Applying metabolic fingerprinting to ecology: The use of Fourier-transform infrared spectroscopy for the rapid screening of plant responses to N deposition

The potential for metabolic fingerprinting via Fourier-transform infrared (FT-IR) spectroscopy to provide a novel approach for the detection of plant biochemical responses to N deposition is examined. An example of spectral analysis using shoot samples taken from an open top chamber (OTC) experiment simulating wet ammonium deposition is given. Sample preparation involved oven drying and homogenisation via mill grinding. Slurries of a consistent dilution were then prepared prior to FT-IR analysis. Spectra from control, 8 and 16 kg N ha^–1 yr^–1 treatments were then subjected to cross-validated discriminant function analysis. Ordination diagrams showed clear separation between the three N treatments examined. The potential for using Calluna vulgaris (L.) Hull as a bioindicator of N deposition is further evident from these results. The results also clearly demonstrate the power of FT-IR in discriminating between subtle phenotypic alterations in overall plant biochemistry as affected by ammonium pollution.     

Energy use,blue water footprint,and greenhouse gas emissions for current food consumption patterns and dietary recommendations in the US

This article measures the changes in energy use, blue water footprint, and greenhouse gas (GHG) emissions associated with shifting from current US food consumption patterns to three dietary scenarios, which are based, in part, on the 2010 USDA Dietary Guidelines (US Department of Agriculture and US Department of Health and Human Services in Dietary Guidelines for Americans, 2010, 7th edn, US Government Printing Office, Washington, 2010). Amidst the current overweight and obesity epidemic in the USA, the Dietary Guidelines provide food and beverage recommendations that are intended to help individuals achieve and maintain healthy weight. The three dietary scenarios we examine include (1) reducing Caloric intake levels to achieve “normal” weight without shifting food mix, (2) switching current food mix to USDA recommended food patterns, without reducing Caloric intake, and (3) reducing Caloric intake levels and shifting current food mix to USDA recommended food patterns, which support healthy weight. This study finds that shifting from the current US diet to dietary Scenario 1 decreases energy use, blue water footprint, and GHG emissions by around 9 %, while shifting to dietary Scenario 2 increases energy use by 43 %, blue water footprint by 16 %, and GHG emissions by 11 %. Shifting to dietary Scenario 3, which accounts for both reduced Caloric intake and a shift to the USDA recommended food mix, increases energy use by 38 %, blue water footprint by 10 %, and GHG emissions by 6 %. These perhaps counterintuitive results are primarily due to USDA recommendations for greater Caloric intake of fruits, vegetables, dairy, and fish/seafood, which have relatively high resource use and emissions per Calorie.     

The effect of industry activities on public support for ‘fracking’

Research suggests that previous, current, and prospective extractive industry activities influence perceptions of new development. Studies that have drawn this conclusion, however, have usually focused on specific projects in specific communities. Here, these factors are examined on an aggregate, national scale. Combining geospatial data on extractive industry activities and survey data from a nationally representative sample (N = 1061), the influence of extractive industry activities on support for fracking is studied. While limited evidence is found for the impact of proximity to oil and gas wells or production on support for fracking, employment levels in the natural resources and mining sector in the respondent’s county and residence in an area experiencing active oil and gas development significantly increase support for fracking. The results highlight the role of spatial and community factors in shaping support for energy development.     

Designing and Implementing a Network for Sensing Water Quality and Hydrology across Mountain to Urban Transitions

Water resources are increasingly impacted by growing human populations, land use, and climate changes, and complex interactions among biophysical processes. In an effort to better understand these factors in semiarid northern Utah, United States, we created a real‐time observatory consisting of sensors deployed at aquatic and terrestrial stations to monitor water quality, water inputs, and outputs along mountain to urban gradients. The Gradients Along Mountain to Urban Transitions (GAMUT) monitoring network spans three watersheds with similar climates and streams fed by mountain winter‐derived precipitation, but that differ in urbanization level, land use, and biophysical characteristics. The aquatic monitoring stations in the GAMUT network include sensors to measure chemical (dissolved oxygen, specific conductance, pH, nitrate, and dissolved organic matter), physical (stage, temperature, and turbidity), and biological components (chlorophyll‐a and phycocyanin). We present the logistics of designing, implementing, and maintaining the network; quality assurance and control of numerous, large datasets; and data acquisition, dissemination, and visualization. Data from GAMUT reveal spatial differences in water quality due to urbanization and built infrastructure; capture rapid temporal changes in water quality due to anthropogenic activity; and identify changes in biological structure, each of which are demonstrated via case study datasets.     

