Rapid amino acid cycling in arctic and antarctic soils

Amino acids constitute one of the largest inputs of organic nitrogen (N) to most polar soils and have been hypothesized to be important in regulating vegetational succession and productivity in Arctic ecosystems. Our understanding of amino acid cycling in these soils, however, is poor. The aim of this study was to investigate the size and rate of turnover of the amino acid pool in a range of Arctic and Antarctic soils. Our results indicate that in polar soils with either high or low ornithogenic inputs the amino acid pool is small in comparison to the inorganic N pool (NO^? ₃ and NH⁺ ₄). The free amino acid pool constituted only a small proportion of the total dissolved organic nitrogen (DON) pool in these soils. Here we show that these low concentrations may be due to rapid use by the soil microbial community in both Arctic and Antarctic soils. The turnover of the amino acid pool in soil was extremely rapid, with a half-life ranging from 2 to 24 h, indicating that this N pool can be turned over many hundred times each summer when polar soils are frequently unfrozen. The implications of amino acids in N cycling and plant and microbial nutrition are discussed.     

Application of a health promotion model to community-based sustainability planning

The future of human health and that of all other species depends on the viability and sustainability of a host of environments and ecosystems. Human behaviours have profound effects (both positive and negative) on such ecosystems. Despite the obviousness of these statements, there remains a lack of clarity around the mechanisms for altering specific behaviours related to sustainability and their impact on environments. This paper offers a conceptual framework for identifying relations between human behaviour and ecosystem health and sustainability. We also discuss strategies for changing target behaviours in the context of a programme or policy planning. Finally, we draw on research that applies this adaptation to a small island community near Vancouver, Canada.     

Sustainable land application: an overview

Man has land-applied societal nonhazardous wastes for centuries as a means of disposal and to improve the soil via the recycling of nutrients and the addition of organic matter. Nonhazardous wastes include a vast array of materials, including manures, biosolids, composts, wastewater effluents, food-processing wastes, industrial by-products; these are collectively referred to herein as residuals. Because of economic restraints and environmental concerns about land-filling and incineration, interest in land application continues to grow. A major lesson that has been learned, however, is that the traditional definition of land application that emphasizes applying residuals to land in a manner that protects human and animal health, safeguards soil and water resources, and maintains long-term ecosystem quality is incomplete unless the earning of public trust in the practices is included. This overview provides an introduction to a subset of papers and posters presented at the conference, "Sustainable Land Application," held in Orlando, FL, in January 2004. The USEPA, USDA, and multiple national and state organizations with interest in, and/or responsibilities for, ensuring the sustainability of the practice sponsored the conference. The overriding conference objectives were to highlight significant developments in land treatment theory and practice, and to identify future research needs to address critical gaps in the knowledge base that must be addressed to ensure sustainable land application of residuals.     

BASIN SCALE WATER MANAGEMENT AND FORECASTING USING ARTIFICIAL NEURAL NETWORKS1

ABSTRACT: Water scarcity in the Sevier River Basin in south‐central Utah has led water managers to seek advanced techniques for identifying optimal forecasting and management measures. To more efficiently use the limited quantity of water in the basin, better methods for control and forecasting are imperative. Basin scale management requires advanced forecasts of the availability of water. Information about long term water availability is important for decision making in terms of how much land to plant and what crops to grow; advanced daily predictions of streamflows and hydraulic characteristics of irrigation canals are of importance for managing water delivery and reservoir releases; and hourly forecasts of flows in tributary streams to account for diurnal fluctuations are vital to more precisely meet the day‐to‐day expectations of downstream farmers. A priori streamflow information and exogenous climate data have been used to predict future streamflows and required reservoir releases at different timescales. Data on snow water equivalent, sea surface temperatures, temperature, total solar radiation, and precipitation are fused by applying artificial neural networks to enhance long term and real time basin scale water management information. This approach has not previously been used in water resources management at the basin‐scale and could be valuable to water users in semi‐arid areas to more efficiently utilize and manage scarce water resources.     

