Browsing by Author "Arain, M. Altaf"

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A data-driven analysis of energy balance closure across FLUXNET research sites: The role of landscape scale heterogeneity
(2013-04-15) Stoy, Paul C.; Mauder, Matthias; Foken, Thomas; Marcolla, Barbara; Boegh, Eva; Ibrom, Andreas; Arain, M. Altaf
The energy balance at most surface-atmosphere flux research sites remains unclosed. The mechanisms underlying the discrepancy between measured energy inputs and outputs across the global FLUXNET tower network are still under debate. Recent reviews have identified exchange processes and turbulent motions at large spatial and temporal scales in heterogeneous landscapes as the primary cause of the lack of energy balance closure at some intensively-researched sites, while unmeasured storage terms cannot be ruled out as a dominant contributor to the lack of energy balance closure at many other sites. We analyzed energy balance closure across 173 ecosystems in the FLUXNET database and explored the relationship between energy balance closure and landscape heterogeneity using MODIS products and GLOBEstat elevation data. Energy balance closure per research site (CEB,s) averaged 0.84 ± 0.20, with best average closures in evergreen broadleaf forests and savannas (0.91–0.94) and worst average closures in crops, deciduous broadleaf forests, mixed forests and wetlands (0.70–0.78). Half-hourly or hourly energy balance closure on a percent basis increased with friction velocity (u*) and was highest on average under near-neutral atmospheric conditions. CEB,s was significantly related to mean precipitation, gross primary productivity and landscape-level enhanced vegetation index (EVI) from MODIS, and the variability in elevation, MODIS plant functional type, and MODIS EVI. A linear model including landscape-level variability in both EVI and elevation, mean precipitation, and an interaction term between EVI variability and precipitation had the lowest Akaike's information criterion value. CEB,s in landscapes with uniform plant functional type approached 0.9 and CEB,s in landscapes with uniform EVI approached 1. These results suggest that landscape-level heterogeneity in vegetation and topography cannot be ignored as a contributor to incomplete energy balance closure at the flux network level, although net radiation measurements, biological energy assimilation, unmeasured storage terms, and the importance of good practice including site selection when making flux measurements should not be discounted. Our results suggest that future research should focus on the quantitative mechanistic relationships between energy balance closure and landscape-scale heterogeneity, and the consequences of mesoscale circulations for surface-atmosphere exchange measurements.
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, Ensheng
Earth 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.
Linking flux network measurements to continental scale simulations: Ecosystem gas exchange capacity along a European transect under non-water-stressed conditions
(2007-01) Owen, Katherine E.; Tenhunen, John; Reichstein, Markus; Wang, Quan; Falge, Eva; Geyer, Ralf; Xiao, Xiangming; Stoy, Paul C.; Ammann, Christof; Arain, M. Altaf; Aubinet, Marc; Aurela, Mika; Bernhofer, Christian; Chojnicki, Bogdan H.; Granier, Andre; Gruenwald, Thomas; Hadley, Julian; Heinesch, Bernard; Hollinger, David Y.; Knohl, Alexander; Kutsch, Werner L.; Lohila, Annalea; Meyers, Tilden P.; Moors, Eddy J.; Moureaux, Christine; Pilegaard, Kim; Saigusa, Nobuko; Verma, Shashi B.; Vesala, Timo; Vogel, Chris
This paper examines long‐term eddy covariance data from 18 European and 17 North American and Asian forest, wetland, tundra, grassland, and cropland sites under non‐water‐stressed conditions with an empirical rectangular hyperbolic light response model and a single layer two light‐class carboxylase‐based model. Relationships according to ecosystem functional type are demonstrated between empirical and physiological parameters, suggesting linkages between easily estimated parameters and those with greater potential for process interpretation. Relatively sparse documentation of leaf area index dynamics at flux tower sites is found to be a major difficulty in model inversion and flux interpretation. Therefore, a simplification of the physiological model is carried out for a subset of European network sites with extensive ancillary data. The results from these selected sites are used to derive a new parameter and means for comparing empirical and physiologically based methods across all sites, regardless of ancillary data. The results from the European analysis are then compared with results from the other Northern Hemisphere sites and similar relationships for the simplified process‐based parameter were found to hold for European, North American, and Asian temperate and boreal climate zones. This parameter is useful for bridging between flux network observations and continental scale spatial simulations of vegetation/atmosphere carbon dioxide exchange.
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.
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, Xuhui
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 ecosystemclimate change feedbacks. The thermal optimality of NEE has implications for understanding fundamental properties of ecosystems in changing environments and benchmarking global models.