Extension of methods for jellyfish and ctenophore trophic ecology to large-scale research

By Jennifer E. Purcell. Hydrobiologia, 2008

197 citations recorded by the source corpus.

Science has rapidly expanded its frontiers with new technologies in the 20th Century. Oceanography now is studied routinely by satellite. Predictive models are on global scales. At the same time, blooms of jellyfish and ctenophores have become problematic, especially after 1980. Although we have learned a great deal about gelatinous zooplankton ecology in the 20th Century on local scales, we generally have not scaled-up to estimate the extent, the causes, or effects of large blooms. In this age of global science, research on gelatinous zooplankton needs to utilize large-scale approaches and predictive equations. Some current techniques enable jellyfish populations (aerial, towed cameras), feeding (metabolic rates, stable isotopes), and dynamics (predictive modeling) to be studied over large spatial and temporal scales. I use examples of scyphomedusae (Aurelia spp., Cyanea capillata, Chrysaoraquinquecirrha) and Mnemiopsis leidyi ctenophores, for which considerable data exist, to explore expanding from local to global scales of jellyfish trophic ecology. Regression analyses showed that feeding rates of Aurelia spp. (FR in copepods eaten medusa−1 d−1) generally could be estimated ±50% from in situ data on medusa wet weight (WW) and copepod density; temperature was not a significant factor. FR of C. capillata and C.quinquecirrha were similar to those of Aurelia spp.; the combined scyphomedusa regression underestimated measured FR of C.quinquecirrha and Aurelia spp. by 50% and 180%, respectively, and overestimated measured FR of C. capillata by 25%. Clearance rates (CR in liters cleared of copepods ctenophore−1 d−1) of M. leidyi were reduced in small containers (≤20 l), and a ratio of container-volume to ctenophore-volume of at least 2,500:1 is recommended for feeding experiments. Clearance rates were significantly related to ctenophore WW, but not to prey density or temperature, and estimated rates within 10–159%. Respiration rates of medusae and ctenophores were similar across habitats with greatly ambient different temperatures (10–30°C), and can be predicted from regressions using only mass. These regressions may permit estimation of feeding effects of gelatinous predators without exhaustive collection of feeding data in situ. I recommend that data on feeding and metabolism of jellyfish and ctenophores be entered in a database to allow generalized predictive relationships to be developed to promote inclusion of these important predators in ecosystem studies and models.

Subfields: Environmental Chemistry, Oceanography, Paleontology

View Paper: https://www.semanticscholar.org/paper/8c8c7420e2ade9ec89dffe25e95aab5922438785

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In Environmental Chemistry

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In Oceanography

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In Paleontology

1. Anthony J. Richardson
2. G. Hays
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4. Daniel Pauly
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Citations in the corpus

• The jellyfish joyride: causes, consequences and management responses to a more gelatinous future. (2009, background): “Enhanced jellyfish observations are now possible through recent advances in acoustic, aerial, automated underwater, diving, molecular and video methods [ 59 ].”
• Influence of jellyfish blooms on carbon, nitrogen and phosphorus cycling and plankton production (2008, background): “Mills, 1995; Arai, 1997; Purcell, 1997, 2008 ) and will not be examined further here.”
• The trophodynamics of marine top predators: Current knowledge, recent advances and challenges (2015, background): “The potential causes of these observed increases include overfishing and trophic cascades (Gershwin, 2013; Roux et al., 2013), eutrophication (Purcell, 2012), and climate change (Atkinson et al., 2004; Purcell, 2012).”
• Increasing jellyfish populations: trends in Large Marine Ecosystems (2012, background): “Furthermore, despite recent advances in research and understanding of jellyfish ecology at local scales, such knowledge is rarely used to evaluate possible causes or consequences of jellyfish blooms at larger scales, or to make predictions (Purcell, 2009).”