Large datasets of greenhouse gas and energy surface-atmosphere fluxes measured with the eddy-covariance technique (e.g., FLUXNET2015, AmeriFlux BASE) are widely used to benchmark models and remote-sensing products. This study addresses one of the major challenges facing model-data integration: To what spatial extent do flux measurements …
Journal: Agricultural And Forest Meteorology, Volume 301-302: 108350 (2021), ISBN . DOI: 10.1016/j.agrformet.2021.108350 Sites: CA-ARB, CA-ARF, CA-Ca1, CA-Ca2, CA-Ca3, CA-Cbo, CA-DBB, CA-ER1, CA-Gro, CA-Let, CA-Man, CA-MR3, CA-MR5, CA-Na1, CA-NS1, CA-NS2, CA-NS3, CA-NS4, CA-NS5, CA-NS6, CA-NS7, CA-Oas, CA-Obs, CA-Ojp, CA-Qc2, CA-Qcu, CA-Qfo, CA-SCC, CA-SF1, CA-SF2, CA-SF3, CA-SJ2, CA-SJ3, CA-TP1, CA-TP3, CA-TP4, CA-TPD, CA-WP1, US-A03, US-A10, US-A32, US-A74, US-ADR, US-AR1, US-AR2, US-ARb, US-ARc, US-ARM, US-Aud, US-Bar, US-Bi1, US-Bi2, US-Bkg, US-Blk, US-Blo, US-Bn1, US-Bn2, US-Bn3, US-Bo1, US-Bo2, US-Br3, US-CaV, US-Ced, US-CF1, US-CF2, US-CF3, US-CF4, US-ChR, US-Cop, US-CPk, US-CRT, US-Ctn, US-Dia, US-Dix, US-Dk1, US-Dk2, US-Dk3, US-EDN, US-Elm, US-EML, US-Fmf, US-FPe, US-FR2, US-FR3, US-Fuf, US-Fwf, US-GLE, US-GMF, US-Goo, US-Ha1, US-Ha2, US-Hn2, US-Hn3, US-Ho1, US-Ho2, US-Ho3, US-IB1, US-IB2, US-Ivo, US-KFS, US-KLS, US-Kon, US-KS1, US-KS2, US-KUT, US-Lin, US-Los, US-LPH, US-LWW, US-Me1, US-Me2, US-Me3, US-Me4, US-Me5, US-Me6, US-MMS, US-MOz, US-Mpj, US-MRf, US-MtB, US-Myb, US-NC1, US-NC2, US-NC3, US-NC4, US-Ne1, US-Ne2, US-Ne3, US-NGB, US-NR1, US-Oho, US-ORv, US-PHM, US-Pon, US-Prr, US-RC1, US-RC2, US-RC3, US-RC4, US-RC5, US-Rls, US-Rms, US-Ro1, US-Ro2, US-Ro5, US-Ro6, US-Rpf, US-Rws, US-SdH, US-Seg, US-Ses, US-SFP, US-Shd, US-Skr, US-Slt, US-Snd, US-Sne, US-Snf, US-SO2, US-SO3, US-SO4, US-SP1, US-SP2, US-SP3, US-SRC, US-SRG, US-SRM, US-Srr, US-Sta, US-StJ, US-Syv, US-Ton, US-Tw1, US-Tw2, US-Tw3, US-Tw4, US-Tw5, US-Twt, US-Uaf, US-UMB, US-UMd, US-Var, US-Vcm, US-Vcp, US-Vcs, US-WBW, US-WCr, US-Wdn, US-Wgr, US-Whs, US-Wi0, US-Wi1, US-Wi3, US-Wi4, US-Wi5, US-Wi6, US-Wi7, US-Wi8, US-Wi9, US-Wjs, US-Wkg, US-Wlr, US-Wpp, US-WPT, US-Wrc, US-xBR, US-xCP, US-xDL, US-xHA, US-xKA, US-xKZ, US-xRM, US-xSR, US-xWD
The global terrestrial carbon sink offsets one-third of the world’s fossil fuel emissions, but the strength of this sink is highly sensitive to large-scale extreme events. In 2012, the contiguous United States experienced exceptionally warm temperatures and the most severe drought since the Dust Bowl era of the 1930s, resulting …
Journal: Proceedings of the National Academy of Sciences, Volume 113 (21): 5880-5885 (2016), ISBN . DOI: 10.1073/pnas.1519620113 Sites: US-Bar, US-Ced, US-Ho1, US-KFS, US-Kon, US-Me2, US-Me6, US-MMS, US-Mpj, US-NR1, US-PFa, US-Slt, US-SRC, US-SRM, US-Ton, US-UMB, US-Var, US-Vcm, US-Vcp, US-Whs, US-Wjs, US-Wkg
Journal: Nature Climate Change, Volume 6 (11): 1023-1027 (2016), ISBN . DOI: 10.1038/nclimate3114 Sites: US-ARM, US-Bar, US-Blk, US-Blo, US-Bo1, US-Br3, US-Dk1, US-Dk2, US-Dk3, US-Fmf, US-FR2, US-Fuf, US-GLE, US-IB1, US-IB2, US-KFS, US-Kon, US-KS2, US-Me1, US-Me2, US-MMS, US-MOz, US-MRf, US-Ne1, US-Ne3, US-NR1, US-Oho, US-SRG, US-SRM, US-Syv, US-Ton, US-UMB, US-Var, US-WBW, US-WCr, US-Whs, US-Wkg
