Temperature and metabolic rate in sedentary fish from the Antarctic,North Sea and Indo-West Pacific Ocean

Resting metabolic rate was measured in demersal stages of the teleostNotothenia neglecta Nybelin from the South Orkney Islands, Antarctica, from 1985 to 1987. The relationship between and body mass (Mb) conformed to the general relationship , wherea is a proportionality constant andb is the scaling exponent. (mg O₂ h^–1) was found to scale toMb ^{(0.82±0.011)} in the summer (November to April, 1.6 to 1 850 g,n=56) and toMb ^{(0.76±0.013)} in the winter (May to October, 0.9 to 1 850 g,n=57) (values ofb are means ± SD). Although the scaling exponents were significantly different (P<0.01), was similar in the juvenile stages of summer- and winter-caught fish matched for body mass. The effects of activity on oxygen consumption was studied using a Brett respirometer. Adult stages had a factorial aerobic scope for activity of 5.7, which is similar to that reported for demersal fish from temperate latitudes. The effects of temperature on resting metabolism was investigated in fish with similar sedentary lifestyles from the North Sea (Agonus cataphractus andMyoxocephalus scorpius) and the Indo-West Pacific (Paracirrhites forsteri, P. arcatus, Neocirrhites armatus andExallias brevis). Extrapolated values of for the tropical species approached zero at 5 to 10°C. For a standard 50 g fish, for the tropical species at 25°C was in the range 3.4 to 4.4 mg O₂ h^–1, compared with 1.3 mg O₂ h^–1 forNotothenia neglecta at its acclimation temperature. Thus, the maximum metabolic rate of sedentary tropical species at 24°C is likely to be 2 to 4 times higher than inN. neglecta at 0°C. This suggests that the energy available for sustained activity is significantly lower in cold- than in warm-water fish.     

Analysing the sensitivity behaviour of two hydrology models

Recently, the New Morris Method has been presented as an effective sensitivity analysis tool for mathematical models. The New Morris Method estimates the sensitivity of an output parameter to a given set of input parameters (first-order effects) and the extent these parameters interact with each other (second-order effects). This method requires the specification of two parameters (runs and resolution) that control the sampling of the output parameter to determine its sensitivity to various inputs. The criteria for these parameters have been set on the analysis of a well-behaved analytical function (see Cropp and Braddock, Reliab. Eng. Syst. Saf. 78:77–83, 2002), which may not be applicable to other physical models that describe complex processes. This paper will investigate the appropriateness of the criteria from (Cropp and Braddock, 2002) and hence the effectiveness of the New Morris Method to determine the sensitivity behaviour of two hydrologic models: the Soil Erosion and Deposition System and Griffith University Representation of Urban Hydrology. In the first case, this paper will separately analyse the sensitivity of an output parameter on a set of input parameters (first- and second-order effects) for each model and discuss the physical meaning of these sensitivities. This will be followed by an investigation into the sampling criteria by exploring the convergence of the sensitivity behaviour for each model as the sampling of the parameter space is increased. By comparing these trends to the convergence behaviour from Cropp and Braddock (2002), we will determine how well the New Morris Method estimates the sensitivity for each model and whether the sampling criteria are appropriate for these models. It will be shown that the New Morris Method can provide additional insight into the functioning of these models, and that, under a different metric, the sensitivity behaviour of these models does converge confirming the sampling criteria set by Cropp and Braddock.     

Investigation of the Influence of Seagrass on Fisheries Catch Level Using Isotonic Regression

The relationship between seagrass area and the commercial catch of some economically important South Australian fish species is not known in any quantitative sense. However, there is evidence in the literature to suggest that seagrass decline will detrimentally impact on species abundance and composition, and consequently that the presence or absence of seagrass will compromise the commercial and recreational fishery. In this paper we describe the construction of models based on order restricted (isotonic) regression and discuss the role of seagrass area, in terms of its influence on the level of commercial catch through modifying the effect of fishing 'effort'.     

