Abstract
ABSTRACT
Morphometric measurements are among the most important phenotypic traits in birds. However, traditional linear measurements can be invasive, are often limited to species that are easier to capture, may be constrained in challenging environments, and typically allow for lower sampling efficiency per unit time. We applied a digital photography approach based on the “pinhole camera model” using an experimental setup with four bird species. We assessed the performance of this approach by varying elevation angles, distances to the subject, and orientations relative to the focal plane to estimate body, tarsus, wing, and bill length. We then extended this approach to 37 bird species photographed in the field and compared our estimates with measurements derived from a global database and museum specimens. We evaluated the performance of single‐species trait estimation and the ability to infer community‐level metrics that incorporate trait diversity. Under optimal viewing conditions (0° relative to the focal plane), body and wing length showed the smallest biases in the experimental setting, ranging from approximately 1%–6% and 1%–9%, respectively. Tarsus and bill length exhibited larger biases, ranging from about 5%–12% and 2%–15%, respectively. We found strong correlations between traits derived from photographic measurements and those obtained from both the global database and our own museum specimens (
ρ
= 0.82–0.95). We found no differences in functional trait diversity metrics between photograph‐based estimates and those derived from the global database, but detected significant differences in assemblage‐level metrics based on museum measurements. Our approach enables robust estimation of linear measurements from a single image, using field‐acquired data, under specific conditions. We provide practical recommendations for applying the pinhole camera model to wild birds. It is straightforward to implement and generalizable across species, thereby enhancing its applicability and expanding opportunities to use camera images in novel ways in bird ecology and behavior.