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The sand tiger shark Carcharias taurus is a highly migratory coastal species with declining populations worldwide. This species exhibits many behaviors that make coastal sharks difficult to manage, including aggregatory behavior, sexual segregation, and large-scale migrations through shallow coastal waters with many opportunities for human interactions. Sand tigers from the Western North Atlantic subpopulation are known to seasonally inhabit Delaware Bay and surrounding coastal waters. This region has been recommended as a habitat area of particular concern for the Western North Atlantic sand tiger population, and increased understanding of their movements and habitat requirements will facilitate management efforts. We developed models to predict sand tiger occupancy using spatially dynamic environmental predictors. Our models predicted sand tiger (juveniles, adult males, adult females, and all sharks combined) occurrences in 2 study regions, the Delaware Bay and the western Mid-Atlantic coastal ocean. Sea surface temperature, day of year, water depth, and remote sensing reflectance at 555 nm were the most important environmental predictors of occurrence, and correctly predicted 80–89% of sand tiger acoustic telemetry records in the 2 study regions. Our models predicted differences in the timing and location of occurrences among juveniles and adults, as well as areas where these life history stages overlap in the Mid-Atlantic coastal ocean. Our hope is that a daily forecast of sand tiger occurrence from our modeling efforts could be useful for conservation and management efforts in this important region, as well as for studying the spatial and behavioral ecology of this important top predator.

Quantifying habitat selection in marine organisms is challenging because it is difficult to obtain species location information with multiple corresponding habitat measurements. In the ocean, habitat conditions vary on many spatiotemporal scales, which have important consequences for habitat selection. While macroscale biotic and abiotic features influence seasonal movements (spatial scales of 100–1000 km), selectivity of conditions on mesoscales (1–100 km) reflects an animal’s response to the local environment. In this study, we examined habitat selectivity by pairing acoustic telemetry with environmental habitat parameters measured by an autonomous underwater vehicle (AUV), and demonstrate that migrating sand tiger sharks Carcharias taurus along the East Coast of the USA did not randomly use the coastal environment. Of the variables examined, we found evidence to suggest that sand tigers were selecting their habitat based on distance to shore, salinity, and colored dissolved organic matter (CDOM). Notably, temperature was not predictive of habitat use in our study. We posit that during their coastal migration, sand tigers select for specific mesoscale coastal habitats that may inform navigation or feeding behaviors. To our knowledge, this is the first empirical measure of mesoscale habitat selection by a coastal marine organism using an AUV. The applications of this method extend beyond the habitat selectivity of sand tigers, and will prove useful for future studies combining in situ observations of marine habitats and animal observations.

Mussels have myriad effects on population, community, and ecosystem processes. Their aggregation behavior is an inducible defense that links non-consumptive effects of predators to benthic spatial pattern formation. Aggregation increases intraspecific competition but can be beneficial due to lower perimeter-related predation and other risks. Mytilus edulis aggregation responses to predation threats have not been investigated outside of Europe. We studied the effects of chemical cues from heterospecifics (predators Carcinus maenas, Nucella lapillus; herbivore Littorina littorea) and conspecifics (injured and intact M. edulis) on M. edulis aggregation behavior in Maine, USA. Mussels self-organized into fractal power-law spatial patterns like those in the field. Aggregations had lower perimeter:area (P:A) ratios than singletons, despite having more complex, irregular shapes with higher fractal dimensions (D). However, with one exception, no significant differences in aggregation rate, P:A ratio, and D were observed for any chemical cue treatment when compared to no-cue controls. Our experiment revealed higher aggregation rates than reported from similar experiments, leaving little scope for additional aggregation when exposed to chemical cues. We suggest that increased aggregation in response to predation threat is context-dependent: costs outweigh benefits beyond some optimal aggregation size, and mussels in our experiment were at the upper aggregation limit beyond which more aggregation could have negative consequences. Bet-hedging with a power-law distribution of aggregation shapes and sizes may be the optimal spatial strategy, especially if predation and other risks are variable in space and time.

Synthesis research in ecology and environmental science improves understanding, advances theory, identifies research priorities, and supports management strategies by linking data, ideas, and tools. Accelerating environmental challenges increases the need to focus synthesis science on the most pressing questions. To leverage input from the broader research community, we convened a virtual workshop with participants from many countries and disciplines to examine how and where synthesis can address key questions and themes in ecology and environmental science in the coming decade. Seven priority research topics emerged: (1) diversity, equity, inclusion, and justice (DEIJ), (2) human and natural systems, (3) actionable and use‐inspired science, (4) scale, (5) generality, (6) complexity and resilience, and (7) predictability. Additionally, two issues regarding the general practice of synthesis emerged: the need for increased participant diversity and inclusive research practices; and increased and improved data flow, access, and skill‐building. These topics and practices provide a strategic vision for future synthesis in ecology and environmental science.