Methane and Nitrous Oxide Fluxes from the Tropical Andes Printer-friendly Version Interactive Discussion Methane and Nitrous Oxide Fluxes from the Tropical Andes Methane and Nitrous Oxide Fluxes from the Tropical Andes Printer-friendly Version Interactive Discussion

Biogeosciences Discussions This discussion paper is/has been under review for the journal Biogeosciences (BG). Please refer to the corresponding final paper in BG if available. Abstract Remote sensing and inverse modelling studies indicate that the tropics emit more CH 4 and N 2 O than predicted by bottom-up emissions inventories, suggesting that terrestrial sources are stronger or more numerous than previously thought. Tropical uplands are a potentially large and important source of CH 4 and N 2 O often overlooked by past 5 empirical and modelling studies. To address this knowledge gap, we investigated spatial , temporal and environmental trends in CH 4 and N 2 O fluxes across a long elevation gradient (600–3700 m a.s.l.) in the Kosñipata Valley, in the southern Peruvian Andes that experiences seasonal fluctuations in rainfall. The aim of this work was to produce preliminary estimates of CH 4 and N 2 O fluxes from representative habitats within this 10 region, and to identify the proximate controls on soil CH 4 and N 2 O dynamics. Ecosystems across this altitudinal gradient were both atmospheric sources and sinks of CH 4 on an annual basis. Montane grasslands (or, puna; 3200–3700 m a.s.l.) were strong atmospheric sources, emitting 56.94 ± 7.81 kg CH 4 − C ha −1 yr −1. Upper montane forest (2200–3200 m a.s.l.) and lower montane forest (1200–2200 m a.s.l.) were net atmo

Recent remote sensing and inverse modelling studies indicate that the tropics emit more methane (CH 4 ) and nitrous oxide (N 2 O) than estimated from prior bottom-up emissions inventories, suggesting that tropical sources are stronger or more numerous than previously thought (Frankenberg et al., 2005(Frankenberg et al., , 2008;;Bergamaschi et al., 2009;Fletcher et al., 2004a, b;Hirsch et al., 2006;Huang et al., 2008;Kort et al., 2011).Recent speculation over discrepancies in the global tropical CH 4 budget have focussed on the potential role of seasonally flooded wetlands (Melack et al., 2004;Bergamaschi et al., 2009) or vegetation in accounting for budgetary gaps; the latter acting either as abiotic producers (Bergamaschi et al., 2007) or conduits for atmospheric egress from anoxic soils (Gauci et al., 2010;Terazawa et al., 2007).Parallel debates over tropical N 2 O budgets have invoked rising agricultural emissions or atmospheric transport processes as possible causes for discrepancies between top-down and bottom-up budgets (Nevison et al., 2007(Nevison et al., , 2011;;Kort et al., 2011).
In the Neotropics, data on upland CH 4 and N 2 O fluxes are particularly scarce, with field observations only from Puerto Rico (Silver et al., 1999;Teh et al., 2005) and Ecuador (Wolf et al., 2011(Wolf et al., , 2012)).Because of the limited spatial coverage and aseasonality of these two regions, it is difficult to draw wider conclusions about the source or sink strength of Neotropical uplands for CH 4 and N 2 O, particularly for areas that experience marked seasonality in rainfall or temperature.To address these knowledge Introduction

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Full  Findings from this research will provide the basis for future more detailed and integrative studies of soil trace gas dynamics in seasonal montane tropical ecosystems; and will also enable us to identify the proximate controls on CH 4 and N 2 O fluxes in these diverse environments.

Study site
Measurements were conducted on the eastern slope of the Andes in the Kosñipata Valley, Manu National Park, Peru (Malhi et al., 2010).This 3.02 × 10 6 ha (30 200 km 2 ) region has been the subject of intensive ecological, biogeochemical and climatological studies since 2003 by the Andes Biodiversity and Ecosystem Research Group (or, ABERG; http://www.andesconservation.org),and contains a series of long-term permanent plots across a 200-3700 m a.s.l.elevation gradient stretching from the western Amazon to the Andes (Malhi et al., 2010;Feeley and Silman, 2010).This part of the Andes experiences pronounced seasonality in rainfall but not in air temperature; the dry season extends from May to September and the wet season from October to April (Girardin et al., 2010;Zimmermann et al., 2010a).Thirteen sampling plots (approximately 20 m × 20 m each) were established at four different elevations across a gradi-Figures

