Cameron Pellett

The heterogeneity of a variable’s distribution, such as its dispersion, inequality, or information entropy, can have profound effects on other variables, like those observed between habitat heterogeneity and biodiversity, and economic inequality and development. However, how well we understand these relationships hinges precariously on how well we can isolate and accurately characterise heterogeneity mathematically. What I have realised in my research is that presently used measures of heterogeneity are biased by the mean's distance to a variable’s boundaries (e.g. tree heights bounded above zero), which has subsequently distorted observed heterogeneity relationships with other variables in numerous fields. My work has, therefore, been dedicated to developing measures of heterogeneity that are uninfluenced by a variable's boundaries, and applying these new measures to advance ecological theory and environmental monitoring.