Browsing by Author "Luo, Yiqi"
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Item Characterizing the performance of ecosystem models across time scales: A spectral analysis of the North American Carbon Program site‐level synthesis(2011-12-20) Dietze, Michael C.; Vargas, Rodrigo; Richardson, Andrew D.; Stoy, Paul C.; Barr, Alan G.; Anderson, Ryan S.; M. Altaf Arain, M. Altaf; Baker, Ian T.; Blac, T. Andrew; Chen, Jing M.; Ciais, Philippe; Flanagan, Lawrence B.; Gough, Christopher M.; Grant, Robert F.; Hollinger, David Y.; Izaurralde, R. Cesar; Kucharik, Christopher J.; Lafleur, Peter; Liu, Shuguang; Lokupitiya, Erandathie; Luo, Yiqi; Munger, J. William; Peng, Changhui; Poulter, Benjamin; Price, David T.; Ricciuto, Daniel M.; Riley, William J.; Sahoo, Alok Kumar; Schaefer, Kevin; Suyker, Andrew E.; Tain, Hanqin; Tonitto, Christina; Verbeeck, Hans; Verma, Shashi B.; Weifeng, Wang; Weng, EnshengEcosystem models are important tools for diagnosing the carbon cycle and projecting its behavior across space and time. Despite the fact that ecosystems respond to drivers at multiple time scales, most assessments of model performance do not discriminate different time scales. Spectral methods, such as wavelet analyses, present an alternative approach that enables the identification of the dominant time scales contributing to model performance in the frequency domain. In this study we used wavelet analyses to synthesize the performance of 21 ecosystem models at 9 eddy covariance towers as part of the North American Carbon Program's site-level intercomparison. This study expands upon previous single-site and single-model analyses to determine what patterns of model error are consistent across a diverse range of models and sites. To assess the significance of model error at different time scales, a novel Monte Carlo approach was developed to incorporate flux observation error. Failing to account for observation error leads to a misidentification of the time scales that dominate model error. These analyses show that model error (1) is largest at the annual and 20–120 day scales, (2) has a clear peak at the diurnal scale, and (3) shows large variability among models in the 2–20 day scales. Errors at the annual scale were consistent across time, diurnal errors were predominantly during the growing season, and intermediate-scale errors were largely event driven. Breaking spectra into discrete temporal bands revealed a significant model-by-band effect but also a nonsignificant model-by-site effect, which together suggest that individual models show consistency in their error patterns. Differences among models were related to model time step, soil hydrology, and the representation of photosynthesis and phenology but not the soil carbon or nitrogen cycles. These factors had the greatest impact on diurnal errors, were less important at annual scales, and had the least impact at intermediate time scales.Item Climate controls over the net carbon uptake period and amplitude of net ecosystem production in temperate and boreal ecosystems(2017-09) Fu, Zheng; Stoy, Paul C.; Luo, Yiqi; Chen, Jiquan; Sun, Jian; Montagnani, Leonardo; Wohlfahrt, Georg; Rahman, Abdullah F.; Rambal, Serge; Bernhofer, Christian; Wang, Jinsong; Shirkey, Gabriela; Niu, ShuliThe seasonal and interannual variability of the terrestrial carbon cycle is regulated by the interactions of climate and ecosystem function. However, the key factors and processes determining the interannual variability of net ecosystem productivity (NEP) in different biomes are far from clear. Here, we quantified yearly anomalies of seasonal and annual NEP, net carbon uptake period (CUP), and the maximum daily NEP (NEPmax) in response to climatic variables in 24 deciduous broadleaf forest (DBF), evergreen forest (EF), and grassland (GRA) ecosystems that include at least eight years of eddy covariance observations. Over the 228 site-years studied, interannual variations in NEP were mostly explained by anomalies of CUP and NEPmax. CUP was determined by spring and autumn net carbon uptake phenology, which were sensitive to annual meteorological variability. Warmer