Visual-acoustic wildlife deterrents as a supporting measure to prevent mowing-related mortality in roe deer fawns
Data files
Jul 30, 2025 version files 36.66 KB
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README.md
7.37 KB
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Stehr_2025_fawn_data_deterrent.csv
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Abstract
Mowing-related mortality is one of the main causes of death among roe deer fawns in agricultural regions, prompting farmers in Germany to implement preventative measures. Understanding the effectiveness of different deterrent methods is crucial to reducing such mortality.
This study examined the effectiveness of visual-acoustic wildlife deterrent devices in preventing roe deer fawns from entering agriculturally used areas before mowing, encouraging those already present to leave, or facilitating their removal by their mothers. A total of 76 fawns were fitted with GPS-collars between 2022 and 2023, and their movements were analysed using a multi-state Markov model.
Our results demonstrate that visual-acoustic wildlife deterrents significantly influenced fawn behaviour, with 36% of the fawns leaving the trial area and not returning at all during the trial period. However, this indicates a substantial risk of injury or death for the fawns remaining in the fields during mowing. Among the tested devices, electronic acoustic deterrents, particularly smoke detectors, were the most effective deterrents, scaring away over 50% of the fawns without any significant habituation effect.
The probability of fawns leaving the meadows was further influenced by several factors such as age, proximity to forest edges, vegetation height, and field size. Younger fawns, following a "hider" strategy, were less likely to leave the agriculturally used areas, whereas older fawns exhibited higher mobility. Fawns more frequently remained in areas with tall vegetation and large field sizes, while deterrents proved more effective in smaller fields and near forest edges.
Despite some success, the limited efficacy of the tested deterrent devices highlights the necessity for additional measures, such as using drones equipped with thermal imaging cameras, to further reduce fawn mortality during mowing. Our findings provide critical insights for improving wildlife management practices in agricultural landscapes and reducing roe deer fawn losses during the mowing season.
Dataset DOI: 10.5061/dryad.g4f4qrg2f
Description of the data and file structure
Description of the data
The data file included in the submission consists of Stehr_2025_fawn_data_deterrent.csv. This study examined the effectiveness of visual-acoustic wildlife deterrent devices in preventing roe deer fawns from entering agriculturally used areas before mowing, encouraging those already present to leave, or facilitating their removal by their mothers. A total of 76 fawns were fitted with GPS-collars between 2022 and 2023, and their movements were analysed using a multi-state Markov model. By achieving greater knowledge about the effectiveness of different deterrent devices, our findings have critical implications for mitigating mowing-related mortality — a topic of increasing public and scientific concern. The integration of these results into wildlife management strategies has the potential to reduce the risk to neonate roe deer during agricultural mowing, a recurring issue that receives significant media and policy attention. Furthermore, the findings contribute valuable insights to the broader understanding of ungulate biology under changing environmental conditions. Since we worked with live animals and handled them during the measurements, increased caution was required, and it was not always possible to collect all data. Missing data, which could not be measured, were marked as N/A in the dataset.
Files and variables
File: Stehr_2025_fawn_data_deterrent.csv
Description:
Variables
- study area: name of study area
- fawn_name: given name of fawn
- Fawn_ID: unique fawn id (Collar ID + fawn Eartag)
- Collar_ID: id of used collar
- Eartag: id of given eartag
- Sex: fawns sex
- Parturition_date: date of birth of investigated fawn
- Age : age at trial start [days]
- Field size: size of trial area [ha]
- N_Start: coordinates N of trial area
- E_Start: coordinates E of trial area
- distance forrest edge: shortest distance between trial area and the nearest forrest edge [m]
- Date Start: Date of Start of the trial
- Time start: Time of Start of the trial
- date end: Date of End of the trial
- Time end: Time of End of the trial
- kind_of_deterrent: used kind of deterrent
- Code_kind_of_deterrent: numeric used kind of deterrent (1=Carry out/ shooing out; 2=Carry out / shooing out; 3=Plastic bag; 4= LARS Wildlife rescuer; 5= Smoke detector; 10= Control)
- Hours until leaving: Hours passed until the trial area was left for the first time
- Hours after end until return: Hours passed until the trial area was entered for the first time after trialend
- Trial: the next 24 variables describe the experiment. We have coded the positions of the fawns for the evaluation as follows: 1=fawn is in the experimental area; 0=fawn is not in the experimental area.
