Potential nitrogen constraints on soil carbon sequestration under low and elevated atmospheric CO2

The interaction between nitrogen cycling and carbon sequestration is critical in predicting the consequences of anthropogenic increases in atmospheric CO2 (hereafter, Ca). The progressive N limitation (PNL) theory predicts that carbon sequestration in plants and soils with rising Ca may be constrained by the availability of nitrogen in many ecosystems. Here we report on the interaction between C and N dynamics during a four-year field experiment in which an intact C3/C4 grassland was exposed to a gradient in Ca from 200 to 560 micromol/mol. There were strong species effects on decomposition dynamics, with C loss positively correlated and N mineralization negatively correlated with Ca for litter of the C3 forb Solanum dimidiatum, whereas decomposition of litter from the C4 grass Bothriochloa ischaemum was unresponsive to Ca. Both soil microbial biomass and soil respiration rates exhibited a nonlinear response to Ca, reaching a maximum at approximately 440 micromol/mol Ca. We found a general movement of N out of soil organic matter and into aboveground plant biomass with increased Ca. Within soils we found evidence of C loss from recalcitrant soil C fractions with narrow C:N ratios to more labile soil fractions with broader C:N ratios, potentially due to decreases in N availability. The observed reallocation of N from soil to plants over the last three years of the experiment supports the PNL theory that reductions in N availability with rising Ca could initially be overcome by a transfer of N from low C:N ratio fractions to those with higher C:N ratios. Although the transfer of N allowed plant production to increase with increasing Ca, there was no net soil C sequestration at elevated Ca, presumably because relatively stable C is being decomposed to meet microbial and plant N requirements. Ultimately, if the C gained by increased plant production is rapidly lost through decomposition, the shift in N from older soil organic matter to rapidly decomposing plant tissue may limit net C sequestration with increased plant production.     

Quantification and reduction of erroneous differences between images in remote sensing

The reliability of image data, along with the difficulty of accurately comparing images acquired at different times or from different sensors, is a generic problem in remote sensing. Measurement repeatability errors occur frequently and can substantially reduce the system’s ability to reliably quantify real spectral and spatial change in a target. This paper outlines methodologies for quantifying and reducing erroneous differences between monochrome and multispectral or hyperspectral images. [Each of these image types is acquired by an instrument that collects light photons across a variable range of the electromagnetic spectrum (often referred to as an image band). The hyperspectral image is often referred to as a hyperspectral cube with XY spatial dimensions and many Z bands (spectral demotions)]. In this paper, we specifically discuss the Pixel Block Transform (PBT), the Spectral Averaging Transform (SAT), and the Wavelet Transform (WAVEL). We briefly address sensor fusion. Results indicate that the PBT is a powerful cross-noise and repeatability error reducing tool, applicable to monochrome, multispectral, and hyperspectral images. The SAT is as powerful as the PBT in reducing error but is suitable only for hyperspectral imagery. WAVEL can reduce some of the finer scale noise, but it is not as powerful in reducing cross-noise as PBT or SAT and it requires some trial and error for selecting the appropriate wavelet function. It is important that those involved in developing statistically sound relationships between remotely sensed imagery and other data sources understand the problems and their solutions to prevent wasting time or developing relationships that are statistically insignificant or unstable, or that lead to faulty conclusions.     

Risk assessment of trihalomethanes from tap water in Fortaleza, Brazil

The cancer risks (CR) by oral ingestion, dermal absorption, and inhalation exposure of trihalomethanes (THM) from tap water of ten districts in Fortaleza, Brazil were estimated. The mean levels of THM compounds were obtained in Fortaleza tap water as follow: 63.9 microg L(-1) for chloroform (CHCl(3)), 40.0 microg L(-1) for bromodichloromethane (CHBrCl(2)), and 15.6 microg L(-1) for dibromochloromethane (CHBr(2)Cl). Bromoform (CHBr(3)) was not detected. The mean CR for THMs in tap water is 3.96 x 10(-4). The results indicate that Fortaleza residents have a higher CR by inhalation than dermal absorption and oral ingestion. The CR for CHCl(3) contributes with 68% as compared with the total CR, followed by CHBrCl(2) (21%), and CHBr(2)Cl (11%). The hazard index (HI) is about ten times lower than unity, not indicating non-cancer effects.     

