| 1. |
- Besnard, Simon, et al.
(author)
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Quantifying the effect of forest age in annual net forest carbon balance
- 2018
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In: Environmental Research Letters. - : IOP Publishing. - 1748-9326. ; 13:12
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Journal article (peer-reviewed)abstract
- Forests dominate carbon (C) exchanges between the terrestrial biosphere and the atmosphere on land. In the long term, the net carbon flux between forests and the atmosphere has been significantly impacted by changes in forest cover area and structure due to ecological disturbances and management activities. Current empirical approaches for estimating net ecosystem productivity (NEP) rarely consider forest age as a predictor, which represents variation in physiological processes that can respond differently to environmental drivers, and regrowth following disturbance. Here, we conduct an observational synthesis to empirically determine to what extent climate, soil properties, nitrogen deposition, forest age and management influence the spatial and interannual variability of forest NEP across 126 forest eddy-covariance flux sites worldwide. The empirical models explained up to 62% and 71% of spatio-temporal and across-site variability of annual NEP, respectively. An investigation of model structures revealed that forest age was a dominant factor of NEP spatio-temporal variability in both space and time at the global scale as compared to abiotic factors, such as nutrient availability, soil characteristics and climate. These findings emphasize the importance of forest age in quantifying spatio-temporal variation in NEP using empirical approaches.
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| 2. |
- Chang, Kuang Yu, et al.
(author)
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Substantial hysteresis in emergent temperature sensitivity of global wetland CH4 emissions
- 2021
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In: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 12:1, s. 2266-2266
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Journal article (peer-reviewed)abstract
- Wetland methane (CH4) emissions ([Formula: see text]) are important in global carbon budgets and climate change assessments. Currently, [Formula: see text] projections rely on prescribed static temperature sensitivity that varies among biogeochemical models. Meta-analyses have proposed a consistent [Formula: see text] temperature dependence across spatial scales for use in models; however, site-level studies demonstrate that [Formula: see text] are often controlled by factors beyond temperature. Here, we evaluate the relationship between [Formula: see text] and temperature using observations from the FLUXNET-CH4 database. Measurements collected across the globe show substantial seasonal hysteresis between [Formula: see text] and temperature, suggesting larger [Formula: see text] sensitivity to temperature later in the frost-free season (about 77% of site-years). Results derived from a machine-learning model and several regression models highlight the importance of representing the large spatial and temporal variability within site-years and ecosystem types. Mechanistic advancements in biogeochemical model parameterization and detailed measurements in factors modulating CH4 production are thus needed to improve global CH4 budget assessments.
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| 3. |
- Knox, Sara H., et al.
(author)
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FLUXNET-CH4 Synthesis Activity : Objectives, Observations, and Future Directions
- 2019
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In: Bulletin of The American Meteorological Society - (BAMS). - 0003-0007 .- 1520-0477. ; 100:12, s. 2607-2632
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Journal article (peer-reviewed)abstract
- This paper describes the formation of, and initial results for, a new FLUXNET coordination network for ecosystem-scale methane (CH4) measurements at 60 sites globally, organized by the Global Carbon Project in partnership with other initiatives and regional flux tower networks. The objectives of the effort are presented along with an overview of the coverage of eddy covariance (EC) CH4 flux measurements globally, initial results comparing CH4 fluxes across the sites, and future research directions and needs. Annual estimates of net CH4 fluxes across sites ranged from -0.2 +/- 0.02 g C m(-2) yr(-1) for an upland forest site to 114.9 +/- 13.4 g C m(-2) yr(-1) for an estuarine freshwater marsh, with fluxes exceeding 40 g C m(-2) yr(-1) at multiple sites. Average annual soil and air temperatures were found to be the strongest predictor of annual CH4 flux across wetland sites globally. Water table position was positively correlated with annual CH4 emissions, although only for wetland sites that were not consistently inundated throughout the year. The ratio of annual CH4 fluxes to ecosystem respiration increased significantly with mean site temperature. Uncertainties in annual CH4 estimates due to gap-filling and random errors were on average +/- 1.6 g C m(-2) yr(-1) at 95% confidence, with the relative error decreasing exponentially with increasing flux magnitude across sites. Through the analysis and synthesis of a growing EC CH4 flux database, the controls on ecosystem CH4 fluxes can be better understood, used to inform and validate Earth system models, and reconcile differences between land surface model- and atmospheric-based estimates of CH4 emissions.
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| 4. |
- Niu, Shuli, et al.
(author)
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Thermal optimality of net ecosystem exchange of carbon dioxide and underlying mechanisms.
