303e2244-4d11-4ab8-86c3-3c305be8cd0d https://www.gbifchina.org.cn/resource?r=aerialsurvey_sonia Jingpeng Cao State Key Laboratory of Regional and Urban Ecology, Research Centre for Eco-Environmental sciences, Chinese Academy of Sciences caojingpeng.eartha@gmail.com Fanjuan Meng State Key Laboratory of Regional and Urban Ecology, Research Centre for Eco-Environmental sciences, Chinese Academy of Sciences George Kirtaev Severtsov Institute of Ecology and Evolution, Russian Academy of Sciences Diana Solovyeva Institute of Biological Problems of the North, Far-Eastern Branch, Russian Academy of Sciences Valeriya Danilova Goose, Swan, and Duck Study Group of Northern Eurasia Natalya Rogova Goose, Swan, and Duck Study Group of Northern Eurasia Evgeniya Melikhova Goose, Swan, and Duck Study Group of Northern Eurasia Zheping Xu Department of Information Resources Management, School of Economics and Management, University of Chinese Academy of Sciences Qingshan Zhao State Key Laboratory of Regional and Urban Ecology, Research Centre for Eco-Environmental sciences, Chinese Academy of Sciences Sonia B. Rozenfeld Severtsov Institute of Ecology and Evolution, Russian Academy of Sciences 2026-04-08 eng We present a comprehensive, decade-long (2014–2024) aerial survey dataset of northern Eurasian waterbirds, covering a broad northern Eurasian study area, with survey effort concentrated in the Russian Arctic and Subarctic. Surveys in a purpose-built light hydroplane covered 1,140,337 km of flight tracks across 67 administrative districts and a net, non-overlapping area of 1,918,845 km² (45.20–76.52°N, 35.49°E–180.00°E / 180.00°W–172.05°W). The dataset contains 97,638 georeferenced occurrence records, comprising 2 distinct survey components: marine (14%) and inland basin (86%) surveys. The 10 most abundant species (4 geese and 6 ducks) account for 76% of all individuals. Following spatial deduplication with survey-type grouping, the dataset encompasses 2,438,521 deduplicated individuals from 42 species in 19 genera, distributed as: marine surveys: 397,373 individuals (16%) from 34 species; basin surveys: 2,041,148 individuals (84%) from 42 species. These records provide a spatially explicit baseline for analyses of broad distribution patterns and conservation planning in surveyed regions of northern Eurasia. sampling event waterbird census; major water basin; species diversity; species distribution; biodiversity monitoring; Darwin Core; GBIF aerial surveys GBIF Dataset Type Vocabulary: http://rs.gbif.org/vocabulary/gbif/dataset_type_2015-07-10.xml Observation GBIF Dataset Subtype Vocabulary: http://rs.gbif.org/vocabulary/gbif/dataset_subtype.xml This work is licensed under a Creative Commons Attribution (CC-BY 4.0) License. Creative Commons Attribution 4.0 International https://spdx.org/licenses/CC-BY-4.0.html CC-BY-4.0 The surveys encompassed a vast geographical range from 45.20°N to 76.52°N in latitude, extending across both sides of the 180° meridian to include western (172.05°W to 180.00°W) and eastern (35.49°E to 180.00°E) longitudinal domains. -179.998085 179.991733 76.519422 45.204045 2015-09-20 2015-09-20 N/A phylum Chordata class Aves order Anseriformes family Anatidae kingdom Animalia Aerial surveys have a long history, and are widely applied to various animal taxa in both terrestrial and marine environments. Its application began relatively early and has become well-established in regions such as Australia, North America, Europe and Africa. Although aerial surveys have also been reported in other regions, their applications in those areas have not yet been systematically developed. The Northern Russia, encompassing near a quarter of the Earth's circumpolar landmass, constitutes a biogeographic linchpin for global waterbird ecology and movement dynamics. As a critical nexus for three transcontinental migratory flyways, the African-Eurasian, Central Asian, and East Asian-Australasian routes, this region underpins evolutionary adaptations across waterbird taxa to extreme thermal gradients and photoperiod variability, anchoring eight distinct waterbirds migration corridors. Despite its ecological importance, due to the vastness of the Northern Russia (spanning 8 million km²), coupled with extreme climatic gradients (−50°C winters to +30°C summers) and geopolitical barriers, the Northern Russia had long persisted as a data desert waterbird conservation prior to the present survey, with systemic monitoring gaps undermining global efforts to reverse population declines. This monitoring gap underscores the necessity of robust survey