Skip to main content
ARS Home » Plains Area » El Reno, Oklahoma » Grazinglands Research Laboratory » Forage and Livestock Production Research » Research » Publications at this Location » Publication #325572

Research Project: Integrated Forage Systems for Food and Energy Production in the Southern Great Plains

Location: Forage and Livestock Production Research

Title: Differential responses of carbon and water vapor fluxes to climate among evergreen needleleaf forests in the USA

Author
item Wagle, Pradeep - University Of Oklahoma
item Xiao, Xiangming - University Of Oklahoma
item Kolb, Thomas - Northern Arizona University
item Law, Beverly - Oregon State University
item Wharton, Sonia - Lawrence Livermore National Laboratory
item Monson, Russel - University Of Arizona
item Chen, Jiquan - Michigan State University
item Blanken, Peter - University Of Colorado
item Novick, Kimberly - Indiana University
item Dore, Sabina - University Of California
item Noormets, Asko - North Carolina State University
item Gowda, Prasanna

Submitted to: Forest Ecology and Management
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/23/2016
Publication Date: 6/15/2016
Citation: Wagle, P., Xiao, X., Kolb, T.E., Law, B.E., Wharton, S., Monson, R.K., Chen, J., Blanken, P.D., Novick, K.A., Dore, S., Noormets, A., Gowda, P. 2016. Differential responses of carbon and water vapor fluxes to climate among evergreen needleleaf forests in the USA. Ecological Processes. DOI 10.1186/s13717-016-0053-5.

Interpretive Summary: Investigating the response of carbon uptake (net ecosystem CO2 exchange, NEE) and evapotranspiration (ET) to major climatic conditions at multiple timescales and sites within widely distributed diverse evergreen needle leaf forests (ENFs) is necessary to move beyond site-level measurements and into realistic carbon and water budgets estimates over regions or continents. We observed large variability in NEE and ET among ENFs. However, spatial (site-to-site) variability was larger for NEE than ET. Responses of NEE and ET to climate variables were different across climatic zones. In particular, the maximum NEE and ET occurred at lower ranges of air temperature for ENF sites in semi-arid and Mediterranean climate than in sites with warm and humid summers. Our results necessitate a more refined parameterization within the ENF plant functional type to improve model predictions of carbon and water vapor fluxes at large spatial scales.

Technical Abstract: Understanding of differences in carbon and water vapor fluxes of spatially distributed evergreen needle leaf forests (ENFs) is crucial to accurately estimating regional carbon and water budgets and when predicting the responses of ENFs to future climate. We investigated cross-site variability in carbon uptake and evapotranspiration (ET) and the underlying controlling mechanisms at ten AmeriFlux ENF sites. Spatial (site-to-site) variability was larger for carbon uptake than ET as we found larger differences in the net ecosystem CO2 exchange (NEE) spectra than in the ET spectra across sites. The wavelet cospectra between ET and climate variables was similar at all sites, while the wavelet cospectra between NEE and climate variables was highest in semi-arid and Mediterranean sites, indicating closer coupling between NEE and climatic drivers in these sites. Consequently, we observed larger variability in NEE and greater coupling between NEE and ET in semi-arid and Mediterranean sites than in sites with warm and humid summers. Responses of NEE and ET to air temperature (Ta) varied across climatic zones. In particular, the maximum NEE and ET occurred at lower ranges of Ta for ENF sites in semi-arid and Mediterranean climate than in sites with warm and humid summers. Maximum and seasonally integrated enhanced vegetation index (EVI) was strongly related to spatial variations in carbon and water vapor fluxes, illustrating application of EVI for understanding of spatial variability in carbon and water vapor fluxes of ENFs. Our results necessitate a more refined parameterization within the ENF plant functional type to improve model predictions of carbon and water vapor fluxes at large spatial scales.