Statistical uncertainty of eddy flux–based estimates of gross ecosystem carbon exchange at Howland Forest, Maine

We present an uncertainty analysis of gross ecosystem carbon exchange (GEE) estimates derived from 7 years of continuous eddy covariance measurements of forest-atmosphere CO2fluxes at Howland Forest, Maine, USA. These data, which have high temporal resolution, can be used to validate process modeling analyses, remote sensing assessments, and field surveys. However, separation of tower-based net ecosystem exchange (NEE) into its components (respiration losses and photosynthetic uptake) requires at least one application of a model, which is usually a regression model fitted to nighttime data and extrapolated for all daytime intervals. In addition, the existence of a significant amount of missing data in eddy flux time series requires a model for daytime NEE as well. Statistical approaches for analytically specifying prediction intervals associated with a regression require, among other things, constant variance of the data, normally distributed residuals, and linearizable regression models. Because the NEE data do not conform to these criteria, we used a Monte Carlo approach (bootstrapping) to quantify the statistical uncertainty of GEE estimates and present this uncertainty in the form of 90% prediction limits. We explore two examples of regression models for modeling respiration and daytime NEE: (1) a simple, physiologically based model from the literature and (2) a nonlinear regression model based on an artificial neural network. We find that uncertainty at the half-hourly timescale is generally on the order of the observations themselves (i.e., ∼100%) but is much less at annual timescales (∼10%). On the other hand, this small absolute uncertainty is commensurate with the interannual variability in estimated GEE. The largest uncertainty is associated with choice of model type, which raises basic questions about the relative roles of models and data

Changes in co-existence mechanisms along a long-term soil chronosequence revealed by functional trait diversity

1. Functional trait diversity can reveal mechanisms of species co-existence in plant communities. Few studies have tested whether functional diversity for foliar traits related to resource use strategy increases or decreases with declining soil phosphorus (P) in forest communities. 2. We quantified tree basal area and four foliar functional traits (i.e. nitrogen (N), phosphorus (P), thickness and tissue density) for all woody species along the c. 120 kyr Franz Josef soil chronosequence in cool temperate rainforest, where strong shifts occur in light and soil nutrient availability (i.e. total soil P declines from 805 to 100 mg g–1). We combined the abundance and trait data in functional diversity indices to quantify trait convergence and divergence, in an effort to determine whether mechanisms of co-existence change with soil fertility. 3. Relationships between species trait means and total soil N and P were examined using multiple regression, with and without weighting of species abundances. We used Rao’s quadratic entropy to quantify functional diversity at the plot scale, then compared this with random expectation, using a null model that randomizes abundances across species within plots. Taxonomic diversity was measured using Simpson’s Diversity. Relationships between functional and taxonomic diversity and total soil P were examined using jackknife linear regression. 4. Leaf N and P declined and leaf thickness and density increased monotonically with declining total soil P along the sequence; these relationships were unaffected by abundance-weighting of species in the analyses. Inclusion of total soil N did not improve predictions of trait means. All measures of diversity calculated from presence/absence data were unrelated to total soil N and P. There was no evidence for a relationship between Rao values using quantitative abundances and total soil P. However, there was a strongly positive relationship between Rao, expressed relative to random expectation, and total soil P, indicating trait convergence of dominant species as soil P declined. 5. Synthesis: Our results demonstrate that at high fertility dominant species differ in resource use strategy, but as soil fertility declines over the long-term, dominant species increasingly converge on a resource-retentive strategy. This suggests that differentiation in resource use strategy is required for co-existence at high fertility but not in low fertility ecosystems

Near-surface remote sensing of spatial and temporal variation in canopy phenology

There is a need to document how plant phenology is responding to global change factors, particularly warming trends. “Near-surface” remote sensing, using radiometric instruments or imaging sensors, has great potential to improve phenological monitoring because automated observations can be made at high temporal frequency. Here we build on previous work and show how inexpensive, networked digital cameras (“webcams”) can be used to document spatial and temporal variation in the spring and autumn phenology of forest canopies. We use two years of imagery from a deciduous, northern hardwood site, and one year of imagery from a coniferous, boreal transition site. A quantitative signal is obtained by splitting images into separate red, green, and blue color channels and calculating the relative brightness of each channel for “regions of interest” within each image. We put the observed phenological signal in context by relating it to seasonal patterns of gross primary productivity, inferred from eddy covariance measurements of surface–atmosphere CO2 exchange. We show that spring increases, and autumn decreases, in canopy greenness can be detected in both deciduous and coniferous stands. In deciduous stands, an autumn red peak is also observed. The timing and rate of spring development and autumn senescence varies across the canopy, with greater variability in autumn than spring. Interannual variation in phenology can be detected both visually and quantitatively; delayed spring onset in 2007 compared to 2006 is related to a prolonged cold spell from day 85 to day 110. This work lays the foundation for regional- to continental-scale camera-based monitoring of phenology at network observatory sites, e.g., National Ecological Observatory Network (NEON) or AmeriFlux

