An overall lack of information prompted the recent listing of Atlantic Sturgeon Acipenser oxyrinchus oxyrinchus under the Endangered Species Act. Key to the restoration of the species and of particular importance is the need to characterize the use of critical habitat across the region, specifically in the Gulf of Maine, where the population was listed as threatened. Much of the research to date has focused on large river systems able to support remnant spawning populations; however, the role of small coastal river systems for Atlantic Sturgeon is not well documented. Several of these systems are being reinhabited, and to facilitate new knowledge about the Gulf of Maine population, a long-term (2009-2014) acoustic telemetry study for 51 Atlantic Sturgeon tagged in the Saco River was evaluated. Results suggested that the majority of fish were aggregating near the natural mouth of the estuary across the 6 years. Gastric lavage samples from 163 (91 juvenile and 72 adult) fish (65.0-171.5 cm fork length) during 2013 and 2014 demonstrated that American Sand Lance Ammodytes americanus was the most common prey (the index of relative importance for 2013 and 2014 was 93.5% and 85.4%, respectively), a finding unique to this river system. In addition, benthic sediment grabs, beam trawls, otter trawls, and beach seines conducted in 2013 and 2014 indicated that the distribution of American Sand Lances was comparable to the aggregation area observed for Atlantic Sturgeon. The combined results suggest that the Saco River estuary provides critical foraging habitat imperative for the future recovery of the Gulf of Maine Atlantic Sturgeon population.
The reproductive hormones associated with sex have been well studied in many sturgeon species. Here, these hormones are quantified as a non-lethal method to determine the sex and maturity of Atlantic sturgeon. The findings imply that the study area is used by multiple life stages, providing evidence for the importance of the habitat.
Resource selection functions (RSFs) have been widely applied to animal tracking data to examine relative habitat selection and to help guide management and conservation strategies. While readily used in terrestrial ecology, RSFs have yet to be extensively used within marine systems. As acoustic telemetry continues to be a pervasive approach within marine environments, incorporation of RSFs can provide new insights to help prioritize habitat protection and restoration to meet conservation goals. To overcome statistical hurdles and achieve high prediction accuracy, machine learning algorithms could be paired with RSFs to predict relative habitat selection for a species within and even outside the monitoring range of acoustic receiver arrays, making this a valuable tool for marine ecologists and resource managers. Here, we apply RSFs using machine learning to an acoustic telemetry dataset of four shark species to explore and predict species-specific habitat selection within a marine protected area. In addition, we also apply this RSF-machine learning approach to investigate predator-prey relationships by comparing and averaging tiger shark relative selection values with the relative selection values derived for eight potential prey-species. We provide methodological considerations along with a framework and flexible approach to apply RSFs with machine learning algorithms to acoustic telemetry data and suggest marine ecologists and resource managers consider adopting such tools to help guide both conservation and management strategies.
Background: Information regarding the movement ecology of horse-eye jack Caranx latus throughout the Caribbean is limited despite their prevalence. Passive acoustic telemetry was used to infer movement patterns of seven adult C. latus within Buck Island Reef National Monument (BIRNM), a no-take marine protected area (MPA) northeast of St. Croix, U.S. Virgin Islands. In addition, a preliminary exploration of detections recorded outside of BIRNM was used to gain knowledge of the potential for larger scale movements. Ascertaining long-term movement patterns, including residency, mobility, and identifying core activity spaces can play a considerable role in how MPAs, like BIRNM, are adapted to meet the needs of mobile species.Results: High residency index values were observed for individual C. latus within the BIRNM array (mean ± SE: 0.913 ± 0.04, range 0.75-1.0) across the 17 months monitored. Most fish were also detected on receivers located outside BIRNM. An observed to expected detection ratio revealed that despite high residency, only 9.6% of expected transmissions were detected based on the average tag transmission rate. Network analysis revealed high individual connectivity with many of the receivers inside BIRNM and a large number of core use receivers (mean: 10.7, range 6-14) within individual networks.Conclusions: Most C. latus were present in BIRNM at least twice per day, but were overall detected below the expected rates, demonstrating mobility, large core activity spaces and wide use of the acoustic array inside BIRNM and greater St. Croix shelf. How residency is inferred from acoustic telemetry detections, and interpreted for species with variable mobility, has important considerations for spatial management planning and telemetry analyses. For MPA development to meet the spatial requirements of species with mixed resident-mobile spatial ecology, detailed long-term movement data are required. Assessing residency in MPAs using acoustic telemetry should be formalized and carefully interpreted based on specific species, environmental conditions, and array configuration.
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