A graphical null model for scaling biodiversity-ecosystem functioning relationships

1. Global biodiversity is declining at rates faster than at any other point in human history. Experimental manipulations at small spatial scales have demonstrated that communities with fewer species consistently produce less biomass than higher diversity communities. Understanding how the global extinction crisis is likely to impact global ecosystem functioning requires applying these local experimental results at substantially larger spatial and temporal scales. 2. Here we propose a null model for scaling biodiversity-ecosystem functioning relationships using observed macroecological patterns. We use species-area and biomass-area curves to predict species richness – biomass relationships at multiple scales and validate these predictions with data from a Minnesota grassland and a Panamanian tropical dry forest. 3. Our null model accurately predicts species richness-biomass relationships across scales from these species-area and biomass-area relationships. However, we note two important caveats that will increase our ability to apply experimentally collected data to the global scale problem of species loss. First when ecosystem functioning is measured as per unit area (e.g., biomass m-2), as is common in biodiversity-ecosystem functioning experiments, the slope of the biodiversity ecosystem functioning relationship should decrease with increasing scale. Alternatively, when ecosystem functioning is not measured per unit area (e.g., summed total biomass), as is common in scaling studies, the slope of the biodiversity-ecosystem functioning relationship should increase with increasing spatial scale. Second, the underlying macroecological patterns of biodiversity experiments are predictably different from some naturally assembled systems. For example, in non-successional naturally assembled ecosystem, biomass is unlikely to change directionally through time. Biodiversity-ecosystem functioning experiments, however, often start from bare ground and biomass increases through time. From these underlying patterns, we would predict that the slope of the biodiversity-productivity relationship in a naturally assembled system not undergoing succession would decrease with increasing time. Alternatively, in an experiment we would predict an increase over time. 4. This paper provides a simple but novel null hypothesis for scaling any relationship between biodiversity and any ecosystem function in space and time. These predictions provide crucial insights into how and when we can extend results from small scale biodiversity experiments to naturally assembled regional and global ecosystems.I have included usage notes with the R code in an R markdown document