Abstract:1. Quantifying movement and demographic events of free-ranging animals is fundamental to studying their ecology, evolution and conservation. Technological advances have led to an explosion in sensor-based methods for remotely observing these phenomena. This transition to big data creates new challenges for data management, analysis and collaboration.2. We present the Movebank ecosystem of tools used by thousands of researchers to collect, manage, share, visualize, analyse and archive their animal tracking and … Show more
“…To investigate the influence of precipitation, sunshine duration and wind speed on activity and flight altitude, these meteorological factors were additionally included in the data analysis. Weather data were obtained by querying the Environmental Data Automated Track Annotation system (Env-DATA) (Dodge et al 2013) in Movebank (Kays et al 2021) for the respective data points, which provided data from the European Centre for Medium-range Weather Forecasts (European Centre for Medium-range Weather Forecast 2011). The weather parameters were average values over a model grid box of 0.75° and 3-h time steps.…”
The Red Kite has come to the forefront of general consciousness in recent decades. A major contributing factor has been repeated collisions of these raptors with wind turbines and the important role they play in the approval process for new turbines. Efforts to improve their protection sometime encounter challenges due to limited knowledge about some life history aspects, e.g., their flight altitude and flight activity. We investigated these parameters from 2012 to 2018 in an approximately 1000-km2 study area in the vicinity of Weimar (Federal State of Thuringia, Federal Republic of Germany) in 29 breeding birds (19 males and 10 females) equipped with GPS loggers. In addition to more than 11 million GPS data records, accelerometer data from the loggers were evaluated. The start of morning activities correlated with sunrise. Most frequently, Red Kites initiated their first hunting flights immediately at sunrise; males started hunting at 9 min and females started hunting at 12 min after sunrise (medians). The Red Kites mostly foraged and hunted their prey during flight. The proportion of time spent flying during their activity phase was highest during midday hours, reaching 30–80% in males depending on the phase of the breeding season. For males, the time spent flying was approximately two and a half times that for females. The birds sporadically reached flight altitudes of up to 1600 m above ground in the breeding area, while they maintained lower altitudes between 5 and 60 m more frequently and predominantly while foraging (56% of location fixes). Higher altitudes were occupied much less frequently than lower altitudes and were often used to travel relatively long distances in an energy-saving manner. The end of activity was well before sunset, at 87 min prior to sunset for males and 154 min prior to sunset (medians) for females.
“…To investigate the influence of precipitation, sunshine duration and wind speed on activity and flight altitude, these meteorological factors were additionally included in the data analysis. Weather data were obtained by querying the Environmental Data Automated Track Annotation system (Env-DATA) (Dodge et al 2013) in Movebank (Kays et al 2021) for the respective data points, which provided data from the European Centre for Medium-range Weather Forecasts (European Centre for Medium-range Weather Forecast 2011). The weather parameters were average values over a model grid box of 0.75° and 3-h time steps.…”
The Red Kite has come to the forefront of general consciousness in recent decades. A major contributing factor has been repeated collisions of these raptors with wind turbines and the important role they play in the approval process for new turbines. Efforts to improve their protection sometime encounter challenges due to limited knowledge about some life history aspects, e.g., their flight altitude and flight activity. We investigated these parameters from 2012 to 2018 in an approximately 1000-km2 study area in the vicinity of Weimar (Federal State of Thuringia, Federal Republic of Germany) in 29 breeding birds (19 males and 10 females) equipped with GPS loggers. In addition to more than 11 million GPS data records, accelerometer data from the loggers were evaluated. The start of morning activities correlated with sunrise. Most frequently, Red Kites initiated their first hunting flights immediately at sunrise; males started hunting at 9 min and females started hunting at 12 min after sunrise (medians). The Red Kites mostly foraged and hunted their prey during flight. The proportion of time spent flying during their activity phase was highest during midday hours, reaching 30–80% in males depending on the phase of the breeding season. For males, the time spent flying was approximately two and a half times that for females. The birds sporadically reached flight altitudes of up to 1600 m above ground in the breeding area, while they maintained lower altitudes between 5 and 60 m more frequently and predominantly while foraging (56% of location fixes). Higher altitudes were occupied much less frequently than lower altitudes and were often used to travel relatively long distances in an energy-saving manner. The end of activity was well before sunset, at 87 min prior to sunset for males and 154 min prior to sunset (medians) for females.
“…1 (4)). As MoveApps has been set up as a partner platform to the Movebank data base within the Movebank Ecosystem [ 41 ], it is most convenient to directly import animal movement data stored in Movebank using the "Movebank" App. This core App allows users to log into Movebank to browse and securely transfer data based on their user access permissions within the Movebank data base, which accommodates both public and controlled-access data, provides support to harmonize data to a shared format and vocabulary, and supports live data feeds [ 41 ].…”
Background
Bio-logging and animal tracking datasets continuously grow in volume and complexity, documenting animal behaviour and ecology in unprecedented extent and detail, but greatly increasing the challenge of extracting knowledge from the data obtained. A large variety of analysis methods are being developed, many of which in effect are inaccessible to potential users, because they remain unpublished, depend on proprietary software or require significant coding skills.
