Exploration of weather and tracking data for the wild bird abundance and movement models of the early warning system for avian influenza in the EU

Abstract Highly pathogenic avian influenza (HPAI) viruses pose a significant threat to both poultry and wild bird populations. Migratory wild birds play a key role in the intercontinental spread of avian influenza (AI), introducing the virus into poultry populations. In response to frequent AI outbreaks in Europe, the European Food Safety Authority (EFSA) is responsible for HPAI surveillance. A key component of this surveillance includes the integration of 1) outbreak data from Member States and 2) contributions from non‐governmental ornithological organisations like the European Bird Census Council (EBCC) and the European Union for Bird Ringing (EURING), in a predictive spatio‐temporal risk assessment model. Previous data integration and modelling efforts led to the development of an early warning system for predicting HPAI outbreaks accessible through a publicly available online user interface: the Bird Flu Radar. This system has since been improved by expanding the species coverage and refining the existing base models behind the epidemiological model. This report details a further refinement of these base models, by exploring the feasibility of using additional data sources in both the wild bird abundance and movement models. For the wild bird abundance model, weather data provided by the ERA5‐Land dataset was included, specifically the variables daily surface temperature (daily average, minimum and maximum) and snow cover. For the wild bird movement model, bird tracking data from Movebank was included for 19 of the 25 study species. For the remaining 6 study species no public data were available. The insights found for the abundance model, will support future study, understanding and prediction of the response of birds to fluctuating weather conditions. The insights found for the movement model provide a refinement and improvement of the estimates already derived from ring‐recovery data.

Authors

Institutions

Publication Details

Journal
EFSA Supporting Publications
Published
2025-04-01
DOI
https://doi.org/10.2903/sp.efsa.2025.en-9423
Citations
1
Primary Topic
Species Distribution and Climate Change
Type
article
Field-Weighted Citation Impact
1.84
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Exploration of weather and tracking data for the wild bird abundance and movement models of the early warning system for avian influenza in the EU

Stephen R. Baillie, Juan Gallego‐Zamorano, H. Sierdsema, Gabriel Gargallo et al.
1 citations
EFSA Supporting Publications
Species Distribution and Climate Change
1.84
article

Exploration of weather and tracking data for the wild bird abundance and movement models of the early warning system for avian influenza in the EU

Stephen R. Baillie, Juan Gallego‐Zamorano, H. Sierdsema, Gabriel Gargallo, Julia Stahl, Céline Faverjon, Robert A. Robinson, Roos Reinartz, Jacob Davies
article en
1 citations

Abstract

Abstract Highly pathogenic avian influenza (HPAI) viruses pose a significant threat to both poultry and wild bird populations. Migratory wild birds play a key role in the intercontinental spread of avian influenza (AI), introducing the virus into poultry populations. In response to frequent AI outbreaks in Europe, the European Food Safety Authority (EFSA) is responsible for HPAI surveillance. A key component of this surveillance includes the integration of 1) outbreak data from Member States and 2) contributions from non‐governmental ornithological organisations like the European Bird Census Council (EBCC) and the European Union for Bird Ringing (EURING), in a predictive spatio‐temporal risk assessment model. Previous data integration and modelling efforts led to the development of an early warning system for predicting HPAI outbreaks accessible through a publicly available online user interface: the Bird Flu Radar. This system has since been improved by expanding the species coverage and refining the existing base models behind the epidemiological model. This report details a further refinement of these base models, by exploring the feasibility of using additional data sources in both the wild bird abundance and movement models. For the wild bird abundance model, weather data provided by the ERA5‐Land dataset was included, specifically the variables daily surface temperature (daily average, minimum and maximum) and snow cover. For the wild bird movement model, bird tracking data from Movebank was included for 19 of the 25 study species. For the remaining 6 study species no public data were available. The insights found for the abundance model, will support future study, understanding and prediction of the response of birds to fluctuating weather conditions. The insights found for the movement model provide a refinement and improvement of the estimates already derived from ring‐recovery data.

EFSA Supporting PublicationsVol. 22(4)
Institut Català d'Ornitologia (ES), Dutch Centre for Field Ornithology (NL), British Trust for Ornithology (GB)
Openalex Percentile: Top 16%
Species Distribution and Climate Change
1.84
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.