Evaluating Strategies for Managing Anthropogenic Mortality on Marine Mammals: An R Implementation With the Package RLA

Bycatch, the undesirable and non-intentional catch of non-target species in marine fisheries, is one of the main causes of mortality of marine mammals worldwide. When quantitative conservation objectives and management goals are clearly defined, computer-based procedures can be used to explore likely population dynamics under different management scenarios and estimate the levels of anthropogenic removals, including bycatch, that marine mammal populations may withstand. Two control rules for setting removal limits are the Potential Biological Removal (PBR) established under the US Marine Mammal Protection Act and the Removals Limit Algorithm (RLA) inspired from the Catch Limit Algorithm (CLA) developed under the Revised Management Procedure of the International Whaling Commission. The PBR and RLA control rules were tested in a Management Strategy Evaluation (MSE) framework. A key feature of PBR and RLA is to ensure conservation objectives are met in the face of the multiple uncertainties or biases that plague real-world data on marine mammals. We built a package named RLA in the R software to carry out MSE of control rules to set removal limits in marine mammal conservation. The package functionalities are illustrated by two case studies carried out under the auspices of the Oslo and Paris convention (OSPAR) (the Convention for the Protection of the Marine Environment of the North-East Atlantic) Marine Mammal Expert Group (OMMEG) in the context of the EU Marine Strategy Framework Directive. The first case study sought to tune the PBR control rule to the conservation objective of restoring, with a probability of 0.8, a cetacean population to 80% of carrying capacity after 100 years. The second case study sought to further develop a RLA to set removals limit on harbor porpoises in the North Sea with the same conservation objective as in the first case study. Estimation of the removals limit under the RLA control rule was carried out within the Bayesian paradigm. Outputs from the functions implemented in the package RLA allows the assessment of user-defined performance metrics, such as time to reach a given fraction of carrying capacity under a given level of removals compared to the time needed given no removals.

Stabilization of a class of underactuated Euler Lagrange system using an approximate model

The energy shaping method, Controlled Lagrangian, is a well-known approach to stabilize the underactuated Euler Lagrange (EL) systems. In this approach, to construct a control rule, some nonlinear and nonhomogeneous partial differential equations (PDEs), which are called matching conditions, must be solved. In this paper, a method is proposed to obtain an approximate solution of these matching conditions for a class of underactuated EL systems. To develop this method, the potential energy matching condition is transformed to a set of linear PDEs using an approximation of inertia matrices. Hence, the assignable potential energy function and the controlled inertia matrix both are constructed as a common solution of these PDEs. Subsequently, the gyroscopic and dissipative forces are determined as the solution for kinetic energy matching condition. Conclusively, the control rule is constructed by adding energy shaping rule and additional dissipation injection to provide asymptotic stability. The stability analysis of the closed-loop system which used the control rule derived with the proposed method is also provided. To demonstrate the success of the proposed method, the stability problem of the inverted pendulum on a cart is considered.

Comparing a suite of surplus-production-based stock status identification approaches and management procedures

Different approaches have been used to identify fishery stock status when only biomass and catch data are available. However, the performance of the approaches may be affected by the uncertainties derived from different sources (e.g., model misspecification, stock productivity changing, observation error). Here, we propose that the observed biomass associated with the highest calculated surplus production can be used as an indicator (Bhighest_S) to identify stock status. We develop a management procedure (MP) atop a widely used method (i.e., Gcontrol) by incorporating Bhighest_S in the harvest control rule. Two simulations are conducted to compare the stock status identification approaches and corresponding MPs. Using Bhighest_S to identify stock status performs better than surplus production modeling approaches in simulated regime shift scenarios. Compared with the old version of Gcontrol, incorporating Bhighest_S or estimated BMSY in the harvest control rule provides more stable and higher yields. This study contributes to the development and evaluation of indicator-based stock status identification approaches and MPs that only require biomass and catch data.

Optimal shape of the harvest control rule for different fishery management objectives

To determine the optimal shape of the harvest control rule (HCR) achieving common fisheries management objectives (maximizing the average catch, reducing the deviation of yields, and avoiding stock collapse) and ensure robustness to observation errors, we estimate the optimal values of biological reference points (BRPs) composing the HCR. While traditional HCRs usually consist of three BRPs based on the fishing mortality coefficient (F3-HCR), we introduce an alternative HCR defined by 21 BRPs based on the catch levels (C21-HCR) to cover various possible shapes of HCR including smooth ones. We compare the shape and the performance between the optimal C21-HCR and the optimal F3-HCR and conclude that the optimal HCR can be composed of the gradual combination of the basic strategies: the constant escapement strategy, the constant harvest rate (CHR) strategy, and the constant catch strategy. However, the current F3-HCR does not necessarily allow this combination and generally returns lower performance levels than the optimal C21-HCR (since the basic strategy is confined to CHR) excluding the range of low biomass. This result will provide a clear perspective to improve HCR according to the magnitude of assessment errors and to compromise multiple fisheries management objectives when various stakeholders are involved.

Estimation of the Efficiency Indices for Operating the Vertical Transportation Systems

Various lifts’ systems with different control rules are considered. It is suggested to use the efficiency indexes: customer’s average waiting in lift cabin time and average total time, including the time of delivering the customer to the desired floor. Various control rules are introduced: Odd-Even, where one lift serves only customers in Odd floors and other lift only does that in Even floors Up-Down control rule where one lift serves only customers who are going from the first floor to the destination floor 2, 3,…, k; another lift serves customers from the first floor to the upper floor k + 1, k + 2, …, n. The results of simulation, allowing to compare various control rules relatively to the efficiency indexes, are given. It is introduced an optimal number of lifts, which minimizes number of lifts, minimizing a customer’s average waiting time. For some systems, the method of finding the optimal number of lifts, is suggested. Necessary figures demonstrating the operation of the lifts’ systems and the results of the simulation allow to estimate the efficiency indexes.

Evaluating a harvest control rule to improve the sustainability of Japanese fisheries

Fisheries management in Japan is currently at a turning point. MSY based reference points have historically been rejected because of impacts on the fishing industry that would result from their adoption. We propose and evaluate a new harvest control rule (HCR) that uses the biological reference points based on sustainable yield from the stochastic hockey-stick stock recruitment relationship. Management strategy evaluation simulations conditioned on data from Japanese stocks demonstrate that the new HCR avoided recruitment overfishing while providing stable and near maximum catch. The new HCR outperformed Japan’s traditional HCR in terms of conservation, and it outperformed an alternative HCR which is widely used around the world in terms of initial catch reduction and future catch variation. For forecasting and hindcasting simulations, the new HCR showed considerable improvements over traditional HCRs in terms of biomass and catch. This new management procedure can improve the current and future status of many overfished stocks in Japan as well as increase economic efficiency and better protect ecosystems.

Optimization Design and Test Bed of Fuzzy Control Rule Base for PV System MPPT in Micro Grid

This paper presents an optimal design of a fuzzy control rule base for tracking the maximum power point of a photovoltaic (PV) system. Fuzzy control is used for the maximum power point tracking (MPPT) of PV systems because it has the advantage of processing nonlinear systems. The rule base of fuzzy control depends on the user or designer’s experience and determines the fuzzy control’s performance. In this paper, we divide the MPPT state of the PV system into four cases according to the operating conditions, and propose the rule base design of the fuzzy control according to each case. The proposed method in the paper tests the MPPT performance using artificial lighting and compares the results with the conventional control method (proportional and integral (PI) and perturbation & observation (P&O) method) to prove its effectiveness.