Faites connaître cette offre !
Reference : UMR5175-OLIDUR-001
Workplace : MONTPELLIER
Date of publication : Tuesday, July 21, 2020
Type of Contract : FTC Technical / Administrative
Contract Period : 12 months
Expected date of employment : 1 October 2020
Proportion of work : Full time
Remuneration : between 2 643,22€ and 3047,48€
Desired level of education : 5-year university degree
Experience required : Indifferent
The environmental impact on birds in operating wind farms is mainly concentrated around mortality due to collision with turbine blades or masts (Köppel 2017). Within the framework of environmental protection policies, wind farm operators have an obligation to reduce these impacts, especially when they affect protected species. To comply with these regulatory requirements, wind farm operators generally rely on automated bird detection devices in the vicinity of the wind farm to reduce the risk of collisions. These systems all rely on remote detection of birds in flight, and thus on the identification of "targets" moving at varying speeds. Target detection technologies can be based on radar, optical or thermal camera systems (Tomé et al. 2017, McClure et al. 2018). Once a target is detected and its trajectory is analysed by the system, several types of actions can be triggered: (1) scaring (using auditory stimuli) to alter the individual's trajectory and move him away from the turbines, or (2) slowing down/stopping the turbines to minimize the risk of collision, or (3) doing nothing. The effectiveness of the system is based on a combination of the bird's detection distance, its speed of movement, and the speed of rotation of the turbines. Thus, the farther the bird is detected, and the slower it moves, the longer it will take to make an appropriate decision to avoid a collision.
The flight characteristics of many bird species remain unknown (Pennycuick 2008). Flight speed is primarily conditioned by the morphology of the species (wing shape and wing loading) and its type of flight: flapping, intermittent, gliding. Flight speed can then vary between individuals according to their physiological state (body condition, reproductive status) or the context and motivation (migration, reproduction period) which can lead the individual to accelerate or slow down in relation to the optimal speed, by modifying the shape of its wings or the inclination of its body. Finally, the environmental conditions of air density and wind will also affect the speed of flight relative to the ground (a bird with the wind at its back will go faster than a bird with a headwind) (Safi et al. 2013).
Designers of mortality reduction systems are seeking to define efficient algorithms based on known flight speeds for each species, or group of species, and for each context, in order to better analyse the bird's trajectory (sinuous or straight) and estimate the probability that the target is heading towards the turbine. However, this is hampered by the relative confusion about the measured and available flight speeds for some species (see above), or the lack of data for many other species. Generally speaking, a recent and updated synthesis of these flight speeds for a maximum of species is a crucial element currently missing. For example, the flight speeds of many species have been measured only by radar or theodolite during migratory flights under particular conditions, channelling large numbers of birds such as at mountain passes, straits, or over the sea (Spaar and Bruderer 1997, Pennycuick et al. 2013, Nilsson et al. 2014). These conditions are not necessarily representative of flying conditions in less constrained environmental contexts, or outside the migration period, and where wind farms are installed. The advent of satellite telemetry from GPS receivers placed on the birds makes it possible to monitor an increasing number of bird species by measuring the instantaneous flight speed in relation to the ground, in addition to the geographical position in three dimensions, without observer bias, throughout the year and can therefore concern local flights, parade flights, and migratory flights for the same individual and be associated with precise measurements of its biometry during capture (sex, age, body condition index etc.) (Bridge et al. 2011).
This position is part of the MAPE project (Avian Mortality in Wind Parks) developed through collaboration between park operators, environmental NGOs, the State (DREAL Occitanie), the OFB, the Occitanie region, ADEME and academic research (CEFE-CNRS and labex CEMEB) and led by the Maison des Sciences de l'Homme de Montpellier. In the framework of the MAPE project, the aim of this work package is to better describe the flight speeds of birds, for a large number of species and in various environmental contexts, to meet the needs of designers of mortality reduction devices, in order to improve future devices. It also aims to better assess the adequacy between flight speeds, detection distances of current devices and the stopping speed of wind turbines. It will be divided into three areas:
1. Creation of a database on flight speeds, complementing the existing biometric and morphometric databases.
a. Exhaustive bibliographical research to document the flight speeds of as many species as possible, in as many contexts and environmental conditions as possible. Possible collaboration with other European experts working on bird flight (Anders Hedenström and Suzane Akesson from Lund University, Sweden; Felix Liechti from the Sempach Biological Station, Switzerland; Judy Shamoun-Baranes and Adrian Dokter from the University of Amsterdam, Netherlands). The focus will be primarily on European terrestrial and marine avifauna, but may include species from other continents in order to generalize the results.
b. Complement this database with new data from GPS telemetry. Thanks to the Movebank database, new telemetry data will be analysed on species for which flight speeds have not yet been published. Possible collaboration with Martin Wikelski, Max Planck Institute of Animal Behaviour (Germany).
c. From this database, it will be possible to update and extend the scope of the allometric and phylogenetic relationship of Alerstam et al (2007) allowing the prediction of flight speeds and even the sinuosity of trajectories.
2. Collecting information on the rotational speed characteristics of wind turbines and their downtime. This step will be carried out in collaboration with turbine engineers, designing the turbines. Indeed, some developers announce a total stop of the blades between 10 and 90 seconds ...
a. Simulation of the minimum detection distances required for a complete stop of the wind turbines as a function of (1) the size of birds belonging to several taxonomic groups of conservation concern, (2) the flight speed and sinuosity of trajectories as a function of the biological and environmental context, (3) the rotation speed of the turbines.
- Doctor in ecology and/or animal behaviour with recognised skills in ornithology and movement ecology.
- Good programming skills (R and QGIS) to analyze trajectories from GPS data.
- Motivation for operational and partnership research with multiple actors.
- Location: UMR5175 Centre d'Ecologie Fonctionnelle et Evolutive - Montpellier; within the Mouvement, Abondance, Distribution (MAD) team, under the supervision of Olivier Duriez, in collaboration with Aurélien Besnard
Constraints and risks
no risk, dataa analysis
) -Send cover letter and CV via the empploi portal.
Successful candidates will be auditioned in September 2020, for a position starting in October 2020.
We talk about it on Twitter!