Abstract
AbstractZooplankton exhibit diverse swimming behaviors to reposition themselves in the water column, feed, find mates, and avoid predation. Environmental stressors that modify behavior can have cascading effects on population distributions and predator–prey interactions. Understanding zooplankton population dynamics is challenging, largely because traditional methods for quantifying zooplankton distributions are costly, limited in scope, and require extended analysis by trained analysts. We developed a novel methodology that combined remotely deployed camera systems, machine learning‐based identification of zooplankton, and video‐based tracking technology to quantify copepod and amphipod in situ swimming behavior in Hood Canal, WA, USA, a seasonally hypoxic and acidified fjord. Behavioral analysis showed copepods of all sizes swam on average 24% slower in stressful (hypoxic and acidified) waters relative to non‐stressful waters. Copepods exhibited less frequent escape responses in stressful waters, with a 68% decrease in the amount of time spent “jumping” for copepods 1–2 mm in length. Interestingly, abundances of small copepods increased in stressful waters, with 56% more 1–2 mm long copepods in stressful vs. non‐stressful conditions. In contrast, amphipods' average “darting” speeds did not differ between environmental conditions, but the abundance of amphipods significantly decreased in stressful waters relative to non‐stressful waters, suggesting avoidance of stressful conditions. Changes in swimming behavior are informative metrics in understanding ecosystem impacts of environmental stress because swimming speed has individual, population, and community‐level implications. Our results suggest that, among copepods, in situ behaviors may be useful proxies in monitoring the impacts of climate change on coastal ecosystems.
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