John M. Norman

Correcting eddy-covariance flux underestimates over a grassland

Independent measurements of the major energy balance flux components are not often consistent with the principle of conservation of energy. This is referred to as a lack of closure of the surface energy balance. Most results in the literature have shown the sum of sensible and latent heat fluxes measured by eddy covariance to be less than the difference between net radiation and soil heat fluxes. This under-measurement of sensible and latent heat fluxes by eddy-covariance instruments has occurred in numerous field experiments and among many different manufacturers of instruments. Four eddy-covariance systems consisting of the same models of instruments were set up side-by-side during the Southern Great Plains 1997 Hydrology Experiment and all systems under-measured fluxes by similar amounts. One of these eddy-covariance systems was collocated with three other types of eddy-covariance systems at different sites; all of these systems under-measured the sensible and latent-heat fluxes. The net radiometers and soil heat flux plates used in conjunction with the eddy-covariance systems were calibrated independently and measurements of net radiation and soil heat flux showed little scatter for various sites. The 10% absolute uncertainty in available energy measurements was considerably smaller than the systematic closure problem in the surface energy budget, which varied from 10 to 30%. When available-energy measurement errors are known and modest, eddy-covariance measurements of sensible and latent heat fluxes should be adjusted for closure. Although the preferred method of energy balance closure is to maintain the Bowen‐ratio, the method for obtaining closure appears to be less important than assuring that eddy-covariance measurements are consistent with conservation of energy. Based on numerous measurements over a sorghum canopy, carbon dioxide fluxes, which are measured by eddy covariance, are underestimated by the same factor as eddy covariance evaporation measurements when energy balance closure is not achieved. Published by Elsevier Science B.V.

Direct and Indirect Estimation of Leaf Area Index, fAPAR, and Net Primary Production of Terrestrial Ecosystems

A primary objective of the Earth Observing System (EOS) is to develop and validate algorithms to estimate leaf area index (L), fraction of absorbed photosynthetically active radiation (fAPAR), and net primary production (NPP) from remotely sensed products. These three products are important because they relate to or are components of the metabolism of the biosphere and can be determined for terrestrial ecosystems from satellite-borne sensors. The importance of these products in the EOS program necessitates the need to use standard methods to obtain accurate ground truth estimates of L, fAPAR, and NPP that are correlated to satellite-derived estimates. The objective of this article is to review direct and indirect methods used to estimate L, fAPAR, and NPP in terrestrial ecosystems. Direct estimates of L, biomass, and NPP can be obtained by harvesting individual plants, developing allometric equations, and applying these equations to all individuals in the stand. Using non-site-specific allometric equations to estimate L and foliage production can cause large errors because carbon allocation to foliage is influenced by numerous environmental and ecological factors. All of the optical instruments that indirectly estimate L actually estimate “effective” leaf area index (LE) and underestimate L when foliage in the canopy is nonrandomly distributed (i.e., clumped). We discuss several methods, ranging from simple to complex in terms of data needs, that can be used to correct estimates of L when foliage is clumped. Direct estimates of above-ground and below-ground net primary production (NPPA and NPPB, respectively) are laborious, expensive and can only be carried out for small plots, yet there is a great need to obtain global estimates of NPP. Process models, driven by remotely sensed input parameters, are useful tools to examine the influence of global change on the metabolism of terrestrial ecosystems, but an incomplete understanding of carbon allocation continues to hamper development of more accurate NPP models. We summarize carbon allocation patterns for major terrestrial biomes and discuss emerging allocation patterns that can be incorporated into global NPP models. One common process model, light use efficiency or epsilon model, uses remotely sensed fAPAR, light use efficiency (LUE) and carbon allocation coefficients, and other meteorological data to estimates NPP. Such models require reliable estimates of LUE. We summarize the literature and provide LUE coefficients for the major biomes, being careful to correct for inconsistencies in radiation, dry matter and carbon allocation units.

