Data · dataset · 2021
Data from: Heterospecific eavesdropping in ant-following birds of the Neotropics is a learned behaviour
Listed in Borealis and Agri-environmental Research Data Dataverse — shown once because both records carry DOI 10.5683/sp2/s0pnar
Description
Abstract
Animals eavesdrop on other species to obtain information about their environments. Heterospecific eavesdropping can yield tangible fitness benefits by providing valuable information about food resources and predator presence. The ability to eavesdrop may therefore be under strong selection, although extensive research on alarm-calling in avian mixed-species flocks has found only limited evidence that close association with another species could select for innate signal recognition.
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Nevertheless, very little is known about the evolution of eavesdropping behaviour and the mechanism of heterospecific signal recognition, particularly in other ecological contexts, such as foraging. To understand whether heterospecific eavesdropping was an innate or learned behaviour in a foraging context, we studied heterospecific signal recognition in ant-following birds of the Neotropics, which eavesdrop on vocalizations of obligate ant-following species to locate and recruit to swarms of the army ant Eciton burchellii, a profitable food resource.
We used a playback experiment to compare recruitment of ant-following birds to vocalizations of two obligate species at a mainland site (where both species are present) and a nearby island site (where one species remains whereas the other went extinct approx. 40 years ago). We found that ant-following birds recruited strongly to playbacks of the obligate species present at both island and mainland sites, but the island birds did not recruit to playbacks of the absent obligate species.
Our results strongly suggest that (i) ant-following birds learn to recognize heterospecific vocalizations from ecological experience and (ii) island birds no longer recognize the locally extinct obligate species after eight generations of absence from the island. Although learning appears to be the mechanism of heterospecific signal recognition in ant-following birds, more experimental tests are needed to fully understand the evolution of eavesdropping behaviour.
Usage notes
Raw point count data The file includes the sampling date, observer, trial start time, point number (i.e. replicate), playback treatment (including species and number of individuals in the playback), trial stage, time of detection (min, sec), responding species, individual, distance from speaker, and vocalization type. RSPB_2017-1785_raw data.xlsx
Links
Where it is published
- Dataverse dataset page borealisdata.ca/dataset.xhtml?persistentId=doi%3A10.5683%2FSP2%2FS0PNAR ↗
landing page · from borealisdata ca
- DOI doi.org/10.5683/sp2/s0pnar ↗
DOI / persistent id · from borealisdata ca
Catalogue records · 1
- Dataverse API borealisdata.ca/api/datasets/:persistentId/?persistentId=doi%3A10.5683%2FSP2%2… ↗
metadata API · from borealisdata ca
Topics
- From keywords
- Chemistry · Computer Science & AI · Earth & Environmental Science · Economics & Finance · Engineering · Humanities · Life Sciences · Mathematics & Statistics · Medicine & Health · Ocean & Atmospheric Science · Social Science
- Inferred from text
- Zoology 69%
Provenance · 2 source records, 20 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Borealis | doi:10.5683/SP2/S0PNAR | 13 d ago | JSON v1 |
| Agri-environmental Research Data Dataverse | doi:10.5683/SP2/S0PNAR | 12 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[field].anzsrc:group:3109 | enrichment · borealisdata ca | taxonomy-embedding@1.0.0 | title+keywords+description (69%) |
| concepts[field].dataverse_subject:other | source · borealisdata ca | connector:borealisdata_ca@1.0.0 | /subjects |
| concepts[field].dataverse_subject:other | source · borealisdata ca dataverse | connector:borealisdata_ca_dataverse@1.0.0 | /subjects |
| concepts[field].local:field:chemistry | mapping · borealisdata ca dataverse | connector:borealisdata_ca_dataverse@1.0.0 | /subjects |
| concepts[field].local:field:computer-science-ai | mapping · borealisdata ca dataverse | connector:borealisdata_ca_dataverse@1.0.0 | /subjects |
| concepts[field].local:field:earth-environmental | mapping · borealisdata ca dataverse | connector:borealisdata_ca_dataverse@1.0.0 | /subjects |
| concepts[field].local:field:economics-finance | mapping · borealisdata ca dataverse | connector:borealisdata_ca_dataverse@1.0.0 | /subjects |
| concepts[field].local:field:engineering | mapping · borealisdata ca dataverse | connector:borealisdata_ca_dataverse@1.0.0 | /subjects |
| concepts[field].local:field:humanities | mapping · borealisdata ca dataverse | connector:borealisdata_ca_dataverse@1.0.0 | /subjects |
| concepts[field].local:field:life-sciences | mapping · borealisdata ca dataverse | connector:borealisdata_ca_dataverse@1.0.0 | /subjects |
| concepts[field].local:field:mathematics-statistics | mapping · borealisdata ca dataverse | connector:borealisdata_ca_dataverse@1.0.0 | /subjects |
| concepts[field].local:field:medicine-health | mapping · borealisdata ca dataverse | connector:borealisdata_ca_dataverse@1.0.0 | /subjects |
| concepts[field].local:field:ocean-atmospheric | mapping · borealisdata ca dataverse | connector:borealisdata_ca_dataverse@1.0.0 | /subjects |
| concepts[field].local:field:social-science | mapping · borealisdata ca dataverse | connector:borealisdata_ca_dataverse@1.0.0 | /subjects |
| created_date | source · borealisdata ca | connector:borealisdata_ca@1.0.0 | |
| description | source · borealisdata ca | connector:borealisdata_ca@1.0.0 | /description |
| publication_date | source · borealisdata ca | connector:borealisdata_ca@1.0.0 | |
| title | source · borealisdata ca | connector:borealisdata_ca@1.0.0 | /name |
| updated_date | source · borealisdata ca | connector:borealisdata_ca@1.0.0 | |
| version_label | source · borealisdata ca | connector:borealisdata_ca@1.0.0 |