Frequency-dependent tolerance to aircraft disturbance drastically alters predicted impact on shorebirds

Anthropogenic disturbance of wildlife is increasing globally. Generalizing impacts of disturbance to novel situations is challenging, as the tolerance of animals to human activities varies with disturbance frequency (e.g. due to habituation). Few studies have quantified frequency-dependent tolerance, let alone determined how it affects predictions of disturbance impacts when these are extrapolated over large areas. In a comparative study across a gradient of air traffic intensities, we show that birds nearly always fled (80%) if aircraft were rare, while birds rarely responded (7%) if traffic was frequent. When extrapolating site-specific responses to an entire region, accounting for frequency-dependent tolerance dramatically alters the predicted costs of disturbance: the disturbance map homogenizes with fewer hotspots. Quantifying frequency-dependent tolerance has proven challenging, but we propose that (i) ignoring it causes extrapolations of disturbance impacts from single sites to be unreliable, and (ii) it can reconcile published idiosyncratic species- or source-specific disturbance responses.

Using DNA barcoding and field surveys to guide wildlife management at Nanjing Lukou International Airport, China

The conflicts between wildlife and aircraft have increased due to the development of the aviation industry. While many studies have quantified the relative hazards of wildlife to aircraft, few studies have combined DNA barcoding techniques with field surveys of bird communities in different habitats to reveal the exact species involved in bird strikes and how the habitat heterogeneity around airports affects bird communities and even the occurrence of bird strikes. Taking Nanjing Lukou International Airport in China as an example, based on the DNA barcoding technology and detailed field research, we establish the most commonly struck species, which can help managers identify the level of hazard and lead to meaningful reductions in hazards and costs associated with bird strike. The investigation of bird communities showed that there were 149 bird species recorded within an 8 km radius. There were 89, 88, 61, and 88 species in the woodland, wetland, farmland, and urban area, respectively. In total, 303 samples identified 82 species representing 13 orders and 32 family of birds from bird strike cases, of which 24 species were not found in the field survey. Passeriformes were the most common order of birds identified, with 43 species represented in 167 identifications. Skylark, Thrush, Shrike, Lapwing, and Swallow were most likely to cause damage or substantial damage to aircraft when strikes occurred. In addition to birds, we identified 69 bats individuals (accounting for 22.77%) using DNA barcoding. The Bray-Curtis similarity analysis revealed that species involved in bird strike had the highest similarity with urban area. Our findings suggest that policymakers should pay more attention to managing the wetlands and urban areas surrounding the airport. These findings imply that DNA barcoding can add to the environmental monitoring in airports, which can facilitate hazard management and improve air safety.

Can we use antipredator behavior theory to predict wildlife responses to high-speed vehicles?

Animals seem to rely on antipredator behavior to avoid vehicle collisions. There is an extensive body of antipredator behavior theory that have been used to predict the distance/time animals should escape from predators. These models have also been used to guide empirical research on escape behavior from vehicles. However, little is known as to whether antipredator behavior models are appropriate to apply to an approaching high-speed vehicle scenario. We addressed this gap by (a) providing an overview of the main hypotheses and predictions of different antipredator behavior models via a literature review, (b) exploring whether these models can generate quantitative predictions on escape distance when parameterized with empirical data from the literature, and (c) evaluating their sensitivity to vehicle approach speed using a simulation approach wherein we assessed model performance based on changes in effect size with variations in the slope of the flight initiation distance (FID) vs. approach speed relationship. The slope of the FID vs. approach speed relationship was then related back to three different behavioral rules animals may rely on to avoid approaching threats: the spatial, temporal, or delayed margin of safety. We used literature on birds for goals (b) and (c). Our review considered the following eight models: the economic escape model, Blumstein's economic escape model, the optimal escape model, the perceptual limit hypothesis, the visual cue model, the flush early and avoid the rush (FEAR) hypothesis, the looming stimulus hypothesis, and the Bayesian model of escape behavior. We were able to generate quantitative predictions about escape distance with the last five models. However, we were only able to assess sensitivity to vehicle approach speed for the last three models. The FEAR hypothesis is most sensitive to high-speed vehicles when the species follows the spatial (FID remains constant as speed increases) and the temporal margin of safety (FID increases with an increase in speed) rules of escape. The looming stimulus effect hypothesis reached small to intermediate levels of sensitivity to high-speed vehicles when a species follows the delayed margin of safety (FID decreases with an increase in speed). The Bayesian optimal escape model reached intermediate levels of sensitivity to approach speed across all escape rules (spatial, temporal, delayed margins of safety) but only for larger (> 1 kg) species, but was not sensitive to speed for smaller species. Overall, no single antipredator behavior model could characterize all different types of escape responses relative to vehicle approach speed but some models showed some levels of sensitivity for certain rules of escape behavior. We derive some applied applications of our findings by suggesting the estimation of critical vehicle approach speeds for managing populations that are especially susceptible to road mortality. Overall, we recommend that new escape behavior models specifically tailored to high-speeds vehicles should be developed to better predict quantitatively the responses of animals to an increase in the frequency of cars, airplanes, drones, etc. they will face in the next decade.

