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Ecol Evol
2019 Dec 01;924:13740-13751. doi: 10.1002/ece3.5784.
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Evaluating the effects of large marine predators on mobile prey behavior across subtropical reef ecosystems.
Phenix LM
,
Tricarico D
,
Quintero E
,
Bond ME
,
Brandl SJ
,
Gallagher AJ
.
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The indirect effect of predators on prey behavior, recruitment, and spatial relationships continues to attract considerable attention. However, top predators like sharks or large, mobile teleosts, which can have substantial top-down effects in ecosystems, are often difficult to study due to their large size and mobility. This has created a knowledge gap in understanding how they affect their prey through nonconsumptive effects. Here, we investigated how different functional groups of predators affected potential prey fish populations across various habitats within Biscayne Bay, FL. Using baited remote underwater videos (BRUVs), we quantified predator abundance and activity as a rough proxy for predation risk and analyzed key prey behaviors across coral reef, sea fan, seagrass, and sandy habitats. Both predator abundance and prey arrival times to the bait were strongly influenced by habitat type, with open homogenous habitats receiving faster arrival times by prey. Other prey behaviors, such as residency and risk-associated behaviors, were potentially driven by predator interaction. Our data suggest that small predators across functional groups do not have large controlling effects on prey behavior or stress responses over short temporal scales; however, habitats where predators are more unpredictable in their occurrence (i.e., open areas) may trigger risk-associated behaviors such as avoidance and vigilance. Our data shed new light on the importance of habitat and context for understanding how marine predators may influence prey behaviors in marine ecosystems.
Figure 1. Map of BRUV survey deployments in Biscayne Bay, FL, USA. Red dots = dry season, green dots = wet season. White line represents boundary of Biscayne National Park
Figure 2. (a) The BRUV assembly; base 74 cm × 74 cm, slant height 72 cm, total height 48cm. (b) Still image captured from BRUV deployment with a bonnethead shark (Sphyrna tiburo) in frame. (c) Still image captured from BRUV deployment with schooling yellow snappers (Ocyurus chrysurus) and a southern stingray (Hypanus americanus) in frame
Figure 3. Mean predicted predator abundance (±95% confidence intervals) from a zero‐inflated negative binomial GLM across four habitat types: coral reef (CR), sand (SD), sea fan (SF), and seagrass (SG). Predicted predator abundance values, as well as mean predicted abundance by habitat (dashed lines) are overlaid on top of raw observational data
Figure 4. Predicted mean prey arrival time (y‐axis) as a function of maximum combined predator abundance (x‐axis) across four habitat types based on a negative binomial GLM. Predicted fits (±95% confidence intervals) are overlaid on top of raw observational data of seven prey families across four habitat types. CR, coral reef; SD, sand; SF, sea fan; SG, seagrass
Figure 5. Multidimensional ordination of predator foraging activity (predator bites and bait damage) and prey risk‐associated behaviors (burst swimming, schooling, and prey residency) across four habitat types. Colors match the previously used habitat‐specific colors
Figure 6. Correlation plot of prey risk behaviors (burst swimming, schooling, and prey residency) compared to predator foraging activity (bites and damage) across four habitat types
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