The consequences of balanced harvesting of fish communities

Balanced harvesting, where species or individuals are exploited in accordance with their productivity, has been proposed as a way to minimize the effects of fishing on marine fish communities and ecosystems. This calls for a thorough examination of the consequences balanced harvesting has on fish community structure and yield. We use a size- and trait-based model that resolves individual interactions through competition and predation to compare balanced harvesting with traditional selective harvesting, which protects juvenile fish from fishing. Four different exploitation patterns, generated by combining selective or unselective harvesting with balanced or unbalanced fishing, are compared. We find that unselective balanced fishing, where individuals are exploited in proportion to their productivity, produces a slightly larger total maximum sustainable yield than the other exploitation patterns and, for a given yield, the least change in the relative biomass composition of the fish community. Because fishing reduces competition, predation and cannibalism within the community, the total maximum sustainable yield is achieved at high exploitation rates. The yield from unselective balanced fishing is dominated by small individuals, whereas selective fishing produces a much higher proportion of large individuals in the yield. Although unselective balanced fishing is predicted to produce the highest total maximum sustainable yield and the lowest impact on trophic structure, it is effectively a fishery predominantly targeting small forage fish

Limited impact of big fish mothers for population replenishment

A recent meta-analysis by Barneche et al. (Science 360(6389): 642) show that fish reproductive output scales hypergeometrically with female weight. This result challenges the common assumption that reproductive output is proportional to weight. The implication made is that current theory and practice severely underestimates the importance of larger females for population replenishment. Their example for cod shows that current practice makes an error of 149%. By properly accounting for fish demography we show that the error is maximally on the order of 10%, and in most other fish stocks likely much less.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Integrating Life Cycle and Impact Assessments to Map Food's Cumulative Environmental Footprint

Producing food exerts pressures on the environment. Understanding the location and magnitude of food production is key to reducing the impacts of these pressures on nature and people. In this Perspective, Kuempel et al. outline an approach for integrating life cycle assessment and cumulative impact mapping data and methodologies to map the cumulative environmental pressure of food systems. The approach enables quantification of current and potential future environmental pressures, which are needed to reduce the net impact of feeding humanity. © 2020 The AuthorsFeeding a growing, increasingly affluent population while limiting environmental pressures of food production is a central challenge for society. Understanding the location and magnitude of food production is key to addressing this challenge because pressures vary substantially across food production types. Applying data and models from life cycle assessment with the methodologies for mapping cumulative environmental impacts of human activities (hereafter cumulative impact mapping) provides a powerful approach to spatially map the cumulative environmental pressure of food production in a way that is consistent and comprehensive across food types. However, these methodologies have yet to be combined. By synthesizing life cycle assessment and cumulative impact mapping methodologies, we provide guidance for comprehensively and cumulatively mapping the environmental pressures (e.g., greenhouse gas emissions, spatial occupancy, and freshwater use) associated with food production systems. This spatial approach enables quantification of current and potential future environmental pressures, which is needed for decision makers to create more sustainable food policies and practices. © 2020 The Author

Workshop to scope and preselect indicators for criterion D3C3 under MSFD decision (EU) 2017/848 (WKD3C3SCOPE)

