Bringing Ecologists and Statisticians Together for the Conservation of Endangered Species

Post provided by Cecilia Pinto and Luigi Spezia

The Benefits of High Frequency Data

One of the tagged flapper skates showing the three different kinds of tags. ©Cecilia Pinto

One of the tagged flapper skates showing the three different kinds of tags. ©Cecilia Pinto

High frequency data, like those obtained from individual electronic tags, carries the potential of giving us detailed information on the behaviour of species at the individual level. Such data are particularly useful for marine species, as we can’t observe them directly for long periods of time.

Understanding how individuals use water columns – both at daily and seasonal scales – can help define conservation measures such as restricting fishing activity to reduce by-catch or defining protected areas to help recovering populations or protect spawning and nursery areas. High frequency data have become popular as they give insight to detailed individual foraging behaviour and therefore the specific energetic needs that are linked to reproduction and fitness. Continue reading

Issue 7.4

Issue 7.4 is now online!

The April issue of Methods is now online!

This month’s issue contains two Applications articles and one Open Access article, all of which are freely available.

CPW Photo Warehouse: freely available software that has been customized to identify, archive, and transform photographs into data formats required for statistical analyses. Users navigate a series of point-and-click menu items that allow them to input information from camera deployments, import photos and store data. Images are seamlessly incorporated into the database windows, but are stored separately.

SIMR: An R package that allows users to calculate power for generalized linear mixed models from the lme4 package. The power calculations are based on Monte Carlo simulations. It includes tools for (i) running a power analysis for a given model and design; and (ii) calculating power curves to assess trade-offs between power and sample size.

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