What Constitutes a Natural Fire Regime? Insight from the Ecology and Distribution of Coniferous Forest Birds in North America

Bird species that specialize in the use of burned forest conditions can provide insight into the prehistoric fire regimes associated with the forest types that they have occupied over evolutionary time. The nature of their adaptations reflects the specific post-fire conditions that occurred prior to the unnatural influence of humans after European settlement. Specifically, the post-fire conditions, nest site locations, and social systems of two species (Bachman\u27s sparrow [Aimophila aestivalis] and red-cockaded woodpecker [Picoides borealis]) suggest that, prehistorically, a frequent, low-severity fire regime characterized the southeastern pine system in which they evolved. In contrast, the patterns of distribution and abundance for several other bird species (black-backed woodpecker [Picoides arcticus], buff-breasted flycatcher [Empidonax fulvifrons], Lewis\u27 woodpecker [Melanerpes lewis], northern hawk owl [Surnia ulula], and Kirtland\u27s warbler [Dendroica kirtlandii]) suggest that severe fire has been an important component of the fire regimes with which they evolved. Patterns of habitat use by the latter species indicate that severe fires are important components not only of higher-elevation and high-latitude conifer forest types, which are known to be dominated by such fires, but also of mid-elevation and even low-elevation conifer forest types that are not normally assumed to have had high-severity fire as an integral part of their natural fire regimes. Because plant and animal adaptations can serve as reliable sources of information about what constitutes a natural fire regime, it might be wise to supplement traditional historical methods with careful consideration of information related to plant and animal adaptations when attempting to restore what are thought to be natural fire regimes

Marginal Eyespots on Butterfly Wings Deflect Bird Attacks Under Low Light Intensities with UV Wavelengths

Predators preferentially attack vital body parts to avoid prey escape. Consequently, prey adaptations that make predators attack less crucial body parts are expected to evolve. Marginal eyespots on butterfly wings have long been thought to have this deflective, but hitherto undemonstrated function.Here we report that a butterfly, Lopinga achine, with broad-spectrum reflective white scales in its marginal eyespot pupils deceives a generalist avian predator, the blue tit, to attack the marginal eyespots, but only under particular conditions-in our experiments, low light intensities with a prominent UV component. Under high light intensity conditions with a similar UV component, and at low light intensities without UV, blue tits directed attacks towards the butterfly head.In nature, birds typically forage intensively at early dawn, when the light environment shifts to shorter wavelengths, and the contrast between the eyespot pupils and the background increases. Among butterflies, deflecting attacks is likely to be particularly important at dawn when low ambient temperatures make escape by flight impossible, and when insectivorous birds typically initiate another day's search for food. Our finding that the deflective function of eyespots is highly dependent on the ambient light environment helps explain why previous attempts have provided little support for the deflective role of marginal eyespots, and we hypothesize that the mechanism that we have discovered in our experiments in a laboratory setting may function also in nature when birds forage on resting butterflies under low light intensities

Effects of Vegetation, Corridor Width and Regional Land Use on Early Successional Birds on Powerline Corridors

Powerline rights-of-way (ROWs) often provide habitat for early successional bird species that have suffered long-term population declines in eastern North America. To determine how the abundance of shrubland birds varies with habitat within ROW corridors and with land use patterns surrounding corridors, we ran Poisson regression models on data from 93 plots on ROWs and compared regression coefficients. We also determined nest success rates on a 1-km stretch of ROW. Seven species of shrubland birds were common in powerline corridors. However, the nest success rates for prairie warbler (Dendroica discolor) and field sparrow (Spizella pusilla) were <21%, which is too low to compensate for estimated annual mortality. Some shrubland bird species were more abundant on narrower ROWs or at sites with lower vegetation or particular types of vegetation, indicating that vegetation management could be refined to favor species of high conservation priority. Also, several species were more abundant in ROWs traversing unfragmented forest than those near residential areas or farmland, indicating that corridors in heavily forested regions may provide better habitat for these species. In the area where we monitored nests, brood parasitism by brown-headed cowbirds (Molothrus ater) occurred more frequently close to a residential area. Although ROWs support dense populations of shrubland birds, those in more heavily developed landscapes may constitute sink habitat. ROWs in extensive forests may contribute more to sustaining populations of early successional birds, and thus may be the best targets for habitat management

Folk psychological and neurocognitive ontologies

It is becoming increasingly clear that our folk psychological ontology of the mental is unlikely to map neatly on to the functional organisation of the brain, leading to the development of novel ‘cognitive ontologies’ that aim to better describe this organisation. While the debate over which of these ontologies to adopt is still ongoing, we ought to think carefully about what the consequences for folk psychology might be. One option would be to endorse a new form of eliminative materialism, replacing the old folk psychological ontology with a novel neurocognitive ontology. This approach assumes a literalist attitude towards folk psychology, where the folk psychological and neurocognitive ontologies represent competing and incompatible ways of categorising the mental. According to an alternative approach, folk psychology aims to describe coarse-grained behaviour rather than fine-grained mechanisms, and the two kinds of ontology are better thought of as having different aims and purposes. In this chapter I will argue that the latter (coarse-grained) approach is a better way to make sense of everyday folk psychological practice, and also offers a more constructive way to understand the relationship between folk psychological and neurocognitive ontologies. The folk psychological ontology of the mental might not be appropriate for describing the functional organisation of the brain, but rather than eliminating or revising it, we should instead recognise that it has a very different aim and purpose than neurocognitive ontologies

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

Style in the Age of Instagram: Predicting Success within the Fashion Industry using Social Media

Fashion is a multi-billion dollar industry with social and economic implications worldwide. To gain popularity, brands want to be represented by the top popular models. As new faces are selected using stringent (and often criticized) aesthetic criteria, a priori predictions are made difficult by information cascades and other fundamental trend-setting mechanisms. However, the increasing usage of social media within and without the industry may be affecting this traditional system. We therefore seek to understand the ingredients of success of fashion models in the age of Instagram. Combining data from a comprehensive online fashion database and the popular mobile image-sharing platform, we apply a ma- chine learning framework to predict the tenure of a cohort of new faces for the 2015 Spring/Summer season throughout the subsequent 2015-16 Fall / Winter season. Our framework successfully predicts most of the new popular models who appeared in 2015. In particular, we find that a strong social media presence may be more important than being under contract with a top agency, or than the aesthetic standards sought after by the industry.