Can we predict performance and spatial structure of two-species mixtures using only single species information from monocultures?
Abstrakt
Understanding the behavior of mixtures of species based solely on knowledge of the individual (component) species remains a big challenge for plant ecology. We used the observed outcome of two-species mixtures from a garden competition experiment with five clonal sedge species (two runners and three clumpers), and compared the data with predictions from a highly parameterized simulation model based only on monoculture data of these species.
After two growing seasons (i.e., 300 growing days), overall performance of the mixtures (total biomass and ramet number of the mixtures, proportion of the biomass and ramet number of each species) was predicted rather well by the simulation model and the simulated variables were all within the 50% fit of observed values. Therefore, the single-species parameterization can capture most of the important processes that determine species behavior in the mixture and there is strong equivalence of species and a weak species-specific effect.
This study demonstrates the power of modeling studies to perform virtual experiments for explicit hypothesis testing. Using this approach, we show that performance of mixtures can be realistically predicted by models parameterized and calibrated based on single species information.