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Full ent spanning 600-3700 m a.s.l., including premontane forest (600-1200 m a.s.l.; n = 3 plots), lower montane forest (1200-2200 m a.s.l.; n = 3 plots), upper montane forest (2200-3200 m a.s.l.; n = 3 plots), and montane grasslands (3200-3700 m a.s.l.; n = 4 plots; hereafter referred to as "puna").In premontane forest, new sampling plots were established in Hacienda Villa Carmen, a 3,065 ha biological reserve operated by the Amazon Conservation Association (ACA), containing a mixture of old-growth forest, secondary forest and agricultural plots.Sampling for gas fluxes was concentrated in the old-growth portions of the reserve.For lower montane and upper montane forests, sampling plots were established adjacent to or within existing 1 ha permanent sampling plots established by ABERG.New sampling plots were also established in puna to capture a representative range of environmental conditions, microforms (1-5 m scale landforms) and mesotopes (100 m-1 km scale landforms) (Belyea and Baird, 2006), as past ABERG studies of puna biogeochemistry were more limited in spatial extent (Gibbon et al., 2010;Zimmermann et al., 2010b).Mesotopic features include ridges, slopes, flats and basins.The latter two landforms include wet, grassy lawns with no discernible grade; and peat-filled depressions found in valley bottoms, respectively.Some (although not all) of these basins abut pool or lake complexes.Because of the logistic challenges of sampling over open water, we did not collect data from the pools or lakes, nor from the shoreline.Summary site descriptions are provided in Table 1 with data on site characteristics collated from prior studies (Feeley and Silman, 2010;Girardin et al., 2010;Zimmermann et al., 2009Zimmermann et al., , 2010b)).each of the thirteen plots (n = 65 flux observations per month).Sampling was spatially stratified to account for mesotope (100 m-1 km) scale variability in redox and hydrologic conditions (Belyea and Baird, 2006); key environmental factors that often regulate soil-atmosphere trace gas fluxes (Silver et al., 1999;Teh et al., 2011).All representative landforms were sampled in each elevation band, including ridges, slopes, flats and basins (Table 1).This spatial stratification of sampling was justified by a prior pilot study conducted across the entire ABERG elevation gradient (i.e.220-3700 m a.s.l.), which found significant within and among plot variability in fluxes, suggesting the need for a spatially explicit sampling design (Saiz and Teh, 2009, unpublished data; n = 75 static chamber measurements; > 10 flux measurements per elevation).

Soil-atmosphere exchange
Daily sampling in puna for 12 days (from 11 November 2011 to 22 November 2011) was performed in order to determine if CH 4 and other trace gas fluxes varied among mesotope-scale landforms (ridge, slope, flat, basin) in response to short-term (daily) fluctuations in rainfall, water table depth and soil moisture content.Sampling followed a stratified design that encompassed a 2.5 ha area including ridge, slope, flat and basin landforms.Twenty-four sampling stations were set-up across this topographic gradient > 1 month prior to sampling, consisting of six 75 m long transects, each running perpendicular to the slope and containing 4 sampling stations each.Each sampling station was instrumented with a chamber base, a soil gas equilibration chamber buried at a depth of 10 cm (Teh et al., 2005), and a piezometer inserted to bedrock or saprolite depth (≤ 50 cm).Measurements of air temperature, flux chamber temperature, soil temperature (5 and 10 cm depth), atmospheric pressure, soil moisture (0-20 cm), soil oxygen (O 2 ) concentration and water table depth were collected concurrent with flux chamber measurements on a daily basis.
Soil-atmosphere fluxes of CH 4 , N 2 O and CO 2 were determined using a static flux chamber approach (Teh et al., 2011;Livingston and Hutchinson, 1995) of approximately 5 cm and inserted > 1 month prior to the commencement of sampling, in order to avoid potential artefacts from root mortality following base emplacement (Varner et al., 2003).Chamber lids were fitted with small computer case fans to promote even mixing in the chamber headspace (Pumpanen et al., 2004).Headspace samples were collected from each flux chamber over a 30 min enclosure period, with samples collected at 4 discrete intervals using a gastight syringe.Gas samples were stored in evacuated Exetainers ® (Labco Ltd., Lampeter, UK), shipped to the UK by courier, and subsequently analysed for CH 4 , N 2 O and CO 2 concentrations using a Thermo TRACE GC Ultra (Thermo Fisher Scientific Inc., Waltham, Massachusetts, USA) at the University of St Andrews.Chromatographic separation was achieved using a Porapak-Q column, and analyte concentrations quantified using a flame ionization detector (FID) for CH 4 , electron capture detector (ECD) for N 2 O, and methanizer-FID for CO 2 .Instrumental precision was determined by repeated analysis of standards and was better than 5 % for all detectors.Fluxes rates were determined by using the R (R Core Team, 2012) HMR package to plot best-fit lines to the data for headspace concentration against time for individual flux chambers (Pedersen et al., 2010).Gas mixing ratios (ppm) were converted to areal fluxes by using the Ideal Gas Law to solve for the quantity of gas in the headspace (on a mole or mass basis), normalized by the surface area of each static flux chamber (Livingston and Hutchinson, 1995).

