Machine learning reveals that climate, geography, and cultural drift all predict bird song variation in coastal Zonotrichia leucophrys DOI
Jiaying Yang, Bryan C. Carstens, Kaiya L. Provost

и другие.

Ornithology, Год журнала: 2023, Номер 141(2)

Опубликована: Дек. 19, 2023

Abstract Previous work has demonstrated that there is extensive variation in the songs of White-crowned Sparrow (Zonotrichia leucophrys) throughout species range, including between neighboring (and genetically distinct) subspecies Z. l. nuttalli and pugetensis. Using a machine learning approach to bioacoustic analysis, we demonstrate song correlated with year recording (representing cultural drift), geographic distance, climatic differences, but response subspecies- season-specific. Automated methods bird annotation can process large datasets more efficiently, allowing us examine 1,913 recordings across ~60 years. We utilize recently published artificial neural network automatically annotate vocalizations. By analyzing differences syllable usage composition, recapitulate known pattern where pugetensis have significantly different songs. Our results are consistent interpretation these caused by changes characteristics syllables repertoire. This supports hypothesis evolution vocalization behavior affected environment, addition population structure.

Язык: Английский

Influence of start-up modes on the noise characteristics of mixed-flow pump during start-up process DOI
Guojun Zhu,

Yifan Xuan,

Jianjun Feng

и другие.

Mechanical Systems and Signal Processing, Год журнала: 2024, Номер 214, С. 111388 - 111388

Опубликована: Март 30, 2024

Язык: Английский

Процитировано

1
A limit to sustained performance constrains trill length in birdsong DOI Creative Commons
Javier Sierro, Selvino R. de Kort, Ian R. Hartley

и другие.

iScience, Год журнала: 2023, Номер 26(11), С. 108206 - 108206

Опубликована: Окт. 14, 2023

In birds, song performance determines the outcome of contests over crucial resources. We hypothesized that 1) sustained is limited within song, resulting in a decline towards end and 2) impact length compromised if declines. To test these hypotheses, we analyzed songs 597 bird species (26 families) conducted playback experiment on blue tits (

Язык: Английский

Процитировано

2
Listening to trees in the forest: Attentional set influences how semantic and acoustic factors interact in auditory perception DOI
Veronica Dudarev,

Jamie W. Kai,

Noor Brar

и другие.

Attention Perception & Psychophysics, Год журнала: 2024, Номер unknown

Опубликована: Янв. 4, 2024

Язык: Английский

Процитировано

0
Machine learning reveals that climate, geography, and cultural drift all predict bird song variation in coastal Zonotrichia leucophrys DOI
Jiaying Yang, Bryan C. Carstens, Kaiya L. Provost

и другие.

Ornithology, Год журнала: 2023, Номер 141(2)

Опубликована: Дек. 19, 2023

Abstract Previous work has demonstrated that there is extensive variation in the songs of White-crowned Sparrow (Zonotrichia leucophrys) throughout species range, including between neighboring (and genetically distinct) subspecies Z. l. nuttalli and pugetensis. Using a machine learning approach to bioacoustic analysis, we demonstrate song correlated with year recording (representing cultural drift), geographic distance, climatic differences, but response subspecies- season-specific. Automated methods bird annotation can process large datasets more efficiently, allowing us examine 1,913 recordings across ~60 years. We utilize recently published artificial neural network automatically annotate vocalizations. By analyzing differences syllable usage composition, recapitulate known pattern where pugetensis have significantly different songs. Our results are consistent interpretation these caused by changes characteristics syllables repertoire. This supports hypothesis evolution vocalization behavior affected environment, addition population structure.

Язык: Английский

Процитировано

1