19 research outputs found

    Effects of Variable Oceanographic Conditions on Forage Fish Lipid Content and Fatty Acid Composition in the Northern California Current

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    Lipids and fatty acids (FA) were investigated in 4 species of forage fish: northern anchovy Engraulis mordax, Pacific sardine Sardinops sagax, Pacific herring Clupea pallasi, and whitebait smelt Allosmerus elongatus, for their ability to serve as biological indicators of ocean conditions in the California Current large marine ecosystem (CCLME). Samples were collected during the oceanographically contrasting years of 2005 and 2006. Upwelling was severely curtailed in the spring and early summer of 2005, leading to delayed biological productivity, whereas upwelling was relatively normal in spring 2006. Principal components analysis described 78% of the variance within the lipid and FA dataset using the first 2 principal components. We found significant intra- and interspecific, interannual, and seasonal differences in lipid and FA profiles using univariate and permutation- based multivariate analysis of variance. Indicator species analysis showed distinct lipid and FA properties associated with each fish species. Using the ratio of docosahexaenoic acid (C22:6n-3) to eicosapentaeonic acid (C20:5n-3), we detected a transition from a diet composed primarily of dinoflagellate origin in early 2005 to a diet resulting from diatom-based productivity by late summer 2006. This shift was due to interannual differences in primary production, which was confirmed through phytoplankton sampling. Our study demonstrates that lipid and FA biomarkers in the forage fish community can provide information on ocean conditions and productivity that affect food web structure in the CCLME

    Multivariate models of adult Pacific salmon returns.

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    Most modeling and statistical approaches encourage simplicity, yet ecological processes are often complex, as they are influenced by numerous dynamic environmental and biological factors. Pacific salmon abundance has been highly variable over the last few decades and most forecasting models have proven inadequate, primarily because of a lack of understanding of the processes affecting variability in survival. Better methods and data for predicting the abundance of returning adults are therefore required to effectively manage the species. We combined 31 distinct indicators of the marine environment collected over an 11-year period into a multivariate analysis to summarize and predict adult spring Chinook salmon returns to the Columbia River in 2012. In addition to forecasts, this tool quantifies the strength of the relationship between various ecological indicators and salmon returns, allowing interpretation of ecosystem processes. The relative importance of indicators varied, but a few trends emerged. Adult returns of spring Chinook salmon were best described using indicators of bottom-up ecological processes such as composition and abundance of zooplankton and fish prey as well as measures of individual fish, such as growth and condition. Local indicators of temperature or coastal upwelling did not contribute as much as large-scale indicators of temperature variability, matching the spatial scale over which salmon spend the majority of their ocean residence. Results suggest that effective management of Pacific salmon requires multiple types of data and that no single indicator can represent the complex early-ocean ecology of salmon

    Observed and predicted spring Chinook adult returns.

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    <p>Observed spring Chinook adult returns (solid circles) and leave-one-out predictions (open diamonds) with 95% prediction intervals obtained from MCA. Predicted returns in 2011 and 2012 (2009 and 2010 juvenile migration year) are shown with 95% prediction intervals (grey diamonds).</p

    Indicator importance values.

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    <p>Percent of variance in salmon returns explained in the MCA analysis that can be attributed to each indicator (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0054134#pone-0054134-t001" target="_blank">Table 1</a>).</p
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