AN INDIVIDUAL‐BASED MODEL FOR FERAL HOGS IN GREAT SMOKY MOUNTAINS NATIONAL PARK

The expansion of feral hog (Sus scrofa) populations in the United States has resulted in increased efforts to develop and implement control strategies designed to minimize the impacts done by this invasive species. We describe an individual‐based model for feral hogs in Great Smoky Mountains National Park (GSMNP). The objectives of the model are to provide an understanding of the population dynamics of this feral hog population and to determine the efficacy of the annual harvest as a population control method. Results suggest that the dynamics of the population are driven by fall hard mast production and the GSMNP harvests currently limit growth of the population, but these control efforts have not reduced the population.     

SOLVING A CROP PROBLEM BY AN OPTIMAL CONTROL METHOD

ABSTRACT. A system of ordinary differential equations coupled with a parabolic partial differential equation is studied in order to understand an interaction between two crops and a pathogen. Two different types of crops are planted in same field in some pattern so that the spread of pathogen can be controlled. The pathogen prefers to eat one crop. The other crop, which is not preferred by the pathogen, is introduced to control the spread of pathogen in the farming land. The “optimal” initial planting pattern is sought to maximize plant yields while minimizing the variation in the planting pattern. The optimal pattern is characterized by a variation inequality involving the solutions of the optimality system. Numerical examples are given to illustrate the results.     

ACS Student Affiliates at University of Michigan Use Their Passion for Chemistry to Inspire the Community and Other Students

Going from almost zero to more than sixty active members in less than a year, the University of Michigan American Chemical Society Student Affiliate chapter is a success story about revitalizing a struggling chapter. Innovative officer positions, increased delegation of authority, and courage to try new ideas generated this special chemistry. In order to encourage each member to be creative and reach his or her full chapter potential, the officers stressed, Dream of an outstanding activity, and everyone will make it happen. Strategically, this philosophy was reinforced by electing members who had spearheaded projects to the new officer positions. In the following article, we will present the events and philosophies that created the strong intra-Student Affiliate and inter-Student Affiliate/community chemical bonds.     

OPTIMAL FISH HARVESTING FOR A POPULATION MODELED BY A NONLINEAR PARABOLIC PARTIAL DIFFERENTIAL EQUATION

As the human population continues to grow, there is a need for better management of our natural resources in order for our planet to be able to produce enough to sustain us. One important resource we must consider is marine fish populations. We use the tool of optimal control to investigate harvesting strategies for maximizing yield of a fish population in a heterogeneous, finite domain. We determine whether these solutions include no‐take marine reserves as part of the optimal solution. The fishery stock is modeled using a nonlinear, parabolic partial differential equation with logistic growth, movement by diffusion and advection, and with Robin boundary conditions. The objective for the problem is to find the harvest rate that maximizes the discounted yield. Optimal harvesting strategies are found numerically.     

CONTROL OF A METAPOPULATION HARVESTING MODEL FOR BLACK BEARS

ABSTRACT. We develop a metapopulation harvesting model that includes density‐dependent immigration and emigration and apply Pontryagin's maximum principle to derive an optimal harvesting and reserve design strategy. The model is designed to mimic the black bear population of eastern Tennessee and western North Carolina. Model results suggest that a forest region's population can be maintained despite high harvest levels due to emigration from a connected, un‐harvested park region. The amount of shared border between the park and forest region is important in determining the optimal harvesting strategy. This technique offers new insight on the spatial control of protected populations.     

OPTIMAL DYNAMIC HARVEST OF A MOBILE RENEWABLE RESOURCE

Abstract We present a mathematical model for the growth, movement, and harvesting of a renewable resource, and characterize the spatiotemporal distribution of harvest effort which maximizes the present value of harvest (yield) over a finite time horizon. We derive the optimality system for this model and show that the yield‐maximizing solution often includes one or more no‐take reserves that change in size over time. We explore how the results change with varying parameter values. The results inform ongoing debate about the use of reserves, and are increasingly relevant as technology enables enforcement of spatially structured harvest constraints.     

REGULATION OF A FISHERY: FROM A LOCAL OPTIMAL CONTROL PROBLEM TO AN “INVARIANT DOMAIN‘ APPROACH

ABSTRACT. This study aims at regulating a fishery by reducing its catch and effort variations around a reference equilibrium point. A simple bioeconomic continuous time model is considered and the control variable acts on the rate of change of effort. Two approaches have been implemented: the first one is a local optimal approach that sets the problem in the classical linear-quadratic framework; it is extended to an “invariant domain‘ approach, whose robustness constitutes a major advantage.     

OPTIMAL HARVESTING OF A SPATIALLY EXPLICIT FISHERY MODEL

Abstract We consider an optimal fishery harvesting problem using a spatially explicit model with a semilinear elliptic PDE, Dirichlet boundary conditions, and logistic population growth. We consider two objective functionals: maximizing the yield and minimizing the cost or the variation in the fishing effort (control). Existence, necessary conditions, and uniqueness for the optimal harvesting control for both cases are established. Results for maximizing the yield with Neumann (no‐flux) boundary conditions are also given. The optimal control when minimizing the variation is characterized by a variational inequality instead of the usual algebraic characterization, which involves the solutions of an optimality system of nonlinear elliptic partial differential equations. Numerical examples are given to illustrate the results.