Climatic regulation of environmental heterogeneity and its effects on plant beta diversity

Background/Question/Methods

Environmental heterogeneity is a prime influence on plant species diversity. However, two commonly considered, spatially variable abiotic factors, topography and soil, vary in their predictive power from strong to none between studies. Here we test the effective heterogeneity hypothesis which is a conceptual model of climate/landscape interaction. The model predicts that the magnitude of the effect environmental heterogeneity has on plant diversity depends on local climate. This interaction has a distinct effect on plant species diversity and accounts for some of the previous variation in predictive power that has been observed using topographic or edaphic variability as an explanatory factor. We test the model using field data from central Texas and eastern Tennessee. Plant species abundance data was parsed into alpha and beta components using the program PARTITION then analyzed in relation to topographic and soil moisture variability. This was done at both the local (10m²) and regional scale (62,000m²-100km²).

Results/Conclusions

Data supports the model at the regional scale but not at the local scale. At the regional sclae, the Texas site exhibited a strong positive relationship between plant beta diversity and topographic variability as expected with intermediate climate. One Tennessee site showed no relationship as predicted by the model for mesic climates while the second site had an unexpected, slightly negative relationship. At the local scale, there was no relationship between plant beta diversity, topography, and soil moisture. It is likely that the model failed at the local scale because the scale of resource variability is smaller than the distance over which plant species competitively interact. These results are the first evidence in support of this hypothesis. It is important that this model continue to be tested because of the implications for conservation planning and potential to predict loss or gain of plant species diversity as a result of climate change. The model could predict potential loss or gain of plant species diversity depending on the state of the system and the direction of the climate shift, wetter or drier.