Acoustic measurement of lubricant-film thickness distribution in ball bearings

An oil-film thickness monitoring system capable of providing an early warning of lubrication failure in rolling element bearings has been developed. The system is used to measure the lubricant-film thickness in a conventional deep groove ball bearing (shaft diameter 80 mm, ball diameter 12.7 mm). The measurement system comprises a 50 MHz broadband ultrasonic focused transducer mounted on the static outer raceway of the bearing. Typically the lubricant-films in rolling element bearings are between 0.1-1.0 μm in thickness and so are significantly smaller than the ultrasonic wavelength. A quasistatic spring model is used to calculate oil-film thickness from the measured reflection coefficient data. An accurate triggering system has been developed to enable multiple reflection coefficient measurements to be made as the contact ellipse sweeps over the measurement location. Experiments are described in which the loading conditions and rotational speed are varied. Lubricant-film thickness distributions measured ultrasonically are described and are shown to agree well with the predictions from classical elastohydrodynamic (EHD) lubrication theory, particularly at high radial loads and low rotary speeds. A range of parameters affecting the performance of the measurement are discussed and the limits of operation of the measurement technique defined. © 2006 Acoustical Society of America

Benefits and challenges of applying Semantic Web Services in the e-Government domain

Joining up services in e-Government usually implies governmental agencies acting in concert without a central control regime. This requires the sharing of scattered and heterogeneous data. Semantic Web Service (SWS) technology can help to integrate, mediate and reason between these datasets. However, since few real-world applications have been developed, it is still unclear which are the actual benefits and issues of adopting such a technology in the e-Government domain. In this paper, we contribute to raising awareness of the potential benefits in the e-Government community by analyzing motivations, requirements, and expected results, before proposing a reusable SWS-based framework. We demonstrate the application of this framework by a compelling use case: a GIS-based emergency planning system. We illustrate the obtained benefits and the key challenges which remain to be addressed

Geospatial data integration with Semantic Web services: the eMerges approach

Geographic space still lacks the semantics allowing a unified view of spatial data. Indeed, as a unique but all encompassing domain, it presents specificities that geospatial applications are still unable to handle. Moreover, to be useful, new spatial applications need to match human cognitive abilities of spatial representation and reasoning. In this context, eMerges, an approach to geospatial data integration based on Semantic Web Services (SWS), allows the unified representation and manipulation of heterogeneous spatial data sources. eMerges provides this integration by mediating legacy spatial data sources to high-level spatial ontologies through SWS and by presenting for each object context dependent affordances. This generic approach is applied here in the context of an emergency management use case developed in collaboration with emergency planners of public agencies

The RNA Ontology (RNAO): An ontology for integrating RNA sequence and structure data

Biomedical Ontologies are intended to integrate diverse biomedical data to enable intelligent data-mining and facilitate translation of basic research into useful clinical knowledge. We present the first version of RNAO, an ontology for integrating RNA 3D structural, biochemical and sequence data. While each 3D data file depicts the structure of a specific molecule, such data have broader significance as representatives of classes of homologous molecules, which, while differing in sequence, generally share core structural features of functional importance. Thus, 3D structure data gain value by being linked to homologous sequences in genomic data and databases of sequence alignments. Likewise genomic data can increase in value by annotation of shared structural features, especially when these can be linked to specific functions. The RNAO is being developed in line with the developing standards of the Open Biomedical Ontologies (OBO) Consortium

Free-Enterprise Farming on Grasslands in Central NSW, Australia

A pathway is described in developing and improving the pastures on family-owned sheep and beef properties at sites near Blayney in central NSW. Initially, the twin approach of sowing perennial grasses, predominantly phalaris (Phalaris aquatica) with subterranean clover (Trifolium subterraneum) plus the recommended addition of superphosphate fertiliser, was closely followed but within a decade ill-thrift in pastures and livestock occurred. Once the core problem of soil acidity was recognised, steps were taken to overcome this constraint with applications of lime. However, an additional modification involving the application of gypsum with lime had to be sorted out and applied. This approach is explained. While recent drought conditions on the Central Tablelands/Slopes have been a factor in reducing the productivity of district pastures, an important part of the problem is a consequence of many landowners not understanding the basic principles of plant and livestock nutrition, an unwillingness of some research/advisory agronomists to recognise the expertise of successful producers, and the implementation of various farmer subsidy and support schemes that appear to reward dependent producers rather than encouraging independence