Applications of artificial neural networks for patterning and predicting aquatic insect species richness in running waters

Two artificial neural networks (ANNs), unsupervised and supervised learning algorithms, were applied to suggest practical approaches for the analysis of ecological data. Four major aquatic insect orders (Ephemeroptera, Plecoptera, Trichoptera, and Coleoptera, i.e. EPTC), and four environmental variables (elevation, stream order, distance from the source, and water temperature) were used to implement the models. The data were collected and measured at 155 sampling sites on streams of the Adour–Garonne drainage basin (South-western France). The modelling procedure was carried out following two steps. First, a self-organizing map (SOM), an unsupervised ANN, was applied to classify sampling sites using EPTC richness. Second, a backpropagation algorithm (BP), a supervised ANN, was applied to predict EPTC richness using a set of four environmental variables. The trained SOM classified sampling sites according to a gradient of EPTC richness, and the groups obtained corresponded to geographic regions of the drainage basin and characteristics of their environmental variables. The SOM showed its convenience to analyze relationships among sampling sites, biological attributes, and environmental variables. After accounting for the relationships in data sets, the BP used to predict the EPTC richness with a set of four environmental variables showed a high accuracy (r=0.91 and r=0.61 for training and test data sets respectively). The prediction of EPTC richness is thus a valuable tool to assess disturbances in given areas: by knowing what the EPTC richness should be, we can determine the degree to which disturbances have altered it. The results suggested that methodologies successively using two different neural networks are helpful to understand ecological data through ordination first, and then to predict target variables.     

Incentive compensation as an injurious condition of work: A study of labelling

A recursive causal model is presented in which individual and work factors are hypothesized to be predictive of workers' labelling an incentive compensation program as potentially injurious to their well-being. The individual factors include the dispositional variable, negative affectivity, and financial needs and resources. The work factors consist of prior incentive compensation, experienced job insecurity, and experienced control. The model was tested using questionnaire responses of 165 managers and professionals. While it was found that the overall model did not fit the data that well, negative affectivity was found to be positively associated and experienced control negatively associated with the incentive compensation program being labelled negatively. The somewhat surprising finding that financial needs and resources were not found to be significantly associated with labelling is discussed. The importance of disposition and experienced control for the labelling of potentially threatening or harmful job conditions as well as some hypothesized antecedents of control also are discussed.     

Die Organisation der chemischen Sammelliteratur

The Science of Nature -     

QUANTIFICATION OF THE WATER BUDGET AND NUTRIENT LOADING IN A SMALL PEATLAND1

ABSTRACT: Few water budgets exist for specific types of wetlands such as peatlands, even though such information provides the basis from which to investigate linkages between wetlands and upland ecosystems. In this study, we first determined the water budget and then estimated nutrient loading from an upland farm field into a 1.5 ha, kettle-block peatland. The wetland contains highly anisotropic peat and has no distinct, active layer of groundwater flow. We estimated the depth of the active layer using Fick's law of diffusion and quantified groundwater flow using a chemical mass balance model. Evapotranspiration was determined using MORECS, a semi-physical model based on the Penman-Monteith approach. Precipitation and surface outflow were measured using physical means. Groundwater provided the major inflow, 84 percent (44,418 m³) in 1993 and 88 percent (68,311 m³) in 1994. Surface outflow represented 54 percent (28,763 m³) of total outflows in 1993 and 48 percent (37,078 m³) in 1994. A comparison of several published water budgets for wetlands and lakes showed that error estimates for hydrologic components in this study are well within the range of error estimates calculated in other studies. Groundwater inflow estimates and nutrient concentrations of three springs were used to estimate agricultural nutrient loading to the site. During the study period, nutrient loading into the peatland via groundwater discharge averaged 24.74 kg K ha^-1, 1.83 kg total inorganic P ha^d, and 21.81 kg NO₃-N ha^-1.     

Optimal municipal investment in boomtowns An empirical analysis

The primary concern of this paper is the use of wage-infrastructure trade-offs as a measure for the social benefits of municipal infrastructure in boomtowns. A regression based on pooled cross sectional and time series data for 26 towns in the Rocky Moutain region suggests that individuals will “trade off” a 1% increase in per capita stocks of municipal infrastructure for a 0.035% decline in wages. These results are then used to calculate “optimal” levels of infrastructure investment for an example boomtown.     

Biochemical methane potential of food and garden waste co-digestion with variation in solid content and inoculum:substrate ratio

Journal of Material Cycles and Waste Management - The objective of this study is to evaluate the influence of the addition of garden waste (GW) on the performance of food waste (FW) anaerobic...     

Maintenance of variable responses for coping with wetland drying in freshwater turtles

Aquatic animals inhabiting temporary wetlands must respond to habitat drying either by estivating or moving to other wetlands. Using radiotelemetry and capture mark recapture, we examined factors influencing the decisions made by individuals in a population of freshwater turtles (Chelodina longicollis) in response to wetland drying in southeastern Australia. Turtles exhibited both behaviors, either remaining quiescent in terrestrial habitats for variable lengths of time (terrestrial estivation) or moving to other wetlands. Both the proportion of individuals that estivated terrestrially and the time individuals spent in terrestrial habitats increased with decreasing wetland hydroperiod and increasing distance to the nearest permanent wetland, suggesting behavioral decisions are conditional or state dependent (i.e., plastic) and influenced by local and landscape factors. Variation in the strategy or tactic chosen also increased with increasing isolation from other wetlands, suggesting that individuals differentially weigh the costs and benefits of residing terrestrially vs. those of long-distance movement; movement to other wetlands was the near universal strategy chosen when only a short distance must be traveled to permanent wetlands. The quality of temporary wetlands relative to permanent wetlands at our study site varies considerably and unpredictably with annual rainfall and with it the cost-benefit ratio of each strategy or tactic. Residency in or near temporary wetlands is more successful during wet periods due to production benefits, but movement to permanent wetlands is more successful, or least costly, during dry periods due to survival and body condition benefits. This shifting balance may maintain diversity in response of turtles to the spatial and temporal pattern in wetland quality if their response is in part genetically determined.