Gabriel G. Katul

FLUXNET: A New Tool to Study the Temporal and Spatial Variability of Ecosystem-Scale Carbon Dioxide, Water Vapor, and Energy Flux Densities

FLUXNET is a global network of micrometeorological flux measurement sites that measure the exchanges of carbon dioxide, water vapor, and energy between the biosphere and atmosphere. At present over 140 sites are operating on a long-term and continuous basis. Vegetation under study includes temperate conifer and broadleaved (deciduous and evergreen) forests, tropical and boreal forests, crops, grasslands, chaparral, wetlands, and tundra. Sites exist on five continents and their latitudinal distribution ranges from 70°N to 30°S. FLUXNET has several primary functions. First, it provides infrastructure for compiling, archiving, and distributing carbon, water, and energy flux measurement, and meteorological, plant, and soil data to the science community. (Data and site information are available online at the FLUXNET Web site, http://www-eosdis.ornl.gov/FLUXNET/.) Second, the project supports calibration and flux intercomparison activities. This activity ensures that data from the regional networks are intercomparable. And third, FLUXNET supports the synthesis, discussion, and communication of ideas and data by supporting project scientists, workshops, and visiting scientists. The overarching goal is to provide information for validating computations of net primary productivity, evaporation, and energy absorption that are being generated by sensors mounted on the NASA Terra satellite. Data being compiled by FLUXNET are being used to quantify and compare magnitudes and dynamics of annual ecosystem carbon and water balances, to quantify the response of stand-scale carbon dioxide and water vapor flux densities to controlling biotic and abiotic factors, and to validate a hierarchy of soil–plant–atmosphere trace gas exchange models. Findings so far include 1) net CO 2 exchange of temperate broadleaved forests increases by about 5.7 g C m −2 day −1 for each additional day that the growing season is extended; 2) the sensitivity of net ecosystem CO 2 exchange to sunlight doubles if the sky is cloudy rather than clear; 3) the spectrum of CO 2 flux density exhibits peaks at timescales of days, weeks, and years, and a spectral gap exists at the month timescale; 4) the optimal temperature of net CO 2 exchange varies with mean summer temperature; and 5) stand age affects carbon dioxide and water vapor flux densities.

Soil fertility limits carbon sequestration by forest ecosystems in a CO2-enriched atmosphere.

Northern mid-latitude forests are a large terrestrial carbon sink. Ignoring nutrient limitations, large increases in carbon sequestration from carbon dioxide (CO2) fertilization are expected in these forests. Yet, forests are usually relegated to sites of moderate to poor fertility, where tree growth is often limited by nutrient supply, in particular nitrogen. Here we present evidence that estimates of increases in carbon sequestration of forests, which is expected to partially compensate for increasing CO2 in the atmosphere, are unduly optimistic. In two forest experiments on maturing pines exposed to elevated atmospheric CO2, the CO2-induced biomass carbon increment without added nutrients was undetectable at a nutritionally poor site, and the stimulation at a nutritionally moderate site was transient, stabilizing at a marginal gain after three years. However, a large synergistic gain from higher CO2 and nutrients was detected with nutrients added. This gain was even larger at the poor site (threefold higher than the expected additive effect) than at the moderate site (twofold higher). Thus, fertility can restrain the response of wood carbon sequestration to increased atmospheric CO2. Assessment of future carbon sequestration should consider the limitations imposed by soil fertility, as well as interactions with nitrogen deposition.

Mechanisms of long-distance dispersal of seeds by wind

Long-distance dispersal (LDD) is central to species expansion following climate change, re-colonization of disturbed areas and control of pests. The current paradigm is that the frequency and spatial extent of LDD events are extremely difficult to predict. Here we show that mechanistic models coupling seed release and aerodynamics with turbulent transport processes provide accurate probabilistic descriptions of LDD of seeds by wind. The proposed model reliably predicts the vertical distribution of dispersed seeds of five tree species observed along a 45-m high tower in an eastern US deciduous forest. Simulations show that uplifting above the forest canopy is necessary and sufficient for LDD, hence, they provide the means to define LDD quantitatively rather than arbitrarily. Seed uplifting probability thus sets an upper bound on the probability of long-distance colonization. Uplifted yellow poplar seeds are on average lighter than seeds at the forest floor, but also include the heaviest seeds. Because uplifting probabilities are appreciable (as much as 1–5%), and tree seed crops are commonly massive, some LDD events will establish individuals that can critically affect plant dynamics on large scales.

