The general warming of the eastern Bering Sea (EBS) and the wide range of abundance exhibited by several eastern Bering Sea flatfish motivated an examination of how density-dependent and density-independent factors may influence the spatial distributions of EBS flatfish. In this study, EBS trawl survey data from 1982 to 2006 were used to examine how temporal changes in the distributions of six flatfish species groups [yellowfin sole (Limanda aspera), rock sole (Lepidopsetta sp.), flathead sole (Hippoglossoides sp.), Alaska plaice (Pleuronectes quadrituberculatus), arrowtooth flounder (Atheresthes sp.), and Greenland turbot (Reinhardtius hippoglossoides)] are related to temporal changes in the location of the 'cold pool' (bottom water < 2°C), and how the area occupied by flatfish are related to the cold pool and population abundance. Rock sole and flathead sole distributions have generally moved northwest since 1982 and are significantly correlated with the movement of the cold pool, whereas arrowtooth flounder avoid the cold pool and their area occupied is inversely related to the size of the cold pool. The area occupied by arrowtooth flounder and rock sole are also significantly related to stock abundance. Multivariate statistical models indicate that the location of rock sole is more strongly related to stock abundance than to the cold pool, whereas the area occupied by arrowtooth flounder is more strongly related to the area of the cold pool rather than abundance. The temperatures occupied by several flatfish stocks indicate a substantial variability in suitable temperatures. These results suggest that a complex suite of density-dependent and density-independent factors may determine the response of EBS flatfish spatial distributions to increasing temperatures.

The goals of this research were to investigate geographic patterns in the Aleutian Island region's demersal ichthyofauna and to determine whether they reflected the physical and biological oceanographic patterns documented by other authors in this volume. The analyses were structured according to the level of organization: at the community level, patterns in species occurrence and community structure were investigated; at the population level, distribution and abundance were examined; at the individual level, food habits and growth were studied. There were stepchanges in species occurrence, diversity, population distribution and food habits at Samalga Pass and at sites farther west. These longitudinal trends indicated physical and biological variation along the length of the Aleutian Islands chain; however, depth-related patterns were as common as longitudinal patterns in demersal fish distribution. In addition, high catches of patchily distributed species occurred in areas expected to be biological 'hot spots' because of increased productivity and prey availability. These patterns suggest linkages between demersal fish ecology and the biophysical processes described by other authors in this volume and indicate that inter-disciplinary research is needed to elucidate the underlying mechanisms.

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Climate-related shifts in marine mammal range and distribution have been observed in some populations; however, the nature and magnitude of future responses are uncertain in novel environments projected under climate change. This poses a challenge for agencies charged with management and conservation of these species. Specialized diets, restricted ranges, or reliance on specific substrates or sites (e.g., for pupping) make many marine mammal populations particularly vulnerable to climate change. High-latitude, predominantly ice-obligate, species have experienced some of the largest changes in habitat and distribution and these are expected to continue. Efforts to predict and project marine mammal distributions to date have emphasized data-driven statistical habitat models. These have proven successful for short time-scale (e.g., seasonal) management activities, but confidence that such relationships will hold for multi-decade projections and novel environments is limited. Recent advances in mechanistic modeling of marine mammals (i.e., models that rely on robust physiological and ecological principles expected to hold under climate change) may address this limitation. The success of such approaches rests on continued advances in marine mammal ecology, behavior, and physiology together with improved regional climate projections. The broad scope of this challenge suggests initial priorities be placed on vulnerable species or populations (those already experiencing declines or projected to undergo ecological shifts resulting from climate Silber et al.Projecting Marine Mammal Distributions changes that are consistent across climate projections) and species or populations for which ample data already exist (with the hope that these may inform climate change sensitivities in less well observed species or populations elsewhere). The sustained monitoring networks, novel observations, and modeling advances required to more confidently project marine mammal distributions in a changing climate will ultimately benefit management decisions across time-scales, further promoting the resilience of marine mammal populations.