Lifeworld Analysis

We argue that the analysis of agent/environment interactions should be extended to include the conventions and invariants maintained by agents throughout their activity. We refer to this thicker notion of environment as a lifeworld and present a partial set of formal tools for describing structures of lifeworlds and the ways in which they computationally simplify activity. As one specific example, we apply the tools to the analysis of the Toast system and show how versions of the system with very different control structures in fact implement a common control structure together with different conventions for encoding task state in the positions or states of objects in the environment.Comment: See http://www.jair.org/ for any accompanying file

Modelling and mapping how common guillemots balance their energy budgets over a full annual cycle

The ability of individual animals to balance their energy budgets throughout the annual cycle is important for their survival, reproduction and population dynamics. However, the annual cycles of many wild, mobile animals are difficult to observe and our understanding of how individuals balance their energy budgets throughout the year therefore remains poor. We developed a hierarchical Bayesian state-space model to investigate how key components of animal energy budgets (namely individual energy gain and storage) varied in space and time. Our model used biologger-derived estimates of time-activity budgets, locations and energy expenditure to infer year-round time series of energy income and reserves. The model accounted for seasonality in environmental drivers such as sea surface temperature and daylength, allowing us to identify times and locations of high energy gain. Our study system was a population of common guillemots Uria aalge breeding at a western North Sea colony. These seabirds manage their energy budgets by adjusting their behaviour and accumulating fat reserves. However, typically during severe weather conditions, birds can experience an energy deficit over a sustained period, leading to starvation and large-scale mortality events. We show that guillemot energy gain varied in both time and space. Estimates of guillemot body mass varied throughout the annual cycle and birds periodically experienced losses in mass. Mass losses were likely to have either been adaptive, or due to energetic bottlenecks, the latter leading to increased susceptibility to mortality. Guillemots tended to be lighter towards the edge of their spatial distribution. We describe a framework that combines biologging data, time-activity budget analysis and Bayesian state-space modelling to identify times and locations of high energetic reward or potential energetic bottlenecks in a wild animal population. Our approach can be extended to address ecological and conservation-driven questions that were previously unanswerable due to logistical complexities in collecting data on wild, mobile animals across full annual cycles

The sensitivity of seabird populations to density-dependence, environmental stochasticity and anthropogenic mortality

The balance between economic growth and wildlife conservation is a priority for many governments. Enhancing realism in assessment of population‐level impacts of anthropogenic mortality can help achieve this balance. Population Viability Analysis (PVA) is commonly applied to investigate population vulnerability, but outcomes of PVA are sensitive to formulations of density‐dependence, environmental stochasticity and life history. Current practice in marine assessments is to use precautionary models that assume no compensation from density‐dependence or rescue‐effects via “re‐seeding” from other colonies. However, if we could empirically quantify regulatory population processes, the responses of populations to additional anthropogenic mortality may be assessed with more realism in PVA. Using Bayesian state‐space models fitted to population time series from three sympatric seabird populations, selected for varied life histories, we inferred the extent to which their dynamics are driven by environmental stochasticity and density‐dependence. Based on these inferences, we conducted an exhaustive PVA across credible parameterizations for intrinsic and extrinsic population regulation, simulated as a closed and re‐seeded system. Scenarios of anthropogenic mortality, along a sliding scale of precaution, were applied both proportionally and as a fixed quota using Potential Biological Removal (PBR). Baseline results from fitting revealed clear environmental regulation in two of our three species. Crucially, we found that for our empirically derived, realistic model parameterizations there are risks of decline to real populations even under very precautionary mortality scenarios. We find that PBR is dubious in application as a sustainable tool for population assessment when we account for regulation. Closed versus re‐seeded models showed a large divergence in outcomes, with sharper declines in closed simulations. Fixed‐quota mortality typically induced greater population declines comparative to proportional mortality, subject to regulation and re‐seeding. Synthesis and applications. Practitioners using arbitrary formulations of population regulation risk over‐precaution (economic constraint) or under‐precaution (endangering populations). The demands of increased economic development and preservation of wildlife require that methodologies apply techniques that confer reality and rigour to assessment. The current practice of employing models lacking density‐dependence and empirical environmental information imposes limitations in the efficacy of estimating impacts. Here, we provide a method to quantify the conditions that predominantly regulate a population and exacerbate the risk of decline from anthropogenic mortality. It is in the interests of both developers and conservationists to apply methods in population impact assessments that capture realism in the processes driving population dynamics

