A NEW APPROACH TO SIMULATING FISHERIES DATA FOR POLICY MAKING

The main objective of natural resource management is to create social and economic value while maintaining sustainability. In this paper, we introduce an enhanced method for simulating high‐dimensional time series and apply it to Icelandic fishing resource management data. The methodology can be used in many contexts, but is particularly appropriate for simulating the many complex interactions involved in natural resource management. The simulations can be used to explore the sensitivity of resource management policies to future changes using an affinity parameter. Affinity, qualitatively similar to correlation, is a ordinal measure between –1 and +1 that models one's belief how much the future might behave like, or different from, the past. The main appeal of the method is its reliance on data and relative independence from assumptions about that data. In the paper, we apply it on data on Icelandic cod with encouraging results.     

Ecological-economic modelling for the sustainable management of biodiversity

Terrestrial and marine biodiversity provides the basis for both ecosystems functioning and numerous commodities or services that underpin human well-being. From several decades, alarming trends have been reported worldwide for both biodiversity and ecosystem services. Therefore the sustainable management of biodiversity requires a double viewpoint balancing ecological conservation with the welfare of human societies. Understanding the underlying trade-offs, synergies and interactions imposes the development of interdisciplinary researches and methods. In that respect, bio-economic or ecological economic modeling is likely to play a major role. The present paper intends to elicit the key features, strengths and challenges of bio-economic approaches especially in mathematical and computational terms. It first recall the main bio-economic methods, models and decisional instruments used in these types of analyses. Then the paper shows to what extent bio-economic sustainability lies between equilibrium, viability and optimality mathematical frameworks. It ends up by identifying new major challenges among which the operationalization of ecosystem based management, the precautionary principle and the implementation of governance are especially important.     

ENVIRONMENTAL CHANGE AND THE CONTRIBUTION OF BIODIVERSITY TO ECOSYSTEM ADAPTATION

Abstract This paper develops a measure of the contribution of biodiversity in enhancing ecosystem performance that is subject to environmental fluctuation. The analysis draws from an ecological model that relates high phenotypic variance with lower short‐term productivity (due to the presence of suboptimal species) and higher long‐term productivity (due to better ability to respond to environmental fluctuations). This feature, which is a notable extension to existing economic‐ecological models of biodiversity, enables assessment of the interactions between diversity and a range of environmental fluctuations to highlight that biodiversity could be rendered economically disadvantageous when environmental fluctuation is insufficient. The resulting economic‐ecological model generates discounted present value of harvests for an ecosystem with diverse set of species. This value is compared with the harvest value of a similar economic‐ecological model with no diversity and that of an ecosystem where the dynamics of phenotypes in response to environmental fluctuations is disregarded. The results show that diversity positively contributes to the performance of ecosystems subject to sufficiently large environmental fluctuation. In addition, neglecting an ecosystem's increasing ability to adapt to match environmental conditions is also shown to be more costly than having no diversity in an otherwise identical ecosystem.     

基于FUDAN-CCDC模型对新冠肺炎的建模和确诊人数的预测

科学地预测疫情发展趋势对疫情防控至关重要.在新时滞动力学模型(TDD-NCP)的基础上,提出基于随机动力学的时滞卷积模型和离散卷积模型,并基于中国疾病预防控制中心的相关研究结果及公开数据以及Wallinga和Lipsitch的工作,反演出COVID-19的重要参数,拟合了武汉及上海市疫情发展趋势.     

THE ROLE OF GROUNDWATER‐DEPENDENT ECOSYSTEMS IN GROUNDWATER MANAGEMENT

Ecosystems provide a wide range of services essential for a proper environmental, economic, and social performance. While the estimated global value of ecosystem services in 2014 is very significant, the annual loss of ecosystem services value is alarming. Our paper focuses on groundwater‐dependent ecosystems (GDEs), some very important to society, which are under threat due to groundwater overexploitation. Considering the ecosystem health/status function is essential for sound groundwater regulation policy. The paper assesses the conjunctive management of groundwater and GDEs both in theory and in a relevant case study, using a certain type of an ecosystem health function. The theoretical results demonstrate how the change in the slope values of a general ecosystem health function affects the optimal groundwater management policy. The analysis also suggests a change in groundwater management strategies as a function of the value of the ecosystem. The theoretical findings are corroborated with data from an aquifer in Spain and its associated GDE—the Tablas de Daimiel Wetland. The paper highlights theoretically and empirically the necessity for a better understanding of GDEs behavior. It calls for groundwater regulation to protect these resources.     

