| The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data G Pastorello, C Trotta, E Canfora, H Chu, D Christianson, YW Cheah, ... Scientific data 7 (1), 225, 2020 | 1629* | 2020 |
| Inter-annual variability of net and gross ecosystem carbon fluxes: A review D Baldocchi, H Chu, M Reichstein Agricultural and Forest Meteorology 249, 520-533, 2018 | 450 | 2018 |
| Representativeness of Eddy-Covariance flux footprints for areas surrounding AmeriFlux sites H Chu, X Luo, Z Ouyang, WS Chan, S Dengel, SC Biraud, MS Torn, ... Agricultural and Forest Meteorology 301, 108350, 2021 | 419 | 2021 |
| FLUXNET-CH 4 Synthesis Activity: Objectives, Observations, and Future Directions SH Knox, RB Jackson, B Poulter, G McNicol, E Fluet-Chouinard, Z Zhang, ... Bulletin of the American Meteorological Society 100 (12), 2607-2632, 2019 | 217 | 2019 |
| FLUXNET-CH4: A global, multi-ecosystem dataset and analysis of methane seasonality from freshwater wetlands KB Delwiche, SH Knox, A Malhotra, E Fluet-Chouinard, G McNicol, ... Earth System Science Data Discussions 2021, 1-111, 2021 | 210 | 2021 |
| Fluxes all of the time? A primer on the temporal representativeness of FLUXNET H Chu, DD Baldocchi, R John, S Wolf, M Reichstein Journal of Geophysical Research: Biogeosciences 122 (2), 289-307, 2017 | 174 | 2017 |
| Identifying dominant environmental predictors of freshwater wetland methane fluxes across diurnal to seasonal time scales SH Knox, S Bansal, G McNicol, K Schafer, C Sturtevant, M Ueyama, ... Global Change Biology 27 (15), 3582-3604, 2021 | 151 | 2021 |
| A new data set to keep a sharper eye on land-air exchanges G Pastorello, D Papale, H Chu, C Trotta, D Agarwal, E Canfora, ... Eos, Transactions American Geophysical Union (Online) 98 (8), 2017 | 151* | 2017 |
| Net ecosystem methane and carbon dioxide exchanges in a Lake Erie coastal marsh and a nearby cropland H Chu, J Chen, JF Gottgens, Z Ouyang, R John, K Czajkowski, R Becker Journal of Geophysical Research: Biogeosciences 119 (5), 722-740, 2014 | 115 | 2014 |
| Gap-filling eddy covariance methane fluxes: Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands J Irvin, S Zhou, G McNicol, F Lu, V Liu, E Fluet-Chouinard, Z Ouyang, ... Agricultural and Forest Meteorology 308, 108528, 2021 | 113 | 2021 |
| Seasonal variability of forest sensitivity to heat and drought stresses: a synthesis based on carbon fluxes from North American forest ecosystems B Xu, MA Arain, TA Black, BE Law, GZ Pastorello, H Chu Global change biology 26 (2), 901-918, 2020 | 101 | 2020 |
| Ten-year variability in ecosystem water use efficiency in an oak-dominated temperate forest under a warming climate J Xie, J Chen, G Sun, T Zha, B Yang, H Chu, J Liu, S Wan, C Zhou, H Ma, ... Agricultural and Forest Meteorology 218, 209-217, 2016 | 86 | 2016 |
| Diurnal to annual changes in latent, sensible heat, and CO2 fluxes over a Laurentian Great Lake: A case study in Western Lake Erie C Shao, J Chen, CA Stepien, H Chu, Z Ouyang, TB Bridgeman, ... Journal of Geophysical Research: Biogeosciences 120 (8), 1587-1604, 2015 | 82 | 2015 |
| Substantial hysteresis in emergent temperature sensitivity of global wetland CH4 emissions KY Chang, WJ Riley, SH Knox, RB Jackson, G McNicol, B Poulter, ... Nature Communications 12 (1), 2266, 2021 | 80 | 2021 |
| ORCHIDEE-PEAT (revision 4596), a model for northern peatland CO, water, and energy fluxes on daily to annual scales C Qiu, D Zhu, P Ciais, B Guenet, G Krinner, S Peng, M Aurela, ... Geoscientific Model Development 11 (2), 497-519, 2018 | 80 | 2018 |
| Climatic variability, hydrologic anomaly, and methane emission can turn productive freshwater marshes into net carbon sources H Chu, JF Gottgens, J Chen, G Sun, AR Desai, Z Ouyang, C Shao, ... Global change biology, 2014 | 79 | 2014 |
| Evapotranspiration of annual and perennial biofuel crops in a variable climate M Abraha, J Chen, H Chu, T Zenone, R John, YJ Su, SK Hamilton, ... GCB Bioenergy 7 (6), 1344-1356, 2015 | 74 | 2015 |
| Causality guided machine learning model on wetland CH4 emissions across global wetlands K Yuan, Q Zhu, F Li, WJ Riley, M Torn, H Chu, G McNicol, M Chen, S Knox, ... Agricultural and Forest Meteorology 324, 109115, 2022 | 65 | 2022 |
| Does canopy wetness matter? Evapotranspiration from a subtropical montane cloud forest in Taiwan HS Chu, SC Chang, O Klemm, CW Lai, YZ Lin, CC Wu, JY Lin, JY Jiang, ... Hydrological Processes 28 (3), 1190-1214, 2014 | 65 | 2014 |
| Upscaling wetland methane emissions from the FLUXNET‐CH4 eddy covariance network (UpCH4 v1. 0): Model development, network assessment, and budget comparison G McNicol, E Fluet‐Chouinard, Z Ouyang, S Knox, Z Zhang, T Aalto, ... AGU Advances 4 (5), e2023AV000956, 2023 | 59 | 2023 |
Jiquan ChenUniversity Distinguished Professor, Michigan State UniversityVerified email at msu.edu