Improving assessments of data-limited populations using life-history theory

Funder: Research EnglandFunder: UK Joint Nature Conservation Committee (DEFRA)Predicting how populations may respond to climate change and anthropogenic pressures requires detailed knowledge of demographic traits, such as survival and reproduction. However, the availability of these data varies greatly across space and taxa. Therefore, it is common practice to conduct population assessments by filling in missing values from surrogate species or other populations of the same species. Using these independent surrogate values concurrently with observed data neglects the life‐history trade‐offs that connect the different aspects of a population's demography. Consequently, this approach introduces biases that could ultimately lead to erroneous management decisions. We use a Bayesian hierarchical framework to combine fragmented multi‐population data with established life‐history theory and reconstruct population‐specific demographic data across a substantial part of a species breeding range. We apply our analysis to a long‐lived colonial species, the black‐legged kittiwake Rissa tridactyla, that is classified as globally Vulnerable and is highly threatened by increasing anthropogenic pressures, including offshore renewable energy development. We then use a projection analysis to examine how the reconstructed demographic parameters may improve population assessments, compared to models that combine observed data with independent surrogate values. Demographic parameters reconstructed using a hierarchical framework can be utilised in a range of population modelling approaches. They can also be used as reference estimates to assess whether independent surrogate values are likely to over or underestimate missing demographic parameters. We show that surrogate values from independent sources are often used to fill in missing parameters that have large potential demographic impact, and that resulting biases are driven in unpredictable directions thus precluding assessments from being consistently precautionary. Synthesis and applications. Our study dramatically increases the spatial coverage of population‐specific demographic data for black‐legged kittiwakes. The reconstructed demographic parameters presented can also be used immediately to reduce uncertainty in the consenting process for offshore wind development in the United Kingdom and Ireland. More broadly, we show that the reconstruction approach used here provides a new avenue for improving evidence‐based management and policy action for animal and plant populations with fragmented and error prone demographic data

Attentional differences in a driving hazard perception task in adults with autism spectrum disorders

The current study explored attentional processing of social and non social stimuli in ASD within the context of a driving hazard perception task. Participants watched videos of road scenes and detected hazards while their eye movements were recorded. Although individuals with ASD demonstrated relatively good detection of driving hazards, they were slower to orient to hazards. Greater attentional capture in the time preceding the hazards’ onset was associated with lower verbal IQ. The findings suggest that individuals with ASD may distribute and direct their attention diferently when identifying driving hazards

Rapid selection of cyclic peptides that reduce alpha-synuclein toxicity in yeast and animal models

Phage display has demonstrated the utility of cyclic peptides as general protein ligands but cannot access proteins inside eukaryotic cells. Expanding a new chemical genetics tool, we describe the first expressed library of head-to-tail cyclic peptides in yeast (Saccharomyces cerevisiae). We applied the library to selections in a yeast model of alpha-synuclein toxicity that recapitulates much of the cellular pathology of Parkinson's disease. From a pool of 5 million transformants, we isolated two related cyclic peptide constructs that specifically reduced the toxicity of human alpha-synuclein. These expressed cyclic peptide constructs also prevented dopaminergic neuron loss in an established Caenorhabditis elegans Parkinson's model. This work highlights the speed and efficiency of using libraries of expressed cyclic peptides for forward chemical genetics in cellular models of human disease