Earlier and more frequent occupation of breeding sites during the non‐breeding season increases breeding success in a colonial seabird

Competition for high-quality breeding sites in colonial species is often intense, such that individuals may invest considerable time in site occupancy even outside the breeding season. The site defense hypothesis predicts that high-quality sites will be occupied earlier and more frequently, consequently those sites will benefit from earlier and more successful breeding. However, few studies relate non-breeding season occupancy to subsequent breeding performance limiting our understanding of the potential life-history benefits of this behavior. Here, we test how site occupancy in the non-breeding season related to site quality, breeding timing, and breeding success in a population of common guillemots Uria aalge, an abundant and well-studied colonially breeding seabird. Using time-lapse photography, we recorded occupancy at breeding sites from October to March over three consecutive non-breeding seasons. We then monitored the successive breeding timing (lay date) and breeding success at each site. On average, sites were first occupied on the 27th October ± 11.7 days (mean ± SD), subsequently occupied on 46 ± 18% of survey days and for 55 ± 15% of the time when at least one site was occupied. Higher-quality sites, sites with higher average historic breeding success, were occupied earlier, more frequently and for longer daily durations thereafter. Laying was earlier at sites that were occupied more frequently and sites occupied earlier were more successful, supporting the site defense hypothesis. A path analysis showed that the return date had a greater or equal effect on breeding success as lay date. Pair level occupancy had no effect on breeding timing or success. The clear effect of non-breeding occupancy of breeding sites on breeding timing and success highlights the benefits of this behavior on demography in this population and the importance of access to breeding sites outside the breeding season in systems where competition for high-quality sites is intense

Quantifying the impacts of predation by great black-backed gulls Larus marinus on an Atlantic puffin Fratercula arctica population: implications for conservation management and impact assessments

The management of predator-prey conflicts can be a key aspect of species conservation. For management approaches to be effective, a robust understanding of the predator-prey relationship is needed, particularly when both predator and prey are species of conservation concern. On the Isle of May, Firth of Forth, Scotland, numbers of breeding Great Black-backed Gulls Larus marinus, a generalist predator, have been increasing since the 1980s, which has led to increasing numbers of sympatrically breeding Atlantic Puffins Fratercula arctica being predated during the breeding season. This may have consequences for species management on the Isle of May and impact assessments of offshore windfarms in the wider Firth of Forth area. We used population viability analysis to quantify under what predation pressure the Atlantic Puffin population may decline and become locally extinct over a three-generation period. The predation level empirically estimated in 2017 (1120 Puffins per year) was not sufficient to drive a decline in the Puffin population. Rather, an increase to approximately 3000 Puffins per year would be required to cause a population decline, and >4000 to drive the population to quasi-extinction within 66 years. We discuss the likelihood of such a scenario being reached on the Isle of May, and we recommend that where predator-prey conflicts occur, predation-driven mortality should be regularly quantified to inform conservation management and population viability analyses associated with impact assessments

Feasibility study of large-scale deployment of colour-ringing on black-legged kittiwake populations to improve the realism of demographic models assessing the population impacts of offshore wind farms

• Renewable energy developments, including offshore wind farms have been identified as a key component in international efforts to mitigate climate change and its impact on biodiversity. This has led to an increasing number of offshore wind farms around the UK, however, these can have negative impacts on seabird populations. • Population Viability Analysis (PVA) is frequently used to quantify these potential negative effects on seabird populations and is a vital part of the consenting process. However, a lack of empirical data on many aspects of seabird demography means that there can be considerable uncertainty in these assessments. • Black-legged Kittiwake Rissa tridactyla populations are thought to be particularly sensitive to additional mortality caused by collision with offshore wind turbines and are often highlighted as a feature of Special Protection Areas (SPAs). Offshore wind farms, therefore, have been identified as potentially causing an adverse effect on site integrity at some SPAs. • Despite being a relatively well-studied species, there is still much uncertainty in our knowledge of Kittiwake demographic rates and meta-population dynamics, which impedes our ability to accurately assess the way populations might respond to additional wind farm-induced mortality. • The Offshore Wind Strategic Monitoring and Research Forum (OWSMRF) identified a large-scale colour-ringing programme of Kittiwake colonies across the UK as one potential approach for improving empirical estimates of Kittiwake demographic rates. • Therefore, the main aim of this project was to determine the extent to which colour-ringing can be used to obtain reliable baseline estimates of key demographic rates in Kittiwake populations to improve the realism of demographic models assessing the population impacts of offshore wind farms, and thereby reduce uncertainty around these predicted impacts

