PS 19-28
Environmental factors affect diversity through shifts in species abundances

Tuesday, August 6, 2013
Exhibit Hall B, Minneapolis Convention Center
Matthew S. Schuler, Dept. of Biological Sciences, Rensselaer Polytechnic Institute, Troy, NY

For nearly a century, ecologists have attempted to define the most influential factors that drive patterns of biodiversity. Yet, we have a minimal understanding of how environmental factors interact to affect species richness patterns. Macroecological studies have found that environmental factors like energy and area interact to affect species richness. However, the mechanisms of these patterns cannot be determined using global species richness datasets, because these data lack information about species abundances. To better understand how environmental factors interact to affect biodiversity, I experimentally manipulated energy input and area in aquatic mesocosms. Using a fully factorial design, I stocked aquatic mesocosms with a regional species pool of zooplankton (50 species) and assessed how energy and area affected other environmental factors to understand what mechanisms directly influenced any changes in species richness. 


The results from this experiment indicate that energy input and habitat area interact to affect species richness patterns. Large, high-energy mesocosms had higher species richness per volume of water than large, homogenous mesocosms. However, small high and low-energy mesocosms did not differ in species richness. The difference in species richness, however, was only due to differences in total abundances of species. Increased energy in large habitats allowed for more individuals per unit volume of water, which allowed for higher observed species richness. Macroecological studies indicating that species richness patterns are driven by an interaction between energy and area failed to account for shifts in the abundances of species among habitats. Therefore, researchers should account for species abundance differences among habitats using Hurlbert’s PIE (Gini-Simpson index).