The workshop to scope and preselect indicators for Descriptor 3 criterion 3 under MSFD Commission Decision (EU) 2017/848 (WKD3C3SCOPE) provided a platform for experts from the EU member states and relevant regional bodies to meet and support development and progress the assessment methodology, based on a request by the EC (DGENV). WKD3C3SCOPE is the first of a series of three workshops (WKD3C3THRESHOLDS and WKSIMULD3) to provide guidance in relation to operational indicators for MSFD D3C3. The workshop was organized as a series of presentations with intermittent group discussions. On the first day of the workshop the participants discussed what defines a ‘healthy population structure’ for species with different life history traits (ToR a). During the following days, the group discussed and identified relevant D3C3 indicators (ToR b) and developed criteria to select among the identified D3C3 indicators to allow further testing and setting of thresholds at WKD3C3THRESHOLDS (ToR c). The participants found that overall, healthy fish stocks are characterized by high productivity, wide age and size structuring in the population, and the ability to quickly recover from disturbances. The groups noted that environmental factors, along with stock biomass and fishing pressure, influence the productivity and health of a stock, with environment playing a particularly large role in the recruitment of short-lived stocks. It was suggested that the age structure of a stock might be more relevant for evaluating the health of long-lived stocks. However, it was acknowledged that not all stocks have sufficient data to evaluate all proposed indicators, and a single indicator is unlikely to suffice for all stocks. Data availability, species- specific factors and regional or sub-regional variation are thus also important considerations. In relation to ToR b, the participants presented their work on potential indicators including: recruitment time-series, proportion of fish larger than the mean size of first sexual maturation, F rec/Fbar, length distribution L 90, relative proportion of old fish above A 90, indicators of spawner quality, and SSB/R. A discussion on pros/cons, benefits to the population of high or low indicator values, benefits supported by empirical evidence, applicability to data-poor stocks and benefits supported by simulation/theoretical considerations followed the presentations. Finally, in relation to ToR c, the difficulty emerged in ranking the indicators alone without considering the data used to estimate them and a new set of evaluation criteria for use in WKD3C3THRESHOLDS were defined. Based on the outputs of the meeting a list of indicators to be further evaluated has been drafted, which also emphasizes the stocks for which studies have empirically demonstrated effects on productivity. In addition to the listed indicators, indicators of genetic diversity and proportion of fish with parasite infestation were mentioned but to the knowledge of the participants, widespread data for these are currently not publicly available.info:eu-repo/semantics/publishedVersio

Joint ICES-SEAwise workshop to quality assure methods to incorporate environmental factors and quantifying ecological considerations in management strategy evaluation tools (WKEcoMSE)

The EU project SEAwise (https://seawiseproject.org/) endeavours to enhance existing multi-stock multi-species Management Strategy Evaluation (MSE) models so that they can be used to define and evaluate fisheries management strategies that address broad Ecosystem-Based Fisheries Management (EBFM) objectives, including in particular identifying Harvest Control Rules (HCRs) that are robust to changes in productivity. The WKEcoMSE workshop was held to: (1) benchmark the approaches used or developed in the project to develop robust and consistent environment-productivity relationships for commercial stocks across selected case studies and integrate them in MSE models used by the SEAwise project and by ICES; (2) to provide context for those approaches within the general field of “environment-enriched” MSEs; and (3) to draw from the participants collective experience some general guidelines about the integration of environmental impacts on stock productivity in MSE tools. 23 presentations were given, both about the work carried out within SEAwise but also by international colleagues working toward similar objectives, and various topics were discussed over eight sessions designed to accommodate participants spread across Europe and Northern America. “Good practices” to incorporate environmental considerations in MSE modelling were then drafted collectively and have been summarized in the panels below. These rely on the experiences of the WKEcoMSE participants and are not exhaustive.info:eu-repo/semantics/publishedVersio

Comparing model predictions for ecosystem-based management

Ecosystem modeling is becoming an integral part of fisheries management, but there is a need to identify differences between predictions derived from models employed for scientific and management purposes. Here, we compared two models: a biomass-based food-web model (Ecopath with Ecosim (EwE)) and a size-structured fish community model. The models were compared with respect to predicted ecological consequences of fishing to identify commonalities and differences in model predictions for the California Current fish community. We compared the models regarding direct and indirect responses to fishing on one or more species. The size-based model predicted a higher fishing mortality needed to reach maximum sustainable yield than EwE for most species. The size-based model also predicted stronger top-down effects of predator removals than EwE. In contrast, EwE predicted stronger bottom-up effects of forage fisheries removal. In both cases, the differences are due to the presumed degree of trophic overlap between juveniles of large-bodied fish and adult stages of forage fish. These differences highlight how each model’s emphasis on distinct details of ecological processes affects its predictions, underscoring the importance of incorporating knowledge of model assumptions and limitation, possibly through using model ensembles, when providing model-based scientific advice to policy makers.</jats:p