Horizontal Branch Stars: The Interplay between Observations and Theory, and Insights into the Formation of the Galaxy

We review HB stars in a broad astrophysical context, including both variable and non-variable stars. A reassessment of the Oosterhoff dichotomy is presented, which provides unprecedented detail regarding its origin and systematics. We show that the Oosterhoff dichotomy and the distribution of globular clusters (GCs) in the HB morphology-metallicity plane both exclude, with high statistical significance, the possibility that the Galactic halo may have formed from the accretion of dwarf galaxies resembling present-day Milky Way satellites such as Fornax, Sagittarius, and the LMC. A rediscussion of the second-parameter problem is presented. A technique is proposed to estimate the HB types of extragalactic GCs on the basis of integrated far-UV photometry. The relationship between the absolute V magnitude of the HB at the RR Lyrae level and metallicity, as obtained on the basis of trigonometric parallax measurements for the star RR Lyrae, is also revisited, giving a distance modulus to the LMC of (m-M)_0 = 18.44+/-0.11. RR Lyrae period change rates are studied. Finally, the conductive opacities used in evolutionary calculations of low-mass stars are investigated. [ABRIDGED]Comment: 56 pages, 22 figures. Invited review, to appear in Astrophysics and Space Scienc

Evaluation in artificial intelligence: From task-oriented to ability-oriented measurement

The final publication is available at Springer via http://dx.doi.org/ 10.1007/s10462-016-9505-7.The evaluation of artificial intelligence systems and components is crucial for the progress of the discipline. In this paper we describe and critically assess the different ways AI systems are evaluated, and the role of components and techniques in these systems. We first focus on the traditional task-oriented evaluation approach. We identify three kinds of evaluation: human discrimination, problem benchmarks and peer confrontation. We describe some of the limitations of the many evaluation schemes and competitions in these three categories, and follow the progression of some of these tests. We then focus on a less customary (and challenging) ability-oriented evaluation approach, where a system is characterised by its (cognitive) abilities, rather than by the tasks it is designed to solve. We discuss several possibilities: the adaptation of cognitive tests used for humans and animals, the development of tests derived from algorithmic information theory or more integrated approaches under the perspective of universal psychometrics. We analyse some evaluation tests from AI that are better positioned for an ability-oriented evaluation and discuss how their problems and limitations can possibly be addressed with some of the tools and ideas that appear within the paper. Finally, we enumerate a series of lessons learnt and generic guidelines to be used when an AI evaluation scheme is under consideration.I thank the organisers of the AEPIA Summer School On Artificial Intelligence, held in September 2014, for giving me the opportunity to give a lecture on 'AI Evaluation'. This paper was born out of and evolved through that lecture. The information about many benchmarks and competitions discussed in this paper have been contrasted with information from and discussions with many people: M. Bedia, A. Cangelosi, C. Dimitrakakis, I. GarcIa-Varea, Katja Hofmann, W. Langdon, E. Messina, S. Mueller, M. Siebers and C. Soares. Figure 4 is courtesy of F. Martinez-Plumed. Finally, I thank the anonymous reviewers, whose comments have helped to significantly improve the balance and coverage of the paper. This work has been partially supported by the EU (FEDER) and the Spanish MINECO under Grants TIN 2013-45732-C4-1-P, TIN 2015-69175-C4-1-R and by Generalitat Valenciana PROMETEOII2015/013.José Hernández-Orallo (2016). Evaluation in artificial intelligence: From task-oriented to ability-oriented measurement. 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From Computer Metaphor to Computational Modeling: The Evolution of Computationalism

In this paper, I argue that computationalism is a progressive research tradition. Its metaphysical assumptions are that nervous systems are computational, and that information processing is necessary for cognition to occur. First, the primary reasons why information processing should explain cognition are reviewed. Then I argue that early formulations of these reasons are outdated. However, by relying on the mechanistic account of physical computation, they can be recast in a compelling way. Next, I contrast two computational models of working memory to show how modeling has progressed over the years. The methodological assumptions of new modeling work are best understood in the mechanistic framework, which is evidenced by the way in which models are empirically validated. Moreover, the methodological and theoretical progress in computational neuroscience vindicates the new mechanistic approach to explanation, which, at the same time, justifies the best practices of computational modeling. Overall, computational modeling is deservedly successful in cognitive (neuro)science. Its successes are related to deep conceptual connections between cognition and computation. Computationalism is not only here to stay, it becomes stronger every year