Is spawning stock biomass a robust proxy for reproductive potential?

Reference points based on fishing mortality (F) and spawning stock biomass (SSB) are a requirement of many fisheries management frameworks. SSB is assumed to be a proxy for stock reproductive potential (SRP). Limit reference points based on SSB are used to indicate the level of biomass below which productivity is affected. SSB fails to account for changes in fecundity, egg viability and sex ratio, and it has been argued that total egg production (TEP) provides a better reflection of SRP. We explore how accounting for TEP impacts limit reference points and evidence for a relationship between stock and recruit. Time series of SSB and TEP are compared for three North Sea stocks: cod (Gadus morhua), herring (Clupea harengus) and plaice (Pleuronectes platessa). Dynamics based on TEP are different from those based on SSB for cod and plaice, but the stock–recruit relationships were not ‘improved’ using TEP. Shifts in productivity (spawner per recruit) occur in all three time series and SSB underestimated uncertainty. Yet again, it was shown that assumptions of stationarity about fish population productivity are incorrect. We argue that the use of TEP does improve the realism in our understanding of stock dynamics, and demographically, more complex management strategy evaluation is required to develop management procedures that are robust to uncertainty and integrate F and the demographic health of a stock. Empirical feedback control systems based on fisheries independent indices including surveys of eggs, larvae, recruits, juveniles or spawning adults should be evaluated and compared to traditional approaches.     

Improving estimates of population status and trend with superensemble models

Fishery managers must often reconcile conflicting estimates of population status and trend. Superensemble models, commonly used in climate and weather forecasting, may provide an effective solution. This approach uses predictions from multiple models as covariates in an additional “superensemble” model fitted to known data. We evaluated the potential for ensemble averages and superensemble models (ensemble methods) to improve estimates of population status and trend for fisheries. We fit four widely applicable data‐limited models that estimate stock biomass relative to equilibrium biomass at maximum sustainable yield (B/B_MSY). We combined these estimates of recent fishery status and trends in B/B_MSY with four ensemble methods: an ensemble average and three superensembles (a linear model, a random forest and a boosted regression tree). We trained our superensembles on 5,760 simulated stocks and tested them with cross‐validation and against a global database of 249 stock assessments. Ensemble methods substantially improved estimates of population status and trend. Random forest and boosted regression trees performed the best at estimating population status: inaccuracy (median absolute proportional error) decreased from 0.42 – 0.56 to 0.32 – 0.33, rank‐order correlation between predicted and true status improved from 0.02 – 0.32 to 0.44 – 0.48 and bias (median proportional error) declined from ?0.22 – 0.31 to ?0.12 – 0.03. We found similar improvements when predicting trend and when applying the simulation‐trained superensembles to catch data for global fish stocks. Superensembles can optimally leverage multiple model predictions; however, they must be tested, formed from a diverse set of accurate models and built on a data set representative of the populations to which they are applied.     

Durable resistance to the wheat rusts: integrating systems biology and traditional phenotype-based research methods to guide the deployment of resistance genes

Genes which confer partial resistance to the rusts in wheat figure prominently in discussions of potential durable resistance strategies. The positional cloning of the first of these genes, Lr34/Yr18 and Yr36, has revealed different protein structures, suggesting that the category of partial resistance genes, as defined by phenotype, likely groups together suites of functionally heterogenous genes. With the number of mapped partial rust resistance genes increasing rapidly as a result of ongoing advances in marker and sequencing technologies, breeding programs needing to select and prioritize genes for deployment confront a fundamental question: which genes or gene combinations are more likely to provide durable protection against these evolving pathogens? We argue that a refined classification of partial rust resistance genes is required to start answering this question, one based not merely on disease phenotype but also on gene cloning, molecular functional characterization, and interactions with other host and pathogen proteins. Combined with accurate and detailed disease phenotyping and standard genetic studies, an integrated wheat-rust interactome promises to provide the basis for a functional classification of partial resistance genes and thus a conceptual framework for their rational deployment.     

