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Publications Found: 82
Scaling Individual Tree Transpiration With Thermal Cameras Reveals Interspecies Differences To Drought Vulnerability
Javadian, M., Aubrecht, D. M., Fisher, J. B., Scott, R. L., Burns, S. P., Diehl, J. L., Munger, J. W., Richardson, A. D.

Understanding tree transpiration variability is vital for assessing ecosystem water-use efficiency and forest health amid climate change, yet most landscape-level measurements do not differentiate individual trees. Using canopy temperature data from thermal cameras, we estimated the transpiration rates of individual trees at Harvard …


Journal: Geophysical Research Letters, Volume 51 (20): (2024). DOI: https://doi.org/10.1029/2024GL111479 Sites: US-Ha1, US-NR1
Forest Carbon Uptake As Influenced By Snowpack And Length Of Photosynthesis Season In Seasonally Snow-Covered Forests Of North America
Yang, J. C., Bowling, D. R., Smith, K. R., Kunik, L., Raczka, B., Anderegg, W. R., Bahn, M., Blanken, P. D., Richardson, A. D., Burns, S. P., Bohrer, G., Desai, A. R., Arain, M. A., Staebler, R. M., Ouimette, A. P., Munger, J. W., Litvak, M. E.


Journal: Agricultural And Forest Meteorology, Volume 353: 110054 (2024). DOI: 10.1016/j.agrformet.2024.110054 Sites: US-NR1
Energy‐Water Asynchrony Principally Determines Water Available For Runoff From Snowmelt In Continental Montane Forests
Webb, R., Knowles, J., Fox, A., Fabricus, A., Corrie, T., Mooney, K., Gallais, J., Frimpong, N., Akurugu, C., Barron‐Gafford, G., Blanken, P., Burns, S., Frank, J., Litvak, M.


Journal: Hydrological Processes, Volume 38 (10): (2024). DOI: 10.1002/hyp.15297 Sites: US-GLE, US-Mpj, US-MtB, US-NR1, US-Vcm
Coupling Of Tree Growth And Photosynthetic Carbon Uptake Across Six North American Forests
Teets, A., Moore, D. J., Alexander, M. R., Blanken, P. D., Bohrer, G., Burns, S. P., Carbone, M. S., Ducey, M. J., Fraver, S., Gough, C. M., Hollinger, D. Y., Koch, G., Kolb, T., Munger, J. W., Novick, K. A., Ollinger, S. V., Ouimette, A. P., Pederson, N., Ricciuto, D. M., Seyednasrollah, B., Vogel, C. S., Richardson, A. D.

Linking biometric measurements of stand-level biomass growth to tower-based measurements of carbon uptake—gross primary productivity and net ecosystem productivity—has been the focus of numerous ecosystem-level studies aimed to better understand the factors regulating carbon allocation to slow-turnover wood biomass pools. However, …


Journal: Journal Of Geophysical Research: Biogeosciences, Volume 127 (4): (2022). DOI: 10.1029/2021JG006690 Sites: US-Bar, US-Ha1, US-Ho1, US-MMS, US-NR1, US-UMB
Testing Stomatal Models At The Stand Level In Deciduous Angiosperm And Evergreen Gymnosperm Forests Using Clima Land (V0.1)
Wang, Y., Köhler, P., He, L., Doughty, R., Braghiere, R. K., Wood, J. D., Frankenberg, C.


Journal: Geoscientific Model Development, Volume 14 (11): 6741-6763 (2021). DOI: https://doi.org/10.5194/gmd-14-6741-2021 Sites: US-MOz, US-NR1
The Effect Of Static Pressure-Wind Covariance On Vertical Carbon Dioxide Exchange At A Windy Subalpine Forest Site
Burns, S. P., Frank, J. M., Massman, W. J., Patton, E. G., Blanken, P. D.


