ORCID Profile
0000-0002-0680-4697
Current Organisations
Oak Ridge National Laboratory
,
Washington State University
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Publisher: American Geophysical Union (AGU)
Date: 05-2014
DOI: 10.1002/2013JG002553
Publisher: Wiley
Date: 25-03-2013
DOI: 10.1111/GCB.12164
Abstract: Predicted responses of transpiration to elevated atmospheric CO2 concentration (eCO2 ) are highly variable amongst process-based models. To better understand and constrain this variability amongst models, we conducted an intercomparison of 11 ecosystem models applied to data from two forest free-air CO2 enrichment (FACE) experiments at Duke University and Oak Ridge National Laboratory. We analysed model structures to identify the key underlying assumptions causing differences in model predictions of transpiration and canopy water use efficiency. We then compared the models against data to identify model assumptions that are incorrect or are large sources of uncertainty. We found that model-to-model and model-to-observations differences resulted from four key sets of assumptions, namely (i) the nature of the stomatal response to elevated CO2 (coupling between photosynthesis and stomata was supported by the data) (ii) the roles of the leaf and atmospheric boundary layer (models which assumed multiple conductance terms in series predicted more decoupled fluxes than observed at the broadleaf site) (iii) the treatment of canopy interception (large intermodel variability, 2-15%) and (iv) the impact of soil moisture stress (process uncertainty in how models limit carbon and water fluxes during moisture stress). Overall, model predictions of the CO2 effect on WUE were reasonable (intermodel μ = approximately 28% ± 10%) compared to the observations (μ = approximately 30% ± 13%) at the well-coupled coniferous site (Duke), but poor (intermodel μ = approximately 24% ± 6% observations μ = approximately 38% ± 7%) at the broadleaf site (Oak Ridge). The study yields a framework for analysing and interpreting model predictions of transpiration responses to eCO2 , and highlights key improvements to these types of models.
Publisher: Wiley
Date: 21-05-2014
DOI: 10.1111/NPH.12847
Abstract: Elevated atmospheric CO 2 concentration ( eCO 2 ) has the potential to increase vegetation carbon storage if increased net primary production causes increased long‐lived biomass. Model predictions of eCO 2 effects on vegetation carbon storage depend on how allocation and turnover processes are represented. We used data from two temperate forest free‐air CO 2 enrichment ( FACE ) experiments to evaluate representations of allocation and turnover in 11 ecosystem models. Observed eCO 2 effects on allocation were dynamic. Allocation schemes based on functional relationships among biomass fractions that vary with resource availability were best able to capture the general features of the observations. Allocation schemes based on constant fractions or resource limitations performed less well, with some models having unintended outcomes. Few models represent turnover processes mechanistically and there was wide variation in predictions of tissue lifespan. Consequently, models did not perform well at predicting eCO 2 effects on vegetation carbon storage. Our recommendations to reduce uncertainty include: use of allocation schemes constrained by biomass fractions careful testing of allocation schemes and synthesis of allocation and turnover data in terms of model parameters. Data from intensively studied ecosystem manipulation experiments are invaluable for constraining models and we recommend that such experiments should attempt to fully quantify carbon, water and nutrient budgets.
Publisher: Proceedings of the National Academy of Sciences
Date: 25-10-2010
Abstract: Stimulation of terrestrial plant production by rising CO 2 concentration is projected to reduce the airborne fraction of anthropogenic CO 2 emissions. Coupled climate–carbon cycle models are sensitive to this negative feedback on atmospheric CO 2 , but model projections are uncertain because of the expectation that feedbacks through the nitrogen (N) cycle will reduce this so-called CO 2 fertilization effect. We assessed whether N limitation caused a reduced stimulation of net primary productivity (NPP) by elevated atmospheric CO 2 concentration over 11 y in a free-air CO 2 enrichment (FACE) experiment in a deciduous Liquidambar styraciflua (sweetgum) forest stand in Tennessee. During the first 6 y of the experiment, NPP was significantly enhanced in forest plots exposed to 550 ppm CO 2 compared with NPP in plots in current ambient CO 2 , and this was a consistent and sustained response. However, the enhancement of NPP under elevated CO 2 declined from 24% in 2001–2003 to 9% in 2008. Global analyses that assume a sustained CO 2 fertilization effect are no longer supported by this FACE experiment. N budget analysis supports the premise that N availability was limiting to tree growth and declining over time —an expected consequence of stand development, which was exacerbated by elevated CO 2 . Leaf- and stand-level observations provide mechanistic evidence that declining N availability constrained the tree response to elevated CO 2 these observations are consistent with stand-level model projections. This FACE experiment provides strong rationale and process understanding for incorporating N limitation and N feedback effects in ecosystem and global models used in climate change assessments.
