title: Sustainable ecosystem management using optimal control theory: part 2 (stochastic systems).
abstract: Sustainable development of ecosystems through external ecosystem management is assuming importance for the environmentalists. To that effect, previous work by the authors looked at the option of manipulating population dynamics of the species in an ecosystem to achieve sustainability. Fisher information is used as the quantifying measure of sustainability and optimal control theory is used to derive the control profiles. However, that work considered only deterministic systems. Uncertainty being prevalent in all systems, particularly in natural systems, this paper extends that work to analyse uncertain systems. Predator-prey models are used to model the species populations and different control philosophies are compared. Ito mean reverting process is used to model the stochastic process, and stochastic maximum principle is used to derive the control profiles. The results for the objective of FI variance minimization qualitatively agree with those for the deterministic system, while the results for the FI maximization objective differ. It is observed that the instability associated with the FI maximization objective for deterministic systems is absorbed by the noise introduced by the uncertainty. Quantitatively, it is observed that the degree of uncertainty, along with its presence, is also important to identify the most appropriate management strategy.
authors.affiliation: Department of Bioengineering, University of Illinois at Chicago, 851 S. Morgan Street, Chicago, IL 60607, USA.
authors.forename: Y
authors.initials: Y
authors.lastname: Shastri
authors.forename: U
authors.initials: U
authors.lastname: Diwekar
mesh_terms: D000818:Animals; D003247:Conservation of Natural Resources; D017753:Ecosystem; D053476:Extinction, Biological; D020387:Food Chain; D008954:Models, Biological; D011157:Population Dynamics; D011235:Predatory Behavior; D013269:Stochastic Processes; D013598:Systems Theory