Maximal species richness: an empirical approach for evaluating woody plant forest biodiversity

Different approaches have been used to determine reference values for species richness, usually as an estimate of potential biodiversity. But, there are practical and theoretical problems with the measurement and concept of potential biodiversity. Here we propose an empirical statistical approach to estimate maximum richness for woody plants. Using a large forest inventory data set from Catalonia (NE Spain), we analyse relationships between richness and nine environmental and structural variables. We selected three of the nine variables (annual potential evapotranspiration, canopy cover and undergrowth cover) to model relationships with maximal average species richness for multiple sites and ranges of environmental conditions. We then used linear regression to compare the lowest maximal average species richness predicted by the models for each site with observed values for a different set of plots. We use empirical information from plots, while most usual approaches are based on potential species distribution. Therefore, our method provides more integrative information of the effects of natural drivers and management practices.