A global dataset of spatiotemporal co-occurrence patterns of avian influenza virus-associated migratory birds

Jun Ma; Yan-He Wang; Yun-Bo Qiu; Jin-Jin Chen; Yun Han; Yan Zhang; Sheng-Hong Lin; Qing-Jie Wang; Long-Tao Chen; Xin-Jing Zhao; Sheng Zhang; Tian Tang; Yao Tian; Yu-Feng Yang; Qiang Xu; Zi-Da Meng; Chen-Long Lv; Guo-Lin Wang; Feng Hong; Li-Qun Fang

doi:10.1038/s41597-026-06701-w

. 2026 Feb 3;13:342. doi: 10.1038/s41597-026-06701-w

A global dataset of spatiotemporal co-occurrence patterns of avian influenza virus-associated migratory birds

Jun Ma ^1,^2,^#, Yan-He Wang ^3,^#, Yun-Bo Qiu ^1,^2,^#, Jin-Jin Chen ^2,⁴, Yun Han ^1,², Yan Zhang ², Sheng-Hong Lin ², Qing-Jie Wang ^1,², Long-Tao Chen ^1,², Xin-Jing Zhao ², Sheng Zhang ^1,², Tian Tang ², Yao Tian ², Yu-Feng Yang ², Qiang Xu ², Zi-Da Meng ², Chen-Long Lv ², Guo-Lin Wang ², Feng Hong ^1,^✉, Li-Qun Fang ^1,^2,^✉

PMCID: PMC12976375 PMID: 41634014

Abstract

Migratory birds facilitate the cross-regional spread of pathogens such as avian influenza virus (AIV). Interspecies interactions among multiple migratory bird species within shared spatiotemporal habitats can substantially enhance pathogen transmission and evolution, thereby posing potential risks to public health and livestock safety. Recent advances in tracking technologies, such as GPS, combined with publicly accessible databases like Movebank, have enabled the reconstruction of avian migratory pathways. However, existing tracking data are largely collected from individual species, remain species-specific and are insufficient for characterizing interspecies contact during migration. By integrating available tracking data from 62 migratory bird species (comprising 3,944 individual records), this study constructed a co-occurrence dataset comprising 50 migratory bird species that exhibited spatial and temporal overlap at shared locations, with a daily temporal resolution and spatial resolution aligned with first-level administrative divisions. This dataset can facilitate the identification of potential hotspots for migratory bird-associated pathogen evolution, thereby providing data-driven support for the prevention and control of emerging infectious diseases.

Subject terms: Animal migration, Behavioural ecology

Background & Summary

The migration of birds represents one of the most remarkable ecological phenomena in nature. Each year, thousands of migratory birds traverse continents and oceans to undertake regular migrations between their breeding and wintering grounds^1,2. This behavior serves as a crucial survival and reproduction strategy for migratory birds while playing an essential role in sustaining the balance of global ecosystems and preserving biodiversity^3–5. Nevertheless, amid escalating global ecological and environmental changes, the risk of pathogen transmission during bird migration has substantially increased, rendering migratory birds a significant pathway for cross-regional pathogen transmission^6–8.

Migratory birds, while traversing multiple ecosystems and crossing international borders during their migration, may serve as vectors for pathogens between breeding sites, stopover sites, and wintering grounds. This poses a potential threat to both public health and ecosystem health. Recent studies have revealed the patterns of specific pathogen carriage and transmission by migratory birds along their migratory routes^9–13. For instance, continuous surveillance by Wang et al. on wild waterfowl has shown that these birds can shed a variety of pathogens, including avian influenza viruses and reoviruses, during migration¹⁴. Such pathogens pose a significant transmission risk not only along migratory corridors but also within the habitats frequented by migratory birds, such as wetlands, agricultural areas, and artificial water bodies^15–27. High-density bird aggregations in these areas increase contact rates among bird individuals, thereby facilitating pathogen transmission^28,29. Concurrently, aquatic environments enable prolonged pathogen survival, allowing infectious agents to remain viable for extended periods in water^30,31. Additionally, interactions between migratory birds and domestic poultry at wintering and stopover sites may facilitate cross-species transmission of pathogens through direct contact in shared aquatic environments and feeding areas^32,33, thereby facilitating pathogen exchange, viral spillover, and potential adaptation within domestic populations^34,35. Among these pathogens, avian influenza virus (AIV) is particularly noteworthy, as its global dissemination is closely associated with the long-distance migration of migratory birds^36–40. For instance, research has demonstrated that avian influenza viruses (AIVs) in migratory birds wintering within the Yangtze River wetlands of eastern China exhibit rich subtype diversity and complex genomic characteristics⁴¹. Notably, some viral segments show high genetic similarity to strains currently circulating in migratory bird populations in North America. This pattern suggests that migratory birds may play a critical role in facilitating intercontinental pathogen transmission, as evidenced by successive multi-continental outbreaks of highly pathogenic avian influenza (HPAI), including the 2005‒2006 H5N1 outbreak, the 2014‒2015 emergence of H5N8, and the ongoing H5N1 clade 2.3.4.4b outbreak that began in 2020^42–47. Building on this evidence, comprehensive studies have integrated avian migration data with AIVs transmission networks. These studies revealed the spatiotemporal dynamics and transmission pathways of the virus across diverse geographical regions⁴⁸. These findings collectively underscore the important role of migratory birds in pathogen transmission and highlight the necessity of implementing robust surveillance and risk management during bird migration.

Advancements in tracking technologies, including Global Positioning System (GPS) and satellite telemetry, have significantly enhanced our understanding of migratory bird movements⁴⁹. Publicly accessible databases like Movebank support the sharing of tracking data, hereby facilitating large-scale analyses of migration patterns^50,51. However, current research has largely concentrated on single-species studies, resulting in fragmented datasets that hinder the identification of spatiotemporal overlap and potential interspecies interactions during migration. This limitation might impede a comprehensive assessment of cross-species pathogen transmission risks. Integrating tracking data from multiple species and applying standardized analytical methods can address this gap. Density-based clustering algorithms, such as T-DBSCAN, have been increasingly applied to migratory bird tracking data^52,53 and provide a standardized approach for identifying stopover sites among different species. These approaches enable the detection of stopover sites from tracking data, thereby facilitating multi-species spatiotemporal analyses when utilized in integrated datasets.

This study aims to integrate existing migratory bird tracking data from the Movebank database and apply the T-DBSCAN algorithm to identify specific spatiotemporal locations of various migratory bird species on given dates. A spatiotemporal co-occurrence dataset of migratory birds was established with a daily temporal resolution and spatial resolution aligned with first-level administrative divisions. Co-occurrence analyses were conducted for migratory bird species with documented detections of AIVs to illustrate the role of this dataset in untangling avian influenza virus variation hotspots and identifying relevant key migratory bird species. This provides a theoretical foundation and data support for the prevention and control of emerging and re-emerging infectious diseases.

Methods

Data collection

To collect migration data for bird species with documented detections of AIVs, we obtained relevant tracking data from Movebank, a global database dedicated to bird movement research. The selection of migratory bird species was based on a published systematic review⁵⁴, which identified 175 migratory bird species with documented natural AIV infections. These species account for infection records across 99 distinct AIV subtypes, providing a comprehensive species list and evidence base for this study.

Based on the taxonomic information, including order, family, genus, species, and common name, for the 175 migratory bird species, we systematically retrieved all

available tracking dataset from the Movebank platform. During data acquisition, only research projects with appropriate data use licenses were included to ensure compliance with relevant data-sharing agreements and terms of use for all downloaded and utilized data. No time restrictions were applied during the retrieval process, thereby maximizing the inclusion of data representing diverse migration patterns and geographic regions.

Through systematic retrieval, tracking data from 182 independent studies involving 62 species were preliminarily obtained from the Movebank platform. Detailed AIV subtype associations for these 62 species, including detection records and corresponding references, are provided in “AIV associated species list.xlsx” available via figshare⁵⁵. All collected raw data contained detailed spatiotemporal records, with metadata such as geographic coordinates, timestamps, individual identification codes, tracking device types, and research project information. The tracking technologies employed in these datasets include GPS positioning, Argos Doppler-based positioning, radio transmitters, solar-powered geolocators, and Sigfox geolocation systems.

Data processing. This study established a comprehensive workflow for identifying stopover sites of migratory birds during their migration (Fig. 1), including data collection, preprocessing, migration pattern identification, representative individual selection, and stopover site identification. Raw tracking data were organized by research project. Individual trajectories within each study were separated based on the “individual-local-identifier” field, and species identification was assigned according to the scientific names recorded in the “taxon-canonic-name” field. To address inconsistencies arising from the mixed use of scientific and common names in the database, all species names were standardized according to the taxonomy of the Handbook of the Birds of the World and BirdLife International⁵⁶. Following the processing of individual trajectory separation and species identification, tracking data for a total of 5,672 individuals were compiled.

Fig. 1 — Workflow for constructing the spatiotemporal co-occurrence dataset of migratory birds.

To focus the analysis on terrestrial ecosystems, a spatial intersection analysis was conducted using the sf package in R⁵⁷. Specifically, terrestrial boundary data at the first administrative level from the Global Administrative Areas database (GADM, https://www.gadm.org) were loaded to spatially filter the tracking points: only those located within terrestrial administrative polygons were retained, whereas points falling within marine areas were excluded. To reduce redundancy in high-frequency tracking data, the original dataset was down-sampled to a uniform temporal resolution of 1-hour intervals. To ensure continuity in individual trajectory analysis, only individuals meeting the following criteria were retained: after down-sampling, at least 80% of consecutive points in their valid tracking sequences exhibited time intervals not exceeding 24 hours. It is noteworthy that these criteria were applied at the individual level. An individual was retained for further analysis only if its overall trajectory met the quality standards; otherwise, it was entirely excluded. Ultimately, valid tracking data from 3,944 individuals across 62 species, derived from 157 studies^58–214, were retained for subsequent identification of stopover sites (detailed information is provided in “Individual tracking data.xlsx” via figshare⁵⁵).

The identification of migratory bird stopover sites was conducted using an adaptive algorithmic strategy. First, a visual analysis of individual movement trajectories was performed to assess their suitability for cluster analysis based on spatiotemporal distribution patterns. Suitability criteria were defined as follows: trajectories considered appropriate for clustering exhibited distinct directional and continuous movement patterns, characterized by regular displacements along relatively fixed directions, with tracking points forming recognizable aggregation patterns in space; trajectories unsuitable for clustering primarily displayed overly sparse tracking points, irregular flight paths (e.g., diamond-shaped patterns), or lacked clear spatial aggregation characteristics. Based on this assessment, trajectories from 2,695 individuals were determined to be applicable for cluster analysis, while trajectories from 1,249 individuals were excluded due to sparse data or irregular patterns.

