The role of surface roughness, albedo, and Bowen ratio on ecosystem energy balance in the Eastern United States

Land cover and land use influence surface climate through differences in biophysical surface properties, including partitioning of sensible and latent heat (e.g., Bowen ratio), surface roughness, and albedo. Clusters of closely spaced eddy covariance towers (e.g., \u3c10 \u3ekm) over a variety of land cover and land use types provide a unique opportunity to study the local effects of land cover and land use on surface temperature. We assess contributions albedo, energy redistribution due to differences in surface roughness and energy redistribution due to differences in the Bowen ratio using two eddy covariance tower clusters and the coupled (land-atmosphere) Variable-Resolution Community Earth System Model. Results suggest that surface roughness is the dominant biophysical factor contributing to differences in surface temperature between forested and deforested lands. Surface temperature of open land is cooler (−4.8 °C to −0.05 °C) than forest at night and warmer (+0.16 °C to +8.2 °C) during the day at northern and southern tower clusters throughout the year, consistent with modeled calculations. At annual timescales, the biophysical contributions of albedo and Bowen ratio have a negligible impact on surface temperature, however the higher albedo of snow-covered open land compared to forest leads to cooler winter surface temperatures over open lands (−0.4 °C to −0.8 °C). In both the models and observation, the difference in mid-day surface temperature calculated from the sum of the individual biophysical factors is greater than the difference in surface temperature calculated from radiative temperature and potential temperature. Differences in measured and modeled air temperature at the blending height, assumptions about independence of biophysical factors, and model biases in surface energy fluxes may contribute to daytime biases

Use of waveform lidar and hyperspectral sensors to assess selected spatial and structural patterns associated with recent and repeat disturbance and the abundance of sugar maple (Acer saccharum Marsh.) in a temperate mixed hardwood and conifer forest.

Abstract Waveform lidar imagery was acquired on September 26, 1999 over the Bartlett Experimental Forest (BEF) in New Hampshire (USA) using NASA\u27s Laser Vegetation Imaging Sensor (LVIS). This flight occurred 20 months after an ice storm damaged millions of hectares of forestland in northeastern North America. Lidar measurements of the amplitude and intensity of ground energy returns appeared to readily detect areas of moderate to severe ice storm damage associated with the worst damage. Southern through eastern aspects on side slopes were particularly susceptible to higher levels of damage, in large part overlapping tracts of forest that had suffered the highest levels of wind damage from the 1938 hurricane and containing the highest levels of sugar maple basal area and biomass. The levels of sugar maple abundance were determined through analysis of the 1997 Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) high resolution spectral imagery and inventory of USFS Northern Research Station field plots. We found a relationship between field measurements of stem volume losses and the LVIS metric of mean canopy height (r2 = 0.66; root mean square errors = 5.7 m3/ha, p \u3c 0.0001) in areas that had been subjected to moderate-to-severe ice storm damage, accurately documenting the short-term outcome of a single disturbance event

Landscape variation in canopy nitrogen and carbon assimilation in a temperate mixed forest

Canopy nitrogen (N) is a key factor regulating carbon cycling in forest ecosystems through linkages among foliar N and photosynthesis, decomposition, and N cycling. This analysis examined landscape variation in canopy nitrogen and carbon assimilation in a temperate mixed forest surrounding Harvard Forest in central Massachusetts, USA by integration of canopy nitrogen mapping with ecosystem modeling, and spatial data from soils, stand characteristics and disturbance history. Canopy %N was mapped using high spectral resolution remote sensing from NASA’s AVIRIS (Airborne Visible/Infrared Imaging Spectrometer) instrument and linked to an ecosystem model, PnET-II, to estimate gross primary productivity (GPP). Predicted GPP was validated with estimates derived from eddy covariance towers. Estimated canopy %N ranged from 0.5 to 2.9% with a mean of 1.75% across the study region. Predicted GPP ranged from 797 to 1622 g C m−2 year−1 with a mean of 1324 g C m−2 year−1. The prediction that spatial patterns in forest growth are associated with spatial patterns in estimated canopy %N was supported by a strong, positive relationship between field-measured canopy %N and aboveground net primary production. Estimated canopy %N and GPP were related to forest composition, land-use history, and soil drainage. At the landscape scale, PnET-II GPP was compared with predicted GPP from the BigFoot project and from NASA’s MODIS (Moderate Resolution Imaging Spectroradiometer) data products. Estimated canopy %N explained much of the difference between MODIS GPP and PnET-II GPP, suggesting that global MODIS GPP estimates may be improved if broad-scale estimates of foliar N were available

