Collaborative proposal: ABI Sustaining: The Environmental-Data Automated Track Annotation (Env-DATA) system

  • Bohrer, Gil (Investigador principal)

Detalles del proyecto

Descripción

How an animal moves through their environment reveals much about their ecology and how they respond to modern changes to the planet such as development and climate change. GPS technology embedded in collars (mammal) or backpacks (birds) has revolutionized the ability to track animals, providing more detail than ever before, sometimes in real-time. However, to make the most of these new tracking data they must be seen in the context of the world through which the animals are moving by linking their tracks to remote sensing maps showing weather and ecosystem. With both the animal and environmental data growing rapidly, there are increasing technical challenges and knowledge gaps that inhibit the widespread application of linking these types of datasets for movement ecology research. The Environmental-Data Automated Track Annotation system (Env-DATA) is a web-based tool to give direct access for movement ecology researchers to thousands of environmental datasets. It provides intuitive and easy to use graphic user interface-based access to these datasets. Env-DATA is hosted by and interfaces with Movebank, a global movement data archive, open to the broad public worldwide. Env-DATA is open and accessible to anyone. It provides easy access to already public datasets, as well and some datasets that are not otherwise open. Env-DATA provides users with tools to publish the combined environmental data along with the animal track it was used to annotate in the Movebank Data Depository. Published data sets are allocated a DOI and can be accessed and searched as electronic publications, provided an agreement from the owner of the track data. Annual workshops at the North Carolina Museum of Natural Sciences will reach out to new users within academia, government, and public organizations that track animals.

Env-DATA is at the cutting edge of the 'contextual revolution' in movement ecology where combining analysis of movement patterns and incorporating the environmental background of the movement has become a necessary component for understanding and modeling animal movement. By providing intuitive and easy to use access to an unprecedented number of environmental datasets and variables, Env-DATA enables animal movement researchers to overcome technical challenges and knowledge gaps, and to fully utilize globally available environmental information. Env-DATA links movement tracks with environmental data from different remote-sensing and global reanalysis data providers, including NASA, NOAA, and ECMWF. Env-DATA interprets environmental variables in the correct encryption, grid, and projection systems and interpolates the data in space and time to the observed animal track locations, or a collection of comparison points or grid. Funding through this proposal will allow support of continuous on-going operations of Env-DATA, which requires regular quality control tests to detect cases where the data providers to Env-DATA may have changed the metadata, location, or access protocol. In these cases, technical support to update the system is necessary. It also requires regular availability of a user-support 'help-desk'. Outreach and training of new and existing users, as well as collecting first-hand feedback from users will be conducted by annual user workshops. All talks and tutorials in the workshop will be filmed and posted to the workshop website and on YouTube. Env-DATA PIs, staff, and researchers using Env-DATA will provide lectures to the broad public in the NC Museum. Undergraduate students will assist in workshop coordination and Env-DATA user support. To access Env-DATA and Movebank, visit https://www.movebank.org/.

EstadoFinalizado
Fecha de inicio/Fecha fin15/7/1631/12/20

Financiación

  • National Science Foundation: USD337,474.00

!!!ASJC Scopus Subject Areas

  • Ecología
  • Bioquímica, genética y biología molecular (todo)

Huella digital

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