Adjustment of parental effort in the puffin; the roles of adult body condition and chick size

 We examined the adjustment of parental effort of puffins by switching 20-day-old chicks randomly between parents of known body condition. Among unmanipulated birds mass gain (5–20 days) and mass of 20-day-old chicks was positively correlated with the body condition of parents at day 6. During the first 5 days after chick switching 28% (n = 55) of the parents deserted their foster chick. Parents which deserted their foster chick originally had a chick of their own that was smaller than that of those which did not desert their foster chick. Whether parents deserted their foster chick was also negatively related to the size of the foster chick. The mass of the foster chick was more important than the size of the parents' own chick in determining the desertion rate of chicks. The mass gain of the foster chick during the first 5 days after switching was positively related to the body condition of foster parents and also positively related to the mass of the foster parents' own chick, but negatively related to the size of the foster chick. The results suggest that puffins adjust their parental effort according to both their own body condition and the size of the chick. The latter may indicate the chick's prospect of survival and recruitment to the population. Received: 20 January 1996 / Accepted after revision: 27 October 1996     

Impact of generated solar radiation on simulated crop growth and yield

The availability of observed daily solar radiation (OSR) is restricted to recent years. Its estimation through different methods is necessary to develop long-term data sets for agricultural and environmental applications. The objective of this study was to analyze the impact of using generated daily solar radiation (GSR) on simulated growth and yield of cotton, maize, and peanut. Nine locations representing Georgia's major crop belt were selected. Daily weather data from the Georgia Automated Environmental Monitoring Network (AEMN), including solar radiation, maximum and minimum temperature, and precipitation, were duplicated. The OSR was removed from one set and then generated using a stochastic procedure. The Cropping System Models (CSM)-CROPGRO-Cotton, CERES-Maize, and CROPGRO-Peanut of the Decision Support System for Agrotechnology Transfer (DSSAT) v4 were used to simulate crop growth and yield at each location with both OSR and GSR and for rainfed and irrigated conditions. The statistical analysis included summary statistics, Pearson's coefficient of correlation, mean squared deviation (MSD) and its components, namely: squared bias (SB), squared difference between standard deviations (SDSD), lack of correlation weighted by the standard deviations (LCS), and regressions. Within locations, for the three crops under rainfed and irrigated conditions, GSR did not significantly affect simulated total evapotranspiration and aboveground biomass and yields. For the three crops, deviations of simulated water use and yields from GSR with respect to simulated water use and yields from OSR were lower for the rainfed than for the irrigated conditions. Yields from the CSM-CROPGRO-Cotton and -Peanut models had lower deviations than yields from the CSM-CERES-Maize model. LCS was the major component of the MSD suggesting that the extent of the difference between standard deviations of GSR and OSRG could affect the outputs of the crop models. Nevertheless, for most locations none of the MSD components of the GSR showed significant correlation with simulated yields and the overall performance of the models was not affected. It can be concluded based on the results of this study that GSR can be used as an input for crop model simulation models when OSR is not available.     

Description of hydrogeologic heterogeneity and evaluation of radionuclide transport at an underground nuclear test

Realistic models of contaminant transport in groundwater demand detailed characterization of the spatial distribution of subsurface hydraulic properties, while at the same time programmatic constraints may limit collection of pertinent hydraulic data. Fortunately, alternate forms of data can be used to improve characterization of spatial variability. We utilize a methodology that augments sparse hydraulic information (hard data) with more widely available hydrogeologic information to generate equiprobable maps of hydrogeologic properties that incorporate patterns of connected permeable zones. Geophysical and lithologic logs are used to identify hydrogeologic categories and to condition stochastic simulations using Sequential Indicator Simulation (SIS). The resulting maps are populated with hydraulic conductivity values using field data and Sequential Gaussian Simulation (SGS). Maps of subsurface hydrogeologic heterogeneity are generated for the purpose of examining groundwater flow and transport processes at the Faultless underground nuclear test, Central Nevada Test Area (CNTA), through large-scale, three-dimensional numerical modeling. The maps provide the basis for simulation of groundwater flow, while transport of radionuclides from the nuclear cavity is modeled using particle tracking methods. Sensitivity analyses focus on model parameters that are most likely to reduce the long travel times observed in the base case. The methods employed in this study have improved our understanding of the spatial distribution of preferential flowpaths at this site and provided the critical foundation on which to build models of groundwater flow and transport. The results emphasize that the impacts of uncertainty in hydraulic and chemical parameters are dependent on the radioactive decay of specific species, with rapid decay magnifying the effects of parameters that change travel time.     

