Community-level analysis of spatiotemporal plant dynamics

We present an approach for the analysis of spatiotemporal patterns and scal e-dependence in the dynamics of plant communities that combines well-known methods to reduce complexity arising from the high-dimensionality of ecolog ical data. Our approach takes into account both correlations and autocorrel ations in the structure and dynamics of the community. In application to a sand dune annual plant community, we find answers to questions regarding th e nature of community response in space and time, and identify significant spatiotemporal interactions and spatiotemporal scales. Community-level spat ial correlograms reveal a fixed pattern in time that is not apparent from s pecies-level dynamics. In this sense, the community is shown to be more sta ble than the sum of its parts. This form of stability is not a simple artif act of averaging species-specific responses, and points to some consistency in species interactions. Temporal correlograms are highly spatially-specif ic. In this sense, the inclusion of the spatial information is shown to cha nge our view of temporal dynamics. The relative importance of biological pr ocesses versus an environmental gradient is examined in the temporal commun ity response. We find that community response to rainfall is also spatially -specific and that the temporal autocorrelation dynamics shows similar patt erns even when the effect of rainfall is removed. Our findings are relevant to both empirical and theoretical work aimed at understanding the interact ion between space and time in ecological communities.