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64 results for “bird song”
UCSB SONGS Mitigation Monitoring: Wetland Performance Standard - Bird Abundance and Species Richness
These data describe the annual estimates of bird density and richness (as a species density) in twenty plots at four coastal wetlands as part of the SONGS San Dieguito Wetland Restoration monitoring program to track long-term patterns in species abundance and diversity. This study began in 2012 in the San Dieguito Wetlands and Tijuana Estuary in San Diego County, CA, Carpinteria Salt Marsh in Santa Barbara County, CA, and Mugu Lagoon in Ventura County, CA. Beginning in 2024, Tijuana Estuary was replaced with Los Penasquitos Lagoon in San Diego County, CA.
UCSB SONGS Mitigation Monitoring: Wetland Performance Standard - Bird Food Chain Support
These data describe annual estimates of the density of feeding birds at four coastal wetlands as part of the SONGS San Dieguito Wetland Restoration monitoring program to track long-term patterns in food chain support provided to birds. This study began in 2012 in the San Dieguito Wetlands and Tijuana Estuary in San Diego County, CA, Carpinteria Salt Marsh in Santa Barbara County, CA, and Point Mugu Lagoon in Ventura County. Beginning in 2024, Tijuana Estuary was replaced with Los Penasquitos Lagoon in San Diego County, CA.
UCSB SONGS Mitigation Monitoring: Wetland Survey - Bird Abundance
These data describe annual estimates of bird density collected as part of the SONGS San Dieguito Wetland Restoration mitigation monitoring program designed to evaluate compliance of the restoration project with conditions of the SONGS permit. Monitoring began in 2012 in the San Dieguito Wetlands and Tijuana Estuary in San Diego County, CA, Carpinteria Salt Marsh in Santa Barbara County, CA, and Mugu Lagoon in Ventura County, CA. Los Penasquitos Lagood in San Diego County replaced Tijuana Estuary in 2024. The abundance of birds is determined from twenty plots spread across each wetland.
UCSB SONGS Mitigation Monitoring: Wetland Survey - Bird Feeding Activity
These data describe annual estimates of shorebird bird feeding activity, measured as the percentage of birds observed feeding, collected as part of the SONGS San Dieguito Wetland Restoration mitigation monitoring program designed to evaluate compliance of the restoration project with conditions of the SONGS permit. Monitoring began in 2012 in the San Dieguito Wetlands and Tijuana Estuary in San Diego County, CA, Carpinteria Salt Marsh in Santa Barbara County, CA, and Point Mugu Lagoon in Ventura County. Bird feeding activity was estimated for twenty plots in each wetland having at least one targeted shorebird species present on the ground. Beginning in 2024, Tijuana Estuary was replaced with Los Penasquitos Lagoon in San Diego County, CA.
Male song structure predicts offspring recruitment to the breeding population in a migratory bird
<p>Bird song is a classic example of a sexually selected trait, but much of the work relating individual song components to fitness has not accounted for song typically being composed of multiple, often-correlated components, necessitating a multivariate approach. We explored the role of sexual selection in shaping complex male song of house wrens (<em>Troglodytes aedon</em>) by simultaneously relating its multiple components to fitness using multivariate selection analysis, which is widely used in insect and anuran studies but not in birds. The analysis revealed significant variation in the form and strength of selection acting on song across different selection episodes, from nest-site defense to recruitment of offspring to the breeding population. Males that sang more song typically employed in close communication sired more offspring that were subsequently recruited to the breeding population than those that sang far-communication song. However, this relationship was not consistent across earlier selection episodes, as evidenced by non-linear selection acting on these song components in other contexts. Collectively, our results present a complex picture of multivariate selection on male song structure that would not be evident using univariate approaches and suggest possible trade-offs within and among song components at different points of the breeding season. </p>
Machine learning reveals that climate, geography, and cultural drift all predict bird song variation in coastal Zonotrichia leucophrys
<p>Previous work has demonstrated that there is extensive variation in the songs of White-crowned Sparrow (<em>Zonotrichia leucophrys</em>) throughout the species range, including between neighboring (and genetically distinct) subspecies <em>Z. l. nuttalli </em>and <em>Z. l. pugetensis</em>. Using a machine learning approach to bioacoustic analysis, we demonstrate that variation in song is correlated with year of recording (representing cultural drift), geographic distance, and climatic differences, but the response is subspecies- and season-specific. Automated machine learning methods of bird song annotation can process large datasets more efficiently, allowing us to examine 1,913 recordings across ~60 years. We utilize a recently published artificial neural network to automatically annotate White-crowned Sparrow vocalizations. By analyzing differences in syllable usage and composition, we recapitulate the known pattern where <em>Z. l. nuttalli </em>and <em>Z. l. pugetensis </em>have significantly different songs. Our results are consistent with the interpretation that these differences are caused by the changes in characteristics of syllables in the White-crowned Sparrow repertoire. This supports the hypothesis that the evolution of vocalization behavior is affected by the environment, in addition to population structure.</p>
Fig. 1 in Growth Processes In The Postembryonic Development In Altricial Birds On The Example Of Song Thrush, Turdus Philomelos (Passeriformers, Turdidae): A Multivariate Approach
Fig. 1. Distribution of centroids for the age-based song thrush samples in the factor space of PC1 and PC2 (figs 1–13 denote nestling's age in days).