Retention of eucalyptus harvest residues reduces soil compaction caused by deep subsoiling

Eucalyptus harvesting, forwarding and soil till-age operations are among the main causes for compaction of forest soils, with potential impacts on productivity....     

Selectivity metrics for fisheries management and advice

Fisheries management typically aims at controlling exploitation rate (e.g., Fbar) to ensure sustainable levels of stock size in accordance with established reference points (e.g., F_MSY, B_MSY). Population selectivity (“selectivity” hereafter), that is the distribution of fishing mortality over the different demographic components of an exploited fish stock, is also important because it affects both Maximum Sustainable Yield (MSY) and F_MSY, as well as stock resilience to overfishing. The development of an appropriate metric could make selectivity operational as an additional lever for fisheries managers to achieve desirable outcomes. Additionally, such a selectivity metric could inform managers on the uptake by fleets and effects on stocks of various technical measures. Here, we introduce three criteria for selectivity metrics: (a) sensitivity to selectivity changes, (b) robustness to recruitment variability and (c) robustness to changes in Fbar. Subsequently, we test a range of different selectivity metrics against these three criteria to identify the optimal metric. First, we simulate changes in selectivity, recruitment and Fbar on a virtual fish stock to study the metrics under controlled conditions. We then apply two shortlisted selectivity metrics to six European fish stocks with a known history of technical measures to explore the metrics’ response in real‐world situations. This process identified the ratio of F of the first recruited age–class to Fbar (Frec/Fbar) as an informative selectivity metric for fisheries management and advice.     

Operating model design in tuna Regional Fishery Management Organizations: Current practice,issues and implications

The five Regional Fishery Management Organizations dedicated to tunas (tRFMOs) are all either developing or implementing Management Strategy Evaluations (MSEs) to provide advice for the stocks under their competencies. Providing a comparative overview will help tRFMOs to learn from one another and to collaborate on common solutions and may also help to more clearly define the challenges of building decision support tools in contexts of large scientific uncertainty and where management requires cooperation across multiple stakeholders characterized by unequal power and divergent interests. For example, our overview showed that in most cases, a grid‐based design with an emphasis on structural uncertainty has been adopted. However, uncertainties such as sampling errors and non‐stationarity of important ecological processes, which are of potentially equal significance for demonstrating robustness of management procedures, were not considered. This paper identifies key issues for operating model (OM) design that challenges the tRFMOs, compares how these challenges are being met, summarizes what lessons have been learned and suggests a way forward. Although the current approach of using assessment models as the basis for OM design is a reasonable starting point, improvements should be made to the conditioning of OMs, especially with respect to enabling the inclusion of other important processes and uncertainties that are difficult to account for in stock assessments but that can crucially affect the robustness of advice. Attempts should also be made to improve documentation and communication of uncertainties that are included and those that are excluded from consideration in the process.     

Effort rights‐based management

Effort rights‐based fisheries management (RBM) is less widely used than catch rights, whether for groups or individuals. Because RBM on catch or effort necessarily requires a total allowable catch (TAC) or total allowable effort (TAE), RBM is discussed in conjunction with issues in assessing fish populations and providing TACs or TAEs. Both approaches have advantages and disadvantages, and there are trade‐offs between the two approaches. In a narrow economic sense, catch rights are superior because of the type of incentives created, but once the costs of research to improve stock assessments and the associated risks of determining the TAC and costs of monitoring, control, surveillance and enforcement are taken into consideration, the choice between catch or effort RBM becomes more complex and less clear. The results will be case specific. Hybrid systems based on both catch and effort are increasingly employed to manage marine fisheries to capture the advantages of both approaches. In hybrid systems, catch or effort RBM dominates and controls on the other supplements. RBM using either catch or effort by itself addresses only the target species stock externality and not the remaining externalities associated with by‐catch and the ecosystem.