2018
DOI: 10.1017/s0266467418000056
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Seasonality of vocal activity of a bird community in an Afrotropical lowland rain forest

Abstract: Abstract:Recent observations from the tropics indicate seasonal peaks in breeding and vocal activity of some bird species. However, information about seasonality in vocal activity at the community level is still lacking in the tropics. We examined seasonal variation in the diurnal vocal activity of lowland rain forest birds on Mount Cameroon, using weekly automatic sound recording throughout the whole year and related it to rainfall and temperature. We show that the bird community in lowland rain forest vocali… Show more

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Cited by 23 publications
(18 citation statements)
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“…surveys between pre‐Isaac and the third day after it landed, between the third and 14th day after the hurricane, and so on). We used a Bray–Curtis distance measure to calculate a dissimilarity index for each site (Corte et al , Vokurkova et al ), and ternary plots to visualize the relative contribution of the three components of β diversity to overall differences between consecutive time periods. In the ternary plots, values of replacement, abundance difference, and similarity decide the position of each dot (representing the difference in community structure measured between consecutive time periods) in the plot.…”
Section: Methodsmentioning
confidence: 99%
“…surveys between pre‐Isaac and the third day after it landed, between the third and 14th day after the hurricane, and so on). We used a Bray–Curtis distance measure to calculate a dissimilarity index for each site (Corte et al , Vokurkova et al ), and ternary plots to visualize the relative contribution of the three components of β diversity to overall differences between consecutive time periods. In the ternary plots, values of replacement, abundance difference, and similarity decide the position of each dot (representing the difference in community structure measured between consecutive time periods) in the plot.…”
Section: Methodsmentioning
confidence: 99%
“…Increasing application of deep learning to such problems will likely help provide a solution (e.g., Sethi et al, 2020b) as will continued efforts to build labelled sound libraries from which automated species detection algorithms can be trained (Deichmann et al, 2018). Moreover, soundscape dynamics are frequently characterised by strong seasonal cycles (e.g., Vokurková et al, 2018), presenting a challenge when attempting to disentangle disturbance responses from seasonal soundscape change (Ross et al, 2023). For example, our focal species differ in their seasonality and phenology, meaning that natural phenological differences may in part be responsible for the differences in species' typhoon responses we observed here.…”
Section: Discussionmentioning
confidence: 99%
“…Moreover, soundscape dynamics are frequently characterised by strong seasonal cycles ( e . g ., Vokurková et al, 2018), presenting a challenge when attempting to disentangle disturbance responses from seasonal soundscape change (Ross et al, 2023). For example, our focal species differ in their seasonality and phenology, meaning that natural phenological differences may in part be responsible for the differences in species’ typhoon responses we observed here.…”
Section: Discussionmentioning
confidence: 99%
“…Acoustic data were collected during the breeding season ( temperate mainland : April 2017; temperate island : March 2017; tropical mainland : November 2016; tropical island : September 2016). Dates of fieldwork differ among the four communities but are equivalent in terms of timing of the breeding season (Christy & Clarke, 1998; Jones & Tye, 2006; Garcia‐del‐Rey, 2011; Serle, 1981; Vokurková et al, 2018; Billerman et al, 2020). The recording apparatus consisted of four unidirectional microphones ME66/K6 [Sennheiser] (flat frequency response between 40 Hz and 20 kHz) coupled with a FR2 recorder [Fostex] and three Song Meter SM3 recorders [Wildlife Acoustics] equipped with omnidirectional microphones.…”
Section: Methodsmentioning
confidence: 99%