Leaf area index of boreal forests: Theory, techniques, and measurements

Leaf area index (LAI) is a key structural characteristic of forest ecosystems because of the role of green leaves in controlling many biological and physical processes in plant canopies. Accurate LAI estimates are required in studies of ecophysiology, atmosphere-ecosystem interactions, and global change. The objective of this paper is to evaluate LAI values obtained by several research teams using different methods for a broad spectrum of boreal forest types in support of the international Boreal Ecosystem-Atmosphere Study (BOREAS). These methods include destructive sampling and optical instruments: the tracing radiation and architecture of canopies (TRAC), the LAI-2000 plant canopy analyzer, hemispherical photography, and the Sunfleck Ceptometer. The latter three calculate LAI from measured radiation transmittance (gap fraction) using inversion models that assume a random spatial distribution of leaves. It is shown that these instruments underestimate LAI of boreal forest stands where the foliage is clumped. The TRAC quantifies the clumping effect by measuring the canopy gap size distribution. For deciduous stands the clumping index measured from TRAC includes the clumping effect at all scales, but for conifer stands it only resolves the clumping effect at scales larger than the shoot (the basic collection of needles). To determine foliage clumping within conifer shoots, a video camera and rotational light table system was used. The major difficulties in determining the surface area of small conifer needles have been largely overcome by the use of an accurate volume displacement method. Hemispherical photography has the advantage that it also provides a permanent image record of the canopies. Typically, LAI falls in the range from 1 to 4 for jack pine and aspen forests and from 1 to 6 for black spruce. Our comparative studies provide the most comprehensive set of LAI estimates available for boreal forests and demonstrate that optical techniques, combined with limited direct foliage sampling, can be used to obtain quick and accurate LAI measurements.

A comparison of optical and direct methods for estimating foliage surface area index in forests

Measurement of foliage surface area index (foliage SAI) is prominent in studies of terrestrial ecosystems because it is an important determinant of water, carbon, and energy exchange at the stand, landscape, and global scales, yet is very time consuming and labor intensive to measure directly. The objectives of this study were to 1) compare the resolution and accuracy of the Ceptometer, LAI-2000, and DEMON which measure a vegetation area index (VAI; includes branches, stems, cones, etc. in addition to leaves) optically using light interception, 2) examine the utility of logarithmic versus linear averaging and a correction factor proposed by Gower and Norman (1991), and 3) determine if there is a ‘universal’ regression relating optical and direct estimates of SAI across the range of foliage areas for most North American forests (and if one exists, how it relates to individual site regressions). For our analysis, data collected in open canopy natural ponderosa pine (Pinus ponderosa Dougl. ex Laws) forests and closed canopy red pine (Pinus resinosa Ait.) plantations were combined with data from previous studies which used one or more of the instruments. We found all instruments generally underestimated SAI when compared with direct estimates. Logarithmic averages of light transmittance reduced this problem, especially for conifer forests with foliage clumped at the shoot and canopy levels. The DEMON, using logarithmically averaged data, provided the most accurate optical estimates of SAI. We did not find the clumping correction factor suggested by Gower and Norman (1991) to be useful and suggest an alternative correction technique that is based on hemisurface area index (HSAI) and includes a shoot shape factor along with a clumping factor. Across a broad range in foliage SAI, all instruments provided optical estimates of SAI that were strongly correlated to direct estimates but the optical estimates were biased. The LAI-2000 (R2 = 0.93) and the DEMON logarithmic (R2 = 0.93) had the best fits. Because of the small size of the data sets evaluated, we strongly recommend the collection of larger data sets across a wider range of foliage SAIs to better test the strength of ‘universal’ regressions relating optical estimates of SAI to direct estimates.

Estimating fluxes on continental scales using remotely sensed data in an atmospheric-land exchange model

A simple model of energy exchange between the land surface and the atmospheric boundary layer, driven by input that can be derived primarily through remote sensing, is described and applied over continental scales at a horizontal resolution of 10 km. Surface flux partitioning into sensible and latent heating is guided by time changes in land surface brightness temperatures, which can be measured from a geostationary satellite platform such as the Geostationary Operational Environmental Satellite. Other important inputs, including vegetation cover and type, can be derived using the Normalized Difference Vegetation Index in combination with vegetation and land use information. Previous studies have shown that this model performs well on small spatial scales, in comparison with surface flux measurements acquired during several field experiments. However, because the model requires only a modicum of surface-based measurements and is designed to be computationally efficient, it is particularly well suited for regional- or continental-scale applications. The input data assembly process for regional-scale applications is outlined. Model flux estimates for the central United States are compared with climatological moisture and vegetation patterns, as well as with surface-based flux measurements acquired during the Southern Great Plains (SGP-97) Hydrology Experiment. These comparisons are quite promising.

