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Environmental DNA (eDNA) monitoring of freshwater fish populations is now more accurate. A new integrated model links eDNA concentrations to fish abundance, improving conservation efforts and detecting population changes due to natural events or harvesting.

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Area of Science:

  • Ecology
  • Conservation Biology
  • Environmental Science

Background:

  • Freshwater biodiversity faces a crisis due to human activities.
  • Traditional population monitoring methods are invasive and costly.
  • Environmental DNA (eDNA) shows potential for monitoring but faces challenges in natural settings.

Purpose of the Study:

  • To develop a novel modeling method for estimating freshwater fish population abundance using eDNA.
  • To address the decoupling of eDNA concentration and abundance in natural ecosystems.
  • To validate the model using Brook Trout populations in the Rocky Mountains.

Main Methods:

  • Integrated bioenergetics and mass-balance frameworks to model eDNA concentration.
  • Related eDNA to fish abundance estimates from mark-recapture data.
  • Applied the model to Brook Trout populations across nine lakes, including those with size-selective harvesting.

Main Results:

  • The integrated model significantly improved the variance explained in eDNA concentrations from 24% to 71%.
  • The model accurately distinguished abundance estimates (94%) across populations and sampling periods.
  • The model detected both natural and harvest-induced population reductions.

Conclusions:

  • This study presents the first empirical integration of DNA production and particle dynamics for eDNA abundance estimation.
  • The novel methodological approach enables rapid and accurate quantification of fish populations.
  • The developed tool can be integrated into existing biodiversity monitoring programs.