Environmental variables
To investigate the effects of environmental variables on trace gas dynamics, we determined soil moisture, soil oxygen content in the 0-10 cm depth, soil temperature, chamber temperature and air temperature at the time of flux sampling.In flooded environments (e.g.puna basins), water table depth was also measured using piezometers installed to a depth of ≤ 50 cm in the soil.Soil moisture was determined using portable moisture probes (ML2x ThetaProbe, Delta-T Device Ltd., Cambridge, UK) inserted into the substrate immediately adjacent to each flux chamber (< 5 cm from each chamber base; depth of 0-10 cm).Soil moisture content was measured both as volumetric wa-Figures

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Full ter content (VWC) and water-filled pore space (WFPS), the latter calculated from VWC and bulk density data (Breuer et al., 2000).Soil O 2 concentration was determined by analysing soil gas with a portable O 2 meter (Apogee Instruments Ltd., Logan, Utah, USA), collected from soil gas equilibration chambers permanently installed to a depth of 0-10 cm adjacent to static flux chambers (Teh et al., 2005).Soil temperature (0-10 cm depth), chamber temperature and air temperature was determined using type K thermocouples (Omega Engineering Ltd., Manchester, UK).Data on aboveground litterfall, meteorological variables (i.e.photosynthetically active radiation, air temperature, relative humidity, rainfall, wind speed, wind direction), continuous plot-level soil moisture and soil temperature measurements (10 cm and 30 cm depths) were also collected, but are not reported in this publication.
Fluctuations in available inorganic N (i.e.ammonium, NH + 4 ; nitrate, NO − 3 ; nitrite, NO − 2 ) concentrations were quantified in all plots using a resin bag approach (Templer et al., 2005).From August 2011 onwards, ion exchange resin bags (n = 15 resin bags per elevation) were deployed in the rhizosphere (i.e.0-10 cm depth in premontane forest, lower montane forest and puna; 0-15 cm in upper montane forest), and collected at monthly intervals (where possible) for determination of monthly time-averaged NH + 4 , NO − 3 and NO − 2 concentrations.For some plots, this sampling frequency was periodically disrupted due to natural hazards (i.e.land slides, river flooding) preventing safe access to the study sites.Resin bags were shipped to the University of Aberdeen after collection from the field, inorganic N was extracted using 2 N KCl (Templer et al., 2005) and concentrations determined colorimetrically using a Burkard SFA2 continuous-flow analyzer (Burkard Scientific Ltd., Uxbridge, UK). per sample) were collected from beneath the rooting zone from sites across the elevation sequence, air-dried and then shipped to the UK by courier.Upon arrival in the UK, 50 g dry soil sub-samples were taken from each soil sample and weighed out into 52 700 mL glass vessels for incubation (n = 19 for premontane forest, n = 3 for lower montane forest, n = 5 for upper montane forest, n = 10 for puna).The uneven sample sizes reflect the fact that this experiment was designed as a preliminary scoping exercise to capture a broad range of environmental conditions, microtopographic and mesotopic features in order to quantify the range of variability in denitrification rates both within and among elevation bands.Soil sub-samples were initially re-wetted to 20 % volumetric water content, and allowed to pre-incubate for 4 days.Soils were further moistened at the start of the experiment to achieve a final WFPS of 80 %.A KNO 3 solution containing 0.2 mL of 0.01 M 40 atom % 15 N-NO − 3 was then added to the soil, and the glass incubation vessels sealed to initiate the experiment.Control incubations were conducted with soils from each elevation band (n = 3 per elevation) to correct for the 15 N natural abundance signature of endogenous N 2 O and N 2 production.Gas samples were collected at 0, 6, 12, 24, 33 and 48 h to quantify N 2 O, 15 N-N 2 O and 15 N-N 2 concentrations.Gas concentrations and isotope ratios were determined at the University of Aberdeen, using an Agilent 6890 GC fitted with an ECD (Agilent Technologies UK Ltd., Workingham, UK) and a SerCon 20 : 20 isotope ratio mass spectrometer (IRMS) equipped with an ANCA TGII pre-concentration module (SerCon Ltd., Crewe, UK), respectively.Instrumental precision was determined by repeated analysis of standards and was better than 5 % for both the GC and IRMS.Potential denitrification rates were calculated from the difference in the 15 N atom % excess values of N 2 O and N 2 relative to the controls.Fluxes of 15 N-N 2 O and 15 N-N 2 were determined using the R (R Core Team; http://www.r-project.org)HMR package (as described above) and normalized for

Statistical analyses
Statistical analyses were performed using JMP IN Version 8 (SAS Institute, Inc., Cary, North Carolina, USA) and R (R Core Team, 2012).The data were log transformed where necessary to meet the assumptions of analysis of variance.Residuals were checked for heteroscedasticity and homogeneity of variances.Repeated measures analysis of variance (ANOVA) was used to explore the influence of spatial (e.

