Bart A. Nolet

The installation of automatic detection systems (ADSs) on operating wind energy facilities is a mitigation measure to reduce bird collisions. The effectiveness of an ADS depends on a combination of parameters, including the detection distance of the bird, its flight speed, and the time to complete the chosen action (e.g., turbine shutdown). We created a web application, Eoldist, to calculate cautionary detection distances required by an ADS, using bird flight speed and turbine shutdown time as input parameters. We compiled a database of the flight speeds of 168 Western Palearctic birds from a review of scientific literature supplemented by an analysis of unpublished GPS-tracking datasets. To estimate turbine shutdown time, we conducted 137 field trials of experimental shutdown at seven wind farms and found that the duration to reach residual rotor speeds of 3 or 2 rotations per minute (rpm) was respectively 32.2 or 38.8 s on average. Based on this data, Eoldist allows the user to select a species from the database, wind turbine characteristics, and a residual rotor speed (3 or 2 rpm); it then calculates the time to reach the selected threshold and provides a distribution curve for the cautionary detection distance needed to prevent collision. This article includes examples of cautionary detection distances required for several species to demonstrate the sensitivity of key input parameters. Eoldist is freely available and should help the wind energy industry, ADS suppliers, and environmental agencies to define requirements for ADS bird detection that are compatible with the biology of the target species.

Aim: Large-scale space use and geographical ranges of animal populations are central topics in ecology. Whereas they are traditionally often based on citizen science or professional sightings of (marked) animals, recent technological developments have presented GPS tracking as an alternative method for inferring space use at the population level. Tracking devices are however much more expensive than traditional marks, rings or collars, leading to datasets that typically consist of much fewer individuals. We study how GPS tracking data and citizen science resighting data of marked individuals compare as alternative sources for inferring range size. Location: Northwestern Europe. Taxon: Bewick's swan (Cygnus columbianus bewickii). Methods: We calculated Bewick's swan range sizes from a wealth of GPS tracking and resighting data during winter, the period of the year when both data types are abundant. We examined the effect of the number of individuals and the total number of spatial records (either resightings or GPS fixes) on the inferred range size. Moreover, we combined GPS tracks with resightings of the same individuals to empirically determine spatial variation in resighting rates. Results: Tracked individuals generated records across an area 1.5–2 times larger than individuals that were merely resighted. Moreover, any given number of daily GPS records (rather than GPS-tracked individuals) yielded an area 1.5 times larger than that same number of resighting records. A small number of GPS-tracked individuals (~20) was sufficient to yield a larger range size compared to much higher numbers of resighted individuals (well over 400). Spatial variation in resighting rates corresponded well with the differences in range size from the two data types, indicating that spatial gaps in observer effort can hamper range estimations. Main Conclusions: When combined with resighting data, tracking data can be used to indicate areas of low observer effort. Although citizen science resightings are essential for collecting various types of biological information, we show that GPS tracking presents a highly efficient alternative to traditional marking for assessing large-scale space use and population ranges, requiring far fewer individuals to be used.

Background: GPS-transmitters enable detailed study of animal behaviour but may impact the animals. Impacts vary from short-term stress and habituation to longer-term effects on e.g., migration and reproduction. To study impacts, ideally, true controls (i.e., uncaptured or untagged animals) are used, but unbiased assessments of their migration timing and breeding performance are challenging, especially in remote areas. Alternatively, quasi-controls can be used: individuals tagged longer ago, or the same tagged individuals but in later years. Quasi-controls reveal tagging effects that differ between the first and following years. Results: We captured Pink-footed geese (Anser brachyrhynchus) in spring and summer and deployed GPS-transmitter neckbands. In spring, geese were caught with cannon or clap nets on stopovers in Norway and Finland, 2 weeks before departure to breeding areas in Svalbard and Novaya Zemlya. In summer, geese were rounded up during wing moult in Svalbard. First, we compared geese tagged recently in spring with geese tagged in spring or summer 1–4 years prior. Newly tagged geese migrated significantly later, by 2 days, than previously tagged geese, both at departure from the spring stopover and arrival to the breeding grounds, while migration duration did not differ. Breeding propensity and laying date did not differ, but nesting success tended to be lowered, resulting in a significantly lower annual probability to produce hatchlings in recently tagged geese than in previously tagged geese. Second, within individuals tagged in spring, spring migration advanced in their next year, suggesting delay in their first spring. This was likely not an ageing effect, as geese tagged in summer showed no advancing spring migration timing over the years. Third, in Svalbard, observed brood sizes of geese tagged in summer and untagged geese did not differ 1 year after tagging. Conclusions: The capture and GPS-tagging of geese 2 weeks before spring departure delayed their spring migration and lowered their probability to produce hatchlings in that year. These effects lasted longer than previously reported week-long effects of GPS-tagging on time budgets in summer and of neck-banding on spring body condition. Additional study is needed to evaluate longer-term or permanent effects which remain undetected with quasi-controls.