Implementation of a finite‐volume method for the determination of effective parameters in fissured porous media

Many studies have proposed one‐equation models to represent transport processes in heterogeneous porous media. This approach is based on the assumption that dependent variables such as pressure, temperature, or concentration can be expressed in terms of a single large‐scale averaged quantity in regions having very different chemical and/or mechanical properties. However, one can also develop large‐scale averaged equations that apply to the distinct regions that make up a heterogeneous porous medium. This approach leads to region‐averaged equations that contain traditional convective and dispersive terms, in addition to exchange terms that account for the transfer between the different media. In our approach, the fissures represent one region, and the porous media blocks represent the second region. The analysis leads to upscaled equations having a domain of validity that is clearly identified in terms of time and length‐scale constraints. Closure problems are developed that lead to the prediction of the effective coefficients that appear in the region averaged equations, and the main purpose of this article is to provide solutions to those closure problems. The method of solution makes use of an unstructured grid and a joint element method in order to take care of the special characteristics of the fissured network. This new numerical method uses the theory developed by Quintard and Whitaker and is applied on considerably more complex geometries than previously published results. It has been tested for several special cases such as stratified systems and “sugarbox” media, and we have compared our calculations with other computational methods. © 2000 John Wiley & Sons, Inc. Numer Methods Partial Differential Eq 16: 237–263, 2000     

A METHOD FOR SIMPLIFYING LARGE ECOSYSTEM MODELS

Abstract Simplifying large ecosystem models is essential if we are to understand the underlying causes of observed behaviors. However, such understanding is often employed to achieve simplification. This paper introduces two model simplification methods that can be applied without requiring intimate prior knowledge of the system. Their utility is measured by the resulting values of given model diagnostics relative to those of the large model. The first method is a simple automated procedure for nondimensionalizing large ecosystem models, which identifies and eliminates terms that have little effect on model diagnostics. Some of its limitations are then addressed by the rate elimination method, which measures the relative importance of model terms using least‐squares regression. The methods are applied to a model of the nitrogen cycle in Port Phillip Bay, Victoria, Australia. The rate elimination method provided more insights into the causal relationships built into the model than the nondimensionalizing method. It also allowed the reduction of the model's dimension. Thus it is a useful first step in model simplification.     

THE VALUE OF SHORT‐RUN CLIMATE FORECASTS IN MANAGING THE COASTAL COHO SALMON (ONCORHYNCHUS KISUTCH) FISHERY IN WASHINGTON STATE

ABSTRACT. . In recent years our understanding of the intricate connections between climate variability, marine and freshwater environmental conditions and the responses of fish stocks has improved considerably. With predictable relationships between the environment and stock abundance, fishery managers should be able to forecast variation in stock survival and recruitment. Such forecasts present an opportunity for increasing the economic value of fisheries and for achieving other management objectives, such as stock conservation and maintenance of population diversity. After describing a 4‐step framework for addressing the question ‘What is a forecast worth?’ in a fishery decision‐making context, we introduce the management system for Washington's coastal coho salmon (Oncorhynchus kisutch) fishery. Then we apply the 4‐step framework to estimate the value of improved run size forecasts in the annual harvest management of coho salmon in Washington State. Our principal analytical tool is a stochastic simulation model that incorporates the main characteristics of the fishery. The paper concludes with a discussion of opportunities and constraints to the use of climate‐based forecasts in fishery management on various spatial and temporal scales, and we consider the challenges associated with forecasting variations in fish stock size caused by shifts in climate and related ocean conditions.     

