Intraguild processes drive space-use patterns in a large-bodied marine predator community
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May 03, 2024 version files 8.47 MB
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Abstract
Interspecific interactions, including predator-prey, intraguild predation (IGP), and competition, may drive distribution and habitat use of predator communities. However, elucidating the relative importance of these interactions in shaping predator distributions is challenging, especially in marine communities comprising highly mobile species.
We used individual-based models (IBMs) to predict the habitat distributions of apex predators, intraguild (IG) prey, and prey. We then used passive acoustic telemetry to test these predictions in a subtropical marine predator community consisting of eight elasmobranch (i.e., shark and ray) species in Bimini, The Bahamas.
IBMs predicted that prey and IG prey will preferentially select habitats based on safety over resources (food), with stronger selection for safe habitat by smaller prey. Elasmobranch space-use patterns matched these predictions. Species with predator-prey and asymmetrical IGP (between apex and small mesopredators) interactions showed the clearest spatial separation, followed by asymmetrical IGP among apex and large mesopredators. Competitors showed greater spatial overlap although with finer-scale differences in microhabitat use.
Our study suggests space-use patterns in elasmobranchs are at least partially driven by interspecific interactions, with stronger spatial separation occurring where interactions include predator-prey relationships or IGP.
Methods
Acoustic transmitters (InnovaSea, Canada; V16; battery life 2,435 to 3,650 days; transmission interval: 90–150 s) were surgically implanted into the body cavity of southern stingrays (Hypanus americanus), blacktip (C. limbatus), bull, Caribbean reef, great hammerhead, lemon (Negaprion brevirostris), nurse, and tiger sharks following capture, or attached externally to the base of the first dorsal fin via freediving for some great hammerheads, between April 2014–July 2018 (Guttridge et al., 2017; Smukall et al., 2022; van Zinnicq Bergmann et al., 2022). Bull, great hammerhead, and tiger sharks were considered apex predators (Cortés, 1999). Caribbean reef, adult lemon (males and females >175 and >185 cm PCL, respectively; Feldheim et al. 2014), and nurse sharks were classified as larger mesopredators, while southern stingrays, blacktip, and subadult lemon sharks were considered smaller mesopredators (Cortés, 1999). Sex and morphometrics (sharks: precaudal length, PCL; stingrays: curved disk width, DW) were recorded for each tagged elasmobranch via direct measurement or estimated via laser-photogrammetry for some great hammerheads instrumented during freediving (Guttridge et al., 2017).
Tagged elasmobranchs were monitored for 2.5 years, from 1 October 2016–30 April 2019, using an acoustic receiver array (VR2W, InnovaSea; n=56). This array covered all major marine biotopes, enabling monitoring of movements to and from the lagoon (Appendix S1: Figure S1). Each time a tagged elasmobranch entered the detection range of an acoustic receiver (500 m at minimum; van Zinnicq Bergmann et al. 2022), the unique tag ID code, date and time of detection were recorded and stored in the memory of that receiver. Receivers were retrieved, downloaded, batteries replaced, and redeployed at least once per year.
Acoustic data were cleaned by eliminating false positives (0.02%) from transmitters detected only once in a 1-hour time bin on a single receiver, excluding double detections (0.02%) from a single transmitter recorded by multiple receivers with overlapping detection ranges, and discarding detections within the initial 24 h post-tagging to prevent bias from tagging stress (van Zinnicq Bergmann et al., 2022). To analyse species-specific temporal trends in the number of tagged elasmobranchs detected on the receiver array, for each species we calculated the proportion of tagged individuals detected per month and year (i.e., the number of detected elasmobranchs divided by the number of tagged elasmobranchs), and subsequently aggregated monthly proportions across years.