Planting on Rural School Grounds

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Familiarity affects social network structure and discovery of prey patch locations in foraging stickleback shoals

Numerous factors affect the fine-scale social structure of animal groups, but it is unclear how important such factors are in determining how individuals encounter resources. Familiarity affects shoal choice and structure in many social fishes. Here, we show that familiarity between shoal members of sticklebacks (Gasterosteus aculeatus) affects both fine-scale social organization and the discovery of resources. Social network analysis revealed that sticklebacks remained closer to familiar than to unfamiliar individuals within the same shoal. Network-based diffusion analysis revealed that there was a strong untransmitted social effect on patch discovery, with individuals tending to discover a task sooner if a familiar individual from their group had previously done so than if an unfamiliar fish had done so. However, in contrast to the effect of familiarity, the frequency with which individuals had previously associated with one another had no effect upon the likelihood of prey patch discovery. This may have been due to the influence of fish on one another's movements; the effect of familiarity on discovery of an empty ‘control’ patch was as strong as for discovery of an actual prey patch. Our results demonstrate that factors affecting fine-scale social interactions can also influence how individuals encounter and exploit resources.Publisher PDFPeer reviewe

Identification and characterisation of 17 polymorphic candidate genes for response to parasitic nematode (Trichostrongylus tenuis) infection in red grouse (Lagopus lagopus scotica)

Acknowledgements This study was funded by a BBSRC studentship (MA Wenzel) and NERC Grants NE/H00775X/1 and NE/D000602/1 (SB Piertney). We are grateful to Jacob Hoglund for providing willow grouse samples, Mario Roder, Keliya Bai, Marianne James, Matt Oliver, Gill Murray-Dickson, Francois Mougeot and Jesus Martınez-Padilla for help with fieldwork, and all grouse estate factors, owners and keepers, most particularly Alistair Mitchell, Shaila Rao, Christopher Murphy, Richard Cooke and Fred Taylor, for providing access to estate game larders.Peer reviewedPostprin

Isolation and characterisation of 17 microsatellite loci for the red-billed chough (Pyrrhocorax pyrrhocorax)

Peer reviewedPostprin

Wiener Reconstruction of Large-Scale Structure from Peculiar Velocities

We present an alternative, Bayesian method for large-scale reconstruction from observed peculiar velocity data. The method stresses a rigorous treatment of the random errors and it allows extrapolation into poorly sampled regions in real space or in k-space. A likelihood analysis is used to determine the fluctuation power spectrum, followed by a Wiener Filter (WF) analysis to obtain the minimum-variance mean fields of velocity and mass density. Constrained Realizations (CR) are then used to sample the statistical scatter about the WF mean field. The WF/CR method is applied as a demonstration to the Mark III data with 1200 km/s, 900 km/s, and 500 km/s resolutions. The main reconstructed structures are consistent with those extracted by the POTENT method. A comparison with the structures in the distribution of IRAS 1.2Jy galaxies yields a general agreement. The reconstructed velocity field is decomposed into its divergent and tidal components relative to a cube of +/-8000 km/s centered on the Local Group. The divergent component is very similar to the velocity field predicted from the distribution of IRAS galaxies. The tidal component is dominated by a bulk flow of 194 +/- 32 km/s towards the general direction of the Shapley concentration, and it also indicates a significant quadrupole.Comment: 28 pages and 8 GIF figures, Latex (aasms4.sty), submitted to ApJ. Postscript version of the figures can be obtained by anonymous ftp from: ftp://alf.huji.ac.il/pub/saleem

Intensive Grandmothering? Exploring the Changing Nature of Grandmothering in the Context of Changes to Parenting Culture

This paper explores the ways in which the intensification of parenting and the notion of children at risk have influenced grandmothers’ narratives and practices. Interviews with grandmothers who regularly look after their grandchildren, reveal that their practices are framed around the notions of children to be protected, educated and entertained. Such notions reveal that aspects of grandmothers’ roles as protectors, educators, playmates and confidants involved negotiations with parents around the ideal of ‘putting the child first’. The paper argues that intensive parenting has influenced grandmothering but the way this is enacted reveals resistance to certain aspects of intensive parenting

Uncertainty assessment of spatial soil information

Uncertainty is present in our daily lives. It affects our decisions on what to do. The weather forecast might tell us that there is a 60% chance that it will rain: we take umbrellas. If it says that the chance of rain is only 10% we might decide to leave our umbrellas at home and risk getting wet. More seriously, farmers want to know the likelihood of disease in their crops and the deficiencies in plant nutrients in the soil. These are matters that affect profit and loss of farm business. Agencies responsible for public health and environmental protection need to weigh the risk of doing nothing in the face of uncertain threats against the cost of acting unnecessarily to counter them when the threats are almost non-existent. There are many examples of decision making problems involving uncertain soil information. They include the remediation of polluted soil, the prevention of soil erosion, and the mitigation of pesticide leaching. They are practical matters, not purely academic exercises in statistics. All measurements of soil properties (and other environmental variables) contain error in the sense that they depart from the true values. That error arises from imperfections in the analytical instruments, from the people who use them and from errors that occur during the processing of the recorded data to make them suitable for storage in information databases. Short-range spatial variation is another source of error, given that soil samples are never returned to where they were taken and sampling locations have positional error. Soil taken from location s and analysed in the laboratory might differ substantially from the soil at location s + h, even if |h| is as small as a few decimeters. Composite soil sampling can diminish these differences, but some error inevitably persists because even such a composite is still only a sample of all the soil at that site. All this means that we can never be sure about the true state of the soil: we, the producers and users of soil information, are to some extent uncertain. Uncertainty tends to increase when measurements of basic soil properties are used to obtain derived ones via pedotransfer functions or mechanistic models of dynamic soil processes, for example. Interpolation from measurements to create maps of soil properties adds to the errors of measurement and so too increases uncertainties. We must conclude that considerable uncertainty is often associated with the information that is stored in soil databases and presented in various forms, including maps. This does not mean that the information is of no value; uncertainty is not the same as ignorance. In many cases we do know a great deal about the soil, but we must also acknowledge that the information is not perfect. Some numerical expression of the uncertainty is important because it is needed to determine whether the information is sufficiently accurate for the purpose that a user has in mind. Soil data of too poor a quality might lead to flawed decisions with serious undesirable consequences, both economic and environmental. For instance, the European legislation on the use of pesticides in agriculture depends crucially on the leaching potential of these substances to the ground- and surface-water, which in turn depends importantly on soil properties. In these circumstances users should be aware of the quality of the soil information so that they can be sure that it is sufficiently reliable for their purposes. Ideally they should account for the uncertainty of the information when making their decisions. This chapter (i) provides a statistical definition of uncertainty in soil information; (ii) extends this definition to uncertainty in spatial soil information; (iii) reviews methods that are used to quantify uncertainty in soil information, while paying attention to different sources of uncertainty; (iv) shows how uncertainty in soil information propagates through subsequent analyses; and (v) explains how uncertainty information can be used in decision making. It focuses on the quantification of uncertainty of soil properties that are measured and recorded on continuous scales: properties such as pH, particle-size distribution, and soil organic matter content. The chapter also addresses uncertainty of categorical variables, such as soil type and diagnostic properties recorded as present or absent, i.e. binary variables. It begins with defining uncertainty in a single soil measuremen