Evidence map›Paper›PMID 42563175›Full record

ArticleMovement ecology2026

Enabling high-resolution wildlife tracking: antenna beam-based approach including novel per-position error estimations for automated radiotelemetry systems.

Mirjam R Rieger, Jan Schmitt, Paula Machin, Johann Musculus, Ralf Dittrich, Thomas K Gottschalk, Jannis Gottwald, Patrick Lampe, Jonas Höchst

Abstract read
In one paragraph

Article in Movement ecology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Mirjam R RiegerUniversity of Applied Forest Sciences Rottenburg, Schadenweilerhof, Rottenburg am Neckar, 72108, Germany. mrieger@posteo.de.
Jan SchmittEberhard Karls University Tübingen, Auf der Morgenstelle 28, Tübingen, 72076, Germany.
Paula MachinEurofins MITOX BV, Science Park 408, Amsterdam, 1098XH, Netherlands.
Johann MusculusEurofins MITOX BV, Science Park 408, Amsterdam, 1098XH, Netherlands.
Ralf DittrichEurofins MITOX BV, Science Park 408, Amsterdam, 1098XH, Netherlands.
Thomas K GottschalkUniversity of Applied Forest Sciences Rottenburg, Schadenweilerhof, Rottenburg am Neckar, 72108, Germany.
Jannis GottwaldtrackIT Systems GmbH, Unterm Bornrain 4, Cölbe, 35039, Germany.
Patrick LampetrackIT Systems GmbH, Unterm Bornrain 4, Cölbe, 35039, Germany.
Jonas HöchsttrackIT Systems GmbH, Unterm Bornrain 4, Cölbe, 35039, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe increasing importance of wildlife movement data in ecology and conservation has fueled the development of Automated Radiotelemetry Systems (ARTS) using very-high-frequency (VHF) transmitters. To make optimal use of this data, highly precise analysis methods are needed to detect even small-scale movement changes and thus provide high data quality. While various approaches have successfully minimized position errors in ARTS, they mostly rely on a single mean error estimate.

methodsWe present two contributions. First, an antenna geometry-based position finding method (antenna beams) for small scale movements that reduces position errors (PE) and increases the number of position estimates. Second, a model for per-position error estimation, predicting error as a function of signal and position characteristics, applicable for data without ground-truth information and across various position finding methods. Using ground-truth data from VHF transmitters recorded simultaneously with the ARTS trackIT and GPS, we validated and compared yield, position errors and predictive performance of our approach with the common angulation and multilateration methods.

resultsOur antenna beam-based method provided a substantial alternative to angulation for directional set-ups, achieving comparable mean PEs (41 m vs. 44 m) and especially higher number of localizations (up to 99% vs. 30 to 66%). The per-position error estimation model demonstrated a strong predictive performance (mean absolute deviation from true error down to 21 m) utilizing parameters such as the number of participating stations and antennas, maximum signal strength, normalized summed up signal strengths and positioning within the study area.

conclusionsOur results indicate that (i) the antenna beam-based position-finding method outperforms common methods in both accuracy and yield, (ii) the novel introduced per-position error estimation model reliably reflects measured PE from ground-truth data, and (iii) the resulting setup provides a robust foundation for high-resolution wildlife movement analyses.

Indexed as

Automated Radiotelemetry SystemPosition errorPosition findingRadiotrackingVHFWildlife movement

Identifiers

PMID42563175
PMCPMC13445756

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.