Igor Lehnherr ‡*, Jason Venkiteswaran ‡, Vincent St. Louis §, Sherry Schiff ‡ and Craig Emmerton § ‡ Department of Earth and Environmental Sciences, University of Waterloo, Waterloo, ON, § Department of Biological Sciences, University of Alberta, Edmonton, AB Ecosystem Metabolism and Air-Water Fluxes of Greenhouse Gases in High Arctic Ponds B13E-0579 Pond MetabolismAir-Water GHG Fluxes Take-Home: Introduction Background: Freshwater ponds are ubiquitous features of many Arctic landscapes These ponds are biogeochemical hotspots with a potentially large influence on regional carbon cycling By contrast, Lake Hazen is ultra-oligotrophic and is the largest lake (by volume) north of the Arctic Circle. These aquatic ecosystems are also sensitive to environmental change  changes in hydrology due increased melting of permafrost and glaciers  changes in growing season length due to longer ice-free season Research Questions: 1.Are these ponds net sources or sinks of carbon (heterophic vs. autotrophic) and other GHGs (greenhouse gases; e.g., N 2 O)? 2.Can we use stable-isotope techniques 1 (e.g.,changes in  18 O of dissolved oxygen (DO)) to gain insights into whole-pond metabolism, despite obvious challenges? i.Low signal (metabolism) to noise (air-water gas exchange) ratio in these shallow systems ii.Continuous daylight and therefore little amplitude in diel DO curves Study Area and location of ponds sampled. GHGs were monitored at a few select sites during June-July starting in A more extensive survey of ponds was conducted in July 2010 for quantifying aquatic ecosystem metabolic processes. A pond (Pond 16) receiving permafrost meltwater during the summer season. July 19 Lake Hazen Pond 1 Pond 2 Pond 11 Use of Stable-Isotopes for Investigating Metabolism  18 O-DO and  13 C-DIC in pond water showed significant deviations from atmospheric equilibrium as result of ecosystem metabolism, especially on 1 st sampling day (calm) compared to 2 nd sampling day (windy) It is possible to obtain rates of production (P) and respiration (R) from the DO concentration and  18 O data However, DIC pools were too large to be able to detect small changes in concentration and  13 C-DIC resulting from P and R Dissolved oxygen model constrained by equations (1) and (2): 1.dO 2 /dt= P – R + (k/z)(O 2(sat) – O 2 ) 2.d  /dt = P(  w +  p ) – R(  +  R  k/z)  k [(  atm  eq ) –  Used continuous measurements of wind speed, and water temperature to estimate gas-exchange component P scaled using measured PAR, R scaled based on water temperature and Q10 function Example of modeled DO concentrations and  18 O-DO compared to measured values Volumetric rates of production, respiration and gas-exchange in ponds during July SiteP:R ratio Pond Pond Pond 79.1 Pond Pond Pond Skeleton Lk.1.2 Are Ponds Heterotrophic or Autotrophic? Based on the dissolved oxygen model a ratio of production to respiration (P:R) was calculated Ponds exhibited a range from net autotrophic (P:R > 1, n = 2) to net heterotrophic (P:R <1, n = 2) with some ponds near-neutral (P:R ~1, n = 3) However, model fit for ponds with P:R > 1 is relatively poor, casting doubt on these results P:R did not appear to be a function of hydrology Model could not be resolved for Pond 10 Pond 1 model results are pending as model currently assumes constant water level which is not appropriate for a pond which becomes flooded ParameterMinMaxMedian Water Temp (°C)81711 pH DIC (  mol L -1 ) DOC (  mol L -1 ) CO 2 (  mol L -1 ) CO 2 (% Saturation) CH 4 (  mol L -1 ) n.d DIN (  g L -1 ) n.d.453 TDN (  g L -1 ) TDP (  g L -1 ) 4588 Cond (  S cm -1 ) Chla (  g L -1 ) A shoreline pond (Pond 1) flooding as a result of rising water levels in Lake Hazen. July 5 July 15 An evaporative pond (Pond 12), hydrologically isolated during the summer season. stream evaporative meltwater receiving shoreline { { { Ponds fall into three general categories based on hydrology : 1.Evaporative ponds: receive no or very little inputs of water after snowmelt is over Ponds 3, 7, 10 and 12 2.Meltwater receiving: receive inputs of water from ephemeral permafrost-fed streams Ponds 11, 16 and Skeleton Lake 3.Shoreline ponds: Exchange water with Lake Hazen depending on lake water level Pond 1: unidirectional flow into the pond Pond 2: bidirectional flow depending on relative water levels Water Chemistry Ponds are characterized by: Alkaline pH and high DIC Low DIN but high dissolved organic nitrogen Low suspended Chla and presence of benthic mosses and macrophytes suggests benthic productivity is more important than pelagic productivity Abbreviations: DIC – dissolved organic carbon; DOC – dissolved organic carbon; DIN – dissolved inorganic nitrogen; TDN – total dissolved nitrogen; TDP – total dissolved phosphorus; Cond – conductivity; Chla – suspended chlorophyll a; n.d. – not detected Pond Hydrology and Chemistry Stable isotope ratios (  13 C and  18 O) of DIC (a) and DO (b) in pond waters; relationship of  18 O vs. saturation (c) a b c Fluxes of CO 2 (a) and CH 4 (b) in Lake Hazen, Skeleton Lake and Pond 1. Note different scale for 2010 plots. a b Site N 2 O consumption (  mol m -2 h -1 ) Pond Pond Pond 1113 Pond 12n. d. Pond N 2 O fluxes: Ponds were N 2 O sinks and saturation ranged from n.d. to 97% N 2 O consumption rates (based on estimated gas exchanges) ranged from n.d. to 13  mol m -2 h -1 Dissolved N 2 O (% saturation) in pond waters on a calm day (first time point) and windy day (2 nd time point) CO 2 and CH 4 fluxes: 1.Fluxes in Pond 1 correlated with water level: CO 2 sink during low water level years (2005, 2007) but source during flood years ( ) CH 4 fluxes also higher in flood years 2.Skelton Lake: CO 2 concentrations higher during partial ice cover, decreasing during summer season CH 4 conc. have increased every year since 2007 during low water level years (2005, 2007) 3.Lake Hazen: Episodic high GHG concentrations, possibly as a result of water column mixing Equilibrium line Equilibrium point Pond 1 not flooded Pond 1 flooded 1 Venkiteswaran et al. Oecologia 2007, 153, Ponds in the Lake Hazen area tended to be heterotrophic and a source of CO 2 and CH 4, despite little allochthonous C inputs. They were also sinks for atmospheric N 2 O 2.Stable-isotope techniques hold promise for investigating metabolic processes in Arctic ponds, despite continuous summer daylight, and non steady-state conditions N 2 O Saturation (%)