Predicting dissolved inorganic nitrogen leaching in European forests using two independent databases

Area of Science:

• Environmental Science
• Forest Ecology
• Biogeochemistry

Background:

• Regional databases are crucial for understanding nitrogen (N) leaching in forests and its environmental drivers.
• Assessing risks like acidification and eutrophication requires identifying N leaching correlates.
• Large, independent datasets are necessary for robust model development and validation.

Purpose of the Study:

• To develop and validate indicators of nitrogen saturation and leaching in European forest ecosystems.
• To identify key environmental drivers influencing nitrogen leaching.
• To assess the predictive power of models for nitrogen leaching.

Main Methods:

• Utilized two large, independent European forest ecosystem databases for model development and validation.
• Considered 35 potential environmental variables influencing nitrogen leaching.
• Developed and tested predictive models for nitrogen leaching based on selected indicators.

Main Results:

• Throughfall N deposition, organic horizon C:N ratio, and mean annual temperature were the most consistent indicators of N leaching.
• Models successfully predicted N leaching (mean error +/-5 kg N ha(-1) y(-1)) in forests at early to intermediate stages of nitrogen saturation.
• Sites with low N deposition (<8 kg N ha(-1) y(-1)) were simulated separately due to low N output fluxes.

Conclusions:

• Simple relationships combining external drivers (deposition, temperature) and site conditions (soil N status) can estimate nitrogen leaching.
• Models are effective for forests not yet severely damaged by nitrogen deposition.
• Further research may be needed for highly nitrogen-saturated forest ecosystems.