Ecosystem-based Management for Protected Species in the North Pacific Fisheries

In the North Pacific Ocean, an ecosystem-based fishery management approach has been adopted. A significant objective of this approach is to reduce interactions between fishery-related activities and protected species. We review management measures developed by the North Pacific Fishery Management Council and the National Marine Fisheries Service to reduce effects of the groundfish fisheries off Alaska on marine mammals and seabirds, while continuing to provide economic opportunities for fishery participants. Direct measures have been taken to mitigate known fishery impacts, and precautionary measures have been taken for species with potential (but no documented) interactions with the groundfish fisheries. Area closures limit disturbance to marine mammals at rookeries and haulouts, protect sensitive benthic habitat, and reduce potential competition for prey resources. Temporal and spatial dispersion of catches reduce the localized impact of fishery removals. Seabird avoidance measures have been implemented through collaboration with fishery participants and have been highly successful in reducing seabird bycatch. Finally, a comprehensive observer monitoring program provides data on the location and extent of bycatch of marine mammals and seabirds. These measures provide managers with the flexibility to adapt to changes in the status of protected species and evolving conditions in the fisheries. This review should be useful to fishery managers as an example of an ecosystem-based approach to protected species management that is adaptive and accounts for multiple objectives

For the good of the group? Exploring group-level evolutionary adaptations using multilevel selection theory.

In this paper, we present an evolutionary framework, multilevel selection theory (MLS), that is highly amenable to existing social psychological theory and empiricism. MLS provides an interpretation of natural selection that shows how group-beneficial traits can evolve, a prevalent implication of social psychological data. We outline the theory and provide a number of example topics, focusing on prosociality, policing behavior, gossip, brainstorming, distributed cognition, and social identity. We also show that individual differences can produce important group-level outcomes depending on differential aggregation of individual types and relate this to the evolutionary dynamics underlying group traits. Drawing on existing work, we show how social psychologists can integrate this framework into their research program and suggest future directions for research

The Relevance of Evolutionary Science For Economic Theory and Policy

NSF’s “Dear Colleague Letter” reflects the widely perceived need to go beyond current economic theory in the formulation of public policy. At the same time, there is a profound lack of unity among the disciplines that comprise the behavioral, social, and economic sciences. This white paper emphasizes the relevance of evolutionary science as a way to integrate the SBE sciences, similar to the integration that is more advanced in the biological sciences. Modern evolutionary science is broadly construed to include cultural in addition to biological evolution and the study of neural and psychological mechanisms (proximate causation) in addition to the environmental factors that brought the mechanisms into existence and result in the expression of specific behaviors (ultimate causation). It provides an exceptionally useful set of theoretical and empirical tools for integrating the many disciplines in the biological and SBE sciences required to formulate economic theory and public policy for the 21st century. The task of integration is already in progress and can be applied to the formulation of public policy without a long academic time lag. We therefore call for integration across disciplines and evolutionary science as an integrative framework to be recognized as a funding priority by NSF.

Bitter taste stimuli induce differential neural codes in mouse brain.

A growing literature suggests taste stimuli commonly classified as "bitter" induce heterogeneous neural and perceptual responses. Here, the central processing of bitter stimuli was studied in mice with genetically controlled bitter taste profiles. Using these mice removed genetic heterogeneity as a factor influencing gustatory neural codes for bitter stimuli. Electrophysiological activity (spikes) was recorded from single neurons in the nucleus tractus solitarius during oral delivery of taste solutions (26 total), including concentration series of the bitter tastants quinine, denatonium benzoate, cycloheximide, and sucrose octaacetate (SOA), presented to the whole mouth for 5 s. Seventy-nine neurons were sampled; in many cases multiple cells (2 to 5) were recorded from a mouse. Results showed bitter stimuli induced variable gustatory activity. For example, although some neurons responded robustly to quinine and cycloheximide, others displayed concentration-dependent activity (p<0.05) to quinine but not cycloheximide. Differential activity to bitter stimuli was observed across multiple neurons recorded from one animal in several mice. Across all cells, quinine and denatonium induced correlated spatial responses that differed (p<0.05) from those to cycloheximide and SOA. Modeling spatiotemporal neural ensemble activity revealed responses to quinine/denatonium and cycloheximide/SOA diverged during only an early, at least 1 s wide period of the taste response. Our findings highlight how temporal features of sensory processing contribute differences among bitter taste codes and build on data suggesting heterogeneity among "bitter" stimuli, data that challenge a strict monoguesia model for the bitter quality

Modeling vitreous silica bilayers

We computer model a free-standing vitreous silica bilayer which has recently been synthesized and characterized experimentally in landmark work. Here we model the bilayer using a computer assembly procedure that starts from a single layer of amorphous graphene, generated using a bond switching algorithm from an initially crystalline graphene structure. Next each bond is decorated with an oxygen atom and the carbon atoms are relabeled as silicon. This monolayer can be now thought of as a two dimensional network of corner sharing triangles. Next each triangle is made into a tetrahedron, by raising the silicon atom above each triangle and adding an additional singly coordinated oxygen atom at the apex. The final step is to mirror reflect this layer to form a second layer and then attach the two layers together to form the bilayer. We show that this vitreous silica bilayer has the additional macroscopic degrees of freedom to easily form a network of identical corner sharing tetrahedra if there is a symmetry plane through the center of the bilayer going through the layer of oxygen ions that join the upper and lower layers. This has the consequence that the upper rings lie exactly above the lower rings, which are tilted in general. The assumption of a network of perfect corner sharing tetrahedra leads to a range of possible densities that we have previously characterized in three dimensional zeolites as a flexibility window. Finally, using a realistic potential, we have relaxed the bilayer to determine the density, and other structural characteristics such as the Si-Si pair distribution functions and the Si-O-Si bond angle distribution, which are compared to the experimental results obtained by direct imaging