Fig. 3 in Growth Processes In The Postembryonic Development In Altricial Birds On The Example Of Song Thrush, Turdus Philomelos (Passeriformers, Turdidae): A Multivariate Approach
Fig. 3. Results of comparison of 20 morphometric traits (1–20) in nestlings of song thrush according to their DRPI and dynamics of growth processes. Numbers of traits as given in table 1.
Cumulative cultural evolution and mechanisms for cultural selection in wild bird songs
<p>Cumulative cultural evolution, the accumulation of sequential changes within a single socially learned behaviour that results in improved function, is prominent in humans and has been documented in experimental studies of captive animals and managed wild populations. Here, we provide evidence that cumulative cultural evolution has occurred in the learned songs of Savannah sparrows. In a first step, "click trains" replaced "high note clusters" over a period of three decades. We use mathematical modeling to show that this replacement is consistent with the action of selection, rather than drift or frequency-dependent learning biases. Generations later, young birds elaborated the "click train" song form by adding more clicks. We show that the new songs with more clicks elicit stronger behavioural responses from both males and females. Therefore, we suggest that a combination of social learning, innovation, and sexual selection favoring a specific discrete trait was followed by directional sexual selection that resulted in naturally occurring cumulative cultural evolution in the songs of this wild animal population.</p>
Song varies with latitude, climate, and species richness in a Neotropical bird
<p>Animals can encode information within acoustic signals, particularly, bird songs can be remarkably complex and can indicate individual identity and quality. Two main sets of hypotheses attempt to explain the evolution of increased birdsong complexity across large-scale geographic ranges: (1) larger acoustic space availability, and (2) greater sexual selection intensity, both of which would favor the evolution of more complex songs at higher latitudes, more seasonal and/or species-poor environments. However, few studies have assessed patterns of song complexity for birds with broad geographic ranges. Here, we determined patterns of song variation in the blue-black grassquit (<em>Volatinia jacarina</em>), considering metrics of song complexity, structure and performance. This Neotropical bird occurs from Mexico to Argentina and produces a monosyllabic song. Using recordings from online databases, we calculated song metrics, such as bandwidth, song rate, number of song components, and proportion of vibratos of this signal. We found that song features varied with latitude, climate seasonality, bird species richness and hemisphere. However, contrary to theoretical predictions, complexity mostly decreased with latitude and greater seasonality, while it was positively correlated with bird species richness. Proportion of vibratos was positively correlated with latitude and seasonality, and may be a feature under sexual selection in this species. Overall, our results did not support the main hypotheses proposed as explanations for song complexity. Our findings also highlight that song complexity does not vary uniformly among songbirds and song parameters, and future studies encompassing more species should clarify patterns and drivers of song variation across broad geographic dimensions.</p>
Manually labeled Bird song dataset of 22 species from Xeno-canto to enhance deep learning acoustic classifiers with contextual information.