- Start: Trial Beginning [1=fawn is in the experimental area; 0=fawn is not in the experimental area]
- 1.h: first trial hour [1=fawn is in the experimental area; 0=fawn is not in the experimental area]
- 2.h: second trial hour [1=fawn is in the experimental area; 0=fawn is not in the experimental area]
- 3.h: Third trial hour [1=fawn is in the experimental area; 0=fawn is not in the experimental area]
- 4.h: Fourth trial hour [1=fawn is in the experimental area; 0=fawn is not in the experimental area]
- 5.h: Fifth trial hour [1=fawn is in the experimental area; 0=fawn is not in the experimental area]
- 6.h: Sixth trial hour [1=fawn is in the experimental area; 0=fawn is not in the experimental area]
- 7.h: Seventh trial hour [1=fawn is in the experimental area; 0=fawn is not in the experimental area]
- 8.h: Eighth trial hour [1=fawn is in the experimental area; 0=fawn is not in the experimental area]
- 9.h: Ninth trial hour [1=fawn is in the experimental area; 0=fawn is not in the experimental area]
- 10.h: Tenth trial hour [1=fawn is in the experimental area; 0=fawn is not in the experimental area]
- 11.h: Eleventh trial hour [1=fawn is in the experimental area; 0=fawn is not in the experimental area]
- 12.h: Twelfth trial hour [1=fawn is in the experimental area; 0=fawn is not in the experimental area]
- 13.h: Thirteenth trial hour [1=fawn is in the experimental area; 0=fawn is not in the experimental area]
- 14.h: Fourteenth trial hour [1=fawn is in the experimental area; 0=fawn is not in the experimental area]
- 15.h: Fifteenth trial hour [1=fawn is in the experimental area; 0=fawn is not in the experimental area]
- 16.h: Sixteenth trial hour [1=fawn is in the experimental area; 0=fawn is not in the experimental area]
- 17.h: Seventeenth trial hour [1=fawn is in the experimental area; 0=fawn is not in the experimental area]
- 18.h: Eighteenth trial hour [1=fawn is in the experimental area; 0=fawn is not in the experimental area]
- 19.h: Nineteenth trial hour [1=fawn is in the experimental area; 0=fawn is not in the experimental area]
- 20.h: Twentieth trial hour [1=fawn is in the experimental area; 0=fawn is not in the experimental area]
- 21.h: Twenty-first trial hour [1=fawn is in the experimental area; 0=fawn is not in the experimental area]
- 22.h: Twenty-second trial hour [1=fawn is in the experimental area; 0=fawn is not in the experimental area]
- 23.h: Twenty-third trial hour [1=fawn is in the experimental area; 0=fawn is not in the experimental area]
- 24.h: Twentyfourth trial hour [1=fawn is in the experimental area; 0=fawn is not in the experimental area]
- hour in deterrent area: Total number of hours the fawn was in the field during the experiment
- number of deterrents: Number of deterrents used (as no transportable deterrents were used for the carry out/shooing out test type, none are entered here)
- Objekt: trial objekt
- vegetation typ: Vegetation typ of the trial
- Average vegetation height without drop plate: measured average vegetation height [cm] measured vegetation height
- Height of vegetation without drop plate1: measured vegetation height [cm]
- Height of vegetation without drop plate2:measured vegetation height [cm]
- Average vegetation height with drop plate: measured average vegetation height [cm] measured vegetation height
- Height of vegetation with drop plate1: measured vegetation height [cm]
- Height of vegetation with drop plate2: measured vegetation height [cm]
- vegetation Density % : determined vegetation density [%]
Code/software
All hypotheses were tested with a significance level of 5%. The statistical analysis was done in SPSS Statistics v. 29.0.1.0 (IBM, 2024) and R v. 4.4.1 (RCoreTeam, 2024). In order to model the probabilities of the transition over time, we employed a 2-D multi-state Markov model using the package “msm” in R (Jackson, 2011). This model class is particularly useful for panel data, as it describes how individuals move between states continuously by calculating transition intensities, representing the instantaneous risk of moving from one state to another (Jackson, 2011).
Access information
Other publicly accessible locations of the data:
- none
Data was derived from the following sources:
- The data were recorded and collected by ourselves