Utilisation of intensive foraging zones by female Australian fur seals.

Within a heterogeneous environment, animals must efficiently locate and utilise foraging patches. One way animals can achieve this is by increasing residency times in areas where foraging success is highest (area-restricted search). For air-breathing diving predators, increased patch residency times can be achieved by altering both surface movements and diving patterns. The current study aimed to spatially identify the areas where female Australian fur seals allocated the most foraging effort, while simultaneously determining the behavioural changes that occur when they increase their foraging intensity. To achieve this, foraging behaviour was successfully recorded with a FastLoc GPS logger and dive behaviour recorder from 29 individual females provisioning pups. Females travelled an average of 118 ± 50 km from their colony during foraging trips that lasted 7.3 ± 3.4 days. Comparison of two methods for calculating foraging intensity (first-passage time and first-passage time modified to include diving behaviour) determined that, due to extended surface intervals where individuals did not travel, inclusion of diving behaviour into foraging analyses was important for this species. Foraging intensity 'hot spots' were found to exist in a mosaic of patches within the Bass Basin, primarily to the south-west of the colony. However, the composition of benthic habitat being targeted remains unclear. When increasing their foraging intensity, individuals tended to perform dives around 148 s or greater, with descent/ascent rates of approximately 1.9 m•s-1 or greater and reduced postdive durations. This suggests individuals were maximising their time within the benthic foraging zone. Furthermore, individuals increased tortuosity and decreased travel speeds while at the surface to maximise their time within a foraging location. These results suggest Australian fur seals will modify both surface movements and diving behaviour to maximise their time within a foraging patch

The geographies of cyberspace

In this I paper I explore the need for a new field of geographic enquiry called cybergeography. This is the investigation of the complex and multifaceted structure, use and experience of the online world inside global computer-communications networks, most obviously represented by the Internet and the World-Wide Web. In particular I focus on how one can study the geography of Internet diffusion from publicly available statistics. Then I consider ways that the landscapes of Cyberspace can be mapped to enhance our understanding of their evolving form and texture using examples of a real-time “weather map” of Internet congestion and maps of the urban structure of virtual world

Environmental public health tracking of childhood asthma using California health interview survey, traffic, and outdoor air pollution data.

BackgroundDespite extensive evidence that air pollution affects childhood asthma, state-level and national-level tracking of asthma outcomes in relation to air pollution is limited.ObjectivesOur goals were to evaluate the feasibility of linking the 2001 California Health Interview Survey (CHIS), air monitoring, and traffic data; estimate associations between traffic density (TD) or outdoor air pollutant concentrations and childhood asthma morbidity; and evaluate the usefulness of such databases, linkages, and analyses to Environmental Public Health Tracking (EPHT).MethodsWe estimated TD within 500 feet of residential cross-streets of respondents and annual average pollutant concentrations based on monitoring station measurements. We used logistic regression to examine associations with reported asthma symptoms and emergency department (ED) visits/hospitalizations.ResultsAssignment of TD and air pollution exposures for cross-streets was successful for 82% of children with asthma in Los Angeles and San Diego, California, Counties. Children with asthma living in high ozone areas and areas with high concentrations of particulate matter < 10 microm in aerodynamic diameter experienced symptoms more frequently, and those living close to heavy traffic reported more ED visits/hospitalizations. The advantages of the CHIS for asthma EPHT include a large and representative sample, biennial data collection, and ascertainment of important socio-demographic and residential address information. Disadvantages are its cross-sectional design, reliance on parental reports of diagnoses and symptoms, and lack of information on some potential confounders.ConclusionsDespite limitations, the CHIS provides a useful framework for examining air pollution and childhood asthma morbidity in support of EPHT, especially because later surveys address some noted gaps. We plan to employ CHIS 2003 and 2005 data and novel exposure assessment methods to re-examine the questions raised here

Autonomous Accident Monitoring Using Cellular Network Data

Mobile communication networks constitute large-scale sensor networks that generate huge amounts of data that can be refined into collective mobility patterns. In this paper we propose a method for using these patterns to autonomously monitor and detect accidents and other critical events. The approach is to identify a measure that is approximately time-invariant on short time-scales under regular conditions, estimate the short and long-term dynamics of this measure using Bayesian inference, and identify sudden shifts in mobility patterns by monitoring the divergence between the short and long-term estimates. By estimating long-term dynamics, the method is also able to adapt to long-term trends in data. As a proof-of-concept, we apply this approach in a vehicular traffic scenario, where we demonstrate that the method can detect traffic accidents and distinguish these from regular events, such as traffic congestions

Tracking Pacific bluefin tuna (Thunnus thynnus orientalis) in the northeastern Pacific with an automated algorithm that estimates latitude by matching sea-surface-temperature data from satellites with temperature data from tags on fish

