Abstract

Gross primary productivity (GPP) often is estimated at regional and global scales by multiplying the amount of photosynthetically active radiation (PAR) absorbed by the plant canopy (PARa) by light-use efficiency (e g ; GPP/PARa). Mass flux techniques are being used to calculate e g . Flux-based estimates of e g depend partly on how PAR absorption by plants is modeled as a function of leaf area index (LAI). We used CO2 flux measurements from three native grasslands in the Great Plains of USA to determine how varying the value of the radiation extinction coefficient (k) that is used to calculate PARa from LAI affected variability in estimates of e g for each week. The slope of linear GPP–PARa regression, an index of e g , differed significantly among the 18 site-years of data, indicating that inter-annual differences in e g contributed to the overall variability in e g values. GPP–PARa slopes differed among years and sites regardless of whether k was assigned a fixed value or varied as an exponential function of LAI. Permitting k to change with LAI reduced overall variability in e g , reduced the slope of a negative linear regression between seasonal means of e g and potential evapotranspiration (PET), and clarified the contribution of inter-annual differences in precipitation to variation in e g . Our results imply that greater attention be given to defining dynamics of the k coefficient for ecosystems with low LAI and that PET and precipitation be used to constrain the e g values employed in light-use efficiency algorithms to calculate GPP for Great Plains grasslands.

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