Back

Soundscape reflects breeding phenology in colonial seabirds

Eddington, V. M.; Fradet, D. T.; Craig, E. C.; Cimino, M. A.; White, E. R.; Kloepper, L. N.

2026-05-30 ecology
10.64898/2026.05.27.728265 bioRxiv
Show abstract

Migratory seabirds are valuable indicators of marine ecosystem change but can be difficult to monitor during the breeding season due to dense colonies, remote breeding sites, and sensitivity to investigator disturbance. Passive acoustic monitoring offers a minimally invasive alternative to traditional surveys; however, high call overlap in large colonies complicates approaches that rely on identifying individual vocalizations. In this study, we evaluate acoustic energy as a simple soundscape metric for monitoring breeding phenology in colonial seabirds. Using a comparative approach, we deployed autonomous recorders at breeding colonies of Adelie penguins (Pygoscelis adeliae) in the Western Antarctic Peninsula and common terns (Sterna hirundo) in the Gulf of Maine. We examined seasonal patterns in acoustic energy and compared these trends with known breeding stages and colony observations. Across both species, acoustic energy exhibited distinct seasonal patterns that correspond to key phenological stages, including courtship, incubation, chick rearing, and fledging. These stages are associated with distinctive colony-wide behavioral shifts in colony attendance, territorial interactions, and parent-offspring communication that structure the breeding-season soundscape. Our results demonstrate that colony-wide acoustic energy can capture key phenological transitions in seabird colonies and provide a scalable, minimally invasive approach for monitoring breeding dynamics in remote or rapidly changing environments. HighlightsO_LIPassive acoustic monitoring can track bioindicator phenology under climate change C_LIO_LIAmplitude captures colony-level activity in dense seabird colonies C_LIO_LISoundscape patterns correspond to key breeding stages C_LIO_LIEffective in both temperate and polar seabird systems C_LIO_LIEnables scalable, low-disturbance monitoring in remote systems C_LI

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

1
PLOS ONE
5266 papers in training set
Top 13%
14.9%
2
Frontiers in Marine Science
62 papers in training set
Top 0.1%
8.8%
3
Marine Ecology Progress Series
21 papers in training set
Top 0.1%
7.8%
4
Ecology and Evolution
267 papers in training set
Top 0.8%
6.7%
5
Remote Sensing in Ecology and Conservation
14 papers in training set
Top 0.1%
6.7%
6
Movement Ecology
20 papers in training set
Top 0.1%
6.7%
50% of probability mass above
7
Methods in Ecology and Evolution
176 papers in training set
Top 0.5%
4.8%
8
Scientific Reports
3612 papers in training set
Top 24%
4.3%
9
Royal Society Open Science
214 papers in training set
Top 1%
4.0%
10
ICES Journal of Marine Science
11 papers in training set
Top 0.1%
3.4%
11
Journal of Animal Ecology
75 papers in training set
Top 0.6%
2.7%
12
Frontiers in Ecology and Evolution
69 papers in training set
Top 0.6%
2.7%
13
Ecological Informatics
33 papers in training set
Top 0.3%
2.1%
14
Proceedings of the Royal Society B: Biological Sciences
393 papers in training set
Top 4%
1.4%
15
Journal of The Royal Society Interface
235 papers in training set
Top 3%
1.1%
16
The Journal of the Acoustical Society of America
35 papers in training set
Top 0.3%
1.0%
17
PeerJ
308 papers in training set
Top 11%
0.8%
18
Ecology
85 papers in training set
Top 2%
0.8%
19
Environmental DNA
56 papers in training set
Top 0.7%
0.8%
20
Molecular Ecology Resources
171 papers in training set
Top 2%
0.8%
21
FACETS
14 papers in training set
Top 0.6%
0.6%
22
Remote Sensing
10 papers in training set
Top 0.2%
0.6%
23
Ecosphere
57 papers in training set
Top 1%
0.6%