Population dynamics and potential of fisheries stock enhancement: practical theory for assessment and policy analysis

The population dynamics of fisheries stock enhancement, and its potential for generating benefits over and above those obtainable from optimal exploitation of wild stocks alone are poorly understood and highly controversial. I review pertinent knowledge of fish population biology, and extend the dynamic pool theory of fishing to stock enhancement by unpacking recruitment, incorporating regulation in the recruited stock, and accounting for biological differences between wild and hatchery fish. I then analyse the dynamics of stock enhancement and its potential role in fisheries management, using the candidate stock of North Sea sole as an example and considering economic as well as biological criteria. Enhancement through release of recruits or advanced juveniles is predicted to increase total yield and stock abundance, but reduce abundance of the naturally recruited stock component through compensatory responses or overfishing. Economic feasibility of enhancement is subject to strong constraints, including trade-offs between the costs of fishing and hatchery releases. Costs of hatchery fish strongly influence optimal policy, which may range from no enhancement at high cost to high levels of stocking and fishing effort at low cost. Release of genetically maladapted fish reduces the effectiveness of enhancement, and is most detrimental overall if fitness of hatchery fish is only moderately compromised. As a temporary measure for the rebuilding of depleted stocks, enhancement cannot substitute for effort limitation, and is advantageous as an auxiliary measure only if the population has been reduced to a very low proportion of its unexploited biomass. Quantitative analysis of population dynamics is central to the responsible use of stock enhancement in fisheries management, and the necessary tools are available.     

Inventory rationing for a system with heterogeneous customer classes

Many retailers find it useful to partition customers into multiple classes based on certain characteristics. We consider the case in which customers are primarily distinguished by whether they are willing to wait for backordered demand. A firm that faces demand from customers that are differentiated in this way may want to adopt an inventory management policy that takes advantage of this differentiation. We propose doing so by imposing a critical level (CL) policy: when inventory is at or below the critical level demand from those customers that are willing to wait is backordered, while demand from customers unwilling to wait will still be served as long as there is any inventory available. This policy reserves inventory for possible future demands from impatient customers by having other, patient, customers wait. We model a system that operates a continuous review replenishment policy, in which a base stock policy is used for replenishments. Demands as well as lead times are stochastic. We develop an exact and efficient procedure to determine the average infinite horizon performance of a given CL policy. Leveraging this procedure we develop an efficient algorithm to determine the optimal CL policy parameters. Then, in a numerical study we compare the cost of the optimal CL policy to the globally optimal state-dependent policy along with two alternative, more naïve, policies. The CL policy is slightly over 2 % from optimal, whereas the alternative policies are 7 and 27 % from optimal. We also study the sensitivity of our policy to the coefficient of variation of the lead time distribution, and find that the optimal CL policy is fairly insensitive, which is not the case for the globally optimal policy.     

Ranked set sampling: cost and optimal set size

McIntyre (1952, Australian Journal of Agricultural Research 3, 385-390) introduced ranked set sampling (RSS) as a method for improving estimation of a population mean in settings where sampling and ranking of units from the population are inexpensive when compared with actual measurement of the units. Two of the major factors in the usefulness of RSS are the set size and the relative costs of the various operations of sampling, ranking, and measurement. In this article, we consider ranking error models and cost models that enable us to assess the effect of different cost structures on the optimal set size for RSS. For reasonable cost structures, we find that the optimal RSS set sizes are generally larger than had been anticipated previously. These results will provide a useful tool for determining whether RSS is likely to lead to an improvement over simple random sampling in a given setting and, if so, what RSS set size is best to use in this case.     

污染环境中可再生资源的最优收获问题

探讨了污染环境下双种群的最优收获问题．利用Pontryagin极大值原理得到一种最优分配方案——处理资源种群体内毒素的努力度与收获资源种群的努力度的分配方案,使经营者的经济收入达到最大,同时也得到次最优均衡解。     

土地利用变化和林业活动碳贮量变化测定与监测中的方法学问题

土地利用、土地利用变化和林业 (L U L U CF)活动是引起大气温室气体浓度上升的主要因素之一 ,评价、监测 L UL UCF活动的碳源 /汇功能还存在很大的不确定性。近年来我国在该方面开展了一些研究和测定工作 ,但研究力度还远远不够 ,研究方法还存在一些问题。针对 L U L UCF活动对碳贮量影响的测定和监测中的碳库选择、监测间隔期、样地数量以及土壤容重影响和校正等有关方法学问题进行了阐述 ,以期为我国该方面的研究和监测有所裨益。     

Optimal strategy for structured model of fishing problem

In this work we study a structured fishing model, basically displaying the two stages of the ages of a fish population, which are in our case juvenile, and adults. We associate to this model the maximization of the total discounted net revenues derived by the exploitation of the stock. The exploitation strategy of the optimal control problem is then developed and presented.     

