Data from: Dispersal in dendritic networks: ecological consequences on the spatial distribution of population densities

1. Understanding the consequences of spatial structure on ecological
dynamics is a central theme in ecology. Recently, research has recognized
the relevance of river and river-analogue network structures, because
these systems are not only highly diverse but also rapidly changing due to
habitat modifications or species invasions. 2. Much of the previous work
on ecological and evolutionary dynamics in metapopulations and
metacommunities in dendritic river networks has been either using
comparative approaches or was purely theoretical. However, the use of
microcosm experiments provides the unique opportunity to study large-scale
questions in a causal and experimental framework. 3. We conducted
replicated microcosm experiments, in which we manipulated the spatially
explicit network configuration of a landscape and addressed how linear
versus dendritic connectivity affects population dynamics, specifically
the spatial distribution of population densities, and movement behavior of
the protist model organism Tetrahymena pyriformis. We tracked population
densities and individual-level movement behavior of thousands of
individuals over time. 4. At the end of the experiment, we found more
variable population densities between patches in dendritic networks
compared to linear networks, as predicted by theory. Specifically, in
dendritic networks, population densities were higher at nodes that
connected to headwaters compared to the headwaters themselves and to more
central nodes in the network. These differences follow theoretical
predictions and emerged from the different network topologies per se.
These differences in population densities emerged despite weakly
density-dependent movement. 5. We show that differences in network
structure alone can cause characteristic spatial variation in population
densities. While such differences have been postulated by theoretical work
and are the underlying precondition for differential dispersal evolution
in heterogeneous networks, our results may be the first experimental
demonstration thereof. Furthermore, these population-level dynamics may
affect extinction risks and can upscale to previously shown metacommunity
level diversity dynamics. Given that many species in natural river systems
exhibit strong spatio-temporal patterns in population densities, our work
suggests that abundance patterns should not only be addressed from a local
environmental perspective, but may be the outcome of processes that are
inherently driven by the respective habitat network structure.