more closely related to ecological factors than precipitation over the YRB in these decades.

Mapping and comparing ecosystem service indicators of global climate regulation in Schleswig-Holstein, Northern Germany

Estimating and mapping Ecosystem Services (ESS) is a primary basis for reasonable ecosystem managing policies. Assessing ESS and optimising the accuracy of ESS assessment is relevant to identify suitable indicators. This study aims to gain a better understanding of global climate regulation service assessments resulting from the application of several indicators that have been derived based on Co-Ordination of INformation on the Environment (CORINE) land cover classes. Therefore, 17 CORINE land cover classes were used to evaluate their effects on the distributions of the annual total Gross Primary Production (GPP), the annual total Net Primary Production (NPP), Soil Organic Carbon (SOC) and Carbon Stocks (CS) in the German federal state Schleswig-Holstein. In addition to the spatial distributions, correlations of distinct quantitative indicators (annual total GPP, annual total NPP, SOC and CS) and a qualitative indicator of Global Climate Regulation (GCR) derived from the ecosystem service matrix method were analysed. We found that qualitative and quantitative indicators of the global climate regulation service had significant correlations based on the comparison analysis of all indicators. The differences in mapping the service with the five indicators resulted from different strategies of the reclassified land covers. In addition, the distinct areas among the land cover classes contributed to the differences in global climate regulation mapping. The interrelations among the annual total GPP, the annual total NPP and statistical data on total harvest of different agricultural products also correlated significantly. Based on the results, GPP, NPP, SOC, CS and GCR are available indicators of global climate regulation service in Schleswig-Holstein. Nevertheless, we especially recommend CS as the indicator owning to its high accuracy in assessments. The indicators and methodology in our study can also be applied to other researches targeted with evaluating global climate regulation service.

Vulnerability and resilience of the carbon exchange of a subarctic peatland to an extreme winter event

Extreme winter events that damage vegetation are considered an important climatic cause of arctic browning—a reversal of the greening trend of the region—and possibly reduce the carbon uptake of northern ecosystems. Confirmation of a reduction in CO2 uptake due to winter damage, however, remains elusive due to a lack of flux measurements from affected ecosystems. In this study, we report eddy covariance fluxes of CO2 from a peatland in northern Norway and show that vegetation CO2 uptake was delayed and reduced in the summer of 2014 following an extreme winter event earlier that year. Strong frost in the absence of a protective snow cover—its combined intensity unprecedented in the local climate record—caused severe dieback of the dwarf shrub species Calluna vulgaris and Empetrum nigrum. Similar vegetation damage was reported at the time along ~1000 km of coastal Norway, showing the widespread impact of this event. Our results indicate that gross primary production (GPP) exhibited a delayed response to temperature following snowmelt. From snowmelt up to the peak of summer, this reduced carbon uptake by 14 (0–24) g C m−2 (~12% of GPP in that period)—similar to the effect of interannual variations in summer weather. Concurrently, remotely-sensed NDVI dropped to the lowest level in more than a decade. However, bulk photosynthesis was eventually stimulated by the warm and sunny summer, raising total GPP. Species other than the vulnerable shrubs were probably resilient to the extreme winter event. The warm summer also increased ecosystem respiration, which limited net carbon uptake. This study shows that damage from a single extreme winter event can have an ecosystem-wide impact on CO2 uptake, and highlights the importance of including winter-induced shrub damage in terrestrial ecosystem models to accurately predict trends in vegetation productivity and carbon sequestration in the Arctic and sub-Arctic.

