Christopher J. Kucharik

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.

Testing the performance of a dynamic global ecosystem model: Water balance, carbon balance, and vegetation structure

While a new class of Dynamic Global Ecosystem Models (DGEMs) has emerged in the past few years as an important tool for describing global biogeochemical cycles and atmosphere-biosphere interactions, these models are still largely untested. Here we analyze the behavior of a new DGEM and compare the results to global-scale observations of water balance, carbon balance, and vegetation structure. In this study, we use version 2 of the Integrated Biosphere Simulator (IBIS), which includes several major improvements and additions to the prototype model developed by Foley et al. [1996]. IBIS is designed to be a comprehensive model of the terrestrial biosphere; the model represents a wide range of processes, including land surface physics, canopy physiology, plant phenology, vegetation dynamics and competition, and carbon and nutrient cycling. The model generates global simulations of the surface water balance (e.g., runoff), the terrestrial carbon balance (e.g., net primary production, net ecosystem exchange, soil carbon, aboveground and belowground litter, and soil CO2 fluxes), and vegetation structure (e.g., biomass, leaf area index, and vegetation composition). In order to test the performance of the model, we have assembled a wide range of continental and global-scale data, including measurements of river discharge, net primary production, vegetation structure, root biomass, soil carbon, litter carbon, and soil CO2 flux. Using these field data and model results for the contemporary biosphere (1965–1994), our evaluation shows that simulated patterns of runoff, NPP, biomass, leaf area index, soil carbon, and total soil CO2 flux agree reasonably well with measurements that have been compiled from numerous ecosystems. These results also compare favorably to other global model results.

Carbon distribution and aboveground net primary production in aspen, jack pine, and black spruce stands in Saskatchewan and Manitoba, Canada

The objectives of this study are to (1) characterize the carbon (C) content, leaf area index, and aboveground net primary production (ANPP) for mature aspen, black spruce, and young and mature jack pine stands at the southern and northern Boreal Ecosystem-Atmosphere Study (BOREAS) areas and (2) compare net primary production and carbon allocation coefficients for the major boreal forest types of the world. Direct estimates of leaf area index, defined as one half of the total leaf surface area, range from a minimum of 1.8 for jack pine forests to a maximum of 5.6 for black spruce forests; stems comprise 5 to 15% of the total overstory plant area. In the BOREAS study, total ecosystem (vegetation plus detritus plus soil) carbon content is greatest in the black spruce forests (445,760–479,380 kg C ha−1), with 87 to 88% of the C in the soil, and is lowest in the jack pine stands (68,370–68,980 kg C ha−1) with a similar distribution of carbon in the vegetation and soil. Forest floor carbon content and mean residence time (MRT) also vary more among forest types in a study area than between study areas for a forest type; forest floor MRT range from 16 to 19 years for aspen stands to 28 to 39 years for jack pine stands. ANPP differs significantly among the mature forests at each of the BOREAS study areas, ranging from a maximum of 3490 to 3520 kg C ha−1 yr−1 for aspen stands to 1170 to 1220 kg C ha−1 yr−1 for jack pine stands. Both net primary production (NPP) and carbon allocation differ between boreal evergreen and deciduous forests in the world, suggesting global primary production models should distinguish between these two forest types. On average, 56% of NPP for boreal forests occurs as detritus and illustrates the need to better understand factors controlling aboveground and below-ground detritus production in boreal forests.

Corn-based ethanol production compromises goal of reducing nitrogen export by the Mississippi River

Corn cultivation in the United States is expected to increase to meet demand for ethanol. Nitrogen leaching from fertilized corn fields to the Mississippi–Atchafalaya River system is a primary cause of the bottom-water hypoxia that develops on the continental shelf of the northern Gulf of Mexico each summer. In this study, we combine agricultural land use scenarios with physically based models of terrestrial and aquatic nitrogen to examine the effect of present and future expansion of corn-based ethanol production on nitrogen export by the Mississippi and Atchafalaya Rivers to the Gulf of Mexico. The results show that the increase in corn cultivation required to meet the goal of 15–36 billion gallons of renewable fuels by the year 2022 suggested by a recent U.S. Senate energy policy would increase the annual average flux of dissolved inorganic nitrogen (DIN) export by the Mississippi and Atchafalaya Rivers by 10–34%. Generating 15 billion gallons of corn-based ethanol by the year 2022 will increase the odds that annual DIN export exceeds the target set for reducing hypoxia in the Gulf of Mexico to >95%. Examination of extreme mitigation options shows that expanding corn-based ethanol production would make the already difficult challenges of reducing nitrogen export to the Gulf of Mexico and the extent of hypoxia practically impossible without large shifts in food production and agricultural management.