spring temperatures led to an earlier start of net carbon uptake activity and higher spring and annual NEP values in DBF and EF, while warmer autumn temperatures in DBF, higher autumn radiation in EF, and more summer and autumn precipitation in GRA resulted in a later ending date of net carbon uptake and associated higher autumn and annual NEP. Anomalies in NEPmax s were determined by summer precipitation in DBF and GRA, and explained more than 50% of variation in summer NEP anomalies for all the three biomes. Results demonstrate the role of meteorological variability in controlling CUP and NEPmax, which in turn help describe the seasonal and interannual variability of NEP.Item Evaluating the agreement between measurements and models of net ecosystem exchange at different times and time scales using wavelet coherence: an example using data from the North American Carbon Program Site-Level Interim Synthesis(2013-11) Stoy, Paul C.; Dietze, Michael C.; Richardson, Andrew D.; Vargas, Rodrigo; Barr, Alan G.; Anderson, R. S.; Arain, M. Altaf; Baker, Ian T.; Black, T. A; Chen, Jing M.; Cook, R. B.; Gough, Christopher M.; Grant, Robert F.; Hollinger, David Y.; Izaurralde, R. Cesar; Kucharik, Christopher J.; Lafleur, Peter; Law, Beverly E.; Liu, Shuguang; Lokupitiya, Erandathie; Luo, Yiqi; Munger, J. William; Peng, Changhui; Poulter, Benjamin; Price, David T.; Ricciuto, Daniel M.; Riley, William J.; Sahoo, Alok Kumar; Schaefer, Kevin; Schwalm, C. R.; Tian, Hui; Verbeeck, Hans; Weng, EnshengEarth system processes exhibit complex patterns across time, as do the models that seek to replicate these processes. Model output may or may not be significantly related to observations at different times and on different frequencies. Conventional model diagnostics provide an aggregate view of model–data agreement, but usually do not identify the time and frequency patterns of model–data disagreement, leaving unclear the steps required to improve model response to environmental drivers that vary on characteristic frequencies. Wavelet coherence can quantify the times and timescales at which two time series, for example time series of models and measurements, are significantly different. We applied wavelet coherence to interpret the predictions of 20 ecosystem models from the North American Carbon Program (NACP) Site-Level Interim Synthesis when confronted with eddy-covariance-measured net ecosystem exchange (NEE) from 10 ecosystems with multiple years of available data. Models were grouped into classes with similar approaches for incorporating phenology, the calculation of NEE, the inclusion of foliar nitrogen (N), and the use of model–data fusion. Models with prescribed, rather than prognostic, phenology often fit NEE observations better on annual to interannual timescales in grassland, wetland and agricultural ecosystems. Models that calculated NEE as net primary productivity (NPP) minus heterotrophic respiration (HR) rather than gross ecosystem productivity (GPP) minus ecosystem respiration (ER) fit better on annual timescales in grassland and wetland ecosystems, but models that calculated NEE as GPP minus ER were superior on monthly to seasonal timescales in two coniferous forests. Models that incorporated foliar nitrogen (N) data were successful at capturing NEE variability on interannual (multiple year) timescales at Howland Forest, Maine. The model that employed a model–data fusion approach often, but not always, resulted in improved fit to data, suggesting that improving model parameterization is important but not the only step for improving model performance. Combined with previous findings, our results suggest that the mechanisms driving daily and annual NEE variability tend to be correctly simulated, but the magnitude of these fluxes is often erroneous, suggesting that model parameterization must be improved. Few NACP models correctly predicted fluxes on seasonal and interannual timescales where spectral energy in NEE observations tends to be low, but where phenological events, multi-year oscillations in climatological drivers, and ecosystem succession are known to be important for determining