- 2012
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In: New Phytologist. - : Wiley. - 1469-8137 .- 0028-646X. ; 194:3, s. 775-783
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Journal article (peer-reviewed)abstract
- • It is well established that individual organisms can acclimate and adapt to temperature to optimize their functioning. However, thermal optimization of ecosystems, as an assemblage of organisms, has not been examined at broad spatial and temporal scales. • Here, we compiled data from 169 globally distributed sites of eddy covariance and quantified the temperature response functions of net ecosystem exchange (NEE), an ecosystem-level property, to determine whether NEE shows thermal optimality and to explore the underlying mechanisms. • We found that the temperature response of NEE followed a peak curve, with the optimum temperature (corresponding to the maximum magnitude of NEE) being positively correlated with annual mean temperature over years and across sites. Shifts of the optimum temperature of NEE were mostly a result of temperature acclimation of gross primary productivity (upward shift of optimum temperature) rather than changes in the temperature sensitivity of ecosystem respiration. • Ecosystem-level thermal optimality is a newly revealed ecosystem property, presumably reflecting associated evolutionary adaptation of organisms within ecosystems, and has the potential to significantly regulate ecosystem-climate change feedbacks. The thermal optimality of NEE has implications for understanding fundamental properties of ecosystems in changing environments and benchmarking global models.
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| 5. |
- Sun, Ge, et al.
(author)
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Environmental Controls of Ecosystem Evapotranspiration (ET): Why generalized ET models do not work for forests?
- 2012
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In: 2012 AGU Meeting, December 3-7, 2012, San Francisco, CA Advances in the Theory, Modeling, Measurement and Remote Sensing of Evapotranspiration from Terrestrial Surfaces.
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Conference paper (other academic/artistic)abstract
- Forests return large amount of fresh water back to the atmosphere through the evapotranspiration (ET) processes, and thus forests have enormous influences on global water, energy, and bigeochemical cycles. Accurately quantifying forest evapotranspiration (ET) is essential to understanding ecohydrological processes, developing regional-scale water and carbon balances, and projecting impacts of environmental changes on natural resources. However, measuring and modeling forest ET remain challenging. Traditional ET models are designed for reference crops (e.g. short green grasses) and not for forested conditions with much higher above and below ground biomass. The large spatial and temporal variability of forests, and complex interactions between physical (temperature and precipitation) and chemical (CO2, Ozone) climate and tree ecophysiological responses also contribute to ET measurement complexity. In this study, we examined environmental controls on ecosystem level ET including forests using multiple measurements (sapflow, watershed hydrologic records, eddy flux measurements, and controlled experiments) and statistical techniques (multivariate linear regressions, best subset regression, stepwise regression). In general, eddy flux data suggest that temperature-based potential ET (PET), measured precipitation (P), and remotely sensed Leaf Area Index (LAI) – a key parameter of ecosystem structure - explain most of the variability of observed monthly forest ET (R2=0.67-0.95) across a wide range of climatic and ecosystem types. VPD is a major driver of forest ET, but P is a rather weak predictor for forest ET. Solar radiation and LAI were highly correlated with ET in grasslands, croplands, and shrublands. Ozone effect was detected only in the mature forests in the Eastern USA where the O3 levels can reach relatively high values. The O3 effect varied with climatic conditions, but the increase in tree transpiration was always associated with reduced streamflow. As the measured ET in forests exceeded Hamon’s PET during the growing season, we conclude that the hydrological models based on these PET estimates are systematically biased low. A series of simple ET models in the form of ET=f(PET, LAI, P) were implemented in a water balance model, WaSSI (Water Supply Stress Index model), for mapping seasonal ET distributions across the continental United States at a scale of approximately 100 km2. We conclude that when eddy flux datasets were extremely useful for understanding ET processes at a fine scale when combined with long term gaged watershed streamflow and remote sensing data. Adding land cover properties into traditional ET models improved model accuracy for simulating seasonal ET. Future models should consider the influences of air pollution, such as CO2, ambient ozone and climate-ozone interactions, on forest ET. Models that include other soil processes such as hydraulic redistribution in the root zones may also improve model accuracy at a large scale.
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| 6. |
- Yao, Yunjun, et al.
