An assessment of diet overlap of two mesocarnivores in the North-West Province, South Africa

We used scat analysis to study the diet of two sympatric medium-sized carnivores: brown hyaena and black-backed jackal, in the NorthWest Province of South Africa. Seven major dietary categories were identified from the scats, with mammal remains being most common for both species. Brown hyaena scats contained more large mammal remains, which together with the presence of invertebrates (in 50% of all brown hyaena scats), suggests that they mainly scavenged. Jackal scats contained a higher proportion of small mammal remains, suggesting that jackals actively hunted more often than brown hyaenas did. The diets differed significantly between the two species, even though diet overlap was fairly high (0.79). Further analysis, albeit based on small sample sizes, suggests that diet of these mesopredators differ between protected reserves with apex predators and unprotected areas without apex predators, thus confounding generalizations. Further studies are therefore required to investigate possible mesopredator release when apex predators are absent

Do Lions Panthera leo Actively Select Prey or Do Prey Preferences Simply Reflect Chance Responses via Evolutionary Adaptations to Optimal Foraging?

Research on coursing predators has revealed that actions throughout the predatory behavioral sequence (using encounter rate, hunting rate, and kill rate as proxy measures of decisions) drive observed prey preferences. We tested whether similar actions drive the observed prey preferences of a stalking predator, the African lion Panthera leo. We conducted two 96 hour, continuous follows of lions in Addo Elephant National Park seasonally from December 2003 until November 2005 (16 follows), and compared prey encounter rate with prey abundance, hunt rate with prey encounter rate, and kill rate with prey hunt rate for the major prey species in Addo using Jacobs' electivity index. We found that lions encountered preferred prey species far more frequently than expected based on their abundance, and they hunted these species more frequently than expected based on this higher encounter rate. Lions responded variably to non-preferred and avoided prey species throughout the predatory sequence, although they hunted avoided prey far less frequently than expected based on the number of encounters of them. We conclude that actions of lions throughout the predatory behavioural sequence, but particularly early on, drive the prey preferences that have been documented for this species. Once a hunt is initiated, evolutionary adaptations to the predator-prey interactions drive hunting success

Mind-modelling with corpus stylistics in David Copperfield

We suggest an innovative approach to literary discourse by using corpus linguistic methods to address research questions from cognitive poetics. In this article, we focus on the way that readers engage in mind-modelling in the process of characterisation. The article sets out our cognitive poetic model of characterisation that emphasises the continuity between literary characterisation and real-life human relationships. The model also aims to deal with the modelling of the author’s mind in line with the modelling of the minds of fictional characters. Crucially, our approach to mind-modelling is text-driven. Therefore we are able to employ corpus linguistic techniques systematically to identify textual patterns that function as cues triggering character information. In this article, we explore our understanding of mind-modelling through the characterisation of Mr. Dick from David Copperfield by Charles Dickens. Using the CLiC tool (Corpus Linguistics in Cheshire) developed for the exploration of 19th-century fiction, we investigate the textual traces in non-quotations around this character, in order to draw out the techniques of characterisation other than speech presentation. We show that Mr. Dick is a thematically and authorially significant character in the novel, and we move towards a rigorous account of the reader’s modelling of authorial intention