Nested scales of spatial heterogeneity in juvenile walleye pollock Theragra chalcogramma in the southeastern Bering Sea

We sought to characterize the distribution of juvenile walleye pollock Theragra chalcogramma in an area of intense predator-prey interactions and to describe habitat features that lead to their observed distributions. The distribution of juvenile walleye pollock around the Pribilof Islands in the southeastern Bering Sea in 2008 and 2009 was patchy, at spatial scales ranging from a few meters to several 10s of kilometers. These patches, and the spaces between them, were hierarchically nested with small, dense patches clustered together into larger aggregations which were further aggregated over the region sampled. Vertical physical habitat structure affected the vertical distribution of juvenile pollock similarly in both years. However, despite largely similar physical characteristics in both years, there were significant differences between years in the horizontal distribution, patch structure, and abundance of juvenile pollock. In neither year did biological or physical environment characteristics explain the broad-scale variability in the horizontal distribution of juvenile pollock, but at small horizontal scales a behavioral component was evident, with fish changing their group coherence as conditions changed despite consistent group sizes. It is clear that if we are to understand the processes that drive the distribution of juvenile pollock, we must consider multiple scales of heterogeneity. Only then will we begin to understand the role of pollock in the ecosystem and be able to predict the consequences of large sources of variability such as climate change, a critical question in the rapidly changing physical and biological environment of the Bering Sea.Keywords: Spatial structure, Walleye pollock, Schooling, Bering Sea, Patchines

Active acoustic examination of the diving behavior of murres foraging on patchy prey

During the 2008 and 2009 breeding seasons of murres Uria spp., we combined visual observations of these predators with active acoustics (sonar), fish trawls, zooplankton net tows, and hydrographic measurements in the area surrounding breeding colonies in the southeastern Bering Sea. We acoustically detected thousands of bubble trails that were strongly correlated with the number of visually detected murres, providing a new tool for quantitatively studying the foraging ecology of diving birds. At the regional scale, the number of acoustically detected bubble trails, which served as a proxy for diving murre abundance, was related to the combined availability and vertical accessibility of squid, krill, and pollock. There were, however, no clear relationships at this scale between diving murres and any individual prey taxon, highlighting the importance of prey diversity to these animals. Individual krill patches targeted by murres had higher krill density and were located shallower than the mean depth of krill patches, but were similar in total krill abundance and overall size. The diving depth of murres within krill patches was highly correlated to the depth of the upper edge of these patches, whereas murres found outside of krill patches showed a depth distribution similar to that of juvenile pollock. Throughout the study area, murres showed strong diel patterns in their diving behavior in response to the diel migrations of their prey. These results suggest that murres select prey with specific patch characteristics implying effective information gathering about prey by murres. The high proportion of diving murres in aggregations and their consistent inter-individual spacing support the hypothesis that intra-specific local enhancement may facilitate foraging in these predators.Keywords: Seabirds, Predator−prey, Acoustics, Foragin

Comparative study between transcriptionally- and translationally-acting adenine riboswitches reveals key differences in riboswitch regulatory mechanisms

Many bacterial mRNAs are regulated at the transcriptional or translational level by ligand-binding elements called riboswitches. Although they both bind adenine, the adenine riboswitches of Bacillus subtilis and Vibrio vulnificus differ by controlling transcription and translation, respectively. Here, we demonstrate that, beyond the obvious difference in transcriptional and translational modulation, both adenine riboswitches exhibit different ligand binding properties and appear to operate under different regulation regimes (kinetic versus thermodynamic). While the B. subtilis pbuE riboswitch fully depends on co-transcriptional binding of adenine to function, the V. vulnificus add riboswitch can bind to adenine after transcription is completed and still perform translation regulation. Further investigation demonstrates that the rate of transcription is critical for the B. subtilis pbuE riboswitch to perform efficiently, which is in agreement with a cotranscriptional regulation. Our results suggest that the nature of gene regulation control, that is transcription or translation, may have a high importance in riboswitch regulatory mechanisms

Prey patch patterns predict habitat use by top marine predators with diverse foraging strategies.