For these suitable trajectories, we employed the T-DBSCAN algorithm^52,53 to identify discrete stopover sites from individual migration trajectories. This spatiotemporal clustering method was selected for its ability to directly output discrete stopover events based on explicit temporal constraints (minStayTime and maxIntervalTime)⁵², allowing operational definitions aligned with species-specific movement ecology. For individuals suitable for clustering, the individual with the highest number of tracking points within each species was selected as the representative for parameter optimization of the T-DBSCAN algorithm. The parameter optimization procedure was conducted as follows: The leaflet package in R was used to generate annual interactive migration trajectory maps for the selected individuals. Through visual inspection, the stopover region with the largest activity area in each year was identified. The annotation function of the interactive map was utilized to determine the start and end point indices for each stopover region. All coordinates (longitude and latitude) within this index range were used as input, and the Welzl algorithm²¹⁵ was applied to calculate the minimum enclosing circle radius (in kilometers) encompassing all these points. Following cross-annual analysis of all stopover regions for the representative individuals of each species, the calculated radii were used as the baseline value for the species’ spatial radius parameter (eps), reflecting its typical activity range. In parallel, local recurrent movement regions within the representative individual’s trajectory were identified via visual inspection of the interactive maps. Such trajectory segments were required to contain at least three consecutive tracking points and exhibit a back-and-forth movement pattern within a specific area. The temporal information for each point in these segments was obtained using the map’s annotation function, and the time span (in hours) of these recurrent movement segments was calculated. By analyzing the distribution of these time spans, the minimum value was recorded as the baseline for the species’ minimum stay time parameter (minStayTime).

Following parameter optimization validation (see Technical Validation section), the final T-DBSCAN parameters were set as follows: eps was set to 1.2 times the baseline value (providing optimal spatial buffering), minStayTime was set to 0.8 times the baseline value, and maxIntervalTime was set to 60 days. The optimized T-DBSCAN spatiotemporal clustering algorithm was applied to all migratory individuals suitable for clustering to identify stopover sites. For individuals not suitable for clustering, the residence time within each first-level administrative division was calculated based on the corresponding boundary data, defined as the time span from the first recorded entry to the last recorded exit from that division.

Data Records

The final constructed spatiotemporal co-occurrence dataset is provided as three separate interrelated files, publicly available via figshare⁵⁵. The database includes the following fields:

Daily species pairs.xlsx

This worksheet constitutes the core component of the dataset, documenting co-occurrence events for specific species pairs within specific first-level administrative divisions on specific dates. Key fields include:

Countries: Countries where co-occurrence events were recorded.
First-level administrative division: The first-level administrative division where co-occurrence events were recorded.
Date: The date of the co-occurrence event (recorded by month-day).
Species 1: The scientific name of the first species in the species pair.
Species 2: The scientific name of the second species in the species pair.
Daily species count: The total number of species recorded in the first-level administrative division on that day.
Pair name: The standardized name of the species pair.

Administrative division summary.xlsx

This worksheet provides summary statistics for each first-level administrative division:

Countries: Countries where co-occurrence events were recorded.
First-level administrative division: The first-level administrative division where co-occurrence events were recorded.
Total pair-days: The total number of species pair-days recorded within the first-level administrative division. A pair-day is defined as the number of unique species pairs co-occurring within the same first-level administrative division on a given calendar date (recorded as month-day), calculated using the combination formula C(n,2), where n represents the number of species observed on that date.
Co-occurrence days: The number of distinct dates (recorded by month-day) on which multi-species co-occurrence was recorded.
Max daily pairs: The maximum number of species pairs recorded on any single co-occurrence date (recorded by month-day) within that first-level administrative division across all recorded dates.
Total species involved: The total number of distinct species involved.
Unique pair types: Number of unique species pair types.

Species pair summary.xlsx

Pair name: Standardized name of the species pair.
Species 1: Scientific name of the first species in the pair.
Species 2: Scientific name of the second species in the pair.
Countries: All countries where the co-occurrence of this species pair has been recorded, separated by semicolons.
Total co-occurrence division-days: For all first-level administrative divisions where the co-occurrence of the species pair was recorded, the cumulative number of division-days was calculated. Division-days are defined as a distinct combination of calendar date (month-day) and first-level administrative division on which the species pair co-occurred.
First-level administrative division count: The number of first-level administrative divisions where co-occurrence of this species pair occurred.
Date range: The temporal span of co-occurrence events, showing the month and day of the first and last recorded co-occurrence of the species pair.

(8–19) January–December: Monthly distribution of co-occurrence, showing the number of days (recorded by month-day) and percentage for each month.

This dataset documents co-occurrence events among migratory bird species across 488 first-level administrative divisions worldwide. Based on tracking data from 62 migratory bird species with documented AIV detection (derived from 3,944 individuals across 157 studies), the dataset captures spatiotemporal co-occurrence events involving 50 species that demonstrated spatial overlap within the same first-level administrative division and temporal overlap on the same calendar date. A total of 385 unique species pairs are represented across 77,862 daily co-occurrence records. Summary statistics of the first-level administrative divisions presented in the worksheet indicate significant spatial heterogeneity in species richness, co-occurrence intensity, and timing of daily peaks across regions (Fig. 2). The number of species tracked per first-level administrative division ranges from 1 to 21 (Fig. 2a), and the number of species pair combinations exhibits distinct spatial clustering characteristics (Fig. 2b). The distribution of cumulative paired days reflects spatial hotspots of migratory bird activity (Fig. 2c), while the maximum number of species recorded on a single day untangles the spatiotemporal concentration of migratory activities (Fig. 2d).

Fig. 2 — Spatiotemporal distribution patterns of tracking data for migratory bird species with records of AIV detection across first-level administrative divisions. (a) Number of species tracked; (b) Number of unique species pairs recorded (log-transformed); (c) Cumulative pair-days (log-transformed); (d) Maximum number of species recorded in a single day. A pair-day is defined as the number of unique species pairs co-occurring within the same first-level administrative division on a given calendar date (recorded as month-day), calculated using the combination formula C(n,2), where n represents the number of species observed on that date.

From a temporal perspective, the 77,862 daily records included in the worksheet demonstrate that species co-occurrence events are not uniformly distributed throughout the year. As shown in Fig. 3, the monthly distribution of cumulative paired days clearly illustrates this inter-monthly variation pattern. The worksheet further summarizes the spatiotemporal statistical characteristics of all unique species pairs, including the number of days each pair was observed, the number of primary administrative divisions covered, and the temporal span, among other information. Figure 4 presents the co-occurrence patterns among species in the form of a heatmap. Figure 5 shows monthly chord diagrams that illustrate how species co-occurrence patterns vary throughout the year.

Fig. 3 — Monthly spatiotemporal distribution patterns of tracking data for migratory bird species with a history of AIV detection. The distribution of cumulative pair-days (log-transformed) per first-level administrative division per month illustrates the seasonal variation in spatiotemporal distribution patterns across different months. A pair-day is defined as the number of unique species pairs co-occurring within the same first-level administrative division on a given calendar date (recorded as month-day), calculated using the combination formula C(n,2), where n represents the number of species observed on that date.

Fig. 4 — Co-occurrence patterns among migratory bird species with previous records of AIV detection. Each cell in the heatmap matrix represents the logarithm of the number of division-days in which a specific pair of species co-occurred. Species are ordered by taxonomic family. Different taxonomic families are distinguished by colored background regions and family labels at the bottom. The bar plot on the right displays the sum of division-days for each species with all other species and its corresponding proportion. Division-days are defined as distinct combinations of calendar date (month-day) and first-level administrative division on which the species pair co-occurred.

Fig. 5 — Monthly co-occurrence patterns of migratory bird species with a history of AIV detection. The chord diagram illustrates the spatiotemporal distribution patterns among species each month. The arcs represent species, and the thickness of the connecting chords indicates the number of division-days for each species pair. For each month, the top 9 species with the highest number of division-days are displayed; the remaining species are grouped into “Others” (shown in gray). Division-days are defined as distinct combinations of calendar date (month-day) and first-level administrative division on which the species pair co-occurred.

In addition to the core dataset, the figshare repository includes the following data files: (1) “AIV associated species list.xlsx” details the associations of AIV subtype for the 62 species, including detection records and corresponding references; (2) “Individual tracking data.xlsx” provides detailed tracking information for all 3,944 individuals included in the analysis; (3) “Spatial co-occurrence validation.xlsx” and (4) “Temporal co-occurrence validation.xlsx” respectively contain the validation results of comparing co-occurrence patterns between the known AIV-associated migratory birds (62 species) and the extended migratory bird range (143 species) scenarios in spatial and temporal dimensions; and (5) “Tracking data sources.xlsx” provides the data sources and attribution for all bird tracking datasets used in this study.

Technical Validation

Validation of AIV-associated migratory bird range representatives

Given the rapid evolution of AIV and its potential for expansion into new migratory bird species, an analysis of the range extension of AIV-associated migratory birds was conducted to evaluate the robustness of spatiotemporal co-occurrence patterns based on known AIV-associated migratory birds under scenarios of AIV-associated migratory bird range expansion.

Two analytical scenarios were established for comparison: (1) the “Known AIV-associated migratory birds” scenario, based on 62 migratory bird species with documented AIV detection; and (2) the “Extended AIV-associated migratory bird range” scenario, which included all available migratory bird species from the Movebank platform (totaling 143 species from 282^{58–214,216–334} studies). Both datasets were processed using identical data processing pipelines and spatiotemporal co-occurrence definitions.

Spatial pattern consistency: Among the 488 common administrative divisions, the rankings of co-occurrence intensity were highly consistent (Spearman’s ρ = 0.80, p < 0.05), indicating that the identification of high co-occurrence intensity regions remained stable after AIV-associated migratory bird range expansion.

Temporal Pattern Consistency: The monthly co-occurrence intensity patterns also demonstrated high consistency (Spearman’s ρ = 0.82, p < 0.05), suggesting that the critical time windows for potential transmission remained consistent under different AIV-associated migratory bird range assumptions.

The strong correlations in both spatial and temporal dimensions (ρ ≥ 0.8, p < 0.05) indicated that the primary hotspot regions and critical time windows remained stable following host range expansion, thereby validating the representativeness and robustness of risk assessments based on known AIV-associated migratory birds (detailed results of spatial comparison and temporal comparison are provided in “Spatial co-occurrence validation.xlsx” and “Temporal co-occurrence validation.xlsx” respectively, available via figshare⁵⁵).

