The environmental-data automated track annotation (Env-DATA) system: linking animal tracks with environmental data

By Somayeh Dodge, Gil Bohrer, Rolf P. Weinzierl, S. Davidson, R. Kays, David C. Douglas, Sebastian Cruz, Jiawei Han, D. Brandes, Martin Wikelski. Movement Ecology, 2013

340 citations recorded by the source corpus.

The movement of animals is strongly influenced by external factors in their surrounding environment such as weather, habitat types, and human land use. With advances in positioning and sensor technologies, it is now possible to capture animal locations at high spatial and temporal granularities. Likewise, scientists have an increasing access to large volumes of environmental data. Environmental data are heterogeneous in source and format, and are usually obtained at different spatiotemporal scales than movement data. Indeed, there remain scientific and technical challenges in developing linkages between the growing collections of animal movement data and the large repositories of heterogeneous remote sensing observations, as well as in the developments of new statistical and computational methods for the analysis of movement in its environmental context. These challenges include retrieval, indexing, efficient storage, data integration, and analytical techniques. This paper contributes to movement ecology research by presenting a new publicly available system, Environmental-Data Automated Track Annotation (Env-DATA), that automates annotation of movement trajectories with ambient atmospheric observations and underlying landscape information. Env-DATA provides a free and easy-to-use platform that eliminates technical difficulties of the annotation processes and relieves end users of a ton of tedious and time-consuming tasks associated with annotation, including data acquisition, data transformation and integration, resampling, and interpolation. The system is illustrated with a case study of Galapagos Albatross (Phoebastria irrorata) tracks and their relationship to wind, ocean productivity and chlorophyll concentration. Our case study illustrates why adult albatrosses make long-range trips to preferred, productive areas and how wind assistance facilitates their return flights while their outbound flights are hampered by head winds. The new Env-DATA system enhances Movebank, an open portal of animal tracking data, by automating access to environmental variables from global remote sensing, weather, and ecosystem products from open web resources. The system provides several interpolation methods from the native grid resolution and structure to a global regular grid linked with the movement tracks in space and time. The aim is to facilitate new understanding and predictive capabilities of spatiotemporal patterns of animal movement in response to dynamic and changing environments from local to global scales.

Subfields: Ecological Modeling, Ecology

View Paper: https://www.semanticscholar.org/paper/27ca6b828835ab8ce6620acbb0079627ff9e7951

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Citations in the corpus

Terrestrial animal tracking as an eye on life and planet (2015, methodology): “Many of the components for this program are already in use for individual projects, including live data streams, community data standards and sharing frameworks, and tools for environmental data integration (14, 23, 78).”
Towards a new understanding of migration timing: slower spring than autumn migration in geese reflects different decision rules for stopover use and departure (2016, methodology): “Wind conditions were obtained 1) for each of the ten line crossings and 2) for each stopover site by track annotation (Dodge et al. 2013; Env-DATA tool by Movebank) using surface-level winds (10 m above the ground) at a resolution of 6 h and 0.75 (ECMWF ERA-interim weather model).”
High juvenile mortality during migration in a declining population of a long-distance migratory raptor (2015, methodology): “To assess what habitats Egyptian Vultures select at the continental scale, we downloaded environmental data for all winter locations of tracked Egyptian Vultures using the track annotation system in Movebank (Dodge et al. 2013).”
Moving in the Anthropocene: Global reductions in terrestrial mammalian movements (2018, methodology): “NDVI data was extracted from MODIS Land Terra Vegetation Indices 500-m 16-day resolution (MOD13A1 V005 (9)) using the Movebank Env-DATA system (10) (environmental-data automated track annotation; http://www.”