Restoration of forest wetlands: Case studies in Michigan and Finland

Forested wetlands throughout the world are valuable habitats; especially in relatively species-poor northern regions, they can be considered biological hotspots. Unfortunately, these areas have been degraded and destroyed. In recent years, however, the biological importance of wetlands has been increasingly recognized, resulting in the desire to restore disturbed habitats or create in place of destroyed ones. Restoration work is taking place across the globe in a diversity of wetland types, and research must be conducted to determine successful techniques. As a result, two studies of the effects of wetland restoration and creation were conducted in forested wetlands in northern Michigan and southern Finland. In North America, northern white-cedar wetlands have been declining in area, despite attempts to regenerate them. Improved methods for successfully establishing northern white-cedar are needed; as a result, the target of the first study was to determine if creating microtopography could be beneficial for white-cedar recruitment and growth. In northern Europe, spruce swamp forests have become a threatened ecosystem due to extensive drainage for forestry. As part of the restoration of these habitats, i.e. rewetting through ditch blocking, Sphagnum mosses are considered to be a critical element to re-establish, and an in-depth analysis of how Sphagnum is responding to restoration in spruce swamp forests has not been previously done. As a result, the aim of the second study was to investigate the ecophysiological functioning of Sphagnum and feather mosses across a gradient of pristine, drained, and restored boreal spruce swamp forests.

A NATURALISTIC COMPUTATIONAL MODEL OF HUMAN BEHAVIOR IN NAVIGATION AND SEARCH TASKS

Planning, navigation, and search are fundamental human cognitive abilities central to spatial problem solving in search and rescue, law enforcement, and military operations. Despite a wealth of literature concerning naturalistic spatial problem solving in animals, literature on naturalistic spatial problem solving in humans is comparatively lacking and generally conducted by separate camps among which there is little crosstalk. Addressing this deficiency will allow us to predict spatial decision making in operational environments, and understand the factors leading to those decisions. The present dissertation is comprised of two related efforts, (1) a set of empirical research studies intended to identify characteristics of planning, execution, and memory in naturalistic spatial problem solving tasks, and (2) a computational modeling effort to develop a model of naturalistic spatial problem solving. The results of the behavioral studies indicate that problem space hierarchical representations are linear in shape, and that human solutions are produced according to multiple optimization criteria. The Mixed Criteria Model presented in this dissertation accounts for global and local human performance in a traditional and naturalistic Traveling Salesman Problem. The results of the empirical and modeling efforts hold implications for basic and applied science in domains such as problem solving, operations research, human-computer interaction, and artificial intelligence.