Validation of the biological relevance of co-occurrence sites

To validate whether the identified co-occurrence sites correspond to actual interspecies contact or pathogen environmental sharing, viral sequences from co-occurring species pairs collected at identified hotspots were retrieved from the GISAID database and analyzed for genetic similarity. Sequences were aligned using MAFFT³³⁵, and genetic similarity (based on p-distance) was calculated using R.

In the Netherlands, a co-occurrence hotspot identified by the dataset, the herring gull (Larus argentatus) and the lesser black-backed gull (Larus fuscus) formed a frequently co-occurring species pair. H5N1 virus strains collected from these two species in April 2022 (accession numbers: EPI_ISL_13201050 and EPI_ISL_12514681) exhibited high genetic similarity across five gene segments (NP: 99.81%, HA: 99.77%, NS: 99.06%, MP: 99.90%, NA: 99.72%). Both samples were collected during the predicted co-occurrence period for these species.

In Belgium, another independent co-occurrence hotspot, H13 virus strains collected from the same species pair in August 2008 (accession numbers: EPI_ISL_63813 and EPI_ISL_63814) demonstrated 99.28% similarity in the HA segment. Sampling occurred within the identified co-occurrence period.

Across two independent geographical regions and time points, the identified co-occurrence hotspots yielded highly similar viral strains ( >99% similarity across gene segments) from co-occurring species pairs. This molecular evidence demonstrates that the identified co-occurrence sites represent not merely statistical spatiotemporal overlap, but correspond to locations where species likely experienced actual pathogen contact or shared contaminated environments. This cross-regional and cross-temporal consistency validates the effectiveness of the tracking data-based co-occurrence identification method in pinpointing key spatiotemporal sites for potential interspecies pathogen transmission.

Usage Notes

This dataset documents the global spatiotemporal co-occurrence patterns of migratory bird species prior records of AIV detection, offering significant value for epidemiological risks assessment, surveillance optimization, and conservation planning.

Ecological research applications

The cumulative pair-days and the maximum daily species count presented in “Administrative division summary.xlsx” can be used to analyze the activity intensity of migratory birds and the patterns of species diversity across different regions. The division-days data in “Species pair summary.xlsx” facilitates the identification of spatiotemporal associations between species and potential ecological interactions by quantifying the total number of distinct date-location combinations where species pairs co-occur.

Disease transmission and variation risk assessment

This dataset can be used to assess the intensity of species contact and assist in estimating the potential risk levels of virus variation across different regions. The “Administrative division summary.xlsx” file provides quantitative metrics for prioritizing surveillance efforts. Divisions with high total pair-days values indicate frequent multi-species interactions, which necessitate enhanced monitoring. Meanwhile, “max daily pairs” values identify areas where numerous species converge simultaneously, suggesting potential transmission hotspots. Surveillance programs should prioritize species pairs that exhibit high-frequency co-occurrence characteristics, focusing on key species combinations where viral strain exchange may occur. The monthly distribution data (columns from January to December) in “Species pair summary.xlsx” facilitates the precise scheduling of surveillance activities, showing exactly when and where peak interspecies interactions are expected in specific administrative divisions.

Conservation planning applications

The number of species pairs and the total species count within each first-level administrative division can help identify activity hotspots for migratory bird species, thereby providing a scientific basis for the arrangement of disease monitoring sites and the identification of potential high-risk areas. Division-days data can guide the scheduling of monitoring and management activities, facilitating improved disease surveillance during periods when species aggregate with high frequency. Specific applications include: allocating resources to divisions with the highest co-occurrence intensity based on total pair-days metrics, timing monitoring efforts by referring to the monthly peak periods from “Species pair summary.xlsx”, and focusing on species pairs that have demonstrated frequent interactions across multiple administrative regions.

Data limitations

It should be acknowledged that tracked individuals may not fully represent the entire species populations, as tracking studies often focus on specific age groups or sexes; there may be potential impacts of tracking devices on migratory behavior; individuals with irregular migration patterns may be systematically excluded due to our data filtering criteria (requiring ≥80% of tracking points with time intervals less than 24 hours); T-DBSCAN algorithm parameters were optimized using single representative individuals of each species, which may not fully capture intraspecific behavioral variation; and definitions of co-occurrence are based on administrative boundaries rather than ecological ones. Furthermore, the current AIV-associated wild bird range does not necessarily indicate which other species could potentially be infected by or serve as vectors for AIVs. Essentially, the present state of knowledge primarily reflects a list of species that have either been subjected to experimental infection studies or have had contact with the virus and subsequently exhibited symptoms and/or undergone testing for active infection or serological response, rather than accurately representing the true extent of wild bird species associated with circulating AIV strains.

Additionally, the efforts in migratory bird tracking are distributed unevenly across global regions. This distribution reflects the cumulative spatiotemporal co-occurrence patterns of avian influenza virus-associated migratory birds based on historical research projects, rather than a pre-planned systematic coverage. Our study integrated existing tracking datasets from the Movebank database, within which tracking studies have, historically, predominantly concentrated on certain migratory flyways. These geographic gaps may arise from varying research priorities, species-specific project focuses, along with technological and logistical constraints across regions. Such uneven coverage may lead to an underestimation of co-occurrence patterns in data-sparse areas, such as certain parts of Asia during winter, where sufficient multi-species tracking data are not yet available. It should be recognized that when interpreting the results, the lack of co-occurrence records in specific geographic areas and time periods may be due to data availability rather than the absence of actual interspecies interactions. Nevertheless, our dataset provides a valuable systematic integration of multi-species tracking data and identifies co-occurrence patterns, which represents a comprehensive analysis achievable through current tracking efforts. Disease surveillance applications will yield the greatest effectiveness in well-sampled regions. Meanwhile, the expansion of multi-species tracking in underrepresented areas may uncover additional transmission hotspots that complement our current findings.

Acknowledgements

This work was funded by grants from the National Key Research and Development Program of China (2022YFC2604403), the National Natural Science Foundation of China (82103901), the Natural Science Foundation of Liaoning Province, China (2025-BS-0952), and the Fund of State Key Laboratory of Pathogen and Biosecurity (SKLPBS2205). We gratefully acknowledge all bird tracking data contributors, i.e., the authors and other researchers in their originating groups responsible for collecting the data and metadata and sharing via Movebank, on which this research is based. We thank all principal investigators and their research teams for making their valuable tracking datasets publicly available under various Creative Commons licenses and custom terms. The complete list of data contributors, including principal investigators, contact persons, citations, data repository DOIs, and specific license agreement types, is provided in “Tracking data sources.xlsx” available via figshare⁵⁵. We also gratefully acknowledge all authors of published studies who contributed to sharing information in the literature, as much of our data compilation and analyses were made possible by the availability of their published work.

Author contributions

All the authors in the author list were involved in this paper’s preparation and writing process, and all of them agreed to be responsible for all aspects of the research paper. L.Q.F. and F.H. designed this study; J.M., Y.H.W., Y.B.Q., J.J.C., Y.H., Z.Y., S.H.L., Q.J.W., L.T.C., X.J.Z., S.Z., T.T., Y.T., and Y.F.Y. performed experiments; J.M. analyzed the data and wrote the manuscript; J.M., Y.H.W., Q.X., and Z.D.M. contributed analysis methods and tools; Y.H.W., Y.B.Q., J.J.C., C.L.L., and G.L.W. provided administrative guidance in this study; J.M., L.Q.F. and F.H. wrote the original draft. All of the authors reviewed the manuscript and approved the final version.

Data availability

The dataset is publicly available on figshare⁵⁵ at 10.6084/m9.figshare.31044229.v1. It comprises eight Excel files, including three core dataset files and five supporting data files.

Code availability

The analysis code is publicly accessible at https://github.com/FlowSpatial/Migratory-birds-code.git. It covers trajectory screening, T-DBSCAN-based stopover identification, and spatiotemporal co-occurrence analysis.

Competing interests

The authors declare no competing interests.

Footnotes

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

These authors contributed equally: Jun Ma, Yan-He Wang, Yun-Bo Qiu.

Contributor Information

Feng Hong, Email: hongfeng-73@163.com.

Li-Qun Fang, Email: fang_lq@163.com.

