Range-wide patterns of geographic variation in songs of Golden-crowned Sparrows (Zonotrichia atricapilla)

Abstract

Discrete geographic variation, or dialects, in songs of songbirds arise as a consequence of complex interactions between ecology and song learning. Four of the five species of Zonotrichia sparrows, including the model species White-crowned Sparrow (Z. leucophrys), have been studied with respect to the causes and consequences of geographic variation in song. Within White-crowned Sparrows, subspecies that migrate farther have larger range size of dialects. Here, we assessed geographic patterns of song variation in the fifth species of this genus, the Golden-crowned Sparrow (Z. atricapilla). We analyzed field-recorded songs from 2 sampling periods (1996-1998 and 2006-2013) covering most of its breeding range in western North America. All songs began with a descending whistle and most songs consisted of 3-4 phrases that contained combinations of whistles, buzzes, and trills. We identified 13 discrete song types based on unique sequences of phrase types and frequency changes between phrases. Over 90% of individuals sang 1 of 5 song types, and we found clear dialect structure composed of these 5 common song types. The geographic range of dialects spanned large distances (500 to 1,700 km), resembling the geographic structure of dialects in the long-distance migrant Gambel's White-crowned Sparrow (Z. l. gambelli), though locations of dialect boundaries differ between species. Because both Golden-crowned Sparrows and Gambel's White-crowned Sparrows migrate similarly long distances, our study provides support to the hypothesis that dialect range size correlates with migration distance. We found little evidence of change in dialect composition in 4 populations that were sampled 15 years apart, which suggests that the dialect structure is stable across multiple generations. Our study opens the door for further comparisons to investigate links between ecology and the emergence of song dialects in this well-studied genus.

Migratory connectivity of Golden-crowned Sparrows from two wintering regions in California

“…A recent analysis demonstrated that across the breeding range, Golden-crowned Sparrows exhibit at least 5 major song types, with individuals breeding on the Gulf Coast of Alaska having a distinctly different song from those in the interior [11]. The different songs, combined with distinct migratory routes suggest that the individuals from these two wintering locations may exhibit differences that extend beyond their migratory tendencies.…”

“…Sparrows have distinct vocalization types [11], suggesting the possibility of a complex population structure, rather than a simple panmictic population. In our preceding study with light-level geolocators, we showed that four Goldencrowned Sparrows that wintered on the coast of California migrated to breeding sites along the Gulf Coast of Alaska [12].…”

The role of early acoustic experience in song discrimination

“…All nestlings in a nest (2-6 per 140 nest, mean 4.2) were temporarily removed and randomly assigned to one of two playback treatments (golden-crowned or white-crowned sparrow song), each consisting of 6 stimulus files created from a unique recording of a different individual male to avoid pseudoreplication (recorded >6 years prior at sites >100km away). These golden-crowned sparrow song recordings are of the same dialect type that males at this study site produce 52 , and have been effective at 145 eliciting strong responses from adult males and nestlings in this population previously 42,43 . As in 40,43 , each stimulus file consisted of one minute of white noise, two minutes of song presentation (the same song recording repeated every 10s), and an additional minute of white noise.…”

Chipper: Open‐source software for semi‐automated segmentation and analysis of birdsong and other natural sounds

“…Often, behavioural studies involve laboratory observations, which can lead to fundamental insights but may disrupt natural animal behaviour (Fehér, Wang, Saar, Mitra, & Tchernichovski, ; Marler & Peters, ; Searcy, ). In addition, scientists can collect acoustic sounds in the wild without disturbing animals, eliminating potential influences of the laboratory environment on behaviour but limiting the types of experiments possible (Grant & Grant, ; Lachlan, Ratmann, & Nowicki, ; Shizuka, Ross Lein, & Chilton, ; Williams, Levin, Ryan Norris, Newman, & Wheelwright, ). Moreover, recordings can be pooled across sources—professionals and hobbyists, analogue and digital, old and new—providing vast datasets that span many years and large geographic scales (Bolus, ; Roach & Phillmore, ).…”