(author)
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Assessment and simulation of global terrestrial latent heat flux by synthesis of CMIP5 climate models and surface eddy covariance observations
- 2016
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In: Agricultural and Forest Meteorology. - : Elsevier BV. - 0168-1923. ; 223, s. 151-167
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Journal article (peer-reviewed)abstract
- The latent heat flux (LE) between the terrestrial biosphere and atmosphere is a major driver of the global hydrological cycle. In this study, we evaluated LE simulations by 45 general circulation models (GCMs) in the Coupled Model Intercomparison Project Phase 5 (CMIP5) by a comparison with eddy covariance (EC) observations from 240 globally distributed sites from 2000 to 2009. In addition, we improved global terrestrial LE estimates for different land cover types by synthesis of seven best CMIP5 models and EC observations based on a Bayesian model averaging (BMA) method. The comparison results showed substantial differences in monthly LE among all GCMs. The model CESM1-CAM5 has the best performance with the highest predictive skill and a Taylor skill score (S) from 0.51-0.75 for different land cover types. The cross-validation results illustrate that the BMA method has improved the accuracy of the CMIP5 GCM's LE simulation with a decrease in the averaged root-mean-square error (RMSE) by more than 3 W/m2 when compared to the simple model averaging (SMA) method and individual GCMs. We found an increasing trend in the BMA-based global terrestrial LE (slope of 0.018 W/m2 yr-1, p <0.05) during the period 1970-2005. This variation may be attributed directly to the inter-annual variations in air temperature (Ta), surface incident solar radiation (Rs) and precipitation (P). However, our study highlights a large difference from previous studies in a continuous increasing trend after 1998, which may be caused by the combined effects of the variations of Rs, Ta, and P on LE for different models on these time scales. This study provides corrected-modeling evidence for an accelerated global water cycle with climate change.
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| 7. |
- Yazbeck, Theresia, et al.
(author)
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Site Characteristics Mediate the Relationship Between Forest Productivity and Satellite Measured Solar Induced Fluorescence
- 2021
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In: Frontiers in Forests and Global Change. - : Frontiers Media SA. - 2624-893X. ; 4
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Journal article (peer-reviewed)abstract
- Solar-Induced Chlorophyll Fluorescence (SIF) can provide key information about the state of photosynthesis and offers the prospect of defining remote sensing-based estimation of Gross Primary Production (GPP). There is strong theoretical support for the link between SIF and GPP and this relationship has been empirically demonstrated using ground-based, airborne, and satellite-based SIF observations, as well as modeling. However, most evaluations have been based on monthly and annual scales, yet the GPP:SIF relations can be strongly influenced by both vegetation structure and physiology. At the monthly timescales, the structural response often dominates but short-term physiological variations can strongly impact the GPP:SIF relations. Here, we test how well SIF can predict the inter-daily variation of GPP during the growing season and under stress conditions, while taking into account the local effect of sites and abiotic conditions. We compare the accuracy of GPP predictions from SIF at different timescales (half-hourly, daily, and weekly), while evaluating effect of adding environmental variables to the relationship. We utilize observations for years 2018–2019 at 31 mid-latitudes, forested, eddy covariance (EC) flux sites in North America and Europe and use TROPOMI satellite data for SIF. Our results show that SIF is a good predictor of GPP, when accounting for inter-site variation, probably due to differences in canopy structure. Seasonally averaged leaf area index, fraction of absorbed photosynthetically active radiation (fPAR) and canopy conductance provide a predictor to the site-level effect. We show that fPAR is the main factor driving errors in the linear model at high temporal resolution. Adding water stress indicators, namely canopy conductance, to a multi-linear SIF-based GPP model provides the best improvement in the model precision at the three considered timescales, showing the importance of accounting for water stress in GPP predictions, independent of the SIF signal. SIF is a promising predictor for GPP among other remote sensing variables, but more focus should be placed on including canopy structure, and water stress effects in the relationship, especially when considering intra-seasonal, and inter- and intra-daily resolutions.
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| 8. |
- Yi, Chuixiang, et al.
(author)
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Climate control of terrestrial carbon exchange across biomes and continents
- 2010
-
In: Environmental Research Letters. - : IOP Publishing. - 1748-9326. ; 5:3
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Journal article (peer-reviewed)abstract
- Understanding the relationships between climate and carbon exchange by terrestrial ecosystems is critical to predict future levels of atmospheric carbon dioxide because of the potential accelerating effects of positive climate-carbon cycle feedbacks. However, directly observed relationships between climate and terrestrial CO2 exchange with the atmosphere across biomes and continents are lacking. Here we present data describing the relationships between net ecosystem exchange of carbon (NEE) and climate factors as measured using the eddy covariance method at 125 unique sites in various ecosystems over six continents with a total of 559 site-years. We find that NEE observed at eddy covariance sites is (1) a strong function of mean annual temperature at mid-and high-latitudes, (2) a strong function of dryness at mid-and low-latitudes, and (3) a function of both temperature and dryness around the mid-latitudinal belt (45 degrees N). The sensitivity of NEE to mean annual temperature breaks down at similar to 16 degrees C (a threshold value of mean annual temperature), above which no further increase of CO2 uptake with temperature was observed and dryness influence overrules temperature influence.
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