AniMove Summer School

AniMove courses are focused on the use of remote sensing and animal movement for conservation based on open source software entirely. The combination of animal movement and environmental information in which these movements have been recorded are essential for the field of movement ecology and have often implications for conservation and management. The volume and structure of both sources of data require knowledge on working with spatio-temporal data and the underlying pitfalls such as projections, time zones, autocorrelation etc. represent some of the challenges when working with them. In this course the programming language R will be used to do most data manipulation, visualisation and analysis. The course is centered around on-hands working on own data sets.

The first week is more teaching heavy, to bring all the participants up to the same level, while the second week is focusing on working on the data sets that the participants have brought along to work with. An advanced to very advanced programming skill level in R is required from the participants.

AniMove is a non-profit training initiative run by volunteers of various organisations such as Max Planck Instiute of Animal Behavior, University of Würzburg,  Smithsonian Conservation Institute, and Senckenberg Biodiversity and Climate Research Centre.

Recommended for 
PhD, PostDoc, Professionals

Course Content
Remote sensing, Movement Ecology, Movement analysis, continuous time movement models, Segmentation, GPS logger data manipulation, raster data classification, visualisation of movement and environmental data

Total teaching hours 
(including lectures, seminars and independent work) amounts to 120 hours

AniMove 2022

We are pleased to announce that AniMove 2023 will take place in August at the University of British Columbia, Okanagan Campus, in Canada.

For more information please see the AniMove website


COMING SOON! As part of our AniMove e-learning programme, we recorded this years AniMove lectures. The lectures will be available in February.

Our Lecturers And Affiliations


Anne Scharf is a postdoc in the Animal-Environment Interactions Lab at the Max-Planck Institute of Animal Behavior.
Through the analysis of movement data, she aims to get a better understanding of how animals interact with their environment and are affected by its changes over time. She mostly works with GPS and acceleration data.


Jakob Schwalb-Willmann is a researcher and lecturer at the University of Würzburg with an academic background in Earth observation, spatial data science and Geography. His research focuses on the machine-learning-driven analysis and exploitation of integrated animal movement tracking and remote sensing data for geoanalytical applications. He has extensive experience in using and developing Open Source software tools for the analysis of satellite imagery and geo-spatial data.


Michael Noonan is a quantitative ecologist with more than a decade of research experience across 3 countries and 5 institutions. He leads the Quantitative Ecology Lab at the University of British Columbia, Okanagan, which is focused on the statistically efficient integration of ecological data into evidence-based conservation. The lab’s work is structured around two separate, but complementary, lines of research. The first falls under an umbrella termed ‘Biology or bias’, and is aimed at developing novel statistical methods, understanding when/why different analytical approaches lead to differing conclusions, and how to avoid estimation bias. The over-arching theme of this work is to demonstrate how the use of biased estimators and/or incorrect statistical procedures can generate misinformative results that weaken both ecological theory and evidence-based conservation initiatives. The second focuses on macro-ecology and species conservation by pairing high quality data with cutting edge analytical tools.


Martina Scacco is a postdoc in the Animal-Environment Interactions lab at the Max-Planck Institute of Animal Behavior.
She is particularly interested in how, and to what extent, the environment affects the movement patterns of different species and their cost of transport through the landscape.
Through studying large-scale movements of soaring birds who are dependent on the support of atmospheric uplifts, she is able to compare the interplay of flight behavior, energy expenditure and environment across different species, to evaluate to what extent different morphologies can define their degree of dependence on the landscape and potentially their differential sensitivity to changes in the environment.


Chloe Bracis is a postdoc in the TIMC/MAGe group at Université Grenoble Alpes. She works on modeling a diverse range of biological processes from infectious diseases to animal movement. In movement ecology her research has focused on how animals make decisions about where to move and then carry out these movements, including questions related to cognition, migration, and territoriality, using simulation models across a range of scales and contexts. She has also worked on movement path segmentation and analyzing a trajectory for recursion, or revisits to particular areas.


Thomas Müller studies theoretical and applied aspects of movement- and wildlife ecology, from the behavioral underpinnings and social interactions to ecosystem functions and macro-ecological patterns. He is particularly interested in understanding the interactions between moving animals and their environment and the exceptional challenges that an increasing human footprint poses for movements of wildlife, which ultimately leads to the question of human-wildlife coexistence.


Kamran Safi is a group leader at the Max Planck Institute for Animal Behavior. His research interests lie in understanding the causes and consequences of biological patterns at various scales and from different perspectives, as well as movement ecology, macro-ecology and macro-evolution. In movement ecology. Kami is interested in relating individual animals to the environmental conditions they operate under to learn the causes and consequences of environmental fluctuation on animal movement across scales. Methodologically he combines and fuses data from the wild, using a wide range of sensors deployed on animals, with remote sensing and other sources of information at large spatial and temporal scales.


Inês Silva is a postdoctoral researcher in the Earth System Science group at the Center for Advanced Systems Understanding (CASUS), located in Görlitz, 
Germany. She has a background spanning animal movement, road ecology and community ecology projects in Southeast Asia and South America. She is particularly interested in how animal movement is influenced by anthropogenic impacts, such as animal-road interactions and wildlife-vehicle collisions, study design and facilitating the uptake of new methods in movement ecology.


Christen Fleming develops statistical models and software for animal tracking data and is the lead developer of the continuous-time movement modeling (ctmm) R package. He is an Associate Research Scientist with the University of Maryland and a Research Associate with the Smithsonian Conservation Biology Institute. He obtained his doctorate in physics from the University of Maryland and his baccalaureate in physics, mathematics and statistics from the University of South Alabama.


Björn Reineking is a quantitative ecologist interested in how environmental conditions shape ecological communities and their dynamics. In movement ecology, he is working on methods such as step selection functions to infer habitat selection from movement tracks. Björn is a researcher at INRAE and based in Grenoble.


  • Martin Wegmann, University of Würzburg
  • Anne Scharf, Max Planck Institute of Animal Behavior and University of Konstanz
  • Martina Scacco, Max Planck Institute of Animal Behavior and University of Konstanz
  • Hannah Williams, Max Planck Institute of Animal Behavior and University of Konstanz
  • Benjamin Leutner, German Aerospace Center (DLR)
  • Chris Flemming, Smithsonian Conservation Biology Institute and University of Maryland
  • Björn Reineking, Université Grenoble Alpes, INRAe, LESSEM
  • Thomas Mueller, Senckenberg Research Institute
  • Justin Calabrese, CASUS Helmholtz-Zentrum Dresden-Rossendorf e.V. (HZDR)
  • Kamran Safi, Max Planck Institute of Animal Behavior and University of Konstanz
  • Chloe Bracis, Université Grenoble Alpes
  • Michael Noonan, Smithsonian-Mason School of Conservation & University of British Columbia
  • Jakob Schwalb-Willmann, University of Würzburg and German Aerospace Center (DLR)

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