Spatial coherence between predators and prey has rarely been observed in pelagic marine ecosystems. We used measures of the environment, prey abundance, prey quality, and prey distribution to explain the observed distributions of three co-occurring predator species breeding on islands in the southeastern Bering Sea: black-legged kittiwakes (Rissa tridactyla), thick-billed murres (Uria lomvia), and northern fur seals (Callorhinus ursinus). Predictions of statistical models were tested using movement patterns obtained from satellite-tracked individual animals. With the most commonly used measures to quantify prey distributions--areal biomass, density, and numerical abundance--we were unable to find a spatial relationship between predators and their prey. We instead found that habitat use by all three predators was predicted most strongly by prey patch characteristics such as depth and local density within spatial aggregations. Additional prey patch characteristics and physical habitat also contributed significantly to characterizing predator patterns. Our results indicate that the small-scale prey patch characteristics are critical to how predators perceive the quality of their food supply and the mechanisms they use to exploit it, regardless of time of day, sampling year, or source colony. The three focal predator species had different constraints and employed different foraging strategies--a shallow diver that makes trips of moderate distance (kittiwakes), a deep diver that makes trip of short distances (murres), and a deep diver that makes extensive trips (fur seals). However, all three were similarly linked by patchiness of prey rather than by the distribution of overall biomass. This supports the hypothesis that patchiness may be critical for understanding predator-prey relationships in pelagic marine systems more generally

Foraging responses of black-legged kittiwakes to prolonged food-shortages around colonies on the Bering Sea Shelf

We hypothesized that changes in southeastern Bering Sea foraging conditions for black-legged kittiwakes (Rissa tridactyla) have caused shifts in habitat use with direct implications for population trends. To test this, we compared at-sea distribution, breeding performance, and nutritional stress of kittiwakes in three years (2008–2010) at two sites in the Pribilof Islands, where the population has either declined (St. Paul) or remained stable (St. George). Foraging conditions were assessed from changes in (1) bird diets, (2) the biomass and distribution of juvenile pollock (Theragra chalcogramma) in 2008 and 2009, and (3) eddy kinetic energy (EKE; considered to be a proxy for oceanic prey availability). In years when biomass of juvenile pollock was low and patchily distributed in shelf regions, kittiwake diets included little or no neritic prey and a much higher occurrence of oceanic prey (e.g. myctophids). Birds from both islands foraged on the nearby shelves, or made substantially longer-distance trips overnight to the basin. Here, feeding was more nocturnal and crepuscular than on the shelf, and often occurred near anticyclonic, or inside cyclonic eddies. As expected from colony location, birds from St. Paul used neritic waters more frequently, whereas birds from St. George typically foraged in oceanic waters. Despite these distinctive foraging patterns, there were no significant differences between colonies in chick feeding rates or fledging success. High EKE in 2010 coincided with a 63% increase in use of the basin by birds from St. Paul compared with 2008 when EKE was low. Nonetheless, adult nutritional stress, which was relatively high across years at both colonies, peaked in birds from St. Paul in 2010. Diminishing food resources in nearby shelf habitats may have contributed to kittiwake population declines at St Paul, possibly driven by increased adult mortality or breeding desertion due to high foraging effort and nutritional stress

The distribution of juvenile walleye pollock in 2009 based on three different metrics.

<p>A. biomass density, the most commonly used measure, B. the mean volumetric density of pollock within aggregations, a measure of local density within a patch, and C. the maximum volumetric density of pollock per sampling transect. Map surfaces were generated using minimum curvature interpolations (N = 165).</p

Predicted and observed predator habitat use in 2009.

<p>A. The predicted density classes for each predator species using the full multiple-regression model based on transect data and B. the kernel densities for tagged individual predators at each sampled transect. C. The difference between the model category and the kernel category. Positive, cool colored values indicate that fewer predators used an area than predicted by the model while negative, warm colored values indicate the opposite. On each plot, the center of each transect that was visually surveyed for birds and mammals and thus was used to create the regression model is shown with a +. The center of each transect for which environmental and prey data were available but could not be used to create the regression model is shown by o. Map surfaces were generated using minimum curvature interpolation that did not allow values plotted at sampled points to differ from their actual values.</p