ArticleEcology and evolution2026
Estimating Dispersal Kernels for Stream Periphyton Using Drifting Lake Algae.
Article in Ecology and evolution, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Dispersal patterns are a key component of many ecological and evolutionary processes, yet they remain understudied in microbial species due to technical challenges. Stream periphyton is a microbial group of public interest and is frequently used as a bioindicator. While high dispersal capability along streams has been suggested for periphyton, no previous studies have empirically estimated dispersal distances for these taxa. Methods for dispersal quantification cannot be used for periphyton species within the river continuum because it is challenging to identify the source point of a given microalga. We propose therefore using phytoplankton drifting from a lake outlet as a proxy for dispersing stream periphyton. The aims of this study were, first, to test the pertinence of using phytoplankton as a dispersal proxy for periphyton, and second, to estimate dispersal distances of stream periphyton. We conducted settling velocity experiments to estimate and compare the buoyancy of phytoplankton and periphyton taxa, confirming that phytoplankton were broadly suitable as proxies. In a lake outlet stream near Dunedin, New Zealand, we exposed ceramic tiles as standardized substrates at different distances from the outlet to collect settling microalgae. A statistical hydraulic model was developed to describe the potential dispersal distances obtained by settling velocities. Dispersal distances were estimated for seven taxa using densities from tiles and for 26 taxa using settling velocities and the statistical hydraulic model. Median travel distances were around 500 m downstream of the lake outlet, with phytoplankton rarely detected further than 2 km from the source. Overall, our findings pointed to stream turbulence and morphological variability within the same algal taxa as the main determinants of dispersal distance. Our novel approach demonstrates how phytoplankton can be used to infer dispersal distances for stream periphyton, representing an important milestone in quantitatively characterizing dispersal patterns in stream periphyton communities.
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