methods capable of operating at a vast spatial scale. Manned aerial surveys are particularly suited for this task, providing the operational capacity for systematic data collection across the Northern Russia. We present a dataset derived from aerial surveys of waterbirds conducted across the Eurasian Arctic, along with several adjacent regions and one wintering area (1,918,845 km²; 45.20°N-76.52°N, 35.49°E-180.00°E /180.00°W-172.05°W), over an 11-year period (2014-2024). The monitoring program utilized a purpose-built light hydroplane, and all bird documentation was performed manually by observers using a Canon Mark 4 camera equipped with a 100–400 mm lens and integrated GPS. Surveys covered 1,140,337 km of flight tracks across 2,057 waterbodies in 67 administrative districts. The dataset comprises 97,550 georeferenced occurrence records, representing 3,449,588 individuals, encompassing 43 species from 19 genera. Data adhere to GBIF Darwin Core standards and include metadata on sampling effort, methodology, and quality control, ensuring interoperability and reuse. This resource provides baseline information on waterbird distribution and abundance, supporting species distribution modelling, climate change impact assessments, and conservation planning for transcontinental wetlands of the Northern Eurasia. This work was supported by the China Biodiversity Observation Networks (Sino BON); and by a range of international and national funding bodies. International support was provided by the U.S. Fish and Wildlife Service, the head office of the “Foster a Goose Program” (Japan), African-Eurasian Migratory Waterbird Agreement small grant program, and LIFE (NAT/BG00847). Funding from the Russian Federation was primarily granted by the Russian Foundation for Basic Research (grant nos. #18-05-70117, #19-44-890003, Expert center “PORA”, the Department of Science and Innovations of the Yamalo-Nenetsky Autonomous Okrug, the Department of Natural Resources and Ecology and Agriculture of the Nenetsky Autonomous Okrug and others. Additional institutional support was received from the Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences; the Presidium of the Russian Academy of Sciences (Program No. 41); and the research plan of the Institute of Biological Problems of the North, Far East Branch, Russian Academy of Sciences. irregular Qingshan Zhao State Key Laboratory of Regional and Urban Ecology, Research Centre for Eco-Environmental sciences, Chinese Academy of Sciences

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qszhao@rcees.ac.cn The aerial surveys primarily employed light hydroplanes. Before 2016, models A-27 and Che-22 were used. Since 2016, the purpose-built STERCH S1 light hydroplane became the primary platform for waterbird monitoring, with the Che-22 also seeing supplemental use in the autumn of 2019. Key characteristics of these aircraft include a 180° field of view for observation, a short 200-250 m turning radius for manoeuvrability, the capability to land on water, and fuel efficiency that supports extended continuous missions of up to 8 hours, coupled with a low-acoustic signature to minimize disturbance to the waterbirds. Survey itineraries were strategically placed in areas with potential animal congregations or high-density aggregations, identified through topographic maps and satellite imagery. Flights were conducted at airspeeds of 80–120 km/h and an altitude of 15–100 m above ground level, with a GPS Garmin unit continuously logging the flight path. Data recording protocols were tailored to group size. For solitary individuals or small groups (n≤10), observers performed direct visual observation using Swarovski 10×42 binoculars and documented species identification, life stage (juvenile or adult) and counts in real-time. When encountering large flocks (n≥30) that were challenging to assess visually, the aircraft descended to a lower altitude of 15-30 m. This manoeuvre facilitated the acquisition of high-resolution, geotagged imagery using Canon 700D or Canon EOS 5D Mark IV cameras. For the Canon 700D, the camera's time was synchronized with a GPS navigator to georeferenced each photograph. The Canon EOS 5D Mark IV, equipped with a built-in GPS module, directly embedded location data. Each image was thus associated with geographic coordinates precise to 0.001 degrees and a timestamp precise to one second. Photographs of flocks, primarily captured with a 100-400 mm lens, enabled subsequent detailed analysis for species identification and population estimation. All observations were supplemented by continuous