Does contrast between eggshell ground and spot coloration affect egg rejection?

Obligate avian brood parasitic species impose the costs of incubating foreign eggs and raising young upon their unrelated hosts. The most common host defence is the rejection of parasitic eggs from the nest. Both egg colours and spot patterns influence egg rejection decisions in many host species, yet no studies have explicitly examined the role of variation in spot coloration. We studied the American robin Turdus migratorius, a blue-green unspotted egg-laying host of the brown-headed cowbird Molothrus ater, a brood parasite that lays non-mimetic spotted eggs. We examined host responses to model eggs with variable spot coloration against a constant robin-mimetic ground colour to identify patterns of rejection associated with perceived contrast between spot and ground colours. By using avian visual modelling, we found that robins were more likely to reject eggs whose spots had greater chromatic (hue) but not achromatic (brightness) contrast. Therefore, egg rejection decision rules in the American robin may depend on the colour contrast between parasite eggshell spot and host ground coloration. Our study also suggests that egg recognition in relation to spot coloration, like ground colour recognition, is tuned to the natural variation of avian eggshell spot colours but not to unnatural spot colours.     

Aggressive behavior of the male parent predicts brood sex ratio in a songbird

Brood sex ratio is often affected by parental or environmental quality, presumably in an adaptive manner that is the sex that confers higher fitness benefits to the mother is overproduced. So far, studies on the role of parental quality have focused on parental morphology and attractiveness. However, another aspect, the partner’s behavioral characteristics, may also be expected to play a role in brood sex ratio adjustment. To test this hypothesis, we investigated whether the proportion of sons in the brood is predicted by the level of territorial aggression displayed by the father, in the collared flycatcher (Ficedula albicollis). The proportion of sons in the brood was higher in early broods and increased with paternal tarsus length. When controlling for breeding date and body size, we found a higher proportion of sons in the brood of less aggressive fathers. Male nestlings are more sensitive to the rearing environment, and the behavior of courting males may often be used by females to assess their future parental activity. Therefore, adjusting brood sex ratio to the level of male aggression could be adaptive. Our results indicate that the behavior of the partner could indeed be a significant determinant in brood sex ratio adjustment, which should not be overlooked in future studies.     

Nation,demographic, and attitudinal boundary conditions on leader social rewards and punishments in local governments

Boundary conditions on the relationships of contingent rewards and noncontingent punishments with evaluated performance and satisfaction are sought for supervisory and professional staff in local governments in the United States and Japan. Subgroup differences in tolerance for noncontingent punishment are reflected in mean differences in its use between nations (more reported in Japan), genders (less reported by women), and regions of the United States. The effects of noncontingent punishment on outcomes were not found for U.S. police sergeants. Evidence for a national contingency is reflected in the finding that the relationship of noncontingent punishments (but not contingent rewards) with cooperation, individual effectiveness, and satisfaction was stronger in the United States than in Japan. The study adds caution to the culture‐free and contingency‐free application of the theory of performance‐contingent rewards and punishments. Implications for the theory of social rewards and punishments and for the contingencies and criteria considered in leadership research, particularly cross‐cultural leadership research, are addressed. Copyright © 2007 John Wiley & Sons, Ltd.     

Using triple bottom line metrics and multi-criteria methodology in corporate settings

With the growing importance of environmental sustainability in the corporate sector, businesses are compelled to progress from assessing and benchmarking their environmental impact to making decisions on how to prioritize impact reduction alternatives. Most often, business decisions are driven by financial metrics, but with sustainability improvements becoming a business goal, it is also important to assess metrics from environmental and social spheres; nevertheless, practically and systematically performing such an assessment is challenging. We present an application of a multi-criteria decision analysis (MCDA) method that addresses the aforementioned challenges in a corporate setting. Our case study company – one of the largest inland marine freight carriers in the United States – promotes a business culture focused on financially viable, yet socially and environmentally responsible solutions. Thus, we combine life cycle analysis (LCA), financial calculation methods, and corporate surveys to quantify environmental, economic, and social performance measures, respectively. Multiattribute utility theory is integrated with analytic hierarchy processes (AHPs) and fuzzy analysis to create a carefully designed framework for corporations with diverse groups of stakeholders. With company leadership, implementation is feasible and successful at prioritizing alternatives among diverse stakeholders. The process provides a platform for negotiation and promotes discussions on decision drivers. The use of MCDA methodologies promoted the inclusion of a suite of metrics that aligned with the company's sense of social and environmental responsibility, generating an in-depth analysis of the alternatives that factored in other things besides economics. Return-on-investments (ROI) calculations, the typical approach used in the corporate setting, would have required significantly less time and effort from the company, but the results of our MCDA application indicated that inclusion of triple bottom line metrics delve deeper into stakeholder preferences. Thus, our case study company gained a holistic view of the candidate alternatives, in addition to creating a platform for structured discussions about company goals and priorities.     

Integrating Temporal Inequality into Conservation Planning to Improve Practice Design and Efficacy

In contrast to spatial inequality, there are currently no methods for leveraging information on temporal inequality to improve conservation efficacy. The objective of this study was to use Lorenz curves to quantify temporal inequality in surface runoff and tile drainage, identify controls on nutrient loading in these flowpaths, and develop design flows for structural conservation practices. Surface runoff (n = 94 site‐years) and tile drainage (n = 90 site‐years) were monitored on 40 fields in Ohio. Results showed, on average, 80% of nitrate‐nitrogen, soluble reactive phosphorus (P), and total P loads occurred between 7 and 12 days per year in surface runoff and between 32 and 58 days per year in tile drainage. Similar temporal inequality between discharge and load provided evidence that loading was transport‐limited and highlighted the critical role hydrologic connectivity plays in nutrient delivery from tile‐drained fields. Design flow criterion for sizing structural practices based on load reduction goals was developed by combining Lorenz curves and flow duration curves. Comparing temporal inequality between fields and the Maumee River, the largest tributary to the western Lake Erie Basin, revealed challenges associated with achieving watershed load reduction goals with field‐scale conservation. In‐field (i.e., improved nutrient and water management), edge‐of‐field (i.e., structural practices), and instream practices will all be required to meet nutrient reduction goals from tile‐drained watersheds.     

Design for resilience in infrastructure distribution networks

The recognition that resilience is a critical aspect of infrastructure security has caused the national and homeland security communities to ask “How does one ensure infrastructure resilience?” Previous network resilience analysis methods have generally focused on either pre-disruption prevention investments or post-disruption recovery strategies. This paper expands on those methods by introducing a stochastic optimization model for designing network infrastructure resilience that simultaneously considers pre- and post-disruption activities. The model seeks investment–recovery combinations that minimize the overall cost to a distribution network across a set of disruption scenarios. A set of numerical experiments illustrates how changes to disruption scenarios probabilities affect the optimal resilient design investments.