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142.The data used in this study were accessed from Movebank (movebank.org, study name “Barn swallows breeding in Kraghede”, study ID 4201934806) on 1 March 2025.
143.The data used in this study were accessed from Movebank (movebank.org, study name “barTailedGodwit_USGS_ASC_argos”, study ID 1718959411) on 1 March 2025.
144.The data used in this study were accessed from Movebank (movebank.org, study name “Bean Goose Anser fabalis Finnmark”, study ID 11223924) on 1 March 2025.
145.The data used in this study were accessed from Movebank (movebank.org, study name “Bill Cochran Peregrine falcon migration 1973-75”, study ID 274355544) on 1 March 2025.
146.The data used in this study were accessed from Movebank (movebank.org, study name “BOP_RODENT - Rodent specialized birds of prey (Circus, Asio, Buteo) in Flanders (Belgium)”, study ID 1278021460) on 1 March 2025.
147.The data used in this study were accessed from Movebank (movebank.org, study name “Bubulcus ibis_Vollot_ENVT_65_ID_PROG1035”, study ID 2915700754) on 1 March 2025.
148.The data used in this study were accessed from Movebank (movebank.org, study name “Chicago BCNH Project (Druid)”, study ID 3902656356) on 1 March 2025.
149.The data used in this study were accessed from Movebank (movebank.org, study name “Chicago BCNH Project”, study ID 2830157729) on 1 March 2025.
150.The data used in this study were accessed from Movebank (movebank.org, study name “Common Crane 2020 (Lithuanian University of Educational Studies; LEU)”, study ID 1229945587) on 1 March 2025.
151.The data used in this study were accessed from Movebank (movebank.org, study name “Common Cuckoo (A), Southern Sweden”, study ID 49915781) on 1 March 2025.
152.The data used in this study were accessed from Movebank (movebank.org, study name “Common Cuckoo (C), Eastern Europe”, study ID 55252460) on 1 March 2025.
153.The data used in this study were accessed from Movebank (movebank.org, study name “Corvus corone [ID_PROG 883]”, study ID 1266784970) on 1 March 2025.
154.The data used in this study were accessed from Movebank (movebank.org, study name “CURLEW_VLAANDEREN - Eurasian curlews (Numenius arquata, Scolopacidae) breeding in Flanders (Belgium)”, study ID 1841091905) on 1 March 2025.
155.The data used in this study were accessed from Movebank (movebank.org, study name “DELTATRACK - Herring gulls (Larus argentatus, Laridae) and lesser black-backed gulls (Larus fuscus, Laridae) breeding at Neeltje Jans (Netherlands)”, study ID 1258895879) on 1 March 2025.
156.The data used in this study were accessed from Movebank (movebank.org, study name “Egrets & Herons”, study ID 17469219) on 1 March 2025.
157.The data used in this study were accessed from Movebank (movebank.org, study name “Forest Park Living Lab”, study ID 1605024900) on 1 March 2025.
158.The data used in this study were accessed from Movebank (movebank.org, study name “FTZ Geese Wadden Sea”, study ID 69724677) on 1 March 2025.
159.The data used in this study were accessed from Movebank (movebank.org, study name “Graugans Zugverhalten Neusiedler See”, study ID 505156776) on 1 March 2025.
160.The data used in this study were accessed from Movebank (movebank.org, study name “Great Cormorant Lake Constance MPIAB”, study ID 2988309) on 1 March 2025.
161.The data used in this study were accessed from Movebank (movebank.org, study name “Gulls - Minsk”, study ID 2272852276) on 1 March 2025.
162.The data used in this study were accessed from Movebank (movebank.org, study name “gullSpecies_USGS_ASC_argosGPS”, study ID 1091848505) on 1 March 2025.
163.The data used in this study were accessed from Movebank (movebank.org, study name “Habitrack European Turtle Dove”, study ID 3413045568) on 1 March 2025.
164.The data used in this study were accessed from Movebank (movebank.org, study name “Herring Gulls (Larus Argentatus); Ronconi; Kent Island, Canada”, study ID 1071101052) on 1 March 2025.
165.The data used in this study were accessed from Movebank (movebank.org, study name “Herring Gulls (Larus Argentatus); Ronconi; Sable Island, Canada”, study ID 1080341737) on 1 March 2025.
166.The data used in this study were accessed from Movebank (movebank.org, study name “HG_OOSTENDE - Herring gulls (Larus argentatus, Laridae) breeding at the southern North Sea coast (Belgium)”, study ID 986040562) on 1 March 2025.
167.The data used in this study were accessed from Movebank (movebank.org, study name “HUJ MPIAB White Stork GSM 2013”, study ID 10449698) on 1 March 2025.
168.The data used in this study were accessed from Movebank (movebank.org, study name “HUJ MPIAB White Stork GSM E-Obs”, study ID 7002955) on 1 March 2025.
169.The data used in this study were accessed from Movebank (movebank.org, study name “ICARUS Cuckoo Holland”, study ID 1539583795) on 1 March 2025.
170.The data used in this study were accessed from Movebank (movebank.org, study name “ICARUS Mongolia cuckoos Nymba”, study ID 1542155599) on 1 March 2025.
171.The data used in this study were accessed from Movebank (movebank.org, study name “ICARUS Pacific Coast Peregrine”, study ID 1748399252) on 1 March 2025.
172.The data used in this study were accessed from Movebank (movebank.org, study name “ICARUS Turkey Cagan”, study ID 1541820092) on 1 March 2025.
173.e data used in this study were accessed from Movebank (movebank.org, study name “ICARUS Turtle doves”, study ID 1542192442) on 1 March 2025.
174.The data used in this study were accessed from Movebank (movebank.org, study name “Lake Constance Ducks”, study ID 2927282) on 1 March 2025.
175.The data used in this study were accessed from Movebank (movebank.org, study name “Larus heuglini_1”, study ID 1445058753) on 1 March 2025.
176.The data used in this study were accessed from Movebank (movebank.org, study name “Larus michahellis X Larus cachinnans hybrids”, study ID 2190520177) on 1 March 2025.
177.The data used in this study were accessed from Movebank (movebank.org, study name “LifeTrack - Evros Delta”, study ID 8927992) on 1 March 2025.
178.The data used in this study were accessed from Movebank (movebank.org, study name “LifeTrack Ducks Lake Constance”, study ID 236953686) on 1 March 2025.
179.The data used in this study were accessed from Movebank (movebank.org, study name “LifeTrack White Stork Greece Evros Delta”, study ID 10449535) on 1 March 2025.
180.The data used in this study were accessed from Movebank (movebank.org, study name “LifeTrack White Stork Loburg”, study ID 10449318) on 1 March 2025.
181.The data used in this study were accessed from Movebank (movebank.org, study name “LifeTrack White Stork Moscow”, study ID 10596067) on 1 March 2025.
182.The data used in this study were accessed from Movebank (movebank.org, study name “LifeTrack White Stork Poland”, study ID 10763606) on 1 March 2025.
183.The data used in this study were accessed from Movebank (movebank.org, study name “LifeTrack White Stork Sarralbe [ID_PROG 1093]”, study ID 1562253659) on 1 March 2025.
184.The data used in this study were accessed from Movebank (movebank.org, study name “LifeTrack White Stork South Africa”, study ID 8008999) on 1 March 2025.
185.The data used in this study were accessed from Movebank (movebank.org, study name “LifeTrack White Stork Tunisia”, study ID 10157679) on 1 March 2025.
186.The data used in this study were accessed from Movebank (movebank.org, study name “LifeTrack White Stork Uzbekistan”, study ID 9493881) on 1 March 2025.
187.The data used in this study were accessed from Movebank (movebank.org, study name “LifeTrack Whooper Swan Latvia”, study ID 92261778) on 1 March 2025.
188.The data used in this study were accessed from Movebank (movebank.org, study name “MEDGULL_ANTWERPEN - Mediterranean gulls (Ichthyaetus melanocephalus, Laridae) breeding near Antwerp (Belgium)”, study ID 1609400843) on 1 March 2025.
189.The data used in this study were accessed from Movebank (movebank.org, study name “MH_ANTWERPEN - Western marsh harriers (Circus aeruginosus, Accipitridae) breeding near Antwerp (Belgium)”, study ID 938783961) on 1 March 2025.
190.The data used in this study were accessed from Movebank (movebank.org, study name “Milvus migrans”, study ID 892924356) on 1 March 2025.
191.The data used in this study were accessed from Movebank (movebank.org, study name “MPIAB White Stork Greece Argos”, study ID 446659) on 1 March 2025.
192.The data used in this study were accessed from Movebank (movebank.org, study name “MPIAB white stork lifetime tracking data (2013-2014)”, study ID 74496970) on 1 March 2025.
193.The data used in this study were accessed from Movebank (movebank.org, study name “MPIAB White Stork Oriental Argos”, study ID 446663) on 1 March 2025.
194.The data used in this study were accessed from Movebank (movebank.org, study name “MPIAB White Stork Prinzesschen”, study ID 1898591) on 1 March 2025.
195.The data used in this study were accessed from Movebank (movebank.org, study name “MPIAB White Stork South African Population Argos”, study ID 446667) on 1 March 2025.
196.The data used in this study were accessed from Movebank (movebank.org, study name “NC Breeding ABDU”, study ID 1404033416) on 1 March 2025.
197.The data used in this study were accessed from Movebank (movebank.org, study name “Osprey Bierregaard North and South America”, study ID 8868155) on 1 March 2025.
198.The data used in this study were accessed from Movebank (movebank.org, study name “Pandion haliaetus Osprey - SouthEast Michigan”, study ID 10204361) on 1 March 2025.
199.The data used in this study were accessed from Movebank (movebank.org, study name “Peregrine Falcon - NYSDEC”, study ID 6459871) on 1 March 2025.
200.The data used in this study were accessed from Movebank (movebank.org, study name “Poultry network China 2022”, study ID 1909487338) on 1 March 2025.
201.The data used in this study were accessed from Movebank (movebank.org, study name “Poultry network Thailand 2022”, study ID 1879445455) on 1 March 2025.
202.The data used in this study were accessed from Movebank (movebank.org, study name “Sarus Crane, van Zalinge, Cambodia”, study ID 47450376) on 1 March 2025.
203.The data used in this study were accessed from Movebank (movebank.org, study name “Satellite tracking of Goosander in Scotland”, study ID 2526306516) on 1 March 2025.
204.The data used in this study were accessed from Movebank (movebank.org, study name “Seaducks in the Fehmarn Belt (southern Baltic)”, study ID 1962595) on 1 March 2025.
205.The data used in this study were accessed from Movebank (movebank.org, study name “Shelduck Italy ISPRA MPIAB”, study ID 1963631608) on 1 March 2025.
206.The data used in this study were accessed from Movebank (movebank.org, study name “Solovki Larus Track”, study ID 312267867) on 1 March 2025.
207.The data used in this study were accessed from Movebank (movebank.org, study name “SPOONBILL_VLAANDEREN - Eurasian spoonbills (Platalea leucorodia, Threskiornithidae) in Flanders (Belgium)”, study ID 2313947453) on 1 March 2025.
208.The data used in this study were accessed from Movebank (movebank.org, study name “Tracking of Caspian Terns (Hydroprogne caspia) in the Swedish Baltic Sea 2017-2020”, study ID 1575973021) on 1 March 2025.
209.The data used in this study were accessed from Movebank (movebank.org, study name “Variability of White Stork flight patterns prior to earthquakes”, study ID 1498452485) on 1 March 2025.
210.The data used in this study were accessed from Movebank (movebank.org, study name “Wader migration German Wadden Sea: bar-tailed godwits”, study ID 5666500) on 1 March 2025.
211.The data used in this study were accessed from Movebank (movebank.org, study name “whimbrel_USGS_ASC_argos”, study ID 854852176) on 1 March 2025.