Effects of Land Cover Change on the Energy and Water Balance of the Mississippi River Basin

Abstract The effects of land cover change on the energy and water balance of the Mississippi River basin are analyzed using the Integrated Biosphere Simulator (IBIS) model. Results of a simulated conversion from complete forest cover to crop cover over a single model grid cell show that annual average net radiation and evapotranspiration decrease, while total runoff increases. The opposite effects are found when complete grass cover is replaced with crop cover. Basinwide energy and water balance changes are then analyzed after simulated land cover change from potential vegetation to the current cover (natural vegetation and crops). In general, net radiation decreases over crops converted from forest and increases over crops converted from grasslands. Evapotranspiration rates decrease over summer crops (corn and soybean) converted from forest and increase over summer crops converted from grassland. The largest decreases (∼0.75 mm day−1; 20%) are found in summer over former forests, and the largest increase...

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.

Evaluation of a Process-Based Agro-Ecosystem Model (Agro-IBIS) across the U.S. Corn Belt: Simulations of the Interannual Variability in Maize Yield

Abstract A process-based terrestrial ecosystem model, Agro-IBIS, was used to simulate maize yield in a 13-state region of the U.S. Corn Belt from 1958 to 1994 across a 0.5° terrestrial grid. For validation, county-level census [U.S. Department of Agriculture (USDA)] data of yield were detrended to calculate annual yield residuals. Daily atmospheric inputs from the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalysis were used in conjunction with the Climate Research Units (CRUs) monthly climate anomaly dataset at 0.5° resolution and a weather generator to drive the model at a 60-min time step. Multiple simulations were used to quantify model sensitivity to hybrid selection (defined by growing degree-day requirements), planting date, and soil type. The calibration of raw yields and model capability to replicate interannual variability were tested. The spatial patterns of simulated mean bias error (mbe) of raw yields were largely unresponsive to var...

Characterizing canopy nonrandomness with a multiband vegetation imager (MVI)

A new method for measuring plant canopy nonrandomness and other architectural components has been developed using a 16 bit (65535 gray scale levels) charged-coupled device (CCD) camera that captures images of plant canopies in two wavelength bands. This complete system is referred to as a multiband vegetation imager (MVI). The use of two wavelength bands (visible (VIS) 400–620 nm and near infrared (NIR) 720–950 nm) permits identification of sunlit and shaded foliage, sunlit and shaded branch area, clouds, and blue sky based on the cameras resolution, and the varying spectral properties that scene components have in the two wavelength bands. This approach is different from other canopy imaging methods (such as fish-eye photography) because it emphasizes measuring the fraction of an image occupied by various scene components (branches, shaded leaves, sunlit leaves) under different sky conditions rather than simply the canopy gap fraction under uniform sky conditions. The MVI has been used during the Boreal Ecosystem-Atmosphere Study (BOREAS) in aspen (Populus tremuloides) and balsam poplar (Populus balsamifera) to estimate architectural characteristics of each canopy. The leaf area index (LAI), sunlit LAI, and degree of nonrandomness within a canopy are architectural properties that have been measured with the MVI. Using a crown-based Monte Carlo model for nonrandom canopies, nonrandomness factors are calculated from MVI data using two approaches (gap fraction and gap-size distribution theories) to correct total and sunlit LAI estimates from indirect methods that assume random foliage distributions. Canopy nonrandomness factors obtained from analyzing the gap-size distribution in a Monte Carlo model are shown to be a function of path length (angle) through the canopy (Ωe(θ)); thus we suggest that LAI-2000 indirect measurements of LAI be adjusted with the value of Ωe(θ) at θ=35° because this is the mean angle at which the canopy gap fraction is measured by the LAI-2000. In this study, values of Ωe(35)=0.69 in an aspen forest. Alternatively, corrections to indirect LAI measurements obtained with the MVI in this study are made using the value of Ωe(0) because the MVI is used to measure the canopy gap-size distribution and gap fraction within 15° of the zenith. Values of Ωe(0) obtained with the MVI in aspen are typically between 0.55 and 0.65; while in balsam poplar, average values of Ωe(0) are equal to 0.82. This study shows that the MVI provides an attractive indirect measurement technique to obtain accurate estimates of total LAI in aspen. Corrected canopy LAI and direct LAI measurements are greater than indirect estimates based on assuming the foliage to be randomly distributed: In aspen, total LAI is 45% larger (3.3 versus 2.0) and sunlit LAI (40° Sun zenith angle) 10% larger, while in balsam poplar, total LAI is 17% larger (2.3 versus 1.9) and sunlit LAI is only 1% larger. The importance of these clumping characteristics is best appreciated with estimates of canopy net CO2 assimilation derived from scaling leaf photosynthesis versus light relations. Aspen canopy assimilation accounting for clumping is 39% larger than estimates based on indirect measurements of total LAI and the assumption that foliage is randomly distributed.

