Habitat geometry rather than visual acuity limits the visibility of a ground-nesting bird's clutch to terrestrial predators

• Main Authors: Hancock, George, Grayhson, Lizzie, Burrell, Ryan, Cuthill, Innes, Hoodless, Andrew, Troscianko, Jolyon
• Format: Dataset
• Language: unknown
• Published: 2023
• Subjects: camouflage; 3D scanning; occlusion; ground-nesting birds; lapwing; Vanellus vanellus
• Online Access: https://zenodo.org/record/8270340; https://doi.org/10.5061/dryad.wm37pvmtb

The nests of ground-nesting birds rely heavily on camouflage for their survival, and predation risk, often linked to ecological changes from human activity, is a major source of mortality. Numerous ground-nesting bird populations are in decline, so understanding the effects of camouflage on their nesting behaviour is of relevance to their conservation concern. Habitat three-dimensional (3D) geometry together with predator visual abilities, viewing distance, and viewing angle determine whether a nest is either visible, occluded or too far away to detect. While this link is intuitive, few studies have investigated how fine-scale geometry is likely to help defend nests from different predator guilds. We quantified nest visibility based on 3D occlusion, camouflage, and predator visual modelling in northern lapwing, Vanellus vanellus, on different land management regimes. Lapwings selected local backgrounds that had a higher 3D complexity at a spatial scale greater than their entire clutches compared to local control sites. Importantly, our findings show that habitat geometry – rather than predator visual acuity – restricts nest visibility to terrestrial predators, and that their field habitats perceived by humans as open are functionally closed with respect to a terrestrial predator searching for nests on the ground. Taken together with lapwings' careful nest site selection, our findings highlight the importance of considering habitat geometry for understanding the evolutionary ecology and management of conservation sites for ground-nesting birds. Running the statistical analyses requires the R code and data frames for 3D and colour measures, stored in the same folder layout as provided for the zip. Simply set the working directory for the R script to the same folder. Example 3D scans and .mspecs are also provided, requiring ImageJ and version 2.2.0 to open. All scripts for our 3D analyses are provided on our GitHub: https://github.com/GeorgeHancock471/3D_RNL_Tools. To open our .mspecs requires the installation of ...