Mario Siqueira

Separating the effects of albedo from eco‐physiological changes on surface temperature along a successional chronosequence in the southeastern United States

[1] InthesoutheasternUnitedStates(SE),theconversionof 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 0.9C for the OF-to-PP conversion, and 0.7C 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 2.1C, 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, Geophys. Res. Lett., 34, L21408, doi:10.1029/2007GL031296.

Onset of water stress, hysteresis in plant conductance, and hydraulic lift: Scaling soil water dynamics from millimeters to meters

[1] Estimation of water uptake by plants and subsequent water stress are complicated by the need to resolve the soil-plant hydrodynamics at scales ranging from millimeters to meters. Using a simplified homogenization technique, the three-dimensional (3-D) soil water movement dynamics can be reduced to solving two 1-D coupled Richards’ equations, one for the radial water movement toward rootlets (mesoscale, important for diurnal cycle) and a second for vertical water motion (macroscale, relevant to interstorm timescales). This approach allows explicit simulation of known features of root uptake such as diurnal hysteresis in canopy conductance, hydraulic lift, and compensatory root water uptake during extended drying cycles. A simple scaling analysis suggests that the effectiveness of the hydraulic lift is mainly controlled by the root vertical distribution, while the soil moisture levels at which hydraulic lift is most effective is dictated by soil hydraulic properties and surrogates for atmospheric water vapor demand.

Soil Moisture Feedbacks on Convection Triggers: The Role of Soil–Plant Hydrodynamics

Abstract The linkages between soil moisture dynamics and convection triggers, defined here as the first crossing between the boundary layer height (hBL) and lifting condensation level (hLCL), are complicated by a large number of interacting processes occurring over a wide range of space and time scales. To progress on this problem, a soil–plant hydrodynamics model was coupled to a simplified ABL budget to explore the feedback of soil moisture on convection triggers. The soil–plant hydraulics formulation accounted mechanistically for features such as root water uptake, root water redistribution, and midday stomatal closure, all known to affect diurnal cycles of surface fluxes and, consequently, ABL growth. The ABL model considered the convective boundary layer as a slab with a discontinuity at the inversion layer. The model was parameterized using the wealth of data already collected for a maturing Loblolly pine plantation situated in the southeastern United States. A 30-day dry-down simulation was used to...

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.

Quantifying organization of atmospheric turbulent eddy motion using nonlinear time series analysis

Using three methods from nonlinear dynamics, we contrast the level of organization inthe vertical wind velocity (w) time series collected in the atmospheric surface layer(ASL) and the canopy sublayer (CSL) for a wide range of atmospheric stability (ξ)conditions. The nonlinear methods applied include a modified Shannon entropy, waveletthresholding, and mutual information content. Time series measurements collected overa pine forest, a hardwood forest, a grass-covered forest clearing, and a bare soil, desertsurface were used for this purpose. The results from applying all three nonlinear timeseries measures suggest that w in the CSL is more organized than that in the ASL, and that as the flows in both layers evolve from near-neutral to near-convective conditions, the level of organization increases. Furthermore, we found that the degree of organization in w associated with changes in ξ is more significant than the transition from CSL to ASL.

Quantifying net ecosystem exchange by multilevel ecophysiological and turbulent transport models

To quantify the interplay between scalar sources and sinks (Sc) and net ecosystem exchange (NEE), ‘‘forward’’ and ‘‘inverse’’ approaches have been proposed. The canonical form of forward approaches is a one-dimensional ecophysiological-radiative transfer scheme coupled to turbulent transport theory. In contrast, inverse approaches strictly rely on turbulent transport theory and mean scalar concentration as their primary input to infer Sc and NEE. While the formulation of both approaches have evolved over the past decade, no systematic comparison between them was undertaken for the same data set, and over a wide range of atmospheric conditions. Our objective is to compare the predicted Sc and NEE from these two approaches with eddy-covariance measurements. The results show that the forward method outperformed all three inverse methods for unstable and neutral conditions on short time scales (� 30 min) but yielded comparable results at longer time scales. Poor agreement was obtained under stable conditions for all models. Hence, for modeling event-based flux variations, forward models are preferred. Since the forward method requires detailed knowledge of ecophysiological, drag, radiative transfer and other canopy attributes, all of which are difficult to obtain on a routine basis, a symbiotic use of forward and inverse approaches is most advantageous. � 2002 Elsevier Science Ltd. All rights reserved.