Interactive Crop Management in the Community Earth System Model (CESM1): Seasonal Influences on Land–Atmosphere Fluxes

AbstractThe Community Earth System Model, version 1 (CESM1) is evaluated with two coupled atmosphere–land simulations. The CTRL (control) simulation represents crops as unmanaged grasses, while CROP represents a crop managed simulation that includes special algorithms for midlatitude corn, soybean, and cereal phenology and carbon allocation. CROP has a more realistic leaf area index (LAI) for crops than CTRL. CROP reduces winter LAI and represents the spring planting and fall harvest explicitly. At the peak of the growing season, CROP simulates higher crop LAI. These changes generally reduce the latent heat flux but not around peak LAI (late spring/early summer). In midwestern North America, where corn, soybean, and cereal abundance is high, simulated peak summer precipitation declines and agrees better with observations, particularly when crops emerge late as is found from a late planting sensitivity simulation (LateP). Differences between the CROP and LateP simulations underscore the importance of simul...

Evaluating the impacts of land management and climate variability on crop production and nitrate export across the Upper Mississippi Basin

[1] The increased use of nitrogen (N) fertilizers in the Mississippi Basin since the 1950s is partially responsible for an increase in crop production, but also a massive increase in nitrate export by the Mississippi River. We used the IBIS terrestrial ecosystem model, including new maize and soybean submodels, and the HYDRA hydrological transport model to investigate the role of climate variability, land cover and N-fertilizer application on crop yield, N cycling and nitrate export in the Upper Mississippi Basin from 1974– 1994. Simulated annual mean maize and soybean yields were both within 20% of USDA historical estimates in over 80% of the crop-growing counties. There was also strong agreement between simulated and USGS estimated annual nitrate export for the Mississippi River at Clinton, Iowa (r 2 = 0.81), the outlet of the basin, and the Minnesota River at Jordan, Minnesota (r 2 = 0.78). The model also indicated a 30% increase in N-fertilizer application across the basin would have caused only a 4% increase in mean maize yield, but a 53% increase in mean dissolved inorganic nitrogen (DIN) leaching, while a 30% decrease in N-fertilizer application would have caused a 10% decrease in maize yield, but a 37% decrease in DIN leaching. At higher levels of N-fertilizer usage, nitrate export becomes increasingly sensitive to the hydrologic conditions, particularly when there is ample residual N in the soil. Therefore any effort to reduce nitrate export without significantly affecting crop yields would have to account for previous soil-N conditions and climate variability. INDEX TERMS: 1871 Hydrology: Surface water quality; 4805 Oceanography: Biological and Chemical: Biogeochemical cycles (1615); 4842 Oceanography: Biological and Chemical: Modeling; 4845 Oceanography: Biological and Chemical: Nutrients and nutrient cycling;