Using GPS and accelerometer data to remotely detect breeding events in two elusive ground-nesting steppe birds

• Type: Article in International Scientific Journal
• Date: 2024

Authors

Ferraz, G (Author) Other; Pacheco, C (Author) Other; Fernández-Tizón, M (Author) Other; Marques, AT (Author) Other; Alves, PC (Author) FCUP; Silva, JP (Author) Other; Mougeot, F (Author) Other

Journal

The Journal is awaiting validation by the Administrative Services.

Title: ANIMAL BIOTELEMETRY

Vol. 12

Indexing

ISI Web of Knowledge - 0 Citations

Scopus - 0 Citations

Other information

Authenticus ID: P-017-AG6

DOI: 10.1186/s40317-024-00385-y

Abstract (EN): 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. Results We 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.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 17