A meta-analytic approach to quantifying scientific uncertainty in stock assessments

Quantifying scientific uncertainty when setting total allowable catch limits for fish stocks is a major challenge, but it is a requirement in the United States since changes to national fisheries legislation. Multiple sources of error are readily identifiable, including estimation error, model specification error, forecast error, and errors associated with the definition and estimation of reference points. Our focus here, however, is to quantify the influence of estimation error and model specification error on assessment outcomes. These are fundamental sources of uncertainty in developing scientific advice concerning appropriate catch levels and although a study of these two factors may not be inclusive, it is feasible with available information. For data-rich stock assessments conducted on the U.S. west coast we report approximate coefficients of variation in terminal biomass estimates from assessments based on inversion of the assessment of the model’s Hessian matrix (i.e., the asymptotic standard error). To summarize variation “among” stock assessments, as a proxy for model specification error, we characterize variation among multiple historical assessments of the same stock. Results indicate that for 17 groundfish and coastal pelagic species, the mean coefficient of variation of terminal biomass is 18%. In contrast, the coefficient of variation ascribable to model specification error (i.e., pooled among-assessment variation) is 37%. We show that if a precautionary probability of overfishing equal to 0.40 is adopted by managers, and only model specification error is considered, a 9% reduction in the overfishing catch level is indicated.

Spatial and seasonal relationships between Pacific harbor seals (Phoca vitulina richardii) and their prey, at multiple scales

Knowing where pinnipeds forage is vital to managing and protecting their populations, and for assessing potential interactions with fisheries. We assessed the spatial relationship between the seasonal distribution of Pacific harbor seals (Phoca vitulina richardii) outfitted with satellite transmitters and the seasonal distributions of potential harbor seal prey species in San Francisco Bay, California. Pearson’s correlation coefficients were calculated between the number of harbor seal locations in an area of the San Francisco Bay and the abundance of specific prey species in the same area. The influence of scale on the analyses was assessed by varying the scale of analysis from 1 to 10 km. There was consistency in the prey species targeted by harbor seals year-round, although there were seasonal differences between the most important prey species. The highest correlations between harbor seals and their prey were found for seasonally abundant benthic species, located within about 10 km of the primary haul-out site. Probable foraging habitat for harbor seals was identified, based on areas with high abundances of prey species that were strongly correlated with harbor seal distribution. With comparable local data inputs, this approach has potential application to pinniped management in other areas, and to decisions about the location of marine reserves designed to protect these species.

Monitoring Hawaii’s marine protected areas: examining spatial and temporal trends using a seascape approach

Hawaii’s coastal marine resources have declined dramatically over the past 100 years due to multiple anthropogenic stressors including overfishing, coastal development, pollution, overuse, invasive species and climate change. It is now becoming evident that ecosystem-based management, in the form of marine protected areas (MPAs), is necessary to conserve biodiversity, maintain viable fisheries, and deliver a broad suite of ecosystem services. Over the past four decades, Hawaii has developed a system of MPAs to conserve and replenish marine resources around the state. These Marine Life Conservation Districts (MLCDs) vary in size, habitat quality, and management regimes, providing an excellent opportunity to test hypotheses concerning MPA design and function using multiple discreet sampling units. NOAA/NOS/NCCOS/Center for Coastal Monitoring and Assessment’s Biogeography Branch used digital benthic habitat maps coupled with comprehensive ecological studies between 2002 and 2004 to evaluate the efficacy of all existing MLCDs using a spatially-explicit stratified random sampling design. The results from this work have shown that areas fully protected from fishing had higher fish biomass, larger overall fish size, and higher biodiversity than adjacent areas of similar habitat quality. Other key findings demonstrated that top predators and other important fisheries species were more abundant and larger in the MPAs, illustrating the effectiveness of these closures in conserving these populations. Habitat complexity, protected area size and habitat diversity were the major factors in determining effectiveness among MPAs.