Using a genetic algorithm to optimize a data-limited catch rule

Many data-limited fish stocks worldwide require management advice. Simple empirical management procedures have been used to manage data-limited fisheries but do not necessarily ensure compliance with maximum sustainable yield objectives and precautionary principles. Genetic algorithms are efficient optimization procedures for which the objectives are formalized as a fitness function. This optimization can be included when testing management procedures in a management strategy evaluation. This study explored the application of a genetic algorithm to an empirical catch rule and found that this approach could substantially improve the performance of the catch rule. The optimized parameterization and the magnitude of the improvement were dependent on the specific stock, stock status, and definition of the fitness function. The genetic algorithm proved to be an efficient and automated method for tuning the catch rule and removed the need for manual intervention during the optimization process. Therefore, we conclude that the approach could also be applied to other management procedures, case-specific tuning, and even data-rich stocks. Finally, we recommend the phasing out of the current generic ICES “2 over 3” advice rule in favour of case-specific catch rules of the form tested here, although we caution that neither works well for fast-growing stocks

Development of probabilistic models for quantitative pathway analysis of plant pest introduction for the EU territory

This report demonstrates a probabilistic quantitative pathway analysis model that can be used in risk assessment for plant pest introduction into EU territory on a range of edible commodities (apples, oranges, stone fruits and wheat). Two types of model were developed: a general commodity model that simulates distribution of an imported infested/infected commodity to and within the EU from source countries by month; and a consignment model that simulates the movement and distribution of individual consignments from source countries to destinations in the EU. The general pathway model has two modules. Module 1 is a trade pathway model, with a Eurostat database of five years of monthly trade volumes for each specific commodity into the EU28 from all source countries and territories. Infestation levels based on interception records, commercial quality standards or other information determine volume of infested commodity entering and transhipped within the EU. Module 2 allocates commodity volumes to processing, retail use and waste streams and overlays the distribution onto EU NUTS2 regions based on population densities and processing unit locations. Transfer potential to domestic host crops is a function of distribution of imported infested product and area of domestic production in NUTS2 regions, pest dispersal potential, and phenology of susceptibility in domestic crops. The consignment model covers the several routes on supply chains for processing and retail use. The output of the general pathway model is a distribution of estimated volumes of infested produce by NUTS2 region across the EU28, by month or annually; this is then related to the accessible susceptible domestic crop. Risk is expressed as a potential volume of infested fruit in potential contact with an area of susceptible domestic host crop. The output of the consignment model is a volume of infested produce retained at each stage along the specific consignment trade chain

Validation of a geographic weighted regression analysis as a tool for area-wide integrated pest management programs for Ceratitis capitata Wiedemann (Diptera: Tephritidae) on Terceira Island, Azores

Extrapolation from quantitative sampling to the surrounding areas is an essential feature of many aspects of real world applications in pest management decision-making. However, these decisions are only as good as the accuracy of the methods that provided the information. The problem of estimating Mediterranean fruit fly population densities from trap grids is a specific case. The efficiency of three methods to estimate fruit flies trapped per day values for non-sampled areas in Terceira Island is evaluated, the inverse distance weighted, ordinary Kriging and the geographic weighted regression (GWR). Each method has its own specificities and merits. The results demonstrate that the GWR method is capable of estimating hotspots for the next season and can be used to identify ecological corridors over a non-sampled area. The high spatial heterogeneity and topographical conditions present on Terceira Island may explain why a more mathematically complex method is more reliable than simpler methods for use in possible future wide-area control program for medfly

Plasmodium falciparum (Haemosporodia: Plasmodiidae) and O'nyong-nyong virus development in a transgenic Anopheles gambiae (Diptera: Culicidae) strain