基于动态线性模型的中国狭义货币需求及缺口的贝叶斯估计

本文应用动态线性模型研究我国的狭义货币需求,利用贝叶斯吉布斯抽样方法估计模型的参数和方差,获得了潜在货币需求趋势和货币缺口,对我国的货币供给进行分析并获得一些有益结论,对于央行更好地实施货币管理,保持经济平稳发展有积极意义。     

A MODEL FOR THE BIOECONOMIC EVALUATION OF MARINE PROTECTED AREA SIZE AND PLACEMENT IN THE NORTH SEA

ABSTRACT. The use of marine protected areas (MPAs) as a basic management tool to limit exploitation rates in marine fisheries has been widely suggested. Models are important in predicting the consequences of management decisions and the design of monitoring programs in terms of policy goals. However, few tools are available that consider both multiple fleets and ecosystem scale dynamics. We use a new applied game theory tool, Ecoseed, that operates within a temporally and spatially explicit biomass dynamics model, Ecopath with Ecosim, to evaluate the efficacy of marine protected areas in the North Sea in both ecological and economic terms. The Ecoseed model builds MPAs based on the change in values of predicted economic rents of fisheries and the existence value of biomass pools in the ecosystem. We consider the market values of four fisheries operating in the North Sea: a trawl fishery, a gill net fishery, a seine fishery, and an industrial (reduction) fishery. We apply existence values, scaled such that their aggregate is similar to the total fishery value, to six biomass pools of concern: juvenile cod, haddock, whiting, saithe, seals, and the collective pool ‘Other predators’ that include marine mammals. Four policy options were considered: to maximize the rent only; to maximize the existence values only; to maximize the sum of the rent and existence values; and, finally, to maximize the sum of the rent and the existence values, but excluding only the trawl fleet from the MPA. The Ecoseed model suggests that policy goals that do not include ecological considerations can negatively impact the rents obtained by the different fishing sectors. The existence values will also be negatively impacted unless the MPA is very large. The Ecoseed model also suggests that policy goals based solely on existence values will negatively impact most fisheries. Under policy options that included ecological considerations, maximum benefits were derived from an MPA that covered 25–40% of the North Sea, placed along the southern and eastern coasts. Finally, the Ecoseed model suggests that an exclusion of the trawl fishery only from the MPA can provide small‐to‐substantial positive impacts to most species and fleets; this relative impact depends on level of interaction between the trawl fleet and the other fleets target species (e.g., through bycatch).     

Integrative interaction analysis using threshold gradient directed regularization

For many complex business and industry problems, high‐dimensional data collection and modeling have been conducted. It has been shown that interactions may have important implications beyond the main effects. The number of unknown parameters in an interaction analysis can be larger or much larger than the sample size. As such, results generated from analyzing a single data set are often unsatisfactory. Integrative analysis, which jointly analyzes the raw data from multiple independent studies, has been conducted in a series of recent studies and shown to outperform single–data set analysis, meta‐analysis, and other multi–data set analyses. In this study, our goal is to conduct integrative analysis in interaction analysis. For regularized estimation and selection of important interactions (and main effects), we apply a threshold gradient directed regularization approach. Advancing from the existing studies, the threshold gradient directed regularization approach is modified to respect the “main effects, interactions” hierarchy. The proposed approach has an intuitive formulation and is computationally simple and broadly applicable. Simulations and the analyses of financial early warning system data and news‐APP (application) recommendation behavior data demonstrate its satisfactory practical performance.     

THE USE OF TELESCOPING SPATIAL SCALES TO CAPTURE INSHORE TO SLOPE DYNAMICS IN MARINE ECOSYSTEM MODELING

Abstract Ecosystem processes function at many scales, and capturing these processes is a challenge for ecosystem models. Nevertheless, it is a necessary step for considering many management issues pertaining to shelf and coastal systems. In this paper, we explore one method of modeling large areas with a focus at a range of scales. We develop an ecosystem model that can be used for strategic management decision support by modeling the waters off southeastern Australia using a polygon telescoping approach, which incorporates fine‐scale detail at the coastal zone, increasing in scale to a very coarse scale in the offshore areas. This telescoping technique is a useful tool for incorporating a wide range of habitats at different scales into a single model.     

Computational aspects of sequential Monte Carlo filter and smoother

Progress in information technologies has enabled to apply computer-intensive methods to statistical analysis. In time series modeling, sequential Monte Carlo method was developed for general nonlinear non-Gaussian state-space models and it enables to consider very complex nonlinear non-Gaussian models for real-world problems. In this paper, we consider several computational problems associated with sequential Monte Carlo filter and smoother, such as the use of a huge number of particles, two-filter formula for smoothing, and parallel computation. The posterior mean smoother and the Gaussian-sum smoother are also considered.     

