Proximity-sensors on GPS collars reveal fine-scale predator-prey behavior during a predation event: A case study from Scandinavia
Cite this dataset
Tallian, Aimee et al. (2023). Proximity-sensors on GPS collars reveal fine-scale predator-prey behavior during a predation event: A case study from Scandinavia [Dataset]. Dryad. https://doi.org/10.5061/dryad.pc866t1wf
Abstract
Although the advent of high-resolution GPS tracking technology has helped increase our understanding of individual and multi-species behavior in wildlife systems, detecting and recording direct interactions between free-ranging animals remains difficult. In 2023, we deployed GPS collars equipped with proximity sensors (GPS proximity collars) on brown bears (Ursus arctos) and moose (Alces alces) as part of a multi-species interaction study in central Sweden. On 6 June, 2023, a collar on an adult female moose and a collar on an adult male bear triggered on each other’s UHF signal and started collecting fine-scale GPS positioning data. The moose collar collected positions every 2 minutes for 89 minutes and the bear collar collected positions every 1 minute for 41 minutes. On 8 June, field personnel visited the site and found a female neonate moose carcass with clear indications of bear bite marks on the head and neck. During the predation event, the bear remained at the carcass while the moose moved back and forth, moving towards the carcass site about 5 times. The moose was observed via drone with 2 calves on 24 May and with only one remaining calf on 9 June. This case study describes, to the best of our knowledge, the first instance of a predation event between two free-ranging, wild species recorded by GPS proximity collars. Both collars successfully triggered and switched to finer-scaled GPS fix rates when the individuals were in close proximity producing detailed movement data for both predator and prey during and after a predation event. We suggest that, combined with standard field methodology, GPS proximity collars placed on free-ranging animals offer the ability for researchers to observe direct interactions between multiple individuals and species in the wild without the need for direct visual observation.
README: Proximity-sensors on GPS collars reveal fine-scale predator-prey behavior during a predation event: A case study from Scandinavia
https://doi.org/10.5061/dryad.pc866t1wf
Give a brief summary of dataset contents, contextualized in experimental procedures and results.
Description of the data and file structure
GENERAL INFORMATION
1. Title of Dataset: Proximity-sensors on GPS collars reveal fine-scale predator-prey behavior during a predation event:
A case study from Scandinavia - https://doi.org/10.5061/dryad.pc866t1wf
2. Author Information
A. Principal Investigator Contact Information
Name: Aimee Tallian
Institution: Norwegian Institution for Nature Research
Address: P.O. Box 5685 Torgarden NO-7485 Trondheim, Norway
Email: aimee.tallian@gmail.com
3. Date of data collection: Sweden (2023-06-06)
4. Geographic location of data collection: Southcentral Sweden
5. Information about funding sources that supported the collection of the data: This project was funded by the Swedish Environmental Protection Agency\, the Norwegian Environmental Protection Agency\, Viltvårdsfonden Grant #2022-00102\, Sveaskog\, and the Administrative County Board in Gävleborg\, Kopparfors Skogar\, the Swedish Association for Hunting and Management of Wildlife.
SHARING/ACCESS INFORMATION
1. Licenses/restrictions placed on the data: None
2. Links to publications that cite or use the data: "Proximity-sensors on GPS collars reveal fine-scale predator-prey behavior during a predation event: A case study from Scandinavia" published in Ecology and Evolution. 2023.
3. Links to other publicly accessible locations of the data: NA
4. Links/relationships to ancillary data sets: NA
5. Was data derived from another source? No
6. Recommended citation for this dataset: Tallian\, Aimee\, Jenny Mattisson\, Fredrik Stenbacka\, Wiebke Neumann\, Anders Johansson\,
Ole Gunnar Støen, Jonas Kindberg (2023). Data from: Nature Note: Proximity-sensors on GPS collars reveal fine-scale predator-prey behavior
during a predation event: A case study from Scandinavia. Dryad Digital Repository. https://doi.org/10.5061/dryad.pc866t1wf
DATA & FILE OVERVIEW
1. File List: Tallian_et_al_2023_Nature_Note_Data
2. Relationship between files\, if important: NA
3. Additional related data collected that was not included in the current data package: NA
4. Are there multiple versions of the dataset? No
METHODOLOGICAL INFORMATION
1. Description of methods used for collection/generation of data: Please see Tallian et al. 2023. Ecology and Evolution for details.
