, Volume 142, Issue 2, pp 159-168
Date: 14 Oct 2004

Mosses and the struggle for light in a nitrogen-polluted world

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The impact of reduced light conditions as an indirect effect of nitrogen (N) deposition was determined on three mosses in a montane ecosystem, where sedge and grass cover increase due to N enrichment. Additionally, in the greenhouse we established the importance of low light to moss growth as an indirect N deposition effect relative to the direct toxic effects of N. The amount of light reaching the moss layer was strongly and negatively related to graminoid abundance. Mosses showed differing sensitivities to reduced light in the field. Racomitrium lanuginosum biomass was found to be highest under high-light conditions, Polytrichum alpinum at intermediate light levels, whilst that of Dicranum fuscescens was unrelated to light availability. Moreover, Racomitrium biomass decreased with increasing amounts of graminoid litter, whereas the other species were little affected. All three mosses responded differently to the combination of elevated N (20 vs 10 kg N ha−1 year−1) and reduced light (60 and 80% reduction) in the greenhouse. Racomitrium growth was strongly influenced by both light reduction and elevated N, in combination reducing shoot biomass up to 76%. There was a tendency for Dicranum growth to be modestly reduced by elevated N when shaded, causing up to 19% growth reduction. Polytrichum growth was not influenced by elevated N but was reduced up to 40% by shading. We conclude that competition for light, induced by vascular plants, can strongly influence moss performance even in unproductive low biomass ecosystems. The effects of reduced light arising from N pollution can be as important to mosses as direct toxicity from N deposition. Yet, different sensitivities of mosses to both toxic and shading effects of elevated N prevent generalisation and can lead to competitive species replacement within moss communities. This study demonstrates the importance of understanding moss-vascular plant interactions to allow interpretation and prediction of ecosystem responses to anthropogenic drivers such as atmospheric N deposition or climate change.