Changes in Gross Primary Production (GPP) over the Past Two Decades Due to Land Use Conversion in a Tourism City

Understanding the changes in gross primary production (GPP), which is the total carbon fixation by terrestrial ecosystems through vegetation photosynthesis, due to land use conversion in a tourism city is important for carbon cycle studies. Satellite data from Landsat 5, Landsat 7 and Landsat 8 and meteorological data are used to calculate annual GPP for 1995, 2003 and 2014, respectively, using the vegetation production model (VPM) in the tourism city Denpasar, Bali, Indonesia. Five land use types generated from topographic maps in three different years over the past two decades are used to quantify the impacts of land use changes on GPP estimation values. Analysis was performed for two periods to determine changes in land use and GPP value as well as their speed. The results demonstrated that urban land development, namely, the increase of settlement areas due to tourism activity, had overall negative effects on terrestrial GPP. The total GPP of the whole area decreased by 7793.96 tC year−1 (12.65%) during the study period. The decline is due to the conversion of agriculture and grassland area into settlements, which caused the city to lose half of its ability to uptake carbon through vegetation. However, although forest area is declining, forest maintenance and restoration by making them protection areas has been helpful in preventing a drastic decline in GPP value over the past two decades. This study provides information that is useful for carbon resource management, tourism, policy making and scholars concerned about carbon reduction in a tourism city.

Satellite-derived LAI products exhibit large discrepancies and can lead to substantial uncertainty in simulated carbon and water fluxes

Understanding the terrestrial carbon and water cycles is crucial for mitigation and adaptation for climate change. Leaf area index (LAI) is a key biophysical parameter in process-based ecosystem models for simulating gross primary productivity (GPP) and evapotranspiration (ET). The uncertainty in satellite-derived LAI products and their effects on the simulation of carbon and water fluxes at regional scales remain unclear. We evaluated three satellite-derived LAI products - MODIS (MCD15), GLASS, and Four-Scale Geometric Optical Model based LAI (FSGOM) over the period 2003–2012 using fine-resolution (30m) LAI data and field LAI measurements. GLASS had higher accuracy than FSGOM and MCD15 for forests, while FSGOM had higher accuracy than MCD15 and GLASS for grasslands. The three LAI products differed in magnitude, spatial patterns, and trends in LAI. We then examined the resulting discrepancies in simulated annual GPP and ET over China using a process-based, diagnostic terrestrial biosphere model. Mean annual total GPP for China's terrestrial ecosystems based on GLASS (6.32PgCyr−1) and FSGOM (6.15PgCyr−1) was 22.5% and 19.2% higher than that based on MCD15 (5.16PgCyr−1), respectively. Annual GPP based on GLASS and MCD15 increased over larger fractions of China's vegetated area (15.9% and 17.3%, respectively) than that based on FSGOM (12.6%). National annual ET based on GLASS (379.9mmyr−1) and FSGOM (374.4mmyr−1) was 7.9% and 6.3% higher than that based on MCD15 (352.1mmyr−1), respectively. Simulated ET increased in larger fractions of the vegetated area for GLASS (5.7%) and MCD15 (5.8%) than for FSGOM (3.9%). Our study shows that there were large discrepancies in LAI among satellite-derived LAI products and the biases of the LAI products could lead to substantial uncertainties in simulated carbon and water fluxes.

Regional contribution to variability and trends of global gross primary productivity

Terrestrial gross primary productivity (GPP) is the largest component of the global carbon cycle and a key process for understanding land ecosystems dynamics. In this study, we used GPP estimates from a combination of eight global biome models participating in the Inter-Sectoral Impact-Model Intercomparison Project phase 2a (ISIMIP2a), the Moderate Resolution Spectroradiometer (MODIS) GPP product, and a data-driven product (Model Tree Ensemble, MTE) to study the spatiotemporal variability of GPP at the regional and global levels. We found the 2000–2010 total global GPP estimated from the model ensemble to be 117 ± 13 Pg C yr−1 (mean ± 1 standard deviation), which was higher than MODIS (112 Pg C yr−1), and close to the MTE (120 Pg C yr−1). The spatial patterns of MODIS, MTE and ISIMIP2a GPP generally agree well, but their temporal trends are different, and the seasonality and inter-annual variability of GPP at the regional and global levels are not completely consistent. For the model ensemble, Tropical Latin America contributes the most to global GPP, Asian regions contribute the most to the global GPP trend, the Northern Hemisphere regions dominate the global GPP seasonal variations, and Oceania is likely the largest contributor to inter-annual variability of global GPP. However, we observed large uncertainties across the eight ISIMIP2a models, which are probably due to the differences in the formulation of underlying photosynthetic processes. The results of this study are useful in understanding the contributions of different regions to global GPP and its spatiotemporal variability, how the model- and observational-based GPP estimates differ from each other in time and space, and the relative strength of the eight models. Our results also highlight the models’ ability to capture the seasonality of GPP that are essential for understanding the inter-annual and seasonal variability of GPP as a major component of the carbon cycle.

