[1] In the southeastern United States (SE), the conversion of abandoned agricultural land to forests is the dominant feature of land-cover change. However, few attempts have been made to quantify the impact of such conversion on surface temperature. Here, this issue is explored experimentally and analytically in three adjacent ecosystems (a grass-covered old-field, OF, a planted pine forest, PP, and a hardwood forest, HW) representing a successional chronosequence in the SE. The results showed that changes in albedo alone can warm the surface by 0.9°C for the OF-to-PP conversion, and 0.7°C for the OF-to-HW conversion on annual time scales. However, changes in eco-physiological and aerodynamic attributes alone can cool the surface by 2.9 and 2.1°C, respectively. Both model and measurements consistently suggest a stronger over-all surface cooling for the OF-to-PP conversion, and the reason is attributed to leaf area variations and its impacts on boundary layer conductance. Citation: Juang, J.-Y., G. Katul, M. Siqueira, P. Stoy, and K. Novick (2007), Separating the effects of albedo from eco-physiological changes on surface temperature along a successional chronosequence in the southeastern United States,

We combined Eddy-covariance measurements with a linear perturbation analysis to isolate the relative contribution of physical and biological drivers on evapotranspiration (ET) in three ecosystems representing two end-members and an intermediate stage of a successional gradient in the southeastern US (SE). The study ecosystems, an abandoned agricultural field [old field (OF)], an early successional planted pine forest (PP), and a late-successional hardwood forest (HW), exhibited differential sensitivity to the wide range of climatic and hydrologic conditions encountered over the 4-year measurement period, which included mild and severe droughts and an ice storm. ET and modeled transpiration differed by as much as 190 and 270 mm yr À1 , respectively, between years for a given ecosystem. Soil water supply, rather than atmospheric demand, was the principal external driver of interannual ET differences. ET at OF was sensitive to climatic variability, and results showed that decreased leaf area index (L) under mild and severe drought conditions reduced growing season (GS) ET (ET GS ) by ca. 80 mm compared with a year with normal precipitation. Under wet conditions, higher intrinsic stomatal conductance (g s ) increased ET GS by 50 mm. ET at PP was generally larger than the other ecosystems and was highly sensitive to climate; a 50 mm decrease in ET GS due to the loss of L from an ice storm equaled the increase in ET from high precipitation during a wet year. In contrast, ET at HW was relatively insensitive to climatic variability. Results suggest that recent management trends toward increasing the land-cover area of PP-type ecosystems in the SE may increase the sensitivity of ET to climatic variability.

We measured net ecosystem CO 2 exchange (NEE) using the eddy covariance (EC) technique for 4 years at adjoining old field (OF), planted pine (PP) and hardwood forest (HW) ecosystems in the Duke Forest, NC. To compute annual sums of NEE and its components-gross ecosystem productivity (GEP) and ecosystem respiration (RE)-different 'flux partitioning' models (FPMs) were tested and the resulting C flux estimates were compared against published estimates from C budgeting approaches, inverse models, physiology-based forward models, chamber respiration measurements, and constraints on assimilation based on sapflux and evapotranspiration measurements. Our analyses demonstrate that the more complex FPMs, particularly the 'non-rectangular hyperbolic method', consistently produced the most reasonable C flux estimates. Of the FPMs that use nighttime data to estimate RE, one that parameterized an exponential model over short time periods generated predictions that were closer to expected flux values. To explore how much 'new information' was injected into the data by the FPMs, we used formal information theory methods and computed the Shannon entropy for: (1) the probability density, to assess alterations to the flux measurement distributions, and (2) the wavelet energy spectra, to assess alterations to the internal autocorrelation within the NEE time series. Based on this joint analysis, gap-filling had little impact on the IC of daytime data, but gap-filling significantly altered nighttime data in both the probability and wavelet spectral domains.

Grasslands cover about 40% of the ice-free global terrestrial surface, but their contribution to local and regional water and carbon fluxes and sensitivity to climatic perturbations such as drought remains uncertain. Here, we assess the direction and magnitude of net ecosystem carbon exchange (NEE) and its components, ecosystem carbon assimilation ( A(c)) and ecosystem respiration ( R(E)), in a southeastern United States grassland ecosystem subject to periodic drought and harvest using a combination of eddy-covariance measurements and model calculations. We modeled A(c) and evapotranspiration (ET) using a big-leaf canopy scheme in conjunction with ecophysiological and radiative transfer principles, and applied the model to assess the sensitivity of NEE and ET to soil moisture dynamics and rapid excursions in leaf area index (LAI) following grass harvesting. Model results closely match eddy-covariance flux estimations on daily, and longer, time steps. Both model calculations and eddy-covariance estimates suggest that the grassland became a net source of carbon to the atmosphere immediately following the harvest, but a rapid recovery in LAI maintained a marginal carbon sink during summer. However, when integrated over the year, this grassland ecosystem was a net C source (97 g C m(-2) a(-1)) due to a minor imbalance between large A(c) (-1,202 g C m(-2) a(-1)) and R(E) (1,299 g C m(-2) a(-1)) fluxes. Mild drought conditions during the measurement period resulted in many instances of low soil moisture (theta<0.2 m(3)m(-3)), which influenced A(c) and thereby NEE by decreasing stomatal conductance. For this experiment, low theta had minor impact on R(E). Thus, stomatal limitations to A(c) were the primary reason that this grassland was a net C source. In the absence of soil moisture limitations, model calculations suggest a net C sink of -65 g C m(-2) a(-1) assuming the LAI dynamics and physiological properties are unaltered. These results, and the results of other studies, suggest that perturbations to the hydrologic cycle are key determinants of C cycling in grassland ecosystems.