ecosystem function. Mechanistic improvements to models must be made to replicate observed NEE variability on seasonal and interannual timescales.Item Improving land surface models with FLUXNET data(2009-07) Williams, Mathew; Richardson, Andrew D.; Reichstein, M.; Stoy, Paul C.; Peylin, Phili; Verbeeck, Hans; Carvalhais, N.; Jung, Martin; Hollinger, David Y.; Kattge, J.; Leuning, R.; Luo, Yiqi; Tomelleri, E.; Trudinger, C.; Wang, Ying-PingThere is a growing consensus that land surface models (LSMs) that simulate terrestrial biosphere exchanges of matter and energy must be better constrained with data to quantify and address their uncertainties. FLUXNET, an international network of sites that measure the land surface exchanges of carbon, water and energy using the eddy covariance technique, is a prime source of data for model improvement. Here we outline a multi-stage process for "fusing" (i.e. linking) LSMs with FLUXNET data to generate better models with quantifiable uncertainty. First, we describe FLUXNET data availability, and its random and systematic biases. We then introduce methods for assessing LSM model runs against FLUXNET observations in temporal and spatial domains. These assessments are a prelude to more formal model-data fusion (MDF). MDF links model to data, based on error weightings. In theory, MDF produces optimal analyses of the modelled system, but there are practical problems. We first discuss how to set model errors and initial conditions. In both cases incorrect assumptions will affect the outcome of the MDF. We then review the problem of equifinality, whereby multiple combinations of parameters can produce similar model output. Fusing multiple independent and orthogonal data provides a means to limit equifinality. We then show how parameter probability density functions (PDFs) from MDF can be used to interpret model validity, and to propagate errors into model outputs. Posterior parameter distributions are a useful way to assess the success of MDF, combined with a determination of whether model residuals are Gaussian. If the MDF scheme provides evidence for temporal variation in parameters, then that is indicative of a critical missing dynamic process. A comparison of parameter PDFs generated with the same model from multiple FLUXNET sites can provide insights into the concept and validity of plant functional types (PFT) – we would expect similar parameter estimates among sites sharing a single PFT. We conclude by identifying five major model-data fusion challenges for the FLUXNET and LSM communities: (1) to determine appropriate use of current data and to explore the information gained in using longer time series; (2) to avoid confounding effects of missing process representation on parameter estimation; (3) to assimilate more data types, including those from earth observation; (4) to fully quantify uncertainties arising from data bias, model structure, and initial conditions problems; and (5) to carefully test current model concepts (e.g. PFTs) and guide development of new concepts.Item Redefinition and global estimation of basal ecosystem respiration rate(2001-10-13) Yuan, Wenping; Luo, Yiqi; Li, Shuguang; Yu, Guirui; Zhou, Tao; Bahn, Michael; Black, Andy T.; Desai, Ankur R.; Cescatti, Alessandro; Marcolla, Barbara; Jacobs, Cor; Chen, Jiquan; Aurela, Mika; Bernhofer, Christian; Gielen, Bert; Bohrer, Gil; Cook, David R.; Dragoni, Danilo; Dunn, Allison L.; Gianelle, Damiano; Grünwald, Thomas; Ibrom, Andreas; Leclerc, Monique Y.; Lindroth, Anders; Liu, Heping; Marchesini, Luca Belelli; Montagnani, Leonardo; Pita, Gabriel; Rodeghiero, Mirco; Rodrigues, Abel; Starr, Gregory; Stoy, Paul C.Basal ecosystem respiration rate (BR), the ecosystem respiration rate at a given temperature, is a common and important parameter in empirical models for quantifying ecosystem respiration (ER) globally. Numerous studies have indicated that BR varies in space. However, many empirical ER models still use a global constant BR largely due to the lack of a functional description for BR. In this study, we redefined BR to be ecosystem respiration rate at the mean annual temperature. To test