Skip to main content
Dryad

Data from: Disturbance reverses classic biodiversity predictions in river-like landscapes

Cite this dataset

Harvey, Eric; Gounand, Isabelle; Fronhofer, Emanuel A.; Altermatt, Florian (2018). Data from: Disturbance reverses classic biodiversity predictions in river-like landscapes [Dataset]. Dryad. https://doi.org/10.5061/dryad.pm4n81q

Abstract

Global analyses of biodiversity consistently reveal recurrent patterns of species distributions worldwide. However, unveiling the specific mechanisms behind those patterns remains logistically challenging, yet necessary for reliable biodiversity forecasts. Here, we combine theory and experiments to investigate the processes underlying spatial biodiversity patterns in dendritic, river-like landscapes, iconic examples of highly threatened ecosystems. We used geometric scaling properties, common to all rivers, to show that the distribution of biodiversity in these landscapes fundamentally depends on how ecological selection is modulated across space: while uniform ecological selection across the network leads to higher diversity in downstream confluences, this pattern can be inverted by disturbances when population turnover (i.e., local mortality) is higher upstream than downstream. Higher turnover in small headwater patches can slow down ecological selection, increasing local diversity in comparison to large downstream confluences. Our results show that disturbance-mediated slowing down of competitive exclusion can generate a specific transient signature in terms of biodiversity distribution when applied over a spatial gradient of disturbance, which is a common feature of many river landscapes.

Usage notes