Improving estimation of flight altitude in wildlife telemetry studies

Cranes soar on thermal updrafts behind cold fronts as they migrate across the sea

Thermal soaring conditions above the sea have long been assumed absent or too weak for terrestrial migrating birds, forcing obligate soarers to take long detours and avoid sea-crossing, and facultative soarers to cross exclusively by costly flapping flight. Thus, while atmospheric convection does develop at sea and is used by some seabirds, it has been largely ignored in avian migration research. Here, we provide direct evidence for routine thermal soaring over open sea in the common crane, the heaviest facultative soarer known among terrestrial migrating birds. Using high-resolution biologging from 44 cranes tracked across their transcontinental migration over 4 years, we show that soaring performance was no different over sea than over land in mid-latitudes. Sea-soaring occurred predominantly in autumn when large water-air temperature difference followed mid-latitude cyclones. Our findings challenge a fundamental migration research paradigm and suggest that obligate soarers avoid sea-crossing not due to the absence or weakness of thermals but due to their low frequency, for which they cannot compensate with prolonged flapping. Conversely, facultative soarers other than cranes should also be able to use thermals over the sea. Marine cold air outbreaks, imperative to global energy budget and climate, may also be important for bird migration.

Movement ecology of an endangered mesopredator in a mining landscape

BACKGROUND

Efficient movement and energy expenditure are vital for animal survival. Human disturbance can alter animal movement due to changes in resource availability and threats. Some animals can exploit anthropogenic disturbances for more efficient movement, while others face restricted or inefficient movement due to fragmentation of high-resource habitats, and risks associated with disturbed habitats. Mining, a major anthropogenic disturbance, removes natural habitats, introduces new landscape features, and alters resource distribution in the landscape. This study investigates the effect of mining on the movement of an endangered mesopredator, the northern quoll (Dasyurus hallucatus). Using GPS collars and accelerometers, we investigate their habitat selection and energy expenditure in an active mining landscape, to determine the effects of this disturbance on northern quolls.

METHODS

We fit northern quolls with GPS collars and accelerometers during breeding and non-breeding season at an active mine site in the Pilbara region of Western Australia. We investigated broad-scale movement by calculating the movement ranges of quolls using utilisation distributions at the 95% isopleth, and compared habitat types and environmental characteristics within observed movement ranges to the available landscape. We investigated fine-scale movement by quolls with integrated step selection functions, assessing the relative selection strength for each habitat covariate. Finally, we used piecewise structural equation modelling to analyse the influence of each habitat covariate on northern quoll energy expenditure.

RESULTS

At the broad scale, northern quolls predominantly used rugged, rocky habitats, and used mining habitats in proportion to their availability. However, at the fine scale, habitat use varied between breeding and non-breeding seasons. During the breeding season, quolls notably avoided mining habitats, whereas in the non-breeding season, they frequented mining habitats equally to rocky and riparian habitats, albeit at a higher energetic cost.

CONCLUSION

Mining impacts northern quolls by fragmenting favoured rocky habitats, increasing energy expenditure, and potentially impacting breeding dispersal. While mining habitats might offer limited resource opportunities in the non-breeding season, conservation efforts during active mining, including the creation of movement corridors and progressive habitat restoration would likely be useful. However, prioritising the preservation of natural rocky and riparian habitats in mining landscapes is vital for northern quoll conservation.

Behavioral responses to offshore windfarms during migration of a declining shorebird species revealed by GPS-telemetry

EU member countries and the UK are currently installing numerous offshore windfarms (OWFs) in the Baltic and North Seas to achieve decarbonization of their energy systems. OWFs may have adverse effects on birds; however, estimates of collision risks and barrier effects for migratory species are notably lacking, but are essential to inform marine spatial planning. We therefore compiled an international dataset consisting of 259 migration tracks for 143 Global Positioning System-tagged Eurasian curlews (Numenius arquata arquata) from seven European countries recorded over 6 years, to assess individual response behaviors when approaching OWFs in the North and Baltic Seas at two different spatial scales (i.e. up to 3.5 km and up to 30 km distance). Generalized additive mixed models revealed a significant small-scale increase in flight altitudes, which was strongest at 0-500 m from the OWF and which was more pronounced during autumn than during spring, due to higher proportions of time spent migrating at rotor level. Furthermore, four different small-scale integrated step selection models consistently detected horizontal avoidance responses in about 70% of approaching curlews, which was strongest at approximately 450 m from the OWFs. No distinct, large-scale avoidance effects were observed on the horizontal plane, although they could possibly have been confounded by changes in flight altitudes close to land. Overall, 28.8% of the flight tracks crossed OWFs at least once during migration. Flight altitudes within the OWFs overlapped with the rotor level to a high degree in autumn (50%) but to a significantly lesser extent in spring (18.5%). Approximately 15.8% and 5.8% of the entire curlew population were estimated to be at increased risk during autumn and spring migration, respectively. Our data clearly show strong small-scale avoidance responses, which are likely to reduce collision risk, but simultaneously highlight the substantial barrier effect of OWFs for migrating species. Although alterations in flight paths of curlews due to OWFs seem to be moderate with respect to the overall migration route, there is an urgent need to quantify the respective energetic costs, given the massive ongoing construction of OWFs in both sea areas.

