Evidence for acoustic niche partitioning depends on the temporal scale in two sympatric Bornean hornbill species
0301 basic medicine
03 medical and health sciences
15. Life on land
DOI:
10.1111/btp.13205
Publication Date:
2023-02-15T12:43:48Z
AUTHORS (5)
ABSTRACT
AbstractUnderstanding niche partitioning of closely related sympatric species is a fundamental goal in ecology. Acoustic communication space can be considered a resource, and the acoustic niche hypothesis posits that competition between species may lead to partitioning of communication space. Here, we compare the calling behavior of two sympatric Bornean hornbill species—the rhinoceros hornbill (Buceros rhinoceros) and the helmeted hornbill (Rhinoplax vigil)—to test for evidence of acoustic niche partitioning. Both hornbill species emit calls heard over many kilometers and have similar habitat preferences which is predicted to result in interspecific competition. We collected acoustic data on sympatric populations of both hornbill species using 10 autonomous recording units in Danum Valley Conservation Area, Sabah, Malaysia. We found that there was substantial spectral overlap between the calls of the two species, indicating the potential for competition for acoustic space. To test for evidence of acoustic niche partitioning, we investigated spatial and temporal patterns of calling in each species. Both hornbills were strictly diurnal and called throughout the day, and we were equally likely to detect both species at each of our recorders. We did not find evidence of temporal acoustic avoidance at a relatively coarse timescale when we divided our dataset into 1 h bins, but we did find evidence of temporal acoustic avoidance at a finer timescale when we used null models to compare the observed duration of overlapping calls to the expected amount of overlap due to chance.Abstract in Malay is available with online material.
SUPPLEMENTAL MATERIAL
Coming soon ....
REFERENCES (61)
CITATIONS (3)
EXTERNAL LINKS
PlumX Metrics
RECOMMENDATIONS
FAIR ASSESSMENT
Coming soon ....
JUPYTER LAB
Coming soon ....