Biology subjects

Safi, K.

Publications and source records attributed to Safi, K..

25 records · Page 2Linked to original sources

bioRxiv2021

The species-specificity of energy landscapes for soaring birds, and its consequences for transferring suitability models across species

O_LISoaring birds use the energy available in the environment in the form of atmospheric uplifts, to subsidize their flight. Their dependence on soaring opportunities makes them extremely sensitive to anthropogenic wind energy development. Predictive modelling is now considered instrumental to forecast the impact of wind farms on single species of concern. However, as multiple species often coexist in the same area, there is clear need to overcome the limitations of single species approaches. C_LIO_LIWe looked for converging patterns in the way two obligate soaring species use the energy available in the landscape to soar, using movement data from 57 white storks, Ciconia ciconia, and 27 griffon vultures, Gyps fulvus. We first compared the soaring efficiency of the two species. We then tested the accuracy of topographic features, important correlates of collision risk in soaring birds, in predicting their soaring behaviour. We finally tested the transferability of soaring suitability models across species. C_LIO_LITopography alone can predict and map the soaring opportunities available to storks across Europe, but not as efficiently in vultures. Only 20.5% of the study area was suitable to both species to soar, suggesting the existence of species-specific requirements in the use of the landscape for soaring. Storks relied on uplift occurrence while vultures on uplift quality, needing stronger uplifts to support their higher body mass and wing loading. C_LIO_LISynthesis and applications: Our results indicate that the flight of highly specialized soaring species is more dependent on atmospheric conditions than on static features, and that more knowledge is required to accurately predict their behaviour. Despite the superficially similar soaring behaviour, the two species have different environmental requirements, suggesting that energy landscapes are species-specific. Our models provide a base to explore the effects that changes in the landscape have on the flight behaviour of different soaring species and suggest that there is no reliable and responsible way to shortcut risk assessment in areas where multiple species might be at risk by anthropogenic structures. C_LI

ecology↗

bioRxiv2020

Sea-crossing along migratory flyways is limited more strongly by wind than by lack of uplift

Flying over the open sea is energetically costly for terrestrial birds. Despite this, over-water journeys of many birds, sometimes hundreds of kilometers long, are uncovered by bio-logging technology. To understand how these birds afford their flights over the open sea, we investigated the role of atmospheric conditions, specifically wind and uplift, in subsidizing over-water flight at the global scale. We first established that {Delta}T, the temperature difference between sea surface and air, is a meaningful proxy for uplift over water. Using this proxy, we showed that the spatio-temporal patterns of sea-crossing in terrestrial migratory birds is associated with favorable uplift conditions. We then analyzed route selection over the open sea for five facultative soaring species, representing all major migratory flyways. The birds maximized wind support when selecting their sea-crossing routes and selected higher uplift when suitable wind support was available. They also preferred routes with low long-term uncertainty in wind conditions. Our findings suggest that, in addition to wind, uplift may play a key role in the energy seascape for bird migration that in turn determines strategies and associated costs for birds crossing ecological barriers such as the open sea.

animal behavior and cognition↗

bioRxiv2020

Wing tags severely impair movement in African Cape Vulture

BackgroundThe use of tracking technologies is key for the study of animal movement and pivotal to ecological and conservation research. However, the potential effects of devices attached to animals are sometimes neglected. The impact of tagging not only rises welfare concerns, but can also bias the data collected, causing misinterpretation of the observed behaviour which invalidates the comparability of information across individuals and populations. Patagial (wing) tags have been extensively used as a marking method for visual resightings in endangered vulture species, but their effect on the aerodynamics of the birds and their flight behaviour is yet to be investigated. Using GPS backpack mounted devices, we compared the flight performance of 27 captive and wild Cape Vultures (Gyps coprotheres), marked with either patagial tags or coloured leg bands. ResultsIndividuals equipped with patagial tags were less likely to fly, travelled shorter distances and flew slower compared to individuals equipped with leg bands. These effects were also observed in one individual that recovered its flight performance after replacing its patagial tag by a leg band. ConclusionsAlthough we did not measure the effects of patagial tags on body condition or survival, our study strongly suggests that they have severe adverse effects on vultures flight behaviour and emphasises the importance of investigating the effects that tagging methods can have on the behaviour and conservation of the study species, as well as on the quality of the scientific results.