Results
We developed MoveApps, an open analysis platform for animal tracking data, to make sophisticated analytical tools accessible to a global community of movement ecologists and wildlife managers. As part of the Movebank ecosystem, MoveApps allows users to design and share workflows composed of analysis modules (Apps) that access and analyse tracking data. Users browse Apps, build workflows, customise parameters, execute analyses and access results through an intuitive web-based interface.
Apps, coded in R or other programming languages, have been developed by the MoveApps team and can be contributed by anyone developing analysis code. They become available to all user of the platform. To allow long-term and cross-system reproducibility, Apps have public source code and are compiled and run in Docker containers that form the basis of a serverless cloud computing system. To support reproducible science and help contributors document and benefit from their efforts, workflows of Apps can be shared, published and archived with DOIs in the Movebank Data Repository.
The platform was beta launched in spring 2021 and currently contains 49 Apps that are used by 316 registered users. We illustrate its use through two workflows that (1) provide a daily report on active tag deployments and (2) segment and map migratory movements.
Conclusions
The MoveApps platform is meant to empower the community to supply, exchange and use analysis code in an intuitive environment that allows fast and traceable results and feedback. By bringing together analytical experts developing movement analysis methods and code with those in need of tools to explore, answer questions and inform decisions based on data they collect, we intend to increase the pace of knowledge generation and integration to match the huge growth rate in bio-logging data acquisition.
“…1.9). This is a free and well-established repository in the movement ecology community (Schneider et al 2021; Kays et al 2022) that provides persistent identifiers for future access and is accepted by scientific journals. The repository is developed in accordance with the FAIR (Wilkinson et al 2016) and TRUST (Lin et al 2020) data principles.…”
Section: Resultsmentioning
confidence: 99%
“…1.4). As MoveApps has been set up as a partner platform to the Movebank data base within the Movebank Ecosystem (Kays et al 2022), it is most convenient to directly import animal movement data stored in Movebank using the "Movebank" App. This core App allows users to log into Movebank to browse and securely transfer data based on their user access permissions within the Movebank data base, which accommodates both public and controlled-access data , provides support to harmonize data to a shared format and vocabulary, and supports live data feeds (Kays et al 2022).…”
Section: Workflow Compilation Use and Schedulingmentioning
confidence: 99%
“…As MoveApps has been set up as a partner platform to the Movebank data base within the Movebank Ecosystem (Kays et al 2022), it is most convenient to directly import animal movement data stored in Movebank using the "Movebank" App. This core App allows users to log into Movebank to browse and securely transfer data based on their user access permissions within the Movebank data base, which accommodates both public and controlled-access data , provides support to harmonize data to a shared format and vocabulary, and supports live data feeds (Kays et al 2022). Relying on Movebank for input of data to MoveApps thus provides a secure method to share data between collaborators, allows users without access to data storage or a fast internet connection to input large data volumes, reduces problems in analysis caused by inconsistent or unknown data formats, and supports automated reporting procedures during data collection (see example workflows below).…”
Section: Workflow Compilation Use and Schedulingmentioning
Background: Bio-logging and animal tracking datasets continuously grow in volume and complexity, documenting animal behaviour and ecology in unprecedented extent and detail, but greatly increasing the challenge of extracting knowledge from the data obtained. A large variety of analysis methods are being developed, many of which in effect are inaccessible to potential users, because they remain unpublished, depend on proprietary software or require significant coding skills. Results: We developed MoveApps, an open analysis platform for animal tracking data, to make sophisticated analytical tools accessible to a global community of movement ecologists and wildlife managers. As part of the Movebank ecosystem, MoveApps allows users to design and share workflows composed of analysis modules (Apps) that access and analyse tracking data. Users browse Apps, build workflows, customise parameters, execute analyses and access results through an intuitive web-based interface. Apps, coded in R or other programming languages, have been developed by the MoveApps team and can be contributed by anyone developing analysis code. They become available to all user of the platform. To allow long-term and cross-system reproducibility, Apps have public source code and are compiled and run in Docker containers that form the basis of a serverless cloud computing system. To support reproducible science and help contributors document and benefit from their efforts, workflows of Apps can be shared, published and archived with DOIs in the Movebank Data Repository. The platform was beta launched in spring 2021 and currently contains 44 Apps that are used by 156 registered users. We illustrate its use through two workflows that (1) provide a daily report on active tag deployments and (2) segment and map migratory movements. Conclusions: The MoveApps platform is meant to empower the community to supply, exchange and use analysis code in an intuitive environment that allows fast and traceable results and feedback. By bringing together analytical experts developing movement analysis methods and code with those in need of tools to explore, answer questions and inform decisions based on data they collect, we intend to increase the pace of knowledge generation and integration to match the huge growth rate in bio-logging data acquisition.
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