State of the marine environment at Little Bay Arm,Newfoundland and Labrador,Canada, 10 years after a "do nothing" response to a mine tailings spill

In 1989, the tailings pond dam at the site of a former copper mine near Little Bay, Newfoundland and Labrador, Canada, ruptured and tailings spilled into Little Bay Arm. At the time, no action was taken to arrest the flow of tailings or to mitigate the effects of the spill. To date, no action has been taken to repair the dam and tailings continue to flow into Little Bay Arm. As a result, the marine environment around Little Bay Arm has become contaminated with heavy metals from the tailings. However, the tailings are not the only source of heavy metals to the ecosystem. An old slag heap and what is presumably concentrated copper ore spilled during the loading of ore freighters, are also contributing to the ecosystem's metal load. Marine sediment throughout the Arm contained elevated concentrations of Cu, Ni, Zn, As, V, Co, and Mn. Beach material also contained elevated concentrations of metals with material near the slag heap being the most contaminated. At this site, Cu concentrations were in excess of 5000 mg kg(-1) dry weight, Zn greater than 3000 mg kg(-1) and Co concentrations exceeded 700 mg kg(-1). The highest concentrations of metals in biota were found near the slag heap, near the tailings dam breach, and at the site of the former concentrate loading dock. Despite elevated metal concentrations, the tailings and nearby sediment were not devoid of life. Bivalves and seaweed were abundant in the area and there were no obvious signs of tissue damage or disease in soft shell clams (Mya arenaria) living in the tailings. These clams may be suffering from chronic exposure to the tailings, however, evidence of lipid peroxidation in the clams was inconclusive.     

Hyperspectral Characteristics of Canopy Components and Structure for Phenological Assessment of an Invasive Weed

Spectral reflectance values of four canopy components (stems, buds, opening flowers, and postflowers of yellow starthistle (Centaurea solstitialis)) were measured to describe their spectral characteristics. We then physically combined these canopy components to simulate the flowering stage indicated by accumulated flower ratios (AFR) 10%, 40%, 70%, and 90%, respectively. Spectral dissimilarity and spectral angles were calculated to quantitatively identify spectral differences among canopy components and characteristic patterns of these flowering stages. This study demonstrated the ability of hyperspectral data to characterize canopy components, and identify different flowering stages. Stems had a typical spectral profile of green vegetation, which produced a spectral dissimilarity with three reproduction organs (buds, opening flowers, and postflowers). Quantitative differences between simulated flower stages depended on spectral regions and phenological stages examined. Using full-range canopy spectra, the initial flowering stage could be separated from the early peak, peak, and late flowering stages by three spectral regions, i.e. the blue absorption (around 480 nm) and red absorption (around 650 nm) regions and NIR plateau from 730 nm to 950 nm. For airborne CASI data, only the red absorption region and NIR plateau could be used to identify the flowering stages in the field. This study also revealed that the peak flowering stage was more easily recognized than any of the other three stages.     

Characterization of Benthic Communities and Physical Habitat in the Stanislaus, Tuolumne, and Merced Rivers, California

The primary goal of this study was to characterize physical habitat and benthic communities (macroinvertebrates) in the Stanislaus, Tuolumne and Merced Rivers in California’s San Joaquin Valley in 2003. These rivers have been listed as impaired water bodies (303 (d) list) by the State of California due to the presence of organophosphate (OP) insecticides chlorpyrifos and diazinon, Group A pesticides (i.e., organochlorine pesticides), mercury, or unknown toxicity. Based on 10 instream and riparian physical habitat metrics, total physical habitat scores in the Stanislaus River ranged from 124 to 188 (maximum possible total score is 200). The highest total habitat score was reported at the upstream site. Tuolumne River physical habitat scores ranged from 86 to 167. Various Tuolumne River physical habitat metrics, including total habitat score, increased from downstream to upstream in this river. Merced River physical habitat scores ranged from 121 to 170 with a significant increase in various physical habitat metrics, including total habitat score, reported from downstream to upstream. Channel flow (an instream metric) and bank stability (a riparian metric) were the most important physical habitat metrics influencing the various benthic metrics for all three rivers. Abundance measures of benthic macroinvertebrates (5,100 to 5,400 individuals) were similar among the three rivers in the San Joaquin watershed. Benthic communities in all three rivers were generally dominated by: (1) Baetidae species (mayflies) which are a component of EPT taxa generally considered sensitive to environmental degradation; (2) Chironomidae (midges) which can be either tolerant or sensitive to environmental stressors depending on the species; (3) Ephemerellidae (mayflies) which are considered sensitive to pollution stress; and (4) Naididae (aquatic worms) which are generally considered tolerant to environmental stressors. The presence of 117 taxa in the Stanislaus River, 114 taxa in the Tuolumne River and 96 taxa in the Merced River implies that the benthic communities in these streams are fairly diverse but without a clear definition of benthic community expectations it is unknown if these water bodies are actually impaired.     

