STATE-AND-TRANSITION MODELING AND ADAPTIVE MANAGEMENT: TOOLS FOR FUTURE CO-DEVELOPMENT OF MADAGASCAR’S NATURAL RESOURCES AND PEOPLE

Madagascar’s terrestrial and aquatic ecosystems have long supported a unique set of ecological communities, many of whom are endemic to the tropical island. Those same ecosystems have been a source of valuable natural resources to some of the poorest people in the world. Nevertheless, with pride, ingenuity and resourcefulness, the Malagasy people of the southwest coast, being of Vezo identity, subsist with low development fishing techniques aimed at an increasingly threatened host of aquatic seascapes. Mangroves, sea grass bed, and coral reefs of the region are under increased pressure from the general populace for both food provisions and support of economic opportunity. Besides purveyors and extractors, the coastal waters are also subject to a number of natural stressors, including cyclones and invasive, predator species of both flora and fauna. In addition, the aquatic ecosystems of the region are undergoing increased nutrient and sediment runoff due, in part, to Madagascar’s heavy reliance on land for agricultural purposes (Scales, 2011). Moreover, its coastal waters, like so many throughout the world, have been proven to be warming at an alarming rate over the past few decades. In recognizing the intimate interconnectedness of the both the social and ecological systems, conservation organizations have invoked a host of complimentary conservation and social development efforts with the dual aim of preserving or restoring the health of both the coastal ecosystems and the people of the region. This paper provides a way of thinking more holistically about the social-ecological system within a resiliency frame of understanding. Secondly, it applies a platform known as state-and-transition modeling to give form to the process. State-and-transition modeling is an iterative investigation into the physical makeup of a system of study as well as the boundaries and influences on that state, and has been used in restorative ecology for more than a decade. Lastly, that model is sited within an adaptive management scheme that provides a structured, cyclical, objective-oriented process for testing stakeholders cognitive understanding of the ecosystem through a pragmatic implementation and monitoring a host of small-scale interventions developed as part of the adaptive management process. Throughout, evidence of the application of the theories and frameworks are offered, with every effort made to retool conservation-minded development practitioners with a comprehensive strategy for addressing the increasingly fragile social-ecological systems of southwest Madagascar. It is offered, in conclusion, that the seascapes of the region would be an excellent case study worthy of future application of state-and-transition modeling and adaptive management as frameworks for conservation-minded development practitioners whose multiple projects, each with its own objective, have been implemented with a single goal in mind: preserve and protect the state of the supporting environment while providing for the basic needs of the local Malagasy people.

DEVELOPMENT AND VALIDATION OF THE ANTERIOR CRUCIATE LIGAMENT INJURY-RISK-ESTIMATION QUIZ (ACL-IQ)

Over 2 million Anterior Cruciate Ligament (ACL) injuries occur annually worldwide resulting in considerable economic and health burdens (e.g., suffering, surgery, loss of function, risk for re-injury, and osteoarthritis). Current screening methods are effective but they generally rely on expensive and time-consuming biomechanical movement analysis, and thus are impractical solutions. In this dissertation, I report on a series of studies that begins to investigate one potentially efficient alternative to biomechanical screening, namely skilled observational risk assessment (e.g., having experts estimate risk based on observations of athletes movements). Specifically, in Study 1 I discovered that ACL injury risk can be accurately and reliably estimated with nearly instantaneous visual inspection when observed by skilled and knowledgeable professionals. Modern psychometric optimization techniques were then used to develop a robust and efficient 5-item test of ACL injury risk prediction skill—i.e., the ACL Injury-Risk-Estimation Quiz or ACL-IQ. Study 2 cross-validated the results from Study 1 in a larger representative sample of both skilled (Exercise Science/Sports Medicine) and un-skilled (General Population) groups. In accord with research on human expertise, quantitative structural and process modeling of risk estimation indicated that superior performance was largely mediated by specific strategies and skills (e.g., ignoring irrelevant information), independent of domain general cognitive abilities (e.g., metal rotation, general decision skill). These cognitive models suggest that ACL-IQ is a trainable skill, providing a foundation for future research and applications in training, decision support, and ultimately clinical screening investigations. Overall, I present the first evidence that observational ACL injury risk prediction is possible including a robust technology for fast, accurate and reliable measurement—i.e., the ACL-IQ. Discussion focuses on applications and outreach including a web platform that was developed to house the test, provide a repository for further data collection, and increase public and professional awareness and outreach (www.ACL-IQ.org). Future directions and general applications of the skilled movement analysis approach are also discussed.