SUMMARY We quantified the flow field generated by tethered and free-swimming Euchaeta antarctica using the particle image velocimetry (PIV)technique. The streamlines around the free-swimming specimens were generally parallel to the body axis, whereas the streamlines around all of the tethered copepodids demonstrated increased curvature. Differences noted in the streamline pattern, and hence the vorticity, dissipation rate and strain rate fields, are explained by considering the forces on the free-swimming specimen compared to the tethered specimen. Viscous flow theory demonstrates that the force on the fluid due to the presence of the tether irrevocably modifies the flow field in a manner that is consistent with the measurements. Hence,analysis of the flow field and all associated calculations differ for tethered versus free-swimming conditions. Consideration of the flow field of the free-swimming predatory copepodid shows the intensity of the biologically generated flow and the extent of the mechanoreceptive signal quantified in terms of shear strain rate. The area in the dorso-ventral view surrounded by the 0.5 s-1 contour of exy, which is a likely threshold to induce an escape response, is 11 times the area of the exoskeletal form for the free-swimming case. Thus, mechanoreceptive predators will perceive a more spatially extended signal than the body size.

Swimming capacity is dependent on size (Johnson and Tarling, 2008) and organism size is directly related to the spatial extent of the hydrodynamic disturbance, which potentially provides a sensory field for prey, predators and conspecifics (Abrahamsen et al., 2010 Accepted 15 February 2011 SUMMARY Krill aggregations vary in size, krill density and uniformity depending on the species of krill. These aggregations may be structured to allow individuals to sense the hydrodynamic cues of neighboring krill or to avoid the flow fields of neighboring krill, which may increase drag forces on an individual krill. To determine the strength and location of the flow disturbance generated by krill, we used infrared particle image velocimetry measurements to analyze the flow field of free-swimming solitary specimens (Euphausia superba and Euphausia pacifica) and small, coordinated groups of three to six E. superba. Euphausia pacifica individuals possessed shorter body lengths, steeper body orientations relative to horizontal, slower swimming speeds and faster pleopod beat frequencies compared with E. superba. The downward-directed flow produced by E. pacifica has a smaller maximum velocity and smaller horizontal extent of the flow pattern compared with the flow produced by E. superba, which suggests that the flow disturbance is less persistent as a potential hydrodynamic cue for E. pacifica. Time record analysis reveals that the hydrodynamic disturbance is very weak beyond two body lengths for E. pacifica, whereas the hydrodynamic disturbance is observable above background level at four body lengths for E. superba. Because the nearest neighbor separation distance of E. superba within a school is less than two body lengths, hydrodynamic disturbances are a viable cue for intraspecies communication. The orientation of the position of the nearest neighbor is not coincident with the orientation of the flow disturbance, however, which indicates that E. superba are avoiding the region of strongest flow.

Previous assessments of the economic feasibility and large-scale productivity of microalgae biofuels have not considered the impacts of land and carbon dioxide (CO 2) availability on the scalability of microalgae-based biofuels production. To accurately assess the near-term productivity potential of large-scale microalgae biofuel in the US, a geographically realized growth model was used to simulate microalgae lipid yields based on meteorological data. The resulting lipid productivity potential of Nannochloropsis under large-scale cultivation is combined with land and CO 2 resource availability illustrating current geographically feasible production sites and corresponding productivity in the US. Baseline results show that CO 2 transport constraints will limit US microalgae based bio-oil production to 4% of the 2030 Department of Energy (DOE) alternative fuel goal. The discussion focuses on synthesis of this large-scale productivity potential results including a sensitivity analysis to land and CO 2 resource assumptions, an evaluation of previous modeling efforts and their assumptions regarding the transportation of CO 2 , the feasibility of microalgae to meet DOE 2030 alternative fuel goals, and a comparison of the productivity potential in several key regions of the US.

Current assessments of the commercial viability and productivity potential of microalgae biofuels have been forced to extrapolate small-scale research data. The resulting analyses are not representative of microalgae cultivation and processing at industrial scale. To more accurately assess the current near-term realizable, large-scale microalgae productivity potential in the USA, this paper presents a model of microalgae growth derived from industrial-scale outdoor photobioreactor growth data. This model is combined with thermal models of the photobioreactor system and 15 years of hourly historical weather data from 864 locations in the USA to more accurately assess the current productivity potential of microalgae. The resulting lipid productivity potential of Nannochloropsis is presented in the form of a map that incorporates various land availability models to illustrate the near-term feasible cultivation locations and corresponding productivity potentials for the USA. The discussion focuses on a comparison of model results with productivity potentials currently reported in literature, an assessment demonstrating the scale of Department of Energy 2030 alternative fuel goals, and a critical comparison of productivity potential in several key regions of the USA. Keywords Biofuels . GIS . Microalgae . Model . Productivity potential Abbreviations PAR Photosynthetic active radiation PFD Photon flux density GIS Geographic information system PBR Photobioreactor ORP Open raceway pond DOE Department of Energy NLCD National Land Cover Database Nomenclature c p Specific heat of water (kJ kg −1 K −1 ) E a Activation energy carboxylation Rubisco (J mol −1 ) G bottom Solar energy reaching the bottom (W m −2 ) G n Solar energy reaching node n (W m −2 ) G sur Solar energy reaching the surface (W m −2Thermal conductivity of water (W m −1 K −1 ) L n Distance between nodes (m) m n Total mass represented by node n (kg) Q i Energy stored/released by ground (W m −2 ) R Universal gas constant (J K −1 mol −1 )Electronic supplementary material The online version of this article (

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