212.The data used in this study were accessed from Movebank (movebank.org, study name “White stork Ciconidae Western Poland”, study ID 1252230318) on 1 March 2025.
213.The data used in this study were accessed from Movebank (movebank.org, study name “White-tailed Eagle Poland.”, study ID 384868221) on 1 March 2025.
214.The data used in this study were accessed from Movebank (movebank.org, study name “Yellow-legged Gulls”, study ID 1724475305) on 1 March 2025.
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227.Hill, J. M. & Renfrew, R. B. Data from: Migration patterns of upland sandpipers in the western hemisphere. Movebank Data Repository, 10.5441/001/1.3pt25757 (2019).
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229.Exo, K.-M., Hillig, F. & Bairlein, F. Data from: Migration routes and strategies of Grey Plovers (Pluvialis squatarola) on the East Atlantic Flyway as revealed by satellite tracking. Movebank Data Repository, 10.5441/001/1.vv0ft02m (2019).
230.Spiegel, O. M. et al. Data from: Moving beyond curve-fitting: using complementary data to assess alternative explanations for long movements of three vulture species. Movebank Data Repository, 10.5441/001/1.8c56f72s (2015).
231.Pedersen, L. et al. Data from: Remarkably similar migration patterns between different red-backed shrike populations suggest that migration rather than breeding area phenology determines the annual cycle. Movebank Data Repository, 10.5441/001/1.4bt7365c (2020).
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234.Pedersen, L., Nina Munkholt, J., Strandberg, R., Thorup, K. & Tøttrup, A. P. Data from: Sex-specific difference in migration schedule as a precursor of protandry in a long-distance migratory bird. Movebank Data Repository, 10.5441/001/1.j71640kh (2019). [DOI] [PubMed]
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236.Ilyashenko, E. I. et al. Data from: Study “1000 Cranes. Russia. Altai.”. Movebank Data Repository, 10.5441/001/1.596 (2024).
237.Ilyashenko, E. I. et al. Data from: Study “1000 Cranes. Russia. Taman. Azov.”. Movebank Data Repository, 10.5441/001/1.594 (2024).
238.Ilyashenko, E. I. et al. Data from: Study “1000 Cranes. Southern Kazakhstan.”. Movebank Data Repository, 10.5441/001/1.591 (2024).
239.Andryushchenko, Y., Pokrovsky, I., Bernd, V., Fiedler, W. & Wikelski, M. Data from: Study “1000 Cranes. Ukraine.”. Movebank Data Repository, 10.5441/001/1.590 (2024).
240.Mallory, M. L., Craik, S., Allard, K. A. & Gutowsky, S. Data from: Study “American Herring Gulls - GPS - Lobster Bay, Southwest Nova Scotia, Canada”. Movebank Data Repository, 10.5441/001/1.292 (2023).
241.Meier, C. M., Peev, S. G. & Liechti, F. Data from: Study “Bulgaria Sofia - Long term study on migratory movement of Alpine swifts (Apus melba)”. Movebank Data Repository, 10.5441/001/1.7kd62k00 (2020).
242.Smith, J. P. Data from: Study “HawkWatch International Golden Eagles”. Movebank Data Repository, 10.5441/001/1.95r77m9k (2019).
243.Powell, A. N., Oppel, S. & McGuire, R. Data from: Study “King Eider Alaska (UAF / USGS)”. Movebank Data Repository, 10.5441/001/1.339 (2024).
244.Batbayar, N., Galtbalt, B., Natsagdorj, T., Sukhbaatar, T. & Wikelski, M. Data from: Study “LifeTrack Mongolia Demoiselle cranes”. Movebank Data Repository, 10.5441/001/1.599 (2024).
245.Seyer, Y., Gauthier, G. & Lecomte, N. Data from: Study “Long-tailed Jaeger - GLS - Canadian Arctic”. Movebank data repositor, 10.5441/001/1.558kn337 (2022).
246.Škrábal, J., Literák, I. & Raab, R. Data from: Study “Milvus_milvus_Soaring_over_Adriatic_sea”. Movebank Data Repository, 10.5441/001/1.300 (2023).
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288.The data used in this study were accessed from Movebank (movebank.org, study name “(EBD) Lesser Kestrel (Falco naumanni) Spain, MERCURIO-SUMHAL”, study ID 2961927604) on 1 March 2025.
289.The data used in this study were accessed from Movebank (movebank.org, study name “A case of home range analysis of Japanese Sparrowhawks during the nestling period”, study ID 2116900796) on 1 March 2025.
290.The data used in this study were accessed from Movebank (movebank.org, study name “Annual Movements of Bicknell’s Thrush (Catharus bicknelli) from Light-level Geolocation”, study ID 1416160002) on 1 March 2025.
291.The data used in this study were accessed from Movebank (movebank.org, study name “Blackbird Czechia ICARUS TinyFox 2022”, study ID 2434921399) on 1 March 2025.
292.The data used in this study were accessed from Movebank (movebank.org, study name “Broad-winged Hawk habitat use, range, and movement ecology”, study ID 28691134) on 1 March 2025.
293.The data used in this study were accessed from Movebank (movebank.org, study name “Brown Pelican Raccoon Island LA 2014-2017”, study ID 581719332) on 1 March 2025.
294.The data used in this study were accessed from Movebank (movebank.org, study name “BTO - Whinnyfold 2021 - Kittiwake”, study ID 4447816442) on 1 March 2025.
295.The data used in this study were accessed from Movebank (movebank.org, study name “Caspian Gulls - Poland”, study ID 1208105916) on 1 March 2025.
296.The data used in this study were accessed from Movebank (movebank.org, study name “CLSW_Nebraska_2022”, study ID 2611337538) on 1 March 2025.
297.The data used in this study were accessed from Movebank (movebank.org, study name “Common Snipe GPS-GSM logger Poland-Russia”, study ID 924418031) on 1 March 2025.
298.The data used in this study were accessed from Movebank (movebank.org, study name “Common Whitethroat, Latvia”, study ID 4310399048) on 1 March 2025.
299.The data used in this study were accessed from Movebank (movebank.org, study name “Dendrocygna bicolor movement from Mexico City Manuel Grosselet”, study ID 3186161092) on 1 March 2025.
300.The data used in this study were accessed from Movebank (movebank.org, study name “Griffon Vulture Albstadt Salzburg (Gypsi)”, study ID 326568799) on 1 March 2025.
301.The data used in this study were accessed from Movebank (movebank.org, study name “Honey Buzzard Care Centre Release S Germany”, study ID 1701931040) on 1 March 2025.
302.The data used in this study were accessed from Movebank (movebank.org, study name “ICARUS Ascension Island Government”, study ID 1531481854) on 1 March 2025.
303.The data used in this study were accessed from Movebank (movebank.org, study name “Ivory gull N Greenland 2018/19”, study ID 1123149708) on 1 March 2025.
304.The data used in this study were accessed from Movebank (movebank.org, study name “KIRA SW LA”, study ID 4739876185) on 1 March 2025.
305.The data used in this study were accessed from Movebank (movebank.org, study name “Lapwing NFW Vanellus Vanellus”, study ID 1448409403) on 1 March 2025.
306.The data used in this study were accessed from Movebank (movebank.org, study name “LifeTrack Bald Eagle”, study ID 20873986) on 1 March 2025.
307.The data used in this study were accessed from Movebank (movebank.org, study name “LifeTrack Griffon Vulture Croatia”, study ID 154820583) on 1 March 2025.
308.The data used in this study were accessed from Movebank (movebank.org, study name “Long-billed Curlew Migration from the Intermountain West”, study ID 42451582) on 1 March 2025.
309.The data used in this study were accessed from Movebank (movebank.org, study name “marbledGodwit_USGS_ASC_argos”, study ID 547404600) on 1 March 2025.
310.The data used in this study were accessed from Movebank (movebank.org, study name “Milvus_milvus_atlantismarcuard”, study ID 672882373) on 1 March 2025.
311.The data used in this study were accessed from Movebank (movebank.org, study name “MPIAB Griffon Vulture Argos”, study ID 446571) on 1 March 2025.
312.The data used in this study were accessed from Movebank (movebank.org, study name “Northern Bald Ibis - Konrad Lorenz Research Station 2016”, study ID 185780950) on 1 March 2025.
313.The data used in this study were accessed from Movebank (movebank.org, study name “O_ASSEN - Eurasian oystercatchers (Haematopus ostralegus, Haematopodidae) breeding in Assen (the Netherlands)”, study ID 1605797471) on 1 March 2025.
314.The data used in this study were accessed from Movebank (movebank.org, study name “O_WESTERSCHELDE - Eurasian oystercatchers (Haematopus ostralegus, Haematopodidae) breeding in East Flanders (Belgium)”, study ID 1099562810) on 1 March 2025.
315.The data used in this study were accessed from Movebank (movebank.org, study name “Purple martin Progne subis movement ecology in southern Quebec”, study ID 1910442974) on 1 March 2025.
316.The data used in this study were accessed from Movebank (movebank.org, study name “Purple martin Progne subis movement ecology in southern Quebec”, study ID 1958514115) on 1 March 2025.
317.The data used in this study were accessed from Movebank (movebank.org, study name “Raptors NABU Moessingen public”, study ID 186178781) on 1 March 2025.
318.The data used in this study were accessed from Movebank (movebank.org, study name “Richard’s Pipit (Anthus richardi)”, study ID 1720094461) on 1 March 2025.
319.The data used in this study were accessed from Movebank (movebank.org, study name “Rough-legged Buzzard in variable environment”, study ID 944655375) on 1 March 2025.
320.The data used in this study were accessed from Movebank (movebank.org, study name “rynchops niger”, study ID 3218698288) on 1 March 2025.
321.The data used in this study were accessed from Movebank (movebank.org, study name “Sabine’s Gulls in the Juan de Fuca Eddy”, study ID 304527187) on 1 March 2025.
322.The data used in this study were accessed from Movebank (movebank.org, study name “Saxicola rubetra Western Lusatia/Germany”, study ID 1668665047) on 1 March 2025.
323.The data used in this study were accessed from Movebank (movebank.org, study name “Semipalmated Sandpiper movement and habitat use in Northeast Brazil”, study ID 1996135412) on 1 March 2025.
324.The data used in this study were accessed from Movebank (movebank.org, study name “Short-eared Owl & Northern Harrier - NYSDEC”, study ID 6250087) on 1 March 2025.
325.The data used in this study were accessed from Movebank (movebank.org, study name “Spanish sparrow (Passer hispaniolensis) Bulgaria”, study ID 1830874036) on 1 March 2025.
326.The data used in this study were accessed from Movebank (movebank.org, study name “Spotted eagles NE Poland”, study ID 384882516) on 1 March 2025.
327.The data used in this study were accessed from Movebank (movebank.org, study name “Surf Scoter (Diving Bird Study)”, study ID 3360767360) on 1 March 2025.
328.The data used in this study were accessed from Movebank (movebank.org, study name “Surfbird_UAF_BLM_InteriorAlaska”, study ID 3945977313) on 1 March 2025.
329.The data used in this study were accessed from Movebank (movebank.org, study name “TBMUCOMU.GastonMontevecchi.NWAtlantic”, study ID 14381504) on 1 March 2025.
330.The data used in this study were accessed from Movebank (movebank.org, study name “Thick-billed murre Elliott Coats 2010”, study ID 248994009) on 1 March 2025.
331.The data used in this study were accessed from Movebank (movebank.org, study name “Thick-billed murre Elliott Coats 2011”, study ID 249266943) on 1 March 2025.
332.The data used in this study were accessed from Movebank (movebank.org, study name “Thick-billed murre Elliott Coats 2013”, study ID 376145741) on 1 March 2025.
333.The data used in this study were accessed from Movebank (movebank.org, study name “Thick-billed murre Gaston PLI 2014”, study ID 394802766) on 1 March 2025.
334.The data used in this study were accessed from Movebank (movebank.org, study name “Thick-billed murre Gilchrist and Elliott Coats 2016”, study ID 287187244) on 1 March 2025.
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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Citations

