| dc.contributor.advisor | Balkenhol, Niko Prof. Dr. | |
| dc.contributor.author | Signer, Johannes Michael | |
| dc.date.accessioned | 2016-04-19T08:47:17Z | |
| dc.date.available | 2016-04-19T08:47:17Z | |
| dc.date.issued | 2016-04-19 | |
| dc.identifier.uri | http://hdl.handle.net/11858/00-1735-0000-0028-8733-2 | |
| dc.identifier.uri | http://dx.doi.org/10.53846/goediss-5616 | |
| dc.language.iso | eng | de |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | |
| dc.subject.ddc | 634 | de |
| dc.title | Evaluating, Implementing, and Applying Methods for Analysing Animal Biotelemetry Data | de |
| dc.type | cumulativeThesis | de |
| dc.contributor.referee | Balkenhol, Niko Prof. Dr. | |
| dc.date.examination | 2016-01-29 | |
| dc.description.abstracteng | Movement ecology is an emerging discipline within ecology. Researchers addressing ba-
sic and applied questions within the movement ecology framework often rely on animal
biotelemetry data. Biotelemetry sensors can collect different types of data (from track-
ing an animal’s position to measuring its heart rate). Rapid technological advances in
satellite based navigation and tracking devices enable researchers to track animals with
smaller devices, leading to steadily increasing sampling rates. To characterize space
requirements of tracked animals, the concept of a home range is often used.
This thesis starts with a general introduction (chapter 1), that connects the following
chapters to the wider conceptual and analytical picture. The main parts of this thesis
focus on the analysis of animal tracking data using home range analyses (chapters 2
through 5) and how to statistically test for the influence of (environmental) covariates
on animal movement (chapter 6). Starting at the level of data management, chapter
2 highlights the need for a data model when working with tracking data. Next, a new
package for program R is introduced that implements the previously discussed data
model and provides functionality for the analysis of animal tracking data (chapter 3).
Within the rhr (reproducible home ranges) package, the most commonly used estimators
for home-range analyses are implemented. Further, functionalities for the automatic
reporting of results and a graphical user interface are provided. After these technical
aspects of tracking data, different methods for the estimation of home-range core areas
(chapter 4) and home ranges as such (chapter 5) are discussed. Moving beyond home
ranges, chapter 6 introduces a method to test which tests whether an animal’s movement
track is influenced by environmental covariates. Finally, this thesis concludes that:
(i) amounts of data (tracking data and auxiliary environmental data) will continue to
increase in the future; (ii) tools to handle, manage, and analyze them are of great
importance (chapter 2 and 3); (iii) researchers should not get lost in methods and lose
sight of the wider biological picture, rather, they should use established as well as new
methods to answer interesting biological questions (chapter 4 through 6). | de |
| dc.contributor.coReferee | Wiegand, Kerstin Prof. Dr. | |
| dc.subject.eng | home range | de |
| dc.subject.eng | movement ecology | de |
| dc.subject.eng | tracking data | de |
| dc.subject.eng | biotelemetry | de |
| dc.subject.eng | R | de |
| dc.identifier.urn | urn:nbn:de:gbv:7-11858/00-1735-0000-0028-8733-2-2 | |
| dc.affiliation.institute | Fakultät für Forstwissenschaften und Waldökologie | de |
| dc.subject.gokfull | Forstwirtschaft (PPN621305413) | de |
| dc.identifier.ppn | 857190598 | |