The csv data file “SAR_TBB.csv” contains data on habitat characteristics and fishing effort of the Dutch beam trawl fleet by grid cells of 1 minute longitude * 1 minute latitude in the North Sea used to study the changes in trawling impact on the benthic ecosystem due to the transition from conventional beam trawling to pulse trawling. Habitat variables include %sand, %gravel, %mud, bed shear stress (N.m-2) and level 3 EUNIS habitat type. Fishing effort, expressed as the annual swept area ratio (area swept by the gear in km2 / surface area of the grid cell (km2)), is given for the total Dutch beam trawl fleet and for a subset of vessels holding a pulse license (PLH) when fishing with the conventional beam trawl gear (PLH.T.year) or with the innovative pulse trawl (PLH.P.year).
Om visserij in de Natura-2000 gebieden Noordzeekustzone en Vlakte van de Raan zodanig te reguleren, dat zij het behalen van de geformuleerde beleidsdoelen niet in de weg staat, is het VIBEG-akkoord gesloten. Kern van de afspraken vormt een ruimtelijke zonering waarmee wordt bepaald welke visserijtechnieken in welke gebieden wel of niet zijn toegestaan.
term population dynamics of 13 herbivore species in this unique national park in northern Tanzania.While population densities of some species have increased over the past 58 year, losses in megaherbivores (African elephant, black rhinoceros, African buff alo) some 30 years ago led to an overall 40% reduction in herbivore biomass with cascading eff ects on vegetation structure and other animal species.
Marine protected areas (MPAs) are widely used to protect exploited fish species as well as to conserve marine habitats and their biodiversity. They have also become a popular management tool for bottom trawl fisheries, a common fishing technique on continental shelves worldwide. The effects of bottom trawling go far beyond the impact on target species, as trawls also affect other components of the benthic ecosystem and the seabed itself. This means that for bottom trawl fisheries, MPAs can potentially be used not only to conserve target species but also to reduce impact of these side effects of the fishery. However, predicting the protective effects of MPAs is complicated because the side effects of trawling potentially alter the food-web interactions between target and non-target species. These changes in predatory and competitive interactions among fish and benthic invertebrates may have important ramifications for MPAs as tools to manage or mitigate the effects of bottom trawling. Yet, in current theory regarding the functioning of MPAs in relation to bottom trawl fisheries, such predatory and competitive interactions between species are generally not taken into account. In this study, we discuss how food-web interactions that are potentially affected by bottom trawling may alter the effectiveness of MPAs to protect (1) biodiversity and marine habitats, (2) fish populations, (3) fisheries yield, and (4) trophic structure of the community. We make the case that in order to be applicable for bottom trawl fisheries, guidelines for the implementation of MPAs must consider their potential food-web effects, at the risk of failing management.
The Acceptable Level of Impact (ALI) methodology defines acceptable limits for the predicted population effects of mortality imposed by offshore wind farms (OWFs) for marine birds. These population effects are quantified using stochastic population models tailored for specific seabird species. The ALI is defined as: 'The probability of a population decline of X% or more, 30 years after the impact, cannot exceed Y'. In this definition, the X threshold determines the reduction in population abundance due to OWFs that is considered acceptable, evaluated 30 years after the onset of the impact. The Y threshold of the ALI is derived from a threshold value for the 'causality probability' (PC). PC is the probability that a violation of X is caused by the impact from OWFs, instead of being caused by variability or uncertainty inherent to predictions of future population abundance. The ALI methodology was reviewed in November 2021 – January 2022. Reviewers concluded that the approach and assumptions of the proposed ALI methodology were a considerable improvement in relation to existing impact-evaluation frameworks (ORNIS, PBR). However, reviewers also raised concerns about the legal tenability and definition of the causality level PC. Several points put forward in the reviews were addressed within the current report, namely a derivation of the causality threshold PC and results of a sensitivity analysis of the ALI methodology, which contained several components. First, an analysis of the effect of uncertainty on the outcome of the ALI was performed. This analysis was done by: 1) changing the way in which parameters of the population model were sampled to simulate year-to-year variation in demographic rates and, 2) changing the standard deviation of the parameters of the population model. Second, the effect of changing the X threshold value on the outcome of the ALI was evaluated. Lastly, the effect of time-varying, as opposed to constant, mortality levels on the outcome of the ALI was explored. We also address concerns about the definition of PC. We derive PC from conditional probabilities. This derivation shows that PC in itself is correctly defined, and is consistently drawn from other commonly used risk measures, such as the 'attributable fraction among the exposed' and the 'relative risk ratio.' The sensitivity analysis reveals that sampling population parameters once at the start of each simulation (initial sampling) leads to considerable more variation in predicted population abundance than sampling population parameters each year (annual sampling). More variation, resulting in more uncertainty of the population projection leads to an increased probability of an X threshold violation in the scenario without OWF impact. In addition, a more strict X threshold also results in an increased probability of an X threshold violation in the scenario without OWF impact. The sensitivity analysis reveals that in the current framework, with the Y threshold being dependent on the causality threshold PT and the probability of violation of the X threshold in the unimpacted scenario, a more strict X threshold leads to a less strict Y threshold, which is considered undesirable. This relationship stems from the use of the causality measure PC, which attempts to correct for false positive outcomes (threshold violation without impact) that are caused by variation (environmental stochasticity) or uncertainty. In principal, the relationship between X and Y can be accounted for in the choice of X and the threshold value for the causal probability, from which Y is derived. However, this would further complicate the methodology and create a potential problem in the application of the framework, because correctly choosing X and Y values would require a thorough methodological understanding of the framework. The sensitivity analysis also showed that the outcome of the ALI was not affected when using time-varying, as opposed to constant, mortality levels. An essential property of any framework is that it is fit for purpose. This includes that it can be applied without risk of accidental misuse by the end users. This is not the case for the current framework, and we therefore strongly advise to further develop the current ALI methodology. We recommend to revise the methodology to increase its simplicity and avoid use of the causality measure PC, which is at the root of the current problem.
