85 research outputs found

    The response of fish larvae to decadal changes in environmental forcing factors off the Oregon coast

    Get PDF
    We conducted a statistical analysis to characterize the influence of large-scale and local environmental factors on presence-absence, concentration, and assemblage structure of larval fish within the northern California Current (NCC) ecosystem, based on samples collected at two nearshore stations along the Newport Hydrographic line off the central Oregon coast. Data from 1996 to 2005 were compared with historical data from the 1970s and 1980s to evaluate pseudo-decadal, annual, and seasonal variability. Our results indicate that the most abundant taxa from 1996 to 2005 differ from those of earlier decades. Concentrations of the dominant taxa and total larvae were generally greater in the winter ⁄ spring than summer ⁄ fall season. Using generalized additive modeling, variations in presence-absence and concentration of taxa were compared to climate indices such as the Pacific Decadal Oscillation, Northern Oscillation Index, and the multivariate ENSO index and local environmental factors, such as upwelling, Ekman transport, and wind stress curl. Significant relationships were found for various combinations of environmental variables with lag periods ranging from 0 to 7 months. We found that the large-scale climate indices explained more of the variance in larval fish concentration and diversity than did the more local factors. Our results indicate that readily available oceanographic and climate indices can explain variations in the dominant ichthyoplankton taxa in the NCC. However, variation in response among taxa to the environmental metrics suggests additional unknown factors not included in the analysis likely contributed to the observed distribution patterns and larval fish community structure in the NCC

    Climate and demography dictate the strength of predator-prey overlap in a subarctic marine ecosystem

    Get PDF
    There is growing evidence that climate and anthropogenic influences on marine ecosystems are largely manifested by changes in species spatial dynamics. However, less is known about how shifts in species distributions might alter predatorprey overlap and the dynamics of prey populations. We developed a general approach to quantify species spatial overlap and identify the biotic and abiotic variables that dictate the strength of overlap. We used this method to test the hypothesis that population abundance and temperature have a synergistic effect on the spatial overlap of arrowtooth flounder (predator) and juvenile Alaska walleye pollock (prey, age-1) in the eastern Bering Sea. Our analyses indicate that (1) flounder abundance and temperature are key variables dictating the strength of flounder and pollock overlap, (2) changes in the magnitude of overlap may be largely driven by density-dependent habitat selection of flounder, and (3) species overlap is negatively correlated to juvenile pollock recruitment when flounder biomass is high. Overall, our findings suggest that continued increases in flounder abundance coupled with the predicted long-term warming of ocean temperatures could have important implications for the predator-prey dynamics of arrowtooth flounder and juvenile pollock. The approach used in this study is valuable for identifying potential consequences of climate variability and exploitation on species spatial dynamics and interactions in many marine ecosystems. Copyright: 2013 Hunsicker et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credite

    A simulation framework for sub-sampling strategy evaluation in multi-stage sampling designs that accounts for spatially structured traits

    Get PDF
    Selecting an appropriate and efficient sampling strategy in biological surveys is a major concern in ecological research, particularly when the population abundance and individual traits of the sampled population are highly structured over space. Multi-stage sampling designs typically present sampling sites as primary units. However, to collect trait data, such as age or maturity, only a sub-sample of individuals collected in the sampling site is retained. Therefore, not only the sampling design, but also the sub-sampling strategy can have a major impact on important population estimates, commonly used as reference points for management and conservation. We developed a simulation framework to evaluate sub-sampling strategies from multi-stage biological surveys. Specifically, we compare quantitatively precision and bias of the population estimates obtained using two common but contrasting sub-sampling strategies: the random and the stratified designs. The sub-sampling strategy evaluation was applied to age data collection of a virtual fish population that has the same statistical and biological characteristics of the Eastern Bering Sea population of Pacific cod. The simulation scheme allowed us to incorporate contributions of several sources of error and to analyze the sensitivity of the different strategies in the population estimates. We found that, on average across all scenarios tested, the main differences between sub-sampling designs arise from the inability of the stratified design to reproduce spatial patterns of the individual traits. However, differences between the sub-sampling strategies in other population estimates may be small, particularly when large sub-sample sizes are used. On isolated scenarios (representative of specific environmental or demographic conditions), the random sub-sampling provided better precision in all population estimates analyzed. The sensitivity analysis revealed the important contribution of spatial autocorrelation in the error of population trait estimates, regardless of the sub-sampling design. This framework will be a useful tool for monitoring and assessment of natural populations with spatially structured traits in multi-stage sampling designs
    corecore