Pastoral farmland habitat diversity in south-east Ireland

In this study, habitat surveys were undertaken on 50 grass-based farms in SE Ireland and data digitised onto aerial photography. Additional data i.e. stocking rates, and participation (or otherwise) in the Irish Rural Environment Protection Scheme (REPS) were collected and analysed as possible explanatory variables for farm habitat composition.Results indicated that approximately 14.3% of the land area of sampled farms comprised of semi-natural habitat types, a proportion substantially greater than has been reported for many other European countries. The most frequently recorded semi-natural habitats included, field boundaries, scrub, and deciduous and riparian woodlands.Multivariate analysis of farm habitat configuration showed a strong dichotomy between dairy and non-dairy farming systems. Habitats such as intensively managed grassland and built ground were closely associated with dairy-based enterprises. In contrast, the incidence of other habitat types was associated with non-dairy and/or REPS participating enterprises. The ecological quality of field boundaries as assessed by the Field Boundary Evaluation and Grading System (FBEGS) Index was significantly greater on dairy, compared with dry-stock farms.This dichotomy in farm habitat composition is not reflected within current Agri-Environment (AE) policy. Integration of locally important drivers of habitat diversity into the design and implementation of AE policy, is integral to the successful performance of AE schemes.     

Evaluating the success of functional restoration after reintroduction of a lost avian pollinator

Conservation translocation is a common method for species recovery, for which one increasingly frequent objective is restoring lost ecological functions to promote ecosystem recovery. However, few conservation translocation programs explicitly state or monitor function as an objective, limiting the ability to test assumptions, learn from past efforts, and improve management. We evaluated whether translocations of hihi (Notiomystis cincta), a threatened New Zealand passerine, achieved their implicit objective of restoring lost pollination function. Through a pollinator-exclusion experiment, we quantified, with log response ratios (lnR), the effects of birds on fruit set and seed quality in hangehange (Geniostoma ligustrifolium), a native flowering shrub. We isolated the contributions of hihi by making comparisons across sites with and without hihi. Birds improved fruit set more at sites without hihi (lnR = 1.27) than sites with hihi (lnR = 0.50), suggesting other avian pollinators compensated for and even exceeded hihi contributions to fruit set. Although birds improved seed germination only at hihi sites (lnR = 0.22–0.41), plants at sites without hihi had germination rates similar to hihi sites because they produced 26% more filled seeds, regardless of pollination condition. Therefore, although our results showed hihi improved seed quality, they also highlighted the complexity of ecological functions. When an important species is lost, ecosystems may be able to achieve similar function through different means. Our results underscore the importance of stating and monitoring the ecological benefits of conservation translocations when functional restoration is a motivation to ensure these programs are achieving their objectives.     

Airborne reduced nitrogen: ammonia emissions from agriculture and other sources

Ammonia is a basic gas and one of the most abundant nitrogen-containing compounds in the atmosphere. When emitted, ammonia reacts with oxides of nitrogen and sulfur to form particles, typically in the fine particle size range. Roughly half of the PM(2.5) mass in eastern United States is ammonium sulfate, according to the US EPA. Results from recent studies of PM(2.5) show that these fine particles are typically deposited deep in the lungs and may lead to increased morbidity and/or mortality. Also, these particles are in the size range that will degrade visibility. Ammonia emission inventories are usually constructed by multiplying an activity level by an experimentally determined emission factor for each source category. Typical sources of ammonia include livestock, fertilizer, soils, forest fires and slash burning, industry, vehicles, the oceans, humans, pets, wild animals, and waste disposal and recycling activities. Livestock is the largest source category in the United States, with waste from livestock responsible for about 3x10(9) kg of ammonia in 1995. Volatilization of ammonia from livestock waste is dependent on many parameters, and thus emission factors are difficult to predict. Despite a seasonal variation in these values, the emission factors for general livestock categories are usually annually averaged in current inventories. Activity levels for livestock are from the USDA Census of Agriculture, which does not give information about animal raising practices such as housing types and grazing times, waste handling systems, and approximate animal slurry spreading times or methods. Ammonia emissions in the United States in 1995 from sources other than livestock are much lower; for example, annual emissions are roughly 8x10(8) kg from fertilizer, 7x10(7) kg from industry, 5x10(7) kg from vehicles and 1x10(8) kg from humans. There is considerable uncertainty in the emissions from soil and vegetation, although this category may also be significant. Recommendations for future directions in ammonia research include designing experiments to improve emission factors and their resolution in all significant source categories, developing mass balance models, and refining of the livestock activity level data by eliciting judgment from experts in this field.