Spatial variation in gas fluxes and environmental variables
The mean CH 4 flux for the entire 13 month dataset was 7.79±1.4 concentration was greatest for upper montane forest, while other habitats did not differ significantly from each other (Fisher's LSD, P < 0.05; Fig. 2a).NH tively.Available NO − 2 concentrations did not vary significantly among elevation bands, averaging 0.02 ± 0.00 µg NO − 2 − N g resin −1 d −1 across the elevation gradient (data not shown).

Temporal variability in gas exchange
CH 4 efflux increased during the wet season (repeated measures ANOVA, r 2 = 0.91,

Temporal variability in environmental variables
Across the elevation gradient, soil moisture changed significantly over time, with temporal trends that varied depending on elevation band (repeated measures ANOVA for VWC, r 2 = 0.86, F 104,800 = 46.42,P < 0.0001; repeated measures ANOVA for WFPS, r 2 = 0.72, F 76,628 = 18.57,P < 0.0001).Soil moisture in premontane forest and puna showed significant month-to-month variability, but did not differ significantly between seasons ( Soil O 2 concentrations varied significantly over time, but temporal patterns differed for each elevation band (repeated measures ANOVA, r 2 = 0.88, F 48,269 = 40.08,P > 0.0001).For lower montane forests, soil O 2 varied significantly from month-to-month, with small but statistically higher soil O 2 observed in the wet season (19.4 ± 0.1 %) compared to the dry season (19.0 ± 0.1 %) (t 90 = 3.21, P < 0.0002; Table 3).Upper montane forests showed significant month-to-month variability, but no significant differences between seasons (overall mean = 18.4 ± 0.1 %).Puna showed a different trend from the other habitats, as lower O 2 concentrations were observed during the wet season (13.3 ± 0.4 %) compared to the dry season (18.4 ± 0.1 %) (t 379 = −3.48,P < 0.0006; Table 3).Data on soil O 2 content in the premontane forest site was too sparse to evaluate seasonal patterns in soil O 2 content due to unanticipated delays in the installation of soil gas sampling equipment.
Soil temperature and air temperature varied significantly over time (repeated measures ANOVA for soil temperature, r 2 = 0.83, F 103,770 = 37.92, P < 0.0001; repeated measures ANOVA for air temperature, r 2 = 0.81, F 75,492 = 28.50,P < 0.0001).In premontane, lower montane and upper montane forests, the overall trend was towards significantly warmer soil and air temperatures forests during the wet season (Table 3).Introduction

