Sensor:
Accessory Measurements

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Name
Accessory Measurements
External ID
accessory-measurements
Is Location Sensor

Search Results

Now showing 1 - 4 of 4
  • Data package
    Data from: Tracking the migration of red-necked stint (Calidris ruficollis) reveals marathon flights and unexpected conservation challenges
    (2020-10-09) Mu, Tong; Tomkovich, Pavel S.; Loktionov, Egor Y.; Syroechkovskiy, Evgeny E.; Wilcove, David S.
    Effective conservation of migratory species depends on understanding both migratory connectivity and migration strategy. The Red‐necked Stint Calidris ruficollis is a small, highly migratory sandpiper of the East Asian‐Australasian Flyway, which is classified as Near Threatened due to ongoing population declines. We tracked the migration of three Red‐necked Stints breeding in southern Chukotka, Russia, using geolocators, and supplemented our tracking data with re‐sighting records of color‐flagged individuals. The three birds, all of which bred within 2km of each other, wintered in three different localities spanning nearly 5,000km. One individual completed its northward migration of >9400 km in two marathon flights; the second leg of that journey was completed in a nonstop flight of 5,350 km. The successful conservation of just this one population requires protection of wintering sites across a vast area, coupled with key staging sites along the flyway. We suggest that other migratory species may pose similar conservation challenges.
  • Data package
    Data from: Migration strategies of the Baltic Dunlin: rapid jump migration in the autumn but slower skipping type spring migration
    (2017-12-31) Pakanen, Veli-Matti; Jaakkonen, Tuomo; Saarinen, Joni; Rönkä, Nelli; Thomson, Robert L.; Koivula, Kari
    Migration during spring is usually faster than during autumn because of competition for breeding territories. In some cases, however, the costs and benefits associated with the environment can lead to slower spring migration, but examples are quite rare. We compared seasonal migration strategies of the endangered Baltic population of the dunlin (Calidris alpina schinzii) using light-level geolocator data from 26 individuals breeding in Finland. Autumn migration was faster, with individuals showing a “jump” and “skipping” migration strategy characterised by fewer stationary periods, shorter total stopping time and faster flight. Spring migration was slower, with individuals using a “skipping” strategy. The duration of migration was longer for early departing birds during spring but not during autumn suggesting that early spring migrants are prevented from arriving to the breeding areas or that fueling conditions are worse on the stopover sites for early arriving individuals. Dunlins showed high migratory connectivity. All individuals had one long staging at the Wadden Sea in the autumn after which half of the individuals flew 4500 km non-stop to Banc d'Arguin, Mauritania. The other half stopped briefly on the Atlantic coast on their way to Mauritania. One bird wintered on the coast of Portugal. Nine individuals that carried geolocators for two years were site faithful to their final non-breeding sites. Based on the strategies during the non-breeding period we identified, Baltic dunlin may be especially vulnerable to rapid environmental changes at the staging and non-breeding areas. Consequently, the preservation of the identified non-breeding areas is important for their conservation.
  • Data package
    Data from: Satellite tracking a wide‐ranging endangered vulture species to target conservation actions in the Middle East and East Africa
    (2019-12-02) Buechley, Evan R.; Şekercioğlu, Çağan H.
    Vultures comprise the most endangered avian foraging guild (obligate scavengers) and their loss from ecosystems can trigger trophic cascades, mesopredator release, and human rabies epidemics, indicating their keystone species status. Vultures’ extremely large home ranges, which often cross international borders of countries that have differing laws and capacity for wildlife conservation, makes conserving them challenging. However, satellite-tracking data can be used to identify habitat preferences and critical sites to target conservation actions. We tracked 16 Egyptian Vultures, Neophron percnopterus, in the Middle East and East Africa. We used dynamic Brownian bridge movement models to calculate home ranges and core-use areas, and we analyzed habitat use in a resource selection framework. Combined summer and winter ranges (99% utilization distributions) of all birds covered 209,800 and 274,300 km2, respectively. However, the core-use areas (50% utilization distributions) in the summer and winter ranges, accounted for only 0.4–1.1% of this area (900 and 3100 km2, respectively). These core-use areas are where the home ranges of multiple individuals overlapped and/or where individuals spent a lot of time, such as feeding and roosting sites, and are places where conservation actions could focus. Resource selection models predicted Egyptian Vulture occurrence throughout little-studied parts of the species’ range in the Middle East and East Africa, and revealed strong selection for proximity to highways, power distribution lines, and towns. While providing roosts (e.g. power pylons) and food (e.g. garbage dumps), anthropogenic features may also function as ecological traps by increasing exposure to electrocution and dietary toxins.
  • Data package
    Data from: Study "NC Wood Stork Tracking"
    (2023-12-23) Schweitzer, Sara; Bryan, A. Lawrence, Jr.; Brzorad, John; Kays, Roland
    We tracked two wood storks (Mycteria americana) from a breeding site in North Carolina, documenting their migrations to southern Florida. This is one of the northernmost breeding grounds for the species. Dice was tracked with a GPS/GSM/ACC tag from e-obs GmbH, and Mr Lay was tracked with a GSM-GPS tag from Microwave Telemetry Inc. Duplicates and location outliers were flagged in Movebank by manually flagging visible outliers and then using filters. First, the duplicate filter was used to flag multiple records records with matching tag ID and timestamp, with a preference to retain "eobs:status" values in the following order: A, B, C, D, blank. Second, the speed filter was run using maximum plausible speed of 50 m/s and maximum location error 100 m, using the "longest consistent track" method.