Performance of GPS/GPRS tracking devices improves with increased fix interval and is not affected by animal deployment

The use of GPS tracking technologies has revolutionized the study of animal movement providing unprecedentedly detailed information. The characterization of GPS accuracy and precision under different conditions is essential to correctly identify the spatial and temporal resolution at which studies can be conducted. Here, we examined the influence of fix acquisition interval and device deployment on the performance of a new GPS/GSM solar powered device. Horizontal and vertical accuracy and precision of locations were obtained under different GPS fix acquisition intervals (1min, 20 min and 60 min) in a stationary test. The test devices were deployed on pre-fledgling white storks (Ciconia ciconia) and we quantified accuracy and precision after deployment while controlling for bias caused by variation in habitat, topography, and animal movement. We also assessed the performance of GPS-Error, a metric provided by the device, at identifying inaccurate locations (> 10 m). Average horizontal accuracy varied between 3.4 to 6.5 m, and vertical accuracy varied between 4.9 to 9.7 m, in high (1 min) and low frequency (60 min) GPS fix intervals. These values were similar after the deployment on white storks. Over 84% of GPS horizontal positions and 71% of vertical positions had less than 10m error in accuracy. Removing 3% of data with highest GPS-Error eliminated over 99% of inaccurate positions in high GPS frequency intervals, but this metric was not effective in the low frequency intervals. We confirmed the suitability of these devices for studies requiring horizontal and vertical accuracies of 5-10m. For higher accuracy data, intensive GPS fix intervals should be used, but this requires more sophisticated battery management, or larger batteries and devices.

A predictive flight-altitude model for avoiding future conflicts between an emblematic raptor and wind energy development in the Swiss Alps

Deployment of wind energy is proposed as a mechanism to reduce greenhouse gas emissions. Yet, wind energy and large birds, notably soaring raptors, both depend on suitable wind conditions. Conflicts in airspace use may thus arise due to the risks of collisions of birds with the blades of wind turbines. Using locations of GPS-tagged bearded vultures, a rare scavenging raptor reintroduced into the Alps, we built a spatially explicit model to predict potential areas of conflict with future wind turbine deployments in the Swiss Alps. We modelled the probability of bearded vultures flying within or below the rotor-swept zone of wind turbines as a function of wind and environmental conditions, including food supply. Seventy-four per cent of the GPS positions were collected below 200 m above ground level, i.e. where collisions could occur if wind turbines were present. Flight activity at potential risk of collision is concentrated on south-exposed mountainsides, especially in areas where ibex carcasses have a high occurrence probability, with critical areas covering vast expanses throughout the Swiss Alps. Our model provides a spatially explicit decision tool that will guide authorities and energy companies for planning the deployment of wind farms in a proactive manner to reduce risk to emblematic Alpine wildlife.

Classifying behavior from short-interval biologging data: An example with GPS tracking of birds

Recent advances in digital data collection have spurred accumulation of immense quantities of data that have potential to lead to remarkable ecological insight, but that also present analytic challenges. In the case of biologging data from birds, common analytical approaches to classifying movement behaviors are largely inappropriate for these massive data sets.We apply a framework for using K-means clustering to classify bird behavior using points from short time interval GPS tracks. K-means clustering is a well-known and computationally efficient statistical tool that has been used in animal movement studies primarily for clustering segments of consecutive points. To illustrate the utility of our approach, we apply K-means clustering to six focal variables derived from GPS data collected at 1-11 s intervals from free-flying bald eagles (Haliaeetus leucocephalus) throughout the state of Iowa, USA. We illustrate how these data can be used to identify behaviors and life-stage- and age-related variation in behavior.After filtering for data quality, the K-means algorithm identified four clusters in >2 million GPS telemetry data points. These four clusters corresponded to three movement states: ascending, flapping, and gliding flight; and one non-moving state: perching. Mapping these states illustrated how they corresponded tightly to expectations derived from natural history observations; for example, long periods of ascending flight were often followed by long gliding descents, birds alternated between flapping and gliding flight.The K-means clustering approach we applied is both an efficient and effective mechanism to classify and interpret short-interval biologging data to understand movement behaviors. Furthermore, because it can apply to an abundance of very short, irregular, and high-dimensional movement data, it provides insight into small-scale variation in behavior that would not be possible with many other analytical approaches.

