DOI: 10.5061/dryad.pc866t1wf
title: Proximity-sensors on GPS collars reveal fine-scale predator-prey behavior during a predation event: A case study from Scandinavia

description: 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.
description: 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.
description: # 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](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 ##