Simulierte Auswirkungen des mehrjährigen Bewirtschaftungsplans für die Dorschfischerei in der westlichen Ostsee und die Möglichkeit einer technischen Alternative

The cod stock in the Western Baltic Sea is assessed to be overfished regarding the definitions of the UN World Summit on Sustainable Development at Johannesburg in 2002. Thus, the European Fisheries Council enforced a multi-annual management plan in 2007. Our medium term simulations over the future 10 years assume similar stock productivity as compared with the past four decades and indicate that the goals of the management plan can be achieved through TAC and consistent effort regulations. Taking account of the uncertainty in the recruitment patterns, the target average fishing mortality of age groups 3 – 6 years of F = 0.6 per year as defined in the management plan is indicated to exceed sustainable levels consistent with high long term yields and low risk of depletion. The stipulated constraint of the annual TAC variations of ±15% will dominate future fisheries management and implies a high recovery potential of the stock through continued reductions in fishing mortality. The scientific assessment of sustainable levels of exploitation and consideration in the plan is strongly advised, taking account of uncertainties attributed to environmental and biological effects. We recommend our study to be complemented with economic impact assessments including effects on by-catch species, which have been disregarded in this study. It is further demonstrated, that the goals of the management plan can alternatively be achieved by mesh size adaptations. An alternative technical option of mesh size increases to realize the required reductions in fishing mortality provides avoidance of discards of undersized fish after a few years by means of improved selectivity, another important element of the Common Fisheries Policy. However, it is emphasized that technical regulations since 1990 failed to affect the by-catch and discards of juvenile cod. In any way, the meaningful implementation of the multiannual management plan through stringent control and enforcement appears critical.

Overfishing, uncertainty, and ocean governance: Lord Perry's question revisited

“Why does overfishing persist in the face of regulation?” The author argues that over fishing,a fundamental cause of the crisis facing our oceans, is the result of the failure of our fishing management agencies (ultimately our politicians and communities) to embrace a small suite of powerful tools (more correctly strategic approaches) which have been developed to account for uncertainty. Broad success in managing fisheries to achieve sustainability goals will only come if these tools are enthusiastically applied. This will not happen until organisational cultures within fishery management agencies undergo a major shift leading to an asset-based biodiversity conservation, rather than resource exploitation, to be placed at the centre of ocean governance.This thesis examines these issues in the context of case studies covering regional, national and provincial (State) fishery management agencies. With the exception of the case study of a regional fishery (the southern ocean krill fishery) all case studies are drawn from Australian experiences. The central recommendation of the thesis is that fishery management agencies, worldwide, should be replaced by biodiversity asset management agencies.

Avoidance of common problems on ponds and lakes.

This report looks at the events that results in fish deaths on ponds and lakes, and how to control and avoid them. Problems include de-oxygenation of the water, algal growth, water temperature, excessive fish stocks, excessive weed growth and excessive zooplankton

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.

Use of genetic data to assess the uncertainty in stock assessments due to the assumed stock structure: the case of albacore (Thunnus alalunga) from the Atlantic Ocean

Stock assessments can be problematic because of uncertainties associated with the data or because of simplified assumptions made when modeling biological processes (Rosenberg and Restrepo, 1995). For example, the common assumption in stock assessments that stocks are homogeneous and discrete (i.e., there is no migration between the stocks) is not necessarily true (Kell et al., 2004a, 2004b).

Beverton and Holt equations: spreadsheet functions and uncertainty

This contribution illustrates how modern spreadsheets aid the calculation and visualization of yield models and how the effects of uncertainties may be incorporated using Monte Carlo simulation. It is argued that analogous approaches can be implemented for other assessment models of simple to medium complexity justifying wider use of spreadsheets in fisheries analysis and training.