Non-reproductive dispersal: an important driver of migratory range dynamics and connectivity

Dispersal is the primary ecological process underpinning spatial dynamics in motile species by generating flux in reproductive locations over time. In migratory species, dispersal can also occur around non-breeding ranges, but this form currently lacks a unifying theoretical framework. We present a novel conceptual model for dispersal in migrants that builds upon existing literature, differentiating ‘reproductive' dispersal (i.e. changes in breeding locations) from ‘non-reproductive' dispersal, which we define as movements resulting in inter-annual or inter-generational changes in non-breeding locations. Crucially, unlike reproductive dispersal where movement outcomes are naturally propagated between generations, the outcomes of non-reproductive dispersal can be non-heritable. We use simulations of a solo-migrant population with a genetically encoded migratory programme to illustrate how variation in this heritability exerts a strong influence on both migratory connectivity and range shift propensity. When exposed to spatially uncoupled shifts in habitable ranges (i.e. seasonal climate niches shifting at different rates), long-term persistence of simulated populations required changes in migratory programmes to arise through heritable forms of non-reproductive dispersal (e.g. mutations in migratory gene complexes). By contrast, non-heritable dispersal mechanisms (e.g. navigation errors) cannot drive long-term shifts in non-breeding ranges, despite being a major component of realised dispersal and migratory connectivity patterns. Migratory connectivity metrics conflate these heritable and non-heritable drivers of non-reproductive dispersal, and therefore have limited power in predicting population responses to environmental change. Our models provide a framework for improving our understanding of spatial dynamics in migratory populations, and highlight the importance of teasing apart the mechanisms that drive migratory variability in order to evaluate and predict range plasticity in migrants

Sensitivity of migratory connectivity estimates to spatial sampling design

Background The use of statistical methods to quantify the strength of migratory connectivity is commonplace. However, little attention has been given to their sensitivity to spatial sampling designs and scales of inference. Methods We examine sources of bias and imprecision in the most widely used methodology, Mantel correlations, under a range of plausible sampling regimes using simulated migratory populations. Results As Mantel correlations depend fundamentally on the spatial scale and configuration of sampling, unbiased inferences about population-scale connectivity can only be made under certain sampling regimes. Within a contiguous population, samples drawn from smaller spatial subsets of the range generate lower connectivity metrics than samples drawn from the range as a whole, even when the underlying migratory ecology of the population is constant across the population. Random sampling of individuals from contiguous subsets of species ranges can therefore underestimate population-scale connectivity. Where multiple discrete sampling sites are used, by contrast, overestimation of connectivity can arise due to samples being biased towards larger between-individual pairwise distances in the seasonal range where sampling occurs (typically breeding). Severity of all biases was greater for populations with lower levels of true connectivity. When plausible sampling regimes were applied to realistic simulated populations, accuracy of connectivity measures was maximised by increasing the number of discrete sampling sites and ensuring an even spread of sites across the full range. Conclusions These results suggest strong potential for bias and imprecision when making quantitative inferences about migratory connectivity using Mantel statistics. Researchers wishing to apply these methods should limit inference to the spatial extent of their sampling, maximise their number of sampling sites, and avoid drawing strong conclusions based on small sample sizes

Genetic diversity, recombination and cross-species transmission of a waterbird gammacoronavirus in the wild

Viruses emerging from wildlife can cause outbreaks in humans and domesticated animals. Predicting the emergence of future pathogens and mitigating their impacts requires an understanding of what shapes virus diversity and dynamics in wildlife reservoirs. In order to better understand coronavirus ecology in wild species, we sampled birds within a coastal freshwater lagoon habitat across 5 years, focussing on a large population of mute swans (Cygnus olor) and the diverse species that they interact with. We discovered and characterised the full genome of a divergent gammacoronavirus belonging to the Goose coronavirus CB17 species. We investigated the genetic diversity and dynamics of this gammacoronavirus using untargeted metagenomic sequencing of 223 faecal samples from swans of known age and sex, and RT-PCR screening of 1632 additional bird samples. The virus circulated persistently within the bird community; virus prevalence in mute swans exhibited seasonal variations, but did not change with swan age-class or epidemiological year. One whole genome was fully characterised, and revealed that the virus originated from a recombination event involving an undescribed gammacoronavirus species. Multiple lineages of this gammacoronavirus co-circulated within our study population. Viruses from this species have recently been detected in aquatic birds from both the Anatidae and Rallidae families, implying that host species habitat sharing may be important in shaping virus host range. As the host range of the Goose coronavirus CB17 species is not limited to geese, we propose that this species name should be updated to ‘Waterbird gammacoronavirus 1’. Non-invasive sampling of bird coronaviruses may provide a tractable model system for understanding the evolutionary and cross-species dynamics of coronaviruses

Towards practice-based studies of HRM: an actor-network and communities of practice informed approach

HRM may have become co-terminus with the new managerialism in the rhetorical orthodoxies of the HRM textbooks and other platforms for its professional claims. However, we have detailed case-study data showing that HR practices can be much more complicated, nuanced and indeed resistive toward management within organizational settings. Our study is based on ethnographic research, informed by actor-network theory and community of practice theory conducted by one of the authors over an 18-month period. Using actor-network theory in a descriptive and critical way, we analyse practices of managerial resistance, enrolment and counter-enrolment through which an unofficial network of managers used a formal HRM practice to successfully counteract the official strategy of the firm, which was to close parts of a production site. As a consequence, this network of middle managers effectively changed top management strategy and did so through official HRM practices, coupled with other actor-network building processes, arguably for the ultimate benefit of the organization, though against the initial views of the top management. The research reported here, may be characterized as a situated study of HRM-in-practice and we draw conclusions which problematize the concept of HRM in contemporary management literature