Seasonal variability of evapotranspiration and carbon exchanges over a biomass sorghum field in the Southern U.S. Great Plains

The eddy covariance method was used to investigate carbon fluxes and evapotranspiration (ET) from a high biomass forage sorghum (Sorghum bicolor L.) field in the Southern U.S. Great Plains for three growing seasons (2013–2015). Above normal precipitation and narrow row spacing (50 cm) led to higher biomass production (25 Mg ha−1) and leaf area index (LAI = 7.2) development in 2014. This also resulted in higher carbon uptake or net ecosystem production (NEP) and ET during that year. Early and late season precipitation enhanced ecosystem respiration (Reco) resulting in lower NEP in 2015. Shorter growing season (119 days) also contributed to lower cumulative NEP in 2015. Estimated gross primary production (GPP) in 2014 (1780 g m−2) was 10% higher than the GPP in 2013 (1591 g m−2) and 24% higher than the GPP in 2015 (1353 g m−2). During all growing seasons, the site was a source of carbon (negative NEP) at the beginning and transitioned to a sink (positive NEP) later in the season. Biomass-GPP relationship indicated that approximately 65% of total GPP was allocated to above ground biomass (AGB). Average monthly ecosystem WUE (expressed as gross carbon gain per unit of ET) ranged from 1.7 g mm−1 to 4.2 g mm−1. Results from our study indicate that weather conditions, growing season length and crop management are important factors in determining the magnitude of carbon uptake and release, and ET of this cellulosic biofuel feedstock crop in the Southern U.S. Great Plains.

Angular normalization of GOME‐2 Sun‐induced chlorophyll fluorescence observation as a better proxy of vegetation productivity

AbstractSun‐induced chlorophyll fluorescence (SIF) has been regarded as a promising proxy for gross primary productivity (GPP) over land. Considerable uncertainties in GPP estimation using remotely sensed SIF exist due to variations in the Sun‐satellite view observation geometry that could induce unwanted variations in SIF observation. In this study, we normalize the far‐red Global Ozone Monitoring Experiment‐2 SIF observations on sunny days to hot spot direction (SIFh) to represent sunlit leaves and compute a weighted sum of SIF (SIFt) from sunlit and shaded leaves to represent the canopy. We found that SIFh is better correlated with sunlit GPP simulated by a process‐based ecosystem model and SIFt is better correlated with the simulated total GPP than the original SIF observations. The coefficient of determination (R2) are increased by 0.04 ± 0.03, and 0.07 ± 0.04 on a global average using SIFh and SIFt, respectively. The most significant increases of the R2 (0.09 ± 0.04 for SIFt and 0.05 ± 0.03 for SIFh) appear in deciduous broadleaf forests.

Enhanced evapotranspiration was observed during extreme drought from Miscanthus, opposite of other crops

AbstractThe impact of extreme drought and heat stress that occurred in the Midwestern U.S. in 2012 on evapotranspiration (ET), net ecosystem productivity (NEP), and water‐use efficiency (WUE) of three perennial ecosystems (switchgrass, miscanthus, prairie) and a maize/soybean agroecosystem was studied as part of a long‐term experiment. Miscanthus had a slower initial response but an eventually drastic ET as drought intensified, which resulted in the largest water deficit among the crops. The substantially higher ET at peak drought was likely supplied by access to deep soil water, but suggests that stomatal conductance of miscanthus during the drought may respond differently than the other ecosystems, consistent with an anisohydric strategy. While there was a discrepancy in the water consumption of maize and switchgrass/prairie in the early time of drought, all these ecosystems followed a water‐saving strategy when drought intensified. The gross primary production (GPP) of miscanthus dropped, but was reversible, when temperature reached 40 °C and still provided the largest total GPP among the ecosystems. Increased ET for miscanthus during 2012 resulted a large decline in ecosystem WUE compared to what was observed in other years. The biophysical responses of miscanthus measured during an extreme, historic drought suggest that this species can maintain high productivity longer than other ecosystems during a drought at the expense of water use. While miscanthus maintained productivity during drought, recovery lagged associated with depleted soil moisture. The enhanced ET of miscanthus may intensify droughts through increase supply of deep soil moisture to the atmosphere.

