Rabbits, stoats and the predator problem: Why a strong animal rights position need not call for human intervention to protect prey from predators

Animal rights positions face the ‘predator problem’: the suggestion that if the rights of nonhuman animals are to be protected, then we are obliged to interfere in natural ecosystems to protect prey from predators. Generally, rather than embracing this conclusion, animal ethicists have rejected it, basing this objection on a number of different arguments. This paper considers but challenges three such arguments, before defending a fourth possibility. Rejected are Peter Singer’s suggestion that interference will lead to more harm than good, Sue Donaldson and Will Kymlicka’s suggestion that respect for nonhuman sovereignty necessitates non-interference in normal circumstances, and Alasdair Cochrane’s solution based on the claim that predators cannot survive without killing prey. The possibility defended builds upon Tom Regan’s suggestion that predators, as moral patients but not moral agents, cannot violate the rights of their prey, and so the rights of the prey, while they do exist, do not call for intervention. This idea is developed by a consideration of how moral agents can be more or less responsible for a given event, and defended against criticisms offered by thinkers including Alasdair Cochrane and Dale Jamieson.

Application of Volterra Equations to Solve Unit Commitment Problem of Optimised Energy Storage and Generation

Development of reliable methods for optimised energy storage and generation is one of the most imminent challenges in modern power systems. In this paper an adaptive approach to load leveling problem using novel dynamic models based on the Volterra integral equations of the first kind with piecewise continuous kernels. These integral equations efficiently solve such inverse problem taking into account both the time dependent efficiencies and the availability of generation/storage of each energy storage technology. In this analysis a direct numerical method is employed to find the least-cost dispatch of available storages. The proposed collocation type numerical method has second order accuracy and enjoys self-regularization properties, which is associated with confidence levels of system demand. This adaptive approach is suitable for energy storage optimisation in real time. The efficiency of the proposed methodology is demonstrated on the Single Electricity Market of Republic of Ireland and Northern Ireland.