Browsing by Author "Pinaud, David"

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    Data from: Is pre-breeding prospecting behaviour affected by snow cover in the irruptive snowy owl? A test using state-space modelling and environmental data annotated via Movebank
    (2015-02-27) Therrien, Jean-François; Pinaud, David; Gauthier, Gilles; Lecomte, Nicolas; Bildstein, Keith L.; Bety, Joël
    Background: Tracking individual animals using satellite telemetry has improved our understanding of animal movements considerably. Nonetheless, thorough statistical treatment of Argos datasets is often jeopardized by their coarse temporal resolution. State-space modelling can circumvent some of the inherent limitations of Argos datasets, such as the limited temporal resolution of locations and the lack of information pertaining to the behavioural state of the tracked individuals at each location. We coupled state-space modelling with environmental characterisation of modelled locations on a 3-year Argos dataset of 9 breeding snowy owls to assess whether searching behaviour for breeding sites was affected by snow cover and depth in an arctic predator that shows a lack of breeding site fidelity. Results: The state-space modelling approach allowed the discrimination of two behavioural states (searching and moving) during pre-breeding movements. Tracked snowy owls constantly switched from moving to searching behaviour during pre-breeding movements from mid-March to early June. Searching events were more likely where snow cover and depth was low. This suggests that snowy owls adapt their searching effort to environmental conditions encountered along their path. Conclusions: This modelling technique increases our understanding of movement ecology and behavioural decisions of individual animals both locally and globally according to environmental variables.
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    Data from: Modelling landscape connectivity for greater horseshoe bat using an empirical quantification of resistance
    (2018-07-09) Pinaud, David; Claireau, Fabien; Leuchtmann, Maxime; Kerbiriou, Christian
    (1) Habitat fragmentation and isolation as a result of human activities have been recognized as great threats to population viability. Evaluating landscape connectivity in order to identify and protect linkages has therefore become a key challenge in applied ecology and conservation. (2) One useful approach to evaluate connectivity is Least‐Cost Path (LCP) analysis. However, several studies have highlighted importance of parameterization with empirical, biologically‐relevant proxies of factors affecting movements, as well as the need to validate the LCP model with an independent dataset. (3) We used LCP analysis incorporating quantitative, empirical data about behaviour of the greater horseshoe bat Rhinolophus ferrumequinum to build up a model of functional connectivity in relation to landscape connecting features. We then validated the accumulated costs surface from the LCP model with two independent datasets; one at an individual level with radio tracking data and one at a population level with acoustic data. (4) When defining resistance, we found that the probability of bat presence in a hedgerow is higher when the distance between hedgerows is below 38 m, and decrease rapidly when gaps are larger than 50 m. The LCP model was validated by both datasets: the independent acoustic data showed that the probability of bat presence was significantly higher in areas with lower accumulated costs, and the radio tracking data showed that foraging was more likely in areas where accumulated costs were significantly lower. (5) Synthesis and applications. Through our modelling approach, we recommend a maximum of 38m (and no more than 50m) between connecting features around colonies of greater horseshoe bats. Our quantitative study highlights the value of this framework for conservation: results are directly applicable in the field and the framework can be applied to other species sensitive to habitat loss, including other bats. Provided that it is parameterized with empirical, biologically‐relevant data, this modelling approach can be used for restoring and evaluating green networks in agri‐environmental schemes and management plans.