Biophysical effects on the interannual variation in carbon dioxide exchange of an alpine meadow on the Tibetan Plateau

Abstract. Eddy covariance measurements from 2012 to 2015 were used to investigate the interannual variation in carbon dioxide exchange and its control over an alpine meadow on the south-east margin of the Tibetan Plateau. The annual net ecosystem exchange (NEE) in the 4 years from 2012 to 2015 was −114.2, −158.5, −159.9 and −212.6 g C m−2 yr−1, and generally decreased with the mean annual air temperature (MAT). An exception occurred in 2014, which had the highest MAT. This was attributed to higher ecosystem respiration (RE) and similar gross primary production (GPP) in 2014 because the GPP increased with the MAT, but became saturated due to the limit in photosynthetic capacity. In the spring (March to May) of 2012, low air temperature (Ta) and drought events delayed grass germination and reduced GPP. In the late wet season (September to October) of 2012 and 2013, the low Ta in September and its negative effects on vegetation growth caused earlier grass senescence and significantly lower GPP. This indicates that the seasonal pattern of Ta has a substantial effect on the annual total GPP, which is consistent with results obtained using the homogeneity-of-slopes (HOS) model. The model results showed that the climatic seasonal variation explained 48.6 % of the GPP variability, while the percentages explained by climatic interannual variation and the ecosystem functional change were 9.7 and 10.6 %, respectively.

Evaluating carbon fluxes of global forest ecosystems by using an individual tree-based model FORCCHN

The carbon budget of forest ecosystems, an important component of the terrestrial carbon cycle, needs to be accurately quantified and predicted by ecological models. As a preamble to apply the model to estimate global carbon uptake by forest ecosystems, we used the CO2 flux measurements from 37 forest eddy-covariance sites to examine the individual tree-based FORCCHN model's performance globally. In these initial tests, the FORCCHN model simulated gross primary production (GPP), ecosystem respiration (ER) and net ecosystem production (NEP) with correlations of 0.72, 0.70 and 0.53, respectively, across all forest biomes. The model underestimated GPP and slightly overestimated ER across most of the eddy-covariance sites. An underestimation of NEP arose primarily from the lower GPP estimates. Model performance was better in capturing both the temporal changes and magnitude of carbon fluxes in deciduous broadleaf forest than in evergreen broadleaf forest, and it performed less well for sites in Mediterranean climate. We then applied the model to estimate the carbon fluxes of forest ecosystems on global scale over 1982–2011. This application of FORCCHN gave a total GPP of 59.41±5.67 and an ER of 57.21±5.32PgCyr−1 for global forest ecosystems during 1982–2011. The forest ecosystems over this same period contributed a large carbon storage, with total NEP being 2.20±0.64PgCyr−1. These values are comparable to and reinforce estimates reported in other studies. This analysis highlights individual tree-based model FORCCHN could be used to evaluate carbon fluxes of forest ecosystems on global scale.

Consistency between sun-induced chlorophyll fluorescence and gross primary production of vegetation in North America

