MétaCan
Menu
Retour à la cohorte
Enregistrement W4394146504 · doi:10.6084/m9.figshare.14104829

Data from: Natal experience and pre-breeding environmental conditions affect lay date plasticity in Savannah sparrows

2021· dataset· en· W4394146504 sur OpenAlexaboutno aff
Joseph B. Burant, Eric W. Heisey, Nathaniel T. Wheelwright, Amy E. M. Newman, Shannon Whelan, Daniel J. Mennill, Stéphanie M. Doucet, Greg W. Mitchell, Bradley K. Woodworth, D. Ryan Norris

Notice bibliographique

RevueFigshare · 2021
Typedataset
Langueen
DomaineEnvironmental Science
ThématiqueAvian ecology and behavior
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésAffect (linguistics)GeographyEcologyBiologyPsychologyCommunication

Résumé

récupéré en direct d'OpenAlex

<b>Summary</b>The repository includes the data and R script for performing an analysis of among- and within-individual differences in the timing of first nesting attempts of the year in natal and pre-breeding environmental conditions (see reference). The data come from a long-term study of the demography of Savannah sparrows (<i>Passerculus sandwichensis</i>) breeding on Kent Island, New Brunswick, Canada (44.58°N, 66.76°W). Climate data were taken from an Environment and Climate Change Canada weather station at the airport in Saint John, NB (45.32°N, 65.89°W; https://www.climate.weather.gc.ca)<br><b>Datasets</b><b>(1)</b> SAVS_all_nests_samp.csv: contains summary information for all nest attempts observed for all females included in the analysis (i.e., including both first-of-year and subsequent lay dates).<b>(2)</b> SAVS_first_nest_per_year_samp.csv: contains detailed information on the first nesting attempt by each female Savannah sparrow monitored in the population over the course of the study (1987-2019, excluding the years 2005-2007; see <i>Methods: Study site and field sampling</i> in reference).<b>(3)</b> mean_daily_temperature.csv: contains mean daily temperature records from the ECCC weather station at Saint John, NB (see above). These mean daily temperatures were used in a climate sensitivity analysis to determine the optimum pre-breeding window on Kent Island.<b>(4)</b> SAVS_annual_summary.csv: contains annual summaries of average lay dates, breeding density, reproductive output, etc.<br><b>Variables</b>- female.id = factor; unique aluminum band number (USGS or Canadian Wildlife Service) assigned to each female- rain.categorical = binary (0 = low rainfall; 1 = high rainfall); groups females into low (81-171 mm) and high (172-378 mm) natal rainfall groups, based on the natal environmental conditions observed in each year (see <i>Methods: Statistical analysis</i> in reference)- year = integer (1987-2019); study year. The population on Savannah sparrows on Kent Island has been monitored since 1987 (excluding three years, 2005-2007)- nest.id = factor; an alpha-numeric code assigned to each nest; unique within years (the combination of year and nest.id would create a unique identifier for each nest)- fledglings = integer; number of offspring fledged from a nest- total.fledglings = integer; the total number of fledglings reared by a given female over the course of her lifetime- nest.attempts = integer; the total number of nest attempts per female (the number of nests over which the total number of fledglings is divided; includes both successful and unsuccessful clutches)<br>hatch.yday = integer; day of the year on which the first egg hatched in a given nestlay.ydate = integer; day of the year on which the first egg was laid in a given nestlay.caldate = date (dd/mm/yyyy); calendar date on which the first egg in a given nest was laidnestling.year = integer; the year in which the female/mother of a given nest was born- nestling.density = integer; the density of adult breeders in the year in which a given female (associated with a particular nest) was born- total.nestling.rain = numeric; cumulative rainfall (in mm) experienced by a female during the nestling period in her natal year of life (01 June to 31 July; see <i>Methods: Temperature and precipitation</i> data in reference)- years.experience = integer; number of previous breeding years per female in a particular year- density.total = integer; total number of adult breeders in the study site in a particular year- MCfden = numeric; mean-centred female density- MCbfden = numeric; mean-centred between-female density- MCwfden = numeric; mean-centred within-female density- mean.t.window = numeric; mean temperature during the identified pre-breeding window (03 May to 26 May; see Methods: Climate sensitivity analysis in reference)- MCtemp = numeric; mean-centred temperature during the optimal pre-breeding window- MCbtemp = numeric; mean-centred between-female temperature during the optimal pre-breeding window- MCwtemp = numeric; mean-centred within-female temperature during the optimal pre-breeding window- female.age = integer; age (in years) of a given female in a given year- MCage = numeric; mean-centred female age- MCbage = numeric; mean-centred between-female age- MCwage = numeric; mean-centred within-female age<br>- mean_temp_c = numeric; mean daily temperature in °C<br>- meanLD = numeric; mean lay date (in days of the year) across all first nest attempts in a given year- sdLD = numeric; standard deviation in lay date (in days of the year) across all first nest attempts in a given year- seLD = numeric; standard error n lay date (in days of the year) across all first nest attempts in a given year- meanTEMP = numeric; mean temperature (in °C) during the breeding period in a given year- records = integer; number of first nest attempts from each year included in the analysis- total.nestling.precip = numeric; total rainfall (in mm) during the nestling period (01 June to 31 July) in a given year- total.breeding.precip = numeric; total rainfall (in mm) during the breeding period (15 April to 31 July) in a given year- density.total = integer; total density of adult breeders on the study site in a given year- total.fledglings = integer; total number of offspring fledged by all breeders in the study site on a given year<br>- cohort.fecundity = numeric; average number of offspring per breeder in a given year<br><b>Code</b>code for Burant et al. - SAVS lay date plasticity analysis.RThe R script provided includes all the code required to import the data and perform the statistical analyses presented in the manuscript. These include:- t-tests investigating the effects of natal conditions (rain.categorical) on female age, nest attempts, and reproductive success- linear models of changes in temperature, precipitation, reproductive success, and population density over time, and lay dates in response to female age, density, etc.- a climate sensing analysis to identify the optimal pre-breeding window on Kent Island- mixed effects models investigating how lay dates respond to changes in within- and between-female age, density, and temperature<br><b>see readme.rtf for a list of datasets and variables.</b>

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesCharge utile insuffisante (le modèle a refusé de juger)
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Jeu de données · Signal consensuel: Jeu de données
Score de désaccord entre enseignants0,655
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,001
Science ouverte0,0010,003
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,6610,006

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,062
Tête enseignante GPT0,302
Écart entre enseignants0,240 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.

Devis d'étudeSans objet
Domainenon disponible
GenreJeu de données

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2021
Routes d'admission1
Résumé présentoui

Explorer davantage

Même revueFigshareMême sujetAvian ecology and behaviorTravaux en français237 207