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Abstract Camera traps (CT) have been used to study a wide diversity of wildlife around the world. However, despite their widespread use, standardized protocols are lacking, potentially leading to reduced efficiency and inhibiting study comparisons, generalizability, and repeatability. While there are general guidelines and considerations researchers should be aware of when designing a CT survey, studies have shown the vital importance of selecting sampling schemes and camera settings tailored to specific characteristics of the wildlife system of interest. For many species and regions, optimal sampling protocols have not been thoroughly evaluated, especially in vast open landscapes. We used CT data on barren‐ground caribou (Rangifer tarandus) in the open landscape of arctic Alaska as a case study to evaluate and quantify the influence of camera trigger type (i.e., motion detection vs. time‐lapse) and time‐lapse interval on data generation to inform sampling protocols for future CT research in this system or others like it. Comparing camera trigger types, we found 5 min interval time‐lapse generated seven‐times more images containing caribou compared to motion detection. However, the detection rate of motion detection was over 11‐times greater than time‐lapse resulting in more efficient data collection with respect to camera battery life, data storage, and data processing time. Exploring the effect of time‐lapse interval length, we found detections were highly sensitive to interval length with a 30 min interval producing 33.7% fewer images containing caribou and identifying 22.2% fewer trap days containing caribou compared to a 5 min interval. Our results provide insight into effective CT sampling protocols for open landscapes and highlight the importance of critically evaluating and selecting camera settings that account for characteristics of the study system to ensure adequate data is generated efficiently to address study objectives.
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Soundscape Ecology to Assess Environmental and Anthropogenic Controls on Wildlife Behavior: Environmental Data (Northeastern Alaska and Northwestern Canada, 2017-2023)
This project used cutting-edge soundscape observations and analyses to quantify the influence of changing environmental dynamics and increasing anthropogenic activity on the behavior and phenology of migratory caribou, waterfowl, and songbird communities in Arctic-boreal Alaska and northwestern Canada. We used acoustic and camera-trap monitoring methods to evaluate wildlife responses in novel and non-invasive ways across broad spatial ranges during crucial seasons. Our study combined field observations, modeling, and analyses included (1) soundscape measurements, (2) camera-trap observations, (3) automated soundscape analyses, (4) analyses of camera-trap caribou observations, (5) high-resolution modeling of environmental variables, and (6) statistical analyses of wildlife occupancy, diversity, and phenology. This “Environmental Data” dataset package describes and includes the high-resolution environmental variables used in this study.
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- Award ID(s):
- 1839195
- PAR ID:
- 10561163
- Publisher / Repository:
- NSF Arctic Data Center
- Date Published:
- Subject(s) / Keyword(s):
- Soundscape Acoustic monitoring Camera-trap monitoring Birds Caribou Environmental variables Snow
- Format(s):
- Medium: X Other: text/xml
- Sponsoring Org:
- National Science Foundation
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