A theory for optimal monitoring of marine reserves

Monitoring of marine reserves has traditionally focused on the task of rejecting the null hypothesis that marine reserves have no impact on the population and community structure of harvested populations. We consider the role of monitoring of marine reserves to gain information needed for management decisions. In particular we use a decision theoretic framework to answer the question: how long should we monitor the recovery of an over‐fished stock to determine the fraction of that stock to reserve? This exposes a natural tension between the cost (in terms of time and money) of additional monitoring, and the benefit of more accurately parameterizing a population model for the stock, that in turn leads to a better decision about the optimal size for the reserve with respect to harvesting. We found that the optimal monitoring time frame is rarely more than 5 years. A higher economic discount rate decreased the optimal monitoring time frame, making the expected benefit of more certainty about parameters in the system negligible compared with the expected gain from earlier exploitation.     

The Use of Asian Ficus Species for Restoring Tropical Forest Ecosystems

Fig (Ficus spp.) trees have been promoted as framework species for tropical forest restoration throughout Asia, because they are considered to be keystone species. This article presents optimal propagation and planting techniques for six Asian dioecious Ficus species, which will enable their inclusion in forest restoration plantings across the Asia‐Pacific region: Ficus auriculata, F. fulva, F. hispida, F. oligodon, F. semicordata, and F. variegata. Nursery experiments compared the growth performance of propagating planting stock from seed and from leafy cuttings, whereas field experiments assessed the cost‐effectiveness and the relative performance of (1) direct seeding, (2) planting stock from seed, and (3) planting stock from cuttings. The most efficient method of producing Ficus spp. was from seed. Propagation from cuttings was much less successful. Seedlings produced from seed had the highest rates of growth and survival both in the nursery and in field trials. In field trials, use of planting stock from seed was also more cost‐effective than direct seeding and vegetative propagation. Establishment costs calculated on the basis of “per plant established” were $1.14 for seed, $6.95 for cutting, and $25.88 for direct seeding.     

Optimization of batch and fed-batch bioreactors using simulated annealing

In order for biobased industrial products to compete economically with petroleum-derived products, significant reduction in their processing cost is necessary. Since most bioprocesses are operated in batch or fed-batch mode, their optimization involves theoretical and computational challenges. Simulated annealing (SA), a stochastic optimization algorithm, is used in this study to solve a number of challenging optimization problems related to the design and operation of bioreactors. Two well-known case studies are considered in which the robustness and efficiency of the SA algorithm is demonstrated. More specifically, in the first case study it is shown that the global optimal solution located by SA achieves significant improved productivity when compared with the results of previous investigations. In the second case study a realistic objective function is considered where the economic performance of a bioprocess is optimized. SA exhibits impeccable performance and robustness and was able to locate the global optimal solution irrespective of the initial point selected.     

The impact of operations redesign on the safety stock investment in supply chains

This study is motivated by a real problem encountered in the manufacturing and distribution process at a local electronic manufacturer of security devices. We investigate the impact of operations redesign (i.e., operations merging) on the cost of safety stock in a supply chain. A simple safety stock method is used to derive a model for estimating safety stock levels. Our result shows that operations redesign can have a significant impact on safety stock investment. We extend and complement the existing literature in the following aspects: (i) we address the issue of safety stock deployment, i.e., we not only investigate the problem of how many operations should be delayed, but also determine which operations need to be delayed, (ii) we provide an efficient heuristic algorithm to determine which operations need to be merged, and (iii) we find the optimal operations redesign strategies under some special cases. Our analysis also reveals some important conditions and insights for better operations redesign, which enable us not only to decide when an operations redesign is appropriate, but also to suggest the scale and the format of the operations redesign.     

