Placing local plant species richness in the context of environmental drivers of metacommunity richness
M.H.H. Stevens (e-mail email@example.com).
- 1Ecologists seem poised to reap the benefits of recent work examining the effects of energy and resources on plant taxonomic richness in local communities. My goal here is to present a qualitative model to further our understanding about the driving forces of plant taxonomic richness across spatial scales.
- 2The model attempts to predict local plant species richness based on previous work regarding (i) correlations between temperature, precipitation and richness, (ii) correlations between soil nutrient availability and richness derived from both descriptions and experimental manipulations, and (iii) empirical demonstrations of the importance of the species pool in regulating local species richness.
- 3The model consists of a phenomenlogical submodel of the multiplicative effects of temperature, water and mineral nutrients on plant species richness, with a spatially implicit submodel of immigration and extinction of species in local communities.
- 4The model makes the following five testable predictions. (i) Local richness increases linearly with immigration rate of new species and curvilinearly with local extinction rate. (ii) The effects of altered local immigration and extinction rates will be most apparent in local communities embedded in species-rich metacommunities. (iii) Local communities are not saturated, but rather increase in richness directly with increasing metacommunity richness. (iv) Unimodal or hump-shaped productivity-richness relations arise when low water or temperature limit diversity at low productivity and mineral nutrients limit diversity at high productivity. (v) An apparent scale-dependence of the effect productivity on richness should arise when there exists a matching scale-dependence of the underlying environmental drivers. These predictions do not contrast sharply with available data, but remain largely untested.
- 5I suggest that continued attempts to synthesize the most predictive patterns emerging from the burgeoning global data bases of both taxonomic and genetic diversity will guide us toward mechanistic explanations of the determinants of species richness, suggest why special cases differ from general patterns, and provide additional novel predictions not currently apparent.