We used principal component analysis (PCA) to explore interannual changes in a time-series lasting more than 40 years of zooplankton abundance from NOAA's Continuous Plankton Recorder (CPR) survey. This analysis identified a complex of taxa, including Centropages typicus, Oithona spp., Pseudocalanus spp., and Metridia lucens that followed a common pattern of interdecadal variability characterized by a dramatic increase in these taxa around 1990, followed by a rapid decline in 2002. All of these taxa showed a large proportional increase in winter abundance between the 1980s and 1990s. These changes could be driven by increased primary productivity during winter, caused by a large-scale freshening of the Northwest Atlantic Shelf. In addition to the “community shift” mode, the analysis found a strong mode of interannual variability attributed to previously described changes in the abundance of late-stage Calanus finmarchicus. To explore the impact of these modes on higher trophic levels, we correlated the zooplankton modes with recruitment time-series from 12 fish stocks from the Gulf of Maine region. Several significant correlations were found, suggesting that the changes in the zooplankton modes may reflect broad changes in the Gulf of Maine ecosystem.
We examined a suite of abiotic, biotic, and human metrics for the northeast U.S. continental shelf ecosystem at the aggregate, community, and system level (>30 different metrics) over three decades. Our primary goals were to describe ecosystem status, to improve understanding of the relationships between key ecosystem processes, and to evaluate potential reference points for ecosystem-based fisheries management (EBFM). To this end, empirical indicators of ecosystem status were examined and standard multivariate statistical methods were applied to describe changes in the system. We found that (i) a suite of metrics is required to accurately characterize ecosystem status and, conversely, that focusing on a few metrics may be misleading; (ii) assessment of ecosystem status is feasible for marine ecosystems; (iii) multivariate points of reference can be determined for EBFM; and (iv) the concept of reference directions could provide an ecosystem level analog to single-species reference points.
Introduction 90Methods 92The production model 92The age structured model 93Accounting for uncertainty and stochasticity 94The early life history 95
AbstractThe relationship between the biomass of reproductively mature individuals (spawning stock) and the resulting offspring added to the population (recruitment), the stock-recruitment relationship, is a fundamental and challenging problem in all of population biology. The steepness of this relationship is commonly defined as the fraction of recruitment from an unfished population obtained when the spawning stock biomass is 20% of its unfished level. Since its introduction about 20 years ago, steepness has become widely used in fishery management, where it is usually treated as a statistical quantity. Here, we investigate the reproductive ecology of steepness, using both unstructured and age-structured models. We show that if one has sufficient information to construct a density-independent population model (maximum per capita productivity and natural mortality for the unstructured case or maximum per capita productivity, natural mortality and schedules of size and maturity at age for the structured model) then one can construct a point estimate for steepness. Thus, steepness cannot be chosen arbitrarily. If one assumes that the survival of recruited individuals fluctuates within populations, it is possible, by considering the early life history, to construct a prior distribution for steepness from this same demographic information. We develop the ideas for both compensatory (Beverton-Holt) and over-compensatory (Ricker) stock-recruitment relationships. We illustrate our ideas with an example concerning bluefin tuna (Thunnus thynnus/ orientalis, Scombridae). We show that assuming that steepness is unity when recruitment is considered to be environmentally driven is not biologically consistent, is inconsistent with a precautionary approach, and leads to the wrong scientific inference (which also applies for assigning steepness any other single value).
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