Publisher: Office of Scientific and Technical Information (OSTI)
Date: 2020
DOI: 10.2172/1784174
Publisher: Springer Science and Business Media LLC
Date: 21-05-2015
DOI: 10.1038/NCLIMATE2621
Publisher: Office of Scientific and Technical Information (OSTI)
Date: 12-2019
DOI: 10.2172/1784183
Publisher: Wiley
Date: 08-11-2013
DOI: 10.1111/PCE.12213
Abstract: Worldwide measurements of nearly 130 C3 species covering all major plant functional types are analysed in conjunction with model simulations to determine the effects of mesophyll conductance (g(m)) on photosynthetic parameters and their relationships estimated from A/Ci curves. We find that an assumption of infinite g(m) results in up to 75% underestimation for maximum carboxylation rate V(cmax), 60% for maximum electron transport rate J(max), and 40% for triose phosphate utilization rate T(u) . V(cmax) is most sensitive, J(max) is less sensitive, and T(u) has the least sensitivity to the variation of g(m). Because of this asymmetrical effect of g(m), the ratios of J(max) to V(cmax), T(u) to V(cmax) and T(u) to J(max) are all overestimated. An infinite g(m) assumption also limits the freedom of variation of estimated parameters and artificially constrains parameter relationships to stronger shapes. These findings suggest the importance of quantifying g(m) for understanding in situ photosynthetic machinery functioning. We show that a nonzero resistance to CO2 movement in chloroplasts has small effects on estimated parameters. A non-linear function with gm as input is developed to convert the parameters estimated under an assumption of infinite gm to proper values. This function will facilitate gm representation in global carbon cycle models.
Publisher: Oxford University Press (OUP)
Date: 2015
Publisher: Springer Science and Business Media LLC
Date: 14-02-2019
DOI: 10.1038/S41467-019-08348-1
Abstract: Increasing atmospheric CO 2 stimulates photosynthesis which can increase net primary production (NPP), but at longer timescales may not necessarily increase plant biomass. Here we analyse the four decade-long CO 2 -enrichment experiments in woody ecosystems that measured total NPP and biomass. CO 2 enrichment increased biomass increment by 1.05 ± 0.26 kg C m −2 over a full decade, a 29.1 ± 11.7% stimulation of biomass gain in these early-secondary-succession temperate ecosystems. This response is predictable by combining the CO 2 response of NPP (0.16 ± 0.03 kg C m −2 y −1 ) and the CO 2 -independent, linear slope between biomass increment and cumulative NPP (0.55 ± 0.17). An ensemble of terrestrial ecosystem models fail to predict both terms correctly. Allocation to wood was a driver of across-site, and across-model, response variability and together with CO 2 -independence of biomass retention highlights the value of understanding drivers of wood allocation under ambient conditions to correctly interpret and predict CO 2 responses.
Publisher: Springer Science and Business Media LLC
Date: 02-03-2015
DOI: 10.1038/NCLIMATE2550
Publisher: Wiley
Date: 08-02-2019
DOI: 10.1111/NPH.15668
Abstract: The temperature response of photosynthesis is one of the key factors determining predicted responses to warming in global vegetation models (GVMs). The response may vary geographically, owing to genetic adaptation to climate, and temporally, as a result of acclimation to changes in ambient temperature. Our goal was to develop a robust quantitative global model representing acclimation and adaptation of photosynthetic temperature responses. We quantified and modelled key mechanisms responsible for photosynthetic temperature acclimation and adaptation using a global dataset of photosynthetic CO
Publisher: AIP Publishing
Date: 05-2023
DOI: 10.1063/5.0131778
Abstract: The Oak Ridge National Laboratory is planning to build the Second Target Station (STS) at the Spallation Neutron Source (SNS). STS will host a suite of novel instruments that complement the First Target Station’s beamline capabilities by offering an increased flux for cold neutrons and a broader wavelength bandwidth. A novel neutron imaging beamline, named the Complex, Unique, and Powerful Imaging Instrument for Dynamics (CUPI2D), is among the first eight instruments that will be commissioned at STS as part of the construction project. CUPI2D is designed for a broad range of neutron imaging scientific applications, such as energy storage and conversion (batteries and fuel cells), materials science and engineering (additive manufacturing, superalloys, and archaeometry), nuclear materials (novel cladding materials, nuclear fuel, and moderators), cementitious materials, biology/medical/dental applications (regenerative medicine and cancer), and life sciences (plant–soil interactions and nutrient dynamics). The innovation of this instrument lies in the utilization of a high flux of wavelength-separated cold neutrons to perform real time in situ neutron grating interferometry and Bragg edge imaging—with a wavelength resolution of δλ/λ ≈ 0.3%—simultaneously when required, across a broad range of length and time scales. This manuscript briefly describes the science enabled at CUPI2D based on its unique capabilities. The preliminary beamline performance, a design concept, and future development requirements are also presented.
No related grants have been discovered for Jeffrey Warren.