Monotone methods and stability results for nonlocal reaction-diffusion equations with time delay

In this paper, we study the applications of the monotone iteration method for investigating the existence and stability of solutions to nonlocal reaction-diffusion equations with time delay. We emphasize the importance of the idea of monotone iteration schemes for investigating the stability of solutions to such equations. We show that every steady state of such equations obtained by using the monotone iteration method is priori stable and all stable steady states can be obtained by using such method. Finally, we apply our main results to three population models.     

Mixing DEA and FDH models together

New formulations of data envelopment analysis (DEA) and free disposal hull (FDH) models in a unified linear framework are proposed. One of the main objectives of this paper is to derive meaningful economic interpretations of the dual models in the price space. In particular, we introduce a new formulation of the returns to scale assumption with a straightforward economic interpretation. This framework allows for mixing DEA and FDH models together in a more general framework.     

Stable limits for sums of dependent infinite variance random variables

The aim of this paper is to provide conditions which ensure that the affinely transformed partial sums of a strictly stationary process converge in distribution to an infinite variance stable distribution. Conditions for this convergence to hold are known in the literature. However, most of these results are qualitative in the sense that the parameters of the limit distribution are expressed in terms of some limiting point process. In this paper we will be able to determine the parameters of the limiting stable distribution in terms of some tail characteristics of the underlying stationary sequence. We will apply our results to some standard time series models, including the GARCH(1, 1) process and its squares, the stochastic volatility models and solutions to stochastic recurrence equations.     

Stability and Hopf bifurcation in a class of nonlocal delay differential equation with the zero‐flux boundary condition

The aim of this paper is to study the stability and Hopf bifurcation in a general class of differential equation with nonlocal delayed feedback that models the population dynamics of a two age structured spices. The existence of Hopf bifurcation is firstly established after delicately analyzing the eigenvalue problem of the linearized nonlocal equation. The direction of the Hopf bifurcation and stability of the bifurcated periodic solutions are then investigated by means of center manifold reduction. Subsequently, we apply our main results to explore the spatial‐temporal patterns of the nonlocal Mackey‐Glass equation. We obtain both spatially homogeneous and inhomogeneous periodic solutions and numerically show that the former is stable while the latter is unstable. We also show that the inhomogeneous periodic solutions will eventually tend to homogeneous periodic solutions after transient oscillations and increasing of the immature mobility constant will shorten the transient oscillation time.     

VIABILITY MODEL OF TROPHIC INTERACTIONS IN MARINE ECOSYSTEMS

ABSTRACT. An attempt to use viability models for studying marine ecosystems is proposed as a possible alternative to classical ecosystem modeling. Viability models do not consider optimal solutions but instead define all possible evolutions of a dynamical system under given constraints. Applied to marine ecosystems, a viability model is formulated based on the trophic coefficients of a mass‐balanced model. This requires relatively few assumptions about the processes involved and can integrate uncertainty associated with the required estimates of input parameters. An iterative algorithm is proposed to calculate the viability kernel, i.e., the envelope of all viable trajectories of the ecosystem. An application to the Benguela ecosystem is presented, considering interactions between detritus, phytoplankton, zooplankton, pelagic fish, demersal fish and fisheries. Results show how a viability kernel could be used to better define the healthy states of a marine ecosystem, by defining what states should be avoided. The paper discusses how viability models of trophic interactions could help to define a new ecosystem‐based indicator for fisheries management. It then discusses how this approach can potentially contribute to a paradigm shift that is emerging in the management of renewable resources.     

Medium‐term horizon volatility forecasting: A comparative study

In this paper, volatility is estimated and then forecast using unobserved components‐realized volatility (UC‐RV) models as well as constant volatility and GARCH models. With the objective of forecasting medium‐term horizon volatility, various prediction methods are employed: multi‐period prediction, variable sampling intervals and scaling. The optimality of these methods is compared in terms of their forecasting performance. To this end, several UC‐RV models are presented and then calibrated using the Kalman filter. Validation is based on the standard errors on the parameter estimates and a comparison with other models employed in the literature such as constant volatility and GARCH models. Although we have volatility forecasting for the computation of Value‐at‐Risk in mind the methodology presented has wider applications. This investigation into practical volatility forecasting complements the substantial body of work on realized volatility‐based modelling in business. Copyright © 2007 John Wiley & Sons, Ltd.