Ecosystem respiration: Drivers of daily variability and background respiration in lakes around the globe

We assembled data from a global network of automated lake observatories to test hypotheses regarding the drivers of ecosystem metabolism. We estimated daily rates of respiration and gross primary production (GPP) for up to a full year in each lake, via maximum likelihood fits of a free‐water metabolism model to continuous high‐frequency measurements of dissolved oxygen concentrations. Uncertainties were determined by a bootstrap analysis, allowing lake‐days with poorly constrained rate estimates to be down‐weighted in subsequent analyses. GPP and respiration varied considerably among lakes and at seasonal and daily timescales. Mean annual GPP and respiration ranged from 0.1 to 5.0 mg O2 L−1 d−1 and were positively related to total phosphorus but not dissolved organic carbon concentration. Within lakes, significant day‐to‐day differences in respiration were common despite large uncertainties in estimated rates on some lake‐days. Daily variation in GPP explained 5% to 85% of the daily variation in respiration after temperature correction. Respiration was tightly coupled to GPP at a daily scale in oligotrophic and dystrophic lakes, and more weakly coupled in mesotrophic and eutrophic lakes. Background respiration ranged from 0.017 to 2.1 mg O2 L−1 d−1 and was positively related to indicators of recalcitrant allochthonous and autochthonous organic matter loads, but was not clearly related to an indicator of the quality of allochthonous organic matter inputs

Sedimentary Environment Influences the Effect of an Infaunal Suspension Feeding Bivalve on Estuarine Ecosystem Function

The suspension feeding bivalve Austrovenus stutchburyi is a key species on intertidal sandflats in New Zealand, affecting the appearance and functioning of these systems, but is susceptible to several environmental stressors including sedimentation. Previous studies into the effect of this species on ecosystem function have been restricted in space and time, limiting our ability to infer the effect of habitat change on functioning. We examined the effect of Austrovenus on benthic primary production and nutrient dynamics at two sites, one sandy, the other composed of muddy-sand to determine whether sedimentary environment alters this key species' role. At each site we established large (16 m2) plots of two types, Austrovenus addition and removal. In winter and summer we deployed light and dark benthic chambers to quantify oxygen and nutrient fluxes and measured sediment denitrification enzyme activity to assess denitrification potential. Rates of gross primary production (GPP) and ammonium uptake were significantly increased when Austrovenus was added, relative to removed, at the sandy site (GPP, 1.5 times greater in winter and summer; ammonium uptake, 8 times greater in summer; 3-factor analysis of variance (ANOVA), p<0.05). Denitrification potential was also elevated in Austrovenus addition plots at the sandy site in summer (by 1.6 times, p<0.1). In contrast, there was no effect of Austrovenus treatment on any of these variables at the muddy-sand site, and overall rates tended to be lower at the muddy-sand site, relative to the sandy site (e.g. GPP was 2.1 to 3.4 times lower in winter and summer, respectively, p<0.001). Our results suggest that the positive effects of Austrovenus on system productivity and denitrification potential is limited at a muddy-sand site compared to a sandy site, and reveal the importance of considering sedimentary environment when examining the effect of key species on ecosystem function

Long-term nitrate removal in a denitrification wall

Denitrification walls are a low-cost approach for removing excess nitrate (NO₃⁻) from shallow groundwater. Denitrification walls need to be maintenance-free for a number of years to remain cost effective, but little is known about the longevity of these walls. In this study, a denitrification wall constructed on a New Zealand dairy farm in 1996 was monitored to determine NO₃⁻ removal by the wall 14 years after installation. After 14 years, the denitrification wall removed 92% of NO₃⁻ input, which ranged from 2.2 to 3.7 mg N L−1. The NO₃⁻ input to the wall had decreased since first constructed, which was attributed to a change in upslope irrigation practices on the farm. Denitrifying enzyme activity (DEA) remained high after 14 years and the wall remained NO₃⁻ limited. However, total C and microbial biomass C in the wall had decreased by approximately half, while available C remained relatively constant since year 2. By applying a first order decay curve, it was determined that total C in the denitrification wall would not be depleted for 66 years, but it is unclear at what amount of total C that denitrification would become limited. This long-term study suggested that denitrification walls are cost effective solutions for remediating groundwater NO₃⁻ pollution, as they can be effective for a number of years without any maintenance

Are geothermal streams important sites of nutrient uptake in an agricultural and urbanising landscape (Rotorua, New Zealand)?