Implementing second-best environmental policy under adverse selection

A key obstacle to practical application of mechanism design theory to regulation is the difficulty of obtaining consistent beliefs regarding information that theoretical models assume to be commonly held. This article presents a solution to this problem by developing an easily implemented empirical methodology with which the government can use available data to develop beliefs regarding the technology and distribution of types in a regulated sector characterized by hidden information. Results are used to calibrate a second-best land conservation mechanism and evaluate its cost relative to simpler alternatives.     

Developing a new alternative risk assessment framework in the work sites by including a stochastic and a deterministic process: A case study for the Greek Public Electric Power Provider

An individual method cannot achieve the optimum risk-assessment result in the worksites, and future perspectives should focus on the parallel application of a deterministic approach with a stochastic approach. In particular, the risk analysis and assessment techniques of the deterministic (DET) approach are classified into three main categories: (a) the qualitative, (b) the quantitative, and (c) the hybrid techniques (qualitative-quantitative, semi-quantitative). Furthermore, the stochastic (STO) approach includes the classic statistical approach (CSA) and the accident forecasting modeling (AFM). The objective of this paper is triple: (a) the presentation and classification of the main risk analysis and risk assessment methods and techniques of the deterministic approach and the stochastic approach as well, (b) the development and presentation of a new alternative risk assessment framework (called as STODET) including a stochastic and a deterministic process, and (c) the application of STODET in the Greek Public Power Corporation (PPC) by using occupational accidents that have been recorded, during the 17-year period of 1993-2009. In particular, the STODET application proves that required actions (or suppressive measures) are essential and must be taken in a medium-term period (1 working year) for abolishing the hazard sources.     

The Effect of Jump on Evaluating Natural Resource Investments

The evaluation of mining and other natural resource projects is made particularly difficult by the high degree of uncertainty attaching to output prices. It is shown that the techniques of continuous time arbitrage and stochastic control theory may be used not only to value such projects but also to determine the optimal policies for developing managing. This paper describes a model for evaluating natural resource investments under uncertainty from a new perspective. The previous works in this field mostly regard the movements of natural resource prices as a continuous GBM process, which pays few attentions to the shock of unexpected bad news. Our model provides the first theoretical method to analyze the impact of such "jump" on investment decisions. It concludes that the more frequently bad news happens, the earlier a project will be invested.     

Evaluating the management strategies of a forestland estate--the S-O-S approach

Connecting Multiple Criteria Decision Support (MCDS) methods with SWOT (Strengths, Weaknesses, Opportunities, and Threats) analysis yields analytical priorities for the factors included in SWOT analysis and makes them commensurable. In addition, decision alternatives can be evaluated with respect to each SWOT factor. In this way, SWOT analysis provides the basic frame within which to perform analyses of decision situations. MCDS methods, in turn, assist in carrying out SWOT more analytically and in elaborating the results of the analyses so that alternative strategic decisions can be prioritized also with respect to the entire SWOT. The A'WOT analysis is an example of such hybrid methods. It makes combined use of the Analytic Hierarchy Process (AHP) and SWOT. In this study, a hybrid method of the Stochastic Multicriteria Acceptability Analysis with Ordinal criteria (SMAA-O) and SWOT is developed as an elaboration of the basic ideas of A'WOT. The method is called S-O-S (SMAA-O in SWOT). SMAA-O enables the handling of ordinal preference information as well as mixed data consisting of both ordinal and cardinal information. Using SMAA-O is enough to just rank decision elements instead of giving them cardinal preference or priority ratios as required by the most commonly used MCDS methods. Using SMAA-O, in addition to analyzing what the recommended action is under certain priorities of the criteria, enables one to analyze what kind of preferences would support each action. The S-O-S approach is illustrated by a case study, where the shareholders of a forest holding owned by a private partnership prepared the SWOT analysis. Six alternative strategies for the management of their forest holding and of old cottage located on the holding were formed. After S-O-S analyses were carried out, one alternative was found to be the most recommendable. However, different importance orders of the SWOT groups would lead to different recommendations, since three of the six alternatives were efficient according to S-O-S analyses.     

A dual-interval fixed-mix stochastic programming method for water resources management under uncertainty

In this study, a dual-interval fixed-mix stochastic programming (DFSP) method is developed for planning water resources management systems under uncertainty. DFSP incorporates interval-parameter programming (IPP) and fuzzy vertex analysis (FVA) within a fixed-mix stochastic programming (FSP) framework to address uncertain parameters described as probability distributions and dual intervals. It can also be used for analyzing various policy scenarios that are associated with different levels of economic consequences since penalties are exercised with recourse actions against any infeasibility. A real case for water resources management planning of Zhangweinan River Basin in China is then conducted for demonstrating the applicability of the developed DFSP method. Solutions in association with α-cut levels are generated by solving a set of deterministic submodels, which are useful for generating a range of decision alternatives under compound uncertainties. The results can help to identify desired water-allocation schemes for local sustainable development that the prerequisite water demand can be guaranteed when the available water resource is scarce.