Using automated passive acoustic monitoring to measure changes in bird and bat vocal activity around hedgerows of different ages

Abstract

Hedgerows are a semi-natural habitat that supports farmland biodiversity by providing food, shelter, and habitat connectivity. Hedgerow planting goals have been set across many countries in Europe and agri-environment schemes (AES) play a key role in reaching these targets. Passive acoustic monitoring using automated vocalisation identification (automated PAM), offers a valuable opportunity to assess biodiversity changes following AES implementation using simple, community-level metrics, such as vocal activity of birds and bats. To evaluate whether vocal activity could be used to indicate the effectiveness of AES following hedgerow planting in future result-based or hybrid schemes, we surveyed twenty-four hedgerows in England classified into a chrono-sequence of three age categories (New, Young, Old). We recorded 4466 h over the course of 30 days and measured bird and bat vocal activity using BirdNET for birds and Kaleidoscope for bats. Vocal activity of all birds, farmland birds, and bats were modelled with age and predictors of hedgerow, habitat, and weather conditions to assess changes occurring from hedgerow planting to maturity. We show an increase of vocal activity in Young and Old hedgerows compared to New ones and highlight elements of the surrounding landscape that should be considered when evaluating AES implementation on bird and bat communities. We found high BirdNET precision in community-level vocal activity and low precision of species-level observations, and we argue that vocal activity may be used in novel AES to link a result-based payment component to automated PAM results, incentivising biodiversity effective hedgerow planting and management by farmers and landowners.