Capturing biodiversity complexities while accounting for imperfect detection: the application of occupancy-based diversity profiles

Abstract

Measuring the multidimensional diversity properties of a community is of great importance for ecologists, conservationists and stakeholders. Diversity profiles, a plotted series of Hill numbers, simultaneously capture all the common diversity indices. However, diversity profiles require information on species abundance and, although it has been shown that detectability varies greatly between species and study sites, raw count data that do not account for imperfect and varying detection are often used to assess diversity. Hierarchical occupancy models explicitly account for variation in detectability, but they only provide information on occurrence, not abundance.Here, we used simulated animal communities and empirical data from a megadiverse tropical bird community to develop a method that allows estimation of diversity profiles from occupancy models. Specifically, we altered the diversity profile formula to use occupancy probabilities instead of abundance. We further tested a novel occupancy thresholding approach to reduce potential biases in the estimated diversity profiles. Finally, we extended the framework to consider trait or phylogeny-based similarity when calculating diversity profiles for our empirical dataset.The simulation study showed that occupancy-based diversity profiles produced among-community patterns in diversity similar to true abundance diversity profiles, although estimates of occupancy were positively biased for species with low detection probability. While this positive bias could be reduced with occupancy thresholding, the threshold resulted in negative biases in species richness estimates and reduced the ability to reproduce true differences among the simulated communities. Application of our approach to a large bird dataset revealed differential diversity patterns in communities of different habitat types. Accounting for phylogenetic and ecological similarities between species, however, reduced the diversity within and among habitats.Our framework allows for the investigation of the complexity of diversity for incidence data, while accounting for imperfect and varying detection probabilities, as well as species similarities. Visualizing results in the form of diversity profiles facilitates comparison of diversity between sites or across time. Therefore, our extension to the diversity profile framework will be a useful tool for studying and monitoring biodiversity.

A guide to between-community functional dissimilarity measures

“…This framework is the most popular currently (e.g. Veresoglou et al 2014, Abrams et al 2021). Effective numbers of species according to Leinster & Cobbold can be easily partitioned into alpha, and beta components in the multiplicative way.…”