Begging calls and parental feeding decisions in tree swallows (Tachycineta bicolor)

We conducted playback experiments to examine how parent tree swallows (Tachycineta bicolor) use nestling begging calls to distribute feedings to individuals within broods. In a first study, we used a paired-choice test to determine if parents discriminated between the taped begging calls of nestlings deprived of food and those of nestlings that had been recently fed. Our results showed that parents directed their first feeding attempt towards model nestlings near speakers playing deprived calls significantly more often than to models near speakers playing fed calls. They also made more feeding attempts overall to models with deprived calls. In the second study, we varied call rate and amplitude to examine which call features parents might use to discriminate begging calls. Parents directed significantly more first feeding attempts and more feeding attempts overall towards non-begging nestlings near speakers playing high call rates than to nestlings near speakers playing low call rates. They did not, however, discriminate between calls differing in amplitude. Previous studies have shown that parent birds use begging calls to regulate overall feeding rates to the brood. Our results suggest that parent tree swallows also use begging calls when feeding individual nestlings and, in particular, prefer calls associated with increased levels of nestling hunger. Received: 14 February 2000 / Revised: 6 October 2000 / Accepted: 16 October 2000     

Prediction of effluent concentration in a wastewater treatment plant using machine learning models

Of growing amount of food waste, the integrated food waste and waste water treatment was regarded as one of the efficient modeling method. However, the load of food waste to the conventional waste treatment process might lead to the high concentration of total nitrogen(T-N) impact on the effluent water quality. The objective of this study is to establish two machine learning models—artificial neural networks(ANNs) and support vector machines(SVMs), in order to predict 1-day interval T-N concentration of effluent from a wastewater treatment plant in Ulsan, Korea. Daily water quality data and meteorological data were used and the performance of both models was evaluated in terms of the coefficient of determination(R~2), Nash–Sutcliff efficiency(NSE), relative efficiency criteria(d rel). Additionally, Latin-Hypercube one-factor-at-a-time(LH-OAT) and a pattern search algorithm were applied to sensitivity analysis and model parameter optimization, respectively. Results showed that both models could be effectively applied to the 1-day interval prediction of T-N concentration of effluent. SVM model showed a higher prediction accuracy in the training stage and similar result in the validation stage.However, the sensitivity analysis demonstrated that the ANN model was a superior model for 1-day interval T-N concentration prediction in terms of the cause-and-effect relationship between T-N concentration and modeling input values to integrated food waste and waste water treatment. This study suggested the efficient and robust nonlinear time-series modeling method for an early prediction of the water quality of integrated food waste and waste water treatment process.     

The impact of warming on the appearance of furunculosis in fish of the James Bay region,Quebec, Canada

A regional climate change impact assessment was conducted which investigated the timing of the first appearance of furunculosis caused by the bacterium, Aeromonas salmonicida, in fish of the Ouje-Bougoumou region of northern Quebec, Canada. Historical data were used to assess whether there was a temporal relationship between increased temperatures (observed climate data) and the appearance of furunculosis (traditional environmental knowledge was used to provide context). To project future impacts of climate change, climate models and lake models were used. Regression analysis revealed a significant, positive temporal trend in mean air temperature. The temperature range conducive to A. salmoncida survival coincided with the first appearance of furunculosis. In addition, it is predicted that lake temperatures will remain suitable for the presence of A. salmonicida into the future; it is likely that the disease will persist throughout the twenty-first century. Climate change appears to be a factor explaining the onset of furunculosis; however, other factors/stressors cannot be discounted, such as, the effects past mining activities near the lakes of the Ouje-Bougoumou region have had on the body burden of contaminants in the fish (and the potential effects on the fish immune system).     

Unemployment and the backward incidence of pollution control

This paper reexamines the backward incidence of pollution control using duality theory for a two-sector general equilibrium model in which the economy experiences large-scale unemployment and perfect capital mobility with a sector-specific rigid wage in the polluting sector. In this context it is shown that with stricter pollution controls the wage rate in the nonpolluting sector rises while the common rental rate falls. In addition, stricter pollution controls are shown to have an uncertain impact on national income.     

