## 1. Introduction

[2] Carbon exchanges between the global biosphere and the atmosphere are critical to determining the CO_{2} concentration of the atmosphere and its coupled influence on the Earth's climate. Net ecosystem CO_{2} exchange (NEE) reflects the balance between two large CO_{2} fluxes, gross photosynthesis and ecosystem respiration (*R*_{e}), and is currently being measured at over 200 sites worldwide as part of regional CO_{2} flux networks [*Baldocchi et al.*, 2001]. NEE is typically measured with the eddy covariance method, which provides a direct measurement of the turbulent CO_{2} flux above the canopy. However, eddy covariance provides a net flux, and seasonal or interannual dynamics in NEE cannot be adequately explained without a means to partition the net flux into its component gross fluxes.

[3] A common model used to gain insight into the component fluxes of NEE can be stated as:

where *F* is NEE, *Q* is the photosynthetic photon flux density, *R*_{e} is the ecosystem respiration rate, *F*_{∞} is the light-saturated net ecosystem CO_{2} flux, and α is the light-use efficiency of NEE (or apparent quantum yield). It is not possible to obtain a true gross ecosystem CO_{2} exchange flux from equation (1), but it is possible to use equation (1) to partition NEE into low light regimes where effects on *R*_{e} exert primary influences on NEE and high light regimes where effects on photosynthesis exert primary influences on NEE. This model has been used in a number of past studies to analyze the response of NEE to light intensity, and to partition NEE into its component processes [e.g., *Wofsy et al.*, 1993; *Ruimy et al.*, 1995; *Barcza*, 2001]. In these studies, it is usually assumed that the daytime ecosystem respiration is an exponential function of temperature, *R*_{e} = *A*e^{BT}, where *A* and *B* can be estimated by nighttime NEE and temperature measurements. However, some apparent uncertainties associated with this approach are: (1) Nighttime NEE can not be accurately measured by the eddy covariance technique especially during calm nights [*Goulden et al.*, 1996; *Yi et al.*, 2000]; (2) Daytime *R*_{e} is different from nighttime *R*_{e} because of light-induced inhibition of leaf respiration [*Brooks and Farquhar*, 1985]; (3) Daytime *R*_{e} may not have the expected exponential relationship with temperature [*Tjoelker et al.*, 2001].

[4] We developed a new nonparametric statistical method that allowed us to use equation (1) in an inverse mode; we constrain the relationship between *F* and *Q* using data from the four forest sites, and then use a nonparametric regression approach to obtain optimized estimates of the parameters in equation (1) (*R*_{e}, *F*_{∞} and α). This new nonparametric statistical method provides an independent way to investigate the temperature dependence of components of NEE. The results of our study provide the insight needed to improve representation of the effect of temperature on NEE in regional and global carbon budget models.