found that years with regional conditions predicted by continued climate change showed a loss of diversity in both microclimate and phenological events, with a more rapid advancement in bud break occurring at higher elevation sites.
Abstract Density dependence is likely to act as a regulatory mechanism in fish stocks that are recovering from overfishing. In general, density dependence in fish stocks is assumed to only occur in reproduction and early life stages and is therefore usually modelled as a stock‐recruitment relationship. Recent research shows that density dependence can also reduce individual growth in body size later in life. In this study, we show how optimal fishing effort changes with the strength of density dependence in individual growth for four stocks of North Sea flatfish species. Using size‐structured population models we show that density dependence arises due to a mechanistic link between the resource availability and life history processes at the individual level. We furthermore show that the stock response to harvesting is either driven by changes in individual reproduction when density dependence in individual growth is weak or by changes in individual growth rate when individual growth is strongly affected by density dependence. These two types or regimes are separated by a sudden shift in dynamics. It is therefore of great importance to account for density dependence in growth when managing fish stocks.
Abstract Dickey-Collas, M., Engelhard, G. H., Rindorf, A., Raab, K., Smout, S., Aarts, G., van Deurs, M., Brunel, T., Hoff, A., Lauerburg R. A. M., Garthe, S., Haste Andersen, K., Scott, F., van Kooten, T., Beare, D., and Peck, M. A. Ecosystem-based management objectives for the North Sea: riding the forage fish rollercoaster. – ICES Journal of Marine Science, 71: . The North Sea provides a useful model for considering forage fish (FF) within ecosystem-based management as it has a complex assemblage of FF species. This paper is designed to encourage further debate and dialogue between stakeholders about management objectives. Changing the management of fisheries on FF will have economic consequences for all fleets in the North Sea. The predators that are vulnerable to the depletion of FF are Sandwich terns, great skua and common guillemots, and to a lesser extent, marine mammals. Comparative evaluations of management strategies are required to consider whether maintaining the reserves of prey biomass or a more integral approach of monitoring mortality rates across the trophic system is more robust under the ecosystem approach. In terms of trophic energy transfer, stability, and resilience of the ecosystem, FF should be considered as both a sized-based pool of biomass and as species components of the system by managers and modellers. Policy developers should not consider the knowledge base robust enough to embark on major projects of ecosystem engineering. Management plans appear able to maintain sustainable exploitation in the short term. Changes in the productivity of FF populations are inevitable so management should remain responsive and adaptive.
The majority of taxa grow significantly during life history, which often leads to individuals of the same species having different ecological roles, depending on their size or life stage. One aspect of life history that changes during ontogeny is mortality. When individual growth and development are resource dependent, changes in mortality can affect the outcome of size-dependent intraspecific resource competition, in turn affecting both life history and population dynamics. We study the outcome of varying size-dependent mortality on two life-history types, one that feeds on the same resource throughout life history and another that can alternatively cannibalize smaller conspecifics. Compensatory responses in the life history dampen the effect of certain types of size-dependent mortality, while other types of mortality lead to dramatic changes in life history and population dynamics, including population (de-)stabilization, and the growth of cannibalistic giants. These responses differ strongly among the two life-history types. Our analysis provides a mechanistic understanding of the population-level effects that come about through the interaction between individual growth and size-dependent mortality, mediated by resource dependence in individual vital rates.