Ma, J. A global dataset of spatiotemporal co-occurrence patterns of avian influenza virus -associated migratory birds. Figshare10.6084/m9.figshare.31044229.v1 (2026). [DOI] [PMC free article] [PubMed]
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Kölzsch, A. et al. Data from: Flyway connectivity and exchange primarily driven by moult migration in geese [North Sea population]. Movebank Data Repository10.5441/001/1.46b0mq21 (2019). [DOI] [PMC free article] [PubMed]
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Data Availability Statement

The dataset is publicly available on figshare⁵⁵ at 10.6084/m9.figshare.31044229.v1. It comprises eight Excel files, including three core dataset files and five supporting data files.

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[CR64] 64.Baak, J. E., Patterson, A., Gilchrist, H. G. & Elliott, K. H. Data from: First evidence of diverging migration and overwintering strategies in glaucous gulls (Larus hyperboreus) from the Canadian Arctic. Movebank Data Repository, 10.5441/001/1.tj948m64 (2021).

[CR65] 65.Kölzsch, A. et al. Data from: Flyway connectivity and exchange primarily driven by moult migration in geese [North Sea population]. Movebank Data Repository10.5441/001/1.46b0mq21 (2019). [DOI] [PMC free article] [PubMed]

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[CR69] 69.Carlson, B., Rotics, S., Nathan, R., Wikelski, M. & Jetz, W. Data from: Individual environmental niches in mobile organisms. Movebank Data Repository, 10.5441/001/1.rj21g1p1 (2021). [DOI] [PMC free article] [PubMed]

[CR70] 70.Efrat, R., Hatzofe, O. & Nathan, R. Data from: Landscape-dependent time versus energy optimisations in pelicans migrating through a large ecological barrier. Movebank Data Repository, 10.5441/001/1.hs79pk45 (2019).

[CR71] 71.Nuijten, R. J. M., Gerrits, T., de Vries, P. P., Müskens, G. J. D. M. & Nolet, B. A. Data from: Less is more: on-board lossy compression of accelerometer data increases biologging capacity. Movebank Data Repository, 10.5441/001/1.8ms7mm80 (2020). [DOI] [PMC free article] [PubMed]

[CR72] 72.Winkler, D. W. et al. Data from: Long-distance range expansion and rapid adjustment of migration in a newly established population of Barn Swallows breeding in Argentina. Movebank Data Repository, 10.5441/001/1.rt00m81v (2017). [DOI] [PubMed]

[CR73] 73.Schwemmer, P. & Garthe, S. Data from: Migrating curlews on schedule: departure and arrival patterns of a long-distance migrant depend on time and breeding location rather than on wind conditions. Movebank Data Repository, 10.5441/001/1.715k46g2 (2021). [DOI] [PMC free article] [PubMed]

[CR74] 74.Buitendijk, N. H. et al. Data from: More grazing, more damage? Assessed yield loss on agricultural grassland relates non-linearly to goose grazing pressure. Movebank Data Repository, 10.5441/001/1.fk899541 (2023).

[CR75] 75.Boiko, D., Wikelski, M. & Fiedler, W. Data from: Moulting sites of Latvian whooper swan Cygnus cygnus cygnets fitted with GPS-GSM transmitters. Movebank Data Repository, 10.5441/001/1.f89984gn (2019).

[CR76] 76.Nye, P., Hewitt, G., Swenson, T. & Kays, R. Data from: New York State bald eagle report 2010. Movebank Data Repository, 10.5441/001/1.s65q50j0 (2018).

[CR77] 77.Byholm, P., Beal, M., Lötberg, U. & Åkesson, S. Data from: Paternal transmission of migration knowledge in a long-distance bird migrant. Movebank Data Repository, 10.5441/001/1.352qf1cv (2022). [DOI] [PMC free article] [PubMed]

[CR78] 78.Petersen, M. R. & Douglas, D. Data from: Post-fledging movements of juvenile common mergansers (Mergus merganser) in Alaska as inferred by satellite telemetry. Movebank Data Repository, 10.5441/001/1.3gc013f3 (2016).

[CR79] 79.Goodenough, K. S. & Patton, R. T. Data from: Satellite telemetry reveals strong fidelity to migration routes and wintering grounds for the gull-billed tern (Gelochelidon nilotica). Movebank Data Repository, 10.5441/001/1.d73t7vt8 (2021).

[CR80] 80.Kölzsch, A., Müskens, G. J. D. M., Nolet, B. A. & Wikelski, M. Data from: Scaring waterfowl as a management tool: how much more do geese forage after disturbance? Movebank Data Repository, 10.5441/001/1.7tp81b7b (2016).

[CR81] 81.Ilyashenko, E. I. et al. Data from: Study “1000 Cranes. Russia. Common Crane.”. Movebank Data Repository, 10.5441/001/1.593 (2024).

[CR82] 82.Ilyashenko, E. I. et al. Data from: Study “1000 Cranes. Russia. Transbaikalia.”. Movebank Data Repository, 10.5441/001/1.592 (2024).

[CR83] 83.Jennings, S., Lumpkin, D., Warnock, N. & Condeso, E. Data from: Study “Audubon Canyon Ranch egret telemetry project”. Movebank Data Repository, 10.5441/001/1.641 (2025).

[CR84] 84.McDermott, M. T., Madden, S. A. & Safran, R. J. Data from: Study “Barn Swallow Hirundidae GPS data from Boulder County, CO, USA”. Movebank Data Repository, 10.5441/001/1.8c9b82qk (2023).

[CR85] 85.Dagys, M. & Žydelis, R. Data from: Study “Common Crane Lithuania GPS, 2015-2016”. Movebank Data Repository, 10.5441/001/1.604 (2024).

[CR86] 86.Giunchi, D. et al. Data from: Study “Eurasian teal, Giunchi, Italy”. Movebank Data Repository, 10.5441/001/1.250 (2023).

[CR87] 87.Žydelis, R., Desholm, M., Månsson, J., Nilsson, L. & Skov, H. Data from: Study “GPS telemetry of Common Cranes, Sweden”. Movebank Data Repository, 10.5441/001/1.597 (2024).

[CR88] 88.Clark, D. E., Mackenzie, S. A., Koenen, K., Whitney, J. & DeStefano, S. Data from: Study “Herring Gulls (Larus Argentatus); Clark; Massachussets, United States”. Movebank Data Repository, 10.5441/001/1.3th8b5q3 (2020).

[CR89] 89.Gilchrist, H. G., Macdonald, C. A., Janssen, M. H., Allard, K. A. & Anderson, C. M. Data from: Study “Herring Gulls (Larus Argentatus); Gilchrist; East Bay Island, Canada”. Movebank Data Repository, 10.5441/001/1.1r1s4v8d (2020).

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[CR91] 91.Fiedler, W. et al. Data from: Study “LifeTrack White Stork Bavaria” (2014-2023). Movebank Data Repository, 10.5441/001/1.v1cs4nn0_2 (2024).

[CR92] 92.Maxhuni, Q., Gashi, A., Hoxha, L., Wolf, G. & Fiedler, W. Data from: Study “LifeTrack White Stork Kosova”. Movebank Data Repository, 10.5441/001/1.s367rd3k (2021).

[CR93] 93.Fiedler, W., Flack, A., Schmid, A., Reinhard, U. & Wikelski, M. Data from: Study “LifeTrack White Stork Oberschwaben” (2014-2023). Movebank Data Repository, 10.5441/001/1.ck04mn78_2 (2024).

[CR94] 94.Fiedler, W. et al. Data from: Study “LifeTrack White Stork Rheinland-Pfalz” (2015-2023). Movebank Data Repository, 10.5441/001/1.4192t2j4_2 (2024).

[CR95] 95.Fiedler, W. et al. Data from: Study “LifeTrack White Stork SW Germany” (2013-2023). Movebank Data Repository, 10.5441/001/1.ck04mn78_2 (2024).

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[CR99] 99.Garthe, S. et al. Data from: Terrestrial and marine foraging strategies of an opportunistic seabird species breeding in the Wadden Sea. Movebank Data Repository, 10.5441/001/1.nk286sc0 (2016). [DOI] [PMC free article] [PubMed]

[CR100] 100.Burnham, K. K. Data from: The history and range expansion of peregrine falcons in the Thule area, northwest Greenland. Movebank Data Repository, 10.5441/001/1.b3b511d2 (2020).

[CR101] 101.Bontekoe, I. D., Flack, A. & Fiedler, W. Data from: The price of being late: short- and long-term consequences of a delayed migration timing [control birds]. Movebank Data Repository, 10.5441/001/1.271 (2023). [DOI] [PMC free article] [PubMed]

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[CR103] 103.Choi, C.-Y. et al. Data from: Tracking domestic ducks: a novel approach for documenting poultry market chains in the context of avian influenza transmission. Movebank Data Repository, 10.5441/001/1.38f467s7 (2016).

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[CR142] 142.The data used in this study were accessed from Movebank (movebank.org, study name “Barn swallows breeding in Kraghede”, study ID 4201934806) on 1 March 2025.

[CR143] 143.The data used in this study were accessed from Movebank (movebank.org, study name “barTailedGodwit_USGS_ASC_argos”, study ID 1718959411) on 1 March 2025.

[CR144] 144.The data used in this study were accessed from Movebank (movebank.org, study name “Bean Goose Anser fabalis Finnmark”, study ID 11223924) on 1 March 2025.

[CR145] 145.The data used in this study were accessed from Movebank (movebank.org, study name “Bill Cochran Peregrine falcon migration 1973-75”, study ID 274355544) on 1 March 2025.

[CR146] 146.The data used in this study were accessed from Movebank (movebank.org, study name “BOP_RODENT - Rodent specialized birds of prey (Circus, Asio, Buteo) in Flanders (Belgium)”, study ID 1278021460) on 1 March 2025.

[CR147] 147.The data used in this study were accessed from Movebank (movebank.org, study name “Bubulcus ibis_Vollot_ENVT_65_ID_PROG1035”, study ID 2915700754) on 1 March 2025.

[CR148] 148.The data used in this study were accessed from Movebank (movebank.org, study name “Chicago BCNH Project (Druid)”, study ID 3902656356) on 1 March 2025.

[CR149] 149.The data used in this study were accessed from Movebank (movebank.org, study name “Chicago BCNH Project”, study ID 2830157729) on 1 March 2025.

[CR150] 150.The data used in this study were accessed from Movebank (movebank.org, study name “Common Crane 2020 (Lithuanian University of Educational Studies; LEU)”, study ID 1229945587) on 1 March 2025.

[CR151] 151.The data used in this study were accessed from Movebank (movebank.org, study name “Common Cuckoo (A), Southern Sweden”, study ID 49915781) on 1 March 2025.