Improvements of nano-SiO2 on sludge/fly ash mortar

Sewage sludge ash has been widely applied to cementitious materials. In this study, in order to determine effects of nano-SiO(2) additives on properties of sludge/fly ash mortar, different amounts of nano-SiO(2) were added to sludge/fly ash mortar specimens to investigate their physical properties and micro-structures. A water-binding ratio of 0.7 was assigned to the mix. Substitution amounts of 0%, 10%, 20%, and 30% of sludge/fly ash (1:1 ratio) were proposed. Moreover, 0%, 1%, 2%, and 3% of nano-SiO(2) was added to the mix. Tests, including SEM and compressive strength, were carried out on mortar specimens cured at 3, 7, and 28 days. Results showed that sludge/fly ash can make the crystals of cement hydration product finer. Moreover, crystals increased after nano-SiO(2) was added. Hence, nano-SiO(2) can improve the effects of sludge/fly ash on the hydration of mortar. Further, due to the low pozzolanic reaction active index of sludge ash, early compressive strengths of sludge/fly ash mortar were decreased. Yet, nano-SiO(2) could help produce hydration crystals, which implies that the addition of nano-SiO(2) to mortar can improve the influence of sludge/fly ash on the development of the early strength of the mortar.     

Wind direction bias in generating wind roses and conducting sector-based air dispersion modeling

Certain widely used wind rose programs and air dispersion models use an overly simple data-transfer algorithm that induces a directional bias in their output products. The purpose of this paper is to provide a revised algorithm that corrects the directional bias that occurs from the aliasing that occurs when the sector widths used to report wind direction data are on the same order of magnitude, but not equal, to the sector widths used in the wind direction summaries. The directional bias issue arises when output products in 16 direction sectors (22.5 degrees each) are produced from wind direction data reported in terms of 36 sectors (10 degrees each). The result directional bias affects the results of simulations of air and surface concentrations using widely applied air dispersion models. Datasets or models with the directional bias discussed here give consistent positive biases (approximately 30%) for cardinal direction sectors (north, south, east, and west) and consistent negative biases for all of the other sectors (around -10%). Data summary and air dispersion programs providing outputs in direction sectors that do not match the observational sectors need to be checked for this bias. A revised data-transfer algorithm is provided that corrects the directional bias that can occur in transferring wind direction data between different sector widths.     

Will Observation Error and Biases Ruin the Use of Simple Extinction Models?

Abstract: Estimating the risk of extinction for populations of endangered species is an important component of conservation biology. These estimates must be made from data that contain both environmental noise in the year-to-year transitions in population size (so-called "process error"), random errors in sampling, and possible biases in sampling ( both forms of observation errors). To determine how much faith to place in estimated extinction rates, it is important to know how sensitive they are to observation error. We used three simple, commonly employed models of population dynamics to generate simulated population time series. We then combined random observation error or systematic biases with those data, fit models to the time series data, and observed how close the extinction dynamics of the fitted models compared with the dynamics of the underlying models. We found that systematic biases in sampling rarely affected estimates of extinction risk. We also found that even moderate levels of random observation error do not significantly affect extinction estimates except over a small range of process errors, corresponding to the region where extinction risk is most uncertain. With more substantial sampling error, estimates of extinction risk degraded rapidly. Field census techniques for a variety of taxa often involve observation errors within ±32% of actual population sizes. For typical time series used in conservation, therefore, we often may not need to be overly concerned about observation errors as an extra source of imperfection in our estimated extinction rates.     

Genetic differentiation in a pelagic crustacean (Meganyctiphanes norvegica: Euphausiacea) from the North East Atlantic and the Mediterranean Sea

Meganyctiphanes norvegica (M. Sars)is a pelagic crustacean that plays a key role in marine food webs of North Atlantic Ocean and marginal seas. We studied eight population samples collected in the European Atlantic and Mediterranean Sea. By means of single strand conformation polymorphism analysis (SSCP) and direct sequencing, we investigated a segment of 158 base pairs of the mitochondrial gene coding for the subunit 1 of NADH dehydrogenase. We found 12 sequence variants among the 385 individuals studied. Analysis of molecular variance (AMOVA) showed that 14.75% of the total genetic variability was explained by differences between populations, thus indicating absence of panmixia for these populations. Pairwise comparisons revealed three distinct genetic pools: the first one represented by Cadiz Bay, the second one by the Ligurian Sea, and the third one included all the NE Atlantic samples. We also investigated one population from the Alboran Sea (within the Mediterranean basin, east of the Strait of Gibraltar). This population was found to be genetically intermediate between the NE Atlantic samples and the Ligurian sample, suggesting that the restriction to the gene flow is not associated with the Strait of Gibraltar, but possibly with the Oran–Almeria oceanographic front. The present work indicates that M. norvegica, although endowed with a high dispersal capacity because of its pelagic habit, can develop separate breeding units inside the same oceanic basin (the Atlantic). Furthermore, the Ligurian sample should be considered as a distinct evolutionary entity, separated from the Atlantic population. Received: 2 May 1999 / Accepted: 26 November 1999