Transgenic Anopheles gambiae Giles (Diptera: Culicidae) mosquitoes have been developed that confer sexual sterility on males that carry a transgene encoding a protein which cuts ribosomal DNA. A relevant risk concern with transgenic mosquitoes is that their capacity to transmit known pathogens could be greater than the unmodified form. In this study, the ability to develop two human pathogens in these transgenic mosquitoes carrying a homing endonuclease which is expressed in the testes was compared with its nontransgenic siblings. Infections were performed with Plasmodium falciparum (Welch) and o'nyong-nyong virus (ONNV) and the results between the transgenic and nontransgenic sibling females were compared. There was no difference observed with ONNV isolate SG650 in intrathoracic infections or the 50% oral infectious dose measured at 14 d postinfection or in mean body titers. Some significant differences were observed for leg titers at the medium and highest doses for those individuals in which virus titer could be detected. No consistent difference was observed between the transgenic and nontransgenic comparator females in their ability to develop P. falciparum NF54 strain parasites. This particular transgene caused no significant effect in the ability of mosquitoes to become infected by these two pathogens in this genetic background. These results are discussed in the context of risk to human health if these transgenic individuals were present in the environment

A Regional Decision Support Scheme for Pest Risk Analysis in Southeast Asia

A key justification to support plant health regulations is the ability of quarantine services to conduct pest risk analyses (PRA). Despite the supranational nature of biological invasions and the close proximity and connectivity of Southeast Asian countries, PRAs are conducted at the national level. Furthermore, some countries have limited experience in the development of PRAs, which may result in inadequate phytosanitary responses that put their plant resources at risk to pests vectored via international trade. We review existing decision support schemes for PRAs and, following international standards for phytosanitary measures, propose new methods that adapt existing practices to suit the unique characteristics of Southeast Asia. Using a formal written expert elicitation survey, a panel of regional scientific experts was asked to identify and rate unique traits of Southeast Asia with respect to PRA. Subsequently, an expert elicitation workshop with plant protection officials was conducted to verify the potential applicability of the developed methods. Rich biodiversity, shortage of trained personnel, social vulnerability, tropical climate, agriculture-dependent economies, high rates of land-use change, and difficulties in implementing risk management options were identified as challenging Southeast Asian traits. The developed methods emphasize local Southeast Asian conditions and could help support authorities responsible for carrying out PRAs within the region. These methods could also facilitate the creation of other PRA schemes in low- and middle-income tropical countries

Exploring a relative harvest rate strategy for moderately data-limited fisheries management

Moderately data-limited fisheries can be managed with simple empirical management procedures without analytical stock assessments. Often, control rules adjust advised catches by the trend of an abundance index. We explored an alternative approach where a relative harvest rate, defined by the catch relative to a biomass index, is used and the target level derived from analysing historical catch length data. This harvest rate rule was tested generically with management strategy evaluation. A genetic algorithm was deployed as an optimisation procedure to tune the parameters of the control rule to meet maximum sustainable yield and precautionary management objectives. Results indicated that this method could outperform trend-based strategies, particularly when optimised, achieving higher long-term yields while remaining precautionary. However, optimum harvest rate levels can be narrow and challenging to find because they depend on historical exploitation and life history characteristics. Misspecification of target levels can have a detrimental impact on management. Nevertheless, harvest rates appear to be a suitable management option for moderately data-limited resources, and their application has modest data requirements. Harvest rate strategies are especially suitable for stocks for which case-specific analyses can be conducted

Risk equivalence in data-limited and data-rich fisheries management: An example based on the ICES advice framework

