The use of polymerase chain reaction for the identification of sciaenid eggs

Traditionally, sciaenid eggs have been identified based on morphological characteristics such as size, number of oil globules and/or pigmentation patterns. Identification of sciaenid eggs by these procedures is time consuming and often inaccurate due to considerable egg size overlap among species. The utilization of molecular techniques for the identification of economically important species has become a fundamental component in ecological studies involving fish eggs and larvae. This study reports the development of a series of both multiplex and individual polymerase chain reactions to identify the eggs of 11 sciaenid species commonly found in the Gulf of Mexico and estuaries near Port Aransas and Corpus Christi, TX, USA. Following method development, the discriminatory power of the assay was first determined with samples from adult fish collected from Aransas and Corpus Christi Bays, Galveston Bay and the lower Laguna Madre in northern Mexico. Most (97%) of these fishes were correctly identified to the level of species. To demonstrate the applicability of the assay, wild fish eggs were collected and analyzed from the Aransas Pass tidal inlet from September through December 2005. During this period, the eggs of four target species were positively identified which was in keeping with current knowledge regarding the spawning areas and seasons of these sciaenids based on the presence of mature females, eggs and/or larvae. Future use of this method can provide valuable information to better discriminate spawning sites and seasons of these species.     

Iterating Masuyama’s method to reduce sampling variation

Masuyama in Sankhya 14(3):181–186, 1954 gave a method for addressing the boundary overlap problem that arises when sampling in a delineated study region. Here we propose a general sampling framework that allows one to iterate Masuyama’s method in a way that provides a smaller sampling variance. Results of simulations comparing the proposed method to existing approaches for addressing the boundary overlap problem are given. Variations, including systematic sampling, are also discussed.     

NEW METHODS OF MODELING WATER AVAILABILITY FOR AGRICULTURE UNDER CLIMATE CHANGE: THE U.S. CORNBELT1

ABSTRACT: This paper reports on new methods of linking climate change scenarios with hydrologic, agricultural an water planning models to study future water availability for agriculture, an essential element of sustainability. The study is based on the integration of models of water supply and demand, and of crop growth and irrigation management. Consistent modeling assumptions, available databases, and scenario simulations are used to capture a range of possible future conditions. The linked models include WATBAL for water supply; CERES, SOYGRO, and CROPWAT for crop and irrigation modeling; and WEAP for water demand forecasting, planning and evaluation. These models are applied to the U.S. Cornbelt using forecasts of climate change, agricultural production, population and GDP growth. Results suggest that, at least in the near term, the relative abundance of water for agriculture can be maintained under climate change conditions. However, increased water demands from urban growth, increases in reservoir evaporation and increases in crop consumptive use must be accommodated by timely improvements in crop, irrigation and drainage technology, water management, and institutions. These improvements are likely to require substantial resources and expertise. In the highly irrigated basins of the region, irrigation demand greatly exceeds industrial and municipal demands. When improvements in irrigation efficiency are tested, these basins respond by reducing demand and lessening environmental stress with an improvement in system reliability, effects particularly evident under a high technology scenario. Rain-fed lands in the Cornbelt are not forced to invest in irrigation, but there is some concern about increased water-logging during the spring and consequent required increased investment in agricultural drainage. One major water region in the Cornbelt also provides a useful caveat: change will not necessarily be continuous and monotonic. Under one GCM scenario for the 2010s, the region shows a significant decrease in system reliability, while the scenario for the 2020s shows an increase.     

Alternative prey and the dynamics of intraguild predation: theoretical perspectives

A rich body of theoretical literature now exists focused on the three-species module of intraguild predation (IGP), in which a top predator both attacks and competes with an intermediate predator. Simple models of intraguild predation are often unstable, either because one consumer is excluded, or because sustained oscillations emerge from long feedback loops. Yet, many natural IGP systems robustly persist. Standard models of intraguild predation simplify natural systems in crucial ways that could influence persistence; in particular, many empirical IGP systems are embedded in communities with alternative prey species. We briefly review the key conclusions of standard three-species IGP theory, and then present results of theoretical explorations of how alternative prey can influence the persistence and stability of a focal intraguild predation interaction.     

