1982–2010 Trends of Light Use Efficiency and Inherent Water Use Efficiency in African vegetation: Sensitivity to Climate and Atmospheric CO2 Concentrations

dc.contributor.authorTraore, Abdoul Khadre
dc.contributor.authorCiais, Philippe
dc.contributor.authorVuichard, Nicolas
dc.contributor.authorMcBean, Natasha
dc.contributor.authorDardel, Cecile
dc.contributor.authorPoulter, Benjamin
dc.contributor.authorPiao, Shilong
dc.contributor.authorFisher, Joshua
dc.contributor.authorViovy, Nicolas
dc.contributor.authorJung, Martin
dc.contributor.authorMyneni, Ranga B.
dc.date.accessioned2014-11-21T20:45:17Z
dc.date.available2014-11-21T20:45:17Z
dc.date.issued2014
dc.descriptionhttp://creativecommons.org/licenses/by/4.0/legalcodeen_US
dc.description.abstractLight and water use by vegetation at the ecosystem level, are key components for understanding the carbon and water cycles particularly in regions with high climate variability and dry climates such as Africa. The objective of this study is to examine recent trends over the last 30 years in Light Use Efficiency (LUE) and inherent Water Use Efficiency (iWUE*) for the major biomes of Africa, including their sensitivities to climate and CO2. LUE and iWUE* trends are analyzed using a combination of NOAA-AVHRR NDVI3g and fAPAR3g, and a data-driven model of monthly evapotranspiration and Gross Primary Productivity (based on flux tower measurements and remote sensing fAPAR, yet with no flux tower data in Africa) and the ORCHIDEE (ORganizing Carbon and Hydrology In Dynamic EcosystEms) process-based land surface model driven by variable CO2 and two different gridded climate fields. The iWUE* data product increases by 10%–20% per decade during the 1982–2010 period over the northern savannas (due to positive trend of vegetation productivity) and the central African forest (due to positive trend of vapor pressure deficit). In contrast to the iWUE*, the LUE trends are not statistically significant. The process-based model simulations only show a positive linear trend in iWUE* and LUE over the central African forest. Additionally, factorial model simulations were conducted to attribute trends in iWUE and LUE to climate change and rising CO2 concentrations. We found that the increase of atmospheric CO2 by 52.8 ppm during the period of study explains 30%–50% of the increase in iWUE* and >90% of the LUE trend over the central African forest. The modeled iWUE* trend exhibits a high sensitivity to the climate forcing and environmental conditions, whereas the LUE trend has a smaller sensitivity to the selected climate forcing.en_US
dc.description.sponsorshipThis work is supported by the ClimAfrica project funded by the European Commission under the 7th Framework Programme (FP7). We are grateful to the GIMMS group for sharing the NDVI3g data (we thank Zaichun Zhu and Ranga B. Myneni). Through Martin Jung, we are thankful to the Department Biogeochemical Integration at the Max Planck Institute for Biogeochemistry for providing Monthly gross primary productivity and evapotranspiration deduced from FLUXNET data from the “La-Thuile-2007” synthesis effort.en_US
dc.identifier.citationTraore, Abdoul Khadre, Philippe Ciais, Nicolas Vuichard, Natasha McBean, Cecile Dardel, Benjamin Poulter, Shilong Piao, Joshua B. Fisher, NIcolas Viovy, Martin Jung, and Ranga Myneni. "1982-2010 Trends of Light Use Efficiency and Inherent Water Use Efficiency in African vegetation: Sensitivity to Climate and Atmospheric CO2 Concentrations." Remote Sensing 6, no. 9 (2014): 8923-8944. http://dx.doi.org/10.3390/rs6098923en_US
dc.identifier.issn2072-4292
dc.identifier.urihttp://dx.doi.org/10.3390/rs6098923
dc.identifier.urihttps://scholarworks.montana.edu/handle/1/8730
dc.publisherMDPIen_US
dc.subjectRemote sciencesen_US
dc.subjectEcologyen_US
dc.title1982–2010 Trends of Light Use Efficiency and Inherent Water Use Efficiency in African vegetation: Sensitivity to Climate and Atmospheric CO2 Concentrationsen_US
dc.typeArticleen_US
mus.citation.extentfirstpage8923en_US
mus.citation.extentlastpage8944en_US
mus.citation.issue9en_US
mus.citation.journaltitleRemote Sensingen_US
mus.citation.volume6en_US
mus.contributor.orcidPoulter, Benjamin|0000-0002-9493-8600en_US
mus.identifier.categoryLife Sciences & Earth Sciencesen_US
mus.identifier.doi10.3390/rs6098923en_US
mus.relation.collegeCollege of Letters & Science
mus.relation.collegeCollege of Letters & Sciencesen_US
mus.relation.departmentEcology.en_US
mus.relation.universityMontana State University - Bozemanen_US

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