Fisheries management needs to ensure that resources are exploited sustainably, and the risk of depletion is at an acceptable level. However, often uncertainty about resource dynamics exists, and data availability may differ substantially between fish stocks. This situation can be addressed through tiered systems, where tiers represent different data limitations, and tier-specific stock assessment methods are defined, aiming for risk equivalence across tiers. As case studies, we selected stocks of European plaice, Atlantic cod and Atlantic herring, where advice is provided by the International Council for the Exploration of the Sea (ICES). We conducted a closed-loop simulation to compare risk equivalence between the data-rich ICES MSY rule, based on a quantitative stock assessment, and the revised data-limited empirical management procedures of the ICES advice framework. The simulations indicated that the data-limited approaches were precautionary and did not lead to a higher risk of depletion than the data-rich approach. Although the catch based on generic data-limited approaches was lower, stock-specific optimisation improved management performance with catch levels comparable with the data-rich approach. Furthermore, the simulation indicated the ICES MSY rule can fail to meet management objectives due to increased depletion risk when management reference points are set suboptimally. We conclude that the recent revisions of the ICES system explicitly account for risk equivalence for data-limited fisheries management and are a major step forward. Finally, we advocate further consideration of simple empirical management procedures irrespective of data limitations due to their ability to meet fisheries management objectives with greater simplicity

Higher Loop Spin Field Correlators in D=4 Superstring Theory

We develop calculational tools to determine higher loop superstring correlators involving massless fermionic and spin fields in four space time dimensions. These correlation functions are basic ingredients for the calculation of loop amplitudes involving both bosons and fermions in D=4 heterotic and superstring theories. To obtain the full amplitudes in Lorentz covariant form the loop correlators of fermionic and spin fields have to be expressed in terms of SO(1,3) tensors. This is one of the main achievements in this work.Comment: 59 pages, 1 figure; v2: final version published in JHE

The economic value of environmental data: a notional insurance scheme for the European anchovy

Anchovy population dynamics in the Gulf of Cádiz are governed by environmental processes. Sea surface temperature, intense easterly winds, and discharges from the Guadalquivir River have been identified as key factors determining early life stage mortality in this anchovy stock. We have constructed an environment-based recruitment model that simulates the abundance of juveniles under alternative parameters representing plausible biological hypotheses. We are able to evaluate how modelling environment-based recruitment can affect stock assessment and how responding to environmental information can benefit fishery management to allow greater average catch levels through the application of harvest control rules (HCRs) based on environmental conditions. While the environment-based rules generally increase allowable catch levels the variance in catch levels also increases, detracting from the improved value based only on average yield. In addition to changes in revenue, the probability of stock collapse is also reduced by using environmental factors in HCRs. To assess the value of these management systems we simulate a notional insurance scheme, which applies a value to both average yields and uncertainty. The value of the information-driven rules can be determined by comparing the relevant premiums payable for equal levels of insurance cover on revenue within each specific management regime. We demonstrate the net value of incorporating environmental factors in the management of anchovies in the Gulf of Cádiz despite the increased variability in revenue. This could be an effective method to describe outcomes for both commercial fisheries and ecosystem management policies, and as a guide to management of other species whose dynamics are predictable based on in-season observations

Holographic View on Quantum Correlations and Mutual Information between Disjoint Blocks of a Quantum Critical System

In (d+1) dimensional Multiscale Entanglement Renormalization Ansatz (MERA) networks, tensors are connected so as to reproduce the discrete, (d + 2) holographic geometry of Anti de Sitter space (AdSd+2) with the original system lying at the boundary. We analyze the MERA renormalization flow that arises when computing the quantum correlations between two disjoint blocks of a quantum critical system, to show that the structure of the causal cones characteristic of MERA, requires a transition between two different regimes attainable by changing the ratio between the size and the separation of the two disjoint blocks. We argue that this transition in the MERA causal developments of the blocks may be easily accounted by an AdSd+2 black hole geometry when the mutual information is computed using the Ryu-Takayanagi formula. As an explicit example, we use a BTZ AdS3 black hole to compute the MI and the quantum correlations between two disjoint intervals of a one dimensional boundary critical system. Our results for this low dimensional system not only show the existence of a phase transition emerging when the conformal four point ratio reaches a critical value but also provide an intuitive entropic argument accounting for the source of this instability. We discuss the robustness of this transition when finite temperature and finite size effects are taken into account.Comment: 21 pages, 5 figures. Abstract and Figure 1 has been modified. Minor modifications in Section 1 and Section