Search citation statements
Paper Sections
Citation Types
Year Published
Publication Types
Relationship
Authors
Journals
Background Modern biologging technologies allow researchers to gain a better understanding of animal movements, offering opportunities to measure survival and remotely study the breeding success of wild birds, i.e., by locating nests. This is particularly useful for species whose nests are difficult to find or access, or when disturbances can impact the breeding outcome. We developed and validated, with field data, a framework to detect nesting events by two sandgrouse species, the black-bellied (Pterocles orientalis) and pin-tailed sandgrouse (Pterocles alchata), using GPS and Overall Dynamic Body Acceleration (ODBA) data. Sandgrouses are ground-nesting, cryptic, and elusive birds with biparental incubation efforts. Because both sexes take turns to incubate, a novel framework considering when tagged individuals are on incubation duty or not needs to be designed to detect nests. ResultsWe tagged 52 birds with high-resolution GPS devices to monitor their breeding during 2021-24. Using remote tracking and field data from the first 2 years (2021-22), we first determined sex-specific time windows for incubation to maximise differentiation between incubation and non-incubation behaviours. We then used a threshold-based classification to identify incubation days and inferred the minimum number of successive incubation days needed to correctly identify a nesting event. We show how ODBA and GPS data can be used to successfully detect nests incubated for only 2 or 3 days. GPS-only data or combined GPS-ODBA data had a success rate of around 95%, whereas ODBA-only data had a success rate of 100%. Cross-validation using data from 2023 to 2024 confirmed the model's performance, showing an overall success > 90% for GPS-only and ODBA-only data and of 85% for combined GPS-ODBA data.Conclusions By accurately identifying nesting events, our framework offers new opportunities to study the breeding of conservation-dependent species. Besides its applicability to ground-nesting species with biparental care and sex-specific incubation schedules, the framework can be adapted to other bird species sensitive to disturbances or with inaccessible nesting sites. By doing so, it reduces the need for nest visits and associated disturbances, as well as the carbon footprint and expenses associated with fieldwork.
Background Modern biologging technologies allow researchers to gain a better understanding of animal movements, offering opportunities to measure survival and remotely study the breeding success of wild birds, i.e., by locating nests. This is particularly useful for species whose nests are difficult to find or access, or when disturbances can impact the breeding outcome. We developed and validated, with field data, a framework to detect nesting events by two sandgrouse species, the black-bellied (Pterocles orientalis) and pin-tailed sandgrouse (Pterocles alchata), using GPS and Overall Dynamic Body Acceleration (ODBA) data. Sandgrouses are ground-nesting, cryptic, and elusive birds with biparental incubation efforts. Because both sexes take turns to incubate, a novel framework considering when tagged individuals are on incubation duty or not needs to be designed to detect nests. ResultsWe tagged 52 birds with high-resolution GPS devices to monitor their breeding during 2021-24. Using remote tracking and field data from the first 2 years (2021-22), we first determined sex-specific time windows for incubation to maximise differentiation between incubation and non-incubation behaviours. We then used a threshold-based classification to identify incubation days and inferred the minimum number of successive incubation days needed to correctly identify a nesting event. We show how ODBA and GPS data can be used to successfully detect nests incubated for only 2 or 3 days. GPS-only data or combined GPS-ODBA data had a success rate of around 95%, whereas ODBA-only data had a success rate of 100%. Cross-validation using data from 2023 to 2024 confirmed the model's performance, showing an overall success > 90% for GPS-only and ODBA-only data and of 85% for combined GPS-ODBA data.Conclusions By accurately identifying nesting events, our framework offers new opportunities to study the breeding of conservation-dependent species. Besides its applicability to ground-nesting species with biparental care and sex-specific incubation schedules, the framework can be adapted to other bird species sensitive to disturbances or with inaccessible nesting sites. By doing so, it reduces the need for nest visits and associated disturbances, as well as the carbon footprint and expenses associated with fieldwork.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.