An approximate analytical model for footprint estimation of scalar fluxes in thermally stratified atmospheric flows

An approximate analytical model was developed to estimate scalar flux footprint in thermally stratified atmospheric surface layer flows. The proposed model was based on a combination of Lagrangian stochastic dispersion model results and dimensional analysis. The main advantage of this model is its ability to analytically relate atmospheric stability, measurement height, and surface roughness length to flux and footprint. Flux estimation by the proposed model was in good agreement with those calculated by detailed Eulerian and Lagrangian models. Measured water vapor fluxes collected along a downwind transect of a transition from a desert to an irrigated potato site were also used to assess the proposed model performance in the field. It was found that the model well reproduced the measured flux evolution with downwind distance.

THE EFFECT OF VEGETATION DENSITY ON CANOPY SUB-LAYER TURBULENCE

The canonical form of atmospheric flows near theland surface, in the absence of a canopy, resembles a rough-wallboundary layer. However, in the presence of an extensive and densecanopy, the flow within and just above the foliage behaves as aperturbed mixing layer. To date, no analogous formulation existsfor intermediate canopy densities. Using detailed laser Dopplervelocity measurements conducted in an open channel over a widerange of canopy densities, a phenomenological model that describesthe structure of turbulence within the canopy sublayer (CSL) isdeveloped. The model decomposes the space within the CSL intothree distinct zones: the deep zone in which the flow field isshown to be dominated by vortices connected with vonKármán vortex streets, butperiodically interrupted by strong sweep events whose features areinfluenced by canopy density. The second zone, which is near thecanopy top, is a superposition of attached eddies andKelvin–Helmholtz waves produced by inflectional instability in themean longitudinal velocity profile. Here, the relative importanceof the mixing layer and attached eddies are shown to vary withcanopy density through a coefficient α. We show that therelative enhancement of turbulent diffusivity over its surface-layer value near the canopy top depends on the magnitude ofα. In the uppermost zone, the flow follows the classicalsurface-layer similarity theory. Finally, we demonstrate that thecombination of this newly proposed length scale and first-orderclosure models can accurately reproduce measured mean velocity andReynolds stresses for a wide range of roughness densities. Withrecent advancement in remote sensing of canopy morphology, thismodel offers a promising physically based approach to connect theland surface and the atmosphere without resorting to empiricalmomentum roughness lengths.

Observed increase in local cooling effect of deforestation at higher latitudes

Deforestation in mid- to high latitudes is hypothesized to have the potential to cool the Earth’s surface by altering biophysical processes. In climate models of continental-scale land clearing, the cooling is triggered by increases in surface albedo and is reinforced by a land albedo–sea ice feedback. This feedback is crucial in the model predictions; without it other biophysical processes may overwhelm the albedo effect to generate warming instead. Ongoing land-use activities, such as land management for climate mitigation, are occurring at local scales (hectares) presumably too small to generate the feedback, and it is not known whether the intrinsic biophysical mechanism on its own can change the surface temperature in a consistent manner. Nor has the effect of deforestation on climate been demonstrated over large areas from direct observations. Here we show that surface air temperature is lower in open land than in nearby forested land. The effect is 0.85 ± 0.44 K (mean ± one standard deviation) northwards of 45° N and 0.21 ± 0.53 K southwards. Below 35° N there is weak evidence that deforestation leads to warming. Results are based on comparisons of temperature at forested eddy covariance towers in the USA and Canada and, as a proxy for small areas of cleared land, nearby surface weather stations. Night-time temperature changes unrelated to changes in surface albedo are an important contributor to the overall cooling effect. The observed latitudinal dependence is consistent with theoretical expectation of changes in energy loss from convection and radiation across latitudes in both the daytime and night-time phase of the diurnal cycle, the latter of which remains uncertain in climate models.

Evapotranspiration: A process driving mass transport and energy exchange in the soil‐plant‐atmosphere‐climate system

[1] The role of evapotranspiration (ET) in the global, continental, regional, and local water cycles is reviewed. Elevated atmospheric CO2, air temperature, vapor pressure deficit (D), turbulent transport, radiative transfer, and reduced soil moisture all impact biotic and abiotic processes controlling ET that must be extrapolated to large scales. Suggesting a blueprint to achieve this link is the main compass of this review. Leaf-scale transpiration (fe) as governed by the plant biochemical demand for CO2 is first considered. When this biochemical demand is combined with mass transfer formulations, the problem remains mathematically intractable, requiring additional assumptions. A mathematical “closure” that assumes stomatal aperture is autonomously regulated so as to maximize the leaf carbon gain while minimizing water loss is proposed, which leads to analytical expressions for leaf-scale transpiration. This formulation predicts well the effects of elevated atmospheric CO2 and increases in D on fe. The case of soil moisture stress is then considered using extensive gas exchange measurements collected in drought studies. Upscaling the fe to the canopy is then discussed at multiple time scales. The impact of limited soil water availability within the rooting zone on the upscaled ET as well as some plant strategies to cope with prolonged soil moisture stress are briefly presented. Moving further up in direction and scale, the soil-plant system is then embedded within the atmospheric boundary layer, where the influence of soil moisture on rainfall is outlined. The review concludes by discussing outstanding challenges and how to tackle them by means of novel theoretical, numerical, and experimental approaches.