Vegetation light use efficiency is a key physiological parameter at the canopy scale, and at the daily time step is a component of remote sensing algorithms for scaling gross …
Journal: Global Change Biology, Volume 9 (3): 383-395 (2003), ISBN . DOI: 10.1046/j.1365-2486.2003.00573.x Sites: CA-Obs, US-Bo1, US-Bo2, US-Ha2, US-KFB, US-Kon
High evaporative demand and periodic drought characterize the growing season in midwestern grasslands relative to deciduous forests of the eastern US, and predicted climatic …
Journal: Global Change Biology, Volume 9 (2): 266-275 (2003), ISBN . DOI: 10.1046/j.1365-2486.2003.00574.x Sites: US-KFB, US-Kon
To address the need for a high quality data set based upon field observations suitable for parameterization, calibration, and validation of terrestrial biosphere models, we have developed a comprehensive global database on net primary productivity (NPP). We have compiled field measurements of biomass and associated environmental …
Journal: Global Change Biology, Volume 8 (8): 736-753 (2002), ISBN . DOI: 10.1046/j.1365-2486.2002.00512.x Sites: US-KFB, US-Kon
Accurate estimates of leaf area index (LAI) and leaf angle distribution (LAD) are important for estimating the exchange of energy and gases in vegetative canopies. Direct estimates of LAI and LAD are laborious, time consuming and often times destructive. Stewart and Dwyer [Agric. For. Meteorol. 66 (1993) 247] introduced a mathematical …
Journal: Agricultural And Forest Meteorology, Volume 108 (1): 45-53 (2001), ISBN . DOI: 10.1016/s0168-1923(01)00219-2 Sites: US-KFB, US-Kon
Spring burning of dead biomass in tallgrass prairie is a common practice that may influence heat and water vapor transport from the landscape. Bowen ratio methods were used to measure the surface energy balances and evapotranspiration (ET) from burned (B) and unburned (UB) prairie near Manhattan, KS, USA. Data were collected from …
Journal: Agricultural And Forest Meteorology, Volume 97 (1): 43-54 (1999), ISBN . DOI: 10.1016/s0168-1923(99)00034-9 Sites: US-KFB, US-Kon
Substantial research seeks to improve estimates of ecosystem processes and fluxes at a range of scales, notably from the stand scale (<1 km2) using ecosystem physiology and eddy covariance techniques, to the landscape (∼102 km2) and …
Journal: Remote Sensing Of Environment, Volume 70 (1): 69-81 (1999), ISBN . DOI: 10.1016/s0034-4257(99)00058-9 Sites: CA-Man, US-KFB, US-Kon
In tallgrass prairie, plant species interactions regulated by their associated mycorrhizal fungi may be important forces that influence species coexistence and community structure; however, the mechanisms and magnitude of these interactions remain unknown. The objective of this study was to determine how interspecific competition, …
Journal: Oecologia, Volume 121 (4): 574-582 (1999), ISBN . DOI: 10.1007/s004420050964 Sites: US-KFB, US-Kon