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Forage fishes are a critical food web link in marine ecosystems, aggregating in a hierarchical patch structure over multiple spatial and temporal scales. Surface‐level forage fish aggregations (FFAs) represent a concentrated source of prey available to surface‐ and shallow‐foraging marine predators. Existing survey and analysis methods are often imperfect for studying forage fishes at scales appropriate to foraging predators, making it difficult to quantify predator–prey interactions. In many cases, general distributions of forage fish species are known; however, these may not represent surface‐level prey availability to predators. Likewise, we lack an understanding of the oceanographic drivers of spatial patterns of prey aggregation and availability or forage fish community patterns. Specifically, we applied Bayesian joint species distribution models to bottom trawl survey data to assess species‐ and community‐level forage fish distribution patterns across the US Northeast Continental Shelf (NES) ecosystem. Aerial digital surveys gathered data on surface FFAs at two project sites within the NES, which we used in a spatially explicit hierarchical Bayesian model to estimate the abundance and size of surface FFAs. We used these models to examine the oceanographic drivers of forage fish distributions and aggregations. Our results suggest that, in the NES, regions of high community species richness are spatially consistent with regions of high surface FFA abundance. Bathymetric depth drove both patterns, while subsurface features, such as mixed layer depth, primarily influenced aggregation behavior and surface features, such as sea surface temperature, sub‐mesoscale eddies, and fronts influenced forage fish diversity. In combination, these models help quantify the availability of forage fishes to marine predators and represent a novel application of spatial models to aerial digital survey data. [ABSTRACT FROM AUTHOR]

It is generally assumed that species with low population sizes have lower genetic diversities than larger populations and vice versa. However, this would not be the case for long-lived species with long generation times, and which populations have declined due to anthropogenic effects, such as the blue whale ( Balaenoptera musculus). This species was intensively decimated globally to near extinction during the 20th century. Along the Chilean coast, it is estimated that at least 4288 blue whales were hunted from an apparently pre-exploitation population size (k) of a maximum of 6200 individuals (Southeastern Pacific). Thus, here, we describe the mtDNA (control region) and nDNA (microsatellites) diversities of the Chilean blue whale aggregation site in order to verify the expectation of low genetic diversity in small populations. We then compare our findings with other blue whale aggregations in the Southern Hemisphere. Interestingly, although the estimated population size is small compared with the pre-whaling era, there is still considerable genetic diversity, even after the population crash, both in mitochondrial ( N = 46) and nuclear ( N = 52) markers (Hd = 0.890 and Ho = 0.692, respectively). Our results suggest that this diversity could be a consequence of the long generation times and the relatively short period of time elapsed since the end of whaling, which has been observed in other heavily-exploited whale populations. The genetic variability of blue whales on their southern Chile feeding grounds was similar to that found in other Southern Hemisphere blue whale feeding grounds. Our phylogenetic analysis of mtDNA haplotypes does not show extensive differentiation of populations among Southern Hemisphere blue whale feeding grounds. The present study suggests that although levels of genetic diversity are frequently used as estimators of population health, these parameters depend on the biology of the species and should be taken into account in a monitoring framework study to obtain a more complete picture of the conservation status of a population. [ABSTRACT FROM AUTHOR]