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Full Puna showed a different pattern from the other study sites; no significant seasonal differences in soil temperature were observed, while air temperatures were warmer in the dry season (12.5 ± 0.3 • C) compared to the wet season (11.3 ± 0.2 • C) (t 198 = −3.53,P < 0.0005; Table 3).Ecosystems across this tropical elevation gradient functioned as both atmospheric sources and sinks of CH 4 , further challenging the long-standing assumption that tropical uplands are only net atmospheric CH 4 sinks (Dutaur and Verchot, 2007;Potter et al., 1996;Ridgwell et al., 1999;Teh et al., 2005, von Fischer andHedin, 2002).CH 4 fluxes varied depending on elevation, topographic position and season.Montane grasslands (puna; 3200-3700 m a.s.l.) were net atmospheric sources; upper montane and lower montane forests were net sinks; and premontane forests fluctuated between sources or sinks depending on the season.From 600 to 3200 m a.s.l., the sink strength for atmospheric CH 4 increased with elevation.This pattern runs counter to observations from elsewhere in Latin America, such as Puerto Rico or Ecuador, where net CH 4 uptake decreased with increasing elevation (Silver et al., 1999;Teh et al., 2005;Wolf et al., 2012).The divergence between this study and others is likely due to local and regional differences in precipitation and soil moisture retention.Rainfall and soil moisture content decreases with rising elevation in this part of the Andes (Girardin et al., 2010), with the notable exception of puna, where soil moisture is elevated relative to other habitats across this elevation gradient due to poor drainage.In contrast, because of regional differences in climate and meteorology, soil moisture increases with elevation in Puerto Rico and Ecuador, favouring greater soil anaerobiosis, enhanced methanogenesis and diminished methanotrophy with rising altitude (Silver et al., 1999;Teh et al., 2005;Wolf et al., 2012).CH 4 fluxes within elevation bands varied with topographic position, with lower topographic positions (e.g.basins) emitting more CH 4 than higher topographic positions (e.g.ridges).The development of more sub-oxic conditions in lower topographic positions likely drives greater methanogenesis and reduced methanotrophy; a common pattern observed in many other CH 4 -emitting ecosystems (Teh et al., 2011;von Fischer et al., 2010;Waddington and Roulet, 1996;Silver et al., 1999).Across the entire altitudinal gradient, puna basins emitted more CH 4 than any other landform, releasing 233.56 ± 28.47 kg CH 4 − C ha −1 yr −1 .Our findings are in general agreement with studies in Puerto Rico, where higher net CH 4 fluxes were observed from low topographic positions (Silver et al., 1999); but differ from research in Ecuador, where no significant difference was found in net CH 4 fluxes among topographic positions within an altitudinal band (Wolf et al., 2012).The most likely explanation for this divergence between the Peruvian and Puerto Rican transects on one hand, and the Ecuadorian transect on the other, is that the investigators in the latter study sampled only ridge and slope landforms, and did not sample lower topographic features such as flats or basins (Wolf et al., 2012).In addition, Wolf et al. (2012) did not sample more water-saturated puna habitats.Lower topographic landforms and puna habitats tend to accumulate water and contain more reduced soils capable of emitting CH 4 , unlike more aerobic ridges and slopes that drain more freely (Teh et al., 2011;von Fischer et al., 2010;Waddington and Roulet, 1996;Silver et al., 1999).).These seasonal trends differ significantly from Puerto Rico or Ecuador, where soil CH 4 fluxes did not vary on an intraannual basis, presumably because of weaker rainfall seasonality in these other regions (Silver et al., 1999;Teh et al., 2005;Wolf et al., 2012).However, these data are consistent with findings from other seasonally dry tropical ecosystems, where greater net CH 4 efflux is associated with wetter periods of the year, where soil anaerobiosis is more prevalent (Davidson et al., 2008;Verchot et al., 2000).Our analysis of spatial, temporal and environmental trends in CH 4 fluxes across the elevation gradient suggest that soil redox is the principal control on CH 4 flux, as is the case elsewhere in the tropics (Teh et al., 2005;Verchot et al., 2000;von Fischer and Hedin, 2007).CH 4 emissions were greatest from elevations, landforms or during times of year when soils were at their most sub-oxic.This conclusion is further supported by the strong inverse correlation observed between soil O 2 concentration (i.e. a proxy for soil redox potential) and CH 4 flux (Silver et al., 1999;Teh et al., 2005), with progressive declines in soil O 2 linked to increasingly large net CH 4 emissions (Fig. 3).Moreover, multiple regression models that included soil O 2 , soil moisture and temperature indicated that soil O 2 concentration was the single best predictor of CH 4 flux, typically accounting for > 99 % of the variance in the entire dataset.(Wolf et al., 2011).Although the cause for this divergence between these observations and past studies is unclear, it may be linked to the higher N status of lower elevation soils in the Kosñipata Valley, which tend to be more N-rich than soils in Ecuador (Wolf et al., 2011;Fisher et al., 2013, van de Weg et al., 2009).Analysis of the field and laboratory data suggests that controls on N 2 O fluxes in the Kosñipata Valley are complex and not easily reducible to simple predictive metrics.

BGD
However, holistic examination of these combined datasets suggests that the availability of N, particularly NO  (Blackmer and Bremner, 1978;Weier et al., 1993;Yang et al., 2011).These data are in broad agreement with findings from Ecuador, where N availability was inversely proportional to altitude and was found to be the dominant control on N 2 O efflux (Wolf et al., 2011).
Soil moisture and WFPS appeared to play a minor role in modulating N 2 O fluxes across the elevation gradient; a surprising finding given the prominent role played by WFPS in regulating N 2 O fluxes elsewhere in the seasonally dry tropics (Davidson et al., 1993(Davidson et al., , 2000(Davidson et al., , 2008;;Davidson and Verchot, 2000;Keller and Reiners, 1994).Variations in soil moisture content and WFPS only appeared to influence N 2 O fluxes in lower montane forest only during the dry season; whereas these variables had no discernible impact on N 2 O fluxes in other elevations or during other seasons.This suggests that soil moisture and WFPS were not limiting during the 13 month period of observation, and that other factors more strongly constrained N 2 O fluxes in these other habitats.
Comprehensive inspection of the environmental data (including soil moisture, WFPS and available N) suggests that the nature of the constraints on N 2 O production may differ for each elevation band.WFPS fell within a relatively narrow range for premontane forest, lower montane forest during the wet season, and puna.Given the complexity of drivers for N 2 O production, this makes it difficult to identify the "signal" of WFPS relative to the background environmental "noise" (Davidson and Verchot, 2000;Groffman et al., Introduction Conclusions References Tables Figures

