Mapping Dynamic Exposure: Constructing GIS Models of Spatiotemporal Heterogeneity in Artificial Stream Systems

  • Kristi K. Weighman
  • Paul A. MooreEmail author


In flowing environments, the degree of turbulent flow determines the movement and distribution of chemicals. Variation in flow alters the patchiness of toxicant plumes within a stream ecosystem. This patchiness translates into variability in exposure pulses for organisms encountering the toxic plume. Throughout a stream, the processes that give rise to chemical plume structure will vary as a function of local flow characteristics. This research examines the influence of toxicant mode of entry and stream flow velocity on the spatiotemporal patterning of exposure. Two introduction treatments were evaluated: one mimicking groundwater and the other mimicking runoff. The influence of flow regime was examined through the comparison of models constructed under two stream flow velocities. Concentrations of a tracer molecule were recorded using an electrochemical monitoring system. From these localized, direct measurements, geographic information systems (GIS) were used to model exposure throughout the stream. Conceptualizing exposure as a series of toxicant pulses, exposure can be defined using a variety of chemical peak characteristics. Three-dimensional, layered maps were constructed defining exposure as the integrated area of toxicant peaks, the magnitude of peaks, and peak frequency. Differences in the spatial and temporal patterning of exposure were apparent both within treatments and between treatments. No two definitions of exposure yielded the same exposure distributions for any treatment. These models demonstrate that distribution of chemical exposure throughout a stream ecosystem is linked to both toxicant mode of introduction and stream hydrodynamics. Furthermore, these results demonstrate that optimal exposure modeling relies on first defining exposure.



The authors thank the Laboratory for Sensory Ecology for their continued support and guidance throughout this project. Special thanks also go out to the University of Michigan Biological Station for funding through the Marian P. and David M. Gates Graduate Student Endowment Fund to K.K.W. and for the use of facilities. Lastly, thank you to Bowling Green State University Faculty Research Committee for a Building Strength Award and a Fulbright Fellowship to P. A. M. for help in funding work essential to the development of this Project.

Supplementary material

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© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Laboratory for Sensory Ecology, Department of Biological SciencesBowling Green State UniversityBowling GreenUSA
  2. 2.University of Michigan Biological StationPellstonUSA
  3. 3.J.P. Scott Center for Neuroscience, Mind and BehaviorBowling Green State UniversityBowling GreenUSA

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