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Metapopulation-level associations in positively interacting stream fishes

Citation

Kim, Seoghyun; Terui, Akira; Dolph, Christine (2022), Metapopulation-level associations in positively interacting stream fishes, Dryad, Dataset, https://doi.org/10.5061/dryad.np5hqbzv6

Abstract

Positive biotic interactions are recognized as important factors determining species distributions. Although effects of positive interactions have often been observed at local scales, much less is known about consequences at larger spatial scales. Here, we study nest associations of stream fishes - widespread reproductive facilitation between host (nest-builder) and beneficiary (nest associate) species in North America - as a model system to examine the role of positive interactions in determining the metapopulation-level relationship between host and beneficiary species. Using regional data of fish distribution in the Midwestern US, we found that watershed-level occupancy of host species (i.e., metapopulation occupancy) remarkably increased that of nest associates. Our results illustrated that the effects of positive biotic interactions at the metapopulation level were comparable or even stronger than environmental drivers, i.e., factors that have been studied most extensively in metapopulation studies. Further, our model supported the hypothesis that the metapopulation-level relationship between hosts and nest associates was mediated by a gradient of environmental conditions: strong associations occurred under stressful habitats. This study provides insightful evidence that positive biotic interactions have larger scale consequences for distributions of organisms than previously thought. Successful biodiversity conservation may need a broader framework that appreciates the role of positive biotic interactions at larger spatial scales.

Methods

1. Dataset was obtained from five state agencies:

(1) Iowa Department of Natural Resources (Wilton, 2004)

(2) Illinois Environmental Protection Agency and Illinois Department of Natural Resources (ILEPA, 2014)

(3) Minnesota Pollution Control Agency (MPCA, 2014)

(4) Wisconsin Department of Natural Resources (WIDNR, 2018)

Note that the raw data are not available due to licensing issues.

 

2. GIS layers adapted from the following materials are licensed under:

(1)  US National Land Cover Database: (https://doi.org/10.5066/P96HHBIE)

(2) Climatologies at high resolution for the earth’s land surface areas: (https://doi.org/10.1038/s41597-020-00587-y)

(3) MERIT Hydro (high-resolution global hydrography map based on latest topography datasets): (https://doi.org/10.1029/2019WR024873)

(4) Global 1-second water body map version 1.0 (https://doi.org/10.1016/j.rse.2015.10.014)

 

References

Wilton, T. F. 2004. Biological assessment of Iowa's wadeable streams. Iowa Department of Natural Resources, Environmental Protection Division, TMDL and Water Quality Assessment Section. Des Moines, Iowa. https://www.iowadnr.gov/Portals/idnr/uploads/watermonitoring/biological/IA_Stream_Bioassessment.pdf

ILEPA. 2014. Illinois water monitoring strategy 2015-2020, Illinois Environmental Protection Agency, Bureau of Water, Springfield, Illinois. https://www2.illinois.gov/epa/Documents/epa.state.il.us/water/water-quality/monitoring-strategy/monitoring-strategy-2015-2020.pdf

MPCA. 2014. Development of a fish-based index of biological integrity for Minnesota’s rivers and streams. Document number wq-bsm2-03. Minnesota Pollution Control Agency, Environmental Analysis and Outcomes Division, St. Paul, Minnesota. https://www.pca.state.mn.us/sites/default/files/wq-bsm2-03.pdf

WIDNR. 2018. Guidelines for assessing fish communities of wadeable streams in Wisconsin version 2.0. Wisconsin Department of Natural Resources. https://www.nemi.gov/methods/method_summary/12960

Funding

National Science Foundation through a Water Sustainability and Climate Program Observatory grant, Award: EAR‐1209402

Environmental Protection Agency through a Water Quality Benefits grant, Award: EPA224G2015-STAR-A1