Published March 31, 2026 | Version Acceptance
Software Open

Simulating drying and human impacts on river networks to evaluate biological quality indices performance through the lens of metacommunity theory

  • 1. IFREMER–DYNECO/LEBCO
  • 2. University of King Juan Carlos
  • 3. Universitat de Barcelona
  • 4. SHE2 group (Surface Hydrology, Ecology and Erosion), Institute of Environmental Assessment and Water Research (IDAEA, CSIC)
  • 5. Complutense University of Madrid
  • 6. Institut de recerca i tecnologia agroalimentàries (IRTA)

Description

Abstract

Accepted in Journal of Applied Ecology

  1. Incorporating metacommunity perspectives into bioassessment represents a major challenge in managing drying river networks, where drying-induced fragmentation compromises the performance of biological indices to assess their ecological status. Current indices focus on local community responses to stressors and neglect the effect of regional processes, such as spatiotemporal connectivity and dispersal, on metacommunity assembly.
  2. In this work, we explored the effect of drying on the performance of a widely used biological index IBMWP (Iberian Biological Monitoring Working Party) using metacommunity simulations on a synthetic drying river network. We assessed how different gradients of drying-driven fragmentation and human impact extent determine local richness and the biological index scores by combining simulations with biomonitoring information.
  3. We used a coalescent metacommunity model to simulate the exchange of individuals between local communities along synthetic drying river networks subjected to different drying extent, intensity and human impact extent scenarios. Additionally, we considered two major characteristics for each simulated taxon: (i) tolerance to human impacts and (ii) dispersal strategy (flying, swimming, or drifting).
  4. For each simulation, we obtained local richness and the biological index value. Then, we calculated biological index performance, defined as the capacity to distinguish between impacted and non-impacted sites. Finally, we tested our approach in six non-impacted European drying river networks, with available drying information.
  5. Our results showed that low spatiotemporal connectivity consistently led to decreased local richness and low index scores, reflecting poor biological quality. As drying extent and intensity increased, drying-induced fragmentation significantly reduced the biological index performance. With a 50% increase in drying extent, index performance fell around 60% and at high drying levels, it dropped more than 90%. This decay followed a convex pattern, with a marked drop as soon as drying appeared in the catchment and leveling off at higher drying extents.
  6. Synthesis and applications: This work constitutes a first step towards developing simulation-based assessments that incorporate catchment drying patterns to support biomonitoring of drying river networks. Our approach can inform stakeholders when current methods fail and contribute to decision-making on whether adapting current methods is possible or developing new indices is necessary.

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