Intensive supplementary feeding improves the performance of wild bird seed plots in provisioning farmland birds throughout the winter: a case study in lowland England

Capsule: Sown bird-food plots with intensive (daily) supplementary feeding throughout the winter attracted substantially greater numbers of seed-eating farmland birds than control plots without additional feeding, whose planted seed resource was exhausted by midwinter. Aims: We studied the performance of cultivated agri-environment scheme (AES) plots, predominantly growing winter bird seed (WBS), in addressing the ‘hungry gap’ of food scarcity for seed-eating farmland birds over the winter period. We assessed whether intensive supplementary feeding can improve AES-WBS plot performance to support greater numbers of birds over a longer period throughout the winter. Methods: Five monthly bird counts were conducted from November to March on AES-WBS plots on three farms during three winters, alongside assessment of standing seed availability on the plants. Daily supplementary feeding of 8-25 kg of mixed seeds was scattered directly onto each treatment plot, with additional seed provided in hanging birdfeeders. The density of target farmland birds, and the depletion of the standing seed resource on plants, was compared between treatment plots and controls over the winter, using generalised linear models. Results: Cultivated AES-WBS plots contained only c. 25% of their potential full capacity of seed availability at the beginning of winter, and this was exhausted by midwinter (January). Supplementary feeding attracted significantly greater numbers of farmland birds to AES-WBS plots than unfed controls, with up to 421 birds per plot, dominated by Common Chaffinches Fringilla coelebs, Yellowhammers Emberiza citronella and Common Linnets Linaria cannabina. Bird densities on fed plots peaked in the late winter (February) ‘hungry gap’, but the magnitude of peak densities varied between years and farms. Conclusion: Intensive supplementary feeding can substantially improve poor performance of AES-WBS plots in supporting farmland birds throughout the winter, particularly during the late winter ‘hungry gap’ when seed availability on AES-WBS plots is otherwise exhausted

Metacognition: computation, biology and function

Many complex systems maintain a self-referential check and balance. In animals, such reflective monitoring and control processes have been grouped under the rubric of metacognition. In this introductory article to a Theme Issue on metacognition, we review recent and rapidly progressing developments from neuroscience, cognitive psychology, computer science and philosophy of mind. While each of these areas is represented in detail by individual contributions to the volume, we take this opportunity to draw links between disciplines, and highlight areas where further integration is needed. Specifically, we cover the definition, measurement, neurobiology and possible functions of metacognition, and assess the relationship between metacognition and consciousness. We propose a framework in which level of representation, order of behaviour and access consciousness are orthogonal dimensions of the conceptual landscape

Understanding concurrent earcons: applying auditory scene analysis principles to concurrent earcon recognition

Two investigations into the identification of concurrently presented, structured sounds, called earcons were carried out. One of the experiments investigated how varying the number of concurrently presented earcons affected their identification. It was found that varying the number had a significant effect on the proportion of earcons identified. Reducing the number of concurrently presented earcons lead to a general increase in the proportion of presented earcons successfully identified. The second experiment investigated how modifying the earcons and their presentation, using techniques influenced by auditory scene analysis, affected earcon identification. It was found that both modifying the earcons such that each was presented with a unique timbre, and altering their presentation such that there was a 300 ms onset-to-onset time delay between each earcon were found to significantly increase identification. Guidelines were drawn from this work to assist future interface designers when incorporating concurrently presented earcons

Accommodating heterogeneous missing data patterns for prostate cancer risk prediction

Objective: We compared six commonly used logistic regression methods for accommodating missing risk factor data from multiple heterogeneous cohorts, in which some cohorts do not collect some risk factors at all, and developed an online risk prediction tool that accommodates missing risk factors from the end-user. Study Design and Setting: Ten North American and European cohorts from the Prostate Biopsy Collaborative Group (PBCG) were used for fitting a risk prediction tool for clinically significant prostate cancer, defined as Gleason grade group greater or equal 2 on standard TRUS prostate biopsy. One large European PBCG cohort was withheld for external validation, where calibration-in-the-large (CIL), calibration curves, and area-underneath-the-receiver-operating characteristic curve (AUC) were evaluated. Ten-fold leave-one-cohort-internal validation further validated the optimal missing data approach. Results: Among 12,703 biopsies from 10 training cohorts, 3,597 (28%) had clinically significant prostate cancer, compared to 1,757 of 5,540 (32%) in the external validation cohort. In external validation, the available cases method that pooled individual patient data containing all risk factors input by an end-user had best CIL, under-predicting risks as percentages by 2.9% on average, and obtained an AUC of 75.7%. Imputation had the worst CIL (-13.3%). The available cases method was further validated as optimal in internal cross-validation and thus used for development of an online risk tool. For end-users of the risk tool, two risk factors were mandatory: serum prostate-specific antigen (PSA) and age, and ten were optional: digital rectal exam, prostate volume, prior negative biopsy, 5-alpha-reductase-inhibitor use, prior PSA screen, African ancestry, Hispanic ethnicity, first-degree prostate-, breast-, and second-degree prostate-cancer family history

The place of strategic environmental assessment in the privatised electricity industry

The private sector has given relatively little attention to the emergence of strategic environmental assessment (SEA); even recently privatised utilities, where SEA might be deemed particularly appropriate, and whose activities are likely to fall within the scope of the European Union SEA Directive, have shown less interest than might be expected. However, the global trend towards the privatisation of state-owned enterprises makes the adaptation of SEA towards these industries all the more pressing. This paper addresses the place that SEA might take within the electricity sector, taking the privatised UK electricity industry as an example. Particular challenges are posed by the radical restructuring of the industry, designed to introduce competitive behaviour, making the development of comprehensive SEA processes problematic, and requiring SEA to be placed in the context of corporate environmental policy and objectives.</p