Modeling Diapause Termination of Rhipicephalus Appendiculatus using Statistical Tools to Detect Sudden Behavioral Changes and Time Dependencies

This paper presents statistical methodology to analyze longitudinal binary responses for which a sudden change in the response occurs in time. Probability plots, transition matrices, and change-point models and more advanced techniques such as generalized auto-regression models and hidden Markov chains are presented and applied on a study on the activity of Rhipicephalus appendiculatus, the major vector of Theileria parva, a fatal disease in cattle. This study presents individual measurements on female R. appendiculatus, which are terminating their diapause (resting status) and become active. Comprehending activity patterns is very important to better understand the ecology of R. appendiculatus. The model indicates that activity and non-activity act in an absorbing way meaning that once a tick becomes active it shows a tendency to remain active. The change-point model estimates that the sudden change in activity happens on December 10. The reaction of ticks on acceleration and changes in rainfall and temperature indicates that ticks can sense climatic changes. The study revealed the underlying not visually observable states during diapause development of the adult tick of R. appendiculatus. These states could be related to phases during the dynamic event of diapause development and post-diapause activity in R. appendiculatus.     

Urban Flood Damage and Greenhouse Scenarios - The Implications for Policy: An Example from Australia

Urban flooding is often used as an illustration of the potentially adverse effects of greenhouse-induced climate change on extreme events. There is however, a paucity of studies that convert climate scenarios into changes in flood damage. This account summarises the use of modelling techniques, for three flood prone urban catchments in south eastern Australia, to assess changes to urban flood losses for the 'most wet' and 'most dry' scenarios for the year 2070. The most wet scenario indicates that annual average flood damage could increase within the range of 2.5 to 10 times, under the most dry scenario flood regimes would be similar to those experienced at present. The socio-economic scenarios based on the changes to flood losses are used to consider policy responses. It is unlikely that many local government authorities will respond because of lack of interest and because of major changes to the climate scenarios proposed over the last decade. Any response is likely to be incremental and accord with the 'no regrets' and the precautionary principle'.