Responses of turkey vultures to unmanned aircraft systems vary by platform

A challenge that conservation practitioners face is manipulating behavior of nuisance species. The turkey vulture (Cathartes aura) can cause substantial damage to aircraft if struck. The goal of this study was to assess vulture responses to unmanned aircraft systems (UAS) for use as a possible dispersal tool. Our treatments included three platforms (fixed-wing, multirotor, and a predator-like ornithopter [powered by flapping flight]) and two approach types (30 m overhead or targeted towards a vulture) in an operational context. We evaluated perceived risk as probability of reaction, reaction time, flight-initiation distance (FID), vulture remaining index, and latency to return. Vultures escaped sooner in response to the fixed-wing; however, fewer remained after multirotor treatments. Targeted approaches were perceived as riskier than overhead. Vulture perceived risk was enhanced by flying the multirotor in a targeted approach. We found no effect of our treatments on FID or latency to return. Latency was negatively correlated with UAS speed, perhaps because slower UAS spent more time over the area. Greatest visual saliency followed as: ornithopter, fixed-wing, and multirotor. Despite its appearance, the ornithopter was not effective at dispersing vultures. Because effectiveness varied, multirotor/fixed-wing UAS use should be informed by management goals (immediate dispersal versus latency).

Combining Tracking and Remote Sensing to Identify Critical Year-Round Site, Habitat Use and Migratory Connectivity of a Threatened Waterbird Species

We tracked 39 western flyway white-naped cranes (Antigone vipio) throughout multiple annual cycles from June 2017 to July 2020, using GSM-GPS loggers providing positions every 10-min to describe migration routes and key staging areas used between their Mongolian breeding and wintering areas in China’s Yangtze River Basin. The results demonstrated that white-naped cranes migrated an average of 2556 km (±187.9 SD) in autumn and 2673 km (±342.3) in spring. We identified 86 critical stopover sites that supported individuals for more than 14 days, within a 100–800 km wide migratory corridor. This study also confirmed that Luan River catchment is the most important staging region, where white-naped cranes spent 18% of the annual cycle (in both spring and autumn) each year. Throughout the annual cycle, 69% of the tracking locations were from outside of the currently protected areas, while none of the critical staging areas enjoyed any form of site protection. We see further future potential to combine avian tracking data and remote-sensing information throughout the annual range of the white-naped crane to restore it and other such species to a more favourable conservation status.

Social information affects Canada goose alert and escape responses to vehicle approach: implications for animal-vehicle collisions

BACKGROUND

Animal-vehicle collisions represent substantial sources of mortality for a variety of taxa and can pose hazards to property and human health. But there is comparatively little information available on escape responses by free-ranging animals to vehicle approach versus predators/humans.

METHODS

We examined responses (alert distance and flight-initiation distance) of focal Canada geese (Branta canadensis maxima) to vehicle approach (15.6 m·s-1) in a semi-natural setting and given full opportunity to escape. We manipulated the direction of the vehicle approach (direct versus tangential) and availability of social information about the vehicle approach (companion group visually exposed or not to the vehicle).

RESULTS

We found that both categorical factors interacted to affect alert and escape behaviors. Focal geese used mostly personal information to become alert to the vehicle under high risk scenarios (direct approach), but they combined personal and social information to become alert in low risk scenarios (tangential approach). Additionally, when social information was not available from the companion group, focal birds escaped at greater distances under direct compared to tangential approaches. However, when the companion group could see the vehicle approaching, focal birds escaped at similar distances irrespective of vehicle direction. Finally, geese showed a greater tendency to take flight when the vehicle approached directly, as opposed to a side step or walking away from the vehicle.

CONCLUSIONS

We suggest that the perception of risk to vehicle approach (likely versus unlikely collision) is weighted by the availability of social information in the group; a phenomenon not described before in the context of animal-vehicle interactions. Notably, when social information is available, the effects of heightened risk associated with a direct approach might be reduced, leading to the animal delaying the escape, which could ultimately increase the chances of a collision. Also, information on a priori escape distances required for surviving a vehicle approach (based on species behavior and vehicle approach speeds) can inform planning, such as location of designated cover or safe areas. Future studies should assess how information from vehicle approach flows within a flock, including aspects of vehicle speed and size, metrics that affect escape decision-making.