<p>Data accompanying the paper: Jeantet and Dufourq (2023). Empowering Deep Learning Acoustic Classifiers with Human-like Ability to Utilize Contextual Information for Wildlife Monitoring. <em>Ecological Informatics</em>. 77, 15749541, DOI: 10.1016/j.ecoinf.2023.102256</p> <p> </p> <p>Our investigation contributes to the field of deep learning and bioacoustics by highlighting the potential for improved classification performance through the incorporation of contextual information such as time and location.</p> <p>To test if spatial-temporal information can enhance deep learning classifier, we developed a subset dataset derived from Xeno-Canto that included location metadata as input alongside the spectrogram. We used this dataset with the primary purpose of creating a bird song classification task with species carefully selected to share similar vocal characteristics but from distinct geographical distributions. We only considered the recordings of category `A', corresponding to the best quality score in the database.</p> <p>The dataset contains songs of <strong>22 bird species</strong> from 5 families and genera differents. The recordings were downloaded from the Xeno-canto database in .wav format and each recording was <strong>manually annotated </strong>by labelling the start and stop time for every vocalisation occurrence using Sonic Visualiser. In total, database contained 6537 occurrences of bird songs of various length from <strong>967 file recordings</strong>. A precise description of the distribution by species and country can be found in the associated article.</p> <p> </p> <p>The audio files are provided in "Audio.zip" and the manually verified annotation in "Annotations.zip". The name of each file follows the following nomenclature: Family_genus_species_country of recording_date of recording_ID Xenocanto_type of song.wav/svl. The meta-data information of each file can be find in the csv file provided (Xenocanto_metadata_qualityA_selection) based on the number of the ID Xeno-canto. The annotations can be viewed using the Sonic Visualiser software. The python codes to process these files and train neural networks can be found here : github</p> <p>The files were divided into a <strong>training folder</strong> and a<strong> validation folder</strong> to train and evaluate the efficiency of each method. For each species and country, we randomly selected 70% of the downloaded recordings for the training dataset and kept the remaining 30% for validation.</p> <p><strong>Process to select the species</strong> : We selected the ten most recorded families in the Passeriformes order, the most represented order in Xeno-canto database. From each of the ten families, we again sub-samples the ten most recorded genera. For each genus, we observed the countries of the recordings and the number of available recordings per species and countries. From these observations, we made a self-selection of genera containing species with similar songs but recorded in different regions, with enough recordings available by species and country to form a dataset . At the end, 5 genus were selected containing 22 species. We considered only recordings associated with bird songs, specifically, within Xeno-canto we selected the `song' type. To balance the number of recordings between species of the same genus, we reduced the number of recordings for the most represented species. Thus, for each genus we calculated the average of the number of records available per species and per country and limited the number of recordings for the species/country pairs that were in greater number to this value plus two.</p> <p> </p> <p> </p> <p> </p>
Song varies with latitude, climate, and species richness in a Neotropical bird
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Cumulative cultural evolution and mechanisms for cultural selection in wild bird songs
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Male song structure predicts offspring recruitment to the breeding population in a migratory bird
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Machine learning reveals that climate, geography, and cultural drift all predict bird song variation in coastal Zonotrichia leucophrys
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Data from: Evolution and plasticity: divergence of song discrimination is faster in birds with innate song than in song learners in Neotropical passerine birds
Plasticity is often thought to accelerate trait evolution and speciation. For example, plasticity in birdsong may partially explain why clades of song learners are more diverse than related clades with innate song. This "song learning" hypothesis predicts that 1) differences in song traits evolve faster in song learners, and 2) behavioral discrimination against allopatric song (a proxy for premating reproductive isolation) evolves faster in song learners. We tested these predictions by analyzing acoustic traits and conducting playback experiments in allopatric Central American sister pairs of song learning oscines (N = 42) and non-learning suboscines (N = 27). We found that non-learners evolved mean acoustic differences slightly faster than did leaners, and that the mean evolutionary rate of song discrimination was 4.3 times faster in non-learners than in learners. This unexpected result may be a consequence of significantly greater variability in song traits in song learners (by 54–79%) that requires song-learning oscines to evolve greater absolute differences in song before achieving the same level of behavioral song discrimination as non-learning suboscines. This points to "a downside of learning" for the evolution of species discrimination, and represents an important example of plasticity reducing the rate of evolution and diversification by increasing variability.