Surface flux estimation using radiometric temperature: A dual‐temperature‐difference method to minimize measurement errors

Surface temperature serves as a key boundary condition that defines the partitioning of surface radiation into sensible and latent heat fluxes. Surface brightness temperature measurements from satellites offer the unique possibility of mapping surface heat fluxes at regional scales. Because uncertainties in satellite measurements of surface radiometric temperature arise from atmospheric corrections, surface emissivity, and instrument calibrations, a number of studies have found significant discrepancies between modeled and measured heat fluxes when using radiometric temperature. Recent research efforts have overcome these uncertainties and in addition have accounted for the difference between radiometric and aerodynamic temperature by considering soil and vegetative-canopy aerodynamic resistances. The major remaining obstacle to using satellite data for regional heat flux estimation is inadequate density of near-surface air temperature observations. In this paper we describe a simple, operational, double-difference approach for relating surface sensible heat flux to remote observations of surface brightness temperature, vegetative cover and type, and measurements of near-surface wind speed and air temperature from the synoptic weather network. A double difference of the time rate of change in radiometric and air temperature observations is related to heat flux. This double-difference approach reduces both the errors associated with deriving a radiometric temperature and with defining meteorological quantities at large scales. The scheme is simpler than other recent approaches because it requires minimal ground-based data and does not require modeling boundary layer development. The utility of this scheme is tested with ground-based radiometric temperature observations from several arid and subhumid climates with a wide range of vegetative cover and meteorological conditions.

Measurements and Modeling of Carbon and Nitrogen Cycling in Agroecosystems of Southern Wisconsin: Potential for SOC Sequestration during the Next 50 Years

Landmanagement practices such as no-tillage agriculture and tallgrass prairie restoration have been proposed as a possible means to sequester atmospheric carbon, helping to refurbish soil fertility and replenish organic matter lost as a result of previous agricultural management practices. However, the relationship between land-use changes and ecosystem structure and functioning is not yet understood. We studied soil and vegetation properties over a 4-year period (1995–98), and assembled measurements of microbial biomass, soil organic carbon (SOC) and nitrogen (N), N-mineralization, soil surface carbon dioxide (CO2) flux, and leached C and N in managed (maize; Zea mays L.) and natural (prairie) ecosystems near the University of Wisconsin Agricultural Research Station at Arlington. Field data show that different management practices (tillage and fertilization) and ecosystem type (prairie vs maize) have a profound influence on biogeochemistry and water budgets between sites. These measurements were used in conjunction with a dynamic terrestrial ecosystem model, called IBIS (the Integrated Biosphere Simulator), to examine the long-term effects of land-use changes on biogeochemical cycling. Field data and modeling suggest that agricultural land management near Arlington between 1860 and 1950 caused SOC to be depleted by as much as 63% (native SOC approximately 25.1 kg C m−2). Reductions in N-mineralization and microbial biomass were also observed. Although IBIS simulations depict SOC recovery in no-tillage maize since the 1950s and also in the Arlington prairie since its restoration was initiated in 1976, field data suggest otherwise for the prairie. This restoration appears to have done little to increase SOC over the past 24 years. Measurements show that this prairie contained between 28% and 42% less SOC (in the top 1 m) than the no-tillage maize plots and 40%–47% less than simulated potential SOC for the site in 1999. Because IBIS simulates competition between C3 and C4 grass species, we hypothesized that current restored prairies, which include many forbs not characterized by the model, could be less capable of sequestering C than agricultural land planted entirely in monocultural grass in this region. Model output and field measurements show a potential 0.4 kg C m−2 y−1 difference in prairie net primary production (NPP). This study indicates that high-productivity C4 grasslands (NPP = 0.63 kg C m−2 y−1) and high-yield maize agroecosystems (10 Mg ha−1) have the potential to sequester C at a rate of 74.5 g C m−2 y−1 and 86.3 g C m−2 y−1, respectively, during the next 50 years across southern Wisconsin.

