Data from: Applying community ecological theory to maximize productivity of cultivated biocrusts
Degraded rangelands around the world may benefit from the reestablishment of lost biological soil crusts (biocrusts, soil surface cryptogamic-microbial communities). Cultivation of biocrust organisms is the first step in this process, and may benefit from harnessing species interactions. Species interactions are a dominant force structuring ecological communities. One key element of community structure, species richness, is itself important because it can promote the productivity of the entire community. Here, we use biological soil crusts as a model to test the effects of species interactions on production of biocrust materials for use in ecosystem rehabilitation. We screened eight different moss and lichen species from semi-arid rangelands of Montana, USA, for growth potential under two watering regimes. Mosses generally grew well, but we were unable to cultivate the selected lichen species. We produced a >400% increase in the biomass of one species (Ceratodon purpureus). We tested whether a parasite-host relationship between two lichens could be used to enhance productivity of the parasite species, but this also resulted in no net gain of lichen productivity. Finally, we constructed all possible community combinations from a pool of five moss species to test for overyielding (community productivity exceeding that expected from the growth of community members in monoculture), and to determine both if, and the mode in which, species richness increases productivity. Polycultures yielded more than would be expected based upon the production of community constituents in monoculture. Using structural equation models we determined that there was a modest effect of species richness on community productivity (r = 0.24-0.25), which was independent of a stronger effect of the identity of species in the community (r = 0.41-0.50). These results will contribute to the optimization of biocrust cultivation, promoting the development of this emerging ecological rehabilitation technology.
Greenhouse monitoring data.csv
- Is cited by
- 10.1002/eap.1582 (DOI)