animal behavior and cognition↗

bioRxiv2020

A comprehensive framework for handling location error in animal tracking data

Animal tracking data are being collected more frequently, in greater detail, and on smaller taxa than ever before. These data hold the promise to increase the relevance of animal movement for understanding ecological processes, but this potential will only be fully realized if their accompanying location error is properly addressed. Historically, coarsely-sampled movement data have proved invaluable for understanding large scale processes (e.g., home range, habitat selection, etc.), but modern fine-scale data promise to unlock far more ecological information. While GPS location error can often be ignored in coarsely sampled data, fine-scale data require more care, and tools to do this have not kept pace. Current approaches to dealing with location error largely fall into two categories--either discarding the least accurate location estimates prior to analysis or simultaneously fitting movement and error parameters in a hidden-state model. In some cases these approaches can provide a level of correction, but they have known limitations, and in some cases they can be worse than doing nothing. Here, we provide a general framework to account for location error in the analysis of triangulated and trilatcralizcd animal tracking data, which includes GPS, Argos Doppler-shift, triangulated VHF, trilatcralized acoustic and cellular location data. We apply our error-modelselection framework to 190 GPS, cellular, and acoustic devices representing 27 models from 14 manufacturers. Collectively, these devices were used to track a wide range of taxa comprising birds, fish, reptiles, and mammals of different sizes and with different behaviors, in urban, suburban, and wild settings. In almost half of the tested device models, error-model selection was necessary to obtain the best performing error model, and in almost a quarter of tested device models, the reported DOP values were actually misinformative. Then, using empirical tracking data from multiple species, we provide an overview of modern, error-informed movement analyses, including continuous-time path reconstruction, home-range distribution, home-range overlap, speed, and distance estimation. Adding to these techniques, we introduce new error-informed estimators for outlier detection and autocorrelation visualization. Because error-induced biases depend on many factors--sampling schedule, movement characteristics, tracking device, habitat, etc.--differential bias can easily confound biological inference and lead researchers to draw false conclusions. We demonstrate how error-informed analyses on calibrated tracking data can provide more accurate estimates are that are insensitive to location error, and allow researchers to use all of their data.

ecology↗

bioRxiv2019

The challenges of estimating the distribution of flight heights from telemetry or altimetry data

BackgroundGlobal positioning systems (GPS) and altimeters are increasingly used to monitor vertical space use by aerial species, a key aspect of their niche that we need to know to understand their ecology and conservation needs, and to manage our own use of the airspace. However, there are various sources of error in flight height data (\"height\" above ground, as opposed to \"altitude\" above a reference like the sea level): vertical error from the devices themselves, error in the ground elevation below the tracked animals, and error in the horizontal position of the animals and thus the predicted ground elevation below them.\n\nMethodsWe used controlled field trials, simulations, and the reanalysis of raptor case studies with state-space models to illustrate the effect of improper error management.\n\nResultsErrors of a magnitude of 20 meters appear in benign conditions (expected to be larger in more challenging context). These errors distort the shape of the distribution of flight heights, inflate the variance in flight height, bias behavioural state assignments, correlations with environmental covariates, and airspace management recommendations. Improper data filters such as removing all negative recorded flight height records introduce several biases in the remaining dataset, and preclude the opportunity to leverage unambiguous errors to help with model fitting. Analyses that ignore the variance around the mean flight height, e.g., those based on linear models of flight height, and those that ignore the variance inflation caused by telemetry errors, lead to incorrect inferences.\n\nConclusionThe state-space modelling framework, now in widespread use by ecologists and increasingly often automatically implemented within on-board GPS data processing algorithms, makes it possible to fit flight models directly to raw flight height records, with minimal data pre-selection, and to analyse the full distribution of flight heights, not just the mean. In addition to basic research about aerial niches, behaviour quantification, and environmental interactions, we highlight the applied relevance of our recommendations for airspace management and the conservation of aerial wildlife.

ecology↗

bioRxiv2019

Age-specific migration timing affects the energy seascape over an ecological barrier

Thermal soaring birds extract energy from the atmosphere to achieve energetically low-cost movement. When encountering regions that are energetically costly to fly over, such as open seas, they attempt to adjust the spatio-temporal pattern of their passage to maximize energy extraction from the atmosphere over these ecological barriers. We apply the concept of energy landscapes to investigate the spatio-temporal dynamics of energy availability over the open sea for soaring flight. We specifically investigated how the \"energy seascape\" may shape age-specific sea-crossing behaviour of European honey buzzards Pernis apivorus over the Mediterranean Sea in autumn. We found uplift potential over the sea to be the main determinant of sea-crossing length, rather than wind conditions. Considering this variable as a proxy for available energy over the sea, we constructed the energy seascape for the autumn migration season using forty years of temperature data. Our results indicate that early-migrating adult buzzards are likely to encounter adverse energy subsidence over the Mediterranean, whereas late-migrating juveniles face less adverse flight conditions, and even conditions conducive to soaring flight. Our study provides evidence that the dynamics of the energy landscape can explain intra-specific variation in migratory behaviour also at sea.

ecology↗

bioRxiv2017

Integrating animal movement with habitat suitability for estimating dynamic landscape connectivity

ContextHigh-resolution animal movement data are becoming increasingly available, yet having a multitude of empirical trajectories alone does not allow us to easily predict animal movement. To answer ecological and evolutionary questions at a population level, quantitative estimates of a species potential to link patches or populations are of importance.\n\nObjectivesWe introduce an approach that combines movement-informed simulated trajectories with an environment-informed estimate of the trajectories plausibility to derive connectivity. Using the example of bar-headed geese we estimated migratory connectivity at a landscape level throughout the annual cycle in their native range.\n\nMethodsWe used tracking data of bar-headed geese to develop a multi-state movement model and to estimate temporally explicit habitat suitability within the species range. We simulated migratory movements between range fragments, and calculated a measure we called route viability. The results are compared to expectations derived from published literature.\n\nResultsSimulated migrations matched empirical trajectories in key characteristics such as stopover duration. The viability of the simulated trajectories was similar to that of the empirical trajectories. We found that, overall, the migratory connectivity was higher within the breeding than in wintering areas, corresponding to previous findings for this species.\n\nConclusionsWe show how empirical tracking data and environmental information can be fused for meaningful predictions of animal movements throughout the year and even outside the spatial range of the available data. Beyond predicting connectivity, our framework will prove useful for modelling ecological processes facilitated by animal movement, such as seed dispersal or disease ecology.

ecology↗