[CR152] 152.The data used in this study were accessed from Movebank (movebank.org, study name “Common Cuckoo (C), Eastern Europe”, study ID 55252460) on 1 March 2025.

[CR153] 153.The data used in this study were accessed from Movebank (movebank.org, study name “Corvus corone [ID_PROG 883]”, study ID 1266784970) on 1 March 2025.

[CR154] 154.The data used in this study were accessed from Movebank (movebank.org, study name “CURLEW_VLAANDEREN - Eurasian curlews (Numenius arquata, Scolopacidae) breeding in Flanders (Belgium)”, study ID 1841091905) on 1 March 2025.

[CR155] 155.The data used in this study were accessed from Movebank (movebank.org, study name “DELTATRACK - Herring gulls (Larus argentatus, Laridae) and lesser black-backed gulls (Larus fuscus, Laridae) breeding at Neeltje Jans (Netherlands)”, study ID 1258895879) on 1 March 2025.

[CR156] 156.The data used in this study were accessed from Movebank (movebank.org, study name “Egrets & Herons”, study ID 17469219) on 1 March 2025.

[CR157] 157.The data used in this study were accessed from Movebank (movebank.org, study name “Forest Park Living Lab”, study ID 1605024900) on 1 March 2025.

[CR158] 158.The data used in this study were accessed from Movebank (movebank.org, study name “FTZ Geese Wadden Sea”, study ID 69724677) on 1 March 2025.

[CR159] 159.The data used in this study were accessed from Movebank (movebank.org, study name “Graugans Zugverhalten Neusiedler See”, study ID 505156776) on 1 March 2025.

[CR160] 160.The data used in this study were accessed from Movebank (movebank.org, study name “Great Cormorant Lake Constance MPIAB”, study ID 2988309) on 1 March 2025.

[CR161] 161.The data used in this study were accessed from Movebank (movebank.org, study name “Gulls - Minsk”, study ID 2272852276) on 1 March 2025.

[CR162] 162.The data used in this study were accessed from Movebank (movebank.org, study name “gullSpecies_USGS_ASC_argosGPS”, study ID 1091848505) on 1 March 2025.

[CR163] 163.The data used in this study were accessed from Movebank (movebank.org, study name “Habitrack European Turtle Dove”, study ID 3413045568) on 1 March 2025.

[CR164] 164.The data used in this study were accessed from Movebank (movebank.org, study name “Herring Gulls (Larus Argentatus); Ronconi; Kent Island, Canada”, study ID 1071101052) on 1 March 2025.

[CR165] 165.The data used in this study were accessed from Movebank (movebank.org, study name “Herring Gulls (Larus Argentatus); Ronconi; Sable Island, Canada”, study ID 1080341737) on 1 March 2025.

[CR166] 166.The data used in this study were accessed from Movebank (movebank.org, study name “HG_OOSTENDE - Herring gulls (Larus argentatus, Laridae) breeding at the southern North Sea coast (Belgium)”, study ID 986040562) on 1 March 2025.

[CR167] 167.The data used in this study were accessed from Movebank (movebank.org, study name “HUJ MPIAB White Stork GSM 2013”, study ID 10449698) on 1 March 2025.

[CR168] 168.The data used in this study were accessed from Movebank (movebank.org, study name “HUJ MPIAB White Stork GSM E-Obs”, study ID 7002955) on 1 March 2025.

[CR169] 169.The data used in this study were accessed from Movebank (movebank.org, study name “ICARUS Cuckoo Holland”, study ID 1539583795) on 1 March 2025.

[CR170] 170.The data used in this study were accessed from Movebank (movebank.org, study name “ICARUS Mongolia cuckoos Nymba”, study ID 1542155599) on 1 March 2025.

[CR171] 171.The data used in this study were accessed from Movebank (movebank.org, study name “ICARUS Pacific Coast Peregrine”, study ID 1748399252) on 1 March 2025.

[CR172] 172.The data used in this study were accessed from Movebank (movebank.org, study name “ICARUS Turkey Cagan”, study ID 1541820092) on 1 March 2025.

[CR173] 173.e data used in this study were accessed from Movebank (movebank.org, study name “ICARUS Turtle doves”, study ID 1542192442) on 1 March 2025.

[CR174] 174.The data used in this study were accessed from Movebank (movebank.org, study name “Lake Constance Ducks”, study ID 2927282) on 1 March 2025.

[CR175] 175.The data used in this study were accessed from Movebank (movebank.org, study name “Larus heuglini_1”, study ID 1445058753) on 1 March 2025.

[CR176] 176.The data used in this study were accessed from Movebank (movebank.org, study name “Larus michahellis X Larus cachinnans hybrids”, study ID 2190520177) on 1 March 2025.

[CR177] 177.The data used in this study were accessed from Movebank (movebank.org, study name “LifeTrack - Evros Delta”, study ID 8927992) on 1 March 2025.

[CR178] 178.The data used in this study were accessed from Movebank (movebank.org, study name “LifeTrack Ducks Lake Constance”, study ID 236953686) on 1 March 2025.

[CR179] 179.The data used in this study were accessed from Movebank (movebank.org, study name “LifeTrack White Stork Greece Evros Delta”, study ID 10449535) on 1 March 2025.

[CR180] 180.The data used in this study were accessed from Movebank (movebank.org, study name “LifeTrack White Stork Loburg”, study ID 10449318) on 1 March 2025.

[CR181] 181.The data used in this study were accessed from Movebank (movebank.org, study name “LifeTrack White Stork Moscow”, study ID 10596067) on 1 March 2025.

[CR182] 182.The data used in this study were accessed from Movebank (movebank.org, study name “LifeTrack White Stork Poland”, study ID 10763606) on 1 March 2025.

[CR183] 183.The data used in this study were accessed from Movebank (movebank.org, study name “LifeTrack White Stork Sarralbe [ID_PROG 1093]”, study ID 1562253659) on 1 March 2025.

[CR184] 184.The data used in this study were accessed from Movebank (movebank.org, study name “LifeTrack White Stork South Africa”, study ID 8008999) on 1 March 2025.

[CR185] 185.The data used in this study were accessed from Movebank (movebank.org, study name “LifeTrack White Stork Tunisia”, study ID 10157679) on 1 March 2025.

[CR186] 186.The data used in this study were accessed from Movebank (movebank.org, study name “LifeTrack White Stork Uzbekistan”, study ID 9493881) on 1 March 2025.

[CR187] 187.The data used in this study were accessed from Movebank (movebank.org, study name “LifeTrack Whooper Swan Latvia”, study ID 92261778) on 1 March 2025.

[CR188] 188.The data used in this study were accessed from Movebank (movebank.org, study name “MEDGULL_ANTWERPEN - Mediterranean gulls (Ichthyaetus melanocephalus, Laridae) breeding near Antwerp (Belgium)”, study ID 1609400843) on 1 March 2025.

[CR189] 189.The data used in this study were accessed from Movebank (movebank.org, study name “MH_ANTWERPEN - Western marsh harriers (Circus aeruginosus, Accipitridae) breeding near Antwerp (Belgium)”, study ID 938783961) on 1 March 2025.

[CR190] 190.The data used in this study were accessed from Movebank (movebank.org, study name “Milvus migrans”, study ID 892924356) on 1 March 2025.

[CR191] 191.The data used in this study were accessed from Movebank (movebank.org, study name “MPIAB White Stork Greece Argos”, study ID 446659) on 1 March 2025.

[CR192] 192.The data used in this study were accessed from Movebank (movebank.org, study name “MPIAB white stork lifetime tracking data (2013-2014)”, study ID 74496970) on 1 March 2025.

[CR193] 193.The data used in this study were accessed from Movebank (movebank.org, study name “MPIAB White Stork Oriental Argos”, study ID 446663) on 1 March 2025.

[CR194] 194.The data used in this study were accessed from Movebank (movebank.org, study name “MPIAB White Stork Prinzesschen”, study ID 1898591) on 1 March 2025.

[CR195] 195.The data used in this study were accessed from Movebank (movebank.org, study name “MPIAB White Stork South African Population Argos”, study ID 446667) on 1 March 2025.

[CR196] 196.The data used in this study were accessed from Movebank (movebank.org, study name “NC Breeding ABDU”, study ID 1404033416) on 1 March 2025.

[CR197] 197.The data used in this study were accessed from Movebank (movebank.org, study name “Osprey Bierregaard North and South America”, study ID 8868155) on 1 March 2025.

[CR198] 198.The data used in this study were accessed from Movebank (movebank.org, study name “Pandion haliaetus Osprey - SouthEast Michigan”, study ID 10204361) on 1 March 2025.

[CR199] 199.The data used in this study were accessed from Movebank (movebank.org, study name “Peregrine Falcon - NYSDEC”, study ID 6459871) on 1 March 2025.

[CR200] 200.The data used in this study were accessed from Movebank (movebank.org, study name “Poultry network China 2022”, study ID 1909487338) on 1 March 2025.

[CR201] 201.The data used in this study were accessed from Movebank (movebank.org, study name “Poultry network Thailand 2022”, study ID 1879445455) on 1 March 2025.

[CR202] 202.The data used in this study were accessed from Movebank (movebank.org, study name “Sarus Crane, van Zalinge, Cambodia”, study ID 47450376) on 1 March 2025.

[CR203] 203.The data used in this study were accessed from Movebank (movebank.org, study name “Satellite tracking of Goosander in Scotland”, study ID 2526306516) on 1 March 2025.

[CR204] 204.The data used in this study were accessed from Movebank (movebank.org, study name “Seaducks in the Fehmarn Belt (southern Baltic)”, study ID 1962595) on 1 March 2025.

[CR205] 205.The data used in this study were accessed from Movebank (movebank.org, study name “Shelduck Italy ISPRA MPIAB”, study ID 1963631608) on 1 March 2025.

[CR206] 206.The data used in this study were accessed from Movebank (movebank.org, study name “Solovki Larus Track”, study ID 312267867) on 1 March 2025.

[CR207] 207.The data used in this study were accessed from Movebank (movebank.org, study name “SPOONBILL_VLAANDEREN - Eurasian spoonbills (Platalea leucorodia, Threskiornithidae) in Flanders (Belgium)”, study ID 2313947453) on 1 March 2025.

[CR208] 208.The data used in this study were accessed from Movebank (movebank.org, study name “Tracking of Caspian Terns (Hydroprogne caspia) in the Swedish Baltic Sea 2017-2020”, study ID 1575973021) on 1 March 2025.

[CR209] 209.The data used in this study were accessed from Movebank (movebank.org, study name “Variability of White Stork flight patterns prior to earthquakes”, study ID 1498452485) on 1 March 2025.

