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Stream macroinvertebrate community metrics consistently respond to a spatiotemporal disturbance gradient but composition is more context-dependent

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Abstract

Context

Improving our understanding of how riverine communities respond to anthropogenic change requires spatial comparisons across multiple sites, high-resolution temporal analyses, and examination of both taxa and trait responses. However, studies that encompass all these aspects remain scarce.

Objectives

We used 10 years of annual monitoring data from 14 sampling sites in the Rhine-Main-Observatory (a Long-Term Ecological Research—LTER—site in Germany) to investigate spatiotemporal responses of stream macroinvertebrate communities along anthropogenic disturbance gradients (measured as ‘ecological quality’).

Methods

We examined spatiotemporal changes in various community components, including taxa, traits, metrics summarizing community responses (e.g., richness), and community composition.

Results

Spatially, consistent patterns over a decade of sampling revealed that less-disturbed communities were characterized by higher taxonomic and trait diversity and occurrence of pollution-sensitive taxa. Anthropogenic disturbance tended to become less severe through time, particularly in more upstream sites, likely driven by improvements in land-use and water quality. Conversely, more downstream sites exhibited a lesser degree of improvement (or none at all) likely owing to persistent or cumulative stressors. Overall, taxonomic/trait metrics consistently reflected the magnitude of the environmental improvement, while community composition did not, suggesting a weaker link between community changes and anthropogenic impacts severity.

Conclusion

Our results emphasize the importance of accounting for the variability in community responses to anthropogenic changes, and identifying optimal monitoring strategies to track such responses. In heterogeneous catchments, choosing which community component to focus and where to locate monitoring sites (e.g., monitoring ecological quality for the EU Water Framework Directive) can determine a timely detection of anthropogenic impacts.

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Data availability

The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

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Acknowledgements

This work is supported by the Collaborative Research Centre 1439 RESIST (Multilevel Response to Stressor Increase and Decrease in Stream Ecosystems; www.sfb-resist.de) funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)—SFB 1439/1 2021 – 426547801. Peter Haase and James Sinclair received additional funding from the EU Horizon 2020 Project eLTER PLUS (Grand Agreement No. 871128). We thank the Hessian Agency for Nature Conservation, Environment and Geology (HLNUG) for the environmental data, the German Weather Service (DWD) for the climate data, and the Development Bank of Hesse (WIBank) for the InVeKoS data provision.

Funding

This work is supported by the Collaborative Research Centre 1439 RESIST (Multilevel Response to Stressor Increase and Decrease in Stream Ecosystems; www.sfb-resist.de) funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)—SFB 1439/1 2021 – 426547801. Peter Haase and James Sinclair received additional funding from the EU Horizon 2020 Project eLTER PLUS (Grand Agreement No. 871128).

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  1. James S. Sinclair and Peter Haase shares last authorship.

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  1. Faculty of Biology, University of Duisburg-Essen, Essen, Germany

    Hong Hanh Nguyen, Daniel Hering & Peter Haase

  2. Department of River Ecology and Conservation, Senckenberg Research Institute and Natural History Museum, Frankfurt, Germany

    Hong Hanh Nguyen, James S. Sinclair & Peter Haase

  3. Institute for Natural Resource Conservation, Christian-Albrechts-University Kiel, Kiel, Germany

    Jens Kiesel & Kristin Peters

  4. Centre for Water and Environmental Research, University of Duisburg-Essen, Essen, Germany

    Daniel Hering

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PH and HHN designed the study. HHN, JK, and KP acquired data. HHN and JSS performed data analysis. HHN drafted original manuscript. All authors revised and approved the final submitted manuscript.

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Nguyen, H.H., Kiesel, J., Peters, K. et al. Stream macroinvertebrate community metrics consistently respond to a spatiotemporal disturbance gradient but composition is more context-dependent. Landsc Ecol 38, 3133–3151 (2023). https://doi.org/10.1007/s10980-023-01769-w

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