A field guide for aging passerine nestlings using growth data and predictive modeling

Sanchez, Audrey A.; Bartlow, Andrew W.; Chan, Allison M.; Fair, Jeanne M.; Skinner, Aaron A.; Hutchins, Kelly; Musgrave, Maria A.; Phillips, Emily M.; Thompson, Brent E.; Hathcock, Charles D.

doi:10.1186/s40657-021-00258-5

A field guide for aging passerine nestlings using growth data and predictive modeling

Journal Article · Wed Jun 02 00:00:00 EDT 2021 · Avian Research

DOI:https://doi.org/10.1186/s40657-021-00258-5· OSTI ID:1785590

; Bartlow, Andrew W.; Chan, Allison M.; Fair, Jeanne M.; Skinner, Aaron A.; Hutchins, Kelly; Musgrave, Maria A.; Phillips, Emily M.; Thompson, Brent E.; Hathcock, Charles D.

Abstract Background

Accurate nestling age is valuable for studies on nesting strategies, productivity, and impacts on reproductive success. Most aging guides consist of descriptions and photographs that are time consuming to read and subjective to interpret. The Western Bluebird ( Sialia mexicana ) is a secondary cavity-nesting passerine that nests in coniferous and open deciduous forests. Nest box programs for cavity-nesting species have provided suitable nesting locations and opportunities for data collection on nestling growth and development.

Methods

We developed models for predicting the age of Western Bluebird nestlings from morphometric measurements using model training and validation. These were developed for mass, tarsus, and two different culmen measurements.

Results

Our models were accurate to within less than a day, and each model worked best for a specific age range. The mass and tarsus models can be used to estimate the ages of Western Bluebird nestlings 0–10 days old and were accurate to within 0.5 days for mass and 0.7 days for tarsus. The culmen models can be used to estimate ages of nestlings 0–15 days old and were also accurate to within less than a day. The daily mean, minimum, and maximum values of each morphometric measurement are provided and can be used in the field for accurate nestling age estimations in real time.

Conclusions

The model training and validation procedures used here demonstrate that this method can create aging models that are highly accurate. The methods can be applied to any passerine species provided sufficient nestling morphometric data are available.

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Research Organization:: Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)

Sponsoring Organization:: USDOE; USDOE National Nuclear Security Administration (NNSA)

Grant/Contract Number:: 89233218CNA000001

OSTI ID:: 1785590

Alternate ID(s):: OSTI ID: 1835759

Report Number(s):: LA-UR--19-23046; 28; PII: 258

Journal Information:: Avian Research, Journal Name: Avian Research Journal Issue: 1 Vol. 12; ISSN 2053-7166

Publisher:: ElsevierCopyright Statement

Country of Publication:: China

Language:: English

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Related Subjects

59 BASIC BIOLOGICAL SCIENCES
Cavity-nesting
Nest boxes
Nestling development
Predictive models
Western Bluebird

A field guide for aging passerine nestlings using growth data and predictive modeling

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References (34)

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