[CR210] 210.The data used in this study were accessed from Movebank (movebank.org, study name “Wader migration German Wadden Sea: bar-tailed godwits”, study ID 5666500) on 1 March 2025.

[CR211] 211.The data used in this study were accessed from Movebank (movebank.org, study name “whimbrel_USGS_ASC_argos”, study ID 854852176) on 1 March 2025.

[CR212] 212.The data used in this study were accessed from Movebank (movebank.org, study name “White stork Ciconidae Western Poland”, study ID 1252230318) on 1 March 2025.

[CR213] 213.The data used in this study were accessed from Movebank (movebank.org, study name “White-tailed Eagle Poland.”, study ID 384868221) on 1 March 2025.

[CR214] 214.The data used in this study were accessed from Movebank (movebank.org, study name “Yellow-legged Gulls”, study ID 1724475305) on 1 March 2025.

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[CR218] 218.Efrat, R., Hatzofe, O., Mueller, T., Sapir, N. & Berger-Tal, O. Data from: Early life and acquired experiences interact in shaping migratory and flight behaviors. Movebank Data Repository, 10.5441/001/1.298 (2023).

[CR219] 219.Bildstein, K. L., Barber, D. & Bechard, M. J. Data from: Environmental drivers of variability in the movement ecology of turkey vultures (Cathartes aura) in North and South America. Movebank Data Repository, 10.5441/001/1.46ft1k05 (2014). [DOI] [PMC free article] [PubMed]

[CR220] 220.Lislevand, T., Hahn, S., Rislaa, S. & Briedis, M. Data from: First records of complete annual cycles in water rails Rallus aquaticus show evidence of itinerant breeding and a complex migration system. Movebank Data Repository, 10.5441/001/1.761jk64n (2020).

[CR221] 221.Pedersen, L., Jackson, K., Thorup, K. & Tøttrup, A. P. Data from: Full-year tracking suggests endogenous control of migration timing in a long-distance migratory songbird. Movebank Data Repository, 10.5441/001/1.7mf48770 (2018).

[CR222] 222.Jeglinski, J. W. E. et al. Data from: HPAIV outbreak triggers short‐term colony connectivity in a seabird metapopulation. Movebank Data Repository, 10.5441/001/1.607 (2024). [DOI] [PMC free article] [PubMed]

[CR223] 223.Meier, C. M., Buchmann, M. & Liechti, F. Data from: Locally adapted migration strategies: Comparing routes and timing of northern wheatears from alpine and lowland European populations [Austria]. Movebank Data Repository, 10.5441/001/1.tn4h3kt0 (2022).

[CR224] 224.Meier, C. M., Rime, Y. & Liechti, F. Data from: Locally adapted migration strategies: Comparing routes and timing of northern wheatears from alpine and lowland European populations [Switzerland]. Movebank Data Repository, 10.5441/001/1.tn4h3kt0 (2022).

[CR225] 225.Sherub, S. & Wikelski, M. Data from: Longer days enable higher diurnal activity for migratory birds [Himalayan griffons]. Movebank data repositor, 10.5441/001/1.4n2501f5 (2021). [DOI] [PubMed]

[CR226] 226.Tøttrup, A. P., Pedersen, L., Onrubia, A. & Thorup, K. Data from: Migration of red-backed shrikes from the Iberian Peninsula: optimal or sub-optimal detour? Movebank Data Repository, 10.5441/001/1.32m2335q (2017).

[CR227] 227.Hill, J. M. & Renfrew, R. B. Data from: Migration patterns of upland sandpipers in the western hemisphere. Movebank Data Repository, 10.5441/001/1.3pt25757 (2019).

[CR228] 228.Moore, J. D. et al. Data from: Migration phenology and patterns of American woodcock in central North America derived using satellite telemetry. Movebank Data Repository, 10.5441/001/1.8764q39q (2021).

[CR229] 229.Exo, K.-M., Hillig, F. & Bairlein, F. Data from: Migration routes and strategies of Grey Plovers (Pluvialis squatarola) on the East Atlantic Flyway as revealed by satellite tracking. Movebank Data Repository, 10.5441/001/1.vv0ft02m (2019).

[CR230] 230.Spiegel, O. M. et al. Data from: Moving beyond curve-fitting: using complementary data to assess alternative explanations for long movements of three vulture species. Movebank Data Repository, 10.5441/001/1.8c56f72s (2015).

[CR231] 231.Pedersen, L. et al. Data from: Remarkably similar migration patterns between different red-backed shrike populations suggest that migration rather than breeding area phenology determines the annual cycle. Movebank Data Repository, 10.5441/001/1.4bt7365c (2020).

[CR232] 232.Buechley, E. R. & Şekercioğlu, C. A. A. H. Data from: Satellite tracking a wide‐ranging endangered vulture species to target conservation actions in the Middle East and East Africa. Movebank Data Repository, 10.5441/001/1.385gk270 (2019).

[CR233] 233.Léandri-Breton, D.-J., Lamarre, J.-F. O. & Bety, J. Data from: Seasonal variation in migration strategies used to cross ecological barriers in a Nearctic migrant wintering in Africa. Movebank Data Repository, 10.5441/001/1.f01v7r80 (2019).

[CR234] 234.Pedersen, L., Nina Munkholt, J., Strandberg, R., Thorup, K. & Tøttrup, A. P. Data from: Sex-specific difference in migration schedule as a precursor of protandry in a long-distance migratory bird. Movebank Data Repository, 10.5441/001/1.j71640kh (2019). [DOI] [PubMed]

[CR235] 235.Batbayar, N., Galtbalt, B., Natsagdorj, T., Sukhbaatar, T. & Wikelski, M. Data from: Study “1000 Cranes. Mongolia.”. Movebank Data Repository, 10.5441/001/1.598 (2024).

[CR236] 236.Ilyashenko, E. I. et al. Data from: Study “1000 Cranes. Russia. Altai.”. Movebank Data Repository, 10.5441/001/1.596 (2024).

[CR237] 237.Ilyashenko, E. I. et al. Data from: Study “1000 Cranes. Russia. Taman. Azov.”. Movebank Data Repository, 10.5441/001/1.594 (2024).

[CR238] 238.Ilyashenko, E. I. et al. Data from: Study “1000 Cranes. Southern Kazakhstan.”. Movebank Data Repository, 10.5441/001/1.591 (2024).

[CR239] 239.Andryushchenko, Y., Pokrovsky, I., Bernd, V., Fiedler, W. & Wikelski, M. Data from: Study “1000 Cranes. Ukraine.”. Movebank Data Repository, 10.5441/001/1.590 (2024).

[CR240] 240.Mallory, M. L., Craik, S., Allard, K. A. & Gutowsky, S. Data from: Study “American Herring Gulls - GPS - Lobster Bay, Southwest Nova Scotia, Canada”. Movebank Data Repository, 10.5441/001/1.292 (2023).

[CR241] 241.Meier, C. M., Peev, S. G. & Liechti, F. Data from: Study “Bulgaria Sofia - Long term study on migratory movement of Alpine swifts (Apus melba)”. Movebank Data Repository, 10.5441/001/1.7kd62k00 (2020).

[CR242] 242.Smith, J. P. Data from: Study “HawkWatch International Golden Eagles”. Movebank Data Repository, 10.5441/001/1.95r77m9k (2019).

[CR243] 243.Powell, A. N., Oppel, S. & McGuire, R. Data from: Study “King Eider Alaska (UAF / USGS)”. Movebank Data Repository, 10.5441/001/1.339 (2024).

[CR244] 244.Batbayar, N., Galtbalt, B., Natsagdorj, T., Sukhbaatar, T. & Wikelski, M. Data from: Study “LifeTrack Mongolia Demoiselle cranes”. Movebank Data Repository, 10.5441/001/1.599 (2024).

[CR245] 245.Seyer, Y., Gauthier, G. & Lecomte, N. Data from: Study “Long-tailed Jaeger - GLS - Canadian Arctic”. Movebank data repositor, 10.5441/001/1.558kn337 (2022).

[CR246] 246.Škrábal, J., Literák, I. & Raab, R. Data from: Study “Milvus_milvus_Soaring_over_Adriatic_sea”. Movebank Data Repository, 10.5441/001/1.300 (2023).

[CR247] 247.Schweitzer, S., Bryan, A. L., Jr., Brzorad, J. & Kays, R. Data from: Study “NC Wood Stork Tracking”. Movebank Data Repository, 10.5441/001/1.303 (2023).

[CR248] 248.d’Entremont, K. J. N., Davoren, G. K. & Montevecchi, W. A. Data from: Study “Northern Gannet Breeding Season GPS Data from Cape St. Mary’s, NL, Canada: 2019 to 2022”. Movebank Data Repository, 10.5441/001/1.5km7v2s3 (2023).

[CR249] 249.Meier, C. M., Aymí, R. & Liechti, F. Data from: Study “Spain Tarragona - Long term study on migratory movement of Alpine swifts (Apus melba)”. Movebank Data Repository, 10.5441/001/1.96t76sg0 (2020).

[CR250] 250.Meier, C. M. & Liechti, F. Data from: Study “Switzerland Lenzburg - Long term study on migratory movement of Alpine swifts (Apus melba)”. Movebank Data Repository, 10.5441/001/1.31v444sc (2020).

[CR251] 251.Meier, C. M., Karaardıç, H. & Liechti, F. Data from: Study “Turkey Pirasali - Long term study on migratory movement of Alpine swifts (Apus melba)”. Movebank Data Repository, 10.5441/001/1.34k562m5 (2020).

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PERMALINK

A global dataset of spatiotemporal co-occurrence patterns of avian influenza virus-associated migratory birds

Jun Ma

Yan-He Wang

Yun-Bo Qiu

Jin-Jin Chen

Yun Han

Yan Zhang

Sheng-Hong Lin

Qing-Jie Wang

Long-Tao Chen

Xin-Jing Zhao

Sheng Zhang

Tian Tang

Yao Tian

Yu-Feng Yang

Qiang Xu

Zi-Da Meng

Chen-Long Lv

Guo-Lin Wang

Feng Hong

Li-Qun Fang

Abstract

Background & Summary

Methods

Data collection

Fig. 1.

Data Records

Daily species pairs.xlsx

Administrative division summary.xlsx

Species pair summary.xlsx

Fig. 2.

Fig. 3.

Fig. 4.

Fig. 5.

Technical Validation

Validation of AIV-associated migratory bird range representatives

Validation of the biological relevance of co-occurrence sites

Usage Notes

Ecological research applications

Disease transmission and variation risk assessment

Conservation planning applications

Data limitations

Acknowledgements

Author contributions

Data availability

Code availability

Competing interests

Footnotes

Contributor Information

References

Associated Data

Data Citations

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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