Acid–base status mediates the selection of organic habitats by upland stream invertebrates
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Freshwater bryophytes support large numbers of invertebrates, but their importance compared to other organic habitats, e.g. submerged terrestrial leaf-litter, is seldom assessed. There is also little information about how water quality might affect bryophyte–invertebrate interactions. Here, we compare macroinvertebrate colonisation of bryophytes and leaf-litter in streams of contrasting acidity. Litterbags containing the liverwort Nardia compressa, a moss mixture dominated by Platyhypnidium riparioides, and oak leaves (Quercus spp.) were exposed in replicate streams at the Llyn Brianne Stream Observatory (Wales, UK), and collected after 42 and 75 days. The family richness and abundance of invertebrates were significantly higher in circumneutral than acid samples. In circumneutral streams, both were significantly higher in oak and N. compressa than in P. riparioides. Under acid conditions, invertebrate colonisation of bryophytes declined markedly relative to oak, due largely to reduced numbers of the otherwise-dominant Leuctridae. Invertebrate assemblage composition differed with both acid–base status and litter type, with acid-tolerant taxa positively associated with bryophytes. We conclude that oak litter and N. compressa are equally valuable habitat under circumneutral conditions, but in acid streams bryophyte quality declines even for acid-tolerant taxa. This effect is consistent with invertebrates using bryophytes as more than physical habitat alone.
KeywordsAcidification Bryophytes Insects Leaf litter Macroinvertebrates Streams
Marian Pye and James Ryalls gave invaluable assistance with fieldwork. We thank Dr. Hugh Feeley for kindly assisting with the chemistry data, and Dr. Linda Johnston for valuable discussion during production of the manuscript. We also thank two anonymous reviewers whose comments have helped us to improve the manuscript. This research was funded by Cardiff School of Biosciences, the Esmee Fairbairn Foundation and the Llyn Brianne Stream Observatory. SJO was funded by the DURESS project (NERC/J014818/1) within the BESS programme funded by NERC, LWEC and BBSRC.
- Atherton, I., S. Bosanquet & M. Lawley (eds), 2010. Mosses and Liverworts of Britain and Ireland – A Field Guide. British Bryological Society, London.Google Scholar
- Bates, D., M. Maechler, B. Bolker & S. Walker, 2014. lme4: linear mixed-effects models using Eigen and S4. R package version 1.1-7. http://CRAN.R-project.org/package=lme4.
- Chantha, S., L. Cloutier & A. Cattaneo, 2000. Epiphytic algae and invertebrates on aquatic mosses in a Quebec stream. Archiv für Hydrobiologie 147: 143–160.Google Scholar
- Dangles, O. & F. Guerold, 2001. Influence of shredders in mediating breakdown rates of beech leaves in circumneutral and acidic forest streams. Archiv für Hydrobiologie 151: 649–666.Google Scholar
- Edwards, R., O. Heal, M. Hornung, R. Page, J. Stoner, R. Wilson, A. Donald, A. Gee, S. Ormerod, P. Whitehead, W. Binns, S. Bird, R. Boon, S. Brown, R. Donaldson, S. LeGrice, J. Jones, I. Littlewood, A. McLauchlin, C. Neal, B. Reynolds, A. Scott, R. Walsh & D. Williams, 1987. Llyn Brianne acid waters project: an investigation into the effects of afforestation and land management on stream acidity. First Technical Summary Report April 1987. Welsh Water Authority, Llanelli.Google Scholar
- Frost, W., 1942. R. Liffey Survey IV. The fauna of the submerged “mosses” in an acid and an alkaline water. Proceedings of the Royal Irish Academy Section B: Biological, Geological, and Chemical Science 47: 293–369.Google Scholar
- Minitab 16 Statistical Software, 2010. [Computer software]. Minitab, Inc., State College, PA. http://www.minitab.com
- Oksanen, J., F. Blanchet, R. Kindt, P. Legendre, P. Minchin, R. O’Hara, G. Simpson, P. Solymos, M. Stevens & H. Wagner, 2013. vegan: Community Ecology Package. http://CRAN.R-project.org/package=vegan.
- R Development Core Team, 2013. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna. http://www.R-project.org