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Full the Kosñipata Valley as a whole), we added together the area-weighted fluxes from each elevation band (Table 5).This exercise produced mean annual flux estimates of 9.42 ± 1.80 kg CH 4 − C ha −1 yr −1 and 1.18 ± 0.79 kg N 2 O − N ha −1 yr −1 , respectively.
The positive sign of the area-weighted CH 4 flux implies that the region as whole is probably a net atmospheric CH 4 source, strongly influenced by the contribution of puna acting as a regional "hotspot" for CH 4 .This speculation is supported by evidence from remote sensing studies showing elevated atmospheric CH 4 concentrations in the tropical Andes, implying the presence of strong regional sources, such as waterlogged, sub-oxic/anoxic puna or páramo grasslands, unaccounted for by past bottom-up emissions inventories (Wania et al., 2007;Bergamaschi et al., 2007).Likewise the estimated regional N 2 O flux for the Kosñipata Valley exceeds both model predictions for the region (< 0.5-1.0kg N 2 O − N ha −1 yr −1 ) (Werner et al., 2007) and observations from comparable ecosystems in Ecuador (mean annual flux of 0.31±0.12kg N 2 O−N ha −1 yr −1 ) (Wolf et al., 2011), probably influenced by the strong emissions from lower elevation bands, which account for ∼54 % of overall land cover.
While these area-weighted flux estimates may only be a first approximation, they are significant because these calculations suggest that Andean ecosystems may behave differently than previously thought, and may be larger emission sources than predicted.These findings also highlight the need for more intensive modeling studies to upscale plot-level measurements to the regional scale in order to more thoroughly evaluate the importance of these ecosystems for regional atmospheric budgets.

Conclusions
These data suggest that tropical Andean ecosystems are potentially important contributors to regional atmospheric budgets of CH 4 and N 2 O, and that these ecosystems need to be considered more fully in future efforts to model and upscale CH  Full spheric sinks (−2.99 ± 0.29 kg CH 4 − C ha −1 yr −1 and −2.34 ± 0.29 kg CH 4 − C ha −1 yr −1 , respectively); while premontane forests (600-1200 m a.s.l.) fluctuated between source or sink depending on the season (wet season: 1.86±1.50kg CH 4 −C ha −1 yr −1 ; dry season: −1.17±0.40kg CH 4 −C ha −1 yr −1 ).Analysis of spatial, temporal and environmental trends in CH 4 flux across the study site suggest that soil redox was a dominant control on net CH 4 flux.CH 4 emissions were greatest from elevations, landforms and during times of year when soils were sub-oxic, and CH 4 efflux was inversely correlated with soil O 2 concentration (r 2 = 0.82, F 1,125 = 588.41,P < 0.0001).Ecosystems across the region were net atmospheric N 2 O sources.N 2 O fluxes declined with increasing elevation; N 2 O emissions from premontane forest, lower montane forest, upper montane forest and montane grasslands averaged 2.23±1.31kg N 2 O−N ha −1 yr −1 , 1.68±0.44kg N 2 O− N ha −1 yr −1 , 0.44 ± 0.47 kg N 2 O − N ha −1 yr −1 and 0.15 ± 1.10 kg N 2 O − N ha −1 yr −1 , respectively.N 2 O fluxes from premontane and lower montane forests exceeded prior 1 Introduction Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper |

