Vapor pressure deficit helps explain biogenic volatile organic compound fluxes from the forest floor and canopy of a temperate deciduous forest.

Biogenic volatile organic compounds (BVOCs) play critical roles in ecological and earth-system processes. Ecosystem BVOC models rarely include soil and litter fluxes and their accuracy is often challenged by BVOC dynamics during periods of rapid ecosystem change like spring leaf out. We measured BVOC concentrations within the air space of a mixed deciduous forest and used a hybrid Lagrangian/Eulerian canopy transport model to estimate BVOC flux from the forest floor, canopy, and whole ecosystem during spring. Canopy flux measurements were dominated by a large methanol source and small isoprene source during the leaf-out period, consistent with past measurements of leaf ontogeny and theory, and indicative of a BVOC flux situation rarely used in emissions model testing. The contribution of the forest floor to whole-ecosystem BVOC flux is conditional on the compound of interest and is often non-trivial. We created linear models of forest floor, canopy, and whole-ecosystem flux for each study compound and used information criteria-based model selection to find the simplest model with the best fit. Most published BVOC flux models do not include vapor pressure deficit (VPD), but it entered the best canopy, forest floor, and whole-ecosystem BVOC flux model more than any other study variable in the present study. Since VPD is predicted to increase in the future, future studies should investigate how it contributes to BVOC flux through biophysical mechanisms like evaporative demand, leaf temperature and stomatal function.

On the difference in the net ecosystem exchange of CO2 between deciduous and evergreen forests in the southeastern United States.

The southeastern United States is experiencing a rapid regional increase in the ratio of pine to deciduous forest ecosystems at the same time it is experiencing changes in climate. This study is focused on exploring how these shifts will affect the carbon sink capacity of southeastern US forests, which we show here are among the strongest carbon sinks in the continental United States. Using eight-year-long eddy covariance records collected above a hardwood deciduous forest (HW) and a pine plantation (PP) co-located in North Carolina, USA, we show that the net ecosystem exchange of CO2 (NEE) was more variable in PP, contributing to variability in the difference in NEE between the two sites (ΔNEE) at a range of timescales, including the interannual timescale. Because the variability in evapotranspiration (ET) was nearly identical across the two sites over a range of timescales, the factors that determined the variability in ΔNEE were dominated by those that tend to decouple NEE from ET. One such factor was water use efficiency, which changed dramatically in response to drought and also tended to increase monotonically in nondrought years (P < 0.001 in PP). Factors that vary over seasonal timescales were strong determinants of the NEE in the HW site; however, seasonality was less important in the PP site, where significant amounts of carbon were assimilated outside of the active season, representing an important advantage of evergreen trees in warm, temperate climates. Additional variability in the fluxes at long-time scales may be attributable to slowly evolving factors, including canopy structure and increases in dormant season air temperature. Taken together, study results suggest that the carbon sink in the southeastern United States may become more variable in the future, owing to a predicted increase in drought frequency and an increase in the fractional cover of southern pines.

Variability in net ecosystem exchange from hourly to inter-annual time scales at adjacent pine and hardwood forests: a wavelet analysis.

Orthonormal wavelet transformation (OWT) is a computationally efficient technique for quantifying underlying frequencies in nonstationary and gap-infested time series, such as eddy-covariance-measured net ecosystem exchange of CO2 (NEE). We employed OWT to analyze the frequency characteristics of synchronously measured and modeled NEE at adjacent pine (PP) and hardwood (HW) ecosystems. Wavelet cospectral analysis showed that NEE at PP was more correlated to light and vapor pressure deficit at the daily time scale, and NEE at HW was more correlated to leaf area index (LAI) and temperature, especially soil temperature, at seasonal time scales. Models were required to disentangle the impacts of environmental drivers on the components of NEE, ecosystem carbon assimilation (Ac) and ecosystem respiration (RE). Sensitivity analyses revealed that using air temperature rather than soil temperature in RE models improved the modeled wavelet spectral frequency response on time scales longer than 1 day at both ecosystems. Including LAI improved RE model fit on seasonal time scales at HW, and incorporating parameter variability improved the RE model response at annual time scales at both ecosystems. Resolving variability in canopy conductance, rather than leaf-internal CO2, was more important for modeling Ac at both ecosystems. The PP ecosystem was more sensitive to hydrologic variables that regulate canopy conductance: vapor pressure deficit on weekly time scales and soil moisture on seasonal to interannual time scales. The HW ecosystem was sensitive to water limitation on weekly time scales. A combination of intrinsic drought sensitivity and non-conservative water use at PP was the basis for this response. At both ecosystems, incorporating variability in LAI was required for an accurate spectral representation of modeled NEE. However, nonlinearities imposed by canopy light attenuation were of little importance to spectral fit. The OWT revealed similarities and differences in the scale-wise control of NEE by vegetation with implications for model simplification and improvement.

Are ecosystem carbon inputs and outputs coupled at short time scales? A case study from adjacent pine and hardwood forests using impulse-response analysis.

A number of recent studies have attributed a large proportion of soil respiration (R(soil)) to recently photoassimilated carbon (C). Time lags (tau(PR)) associated with these pulses of photosynthesis and responses of R(soil) have been found on time scales of hours to weeks for different ecosystems, but most studies find evidence for tau(PR) on the order of 1-5 d. We showed that such time scales are commensurate with CO(2) diffusion time scales from the roots to the soil surface, and may thus be independent from photosynthetic pulses. To further quantify the role of physical (i.e. edaphic) and biological (i.e. vegetative) controls on such lags, we investigated tau(PR) at adjacent planted pine (PP) and hardwood (HW) forest ecosystems over six and four measurement years, respectively, using both autocorrelation analysis on automated soil surface flux measurements and their lagged cross-correlations with drivers for and surrogates of photosynthesis. Evidence for tau(PR) on the order of 1-3 d was identified in both ecosystems and using both analyses, but this lag could not be attributed to recently photoassimilated C because the same analysis yielded comparable lags at HW during leaf-off periods. Future efforts to model ecosystem C inputs and outputs in a pulse-response framework must combine measurements of transport in the physical and biological components of terrestrial ecosystems.