With life-history traits involving high survival, low reproductive output, years of natal dispersal and deferred maturity, the population ecology and behaviour of large raptors which occur at low densities can be difficult to study. The age at which large raptors first settle on a prospective breeding territory receives relatively little attention, but is a key metric in population modelling including, for example, projections of reintroduction projects. It can also be a barometer of the “health” of populations and the availability of breeding opportunities. The advancement of GPS-telemetry has proved invaluable in gaining insights into several aspects of large raptor ecology and behaviour. Age of first territory settlement (AFTS) is one such aspect. AFTS is important in modelling population trajectories and considering individuals’ lifetime reproductive success. We used an algorithm based on GPS-records from dispersing Golden Eagles tagged as nestlings in Scotland to estimate AFTS. While the lifespan of GPS-tags can bias against settlement dates of older birds, they can also potentially reveal settlement ages difficult or impossible to discern from other methods. We found a range of ages for AFTS, including those in their second calendar year; much younger than previously documented by other methods. Ground-truthing – when possible and if inevitably slightly delayed – confirmed territory occupation on field-based survey criteria. We found that eagles settled younger in vacant territories and when older in occupied existing territories. Birds’ sex had no effect on AFTS. Birds which dispersed earlier from their natal territory (indicative of “quality” from some previous research) had no association with AFTS. Our results indicate that within technological temporal limits GPS-data can provide for accurate and precise estimations of AFTS including early settlement not consistently or precisely recorded by other methods. Within our study’s variable competitive landscape we found that AFTS was associated with the availability of territorial opportunities but not with the timing of dispersal. These findings have consequences for studying and understanding large raptor population dynamics.

Many large raptors exploit or rely on anabatic and orographic winds which provide vertical lift, to supplement or provide the energy fuelling flight. Airspace is therefore a critical habitat for such large raptors and its use is subject to the underlying terrestrial topography, because particular topographical features are more likely to provide wind‐energetic lift. Accordingly, ridges and/or ‘rugged topography’ are common preferred features in habitat use by large raptors. Our study aimed to provide a simple model of space use for a large raptor, the Golden Eagle Aquila chrysaetos, based on thousands of GPS telemetry records during juvenile dispersal of 92 birds tagged as nestlings between 2007 and 2016 across upland Scotland. Model development was based on the hypothesis that four topographical variables would be influential: slope, aspect, altitude and distance from ridge. The telemetry dataset was divided into training and two testing components. The first testing set was derived by a temporal split resulting in approximately equal sample size on records and some temporal overlap in individuals’ records with training data. The second testing set involved no individuals from the training set. Aspect was removed early in training model development because it was not influential. The model found that young Golden Eagles preferred, or used according to availability, space above slopes greater than 10°, at an altitude of ≥ 300 m, and within 300 m of a ridge. The test data were highly correlated with those from the training data in the model variables, and performance as regard to expected preferences from the model was improved in both test datasets, indicating the model was robust. Given the apparent universal nature of large raptor dependence on topography, that topography is relatively immutable according to time and use, and that topographical data are readily available, we commend our approach to other habitat preference studies of Golden Eagles and other large raptors elsewhere.

Wind farms can have two broad potential adverse effects on birds via antagonistic processes: displacement from the vicinity of turbines (avoidance), or death through collision with rotating turbine blades. These effects may not be mutually exclusive. Using detailed data from 99 turbines at two wind farms in central Scotland and thousands of GPS-telemetry data from dispersing golden eagles, we tested three hypotheses. Before-and-after-operation analyses supported the hypothesis of avoidance: displacement was reduced at turbine locations in more preferred habitat and with more preferred habitat nearby. After-operation analyses (i.e. from the period when turbines were operational) showed that at higher wind speeds and in highly preferred habitat eagles were less wary of turbines with motionless blades: rejecting our second hypothesis. Our third hypothesis was supported, since at higher wind speeds eagles flew closer to operational turbines; especially–once more–turbines in more preferred habitat. After operation, eagles effectively abandoned inner turbine locations, and flight line records close to rotor blades were rare. While our study indicated that whole-wind farm functional habitat loss through avoidance was the substantial adverse impact, we make recommendations on future wind farm design to minimise collision risk further. These largely entail developers avoiding outer turbine locations which are in and surrounded by swathes of preferred habitat. Our study illustrates the insights which detailed case studies of large raptors at wind farms can bring and emphasises that the balance between avoidance and collision can have several influences.

Wind farms may have two broad potential adverse effects on birds via antagonistic processes: displacement from the vicinity of turbines (avoidance), or death through collision with rotating turbine blades. Large raptors are often shown or presumed to be vulnerable to collision and are demographically sensitive to additional mortality, as exemplified by several studies of the Golden Eagle Aquila chrysaetos. Previous findings from Scottish Eagles, however, have suggested avoidance as the primary response. Our study used data from 59 GPS-tagged Golden Eagles with 28 284 records during natal dispersal before and after turbine operation < 1 km of 569 turbines at 80 wind farms across Scotland. We tested three hypotheses using measurements of tag records' distance from the hub of turbine locations: (1) avoidance should be evident; (2) older birds should show less avoidance (i.e. habituate to turbines); and (3) rotor diameter should have no influence (smaller diameters are correlated with a turbine's age, in examining possible habituation). Four generalized linear mixed models (GLMMs) were constructed with intrinsic habitat preference of a turbine location using Golden Eagle Topography (GET) model, turbine operation status (before/after), bird age and rotor diameter as fixed factors. The best GLMM was subsequently verified by k-fold cross-validation and involved only GET habitat preference and presence of an operational turbine. Eagles were eight times less likely to be within a rotor diameter's distance of a hub location after turbine operation, and modelled displacement distance was 70 m. Our first hypothesis expecting avoidance was supported. Eagles were closer to turbine locations in preferred habitat but at greater distances after turbine operation. Results on bird age (no influence to 5+ years) rejected hypothesis 2, implying no habituation. Support for hypothesis 3 (no influence of rotor diameter) also tentatively inferred no habituation, but data indicated birds went slightly closer to longer rotor blades although not to the turbine tower. We proffer that understanding why avoidance or collision in large raptors may occur can be conceptually envisaged via variation in fear of humans as the 'super predator' with turbines as cues to this life-threatening agent.

Since May 1977 the Penzance Branch of the British Sub-Aqua Club has carried out a routine survey, as a contribution towards the Underwater Conservation Year Programme, on the fauna and flora of a sublittoral reef situated about 300 m to the south west of the Gear Reef in Penzance Bay. The reef is situated in water of about 17 m depth and is generally surrounded by firm sand with patches of Zostera. The reef itself is about 30 m long and 17 m wide at its widest point and 8 m high with vertical faces and overhangs at its northern end. The sides slope by stages to the sand at the southern end and contain many deep fissures with a large one at the northern end widening to a cave that passes through from east to west. The reef is aligned with its longitudinal axis running north-south and provides a diverse environment for a rich fauna and flora, a considerable background knowledge of which has been gained by the survey: by late August 1978 a total of over 30 dives, each of approximately one hour's duration, had been made in this area.