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4 results for “wildlife telemetry”
Data from: UAV wildlife radio telemetry: system and methods of localization
1. The majority of bird and bat species are incapable of carrying tags that transmit their position to satellites. Given fundamental power requirements for such communication, burdened mass guidelines, and battery technology, this constraint necessitates the continued use of very high frequency (VHF) radio beacons. As such, efforts should be made to mitigate their primary deficiencies: detection range, localization time, and localization accuracy. 2. The integration of a radio telemetry system with an unmanned aerial vehicle (UAV) could significantly improve the capacity for data collection from VHF tags. We present a UAV-integrated radio telemetry system that relies on open source hardware and software. Localization methods including signal processing, bearing estimation based on principal component analysis, localization techniques, and test results are discussed. 3. Using a low power beacon applicable for bats and small birds, testing showed that the improved vantage of the UAV-radio telemetry system (UAV-RT) provided significantly higher received signal power compared to low level flights (maximum range beyond 1.4 km). Flight testing of localization methods showed median bearing errors between 2.3-6.8 degrees, with localization errors of between 5-14% of the distance to the tag. In a direct comparison to an experienced radio telemetry user, the UAV-RT system provided bearing and localization estimates with 53% less error. 4. This paper introduces the core functionality and use methods of the UAV-RT system, while presenting baseline localization performance metrics. An associated website hosts plans for assembly and software installation. The methods of UAV-RT use for tag detection will be further developed in future works. For both the detection and localization problems, the mobility of a flying asset drastically reduces tracker time requirements. A seven-minute flight would be sufficient to collect five equally spaced bearing estimates over a 1 km transect. The use of a software defined radio on the UAV-RT system will allow for the simultaneous detection and localization of multiple tags.
Data from: UAV wildlife radio telemetry: system and methods of localization
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Dataset from: Are we telling the same story? Comparing inferences made from camera trap and telemetry data for wildlife monitoring
<p>Estimating habitat and spatial associations for wildlife is common across ecological studies, and it is well known that individual traits can drive population dynamics and vice versa. Thus, it is commonly assumed that individual- and population-level data should represent the same underlying processes, but few studies have directly compared contemporaneous data representing these different perspectives. We evaluated the circumstances under which data collected from Lagrangian (individual-level) and Eulerian (population-level) perspectives could yield comparable inferences in an effort to understand how scalable information is from the individual to the population. We used Global Positioning System (GPS) collar (Lagrangian) and camera trap (Eularian) data for seven species collected simultaneously in eastern Washington (2018 – 2020) to compare inferences made from different survey perspectives. We fit the respective data streams to resource selection functions (RSFs) and occupancy models and compared estimated habitat- and space-use patterns for each species. Although previous studies have considered whether individual- and population-level data generated comparable information, ours is the first to make this comparison for multiple species simultaneously and to specifically ask whether inferences from the two perspectives differ depending on the focal species. We found general agreement between the predicted spatial distributions for most paired analyses, though specific habitat relationships differed. We hypothesized the discrepancies arose due to differences in statistical power associated with camera and GPS-collar sampling, as well as spatial mismatches in the data. Our research suggests data collected from individual-based sampling methods can capture coarse population-wide patterns for a diversity of species, but results differ when interpreting specific wildlife-habitat relationships.</p>
Dataset from: Are we telling the same story? Comparing inferences made from camera trap and telemetry data for wildlife monitoring
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