Increased nutrient loading and eutrophication are common problems for lakes globally (Carpenter et al., 1998; Smith & Schindler, 2009). New Zealand is no exception, where 30% of lakes >1 ha have very poor to extremely poor water quality (Van Bunnik et al., 2007). Many of the iconic lakes in the well-known, geothermally active Rotorua region of New Zealand exhibit the adverse affects of eutrophication, including harmful algal blooms, bottom water hypoxia, reduced clarity (Hamilton et al., 2010) and loss of aquatic biodiversity (Hamilton, 2004; Burns, Mcintosh & Scholes, 2009). These lakes are important to New Zealand both economically and culturally (Edgar, 2009)

Denitrification potential in lake sediment increases across a gradient of catchment agriculture

Intensification of catchment agriculture has increased nutrient loads and accelerated eutrophication in some lakes, often resulting in episodic harmful algal blooms or prolonged periods of anoxia. The influence of catchment agriculture on lake sediment denitrification capacity as a nitrogen (N) removal mechanism in lakes is largely unknown, particularly in contrast to research on denitrification in agricultural streams and rivers. We measured denitrification enzyme activity (DEA) to assess sediment denitrification potential in seven monomictic and three polymictic lakes that range in the proportion of agriculture in the catchment from 3 to 96% to determine if there is a link between agricultural land use in the lake catchment and sediment denitrification potential. We collected sediment cores for DEA measurements over 3 weeks in austral spring 2008 (October– November). Lake Okaro, with 96% catchment agriculture, had approximately 15 times higher DEA than Lake Tikitapu, with 3% catchment agriculture (232.2 ± 55.9 vs. 15.9 ± 4.5 lg N gAFDM -1 h-1, respectively). Additionally, sediment denitrification potential increased with the proportion of catchment in agriculture (R2 = 0.85, P < 0.001). Our data suggest that lakes retain a high capacity to remove excessNvia denitrification under increasing N loads from higher proportions of catchment agriculture. However, evidence from the literature suggests that despite a high capacity for denitrification and longer water residence times, lakes with high N loads will still remove a smaller proportion of their N load. Lakes have a denitrification potential that reflects the condition of the lake catchment, but more measurements of in situ denitrification rates across lake catchments is necessary to determine if this capacity translates to high N removal rates

Rates, controls and potential adverse effects of nitrate removal in a denitrification bed

Denitrification beds are a simple approach for removing nitrate (NO₃⁻) from a range of point sources prior to discharge into receiving waters. These beds are large containers filled with woodchips that act as an energy source for microorganisms to convert NO₃⁻ to nitrogen (N) gases (N₂O, N₂) through denitrification. This study investigated the biological mechanism of NO₃⁻ removal, its controlling factors and its adverse effects in a large denitrification bed (176 m × 5 m × 1.5 m) receiving effluent with a high NO₃⁻ concentration (>100 g N m⁻³) from a hydroponic glasshouse (Karaka, Auckland, New Zealand). Samples of woodchips and water were collected from 12 sites along the bed every two months for one year, along with measurements of gas fluxes from the bed surface. Denitrifying enzyme activity (DEA), factors limiting denitrification (availability of carbon, dissolved organic carbon (DOC), dissolved oxygen (DO), temperature, pH, and concentrations of NO₃⁻, nitrite (NO₂⁻) and sulfide (S²⁻)), greenhouse gas (GHG) production – as nitrous oxide (N₂O), methane (CH₄), carbon dioxide (CO₂) – and carbon (C) loss were determined. NO₃⁻-N concentration declined along the bed with total NO₃⁻-N removal rates of 10.1 kg N d⁻¹ for the whole bed or 7.6 g N m⁻³ d⁻¹. NO₃⁻-N removal rates increased with temperature (Q₁₀ = 2.0). In laboratory incubations, denitrification was always limited by C availability rather than by NO₃⁻. DO levels were above 0.5 mg L⁻¹ at the inlet but did not limit NO₃⁻-N removal. pH increased steadily from about 6 to 7 along the length of the bed. Dissolved inorganic carbon (C-CO₂) increased in average about 27.8 mg L⁻¹, whereas DOC decreased slightly by about 0.2 mg L⁻¹ along the length of the bed. The bed surface emitted on average 78.58 μg m−² min⁻¹ N₂O-N (reflecting 1% of the removed NO₃⁻-N), 0.238 μg m⁻² min⁻¹ CH₄ and 12.6 mg m⁻² min⁻¹ CO₂. Dissolved N₂O-N increased along the length of the bed and the bed released on average 362 g dissolved N₂O-N per day coupled with N₂O emission at the surface about 4.3% of the removed NO₃⁻-N as N₂O. Mechanisms to reduce the production of this GHG need to be investigated if denitrification beds are commonly used. Dissolved CH₄ concentrations showed no trends along the length of the bed, ranging from 5.28 μg L⁻¹ to 34.24 μg L⁻¹. Sulfate (SO₄²⁻) concentrations declined along the length of the bed on three of six samplings; however, declines in SO₄²⁻ did not appear to be due to SO₄²⁻ reduction because S²⁻ concentrations were generally undetectable. Ammonium (NH₄⁺) (range: <0.0007 mg L⁻¹ to 2.12 mg L⁻¹) and NO₂⁻ concentrations (range: 0.0018 mg L⁻¹ to 0.95 mg L⁻¹) were always very low suggesting that anammox was an unlikely mechanism for NO₃⁻ removal in the bed. C longevity was calculated from surface emission rates of CO₂ and release of dissolved carbon (DC) and suggested that there would be ample C available to support denitrification for up to 39 years. This study showed that denitrification beds can be an efficient tool for reducing high NO₃⁻ concentrations in effluents but did produce some GHGs. Over the course of a year NO₃⁻ removal rates were always limited by C and temperature and not by NO₃⁻ or DO concentration