Canopy nitrogen, carbon assimilation, and albedo in temperate and boreal forests: Functional relations and potential climate feedbacks

The availability of nitrogen represents a key constraint on carbon cycling in terrestrial ecosystems, and it is largely in this capacity that the role of N in the Earths climate system has been considered. Despite this, few studies have included continuous variation in plant N status as a driver of broad-scale carbon cycle analyses. This is partly because of uncertainties in how leaf-level physiological relationships scale to whole ecosystems and because methods for regional to continental detection of plant N concentrations have yet to be developed. Here, we show that ecosystem CO2 uptake capacity in temperate and boreal forests scales directly with whole-canopy N concentrations, mirroring a leaf-level trend that has been observed for woody plants worldwide. We further show that both CO2 uptake capacity and canopy N concentration are strongly and positively correlated with shortwave surface albedo. These results suggest that N plays an additional, and overlooked, role in the climate system via its influence on vegetation reflectivity and shortwave surface energy exchange. We also demonstrate that much of the spatial variation in canopy N can be detected by using broad-band satellite sensors, offering a means through which these findings can be applied toward improved application of coupled carbon cycle–climate models.

DETERMINANTS OF LONG-DISTANCE SEED DISPERSAL BY WIND IN GRASSLANDS

Long-distance seed dispersal is an important topic in ecology, but notoriously difficult to quantify. Previous modeling approaches have failed to simulate long-distance dispersal, and it has remained unclear which mechanisms determine long-distance dispersal and what their relative importance is. We simulated wind dispersal of grassland plant seeds with four mechanistic models of increasing complexity and realism to assess which processes and which attributes of plants and their environment determine dispersal distances. We compared simulation results of the models to each other and to data from field dispersal experiments. The more complex and realistic models predicted short-distance dispersal more accurately and were the only models able to simulate long-distance dispersal. The model comparisons showed that autocorrelated turbulent fluctuations in vertical wind velocity are the key mechanism for long-distance dispersal. Seed dispersal distances are longest under high wind velocity conditions, when mechanically produced turbulent air movements are large. Under very low wind velocity conditions seeds are dispersed farther when there is more surface heating, but never as far as during strong wind events. Model sensitivity analyses showed that mean horizontal wind velocity, seed release height, and vegetation height are crucial determinants of dispersal potential and dispersal distances. Between plant species (but not within a species), seed terminal velocity is an additional important determinant of long-distance dispersal. These results imply that seed release height is the most important plant-controlled dispersal parameter for grassland plants, and that the structure of the local vegetation greatly affects dispersal distances. Thus, management plans for grasslands should take into account that changes in vegetation structure, e.g., due to eutrophication, can reduce the seed dispersal ability of wind-dispersed plant species.

Mechanistic Analytical Models for Long‐Distance Seed Dispersal by Wind

We introduce an analytical model, the Wald analytical long‐distance dispersal (WALD) model, for estimating dispersal kernels of wind‐dispersed seeds and their escape probability from the canopy. The model is based on simplifications to well‐established three‐dimensional Lagrangian stochastic approaches for turbulent scalar transport resulting in a two‐parameter Wald (or inverse Gaussian) distribution. Unlike commonly used phenomenological models, WALD’s parameters can be estimated from the key factors affecting wind dispersal—wind statistics, seed release height, and seed terminal velocity—determined independently of dispersal data. WALD’s asymptotic power‐law tail has an exponent of −3/2, a limiting value verified by a meta‐analysis for a wide variety of measured dispersal kernels and larger than the exponent of the bivariate Student t‐test (2Dt). We tested WALD using three dispersal data sets on forest trees, heathland shrubs, and grassland forbs and compared WALD’s performance with that of other analytical mechanistic models (revised versions of the tilted Gaussian Plume model and the advection‐diffusion equation), revealing fairest agreement between WALD predictions and measurements. Analytical mechanistic models, such as WALD, combine the advantages of simplicity and mechanistic understanding and are valuable tools for modeling large‐scale, long‐term plant population dynamics.