2. Methods for processing the data: Please see Tallian et al. 2023. Ecology and Evolution for details.
3. Instrument- or software-specific information needed to interpret the data: Microsoft Excel or R
4. Standards and calibration information\, if appropriate: NA
5. Environmental/experimental conditions: Please see Tallian et al. 2023. Ecology and Evolution for details.
6. Describe any quality-assurance procedures performed on the data: Please see Tallian et al. 2023. Ecology and Evolution for details.
7. People involved with sample collection\, processing\, analysis and/or submission: Aimee Tallian\, Jenny Mattisson\, Fredrik Stenbacka\, Wiebke Neumann\, Anders Johansson\, Ole Gunnar Støen\, Jonas Kindberg
DATA-SPECIFIC INFORMATION FOR: Tallian_et_al_2023_Nature_Note_Data
1. Number of variables: 19
2. Number of cases/rows: 91
3. Variable List:
- Object ID - Unique name for the animal
- Collar ID - ID of the collar on the animal
- PubName - common name of the animal
- Species - moose or bear
- GMT Date - Date and time in GMT format
- LMT Date - Date and time in local mean time format (GMT +1)
- Longitude - X-coordinate - geographical position in WGS1984
- Latitude - Y-coordinate - geographical position in WGS1984
- Height - Z-coordinate - geographical position in WGS1984 (height above ground in m)
- DOP - (Dilution of Precision) value for the geometric constellation of the received GPS satellites
- Sats used - number of satellites used for the fix
- Main - voltage of the main battery in Volts
- Bkup - voltage of the backup battery in Volts
- Temp - ambient temperature in degreed Celcius
- SMS date - date data received
- pnt_WGS84 - geographical position in WGS1984
4. Missing data codes: n/a (data not missing per say\, but not present in that specific dataset)
5. Specialized formats or other abbreviations used: NA
Methods
Bears and female moose were captured and collared via helicopter using established protocols (Kreeger and Arnemo 2007, Arnemo et al. 2012, Lian et al. 2014), which were approved by the Swedish Ethical Committee on Animal Research; Permits Dnr 5.8.18-03376/2020 and Dnr A11-2020. Moose capture efforts began in 2020, with the goal of collaring females near the 2018 burn and within the core study area (Fig. 1). Bear capture efforts began in 2022 and were focused on the area where moose had previously been collared to maximize temporal and spatial overlap between species and thus, the potential to observe interspecific interactions.
Captured bear and moose were equipped with GPS neck collars (Vectronic Aerospace, 2023). During the 2023 capture, a sub-sample of bears (n = 4; 2 adult males, 1 solitary female, and 1 female with cubs of the year) and moose (n = 18) were fit with GPS neck-collars that also had proximity sensors and UHF transmitters, i.e., GPS proximity-collars (Vectronic Aerospace GmbH, Berlin, Germany). Proximity collars are equipped with a UHF transmitter and receiver; the transmitter sends a weak UHF signal while the receiver scans for other UHF signals (see Table 1 for detailed settings). Once a signal was received by a collar, the collar reconfigured to a pre-determined fix schedule and logged the ID of the collar that it was triggered by. Once the signal was lost, the collar reverted to its original programming after a pre-scheduled amount of time. The range of UHF signal detection is based on terrain and cover but is usually about 100 m or so away.
Bear proximity collars were programmed to take GPS positions every 30 minutes and increase to a fixed rate of 1 position every 1 minute for a duration of 15 minutes when they came within range of another UHF signal (Table 1). Moose proximity collars were programmed to take GPS positions every 30 minutes and increase to a fixed rate of 1 position every 2 minutes for a duration of 60 minutes when they came within range of a proximity-collared bear; the 2-minute setting was chosen to save battery life over the longer fix duration. Using the GSM-network or IRIDIUM satellite, the collars send continuously positions to the existing database Wireless Remote Animal Monitoring (Dettki et al. 2014) at the Swedish University of Agricultural Sciences, which allows us to monitor animals remotely in near real-time.
Funding
Swedish Environmental Protection Agency, Award: 2022-00102, Viltvårdsfonden