Parsimony analysis of unaligned sequence data: maximization of homology and minimization of homoplasy,not minimization of operationally defined total cost or minimization of equally weighted transformations

Wheeler (2012) stated that minimization of ad hoc hypotheses as emphasized by Farris (1983) always leads to a preference for trivial optimizations when analysing unaligned sequence data, leaving no basis for tree choice. That is not correct. Farris's framework can be expressed as maximization of homology, a formulation that has been used to overcome the problems with inapplicables (it leads to the notion of subcharacters as a quantity to be co‐minimized in parsimony analysis) and that is known not to lead to a preference for trivial optimizations when analysing unaligned sequence data. Maximization of homology, in turn, can be formulated as a minimization of ad hoc hypotheses of homoplasy in the sense of Farris, as shown here. These issues are not just theoretical but have empirical relevance. It is therefore also discussed how maximization of homology can be approximated under various weighting schemes in heuristic tree alignment programs, such as POY, that do not take into account subcharacters. Empirical analyses that use the so‐called 3221 cost set (gap opening cost three, transversion and transition costs two, and gap extension cost one), the cost set that is known to be an optimal approximation under equally weighted homology in POY, are briefly reviewed. From a theoretical point of view, maximization of homology provides the general framework to understand such cost sets in terms that are biologically relevant and meaningful. Whether or not embedded in a sensitivity analysis, this is not the case for minimization of a cost that is defined in operational terms only. Neither is it the case for minimization of equally weighted transformations, a known problem that is not addressed by Kluge and Grant's (2006) proposal to invoke the anti‐superfluity principle as a rationale for this minimization.     

Optimal choice of species and size class for transplanting coral community

Transplantation of sessile organisms living in a planned destruction site to a safe site is an important means of restoration to mitigate biodiversity loss following anthropogenic developments. In particular, corals, which play fundamental roles in the coral reef ecosystem and contribute to biodiversity, are good candidates for transplantation. In this study, we investigate the optimal choice of species and size class to be used for coral transplantation. We first studied a case in which the objective function to evaluate the success of transplantation is the maximum total coverage. The optimal strategy is to choose the species and size class with higher net coverage gain per unit handling effort. It is often recommended to transplant only one or a few species and neglect others, even if the original community consists of many species. This may achieve high coverage in the restored coral community but cause loss of species diversity. To overcome this problem, we next study a case in which the objective of the transplantation operation is to maximize the “prosperity index”, defined as the product of total coverage and species diversity. In this case, the optimal strategy depends on the species property, population size, and the limitation of total cost allowed for transplantation, but it tends to recommend more species to be transplanted than what is recommended by the coverage maximization criterion. We conclude that maximization of the prosperity index is a better criterion for transplantation than simple coverage maximization.     

Feasible and optimal retrofitting of batch-soluble to continuous-immobilized enzyme processes applied to adsorbed enzymes

The advantages of retrofitting an in situ soluble enzyme batch process to an immobilized enzyme continuous process are contrasted against the disadvantages by means of a dimensionless feasibility/optimization analysis. The general analysis is applied to the case of an adsorbed enzyme system where a maximum in activity occurs with respect to loading. For this case, a minimum in the ratio of enzyme-carrier complex working lifetime to in situ batch process time and a maximum in the cost difference between the in situ and retrofit processes occurs with respect to loading and retrofit process conversion. For the maximization of cost difference, the analysis also suggests a criterion that can be used to determine whether the values for optimal loading and retrofit conversion will result in the retrofit being economically feasible. When infeasibility occurs, qualitative sensitivity analysis for a variety of situations points out whether a catalyst or process modification will improve feasibility the most. Apart from forming the basis for an iterative retrofit process design algorithm, the modeling approach's ability to specify optimal values of catalyst properties such as loading lends itself to defining process-specific, catalyst design "targets" would be useful for those developing immobilized enzyme preparation methodology and those investigating enzyme-carrier interactions.     