EFFECTIVENESS OF WASTE MINIMIZATION PROJECTS IN REDUCING WATER DEMAND BY UK INDUSTRY1

ABSTRACT: There is growing interest in managing water demand in the UK. A series of waste minimization clubs have been set up within the country and this paper identifies the effectiveness of these clubs in reducing the demand for water within industry. Membership of these clubs is voluntary and the only incentive for industry to reduce water consumption, and consequently the production of effluent, is the almost immediate financial saving made by the company, often achieved by accounting for the water consumption and loss within site from the point of input from the water supplier to output in the form of effluent. On average, companies are able to reduce water consumption by up to 30 percent. If the entire industrial sector within the UK were to achieve this degree of savings, it is possible that approximately 1300Ml/d could be saved.     

Score averaging for alien species risk assessment: a probabilistic alternative

In many biological risk assessment problems and specifically those involving invasive alien species and quarantine pests, ordinal scoring systems are used as a basis for risk quantification. Frequently, the problem is disaggregated into a series of components to allow a more structured and systematic evaluation. Each component is then scored and an overall measure of risk calculated from the set of scores. No satisfactory method exists to compute an overall measure of risk and most practitioners have resorted to score-averaging. Here we describe an approach involving the linear mapping of scores to notional probabilities to allow the use of conditional probability to derive an overall measure. Initial results give better discrimination between high and low risk cases and closer correspondence with independent expert judgement than does score-averaging.     

Toxic effects of Pb2+ on growth of cowpea (Vigna unguiculata)

A concentration as low as 1 microM lead (Pb) is highly toxic to plants, but previous studies have typically related plant growth to the total amount of Pb added to a solution. In the present experiment, the relative fresh mass of cowpea (Vigna unguiculata) was reduced by 10% at a Pb2+ activity of 0.2 microM for the shoots and at a Pb2+ activity of 0.06 microM for the roots. The primary site of Pb2+ toxicity was the root, causing severe reductions in root growth, loss of apical dominance (shown by an increase in branching per unit root length), the formation of localized swellings behind the root tips (due to the initiation of lateral roots), and the bending of some root tips. In the root, Pb was found to accumulate primarily within the cell walls and intercellular spaces.     

RNA:DNA ratio during the critical period and early larval growth of the red drum Sciaenops ocellatus

Eggs from two separate spawning stocks of the red drum Sciaenops ocellatus (Linnaeus) were hatched, and the larvae were reared in the laboratory for 2 wk under closely controlled conditions. Total RNA, DNA, and soluble protein were measured in each population daily in triplicate pooled samples of larvae from each of three tanks. Growth rate in mm d^-1 was determined for each population at 2 d intervals. Growth rate explained 72 and 95% of the variation in the RNA:DNA ratios of the two populations individually, and 86% of the variation in the RNA:DNA ratio when data from the two populations were combined. The RNA:DNA ratio appeared to be most effective as an indicator of growth in rapidly growing larvae, and to lose some resolution when growth was intermittent. The rates of deposition of RNA, DNA, and protein into tissue were all highly correlated with growth rate and with each other. Mean population RNA:DNA ratios of red drum yolk-sac larvae decreased from Day 1 post-hatch until larvae initiated successful feeding behavior, and then increased steadily throghout the remainder of the experimental period. This pattern of change in the RNA:DNA ratios during the yolk-sac stage appears to be an intrinsic developmental pattern of red drum ontogeny. The lowest values for the RNA:DNA ratio were observed just prior to the initiation of feeding or during the critical period, indicating that red drum larvae experience a decrease in capacity for protein synthesis as they initiate feeding. Intrinsic variation in the RNA:DNA ratio during development suggests that caution be used when comparing the RNA:DNA ratios of yolk-sac larvae to a critical ratio calculated from Buckley's general model.     

Data requirements of GREAT-ER: Modelling and validation using LAS in four UK catchments

Higher-tier environmental risk assessments on “down-the-drain” chemicals in river networks can be conducted using models such as GREAT-ER (Geography-referenced Regional Exposure Assessment Tool for European Rivers). It is important these models are evaluated and their sensitivities to input variables understood. This study had two primary objectives: evaluate GREAT-ER model performance, comparing simulated modelled predictions for LAS (linear alkylbenzene sulphonate) with measured concentrations, for four rivers in the UK, and investigate model sensitivity to input variables. We demonstrate that the GREAT-ER model is very sensitive to variability in river discharges. However it is insensitive to the form of distributions used to describe chemical usage and removal rate in sewage treatment plants (STPs). It is concluded that more effort should be directed towards improving empirical estimates of effluent load and reducing uncertainty associated with usage and removal rates in STPs. Simulations could be improved by incorporating the effect of river depth on dissipation rates.