Journal: Agricultural And Forest Meteorology, Volume 306: 108402 (2021). DOI: 10.1016/j.agrformet.2021.108402 Sites: US-GLE, US-NR1
Accounting for canopy structure improves hyperspectral radiative transfer and sun-induced chlorophyll fluorescence representations in a new generation Earth System model
Braghiere,R.K., Wang,Y., Doughty,R., Sousa,D., Magney,T., Widlowski,J.-L., Longo,M., Bloom,A.A., Worden,J., Gentine,P., Frankenberg,C.

Three-dimensional (3D) vegetation canopy structure plays an important role in the way radiation interacts with the land surface. Accurately representing this process in Earth System models (ESMs) is crucial for the modeling of the global carbon, energy, and water cycles and hence future climate projections. Despite the importance …


Journal: Remote Sensing of Environment, Volume 261: (2021). DOI: https://doi.org/10.1016/j.rse.2021.112497 Sites: US-NR1, US-UMB
Representativeness Of Eddy-Covariance Flux Footprints For Areas Surrounding Ameriflux Sites
Chu, H., Luo, X., Ouyang, Z., Chan, W. S., Dengel, S., Biraud, S. C., Torn, M. S., Metzger, S., Kumar, J., Arain, M. A., Arkebauer, T. J., Baldocchi, D., Bernacchi, C., Billesbach, D., Black, T. A., Blanken, P. D., Bohrer, G., Bracho, R., Brown, S., Brunsell, N. A., Chen, J., Chen, X., Clark, K., Desai, A. R., Duman, T., Durden, D., Fares, S., Forbrich, I., Gamon, J. A., Gough, C. M., Griffis, T., Helbig, M., Hollinger, D., Humphreys, E., Ikawa, H., Iwata, H., Ju, Y., Knowles, J. F., Knox, S. H., Kobayashi, H., Kolb, T., Law, B., Lee, X., Litvak, M., Liu, H., Munger, J. W., Noormets, A., Novick, K., Oberbauer, S. F., Oechel, W., Oikawa, P., Papuga, S. A., Pendall, E., Prajapati, P., Prueger, J., Quinton, W. L., Richardson, A. D., Russell, E. S., Scott, R. L., Starr, G., Staebler, R., Stoy, P. C., Stuart-Haëntjens, E., Sonnentag, O., Sullivan, R. C., Suyker, A., Ueyama, M., Vargas, R., Wood, J. D., Zona, D.

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). 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
Seasonal Variability Of Forest Sensitivity To Heat And Drought Stresses: A Synthesis Based On Carbon Fluxes From North American Forest Ecosystems
Xu, B., Arain, M. A., Black, T. A., Law, B. E., Pastorello, G. Z., Chu, H.

Climate extremes such as heat waves and droughts are projected to occur more Frequently with increasing temperature and an intensified hydrological cycle. It is Important to understand and quantify how forest carbon fluxes respond to heat and drought stress. In this study, we developed a series of daily indices of sensitivity to …


Journal: Global Change Biology, Volume 26 (2): 901-918 (2020). DOI: 10.1111/gcb.14843 Sites: CA-Ca1, CA-Ca2, CA-Ca3, CA-Gro, CA-Man, CA-NS1, CA-NS2, CA-NS3, CA-NS4, CA-NS5, CA-Oas, CA-Obs, CA-Qfo, CA-SF2, CA-TP1, CA-TP2, CA-TP3, CA-TP4, US-Bar, US-Blo, US-GLE, US-Ha1, US-Ho1, US-Me2, US-Me3, US-Me6, US-MMS, US-NR1, US-Oho, US-PFa, US-Prr, US-Syv, US-UMB, US-UMd, US-WCr
Hillslope Hydrology Influences The Spatial And Temporal Patterns Of Remotely Sensed Ecosystem Productivity
Tai, X., Anderegg, W. R., Blanken, P. D., Burns, S. P., Christensen, L., Brooks, P. D.


Journal: Water Resources Research, Volume 56 (11): (2020). DOI: 10.1029/2020WR027630 Sites: US-NR1