Abstract
The growing interest in combining spatial and temporal patterns in nature has
been fostered by the current availability of high-frequency measurements.
However, we still lack a methodological framework to process and interpret
spatiotemporal datasets into meaningful values, adaptable to different time
windows and/or responding to different spatial structures. Here, we developed
and tested a framework to evaluate spatiotemporal connectivity using two new
measures: the spatiotemporal connectivity (STcon) and the spatiotemporal
connectivity matrix (STconmat). To obtain these measures, we consider a set of
spatially connected sites within a temporally dynamic network. These measures
are calculated from a spatiotemporal matrix where spatial and temporal
connections across sites are captured. These connections respond to a determined
network structure, assign different values to these connections and generate
different scenarios from which we obtain the spatiotemporal connectivity. We
developed these measures by using a dataset of stream flow state spanning a
513-day period obtained from data loggers installed in seven temporary streams.
These measures allowed us to characterise connectivity among stream reaches and
relate spatiotemporal patterns with macroinvertebrate community structure and
composition. Spatiotemporal connectivity differed within and among streams, with
STcon and STconmat capturing different hydrological patterns. Macroinvertebrate
richness and diversity were higher in more spatiotemporally connected sites.
Community dissimilarity was related to STconmat showing that more
spatiotemporally connected sites had similar communities for active and passive
dispersers. Interestingly, both groups were related to spatiotemporal
connectivity patterns for some of the analysed scenarios, highlighting the
relevance of spatiotemporal connectivity in dynamic systems. As we exemplified,
the proposed framework can help to disentangle and quantify spatiotemporal
dynamics or be applied in the conservation of dynamic systems such as temporary
streams. However, the current framework is not limited to the temporal and
spatial features of temporary streams. It can be extended to other ecosystems by
including different time windows and/or consider different network structures to
assess spatiotemporal patterns. Such spatiotemporal measures are especially
relevant in a context of global change, with the spatiotemporal dynamics of
ecosystems being heavily disrupted by human activities.
Publication
Methods in Ecology and Evolution