Indices for monitoring biodiversity change: Are some more effective than others?

Statistically rigorous methods for summarizing and reporting trends in the intactness of biodiversity are a key element of effective biodiversity monitoring programs. There are four major approaches for translating complex monitoring data into easily communicated summary statistics: (1) traditional diversity indices such as species richness and Simpson's diversity, (2) species intactness indices based on occurrence, (3) species intactness indices based on abundance, and (4) multivariate community indices. We use simulated data to evaluate the effectiveness of 13 indices from these four categories based on statistical robustness, sensitivity to errors and noise in the data, ecological relevance, and ease of communication. We show that indices that calculate species intactness using equations like Buckland's arithmetic mean index are the most effective for use in large-scale biodiversity intactness monitoring programs. Traditional diversity indices are unsuitable for monitoring of biodiversity intactness, and multivariate indices can be highly sensitive to errors and noise in the data. Finally, we provide guidelines for the application of these indices in biodiversity intactness monitoring.