Examining spectral reflectance features related to foliar nitrogen in forests: Implications for broad-scale nitrogen mapping

The concentration of nitrogen (N) in foliage often limits photosynthesis and can influence a number of important biogeochemical processes. For this reason, methods for estimating foliar %N over a range of scales are needed to enhance understanding of terrestrial carbon and nitrogen cycles. High spectral resolution aircraft remote sensing has become an increasingly common tool for landscape-scale estimates of canopy %N because reflectance in some portions of the spectrum has been shown to correlate strongly with field-measured %N. These patterns have been observed repeatedly over a wide range of biomes, opening new possibilities for planned Earth observation satellites. Nevertheless, the effects of spectral resolution and other sensor characteristics on %N estimates have not been fully examined, and may have implications for future analyses at landscape, regional and global scales. In this study, we explored the effects of spectral resolution, spatial resolution and sensor fidelity on relationships between forest canopy %N and reflectance measurements from airborne and satellite platforms. We conducted an exercise whereby PLS, simple and multiple regression calibrations to field-measured canopy %N for a series of forested sites were iteratively performed using (1) high resolution data from AVIRIS (Airborne Visible/Infrared Imaging Spectrometer) that were degraded spectrally from 10 nm to 30 nm, 50 nm, 70 nm, and 90 nm bandwidths, and spatially from 18 m to 30 m and 60 m pixels; (2) data representing Landsat and MODIS (Moderate Resolution Imaging Spectroradiometer) spectral bands simulated with data from AVIRIS; and (3) actual data from Landsat and MODIS. We observed virtually no reduction in the strength of relationships between %N and reflectance when using coarser bandwidths from AVIRIS, but instead saw declines with increasing spatial resolution and loss of sensor fidelity. This suggests that past efforts to examine foliar %N using broad-band sensors may have been limited as much by the latter two properties as by their coarser spectral bandwidths. We also found that regression models were driven primarily by reflectance over broad portions of the near infrared (NIR) region, with little contribution from the visible or mid infrared regions. These results suggest that much of the variability in canopy %N is related to broad reflectance properties in the NIR region, indicating promise for broad scale canopy N estimation from a variety of sensors

kbs_aviris2009_CRspectra_FINAL

Tab delimited .txt file of continuum removed spectral data for the 300 50x50 m plots used in this study, with header row of column names. First column is plot id, second is whether the plot is in forest or agriculture (0 = forest, 1 = agriculture), followed by the continuum removed spectral data. More info and R code to process can be found in the associated manuscript. Original data is from AVIRIS flightline f090720t01p00r05 which was supported by funding from the NASA Terrestrial Ecology program (Grant # NNX11AB88G; PI S. Ollinger); contact S. Ollinger for total flightline reflectance data

Remote sensing of foliar nitrogen in cultivated grasslands of human dominated landscapes

