Abstract. High-impact floods have become a virtually annual experience in Malaysia, yet flood insurance has remained a grossly neglected part of comprehensive integrated flood risk management. Using discriminant analysis, this study seeks to identify the demand-side variables that best predict flood insurance purchase and risk aversion between two groups of residential homeowners in three districts of Johor State, Malaysia: those who purchased flood insurance and those who did not. Our results revealed an overall 34 % purchase rate, with Kota Tinggi district having the highest (44 %) and thus the highest degree of flood risk aversion. The Wilks' lambda F test for equality of group means, standardised discriminant function coefficients, structure correlation, and canonical correlation has clearly shown that there are strong significant attribute differences between the two groups of homeowners, based on the measures of objective flood risk exposure, subjective risk perception, and socioeconomic cum demographic variables. However, the measures of subjective risk perception were found to be more predictive of flood insurance purchase and flood risk aversion.

Abstract. High impact flood has virtually become an annual experience in Malaysia, yet flood insurance has remained a grossly neglected part of comprehensive integrated flood risk management. Using discriminant analysis, this study seeks to indentify the demand-side variables that best predict flood insurance penetration and risk aversion between two groups of residential homeowners in three districts of Johor State, Malaysia: those who purchased flood insurance and the group that did not. Our result revealed 34% penetration rate with Kota Tinggi district having the highest penetration (44%) and thus, the highest degree of flood risk aversion. The Wilks' Lambda F test for equality of group means, SCDFC, structure correlation and canonical correlation have clearly shown that there are strong significant attribute differences between the two groups of homeowners based on measures of objective flood risk exposure, subjective risk perception, and socio-economic cum demographic variables. However, measures of subjective risk perception were found more predictive of flood insurance penetration and flood risk aversion.

No abstract

Efforts to monitor terrestrial decomposition dynamics at broad spatial scales are hampered by the lack of a cost-effective and scalable means to track the decomposition process. Recent advances in remote sensing have enabled the simulation of litter spectra throughout decomposition for grasses in general, yet unique decomposition pathways are hypothesized to create subtly different litter spectral signatures with unique ecosystem functional significance. The objectives of this study were to improve spectra–decomposition linkages and thereby enable the more comprehensive monitoring of ecosystem processes such as nutrient and carbon cycles. Using close-range hyperspectral imaging, litter spectra and multiple decomposition metrics were concurrently monitored in four classes of naturally decayed litter under four decomposition treatments. The first principal component accounted for approximately 94% of spectral variation in the close-range imagery and was attributed to the progression of decomposition. Decomposition-induced spectral changes were moderately correlated with the leaf carbon to nitrogen ratio (R2 = 0.52) and sodium hydroxide extractables (R2 = 0.45) but had no correlation with carbon dioxide flux. Temperature and humidity strongly influenced the decomposition process but did not influence spectral variability or the patterns of surface decomposition. The outcome of the study is that litter spectra are linked to important metrics of decomposition and thus remote sensing could be utilized to assess decomposition dynamics and the implications for nutrient recycling at broad spatial scales. A secondary study outcome is the need to resolve methodological challenges related to inducing unique decomposition pathways in a lab environment. Improving decomposition treatments that mimic real-world conditions of temperature, humidity, insolation, and the decomposer community will enable an improved understanding of the impacts of climatic change, which are expected to strongly affect microbially mediated decomposition.