the validity of this concept, we conducted a synthesis analysis using 276 site-years of eddy covariance data, from 79 research sites located at latitudes ranging from ∼3°S to ∼70°N. Results showed that mean annual ER rate closely matches ER rate at mean annual temperature. Incorporation of site-specific BR into global ER model substantially improved simulated ER compared to an invariant BR at all sites. These results confirm that ER at the mean annual temperature can be considered as BR in empirical models. A strong correlation was found between the mean annual ER and mean annual gross primary production (GPP). Consequently, GPP, which is typically more accurately modeled, can be used to estimate BR. A light use efficiency GPP model (i.e., EC-LUE) was applied to estimate global GPP, BR and ER with input data from MERRA (Modern Era Retrospective-Analysis for Research and Applications) and MODIS (Moderate resolution Imaging Spectroradiometer). The global ER was 103 Pg C yr −1, with the highest respiration rate over tropical forests and the lowest value in dry and high-latitude areas.Item Thermal Adaptation of Net Ecosystem Exchange(2011-06-06) Yuan, Wenping; Luo, Yiqi; Liang, S.; Yu, Guirui; Niu, Shuli; Stoy, Paul C.; Chen, Jing M.; Desai, Ankur R.; Lindroth, Anders; Gough, Christopher M.; Ceulemans, R.; Arain, M. Altaf; Bernhofer, C.; Cook, B.; Cook, David R.; Dragoni, Danilo; Gielen, Bert; Janssens, I. A.; Longdoz, B.; Liu, Heping; Lund, Magnus; Matteucci, Giorgio; Moors, Eddy; Scott, Russell L.; Seufert, G.; Varner, R." Thermal adaptation of gross primary production and ecosystem respiration has been well documented over broad thermal gradients. However, no study has examined their interaction as a function of temperature, i.e. the thermal responses of net ecosystem exchange of carbon (NEE). In this study, we constructed temperature response curves of NEE against temperature using 380 site-years of eddy covariance data at 72 forest, grassland and shrubland ecosystems located at latitudes ranging from ~29° N to 64° N. The response curves were used to define two critical temperatures: transition temperature (Tb) at which ecosystem transfer from carbon source to sink and optimal temperature (To) at which carbon uptake is maximized. Tb was strongly correlated with annual mean air temperature. To was strongly correlated with mean temperature during the net carbon uptake period across the study ecosystems. Our results imply that the net ecosystem exchange of carbon adapts to the temperature across the geographical range due to intrinsic connections between vegetation primary production and ecosystem respiration.Item Thermal optimality of net ecosystem exchange of carbon dioxide and underlying mechanisms(2012-03-07) Niu, Shuli; Luo, Yiqi; Fei, Shenfeng; Yuan, Wenping; Schimel, David; Law, Beverly E.; Ammann, Christof; Arain, M. Altaf; Arneth, Almut; Aubinet, Marc; Barr, Alan G.; Beringer, Jason; Bernhofer, Christian; Black, T. Andrew; Buchmann, Nina; Cescatti, Alessandro; Chen, Jiquan; Davis, Kenneth J.; Dellwik, Ebba; Desai, Ankur R.; Etzold, Sophia; Francois, Louis; Gianelle, Damiano; Gielen, Bert; Goldstein, Allen; Groenendijk, Margriet; Gu, Lianhong; Hanan, Niall; Helfter, Carole; Hirano, Takashi; Hollinger, David Y.; Jones, Mike B.; Kiely, Gerard; Kolb, Thomas E.; Kutsch, Werner L.; Lafleur, Peter; Lawrence, David M.; Li, Linghao; Lindroth, Anders; Litvak, Marcy; Loustau, Denis; Lund, Magnus; Marek, Michal; Martin, Timothy A.; Matteucci, Giorgio; Migliavacca, Mirco; Montagnani, Leonardo; Moors, Eddy; Munger, J. William; Noormets, Asko; Oechel, Walter C.; Olejnik, Janusz; Pilegaard, Kim; Paw U, Kyaw Tha; Pilegaard, Kim; Rambal, Serge; Raschi, Antonio; Scott, Russell L.; Seufert, Günther; Spano, Donatella; Stoy, Paul C.; Sutton, Mark A.; Varlagin, Andrej; Vesala, Timo; Weng, Ensheng; Wohlfahrt, Georg; Yang, Bai; Zhang, Zhongda; Zhou, XuhuiIt 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 ecosystemclimate change feedbacks. The thermal optimality of NEE has implications for understanding fundamental properties of ecosystems in changing environments and benchmarking global models.