Male song stability shows cross-year repeatability but does not affect reproductive success in a wild passerine bird
<p>Predictable behaviour (or "behavioural stability") might be favoured in certain ecological contexts, e.g. when representing a quality signal. Costs associated with producing stable phenotypes imply selection should favour plasticity in stability when beneficial. Repeatable among-individual differences in degree of stability are simultaneously expected if individuals differ in ability to pay these costs, or in how they resolve cost-benefit trade-offs. Bird song represents a prime example, where stability may be costly yet beneficial when stable singing is a quality signal favoured by sexual selection. Assuming energetic costs, ecological variation (e.g. in food availability) should result in both within- and among-individual variation in stability. If song stability represents a quality signal, we expect directional selection favouring stable singers. For a three-year period, we monitored 12 nest box plots of great tits Parus major during breeding. We recorded male songs during simulated territory intrusions, twice during their mate's laying stage, and twice during incubation. Each preceding winter, we manipulated food availability. Assuming that stability is costly, we expected food-supplemented males to sing more stable songs. We also expected males to sing more stable songs early in the breeding season (when paternity is not decided), and stable singers to have increased reproductive success. We found strong support for plasticity in stability for two key song characteristics: minimum frequency and phrase length. Males were plastic because they became more stable over the season, contrary to expectations. Food-supplementation did not affect body condition but increased stability in minimum frequency. This treatment effect occurred only in one year, implying that food supplementation affected stability only in interaction with (unknown) year-specific ecological factors. We found no support for directional, correlational, or fluctuating selection on the stability in minimum frequency (i.e., the song trait whose stability exhibited cross-year repeatability): stable singers did not have higher reproductive success. Our findings imply that stability in minimum frequency is not a fitness quality indicator unless males enjoy fitness benefits via pathways not studied here. Future studies should thus address the mechanisms shaping and maintaining individual repeatability of song stability in the wild.</p>
Machine Learning for Bird Song Learning (ML4BL) dataset
<p><strong>General description</strong></p> <p>This dataset contains Zebra Finch decisions about perceptual similarity on song units. All the data and files are used for reproducing the results of the paper 'Bird song comparison using deep learning trained from avian perceptual judgments' by the same authors. </p> <p><strong>Git repo on Zenodo:</strong> <a href="https://doi.org/10.5281/zenodo.5545932">https://doi.org/10.5281/zenodo.5545932</a><br> <strong>Git repo access: </strong><a href="https://github.com/veronicamorfi/ml4bl/tree/v1.0.0">https://github.com/veronicamorfi/ml4bl/tree/v1.0.0</a></p> <p><strong>Directory organisation:</strong><br> ML4BL_ZF<br> |_files<br> |_Final_probes_20200816.csv - all trials and decisions of the birds (aviary 1 cycle 1 data are removed from experiments)<br> |_luscinia_triplets_filtered.csv - triplets to use for training<br> |_mean_std_luscinia_pretraining.pckl - mean and std of luscinia triplets used for trianing<br> |_*_cons_* - % side consistency on triplets (train/test) - train set contains both train and val splits<br> |_*_gt_* - cycle accuracy for triplets of the specific bird (train/test) - train set contains both train and val splits<br> |_*_trials_* - number of decisions made for a triplet (train/test) - train set contains both train and val splits<br> |_*_triplets_* - triplet information (aviary_cycle-acc_birdID, POS, NEG, ANC) (train/test) - train set contains both train and val splits<br> |_*_low*_ - low-margin (ambiguous) triplets (train/val/test)<br> |_*_high_ - high-margin (unambiguous) triplets (train/val/test)<br> |_*_cycle_bird_keys_* - unique aviary_cycle-acc_birdID keys (train/test) - train set contains both train and val splits<br> |_TunedLusciniaV1e.csv - pairwise distance of two recordings computed by Luscinia<br> |_training_setup_1_ordered_acc_single_cons_50_70_trials.pckl - dictionary containing everything needed for training the model (keys: 'train_keys', 'train_triplets', 'val_keys', 'vali_triplets', 'test_triplets', 'test_keys', 'train_mean', 'train_std')<br> |_melspecs - *.pckl - melspectrograms of recordings<br> |_wavs - *wav - recordings<br> |_README.txt</p> <p><strong>Recordings</strong></p> <p>887 syllables extracted from zebra finch song recordings, with a sampling rate of 48kHz and high pass filtered (100Hz), with a 20ms intro/outro fade. </p> <p><strong>Decisions</strong></p> <p>Triplets were created from the recordings and the birds made side based decisions about their similarity (see 'Bird song comparison using deep learning trained from avian perceptual judgments' for further information).