Abstract
Summary1. Atmospheric ammonia (NH3) is one of the main drivers for ecosystem changes world‐wide, including biodiversity loss. Modelling its deposition to evaluate its impact on ecosystems has been the focus of many studies. For that, universal indicators are needed to determine and compare the early effects of NH3 across ecosystems.2. We evaluate the effects of atmospheric NH3 in ecosystems using lichens, which are one of the most sensitive communities at the ecosystem level. Rather than measuring total diversity, we use a functional diversity approach because this is potentially a more universal tool.3. We evaluated the spatial and temporal patterns of atmospheric NH3 concentrations ([NH3]atm) emitted from a point‐source over a 1‐year period in a cork oak Mediterranean woodland. We observed a temporal pattern of [NH3]atm, with maximum concentrations during autumn.4. The distribution of lichen species was c. 90% explained by [NH3]atm. The tolerance of lichen species to atmospheric NH3, based on expert knowledge from literature, was tested for the first time against direct measurements of atmospheric NH3. Most species were well classified, with the exception of Lecanora albella and Chrysothrix candelaris, which were more tolerant than expected. Our updated lichen classification can be used to establish lichen functional groups that respond to atmospheric NH3, and these can be used in other Mediterranean countries.5. Increasing [NH3]atm led to a complete replacement of oligotrophic by nitrophytic species within 65 m of the NH3 source. The geostatistical analysis of functional diversity variables yielded a spatial model with low non‐spatial variance, indicating that these variables can cope robustly with high spatial variation in NH3.6. Synthesis and applications. Our results support the use of functional diversity variables, such as a lichen diversity value, as accurate and robust indicators of the effects of atmospheric NH3 on ecosystems. The spatial modelling of these indicators can provide information with high spatial resolution about the effects of atmospheric NH3 around point‐ and diffuse sources. As this methodology is based on functional groups, it can be applied to monitor both the impact of atmospheric NH3 and the success of mitigation strategies.
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