Methane indicator values for peatlands: a comparison of species and functional groups

Abstract

(300) 1Previous studies have shown a correspondence between the abundance of particular plant 2 species and methane flux. Here we apply multivariate analyses, including a weighted 3 averaging approach, to assess the suitability of vegetation composition as a predictor of 4 methane flux. We developed a functional classification of the vegetation, in terms of a 5 number of plant traits expected to influence methane production and transport, and compared 6 this with a purely taxonomic classification at species-level and higher. We applied both 7 weighted averaging and indirect and direct ordination approaches to six sites in the UK, and 8 found good relationships between methane flux and vegetation composition (classified both 9 taxonomically and functionally). Plant species and functional groups also showed meaningful 10 responses to management and experimental treatments. In addition to the UK, we applied the 11 functional group classification across different geographical regions (Canada and 12 Netherlands) to assess the generality of the method. Again, the relationship appeared good at 13 the site level, suggesting some general applicability of the functional classification. The 14 method seems to have the potential for incorporation into large-scale (national) greenhouse 15 gas accounting programmes (in relation to peatland condition/management) using vegetation 16 mapping schemes. The results presented here strongly suggest that robust predictive models 17 can be derived using plant species data (for use in national-scale studies). For trans-national-18 scale studies, where the taxonomic assemblage of vegetation differs widely between study 19 sites, a functional classification of plant species data provide an appropriate basis for 20 predictive models of methane flux. 21

Nitrous oxide emissions from a peatbog after 13 years of experimental nitrogen deposition

“…Shifts in the species composition appeared to be the clearest sign that N deposition was affecting the long-term outcome of resource competition for nitrate, and thereby influencing N 2 O flux. A similar result was found in a multivariate analysis of vegetation in relation to methane flux in the UK ecosystems (Levy et al, 2012;Gray et al, 2013). Direct relationships between N 2 O flux and both nitrate and ammonium were poor, possibly because these are influenced by feedback from the flux itself.…”

Differential response of carbon cycling to long-term nutrient input and altered hydrological conditions in a continental Canadian peatland

“…In existing studies, the greatest emissions were similarly found in wetter habitats dominated by graminoids (Levy et al, 2012;Gray et al, 2013). Given that CH 4 emissions at site 2 were significantly smaller than those from site 3, even though the two sites featured a very similar graminoid-moss-dominated vegetation cover, the differences in CH 4 fluxes could be attributed to (i) the wetter conditions at site 3, (ii) a greater nutrient supply at site 3 stimulating greater CH 4 production and emissions (Eriksson et al, 2010), or (iii) a mixture of both effects.…”

Growing season CH<sub>4</sub> and N<sub>2</sub>O fluxes from a subarctic landscape in northern Finland; from chamber to landscape scale

“…The PRS probes utilize ion-exchange resin membranes to provide an index of relative plant nutrient availability (Hangs et al, 2002), measured ions included total N, NO 3 -N, NH 4 -N, Ca, Mg, K, P, Fe, Mn, Zn, B, S, Pb, Al and Cd. During the summer campaign probes were deployed on 11 and 12 July, and recovered on 1 August.…”

“…Where such species are present they can act as gas conduits, allowing GHGs produced in the anoxic layer to be transported to the atmosphere with minimal oxidation, subsequently increasing emissions by up to an order of magnitude (Dinsmore et al, 2009a;MacDonald et al, 1998;Minkkinen and Laine, 2006). Vegetation community structure also provides a useful proxy for environmental variables that are themselves difficult to measure, such as long-term water table dynamics (Gray et al, 2013;Levy et al, 2012).…”