</p> <p><strong>Training dictionary Information</strong></p> <p>Dictionary keys:<br> 'train_keys', 'train_triplets', 'val_keys', 'vali_triplets', 'test_triplets', 'test_keys', 'train_mean', 'train_std'</p> <p>train_triplets/vali_triplets/test_triplets: <br> Aviary_Cycle_birdID, POS, NEG, ANC, Decisions, Cycle_ACC(%), Consistency(%)<br> <br> train_keys/val_keys/test_keys:<br> Aviary_Cycle_birdID</p> <p>train_mean/train_std:<br> shape: (1, mel_bins)</p> <p> </p> <p><strong>Open Access</strong></p> <p>This dataset is available under a Creative Commons Attribution 4.0 International (CC BY 4.0) license.</p> <p><br> <strong>Contact info</strong></p> <p>Please send any questions about the recordings to:<br> Lies Zandberg: Elisabeth.Zandberg@rhul.ac.uk</p> <p>Please send any feedback or questions about the code and the rest of the data to:<br> Veronica Morfi: g.v.morfi@qmul.ac.uk</p>
Ecological and evolutionary drivers of geographic variation in songs of a Neotropical suboscine bird: The Drab-breasted Bamboo Tyrant (Hemitriccus diops, Rhynchocyclidae)
<p>Understanding the evolutionary and ecological mechanisms that shape the spatial divergence of signals involved in reproductive isolation is a central goal in studies of speciation. For birds with innate songs, such as the suboscine passerine birds, the integration and comparison of both genetic and ecological factors in explaining song variation at the microevolutionary scale is rare. Here we evaluated the evolutionary and ecological processes underlying the variation in the songs of the Atlantic Forest endemic Drab-breasted Bamboo Tyrant (<i>Hemitriccus diops</i>), testing the effects of both stochastic and adaptive processes, namely the Stochastic and Adaptation Acoustic Hypotheses, respectively. We combined vocal, genetic and ecological (climate and forest cover) data across the species' range. To this end, we analyzed 89 samples of long and short songs. We performed analyses on raw and synthetic data song variables with linear mixed models and multivariate statistics. Our results show that both song types differ in spectral features between the two extant phylogeographic lineages of this species, but such vocal divergence is weak and subtle in both song types. Overall, there is a positive relationship of acoustic distances with the amount of forest cover in long songs. Our results suggest that there is cryptic geographical variation in both song types and that this variation is associated with low levels of genetic divergence in both songs and with ecological factors in long songs.</p>
Data for: Male-specific nocturnal song functions similar to day song in a diurnal bird species
<p class="MsoNormal">Historically, birdsong research has been biased towards song of male birds at dawn and during the day, even though some diurnal birds sing at night. To address this gap, we studied how song in the willie wagtail, <em>Rhipidura leucophrys</em>—a diurnal species with prolific male-specific nocturnal song during the breeding season—varies with time of day, breeding status, and simulated intrusions. <span>We recorded male nocturnal and dawn song over three breeding seasons and examined how this related to fertile and non-fertile breeding stages of females. To test whether song functions for territory defence, we simulated territorial intrusion experimentally in both sexes with daytime and nighttime playback of male and female song. To test whether nocturnal song could function for mate guarding or post-pairing mate attraction, we describe the mating system of willie wagtails using molecular genetic methods. We showed that both nocturnal and daytime song of male willie wagtails has roles in mate attraction and territory defence, while daytime song by females functioned primarily for territorial defence. </span>Males increased song behaviour during fertile periods of resident females, suggesting possible roles in mate stimulation and mate guarding. <span>Males and females responded similarly to simulated daytime intrusions and no differences were seen in male responses dependent on the time of day.</span> We found 10%-14% of offspring were fathered by extra-pair males, suggesting song may also function for mate guarding and post-pairing mate attraction<span>.</span><span> In a species with small repertoires and simple songs like the willie wagtail, differences between males in overall song output achieved through nocturnal singing may be important in mate attraction and territory defence.</span></p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.