Data from: Changing measurements or changing movements? Sampling scale and movement model identifiability across generations of biologging technology

• Main Authors: Johnson, Leah R., Boersch-Supan, Philipp H., Phillips, Richard A., Ryan, Sadie J.
• Format: Dataset
• Language: unknown
• Published: 2018
• Subjects: biologger; Diomedea exulans; Thalassarche melanophris; Antarctic albatrosses; statistics; Antarctic; Antarc*
• Online Access: https://zenodo.org/record/4960229; https://doi.org/10.5061/dryad.t1r3v

1. Animal movement patterns contribute to our understanding of variation in breeding success and survival of individuals, and the implications for population dynamics. 2. Over time, sensor technology for measuring movement patterns has improved. Although older technologies may be rendered obsolete, the existing data are still valuable, especially if new and old data can be compared to test whether a behavior has changed over time. 3. We used simulated data to assess the ability to quantify and correctly identify patterns of seabird flight lengths under observational regimes used in successive generations of wet/dry logging technology. 4. Care must be taken when comparing data collected at differing time-scales, even when using inference procedures that incorporate the observational process, as model selection and parameter estimation may be biased. In practice, comparisons may only be valid when degrading all data to match the lowest resolution in a set. 5. Changes in tracking technology, such as the wet/dry loggers explored here, that lead to aggregation of measurements at different temporal scales make comparisons challenging. We therefore urge ecologists to use synthetic data to assess whether accurate parameter estimation is possible for models comparing disparate data sets before planning experiments and conducting analyses such as responses to environmental changes or the assessment of management actions. dry segment data from flights of Antarctic albatrossesSee README file for data informationalbatross_drysegments.csvImplementation of the negative log likelihood - 1992 style loggersThis file implements the negative log-likelihood corresponding to the 1992-style immersion loggers. The file includes examples of fitting parameters of this distribution to flight data. requires "shifted_dists.R"mle_1992.RImplementation of the negative log likelihood - 2004 style loggersThis file implements the negative log-likelihood corresponding to the 2004-style immersion loggers. The file includes examples of fitting ...