Environmental quality control and environmental games

Conclusion  In this paper we have considered a specific environmental game emphasizing both control-prevention efforts and the propensity to pollute by a firm which adopts a given pollution abatement technology. A random payoff game was constructed and solved under a risk neutral assumption and quadratic utilities for both the firm and the environmental controller. The game thus defined, provides a wide range of interpretations and potential approaches for selecting a control-inspection policies to prevent environmental risks. There are of course many facets to this problem, which could be considered and have not been considered in sufficient depth. For example, more complex control mechanisms and liabilities, the effects of insurance and risk sharing, the application of cooperative efforts and subvention of pollution abatement investments (through tax incentives and their like), etc. have not been considered [5,7]. These are topics for further research. The basic presumption of this paper is that it is very difficult to fully enforce pollution prevention by firms, as a result, some controls are needed to ensure that firms be controlled so that appropriate efforts are carried.     

profiling areas of ground water contamination by pesticides in california: phase ii – evaluation and modification of a statistical model

A well sampling study was conducted to evaluate anempirical approach to classifying areasof land in California as vulnerable to ground watercontamination by pesticides (Troiano et al., 1994). Wells were sampled from sections of land that had noprevious detections of pesticideresidues. The sections had been classified into vulnerablesoil clusters or into a not-classified groupusing a procedure based on Principal Components Analysis(PCA). Grape, citrus, and olive growingareas of Fresno and Tulare Counties were targeted, areas wherepre-emergence herbicide residues hadbeen detected in well water. Overall, herbicide residues weredetected in 75 of 176 sampled wells, ahigh frequency of detection in relation to results fromprevious targeted well sampling studies. Sinceresidues were also detected in the not-classified group, theclassification procedure was modified usingan approach based on Canonical Variates Analysis (CVA). Moresections were classified intovulnerable soil clusters with the CVA approach than with thePCA method. Data from two otherexplanatory variables, depth to ground water and amount ofpesticide used per section, were includedto illustrate how additional information can be incorporatedinto this approach of identifying vulnerable areas.     

Integrating disciplinary research into an interdisciplinary framework: A case study in sustainability research

The complexity of today’s research problems increasingly demands that scientists move beyond the confines of their own discipline. In this special issue, the basics of a transdisciplinary framework are established and problems analyzed in a specific discipline are successfully integrated in this transdisciplinary network. The intent has been to go beyond only statements about the importance of enabling early stage researchers to work across disciplinary boundaries, and to show that important discoveries are being made at the intersection of disciplines. Embedding various research projects in a more global framework can meet the demands of an interdisciplinary or transdisciplinary approach (especially for early stage researchers) and contribute significantly to sustainable research.     

A study on the orbit of air temperature movement

In this paper, we describe an air temperature movement by mapping its time series to the polar coordinates: the value of the time series is plotted on the radial coordinate and the time on the angular coordinate. In this way, both the yearly and daily air temperature movements from five different locations of China are used to demonstrate that, in an intuitionistic view, air temperature movement is neither random nor chaotic, but has its own orbit. We then propose an elliptic orbit model for the air temperature movement. Our proposed model provides quite good results when it is applied to the evaluation of yearly air temperature movements in eight locations in various parts of the world, and the evaluation of daily air temperature movements in five locations in Hunan Province of China on December 17, 2005. Results show that our approach provides a concise and helpful model for air temperature analysis.     

Use of cluster and principal component analyses to profile areas in California where ground water has been contaminated by pesticides

An empirical approach to profiling areas of ground water contamination by pesticides was devised that did not rely upon determining the level of vulnerability between land areas and that did not assume any particular pathway for ground water contamination. Climatic and soil data were obtained for 1-square mile sections of land in California where pesticide residues had been found in well water samples and the detection was attributed to legal agricultural applications. These sections were designated as known contaminated (KC) sections. Climate and soil data were also obtained for sections which lacked either well sampling data or a positive pesticide detection. These sections were designated as candidate sections. Statistical procedures were used to cluster groups of KC sections first with respect to climate characteristics and then with respect to soil characteristics. Principal components analysis (PCA) was used to construct a statistical profile of soil variables for each cluster of KC sections. A method based on the PCA was developed to compare the similarity of soil profiles derived for each KC section cluster to individual candidate sections. Since the profiling scheme was based only on data from KC sections, candidate sections that did not match any KC cluster profile could only be considered dissimilar to contaminated sections, receiving a status of not-classified. This profiling method is flexible and it can be revised to incorporate updated well sampling information.     

Assessing land use impacts on flood processes in complex terrain by using GIS and modeling approach

A distributed hydrologic modeling and GIS approach is applied for the assessment of land use impact in the Steinsel sub-basin, Alzette, Grand-Duchy of Luxembourg. The assessment focuses on the runoff contributions from different land use classes and the potential impact of land use changes on runoff generation. The results show that the direct runoff from urban areas is dominant for a flood event compared with runoff from other land use areas in this catchment, and tends to increase for small floods and for the dry season floods, whereas the interflow from forested, pasture and agricultural field areas contributes to the recession flow. Significant variations in flood volume, peak discharge, time to the peak, etc., are found from the model simulation based on the three hypothetical land use change scenarios.