Flight altitudes of a soaring bird suggest landfill sites as power line collision hotspots

Anthropogenic structures are increasingly encroaching wildlife habitats, creating conflicts between humans and animals. Scaling up renewable energy requires new infrastructures such as power lines, that cause high mortality among birds since they act as obstacles to flight and are used for perching and nesting, which can result in collisions or electrocutions. These interactions often endanger wildlife populations and may also result in high financial costs for companies. Flight behaviour plays a crucial role in collision risk, and the study of flight altitudes enables us to understand what drives birds to fly at collision risk altitudes. This allows the identification of high-risk areas, conditions and bird behaviours, and the implementation of mitigation measures by power line companies. In this study, we use boosted random tree modelling to identify drivers of white stork (Ciconia ciconia) flight altitudes and to investigate the factors that lead them to fly at collision risk altitudes. We found that the main drivers of flight altitude for this soaring bird species were time of day, distance to the nearest landfill site and cloud cover density. Bird age, habitat type and season were comparatively less important. Collision risk increases during crepuscular hours near landfill sites, also in days with high cloud cover density and during the breeding season. In recent years, hundreds to thousands of storks congregate daily at landfill sites to take advantage of the predictability and superabundance of anthropogenic food waste. Some of these sites have high density of power lines, becoming collision risk hotspots for storks and other landfill users. Despite being susceptible to collision, our results suggest that white storks can avoid power lines to a certain extent, by changing their flight altitude at ca. 80 m from these structures. This study shows that the implementation of mitigation measures for existing power lines should be prioritized in areas in the vicinity of landfill sites within white stork distribution ranges, and the projection of new lines should avoid those areas. These measures would benefit species vulnerable to mortality due to power line collision, and it would also reduce associated power outages and economic costs.

Far eastern curlew and whimbrel prefer flying low - wind support and good visibility appear only secondary factors in determining migratory flight altitude

BACKGROUND

In-flight conditions are hypothesized to influence the timing and success of long-distance migration. Wind assistance and thermal uplift are thought to reduce the energetic costs of flight, humidity, air pressure and temperature may affect the migrants' water balance, and clouds may impede navigation. Recent advances in animal-borne long-distance tracking enable evaluating the importance of these factors in determining animals' flight altitude.

METHODS

Here we determine the effects of wind, humidity, temperature, cloud cover, and altitude (as proxy for climbing costs and air pressure) on flight altitude selection of two long-distance migratory shorebirds, far eastern curlew (Numenius madagascariensis) and whimbrel (Numenius phaeopus). To reveal the predominant drivers of flight altitude selection during migration we compared the atmospheric conditions at the altitude the birds were found flying with conditions elsewhere in the air column using conditional logistic mixed effect models.

RESULTS

Our results demonstrate that despite occasional high-altitude migrations (up to 5550 m above ground level), our study species typically forego flying at high altitudes, limiting climbing costs and potentially alleviating water loss and facilitating navigation. While mainly preferring migrating at low altitude, notably in combination with low air temperature, the birds also preferred flying with wind support to likely reduce flight costs. They avoided clouds, perhaps to help navigation or to reduce the risks from adverse weather.

CONCLUSIONS

We conclude that the primary determinant of avian migrant's flight altitude selection is a preference for low altitude, with wind support as an important secondary factor. Our approach and findings can assist in predicting climate change effects on migration and in mitigating bird strikes with air traffic, wind farms, power lines, and other human-made structures.

High-Resolution Modeling of Uplift Landscapes can Inform Micrositing of Wind Turbines for Soaring Raptors

Collision risk of soaring birds is partly associated with updrafts to which they are attracted. To identify the risk-enhancing landscape features, a micrositing tool was developed to model orographic and thermal updraft velocities from high-resolution remote sensing data. The tool was applied to the island of Hitra, and validated using GPS-tracked white-tailed eagles (Haliaeetus albicilla). Resource selection functions predicted that eagles preferred ridges with high orographic uplift, especially at flight altitudes within the rotor-swept zone (40-110 m). Flight activity was negatively associated with the widely distributed areas with high thermal uplift at lower flight altitudes (<110 m). Both the existing wind-power plant and planned extension are placed at locations rendering maximum orographic updraft velocities around the minimum sink rate for white-tailed eagles (0.75 m/s) but slightly higher thermal updraft velocities. The tool can contribute to improve micrositing of wind turbines to reduce the environmental impacts, especially for soaring raptors.