A comparison of different approaches for measuring denitrification rates in a nitrate removing bioreactor

Denitrifying woodchip bioreactors (denitrification beds) are increasingly used to remove excess nitrate (NO₃⁻) from point-sources such as wastewater effluent or subsurface drains from agricultural fields. NO₃⁻ removal in these beds is assumed to be due to microbial denitrification but direct measurements of denitrification are lacking. Our objective was to test four different approaches for measuring denitrification rates in a denitrification bed that treated effluent discharged from a glasshouse. We compared these denitrification rates with the rate of NO₃⁻ removal along the length of the bed. The NO₃⁻ removal rate was 8.73 ± 1.45 g m⁻³ d⁻¹. In vitro acetylene inhibition assays resulted in highly variable denitrification rates (DRAI) along the length of the bed and generally 5 times greater than the measured (NO₃⁻- N removal rate. An in situ push–pull test, where enriched ¹⁵N- NO₃⁻was injected into 2 locations along the bed, resulted in rates of 23.2 ± 1.43 g N m⁻³ d⁻¹ and 8.06 ± 1.64 g N m⁻³ d⁻¹. The denitrification rate calculated from the increase in dissolved N2 and N2O concentrations (DRN2) along the length of the denitrification bed was 6.7 ± 1.61 g N m⁻³ d⁻¹. Lastly, denitrification rates calculated from changes in natural abundance measurements of δ¹⁵N-N₂ and δ¹⁵N- NO₃⁻ along the length of the bed yielded a denitrification rate (DRNA) of 6.39 ± 2.07 g m⁻³ d⁻¹. Based on our experience, DRN2 measurements were the easiest and most efficient approach for determining the denitrification rate and N₂O production of a denitrification bed. However, the other approaches were useful for testing other hypotheses such as factors limiting denitrification or may be applied to determine denitrification rates in environmental systems different to our study site. DRN2 does require very careful sampling to avoid atmospheric N2 contamination but could be used to rapidly determine denitrification rates in a variety of aquatic systems with high N2 production and even water flows. These measurements demonstrated that the majority of NO₃⁻ removal was due to heterotrophic denitrification

3-factor ANOVA (analysis of variance) results for log₁₀ transformed DEA (denitrification enzyme activity; i.e. sediment denitrification potential).

<p>Factors are site (Sd  =  Sandy, Ms  =  Muddy-sand), season (Wi  =  Winter, Su  =  Summer) and treatment (+AS  =  <i>Austrovenus</i> addition, –AS  =  <i>Austrovenus</i> removal). Values in bold are significant at <i>p</i><0.05. Tukey post-hoc tests for significant differences between site, season and treatment are shown at α = 0.05.</p

O₂ fluxes and gross primary production (GPP).

<p>(A) Mean (+ 1 SD; n = 3) O₂ fluxes in light (no fill) and dark (black fill) chambers in <i>Austrovenus</i> addition (+AS) and removal (–AS) plots, as a function of site and season. Positive values represent an efflux out of the sediment, and negative values represent an influx into the sediment. (B) Mean (+ 1 SD; n = 3) normalised GPP (light minus dark chamber O₂ flux) in +AS (grey fill) and –AS (no fill) plots, as a function of site and season.</p