Mixed-Grass Prairie Canopy Structure and Spectral Reflectance Vary with Topographic Position

Managers of the nearly 0.5 million ha of public lands in North and South Dakota, USA rely heavily on manual measurements of canopy height in autumn to ensure conservation of grassland structure for wildlife and forage for livestock. However, more comprehensive assessment of vegetation structure could be achieved for mixed-grass prairie by integrating field survey, topographic position (summit, mid and toeslope) and spectral reflectance data. Thus, we examined the variation of mixed-grass prairie structural attributes (canopy leaf area, standing crop mass, canopy height, nitrogen, and water content) and spectral vegetation indices (VIs) with variation in topographic position at the Grand River National Grassland (GRNG), South Dakota. We conducted the study on a 36,000-ha herbaceous area within the GRNG, where randomly selected plots (1?km² in size) were geolocated and included summit, mid and toeslope positions. We tested for effects of topographic position on measured vegetation attributes and VIs calculated from Landsat TM and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data collected in July 2010. Leaf area, standing crop mass, canopy height, nitrogen, and water content were lower at summits than at toeslopes. The simple ratio of Landsat Band 7/Band 1 (SR71) was the VI most highly correlated with canopy standing crop and height at plot and landscape scales. Results suggest field and remote sensing-based grassland assessment techniques could more comprehensively target low structure areas at minimal expense by layering modeled imagery over a landscape stratified into topographic position groups.     

Graduate Education for Air Pollution Control Personnel

Tendergreen bean plants were grown from seeding to seed maturity under continuous exposure to HF gas at fairly uniform concentrations averaging 0.58, 2.1, 9.1, and 10.5 µg F/m³. Progeny of these plants and of comparable control plants were grown in a clean atmosphere to determine if subsequent generations were affected by HF treatment of the parents.

No effects of HF were found among the progeny of the plants grown at 0.58 µg F/m³. The F₁ generation progeny of the other HF treated plants were less vigorous than control plant progeny, as shown by later emergence, smaller primary leaves, and slower stem growth. This probably was a consequence of the lower starch content of the seed of the HF treated plants. The primary leaves of some F₁ progeny of the plants grown in the three highest HF treatments were severely stunted and distorted. This also may have been due to the low starch content of the seed, or perhaps it resulted from damage to the plumules in shriveled, distorted seed produced in these treatments.

Some of the early trifoliate leaves of many F₁ generation progeny of the plants grown at 2.1 µg F/m³ and higher were abnormal in the separation and number of their leaflets. This abnormality apparently was heritable, for in the next (F₂) generation it occurred most frequently among plants whose parents were abnormal. However, considerably fewer F₃ generation plants had abnormal trifoliate leaves, indicating rapid reversal to the normal form.     

Applying metabolic fingerprinting to ecology: The use of Fourier-transform infrared spectroscopy for the rapid screening of plant responses to N deposition

The potential for metabolic fingerprinting via Fourier-transform infrared (FT-IR) spectroscopy to provide a novel approach for the detection of plant biochemical responses to N deposition is examined. An example of spectral analysis using shoot samples taken from an open top chamber (OTC) experiment simulating wet ammonium deposition is given. Sample preparation involved oven drying and homogenisation via mill grinding. Slurries of a consistent dilution were then prepared prior to FT-IR analysis. Spectra from control, 8 and 16 kg N ha^?1 yr^?1 treatments were then subjected to cross-validated discriminant function analysis. Ordination diagrams showed clear separation between the three N treatments examined. The potential for using Calluna vulgaris (L.) Hull as a bioindicator of N deposition is further evident from these results. The results also clearly demonstrate the power of FT-IR in discriminating between subtle phenotypic alterations in overall plant biochemistry as affected by ammonium pollution.     

Preparing future engineers for challenges of the 21st century: Sustainable engineering

The field of engineering is changing rapidly as the growing global population puts added demands on the earth's resources: engineering decisions must now account for limitations in materials and energy as well as the need to reduce discharges of wastes. This means educators must revise courses and curricula so engineering graduates are prepared for the new challenges as practicing engineers. The Center for Sustainable Engineering has been established to help faculty members accommodate such changes through workshops and new educational materials, including a free access website with peer-reviewed materials.     

A trait-based test for habitat filtering: convex hull volume

Community assembly theory suggests that two processes affect the distribution of trait values within communities: competition and habitat filtering. Within a local community, competition leads to ecological differentiation of coexisting species, while habitat filtering reduces the spread of trait values, reflecting shared ecological tolerances. Many statistical tests for the effects of competition exist in the literature, but measures of habitat filtering are less well-developed. Here, we present convex hull volume, a construct from computational geometry, which provides an n-dimensional measure of the volume of trait space occupied by species in a community. Combined with ecological null models, this measure offers a useful test for habitat filtering. We use convex hull volume and a null model to analyze California woody-plant trait and community data. Our results show that observed plant communities occupy less trait space than expected from random assembly, a result consistent with habitat filtering.