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Data for: Modeling short-term energetic costs of sonar disturbance to cetaceans using high resolution foraging data

Citation

Czapanskiy, Max et al. (2021), Data for: Modeling short-term energetic costs of sonar disturbance to cetaceans using high resolution foraging data, Dryad, Dataset, https://doi.org/10.5061/dryad.pvmcvdnkq

Abstract

  1. Anthropogenic noise is a pervasive and increasing source of disturbance to wildlife. Marine mammals exhibit behavioral and physiological responses to naval sonar and other sound sources. The lost foraging opportunities and elevated locomotor effort associated with sonar disturbance likely carry energetic costs, which may lead to population-level consequences.
  2. We modeled the energetic costs associated with behavioral responses using (1) empirical datasets of cetacean feeding rates and prey characteristics and (2) allometry of swimming performance and metabolic rates.
  3. We applied our model to compare the short-term (i.e., the scale of the disturbance response; hours to days) energetic costs of a variety of observed behavioral responses. Efficient foragers (e.g., baleen whales) incur a greater relative energetic cost for mild behavioral responses as compared to the most extreme observed response for larger odontocetes (e.g., beaked whales). Energetic costs are more sensitive to lost feeding opportunities than increased energy expenditure from elevated locomotor effort.
  4. In order to scale up from short-term costs to long-term effects (months to years), future research should address individuals’ capacity to compensate for energetic losses as well as energetic thresholds for demographic rates (survival, fecundity). We discuss how relative energetic costs correlate with species’ pace of life and the implications for conservation planning.
  5. Synthesis and applications. Current approaches towards understanding the Population Consequences of Disturbance (PCoD) often must rely on expert opinion due to data deficiency. Our model provides an empirical method for linking behavior to energetics, which is critical for managers to make informed decisions on actions that may affect marine mammal species. Furthermore, our model is applicable to other forms of disturbance, such as vessel traffic or seismic exploration, and our scaling approach enables risk projections for understudied species.

Methods

This dataset contains three types of data.

Prey: the log mean and log standard deviation of energy acquired per feeding event (kJ). For single prey item foragers (toothed whales; odontoceti), this is the mean and standard deviation of the logged energy content of prey (kJ), weighted by diet proportion. For bulk filter feeders (rorqual whales; Balaenopteridae), this is the mean and standard deviation of the logged biomass density (kg m-3) of krill swarms in the vicinity of feeding whales, multiplied by predator engulfment capacity (m3) and prey energy density (kJ kg-1).

Feeding: the number of feeding events in an hour by tagged cetaceans. Each row corresponds to one hour of a tag deployment.

Morphology: the representative length (m) and mass (kg) of cetacean species used in the analysis.

Usage Notes

This dataset was formatted to work with the Supplemental Information for "Modeling short-term energetic costs of sonar disturbance to cetaceans using high resolution foraging data". The Supplemental Information is available as an R Markdown file archived at Zenodo (https://doi.org/10.5281/zenodo.4646110).