audio logs to minimize data gaps. The width of the survey strip was adjusted based on survey objectives and target species. For large flocks, a 2 km total strip width (1,000 m per side) was applied, representing the effective detection distance. For breeding pairs surveys, the strip width was set at 400 m (200 m per side) for ducks, while a wider strip of 800 m (400 m per side) was used for geese and swans. The use of survey’s routes according the biotope distribution of birds was crucial for maintaining consistent and accurate counts across the vast survey area. All species identification, age classification (juvenile or adult), and counting from imagery were performed manually by trained observers. To ensure consistent identification, a custom photographic guide for local Anseriformes was developed, based on the complete collection of geotagged images from the survey and following a structure adapted from North American protocols. For each identifiable individual or group within the imagery, observers recorded the species, life stage and count. For large aggregations (n > 100), multi-frame photographs of different sections were taken to ensure comprehensive coverage and facilitate accurate counting across the entire flock. Any birds that could not be definitively identified to species or age class were systematically excluded from the final population tallies to ensure analytical rigor. The surveys encompassed a vast geographical range from 45.20°N to 76.52°N in latitude, extending across both sides of the 180° meridian to include western (172.05°W to 180.00°W) and eastern (35.49°E to 180.00°E) longitudinal domains. Systematic aerial surveys of waterbird populations were conducted from 2014 to 2024 using purpose-built light hydroplane. Data collected prior to 2014 during the initial methodological development phase (including 2012) exhibited inconsistencies and incomplete timestamps due to early protocol limitations. Therefore, the dataset excludes these preliminary records and only includes surveys from 2014 onward, which feature detailed, corrected, and reliable data recording. All spatial data use the EPSG:5940 coordinate system, based on the WGS84 datum and optimized for accurate area and distance measurements in Arctic study region. To ensure consistency and accuracy in species identification, a standardized workflow was implemented post-survey. All aerial photographs were systematically compiled to create a project-specific reference. This reference served as the primary resource for manual species identification, enabling direct visual comparison and ensuring that all identifiers used the same set of diagnostic morphological criteria. This approach guaranteed that identifications were based on consistent traits such as head-to-bill ratios, bill coloration, and body proportions, which is crucial for reliably differentiating cryptic species pairs like Anser albifrons and A. erythropus. The integrity of the spatial and temporal data was secured through a multi-source validation process. The geographic coordinates and timestamps embedded in each photograph (via synchronized or built-in GPS) were cross-referenced with the continuous tracklog from the aircraft's primary GPS unit. This step identified and corrected any potential discrepancies. Furthermore, the continuous audio logs made by observers during the flight were transcribed and matched to the corresponding images and GPS positions using their synchronized timestamps, creating a robust chain of evidence from observation to final data record. During the image analysis phase, stringent measures were taken to prevent over-counting. Overlapping aerial photographs of the same flock were identified and the duplicates were excluded from analysis using Adobe Photoshop. All validated images were then analysed, with species identity, count, and life stage (juvenile or adult) systematically recorded in standardized spreadsheets. Any bird that could not be definitively identified to species or age class was excluded from the final tallies to maintain analytical rigor. Qingshan Zhao This work was supported by the China Biodiversity Observation Networks (Sino BON). 2025-12-07T16:36:27.752+08:00 dataset Cao J, Meng F, Kirtaev G, Solovyeva D, Danilova V, Rogova N, Melikhova E, Xu Z, Zhao Q, Rozenfeld S B (2026). A Sampling-event Dataset from Aerial Surveys of Northern Eurasian Waterbirds, 2014–2024. Version 1.4. Chinese Academy of Sciences (CAS). Samplingevent dataset. https://www.gbifchina.org.cn/resource?r=aerialsurvey_sonia&v=1.4 303e2244-4d11-4ab8-86c3-3c305be8cd0d/v1.4.xml