Foliar nitrogen (N) in plant canopies is central to a number of important ecosystem processes and continues to be an active subject in the field of remote sensing. Previous estimates of foliar N at the landscape scale have primarily focused on intact forests and grasslands using aircraft imaging spectrometry and various techniques of statistical calibration and modeling. The present study extends this work by examining the potential to estimate the foliar N concentration (%N) of residential, agricultural and other cultivated grassland areas within a suburbanizing watershed in southeastern New Hampshire. These grasslands occupy a relatively small fraction (17.5%) of total land area within the study watershed, but are important to regional biogeochemistry and are highly valued by humans. In conjunction with ground-based vegetation sampling (n = 20 sites with 54 sample plots), we developed partial least squares regression (PLSR) models for predicting mass-based canopy %N across management types using input from airborne and field-based imaging spectrometers. Models yielded strong relationships for predicting canopy %N from both ground- and aircraft-based sensors (r2 = 0.76 and 0.67, respectively) across sites that included turf grass, grazed pasture, hayfields and fallow fields. Similarities in spectral resolution between the sensors used in this study and the proposed HyspIRI mission suggest promise for detecting canopy %N across multiple forms of managed grasslands, with the possible exception of areas containing lawns too small to be captured with HyspIRI\u27s planned 60 m spatial resolution

Foliar nitrogen in relation to plant traits and reflectance properties of New Hampshire forests.

Abstract Several recent studies have shown that the mass-based concentration of nitrogen in foliage (%N) is positively correlated with canopy near-infrared reflectance (NIRr) and midsummer shortwave albedo across North American forests. Understanding the mechanisms behind this relationship would aid in interpretation of remote sensing imagery and improve our ability to predict changes in reflectance under future environmental conditions. The purpose of this study was to investigate the extent to which foliar nitrogen at leaf and canopy scales covary with leaf- and canopy-scale structural traits that are known to influence NIR scattering and reflectance. To accomplish this, we compared leaf and canopy traits with reflectance spectra at 17 mixed temperate forest stands. We found significant positive associations among %N and NIRr at both the leaf and canopy scale. At the canopy scale, both %N and NIRr were correlated with a number of structural traits as well as with the proportional abundance of deciduous and evergreen foliage. Identifying specific causal factors for observed reflectance patterns was complicated by interrelations among multiple traits across scales. Among simple metrics of canopy structure, we saw no relationship between NIRr and leaf area index, but we observed a strong, inverse relationship with the number of leaves per unit canopy volume

Impacts of recent droughts on North American terrestrial ecosystems

The frequency and severity of droughts have been increasing, and their impacts on terrestrial ecosystems have received growing attention. There has been limited research on the responses of carbon fluxes, evapotranspiration (ET), and water use efficiency (WUE) to severe and extended droughts at regional to continental scales. Here we combine a gridded carbon and water flux dataset (EC-MOD), Palmer Drought Severity Index (PDSI), a process-based ecosystem model, and agricultural statistics to examine the impacts of recent droughts on North American terrestrial ecosystems. The gridded flux dataset was upscaled from eddy covariance flux observations across North America through a data-driven approach. We assess the responses of ecosystem carbon fluxes, ET, and WUE to severe and extended droughts at the continental scale using EC-MOD. Drought can lead to significant declines in ET and subsequent decreases in carbon fluxes. The responses of WUE to drought are assessed at the annual scale. Simulations from a process-based ecosystem model and crop yield statistics are also used to assess the effects of drought on agricultural productivity and WUE. Drought is one of the main sources of the interannual variability of carbon and water fluxes in North America. Drought is expected to become more frequent and more severe during the remainder of the 21st century and therefore will likely have larger impacts on terrestrial ecosystems

The Review of Nuclear Microscopy Techniques: An Approach for Nondestructive Trace Elemental Analysis and Mapping of Biological Materials

The properties of many biological materials often depend on the spatial distribution and concentration of the trace elements present in a matrix. Scientists have over the years tried various techniques including classical physical and chemical analyzing techniques each with relative level of accuracy. However, with the development of spatially sensitive submicron beams, the nuclear microprobe techniques using focused proton beams for the elemental analysis of biological materials have yielded significant success. In this paper, the basic principles of the commonly used microprobe techniques of STIM, RBS, and PIXE for trace elemental analysis are discussed. The details for sample preparation, the detection, and data collection and analysis are discussed. Finally, an application of the techniques to analysis of corn roots for elemental distribution and concentration is presented