Field
sampling was performed over a 13 month period from December 2010 to December 2011 for all habitats except premontane forest.Because of circumstances outside our control, only 6 months of data were collected for premontane forest, with sampling only commencing in July 2011.Soil-atmosphere fluxes were collected monthly, except where flooding or landslides prevented safe access by fieldworkers to the study sites.Gas exchange rates were determined with five replicate gas flux chambers deployed in Discussion Paper | Discussion Paper | Discussion Paper | , although only CH 4 and N 2 O fluxes are reported here.Static flux chamber measurements were made by enclosing a 0.03 m 2 area with cylindrical, opaque (i.e.dark), two-component (i.e.base and lid) vented chambers.Chamber bases were permanently installed to a depth Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Potential denitrification rates across the elevation sequence were determined by performing an exploratory 15 N-labeled nitrate ( 15 N-NO − Discussion Paper | Discussion Paper | Discussion Paper | soil dry weight.Total denitrification potential (i.e.sum of 15 N-N 2 O plus 15 N-N 2 fluxes) and N 2 O yield (i.e. the ratio of 15 N-N 2 O : 15 N-N 2 O flux + 15 N-N 2 flux) were also calculated (Yang et al., 2011).Discussion Paper | Discussion Paper | Discussion Paper | 14 mg CH 4 −C m −2 d −1 .CH 4 fluxes varied significantly among elevation bands (habitats) and over time (repeated measures ANOVA, r 2 = 0.91, F 101,731 = 75.75,P < 0.00001).Multiple comparisons tests indicated that CH 4 fluxes from puna differed significantly from other habitats (Fisher's LSD, P < 0.05; Fig. 1a).Puna were net sources of CH 4 , with mean fluxes of 15.60 ± 2.14 mg CH 4 − C m −2 d −1 .In contrast, premontane, lower montane and upper Introduction Discussion Paper | Discussion Paper | Discussion Paper | montane forests were all net atmospheric sinks, with mean uptake rates of −0.16 ± 0.13 mg CH 4 − C m −2 d −1 , −0.64 ± 0.08 mg CH 4 − C m −2 d −1 and −0.82 ± 0.08 mg CH 4 − C m −2 d −1 , respectively (Fig. 1a).CH 4 fluxes varied significantly among topographic features (ANOVA, r 2 = 0.54, F 6,826 = 161.15,P < 0.0001; data not shown).Basin landforms, found only in the puna, emitted significantly more CH 4 than other topographic features (mean CH 4 flux for basin landforms was 63.99 ± 7.80 mg CH 4 − C m −2 d −1 ; Fisher's LSD, P < 0.05; data not shown).Other landforms were either weak sources or sinks, but could not be distinguished from each other statistically because of the large variance in fluxes.The mean for pooled CH 4 fluxes from ridge, slope and flat landforms (i.e. the entire dataset excluding basin landforms) was 0.47 ± 0.18 mg CH 4 − C m −2 d −1 , with a range from −8.71 to 78.5 mg CH 4 − C m −2 d −1 .The mean N 2 O flux for the entire 13 month dataset was 0.22 ± 0.12 mg N 2 O − N m −2 d −1 .N 2 O fluxes varied widely among elevations bands (habitats) and over time (repeated measures ANOVA, r 2 = 0.17, F 76,381 = 1.06,P < 0.35).Mean N 2 O fluxes declined progressively with increasing elevation, although this pattern was only statistically significant at the P < 0.1 level due to high variance in fluxes both within and among study sites (Fig. 1b).The highest mean fluxes observed were in premontane forests (0.61 ± 0.36 mg N 2 O − N m −2 d −1 ), followed by lower montane forests (0.46 ± 0.12 mg N 2 O−N m −2 d −1 ), upper montane forests (0.12±0.13 mg N 2 O−N m −2 d −1 ) and puna (0.04 ± 0.30 mg N 2 O − N m −2 d −1 ) (Fig. 1b).N 2 O fluxes did not vary significantly among topographic features within elevation bands (ANOVA, r 2 = 0.02, F 6,451 = 1.36,P > 0.2).Soil moisture varied significantly among elevation bands (habitats) and over time.Patterns were qualitatively similar whether volumetric water content or WFPS were used as metrics of soil moisture (repeated measures ANOVA for VWC, r 2 = 0.86, F 104,800 = 46.42,P < 0.0001; repeated measures ANOVA for WFPS, r 2 = 0.72, F 76,628 = 18.57,P < 0.0001).Multiple comparison tests indicate that soil moisture varied significantly among elevations (Fisher's LSD, P < 0.05;

N 2 O
fluxes across the elevation gradient showed no easily identifiable temporal trends.There was insufficient data to fully characterise seasonal trends in NH + only 4 months of data were collected over the sampling period.However, significant month-to-month variability was observed in NH + 4 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | CH 4 fluxes across the elevation gradient were weakly correlated with soil moisture content (plot-averaged VWC versus CH 4 flux: r 2 = 0.24, F 1,152 = 48.64,P < 0.0001; data not shown) and strongly negatively correlated with soil O 2 (plot-averaged soil oxygen versus CH 4 flux: r 2 = 0.82, F 1,125 = 588.41,P < 0.0001; Fig.3).A multiple regression model incorporating soil moisture and soil O 2 concentration explained only a further 1 % of the variance in the entire CH 4 dataset (r 2 = 0.83, F 2,124 = 295.47,P < 0.0001), with soil O 2 accounting for > 99 % of the sum of squares in the multiple regression model (data not shown).No relationship between net CH 4 flux and temperature was found.When these CH 4 flux data were disaggregated by elevation band and season, other relationships emerged, suggesting more habitat-specific controls on CH 4 flux.For lower montane forest, CH 4 fluxes were negatively correlated with soil temperature during the dry season (plot-averaged soil temperature versus CH 4 flux: r 2 = 0.46, F 1,13 = 10.86,P < 0.006; data not shown), but not during the wet season.For puna, CH 4 fluxes were more strongly correlated with soil moisture content than for the overall pooled dataset (r 2 = 0.24 for the data pooled across the entire elevation gradient; data not shown).For example, taking both dry and wet season together for puna, the r 2 for the regression of CH 4 flux and VWC was 0.39 (F 1,64 = 41.44,P < 0.0001), while the r 2 for the wet season data alone was higher (r 2 = 0.46, F 1,43 = 36.29,P < 0.0001).Dry season puna CH 4 fluxes were not significantly correlated with VWC.Only dry season N 2 O fluxes from lower montane forest showed any relationship with environmental variables (Fig. 4), with N 2 O fluxes negatively correlated with soil ecosystems as both atmospheric sources and sinks of CH 4 Discussion Paper | Discussion Paper | Discussion Paper | CH 4 fluxes varied substantially depending on season, with an overall shift towards greater CH 4 emission or significant weakening of net soil sinks during the rainy season.These patterns were most pronounced for puna and premontane forest; the former showed a nineteen-fold increase in net CH 4 efflux from dry season to wet (0.97 ± 0.47 mg CH 4 − C m −2 d −1 to 18.57 ± 2.55 mg CH 4 − C m −2 d −1 ), while the latter switched from a net atmospheric sink (−0.32 ± 0.11 mg CH 4 − C m −2 d −1 ) to a net atmospheric source (0.51 ± 0.41 mg CH 4 − C m −2 d −1 Discussion Paper | Discussion Paper | Discussion Paper |

