How Big Data Fast Tracked Human Mobility Research and the Lessons for Animal Movement Ecology

Thums, Michele; Fernández-Gracia, Juan; Sequeira, Ana M. M.; Eguı́luz, Vı́ctor M.; Duarte, Carlos M.; Meekan, Mark G.

doi:10.3389/fmars.2018.00021

Cited by 48 publications

(58 citation statements)

References 109 publications

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“…Recent advances made in the field of telemetry and bio‐logging have led to an exponential increase in satellite telemetry studies (Thums et al. ), with very large sample size (≫1,000 tracks) recently starting to appear in the literature (Block et al. , Brodie et al.…”

Section: Resultsmentioning

confidence: 99%

Section: Moving Toward Big Data Analysis (Very Large Sample Sizes; ≫100)mentioning

confidence: 99%

“…In the last decade, many tens of thousands of tags have been deployed on animals and, if shared, the resulting data sets will allow for powerful analysis at large spatiotemporal scales (Thums et al 2018a). Such data sets can assist in answering topical questions (Hays et al 2016), refine conservation benefits (Allen and Singh 2016), and facilitate the use of big data approaches to enhance our understanding of animal movements (Meekan et al 2017, Rodriguez et al 2017.…”

Section: Moving Toward Big Data Analysis (Very Large Sample Sizes; ≫100)mentioning

confidence: 99%

“…Recent advances made in the field of telemetry and bio-logging have led to an exponential increase in satellite telemetry studies (Thums et al 2018a), with very large sample size (≫1,000 tracks) recently starting to appear in the literature (Block et al 2011, Brodie et al 2018, Sequeira et al 2018. In spite of that, a sample size of one with sufficient track length can still lead to scientific insights.…”

Section: )mentioning

confidence: 99%

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The importance of sample size in marine megafauna tagging studies

Sequeira

Heupel

Lea

et al. 2019

Ecological Applications

103

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Telemetry is a key, widely used tool to understand marine megafauna distribution, habitat use, behavior, and physiology; however, a critical question remains: “How many animals should be tracked to acquire meaningful data sets?” This question has wide‐ranging implications including considerations of statistical power, animal ethics, logistics, and cost. While power analyses can inform sample sizes needed for statistical significance, they require some initial data inputs that are often unavailable. To inform the planning of telemetry and biologging studies of marine megafauna where few or no data are available or where resources are limited, we reviewed the types of information that have been obtained in previously published studies using different sample sizes. We considered sample sizes from one to >100 individuals and synthesized empirical findings, detailing the information that can be gathered with increasing sample sizes. We complement this review with simulations, using real data, to show the impact of sample size when trying to address various research questions in movement ecology of marine megafauna. We also highlight the value of collaborative, synthetic studies to enhance sample sizes and broaden the range, scale, and scope of questions that can be answered.

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Section: Resultsmentioning

confidence: 99%

Section: Moving Toward Big Data Analysis (Very Large Sample Sizes; ≫100)mentioning

confidence: 99%

Section: Moving Toward Big Data Analysis (Very Large Sample Sizes; ≫100)mentioning

confidence: 99%

Section: )mentioning

confidence: 99%

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The importance of sample size in marine megafauna tagging studies

Sequeira

Heupel

Lea

et al. 2019

Ecological Applications

103

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“…Indeed, tags tend to miniaturize, and geolocalization technology, as well as network coverage, is getting improved and cheaper. Today, electronic tags are widely used to study species' movements and migration, resulting in an enormous amount of data (Li et al 2015, Thums et al 2018. Currently, platforms like Movebank enable data storage, visualization and management.…”

Section: Introductionmentioning

confidence: 99%

A Machine Learning Tool to Transform Raw Movement Data into Cleaned, Annotated, and Usable Information

Jambon¹,

Albertini²,

Berton³

et al. 2019

BISS

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The term bio-logging is given to ‘the use of miniaturized animal-attached tags for logging and/or relaying data about an animal’s movements, behaviour, physiology, and/or environment’ (Rutz and Hays 2009). It has been spreading over the scientific world through the last ten years and will become even more popular in the next decade thanks to engineering progresses. Indeed, tags tend to miniaturize, and geolocalization technology, as well as network coverage, is getting improved and cheaper. Today, electronic tags are widely used to study species’ movements and migration, resulting in an enormous amount of data ( Li et al. 2015 , Thums et al. 2018). Currently, platforms like Movebank enable data storage, visualization and management. However, no easy-to-use tool is currently available for conducting a various array of pre-treatment procedures on those data, such as outliers identification, elevation or time management. In that context, we are developing an open source platform based on algorithms and machine learning to automatically return cleaned and annotated data.

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Bryde's whales in the North‐East Atlantic: New insights on site fidelity and connectivity between oceanic archipelagos

Ferreira

Dinis

Badenas

et al. 2021

Aquatic Conservation

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The conservation of marine megafauna presents numerous difficulties owing to their high mobility over difficult‐to‐access oceanic areas that impairs the collection of basic, but essential, biological information. The Bryde's whale (Balaenoptera edeni) is one of the most elusive species of baleen whales, and although it is known to be a seasonal visitor to several archipelagos in Macaronesia (the Azores, Madeira, and Canaries), there are no studies regarding its occurrence or geographical connectivity in this area of the Atlantic. A 14‐year photographic database was used to determine short‐term (intra‐seasonal) and long‐term (inter‐annual) Bryde's whale site fidelity and to estimate individual residency times in Madeira, whereas photographic catalogues from Madeira and the Canaries were compared in order to assess large‐scale movements (i.e. on the scale of hundreds of kilometres). In Madeira, 59 individuals were identified, 27 (45.8%) of which were recaptured. Of these, 10 individuals (37.0%) presented short‐term site fidelity and 17 individuals (63.0%) presented long‐term site fidelity, with a maximum recapture interval of 12 years. Lagged identification rates showed that five individuals (SE = 2) remained in the area for 32 days (SE = 108 days) before leaving and not returning during the same year. Seven individuals were seen both in Madeira and the Canaries (catalogue comprising 51 individuals), three of which were identified multiple times in both archipelagos, with a minimum of 43 days between consecutive sightings. This information combined with the fact that this species is commonly sighted accompanied by calves and feeding in both archipelagos highlights the ecological importance of this area for Bryde's whales. This should be taken into consideration by policymakers when implementing conservation measures, where coordination of effort among countries is needed. This study also reinforces the value of using data from platforms of opportunity and of making photographic data open access.

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How Big Data Fast Tracked Human Mobility Research and the Lessons for Animal Movement Ecology

Cited by 48 publications

References 109 publications

The importance of sample size in marine megafauna tagging studies

The importance of sample size in marine megafauna tagging studies

A Machine Learning Tool to Transform Raw Movement Data into Cleaned, Annotated, and Usable Information

Bryde's whales in the North‐East Atlantic: New insights on site fidelity and connectivity between oceanic archipelagos

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