Vulnerability and adaptation to climate change in Guam – a case-study of the perceptions, attitudes, behaviors, and knowledge of a small rural community towards their watershed

This thesis argues that examining the attitudes, perceptions, behaviors, and knowledge of a community towards their specific watershed can reveal their social vulnerability to climate change. Understanding and incorporating these elements of the human dimension in coastal zone management will lead to efficient and effective strategies that safeguard the natural resources for the benefit of the community. By having healthy natural resources, ecological and community resilience to climate change will increase, thus decreasing vulnerability. In the Pacific Ocean, climate and SLR are strongly modulated by the El Niño Southern Oscillation. SLR is three times the global average in the Western Pacific Ocean (Merrifield and Maltrud 2011; Merrifield 2011). Changes in annual rainfall in the Western North Pacific sub‐region from 1950-2010 show that islands in the east are getting much less than in the past, while the islands in the west are getting slightly more rainfall (Keener et al. 2013). For Guam, a small island owned by the United States and located in the Western Pacific Ocean, these factors mean that SLR is higher than any other place in the world and will most likely see increased precipitation. Knowing this, the social vulnerability may be examined. Thus, a case-study of the community residing in the Manell and Geus watersheds was conducted on the island of Guam. Measuring their perceptions, attitudes, knowledge, and behaviors should bring to light their vulnerability to climate change. In order to accomplish this, a household survey was administered from July through August 2010. Approximately 350 surveys were analysed using SPSS. To supplement this quantitative data, informal interviews were conducted with the elders of the community to glean traditional ecological knowledge about perceived climate change. A GIS analysis was conducted to understand the physical geography of the Manell and Geus watersheds. This information about the human dimension is valuable to CZM managers. It may be incorporated into strategic watershed plans, to better administer the natural resources within the coastal zone. The research conducted in this thesis is the basis of a recent watershed management plan for the Guam Coastal Management Program (see King 2014).

Monitoring and modelling the morphodynamic evolution of a breached barrier beach system

Predicting the evolution of a coastal cell requires the identification of the key drivers of morphology. Soft coastlines are naturally dynamic but severe storm events and even human intervention can accelerate any changes that are occurring. However, when erosive events such as barrier breaching occur with no obvious contributory factors, a deeper understanding of the underlying coastal processes is required. Ideally conclusions on morphological drivers should be drawn from field data collection and remote sensing over a long period of time. Unfortunately, when the Rossbeigh barrier beach in Dingle Bay, County Kerry, began to erode rapidly in the early 2000’s, eventually leading to it breaching in 2008, no such baseline data existed. This thesis presents a study of the morphodynamic evolution of the Inner Dingle Bay coastal system. The study combines existing coastal zone analysis approaches with experimental field data collection techniques and a novel approach to long term morphodynamic modelling to predict the evolution of the barrier beach inlet system. A conceptual model describing the long term evolution of Inner Dingle Bay in 5 stages post breaching was developed. The dominant coastal processes driving the evolution of the coastal system were identified and quantified. A new methodology of long term process based numerical modelling approach to coastal evolution was developed. This method was used to predict over 20 years of coastal evolution in Inner Dingle Bay. On a broader context this thesis utilised several experimental coastal zone data collection and analysis methods such as ocean radar and grain size trend analysis. These were applied during the study and their suitability to a dynamic coastal system was assessed.