The Optimality of Decision Making During Motor Learning

In our daily lives, we often must predict how well we are going to perform in the future based on an evaluation of our current performance and an assessment of how much we will improve with practice. Such predictions can be used to decide whether to invest our time and energy in learning and, if we opt to invest, what rewards we may gain. This thesis investigated whether people are capable of tracking their own learning (i.e. current and future motor ability) and exploiting that information to make decisions related to task reward. In experiment one, participants performed a target aiming task under a visuomotor rotation such that they initially missed the target but gradually improved. After briefly practicing the task, they were asked to select rewards for hits and misses applied to subsequent performance in the task, where selecting a higher reward for hits came at a cost of receiving a lower reward for misses. We found that participants made decisions that were in the direction of optimal and therefore demonstrated knowledge of future task performance. In experiment two, participants learned a novel target aiming task in which they were rewarded for target hits. Every five trials, they could choose a target size which varied inversely with reward value. Although participants’ decisions deviated from optimal, a model suggested that they took into account both past performance, and predicted future performance, when making their decisions. Together, these experiments suggest that people are capable of tracking their own learning and using that information to make sensible decisions related to reward maximization.

Biological Impacts and Uses of Black Bass Competitive Fishing Tournaments on Large Lake Systems

Recreational fisheries in North America are valued between $47.3 billion and $56.8 billion. Fisheries managers must make strategic decisions based on sound science and knowledge of population ecology, to effectively conserve populations. Competitive fishing, in the form of tournaments, has become an important part of recreational fisheries, and is common on large waterbodies including the Great Lakes. Black Bass, Micropterus spp., are top predators and among the most sought after species in competitive catch-and-release tournaments. This study investigated catch-and-release tournaments as an assessment tool through mark-recapture for Largemouth Bass (>305mm) populations in the Tri Lakes, and Bay of Quinte, part of the eastern basin of Lake Ontario. The population in the Tri Lakes (1999-2002) was estimated to be stable between 21,928-29,780, and the population in the Bay of Quinte (2012-2015) was estimated to be between 31,825-54,029 fish. Survival in the Tri Lakes varied throughout the study period, from 31%-54%; while survival in the Bay of Quinte remained stable at 63%. Differences in survival may be due to differences in fishing pressure, as 34-46% of the Largemouth Bass population on the Tri Lakes is harvested annually and only 19% of catch was attributed to tournament angling. Many biological issues still surround catch-and-release tournaments, particularly concerning displacement from initial capture sites. In the past, the majority of studies have focused on small inland lakes and coastal areas, displacing bass relatively short distances. My study displaced Largemouth and Smallmouth Bass up to 100km, and found very low rates of return; only 1 of 18 Largemouth Bass returned 15 km and 1 of 18 Smallmouth Bass returned 135 km. Both species remained near the release sites for an average of approximately 2 weeks prior to dispersing. Tournament organizers should consider the use of satellite release locations to facilitate dispersal and prevent stockpiling at the release site. Catch-and-release tournaments proved to be a valuable tool in assessing population variables and the effects of long distance displacement through the use of mark recapture and acoustic telemetry on large lake systems.