AI Summary & Key Takeaways
AI InsightSampling strategies involvingpleurocarpousmoss species have thepotential to inform traditional monitoring networks towards improved spatial mapping of N deposition.
📌 3 Key Takeaways
Özet
Emissions from fossil fuel combustion and intensive agriculture have led to a significant increase in globalatmospheric concentrations of reactive nitrogen (Nr). Traditional monitoring networks do not capture the highspatial variability of Nr emissions sources; as such,pleurocarpousmoss species have been used as a biomonitor forNr deposition. Tissue concentrations of nitrogen (%N) in the moss speciesHylocomium splendensat more than100 locations in Ireland were used in conjunction with environmental variables (e.g., mean temperature (°C),sun hours, rain (mm), distance to coast) to determine predictive models of total nitrogen (N) deposition (kg Nha−1yr−1) and atmospheric ammonia (NH3) concentrations (μgm−3). Tissue N concentrations ranged from 0.5to 1.2%, with an average of 0.8%; concentrations showed a (low−high) gradient from the west (Atlantic) coastto the east coast. Univariate regression analysis showed that %N tissue concentrations and environmentalvariables had similar spatial trends and associations. Tissue N concentrations had a stronger relationship withtotal N deposition compared with atmospheric NH3(R2= 0.2, p < 0.001; R2= 0.1, p < 0.001, respectively).The best predictive model (based on backwards stepwise multiple regression, with model selection based oncorrected Akaike Information Criterion) for total N deposition included tissue N concentrations; however, themodel for atmospheric NH3only included environmental variables (Total N deposition: R2= 0.61, p < 0.001;atmospheric NH3:R2= 0.73, p < 0.001). Sampling strategies involvingpleurocarpousmoss species have thepotential to inform traditional monitoring networks towards improved spatial mapping of N deposition.