Bioacoustic monitoring reveals shifts in breeding songbird populations and singing behaviour with selective logging in tropical forests

Selective logging is the primary cause of tropical forest degradation and is rapidly expanding worldwide. While the impacts of logging on species diversity and distributions are well understood, little is known about the effects of logging on animal behaviours central to individual fitness and popul...

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Bibliographic Details
Published inThe Journal of applied ecology Vol. 56; no. 11; pp. 2482 - 2492
Main Authors Pillay, Rajeev, Fletcher, Robert J., Sieving, Kathryn E., Udell, Bradley J., Bernard, Henry, Paiva, Vitor
Format Journal Article
LanguageEnglish
Published Oxford Blackwell Publishing Ltd 01.11.2019
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Summary:Selective logging is the primary cause of tropical forest degradation and is rapidly expanding worldwide. While the impacts of logging on species diversity and distributions are well understood, little is known about the effects of logging on animal behaviours central to individual fitness and population persistence. The song rate of breeding songbirds is a behavioural trait that is often positively associated with male density and used by conspecific females as an indicator of territory and male quality. Thus, contrasting logging‐induced adjustments in song rates of individual birds with population shifts may illuminate potential mechanisms underlying population distributions. We present a novel application of bioacoustic monitoring, integrating counts of individuals, songs and duets from single automated recording units (ARUs) with N‐mixture models, to estimate shifts in population parameters (occupancy, abundance) and singing behaviours (per‐capita song rates, per‐pair duet rates) of 32 Bornean songbird species with logging. We tested hypotheses on the relationships between adjustments in behavioural and population parameters with logging, and further tested the extent to which species traits predicted behavioural and population shifts. Adjustments to singing behaviour in 59 and 53% of species (57% of duetting species) were concordant with differences in occupancy and abundance respectively, such that species showing reduced populations with logging also produced fewer songs per‐capita, and vice versa. Species known to prefer undisturbed habitats and large‐bodied species showed the most negative effects of logging on singing behaviour and population distributions. Species known to exploit degraded habitats exhibited the opposite pattern. Subdued singing in logged forests by species of conservation concern suggests limited competition between territorial males in small populations and may also signal low‐quality territories. Synthesis and applications. We demonstrate that bioacoustic monitoring can be used to not only estimate important population parameters of occupancy and abundance across a diverse tropical songbird community, but also enables quantification of behaviours considered relevant to individual fitness, yet unobtainable with conventional methods (e.g. point counts). Bioacoustics provides a viable approach to reliable automated large‐scale monitoring of hyperdiverse tropical forest systems under logging operations and other land‐use pressures. In breeding songbirds, male song rate often serves as an indicator of territory quality to conspecific females. The authors integrate acoustic counts with N‐mixture models to assess how logging impacts populations (occupancy, abundance) and singing behaviours (per‐capita song rates, per‐pair duet rates) of a breeding songbird community in Bornean forests. They found that species associated with undisturbed forests were negatively affected by logging in both populations and singing behaviours. Conversely, species that exploit degraded habitats not only thrived in logged forests but also produced more songs per‐capita. These results suggest that logging may alter territory quality for tropical songbirds, either enhancing it or degrading it, depending on species’ functional traits. Photo: Grey‐headed canary‐flycatcher singing, by Michelle and Peter Wong.
ISSN:0021-8901
1365-2664
DOI:10.1111/1365-2664.13492