Predicting catchment suitability for biodiversity at national scales

Area of Science:

• Freshwater ecology
• Conservation biology
• Environmental management

Background:

• Biomonitoring of water quality and catchment management are often disconnected due to scale mismatches.
• Traditional freshwater biomonitoring focuses on organic pollution indicators, often ignoring threatened or invasive species.
• Existing data on rare/invasive species can be repurposed for broader biomonitoring applications.

Purpose of the Study:

• To demonstrate a proof-of-concept for linking catchment-scale management of freshwater ecosystems and biodiversity.
• To use extensive species records to connect biodiversity to potential environmental drivers across England.
• To develop new biomonitoring tools for catchment managers.

Main Methods:

• Utilized national land use and water quality datasets for England.
• Employed predictive modeling to assess the presence/absence of 48 focal threatened or invasive species at the catchment scale.
• Validated model accuracy using receiver operating characteristic curves.

Main Results:

• Achieved a median prediction accuracy of 0.81 for species presence/absence.
• Identified water quality indicators and land-use types as significant predictors.
• Highlighted the critical importance of freshwater coverage within a catchment for supporting biodiversity.

Conclusions:

• Repurposing biomonitoring data can link water quality control to biodiversity protection.
• The developed method can inform new catchment management strategies and prioritize restoration efforts.
• This approach represents a significant step towards integrated catchment management linking controllable drivers to protected biota.