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NERC has developed NORA to enable users to access research outputs wholly or partially funded by NERC. Copyright and other rights for material on this site are retained by the rights owners. Users should read the terms and conditions of use of this material at http://nora.nerc.ac.uk/policies.html#access This document is the author's final manuscript version of the journal article, incorporating any revisions agreed during the peer review process. Some differences between this and the publisher's version remain. You are advised to consult the publisher's version if you wish to cite from this article.The definitive version is available at http://onlinelibrary.wiley.com Contact CEH NORA team at noraceh@ceh.ac.ukThe NERC and CEH trademarks and logos ('the Trademarks') are registered trademarks of NERC in the UK and other countries, and may not be used without the prior written consent of the Trademark owner. (Evans et al., 2005). In the water 55 industry, the high cost of DOC removal, and associated health risks through trihalomethane 56 formation (e.g. Chow et al., 2003), result in it being widely viewed as a pollutant. Changes in DOC 57 export to surface waters also affect aquatic energy supply and light regime (due to the 58 chromophoric properties of organic compounds), with potentially major consequences for the 59 functioning of aquatic ecosystems (Cole et al., 2001; Battin et al., 2009;Karlsson et al., 2010). When 60 first detected, DOC increases were thought to be a consequence of climate change (Freeman et al., 61 2001; Hejzlar et al., 2003;Worrall & Burt, 2007; Hongve et al., 2004), and thus evidence of 62 ecosystem destabilisation, contributing to terrestrial carbon losses (Bellamy et al., 2005). Some 63 recent studies also suggest high climate-sensitivity of DOC leaching (e.g. Larssen et al., 2011; Fenner 64 & Freeman, 2011 Oulehle & Hruska, 2009; Chapman et 72 al., 2010; Arvola et al., 2010; Clark et al., 2011; Ekström et al., 2011;SanClements et al., 2012) and 73 challenging (e.g. Roulet & Moore, 2006; Eimers et al., 2008;Worrall et al., 2008; Clair et al., 2008; 74 Sarkkola et al., 2009;Sarkkola et al., 2009;Zhang et al., 2010; Couture et al., 2011; Löfgren and 75 Zetterberg, 2011; Pärn & Mander, 2012) Figure S1b). 167At the Afon Gwy AWMN site, 50 km to the south, DOC has increased by 51% over the same period , pH range 3.9 to 4.4). In addition, the Peak District peat 237 and Migneint podzol sites exhibited some pre-treatment differences in mean DOC concentrations 238 between control and treatment plots ( Figure 1, Table 1). To explore underlying relationships 239 between DOC and pH change, we therefore standardised DOC concentrations by dividing mean DOC 240 for each treatment at each site and sampling interval by the corresponding pre-treatment mean. 241Deviation from this initial level due to treatment was quantified as the ratio of mean standardised habitats showed an increase in mean pH between the two surveys, and these mean values were 296 used to calculate RH std as above,...

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Background: Peatlands cover 2 to 5 percent of the global land area, while storing between 30 and 50 percent of all global soil carbon (C). Peatlands constitute a substantial sink of atmospheric carbon dioxide (CO 2 ) via photosynthesis and organic matter accumulation, but also release methane (CH 4 ), nitrous oxide (N 2 O), and CO 2 through respiration, all of which are powerful greenhouse gases (GHGs). Lowland peats in boreo-temperate regions may store substantial amounts of C and are subject to disproportionately high land-use pressure. Whilst evidence on the impacts of different land management practices on C cycling and GHG fluxes in lowland peats does exist, these data have yet to be synthesised. Here we report on the results of a Collaboration for Environmental Evidence (CEE) systematic review of this evidence. Methods: Evidence was collated through searches of literature databases, search engines, and organisational websites using tested search strings. Screening was performed on titles, abstracts and full texts using established inclusion criteria for population, intervention/exposure, comparator, and outcome key elements. Remaining relevant full texts were critically appraised and data extracted according to pre-defined strategies. Meta-analysis was performed where sufficient data were reported.

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Wetland soils are globally important carbon stores, and natural wetlands provide a sink for atmospheric carbon dioxide (CO 2 ) through ongoing carbon accumulation. Recognition of coastal wetlands as a significant contributor to carbon storage (blue carbon) has generated interest into the climate change mitigation benefits of restoring or recreating saltmarsh habitat. However, the length of time a re-created marsh will take to become functionally equivalent to a natural (reference) system, or indeed, whether reference conditions are attainable, is largely unknown. Here, we describe a combined field chronosequence and modelling study of saltmarsh carbon accumulation and provide empirically based predictions of changes in the carbon sequestration rate over time following saltmarsh restoration. Carbon accumulation was initially rapid (average 1.04 t C ha −1 yr −1 during the first 20 years), slowing to a steady rate of around 0.65 t C ha −1 yr −1 thereafter. The resulting increase in C stock gave an estimated total C accumulation of 74 t C ha −1 in the century following restoration. This is approximately the same as our observations of natural marsh C content (69 t C ha −1 ), suggesting that it takes approximately 100 years for restored saltmarsh to obtain the same carbon stock as natural sites.

(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