Spatial modelling of aerial survey data reveals an important European storm-petrel hotspot and its underlying drivers within the North-East Atlantic

Determining the distribution and population size of marine species is crucial for conservation and management. However, for many species, the abundance and at-sea distribution are poorly known because of their large geographic ranges, high mobility, and cryptic breeding habits. This is especially true for small pelagic seabirds such as the European storm-petrel. Large-scale observer-based aerial surveys were conducted over four summers in the North-East Atlantic extending 200 nautical miles from the coast of Ireland. Species distribution models were produced using generalised additive models with a combination of static and dynamic environmental variables to assess the impact of survey altitude on storm-petrel detectability, and to model their abundance and distribution. Reduced storm-petrel detectability was identified at higher survey altitudes and rougher seas, and an at-sea abundance of 154,044 (95% CI: 94,347 – 452,299) individuals was estimated. Our results reveal fine scale varia..., , , # **Spatial modelling of aerial survey data reveals important European storm-petrel hotspots and their underlying drivers within the North-East Atlantic**

[https://doi.org/10.5061/dryad.c2fqz61kc](https://doi.org/10.5061/dryad.c2fqz61kc)

## Description of the data and file structure

Offshore broad-scale and coastal fine-scale aerial surveys were conducted in the Irish Exclusive Economic Zone (EEZ) by a team of trained observers between May and September in 2015, 2016, 2021, and 2022, following a standard strip-transect methodology. All sightings of storm-petrels within 200m of the transect line on each side of the aircraft, and the group size, were recorded. Generalised Additive Models (GAMs) were used to predict the distribution and abundance of storm-petrels in the study area using this extensive survey dataset and a combination of static and dynamic predictor variables. 

### Files and variables

#### File: aerial\_survey\_data.zip

**Description:** Folder containing aerial survey...,