Predicting Scalar Source-Sink and Flux Distributions Within a Forest Canopy Using a 2-D Lagrangian Stochastic Dispersion Model

This study proposes a two-dimensional Lagrangian stochastic dispersion model forestimating spatial and temporal variation of scalar sources, sinks, and fluxes withina forest canopy. Carbon dioxide and heat dispersion experiments were conducted forfield testing the model. These experiments also provided data for field testing a newlydeveloped one-dimensional Lagrangian analytical dispersion model. It was found that these two models produce similar scalar source-sinkand flux distribution patterns. Comparing with CO2 flux measurements, the one-dimensional model performed as well as the two-dimensional model even whenthe fetch is short (≈100 m). To drive these Lagrangian models, velocitystatistics through the canopy volume must be specified a priori. The sensitivity of thecomputed sources, sinks, and fluxes to the description of the flow statistics was furtherexamined. All in all, we found good agreement between model predicted andeddy-correlation measured CO2 and sensible heat fluxes.

Dispersal of Transgenic Conifer Pollen

Long-distance dispersal (LDD) of pollen in conifers presents a risk for transgenic escape into unmanaged forests. Here, we report simulations of transgenic pollen dispersal and LDD from genetically modified forests using a mechanistic turbulent dispersal model. The dispersal model is based on coupled Eulerian-Lagrangrian closure (CELC) principles that model turbulent velocity excursions within the canopy. Contrary to recent studies and measurements from annual crop canopies, which reported maximum pollen dispersal distances ranging from 6 m to 800 m, conifer pollen LDD can readily exceed 8 km in less than 1 hour without escaping the atmospheric boundary layer. These LDD estimates were conducted using a conservative terminal velocity (Vt) of 0.07 m s. When using a Vt of 0.03 m s ± 0.02 m s, which is characteristic of pine species pollen, LDD increased by almost a factor of 3, from about 8 to 21 km for a stand at its reproductive onset and from about 13 km to 33 km for a stand at nearharvesting age. The fact that pollen can travel such distances without escaping the ABL has important consequences about viability and ecological risk assessment and gene flow.

Multi-scale model inter-comparisons of CO2 and H2O exchange rates in inhomogeneous canopies

Models for the exchange of CO2 and H2O between the atmosphere and terrestrial ecosystems are needed for assessing the effects of anthropogenic CO2 emissions on atmospheric concentration of CO2. To date, no single model captures the entire spectrum of variability of the processes affecting CO2 and H2O transfer and storage within terrestrial ecosystems; rather, a modular approach is adopted in which the forcing and response variables are coupled over an inherent or assumed time scale that is then integrated to longer time scales. The effect of such modular parameterization of the “fast” processes and their cross-scale interaction with the slowly varying processes on long-term carbon sequestration remains a subject of investigation. Here, we compared four existing process-based stand-level models of varying complexity (3-PG, PnET II, Biome-BGC, and SECRETS-3PG) and a newly proposed nested model with 4 years of eddy-covariance water vapor (LE) and CO2 (Fc) fluxes measured above a maturing loblolly pine forest near Durham, North Carolina, USA. The nested model resolves the “fast” CO2 and H2O exchange processes using canopy turbulence theories and radiative transfer principles while slow evolving processes were resolved using standard carbon allocation methods modified to improve leaf phenology. The model comparisons showed strong linkages between carbon production and LAI variability, which necessitates the use of multi-layer models to reproduce the seasonal dynamics of LAI, Net Ecosystem Exchange (NEE) and LE. However, our findings suggest that increasing model complexity, often justified for resolving faster processes, does not necessarily translate into improved predictive skills at all time scales, especially annual and longer. To address this spectral discrepancy, we performed a variance component analysis of NEE at annual time scales that revealed that most of the inconsistency seems to originate from different model responses to drought. None of the models tested here adequately captured drought effects on water and CO2 fluxes. Furthermore, the good spectral performance of some models on inter-annual time scales appears to stem from erroneously capturing LAI dynamics and from over sensitivity to droughts that injects unrealistic variability at longer time scales.