Copy this text
Remote reefs and seamounts are the last refuges for marine predators across the Indo-Pacific
Since the 1950s, industrial fisheries have expanded globally, as fishing vessels are required to travel further afield for fishing opportunities. Technological advancements and fishery subsidies have granted ever-increasing access to populations of sharks, tunas, billfishes, and other predators. Wilderness refuges, defined here as areas beyond the detectable range of human influence, are therefore increasingly rare. In order to achieve marine resources sustainability, large no-take marine protected areas (MPAs) with pelagic components are being implemented. However, such conservation efforts require knowledge of the critical habitats for predators, both across shallow reefs and the deeper ocean. Here, we fill this gap in knowledge across the Indo-Pacific by using 1,041 midwater baited videos to survey sharks and other pelagic predators such as rainbow runner (Elagatis bipinnulata), mahi-mahi (Coryphaena hippurus), and black marlin (Istiompax indica). We modeled three key predator community attributes: vertebrate species richness, mean maximum body size, and shark abundance as a function of geomorphology, environmental conditions, and human pressures. All attributes were primarily driven by geomorphology (35%−62% variance explained) and environmental conditions (14%−49%). While human pressures had no influence on species richness, both body size and shark abundance responded strongly to distance to human markets (12%−20%). Refuges were identified at more than 1,250 km from human markets for body size and for shark abundance. These refuges were identified as remote and shallow seabed features, such as seamounts, submerged banks, and reefs. Worryingly, hotpots of large individuals and of shark abundance are presently under-represented within no-take MPAs that aim to effectively protect marine predators, such as the British Indian Ocean Territory. Population recovery of predators is unlikely to occur without strategic placement and effective enforcement of large no-take MPAs in both coastal and remote locations.
Full Text
File | Pages | Size | Access | |
---|---|---|---|---|
Publisher's official version | 20 | 3 Mo | ||
S1 Fig. Schematic of free-drifting BRUVS [49–51]. (A) Stereo rig with individual components. (B) Rig suspended in the midwater. BRUVS, baited remote underwater video system. | - | 459 Ko | ||
S2 Fig. Values (mean and range) of explanatory drivers of predator distribution at the deployment and prediction sites. (A–D) Environment drivers (in green). (E–G) Geomorphology drivers (in blue).. | - | 661 Ko | ||
S1 Table. Marine species and their maximum length, as recorded by midwater BRUVS across the Indo-Pacific, ordered by family. BRUVS, baited remote underwater video system. | - | 42 Ko | ||
S2 Table. BRT parameters used to fit the models on specific predator attributes. | - | 36 Ko | ||
S1 Data. Raw SR, body size (MaxL), and shark abundance (TaSharks) at each individual BRUVS deployment, pertaining to Fig 1B–1E. | - | 210 Ko | ||
S2 Data. Relative contribution of each BRT driver, pertaining to Fig 3A, Fig 4A, and Fig 5A. BRT, boosted regression tree. | - | 54 Ko | ||
S3 Data. Raw values of explanatory drivers of predator distribution at the deployment and prediction sites, pertaining to S2 Fig. | - | 2 Mo |