Accurate estimation of the gross primary production (GPP) of terrestrial ecosystems is vital for a better understanding of the spatial-temporal patterns of the global carbon cycle. In this study,we estimate GPP in North America (NA) using the satellite-based Vegetation Photosynthesis Model (VPM), MODIS (Moderate Resolution Imaging Spectrometer) images at 8-day temporal and 500 meter spatial resolutions, and NCEP-NARR (National Center for Environmental Prediction-North America Regional Reanalysis) climate data. The simulated GPP (GPP (sub VPM)) agrees well with the flux tower derived GPP (GPPEC) at 39 AmeriFlux sites (155 site-years). The GPP (sub VPM) in 2010 is spatially aggregated to 0.5 by 0.5-degree grid cells and then compared with sun-induced chlorophyll fluorescence (SIF) data from Global Ozone Monitoring Instrument 2 (GOME-2), which is directly related to vegetation photosynthesis. Spatial distribution and seasonal dynamics of GPP (sub VPM) and GOME-2 SIF show good consistency. At the biome scale, GPP (sub VPM) and SIF shows strong linear relationships (R (sup 2) is greater than 0.95) and small variations in regression slopes ((4.60-5.55 grams Carbon per square meter per day) divided by (milliwatts per square meter per nanometer per square radian)). The total annual GPP (sub VPM) in NA in 2010 is approximately 13.53 petagrams Carbon per year, which accounts for approximately 11.0 percent of the global terrestrial GPP and is within the range of annual GPP estimates from six other process-based and data-driven models (11.35-22.23 petagrams Carbon per year). Among the seven models, some models did not capture the spatial pattern of GOME-2 SIF data at annual scale, especially in Midwest cropland region. The results from this study demonstrate the reliable performance of VPM at the continental scale, and the potential of SIF data being used as a benchmark to compare with GPP models.

Seasonal Variations of Carbon Dioxide, Water Vapor and Energy Fluxes in Tropical Indian Mangroves

We present annual estimates of the net ecosystem exchange (NEE) of carbon dioxide (CO2) accumulated over one annual cycle (April 2012 to March 2013) in the world’s largest mangrove ecosystem, Sundarbans (India), using the eddy covariance method. An eddy covariance flux tower was established in April 2012 to study the seasonal variations of carbon dioxide fluxes due to soil and vegetation-atmosphere interactions. The half-hourly maximum of the net ecosystem exchange (NEE) varied from −6 µmol·m−2·s−1 during the summer (April to June 2012) to −10 µmol·m−2·s−1 during the winter (October to December 2012), whereas the half-hourly maximum of H2O flux varied from 5.5 to 2.5 mmol·m−2·s−1 during October 2013 and July 2013, respectively. During the study period, the study area was a carbon dioxide sink with an annual net ecosystem productivity (NEP = −NEE) of 249 ± 20 g·C m−2·year−1. The mean annual evapotranspiration (ET) was estimated to be 1.96 ± 0.33 mm·day−1. The gap-filled NEE was also partitioned into Gross Primary Productivity (GPP) and Ecosystem Respiration (Re). The total GPP and Re over the study area for the annual cycle were estimated to be1271 g C m−2·year−1 and 1022 g C m−2·year−1, respectively. The closure of the surface energy balance accounted for of about 78% of the available energy during the study period. Our findings suggest that the Sundarbans mangroves are currently a substantial carbon sink, indicating that the protection and management of these forests would lead as a strategy towards reduction in carbon dioxide emissions.

Estimation of gross primary production in China (1982–2010) with multiple ecosystem models

Terrestrial gross primary production (GPP) is a major flux affecting land–atmosphere CO2 exchange and is important for regulating atmospheric CO2 concentrations, thereby affecting climate change. Dynamic global vegetation models (DGVMs) are important tools for simulation of vegetation productivity and can be coupled with other components of Earth system models. This study simulated GPP of terrestrial ecosystems in China from 1982 to 2010 utilizing five state-of-the-art DGVMs, which considered increasing atmospheric CO2 concentrations and climate change. Our models consistently showed an ascending GPP gradient from northwest to southeast China. The annual total GPP in China estimated by the DGVMs (mean=7.97PgCyr−1; range=6.14–9.76PgCyr−1) were generally higher than estimations from previous studies. The greatest overestimation of GPP occurred in south China in warm, wet climates. All DGVMs and JU11 indicated that annual GPP in China increased from 1982 to 2010. There was a statistically significant correlation between simulated GPP and temperature in the Tibetan Plateau, which was supported by flux tower measurements. Additionally, there was a significant correlation between simulated GPP and precipitation in east China, though this should be interpreted cautiously. Further research is needed to improve simulations to better account for spatial and temporal variations in GPP at regional scales by improving representations of existing processes and incorporating currently unconsidered processes.