Capercaillie Emergency Plan 2025 - 2030 - Flipbook - Page 44
2. Undertake brood counting with dogs in tandem with trail cameras where
possible to explore, through on the ground learning, how to maintain historic
brood datasets if brood counting with dogs is prohibited.
Measures of success
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Reliable, non-invasive methods for monitoring capercaillie productivity
adopted across the capercaillie range.
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Successful gathering of accurate productivity data across the capercaillie range.
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Identification of correlations between capercaillie productivity and management
strategies employed.
Results integrated into future predator management plans, leading to measurable
Partners (alongside the Park Authority and NatureScot)
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University of Aberdeen
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University of St. Andrews
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Seafield and Strathspey Estates
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Rothiemurchus Estate
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GWCT
Key points on current feasibility and delivery
1. The University of Aberdeen has developed a robust model using camera trap
data to assess the impact of diversionary feeding, demonstrating its suitability
for evaluating other management interventions. Using this method, it is
possible to provide a chick to hen ratio by comparing images of broods to
images of barren hens.
2. Using a sample set of 18,000 images from ~400,000 images captured from
dust baths during the diversionary trial, AI has been trained to identify a cock
capercaillie and a hen capercaillie in camera trap images.
3. Compared to brood counts with dogs, camera trap data offers more detailed
insights into factors affecting capercaillie, such as brood activity patterns,
changes in brood size over time, and the ratio of chicks to hens within
specific timeframes. This creates opportunities for adaptive management if,
for example, image data shows different survival rates at different life
stages and on different sites.
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