Controlling industrial pollution using EIA: Case study of a Kenyan tannery project

Summary Since the late 1970s, the National Environment Secretariat (NES) in Kenya has viewed environmental impact assessment (EIA) as a principal tool for meeting its environmental protection objectives. Prior to the formation of the Inter-Ministerial Committee on the Environment (IMCE), NES was ineffective in forcing any project proponents to take the EIA requirements seriously. The IMCE has provided NES with the ability to co-opt Committee members and to use the legislatively based mandates of those members to enforce its EIA requirements for industrial projects. A successful example of this co-optation is the case of the Leather Industries of Kenya (LIK), involving a new tannery whose final siting and wastewater treatment control facilities were substantially influenced by the EIA process. Although the LIK case does not offer a basis for generalisation, it provides insights into: (a) how EIA is implemented for new industrial facilities in Kenya, (b) the advantages and disadvantages of the EIA system, and (c) the constructive roles donor agencies can play in promoting institutional reforms for EIA.Dr Rafik Hirji is a Senior Engineer at James M. Montgomery Consulting Engineers, Inc., Suite 160, Sacramento, CA 95825. He was formerly a graduate research assistant in the Department of Civil Engineering at Stanford University. Dr Leonard Ortolano is the UPS Foundation Professor of Civil Engineering at Stanford University, Stanford, CA 94305-4020, USA.     

MINIMIZING THE IMPACT OF URBANIZATION ON LONG TERM RUNOFF1

Increasing concern about the problems caused by urban sprawl has encouraged development and implementation of smart growth approaches to land use management. One of the goals of smart growth is water resources protection, in particular minimizing the runoff impact of urbanization. To investigate the magnitude of the potential benefits of land use planning for water resources protection, possible runoff impacts of historical and projected urbanization were estimated for two watersheds in Indiana and Michigan using a long term hydrological impact analysis model. An optimization component allowed selection of land use change placements that minimize runoff increase. Optimizing land use change placement would have reduced runoff increase by as much as 4.9 percent from 1973 to 1997 in the Indiana study watershed. For nonsprawl and sprawl scenarios in the Michigan watershed for 1978 to 2040, optimizing land use change placement would have reduced runoff increase by 12.3 percent and 20.5 percent, respectively. The work presented here illustrates both an approach to assessing the magnitude of the impact of smart growth and the significant potential scale of smart growth in moderating runoff changes that result from urbanization. The results of this study have significant implications for urban planning.     

Process evaluation for optimization of EDTA use and recovery for heavy metal removal from a contaminated soil

This study aimed to establish an optimized, closed loop application of ethylenediaminetetraacetic acid (EDTA) in heavy metal removals from a contaminated soil through integrating EDTA recovery/regeneration and metal precipitation processes in the treatment train. Three divalent heavy metals were investigated, namely, Pb, Cd, and Ni. The extractability of the metals by EDTA followed the decreasing order of CdPb>Ni. The first part of this study was to search for the optimal use of the fresh EDTA in removing these heavy metals from the contaminated soil. The second part of this study was devoted to the recovery/regeneration of the spent EDTA which followed the sequential processes involving (1) complex destabilization by adding ferric ion (Fe(III)) to liberate Pb, Cd, and Ni, (2) precipitation of the liberated Pb, Cd, and Ni in phosphate (PO4(3-)) forms, and (3) precipitation of the excess Fe(III) which eventually produced free EDTA for reuse. The process variables were dosages of Fe(III) and PO4(3-), pH and reaction times. Laborious trial experiments would be needed in searching for the optimum conditions for the above processes. To expedite this exercise, a geochemical equilibrium model, MINTEQA2, was used to find the thermodynamically favorable conditions for recoveries of both EDTA and heavy metals. This was then followed by experimental examination of the process kinetics to observe for the optimal reaction time for each thermodynamically favorable process. This study revealed that 2 h of reaction time each for the complex destabilization reaction and the metal phosphate precipitation reaction was sufficient to achieve equilibrium. With the optimized process condition identified in this study, a total of 95%, 89% and 90% of the extracted Pb, Cd and Ni, respectively, could be precipitated from the spent EDTA solution, with 84% EDTA recovery. The reused EDTA maintained more than 90% of its preceding extraction power in each cycle of reuse.