On Friday you will have the opportunity to participate one of the workshops which are described in more detail below. Please inform Wouter Vansteelant which two workshops you would be most interested to participate in before June 26th.

1. Analysis of geolocation data (Felix Liechti)

Geolocation today is identical with “Geo-positioning by light level data”. The use of geolocators have increase dramatically within only a few years. They are relatively cheap and very light-weight (0.5g). In contrast to the simple principle of light-level geolocation the analysis of the data is not simple at all. We will go through different analyses steps and will also have a look on the analyses presented in recent papers.

Recommended reading:

  • Bridge, E. S., Kelly, J. F., Contina, A., Gabrielson, R. M., MacCurdy, R. B. and Winkler, D. W. 2013. Advances in tracking small migratory birds: a technical review of light-level geolocation. - J. Field Ornithol. 84: 121-137.
  • Liechti, F., Scandolara, C., Rubolini, D., Ambrosini, R., Korner-Nievergelt, F., Hahn, S., Lardelli, R., Romano, M., Caprioli, M., Romano, A., Sicurella, B. and Saino, N. 2014. Timing of migration and residence areas during the non-breeding period of barn swallows Hirundo rustica in relation to sex and population. - J. Avian Biol. n/a.
  • Lisovski, S., Hewson, C. M., Klaassen, R. H. G., Korner-Nievergelt, F., Kristensen, M. W. and Hahn, S. 2012. Geolocation by light: accuracy and precision affected by environmental factors. - Methods Ecol Evol 3: 603-612.
  • Streby, H., Kramer, G., Peterson, S., Lehman, J., Buehler, D. and Andersen, D. Tornadic Storm Avoidance Behavior in Breeding Songbirds. - Current Biology 25: 98-102

2. Visualizing tracking data and telling stories with CartoDB (Peter Desmet)

Tracking data are beautiful! Want to tell the stories in your data in a compelling way? CartoDB - a tool to analyse and visualize geospatial data online - allows you to do so, in your browser. In this workshop you'll learn how to upload data to CartoDB, how to make use of the underlying PostgreSQL + PostGIS database, how to alter settings like visualization type, colour, css, basemap, and annotation elements, and how to share your visualization with the world. Want to get a preview of how tracking data can look like? Check out the CartoDB profile page of LifeWatch INBO at https://inbo.cartodb.com/u/lifewatch.

The workshop tutorial is available at: https://github.com/LifeWatchINBO/bird-tracking/blob/master/cartodb/scge/README.md

3. Annotating movement and weather data at multiple scales (Wouter Vansteelant)

Animals travelling through water and air must correct for the influence of the currents through which they travel while they are on the move. Fortunately, the ever increasing availability of global weather and environment data, in combination with animal tracking technology, makes it increasingly easy to study how animals move through dynamic environments. In this workshop, you will get a basic introduction to online weather data resources in general and the RNCEP package and its functionality in particular. Using Honey Buzzard migration as a case-study, you will become familiar with analysis of weather influences (particularly wind effects) on movement. Finally, we will have a group discussion in order to identify best-practices for integrating weather and movement data at multiple scales, depending on research questions, tracking methods, resolution of data.

Recommended reading:

  • Kemp, M. U., van Loon, E.E., Shamoun-Baranes, J. and Bouten, W. 2012. RNCEP: global weather and climate data at your fingertips. Methods in Ecology and Evolution, 3: 65–70. doi: 10.1111/j.2041-210X.2011.00138.x

For those working with light-level geolocation data

  • Drake, A., Rock, C.A., Quinlan, S.P., Martin, M., Green, D.J. 2014. Wind Speed during Migration Influences the Survival, Timing of Breeding, and Productivity of a Neotropical Migrant, Setophaga petechia. PLoS ONE 9(5): e97152. doi:10.1371/journal.pone.0097152

For those working with GPS tracking data or satellite telemetry

  • Vansteelant, W.M.G.; Bouten, W.; Klaassen, R.H.G.; Koks, B.J.; Schlaich, A.E.; van Diermen, J.; van Loon, E. E.; Shamoun-Baranes, J.Z. 2015.Regional and seasonal flight speeds of soaring migrants and the role of weather conditions at hourly and daily scales. Journal of Avian Biology 46: 25–39. doi: 10.1111/jav.00457

4. Annotating and classifying accelerometer data (Willem Bouten)

Accelerometers in animal attached devices provide the opportunity to monitor fine scale body movements and thus behavior of animals. In follow up of the interactive lecture in the morning we will discuss the complete workflow from the aims of your study up to the classification of behavior and the use of these data to answer your ecological questions. With hands-on exercises you will experience annotation based on video footage and some of the opportunities and limitations of machine learning. We will discuss how we “see” behavior in the data and how the computer can recognize this.

Recommended reading:

  • Bom R.A., Bouten W., Piersma T., Oosterbeek K., van Gils J.A. 2014. Optimizing acceleration-based movement ethograms: the use of variable-time versus fixed-time segmentation. Movement Ecology, 2-6. DOI:10.1186/2051-3933-3-6
  • Shamoun-Baranes J., Bom, R., van Loon E.E., Ens K., Oosterbeek B.J. & Bouten W. 2012. From sensor data to animal behaviour: an oystercatcher example. PLoS One, 7(5). e37997

5. Working with Brownian Bridges (Emiel van Loon)

The Brownian-Bridge movement model is increasingly being used to process and analyse animal tracking data. At one end of the ‘analysis spectrum’ the model is used as a statistical interpolator for tracking data while the other end it is used as a null model against which more elaborate movement models are tested. Even though the model is claimed to be simple, considerable skill is required for its correct application and interpretation. We will apply a few variants of the Brownian Bridge movement model to prepared data sets in order demonstrate its use and investigate some properties. There is also room to apply the methods to data that participants may bring themselves.

Recommended reading:

Please contact Lourens Veen if you have any technical problems with the wiki.