Estimating chlorophyll profiles from electronic tags deployed on pelagic animals

  • Teo S
  • Kudela R
  • Rais A
  • et al.
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Abstract

Electronic tags deployed on pelagic animals in the ocean are revolutionizing our understanding of how pelagic species interact with the physical environment, by making simultaneous eco-physiological and in situ oceanographic measurements at relatively low cost. Pelagic animals with electronic tags are also increasingly being used as ocean sensing platforms. Here, we demonstrate the concept of estimating in situ chlorophyll concentration profiles from light level and depth data collected by electronic tags, using a bio-optical model. We assessed this concept by deploying electronic tags at 14 oceanographic stations in the Pacific Ocean, together with a fluorometer and Niskin bottles. In the euphotic zone, tag-estimated chlorophyll concentrations correlated significantly with simultaneous chlorophyll concentration measurements from filtered water samples (R-2 = 0.41, p < 0.0001) and a profiling fluorometer (R-2 = 0.29, p < 0.0001). Below the euphotic zone, peaks in the light attenuation profile corresponded to deep scattering layers, with a 17 m rms difference between the deep scattering layer depths estimated by the tags and an Acoustic Doppler Current Profiler. In situ chlorophyll profiles were also derived from electronic tags deployed on Pacific bluefin tuna in Baja California waters, and found to be comparable to chlorophyll profiles in the World Ocean Database for the region and season. Although more research is needed to improve this approach, the results from both shipboard and Pacific bluefin tuna experiments indicate that light level attenuation profiles derived from electronic tags can be successfully used to estimate chlorophyll concentration profiles.

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APA

Teo, S., Kudela, R., Rais, A., Perle, C., Costa, D., & Block, B. (2009). Estimating chlorophyll profiles from electronic tags deployed on pelagic animals. Aquatic Biology, 5, 195–207. https://doi.org/10.3354/ab00152

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