Evaluating the Effects of Subpixel Heterogeneity on Pixel Average Fluxes

Abstract Radiometric temperature observations TR(φ) at a sensor view angle φ are routinely available from weather satellites such as the Geostationary Orbiting Environmental Satellite (GOES) and provide a unique spatially distributed boundary condition for surface energy balance modeling at regional scales. Reliable flux estimates over heterogeneous surfaces have been obtained using two-source models that implicitly account for differences between TR(φ) and aerodynamic temperature, TO, by considering separately the contributions of soil/substrate and vegetation to TR(φ) observations and to the turbulent fluxes. A simple two-source energy balance model developed to use TR(φ) observations has been applied successfully to a wide range of vegetation cover conditions at the field scale. However, its application with course resolution weather satellite data (i.e., pixel resolution≳1 km) will invariably result in errors in pixel-averaged heat flux estimation for surfaces with significant variability in vegetation cover and stress conditions. Indeed, with the highest resolution of satellite TR(φ) data∼100 m, subpixel heterogeneity will still be significant for many landscapes, especially arid and semiarid areas. Uncertainty in flux estimation due to significant subpixel heterogeneity is examined using the simplified two-source model with TR(φ) inputs from simulations using a detailed plant-environment model (Cupid) under six different “homogeneous” surface conditions commonly found in semiarid and arid regions and under high and low winds. These surface types are comprised of shrub and tall riparian vegetation, high and low canopy cover, wet and dry surface soil moisture state, and stressed versus unstressed vegetation condition. From six homogeneous surface conditions defined by vegetation type, cover, surface moisture and stress, four mixed-pixel cases were constructed, each containing two contrasting surface types. Significant or unacceptable errors (i.e., ∼50 W m−2) in pixel-average heat fluxes are found in all four mixed-pixel cases, but the significant errors primarily occur when the fraction of the extreme surface condition (e.g., riparian wetland) comprises between ∼20% and 80% of the mixed-pixel. Additionally, the results are influenced by the wind conditions with a higher wind speed tending to reduce errors. This preliminary analysis suggests that when there is a significant discontinuity in surface conditions, particularly under low winds, the subpixel variability in energy fluxes will likely cause unacceptable errors in two-source model predictions. However, daytime wind speeds are typically >2 m s−1 and the resolution of TR(φ) observations from weather satellites are relatively coarse (i.e., ∼5–10 km), which means riparian areas are likely to comprise less than 10% of a pixel. Both of these factors are likely to reduce errors in heat flux predictions at these large spatial scales caused by using pixel-average inputs. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) instrument proposed for NASAs Earth Observing System (EOS) has 90 m resolution. This will be useful for evaluating the impact of subpixel variability on flux predictions with coarser resolution data more routinely available from weather satellites.

CARBON BUDGETS FOR A PRAIRIE AND AGROECOSYSTEMS: EFFECTS OF LAND USE AND INTERANNUAL VARIABILITY

Midwestern grasslands have undergone dramatic changes in land use and management practices, but the effects of these changes on terrestrial carbon budgets are poorly understood. This study compared, for five years, the effects of land-use type on components of the carbon (C) budget (above- and belowground net primary production [NPP], C leaching, soil surface CO2 flux, vegetation and soil C contents, and C export from burning and grain removal) of a restored tallgrass prairie and maize agroecosystems on a silt loam soil. Interannual variation of the C budget was addressed by correlating annual fluctuations of environmental variables and soil properties with C-budget components. The C losses we estimated, in order of increasing magnitude, were C leaching, grain C removal from the maize agroecosystems, and soil surface CO2 flux. NPP was significantly greater for N-fertilized maize (10.4 Mg C·ha−1·yr−1) than unfertilized maize agroecosystems (6.2 Mg C·ha−1·yr−1), and both were significantly greater than rest...

Nest structure of ant Lasius neoniger Emery and its implications to soil modification

Abstract The ant Lasius neoniger Emery is one of the most abundant ant species found in the temperate regions of North America and has been studied primarily from an entomological standpoint. This study was conducted to characterize its nest structure and implications to soil modification. To study the structure, development, and micromorphological characteristics of the ant nests, we constructed three-dimensional models of the nests from excavated nest castings made with dental gypsum and ant farms with Plexiglas, and made thin sections ( ≈30 μm thick) from undisturbed field soil samples that contained the nests. We assessed the effect of the ant on soil chemical properties by comparing the composition of ant crater rim and nest materials with that of associated bulk soil. The ant nests consisted of underground branched networks of galleries and chambers concentrated in the upper 0.3 m of the soil, with a few vertical galleries penetrating to about 0.7 m. The galleries tended to be circular tubes (channels) 1.5 to 5.0 mm in diameter, whereas the chambers, connected by the galleries, bulged to diameters of 10 to 20 mm and were 30 to 50 mm in length. The volume of the nests ranged from 20 to 250 cm 3 . Walls of the nests ( ≈1 μm thick) were more consolidated and contained larger amounts of fine sand, silt, and colloidal material than adjoining bulk soil. The primary effect of the ants was mixing of the upper 0.7 m of soil. Estimated soil turnover time ranges, for upper 0.3 m soil, from approximately 1000 years for the grass border areas of a corn field to 2800 years inside the field. For soils between 0.3 and 0.7 m depths, estimated soil turnover time ranges from approximately 9000 years for the grass border areas to 24,000 years inside the corn field. Selective mining by ants of fine-particles, which concentrate in the upper tier of the soil, may also counter balance processes such as clay translocation and nutrient leaching that tend to degrade physical and chemical attributes of sandy soil surfaces forming in humid environment.