Aim Ecological patterns and process change across spatial, temporal and taxonomic scales. This confounds comparisons between modern and fossil communities, which are sampled across very different scales, especially temporal ones. We use a recent bone dataset (i.e., death assemblages) from a modern ecosystem to explore spatial, temporal and taxonomic scaling in biodiversity assessments. Our ultimate goal is to create a model based on these scaling relationships to facilitate meaningful comparisons between modern and fossil communities. LocationTime periodAmboseli National Park, southern Kenya. Mid-1960s to present day. Major taxa studiedMethodsLarge mammals (>1kg). We implemented a random placement null model and used model selection methods to investigate how species richness at Amboseli scales as a function of time and area [i.e., the species-time-area relationship (STAR) model]. We then analysed how the model coefficients change at different taxonomic scales (i.e., genus, family, order). ResultsMain conclusionsIn agreement with previous studies, we find species richness scales positively with time and area but with a negative interaction between the two. Rates of richness turnover decrease as taxonomic scale increases. We hypothesize that decreasing rates of turnover with increasing spatial and/or temporal scale are caused by taking progressively larger samples from a species pool that is changing at a slower rate relative to turnover at the scale of sampling. Because increasing area and time are simply alternative ways of uncovering the species pool, increased time-averaging of communities results in a more spatially averaged ecological signal. Increasing taxonomic scale causes turnover rates to decrease because of how lower-level taxa are aggregated into coarser, higher-level ones. The STAR model presents a framework for extrapolating and comparing richness between small-scale modern and large-scale fossil communities, as well as a means to understand the general processes involved with changing scale.