Cost-effective control of chronic viral diseases: Finding the optimal level of screening and contact tracing

Chronic viral diseases such as human immunodeficiency virus (HIV) and hepatitis B virus (HBV) afflict millions of people worldwide. A key public health challenge in managing such diseases is identifying infected, asymptomatic individuals so that they can receive antiviral treatment. Such treatment can benefit both the treated individual (by improving quality and length of life) and the population as a whole (through reduced transmission). We develop a compartmental model of a chronic, treatable infectious disease and use it to evaluate the cost and effectiveness of different levels of screening and contact tracing. We show that: (1) the optimal strategy is to get infected individuals into treatment at the maximal rate until the incremental health benefits balance the incremental cost of controlling the disease; (2) as one reduces the disease prevalence by moving people into treatment (which decreases the chance that they will infect others), one should increase the level of contact tracing to compensate for the decreased effectiveness of screening; (3) as the disease becomes less prevalent, it is optimal to spend more per case identified; and (4) the relative mix of screening and contact tracing at any level of disease prevalence is such that the marginal efficiency of contact tracing (cost per infected person found) equals that of screening if possible (e.g., when capacity limitations are not binding). We also show how to determine the cost-effective equilibrium level of disease prevalence (among untreated individuals), and we develop an approximation of the path of the optimal prevalence over time. Using this, one can obtain a close approximation of the optimal solution without having to solve an optimal control problem. We apply our methods to an example of hepatitis B virus.     

An integrated environmental and cost assessment method based on LCA and LCC for automobile interior and exterior trim design scheme optimization

Purpose

This paper provided an integrated method to evaluate environmental impact and life cycle cost (LCC) of various alternative design schemes in the early design and development stages of complex mechanical product; an optimization method of product design schemes based on life cycle assessment (LCA) and LCC is proposed as a supporting design tool to achieve optimal integration of environmental impact and cost of the design.

Methods

The applied research methods include product level deconstruction model, LCA/LCC integrated analysis model, and the product design scheme optimization method. In the life cycle environmental assessment, GaBi software and CML2001 evaluation method are used to evaluate product environmental impact. In terms of product design configuration scheme optimization, the TOPSIS method is used to optimize the design schemes generated. Taking the internal and external trim of automobile as an example, the specific implementation process of the method is illustrated.

Results and discussion

The case study indicates that, when comprehensively considering the environmental impact and cost, the composite indices of the optimal and worst schemes are 0.8667 and 0.3001, respectively; their costs are ¥164.87 and ¥179.68, respectively; and the eco points of environmental impact are 14.74 and 39.78, respectively. The cost of the two schemes are not much different, but the environmental impact of the optimal scheme is only 37.1% of the worst scheme’s; When cost is the only factor to be considered, the lowest cost design scheme is about 36.7% of the maximum scheme’s cost, and the environmental impact of the lowest cost design scheme is about 1.6 times of the maximum cost scheme’s. When environmental impact is the only factor to be considered, the least environmental impact of design scheme accounts about 31.7% of the largest; the cost of design scheme with the least environmental impact accounts for about 58.1% of the largest one’s. Integrating LCA and LCC, scientific suggestions can be provided from several perspectives.

Conclusions

By considering the environmental impact and LCC, this paper proposes a method of product design scheme optimization as a supporting design tool which could evaluate the design options of the product and identify the preferred option in the early stage of product design. It is helpful to realize the sustainability of the product. In order to improve the applicability of this method, the weighting factors of environmental impact and cost could be adjusted according to the requirements of energy saving and emission reduction of different enterprises.

     

Dynamic economic analysis on invasive species management: Some policy implications of catchability

The problem of controlling invasive species has emerged as a global issue. In response to invasive species threats, governments often propose eradication. This article challenges the eradication view by studying optimal strategies for controlling invasive species in a simple dynamic model. The analysis mainly focuses on deriving policy implications of catchability in a situation where a series of controlling actions incurs operational costs that derive from the fact that catchability depends on the current stock size of invasive species. We analytically demonstrate that the optimal policy changes drastically, depending on the sensitivity of catchability in response to a change in the stock size, as well as on the initial stock. If the sensitivity of catchability is sufficiently high, the constant escapement policy with some interior target level is optimal. In contrast, if the sensitivity of catchability is sufficiently low, there could exist a threshold of the initial stock which differentiates the optimal action between immediate eradication and giving-up without any control. In the intermediate range, immediate eradication, giving-up without any control, or more complex policies may be optimal. Numerical analysis is employed to present economic intuitions and insights in both analytically tractable and intractable cases.     

