A pathway in primate brain for internal monitoring of movements.

It is essential to keep track of the movements we make, and one way to do that is to monitor correlates, or corollary discharges, of neuronal movement commands. We hypothesized that a previously identified pathway from brainstem to frontal cortex might carry corollary discharge signals. We found that neuronal activity in this pathway encodes upcoming eye movements and that inactivating the pathway impairs sequential eye movements consistent with loss of corollary discharge without affecting single eye movements. These results identify a pathway in the brain of the primate Macaca mulatta that conveys corollary discharge signals.

Modeling the Effects of Habitat Fragmentation on the Movements of the Mongolian Gazelle in the Eastern Mongolian Steppe

The Mongolian gazelle, Procapra gutturosa, resides in the immense and dynamic ecosystem of the Eastern Mongolian Steppe. The Mongolian Steppe ecosystem dynamics, including vegetation availability, change rapidly and dramatically due to unpredictable precipitation patterns. The Mongolian gazelle has adapted to this unpredictable vegetation availability by making long range nomadic movements. However, predicting these movements is challenging and requires a complex model. An accurate model of gazelle movements is needed, as rampant habitat fragmentation due to human development projects - which inhibit gazelles from obtaining essential resources - increasingly threaten this nomadic species. We created a novel model using an Individual-based Neural Network Genetic Algorithm (ING) to predict how habitat fragmentation affects animal movement, using the Mongolian Steppe as a model ecosystem. We used Global Positioning System (GPS) collar data from real gazelles to “train” our model to emulate characteristic patterns of Mongolian gazelle movement behavior. These patterns are: preferred vegetation resources (NDVI), displacement over certain time lags, and proximity to human areas. With this trained model, we then explored how potential scenarios of habitat fragmentation may affect gazelle movement. This model can be used to predict how fragmentation of the Mongolian Steppe may affect the Mongolian gazelle. In addition, this model is novel in that it can be applied to other ecological scenarios, since we designed it in modules that are easily interchanged.

Public sector pay in the UK: has the historic pattern of public/private sector pay movements been broken?

The historic pattern of public sector pay movements in the UK has been counter-cyclical with private sector pay growth. Periods of relative decline in public sector pay against private sector movements have been followed by periods of ‘catch-up’ as Government controls are eased to remedy skill shortages or deal with industrial unrest among public servants. Public sector ‘catch up’ increases have therefore come at awkward times for Government, often coinciding with economic downturn in the private sector (Trinder 1994, White 1996, Bach 2002). Several such epochs of public sector pay policy can be identified since the 1970s. The question is whether the current limits on public sector pay being imposed by the UK Government fit this historic pattern or whether the pattern has been broken and, if so, how and why? This paper takes a historical approach in considering the context to public sector pay determination in the UK. In particular the paper seeks to review the period since Labour came into office (White and Hatchett 2003) and the various pay ‘modernisation’ exercises that have been in process over the last decade (White 2004). The paper draws on national statistics on public sector employment and pay levels to chart changes in public sector pay policy and draws on secondary literature to consider both Government policy intentions and the impact of these policies for public servants.

Encounter success of free-ranging marine predator movements across a dynamic prey landscape

Movements of wide-ranging top predators can now be studied effectively using satellite and archival telemetry. However, the motivations underlying movements remain difficult to determine because trajectories are seldom related to key biological gradients, such as changing prey distributions. Here, we use a dynamic prey landscape of zooplankton biomass in the north-east Atlantic Ocean to examine active habitat selection in the plankton-feeding basking shark Cetorhinus maximus. The relative success of shark searches across this landscape was examined by comparing prey biomass encountered by sharks with encounters by random-walk simulations of ‘model’ sharks. Movements of transmitter-tagged sharks monitored for 964 days (16754km estimated minimum distance) were concentrated on the European continental shelf in areas characterized by high seasonal productivity and complex prey distributions. We show movements by adult and sub-adult sharks yielded consistently higher prey encounter rates than 90% of random-walk simulations. Behavioural patterns were consistent with basking sharks using search tactics structured across multiple scales to exploit the richest prey areas available in preferred habitats. Simple behavioural rules based on learned responses to previously encountered prey distributions may explain the high performances. This study highlights how dynamic prey landscapes enable active habitat selection in large predators to be investigated from a trophic perspective, an approach that may inform conservation by identifying critical habitat of vulnerable species.

Seasonal movements and behaviour of basking sharks from archival tagging: No evidence of winter hibernation

Habitat selection processes in highly migratory animals such as sharks and whales are important to understand because they influence patterns of distribution, availability and therefore catch rates. However, spatial strategies remain poorly understood over seasonal scales in most species, including, most notably, the plankton-feeding basking shark Cetorhinus maximus. It was proposed nearly 50 yr ago that this globally distributed species migrates from coastal summer-feeding areas of the northeast Atlantic to hibernate during winter in deep water on the bottom of continental-shelf slopes. This view has perpetuated in the literature even though the 'hibernation theory' has not been tested directly. We have now tracked basking sharks for the first time over seasonal scales (1.7 to 6.5 mo) using 'pop-up' satellite archival transmitters. We show that they do not hibernate during winter but instead undertake extensive horizontal (up to 3400 km) and vertical (> 750 m depth) movements to utilise productive continental-shelf and shelf-edge habitats during summer, autumn and winter. They travel long distances (390 to 460 km) to locate temporally discrete productivity 'hotspots' at shelf-break fronts, but at no time were prolonged movements into open-ocean regions away from shelf waters observed. Basking sharks have a very broad vertical diving range and can dive beyond the known range of planktivorous whales. Our study suggests this species can exploit shelf and slope-associated zooplankton communities in mesopelagic (200 to 1000 m) as well as epipelagic habitat (0 to 200 m).