Data recovered from 11 popup satellite archival tags and 3 surgically implanted archival tags were used to analyze the movement patterns of juvenile northern bluefin tuna (Thunnus thynnus orientalis) in the eastern Pacific. The light sensors on archival and pop-up satellite transmitting archival tags (PSATs) provide data on the time of sunrise and sunset, allowing the calculation of an approximate geographic position of the animal. Light-based estimates of longitude are relatively robust but latitude estimates are prone to large degrees of error, particularly near the times of the equinoxes and when the tag is at low latitudes. Estimating latitude remains a problem for researchers using light-based geolocation algorithms and it has been suggested that sea surface temperature data from satellites may be a useful tool for refining latitude estimates. Tag data from bluefin tuna were subjected to a newly developed algorithm, called “PSAT Tracker,” which automatically matches sea surface temperature data from the tags with sea surface temperatures recorded by satellites. The results of this algorithm compared favorably to the estimates of latitude calculated with the lightbased algorithms and allowed for estimation of fish positions during times of the year when the lightbased algorithms failed. Three near one-year tracks produced by PSAT tracker showed that the fish range from the California−Oregon border to southern Baja California, Mexico, and that the majority of time is spent off the coast of central Baja Mexico. A seasonal movement pattern was evident; the fish spend winter and spring off central Baja California, and summer through fall is spent moving northward to Oregon and returning to Baja California

Using tracked mobile sensors to make maps of environmental effects

We present a study the results of a study of environmental carbon monoxide pollution that has uses a set of tracked, mobile pollution sensors. The motivating concept is that we will be able to map pollution and other properties of the real world a fine scale if we can deploy a large set of sensors with members of the general public who would carry them as they go about their normal everyday activities. To prove the viability of this concept we have to demonstrate that data gathered in an ad-hoc manner is reliable enough in order to allow us to build interesting geo-temporal maps. We present a trial using a small number of global positioning system-tracked CO sensors. From analysis of raw GPS logs we find some well-known spatial and temporal properties of CO. Further, by processing the GPS logs we can find fine-grained variations in pollution readings such as when crossing roads. We then discuss the space of possibilities that may be enabled by tracking sensors around the urban environment – both in getting at personal experience of properties of the environment and in making summative maps to predict future conditions. Although we present a study of CO, the techniques will be applicable to other environmental properties such as radio signal strength, noise, weather and so on

Predicting Risk for Deer-Vehicle Collisions Using a Social Media Based Geographic Information System

As an experiment investigating social media as a data source for making management decisions, photo sharing websites were searched for data on deer sightings. Data about deer density and location are important factors in decisions related to herd management and transportation safety, but such data are often limited or not available. Results indicate that when combined with simple rules, data from photo sharing websites reliably predicted the location of road segments with high risk for deer-vehicle collisions as reported by volunteers to an internet site tracking roadkill. Use of Google Maps as the GIS platform was helpful in plotting and sharing data, measuring road segments and other distances, and overlaying geographical data. The ability to view satellite images and panoramic street views proved to be a particularly useful. As a general conclusion, the two independently collected sets of data from social media provided consistent information, suggesting investigative value to this data source. Overlaying two independently collected data sets can be a useful step in evaluating or mitigating reporting bias and human error in data taken from social media

Validating the use of intrinsic markers in body feathers to identify inter-individual differences in non-breeding areas of northern fulmars

Acknowledgments We thank Claire Deacon, Gareth Norton and Andrea Raab for help with laboratory work at the University of Aberdeen, and Barry Thornton and Gillian Martin for running stable isotope analysis at the James Hutton Institute. Thanks to all involved in the collection and processing of dead fulmars through the North Sea plastic pollution project at IMARES, with special thanks to Jens-Kjeld Jensen, Bergur Olsen and Elisa Bravo Rebolledo for samples from the Faroe Islands and Susanne Kühn for those from Iceland. Thanks to Orkney Islands Council for access to Eynhallow and to all the fieldworkers involved in deployment and recovery of the GLS tags. All ringing work was carried out under permit from the BTO, and feather sampling was carried out under licence from the Home Office. We are grateful to James Fox of Migrate Technologies for recovering data from GLS loggers which would not download, and Richard Phillips and Janet Silk of BAS for advice on GLS analysis. We thank Deborah Dawson of the NERC Biomolecular Analysis Facility, University of Sheffield and Stuart Piertney of University of Aberdeen for molecular sexing of the fulmars. Lucy Quinn was supported by a NERC Studentship and additional funding to support fieldwork was gratefully received from Talisman Energy (UK) Ltd. We thank Yves Cherel and two anonymous reviewers for their constructive comments on the manuscript.Peer reviewedPublisher PD