Delayed compensatory responses in a guild of ant-followers

I studied the influence of competition on the maintenance of a dominance structured multi-species guild of ant-following birds. I explored the numerical and behavioral responses of bicolored (Gymnopithys leucaspis) and spotted (Hylophylax naevioides) antbirds several generations after the extirpation of the dominant ocellated (Phaenostictus mcleannani) antbird on Barro Colorado Island, Panama. I compared the abundances and behavior of these species to data collected by E.O. Willis and others prior to the decline of ocellated antbirds on Barro Colorado, and to a nearby mainland control in Parque Nacional Soberania, where the complete guild of these ant-followers still exists. Populations of bicolored and spotted antbirds increased in density on Barro Colorado, completely compensating in combined biomass for the loss in overall biomass by ocellated antbirds. Historical records suggest that complete population turnover of these species occurred before density compensation was detectable. At ant swarms on Barro Colorado, the numbers of spotted antbirds doubled from historical records and in comparison to Soberania. The increased proportion of biomass of spotted antbirds at swarms on Barro Colorado compensated for the reduced proportion of biomass of ocellated antbirds. No shifts in microhabitat use by bicolored antbirds was observed after the loss of the dominant ocellated antbird. Bicolored antbirds foraged at similar rates, showed similar aggression towards conspecifics, and equal activity at ant swarms on Barro Colorado and in Soberania. Rates of aggression between bicolored and spotted antbirds on Barro Colorado, however, increased. Ocellated antbirds rarely interacted directly with spotted antbirds in Soberania, consistent with historical observations. Thus, the limited swarm use by spotted antbirds historically on Barro Colorado and in Soberania likely results from indirect competitive pressure promoted by ocellated antbirds and mediated through direct interactions with bicolored antbirds. My results suggest that interspecific competition actively maintains guild structure in this complex tropical foraging association through direct and indirect interactions. Behavioral adaptations in guilds may occur over several generations, delaying the onset of compensatory responses. Detailed long-term experiments and/or comparative analyses are needed to fully understand the role of competition in the structuring of multi-species guilds in tropical forests.Science, Faculty ofZoology, Department ofGraduat

Appendix A. A figure of metabolically corrected biomass/100 ha of the antbird clinger guild during census years on Barro Colorado Island and in Soberania National Park, Panama.

A figure of metabolically corrected biomass/100 ha of the antbird clinger guild during census years on Barro Colorado Island and in Soberania National Park, Panama

Effect of captive rearing on song structure in <i>Hylophylax naevioides</i>, where song is defined by PC1, PC2 and PC3 (mean ± SD).

<p>*Statistics derive from a Kruskal Wallis test; N₁ = 5 captive-reared birds, N₂ = 32 wild birds (sexes pooled).</p

Representative song spectrograms from individuals in each treatment group

<p>. Broadband spectrograms show (<b>A, B</b>) captive <i>H. naevioides</i> reared in silence with no tutor, (<b>C–E</b>) captive <i>H. naevioides</i> reared with <i>H. naevius</i> tutor, (<b>F</b>) wild male <i>H. naevioides</i>, (<b>G</b>) wild female <i>H. naevioides</i>, (<b>H</b>) wild male <i>H. naevius</i>.</p

Null distributions showing range of acoustic variation in wild birds.

<p>Arrows indicate where the songs of captive-reared individuals fall within the sampling distribution generated from the songs of wild males (<b>A</b>) and females (<b>B</b>), where songs are described by PC1 (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0095746#pone.0095746.s001" target="_blank">Table S1</a>). Null distributions were generated with 10,000 bootstrap replicates.</p

Comparison of the structure of the songs of experimental versus wild individuals.

<p>Songs by male (closed symbols) and female (open symbols) wild (circles) and captive-reared (red triangles) <i>H. naevioides</i> grouped together while those produced by <i>H. naevius</i> (closed diamonds) grouped separately. Plot produced according to three principal components generated from acoustic data extracted from spectrograms; PC3 is represented by depth and is not labelled (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0095746#pone.0095746.s001" target="_blank">Table S1</a> for factor loadings).</p

Discriminant function analysis grouping (proportion) of song profiles by captive-reared no tutor and heterospecific treatment individuals with respect to song profiles by wild conspecific <i>H. navioides</i> and heterospecific wild <i>H. naevius</i>.

<p>Discriminant function analysis grouping (proportion) of song profiles by captive-reared no tutor and heterospecific treatment individuals with respect to song profiles by wild conspecific <i>H. navioides</i> and heterospecific wild <i>H. naevius</i>.</p

Acoustic analysis of <i>Hylophylax naevioides</i> song.

<p>Broadband spectrogram illustrates an example of one song produced by a wild adult male. Boxes denote the acoustic selections used in this study to calculate acoustic parameters using robust statistical estimators in Raven 1.4. Parameters were calculated as averages across five different subsets of notes separately: the full song, the first half of the song by the nearest note to the middle time, the second half of the song by the nearest note to the middle time, the long notes and the short notes (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0095746#pone-0095746-t001" target="_blank">Table 1</a>).</p

Description of acoustic parameters extracted from songs (see Figure 3).

<p>*For all parameters except 1–3, mean was calculated for notes within a song.</p>†<p>Power values in short-time spectra and frequency bands that compose the spectrogram are summed to generate aggregate power envelopes and spectra, resulting in a power versus time envelope and power versus frequency spectrum, respectively.</p><p>The aggregates are normalized and treated as probability density functions with time or frequency being the variate, and density the fraction of the total signal energy. From the distribution function, various measures of central tendency and dispersion are then used to characterize the signal energy distribution in time and frequency. (See <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0095746#pone.0095746-Cortopassi1" target="_blank">[39]</a>).</p