− 3 ,
may play a pivotal role in limiting N 2 O emissions across the Discussion Paper | Discussion Paper | Discussion Paper | elevation gradient.The central role of N availability in regulating N 2 O fluxes is highlighted by the altitudinal trends in N 2 O fluxes, available NO − 3 concentrations, potential N 2 O and N 2 production, and 15 N-N 2 O yields.Even though potential denitrification rates were similar across the elevation gradient (with the exception of upper montane forest), net N 2 O fluxes and NO − 3 availability declined with elevation.Taken together, these data collectively suggest that altitudinal trends in N 2 O fluxes were due to variations in denitrification, driven by differences in NO − 3 availability.Data on denitrification potential in upper montane forest further reinforces this interpretation of the data; upper montane forests had lower N 2 O production potential, higher N 2 production potential and lower N 2 O yields than other sites -all characteristics reflective of NO − 3 -limitation of denitrification Discussion Paper | Discussion Paper | Discussion Paper | 4 and N 2 O fluxes from the terrestrial tropics.Ecosystems across this tropical altitudinal gradient were both atmospheric sources and sinks of CH 4 , challenging long-standing assump-Discussion Paper | Discussion Paper | Discussion Paper | Tejedor from the Amazon Conservation Association, who provided assistance with site access and selection at Hacienda Villa Carmen.Thanks are also owed to TCH for providing comments on an earlier draft of this manuscript.This publication is a contribution from the Scottish Alliance for Geoscience, Environment and Society (http://www.sages.ac.uk)DiscussionPaper | Discussion Paper | Discussion Paper | Weier, K. L., Doran, J. W., Power, J. F., and Walters, D. T.: Denitrification and the dinitrogen nitrous-oxide ratio as affected by soil-water, available carbon, and nitrate, Soil Sci.Soc.Am.J., 57, 66-72 1993.1993.Werner, C., Butterbach-Bahl, K., Haas, E., Hickler, T., and Kiese, R.: A global inventory of N 2 O emissions from tropical rainforest soils using a detailed biogeochemical model, Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper |

Fig. 1 .Fig. 3 .Fig. 4 .Fig. 5 .
Fig. 1. (A) Net CH 4 and (B) net N 2 O fluxes by elevation band.The short-dash line within each box represents the mean, whereas the solid line represents the median.Boxes enclose the interquartile range, whiskers indicate the 90th and 10th percentiles.The dotted line running across the boxes indicates zero net flux.Lower case letters indicate statistically significant differences among means (Fisher's LSD, P < 0.05).
gaps, we performed a preliminary study of CH 4 and N 2 O cycling across a long elevation gradient (600-3700 m a.s.l.) in the Peruvian Andes that experiences seasonal variations in rainfall, and include a wide range of habitats stretching from premontane forests to wet montane grasslands.Our principal objectives were to: g. elevation band, topography) and temporal factors (e.g.day of year, season) on gas fluxes and environmental variables.A student's t test was used to compare differences in fluxes and environmental variables between seasons (dry, wet).Bivariate or multiple regression was utilized to investigate the relationship among environmental variables and trace gas fluxes.Repeated measures analysis of covariance (ANCOVA) was used to evaluate the relative contribution of ordinal variables (elevation band, topography, day of year, season) and continuous environmental covariates (soil moisture, soil oxygen, soil temperature, air temperature) in regulating gas fluxes.Means comparisons were performed using Fisher's Least Significant Difference test(Fisher's LSD).Statistical significance was determined at the P < 0.05 level, unless otherwise noted.Values are reported as means and standard errors (±1 SE).

Table 2 .
Summary of soil sampling scheme for denitrification potential experiment.