Fisheries exploitation pattern of narrow-barred Spanish mackerel, Scomberomorus commerson, in Oman and potential management options

A data base including length frequency distributions and catches of the Scomberomorus commerson in Oman according to fleet (gear/technique) and region has been established to carry out length cohort analyses, determine yield per recruit and simulate changes in fishing effort and/or increase in minimum length limit in catches. The analyse of data showed that: (i) The average fishing mortality rate is moderate (0.5–0.6), but acts in part on the juvenile fraction of the stock. The exploitation pattern differs, however, among fleets with some fleet components targeting largely immature kingfish and others largely the adult stock. (ii) An increase in total fishing effort would lead to long‐term losses in total catch; the losses would be highest for fleets that target the larger specimens. A reduction of the effort would, in the long term, lead to an increase in yield and spawning stock biomass. (iii) An increase of minimum length limit in catches would, in the long term, lead to a substantial increase in yield and spawning stock biomass; the gain in catch would be largest for fleet components that target the adult fraction of the stock and (iv) an increase in minimum length limit in catches combined with an increased selectivity of the fisheries (i.e. favorising fleets targeting the adult fraction of the stock) would lead to the highest gain in sustainable catch. In this case, the sustainable catch could be increased by more than 50%. Therefore, this option represents the optimal management strategy obtained in the present study.     

Optimal harvesting of fish stocks under a time-varying discount rate

Optimal control theory has been extensively used to determine the optimal harvesting policy for renewable resources such as fish stocks. In such optimisations, it is common to maximise the discounted utility of harvesting over time, employing a constant time discount rate. However, evidence from human and animal behaviour suggests that we have evolved to employ discount rates which fall over time, often referred to as “hyperbolic discounting”. This increases the weight on benefits in the distant future, which may appear to provide greater protection of resources for future generations, but also creates challenges of time-inconsistent plans. This paper examines harvesting plans when the discount rate declines over time. With a declining discount rate, the planner reduces stock levels in the early stages (when the discount rate is high) and intends to compensate by allowing the stock level to recover later (when the discount rate will be lower). Such a plan may be feasible and optimal, provided that the planner remains committed throughout. However, in practice there is a danger that such plans will be re-optimized and adjusted in the future. It is shown that repeatedly restarting the optimization can drive the stock level down to the point where the optimal policy is to harvest the stock to extinction. In short, a key contribution of this paper is to identify the surprising severity of the consequences flowing from incorporating a rather trivial, and widely prevalent, “non-rational” aspect of human behaviour into renewable resource management models. These ideas are related to the collapse of the Peruvian anchovy fishery in the 1970's.     

The Energetics of Asexual Reproduction and Colony Formation in Benthic Marine Invertebrates

There are several formsof individual and colon) organizationavailable to benthic marine invertebrates with indeterminategrowth In particular anthozoan coelenterates exhibit three suchforms of organization 1 solitary individuals without asexualreproduction 2 colonies or clonal groups with determinate polypsize and indeterminate colony size and 3 colonies or clonalgroups with both indeterminate polyp size and indeterminatecolonyor clone size The last group includes species where asexualreproduction is continuous and those where it is limited toa single season of the year A model is presented which definesthree optimal sizes for indeterminately growing organisms 1optimal size for a solitary individual 2 optimal size of a polypwithin a colony and 3 optimal size at asexual division The optimaare derived by maximizing the difference between energy intakeand energetic cost Simulations allow prey size and habitat qualityto vary and derive predictions of optimal size and organizationfor each case Individual and clonal growth rates are modelledfor the case where asexual reproduction is limited to a singleseason and poly p sizes within clones are compared The modelpredicts that the three torms of organization among anthozoanpolyps are related primarily to the size distribution of prey     

The effect of costly information in diet choice

Summary We distinguish three cases which consider the effect of information on animal behaviour: static information, obligate information and facultative information. Static information deals with the case in which the animal does not acquire additional information; it starts with enough information to discriminate options. Obligate information deals with the case in which the animal acquires information at no additional cost. Facultative information is when the animal may choose to pay a cost in order to acquire information. We illustrate the differences among these three situations by analysing the optimal diet problem subject to the different information regimes. Compared to the case with static information, obligate recognition time narrows the range of prey densities over which an optimal forager feeds selectively, and facultative recognition time reduces it further still. The three models yield qualitatively different predictions regarding how the optimal diet varies with relative abundances of alternative resources. In the space of resource densities, the line separating the optimal behaviours of selectivity and opportunism is straight for both the perfect and obligate information cases. In the case of facultative recognition time this line or isoleg is part of a quadratic curve. This non-linearity yields two completely new predictions: a less profitable resource may be lost from the diet after becoming more abundant and the poor resource may be included in the diet as a result of the rich resource becoming more common.