Intermittent breeding is an important tactic in long-lived species that trade off survival and reproduction to maximize lifetime reproductive success. When breeding conditions are unfavourable, individuals are expected to skip reproduction to ensure their own survival. Breeding propensity (i.e. the probability for a mature female to breed in a given year) is an essential parameter in determining reproductive output and population dynamics, but is not often studied in birds because it is difficult to obtain unbiased estimates. Breeding conditions are especially variable at high latitudes, potentially resulting in a large effect on breeding propensity of Arctic-breeding migratory birds, such as geese. With a novel approach, we used GPS-tracking data to determine nest locations, breeding propensity and nesting success of barnacle geese, and studied how these varied with breeding latitude and timing of arrival on the breeding grounds relative to local onset of spring. Onset of spring at the breeding grounds was a better predictor of breeding propensity and nesting success than relative timing of arrival. At Arctic latitudes (>66° N), breeding propensity decreased from 0.89 (95% CI: 0.65–0.97) in early springs to 0.22 (95% CI: 0.06–0.55) in late springs, while at temperate latitudes, it varied between 0.75 (95% CI: 0.38–0.93) and 0.89 (95% CI: 0.41–0.99) regardless of spring phenology. Nesting success followed a similar pattern and was lower in later springs at Arctic latitudes, but not at temperate latitudes. In early springs, a larger proportion of geese started breeding despite arriving late relative to the onset of spring, possibly because the early spring enabled them to use local resources to fuel egg laying and incubation. While earlier springs due to climate warming are considered to have mostly negative repercussions on reproductive success through phenological mismatches, our results suggest that these effects may partly be offset by higher breeding propensity and nesting success.

The Russian breeding population of barnacle geese Branta leucopsis has shown a rapid increase in numbers since 1980, which has coincided with a southwest-wards breeding range expansion within the Russian Arctic. Here barnacle geese also started to occupy coastal and marsh land habitats, in which they were not know to nest on their traditional breeding grounds. While these changes have been well documented by studies and observations throughout the new breeding range of barnacle geese, observations are lacking from the traditional breeding grounds on Novaya Zemlya, as this area is remote and difficult to access. This is especially relevant given rapid climate warming in this area, which may impact local distribution and population size. We used GPS-tracking and behavioural biologging data from 46 individual barnacle geese captured on their wintering grounds to locate nest sites in the Russian Arctic and study nesting distribution in 2008–2010 and 2018–2020. Extrapolating from nest counts on Kolguev Island, we estimate the breeding population on Novaya Zemlya in 2018–2020 to range around 75,250 pairs although the confidence interval around this estimate was large. A comparison with the historical size of the barnacle goose population suggests an increase in the breeding population on Novaya Zemlya, corresponding with changes in other areas of the breeding range. Our results show that many barnacle geese on Novaya Zemlya currently nest on lowland tundra on Gusinaya Zemlya Peninsula. This region has been occupied by barnacle geese only since 1990 and appears to be mainly available for nesting in years with early spring. Tracking data are a valuable tool to increase our knowledge of remote locations, but counts of breeding individuals or nests are needed to further corroborate estimates of breeding populations based on tracking data.