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Factors influencing nest site selection of the Laughing Dove (Spilopelia senegalensis) in an urban area in Karaj, Iran Cover

Factors influencing nest site selection of the Laughing Dove (Spilopelia senegalensis) in an urban area in Karaj, Iran

Open Access
|Dec 2024

Abstract

Urban habitats are rapidly changing, making the conservation and management of species adapted to these environments challenging. Nest site selection is a pivotal point in the process of habitat selection and breeding for bird species. We measured 10 structural and spatial characteristics at 32 nest presence sites and 64 randomly selected nest absence sites of Laughing Doves (Spilopelia senegalensis) in an urban environment in Karaj, Iran. To model the nest site selection, we performed spline binary logistic regression. Two variables significantly influenced the nest site selection of Laughing Doves: nest height above ground, with an optimal range of ~286–347 cm, and nest concealment, favoring invisible places from the front and sides. Distance to opposite building, with an optimal range of ~16–34 m, was marginally significant. Additionally, we surveyed the feasibility of occupying artificial nestboxes (n = 17) by Laughing Doves between February and September 2019. The occupancy rate of the artificial nestboxes was ~35%. Overall, these results suggest that despite the relatively high structural heterogeneity of our urban environment, Laughing Doves exhibit distinct preferences for certain nest site characteristics, which may reflect a dependence on close proximity to humans for safety and access to food and water.

DOI: https://doi.org/10.2478/orhu-2024-0026 | Journal eISSN: 2061-9588 | Journal ISSN: 1215-1610
Language: English
Page range: 117 - 137
Submitted on: Sep 5, 2024
Accepted on: Oct 14, 2024
Published on: Dec 8, 2024
Published by: MME/BirdLife Hungary
In partnership with: Paradigm Publishing Services
Publication frequency: 2 issues per year

© 2024 Morteza Banisaffar, Afshin Alizadeh Shabani, published by MME/BirdLife Hungary
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.