Next Article in Journal
The 2021 Bitcoin Bubbles and Crashes—Detection and Classification
Next Article in Special Issue
Stylometry and Numerals Usage: Benford’s Law and Beyond
Previous Article in Journal
Estimating the RMSE of Small Area Estimates without the Tears
Previous Article in Special Issue
Some New Tests of Conformity with Benford’s Law
Article

Benford’s Law for Telemetry Data of Wildlife

1
Department of Integrative Biology and Biodiversity Research, Institute of Wildlife Biology and Game Management, University of Natural Resources and Life Sciences, Vienna (BOKU), 1180 Vienna, Austria
2
Department of Integrative Biology and Biodiversity Research, Institute of Mathematics, University of Natural Resources and Life Sciences, Vienna (BOKU), 1180 Vienna, Austria
*
Author to whom correspondence should be addressed.
Academic Editor: Claudio Lupi
Stats 2021, 4(4), 943-949; https://doi.org/10.3390/stats4040055
Received: 4 October 2021 / Revised: 16 November 2021 / Accepted: 18 November 2021 / Published: 20 November 2021
(This article belongs to the Special Issue Benford's Law(s) and Applications)
Benford’s law (BL) specifies the expected digit distributions of data in social sciences, such as demographic or financial data. We focused on the first-digit distribution and hypothesized that it would apply to data on locations of animals freely moving in a natural habitat. We believe that animal movement in natural habitats may differ with respect to BL from movement in more restricted areas (e.g., game preserve). To verify the BL-hypothesis for natural habitats, during 2015–2018, we collected telemetry data of twenty individuals of wild red deer from an alpine region of Austria. For each animal, we recorded the distances between successive position records. Collecting these data for each animal in weekly logbooks resulted in 1132 samples of size 65 on average. The weekly logbook data displayed a BL-like distribution of the leading digits. However, the data did not follow BL perfectly; for 9% (99) of the 1132 weekly logbooks, the chi-square test refuted the BL-hypothesis. A Monte Carlo simulation confirmed that this deviation from BL could not be explained by spurious tests, where a deviation from BL occurred by chance. View Full-Text
Keywords: Benford’s law (BL); logbook; habitat use; Monte Carlo simulation; red deer (Cervus elaphus); telemetry Benford’s law (BL); logbook; habitat use; Monte Carlo simulation; red deer (Cervus elaphus); telemetry
Show Figures

Figure 1

MDPI and ACS Style

Pröger, L.; Griesberger, P.; Hackländer, K.; Brunner, N.; Kühleitner, M. Benford’s Law for Telemetry Data of Wildlife. Stats 2021, 4, 943-949. https://doi.org/10.3390/stats4040055

AMA Style

Pröger L, Griesberger P, Hackländer K, Brunner N, Kühleitner M. Benford’s Law for Telemetry Data of Wildlife. Stats. 2021; 4(4):943-949. https://doi.org/10.3390/stats4040055

Chicago/Turabian Style

Pröger, Lasse, Paul Griesberger, Klaus Hackländer, Norbert Brunner, and Manfred Kühleitner. 2021. "Benford’s Law for Telemetry Data of Wildlife" Stats 4, no. 4: 943-949. https://doi.org/10.3390/stats4040055

Find Other Styles

Article Access Map by Country/Region

1
Back to TopTop