ECOHYDROLOGY Ecohydrol. (2015) Published online in Wiley Online Library (wileyonlinelibrary.com) DOI: 10.1002/eco.1615
Nighttime and daytime respiration in a headwater stream Ricardo González-Pinzón,1* Marc Peipoch,2 Roy Haggerty,3 Eugènia Martí2 and Jan H. Fleckenstein4 2
1 Department of Civil Engineering, University of New Mexico, Albuquerque, NM 87131, USA Biogeodynamics and Biodivers Group, Centre d’Estudis Avançats de Blanes, Consejo Superior de Investigaciones Cientificas (CEAB-CSIC), Blanes, Spain 3 College of Earth, Ocean and Atmospheric Sciences, Oregon State University, Corvallis, OR 97331, USA 4 Department of Hydrogeology, UFZ—Helmholtz Centre for Environmental Research, Permoserstr. 15, 04318 Leipzig, Germany
ABSTRACT We investigated changes in respiration across nighttime and daytime in a headwater stream. For this, we conducted consecutive nighttime and daytime experiments injecting the bioreactive tracer resazurin in two reaches with different riparian canopy densities (different levels of photosynthetically active radiation) to compare respiration rate coefficients. We found that even though stream water temperatures measured above the streambed at day and night (half-day timescale) were different within each reach and across reaches (95% confidence level), apparent respiration rate coefficients were not different across nighttime and daytime conditions (95% confidence level). A likely explanation for this is that the bulk of stream respiration takes place in the hyporheic zone, where diel fluctuations of stream temperature and photosynthetically active radiation are considerably attenuated and where temperature is not measured in routine investigations of stream metabolism. Our results suggest that community respiration in headwater streams may not need to be ‘corrected’ for temperature between daytime and nighttime, even though instantaneous changes in respiration are expected to occur from a pure biological perspective. Copyright © 2015 John Wiley & Sons, Ltd. KEY WORDS
community respiration; resazurin; smart tracers; diel fluctuations; headwater stream; hyporheic zone; stream temperature; stream metabolism
Received 25 August 2014; Revised 28 January 2015; Accepted 30 January 2015
INTRODUCTION Correcting biological processing rates (e.g. respiration, decay) and chemical rates (e.g. stream–atmosphere mass transfer, hydrolysis) for temperature changes is a common practice (Metzger and Dobbins, 1967; Genereux and Hemond, 1992; Gillooly et al., 2001; Huey and Kingsolver, 2011). In biological systems, reaction rates increase with temperature until some maximum value where enzymatic activity is interrupted. As a first approximation, biological reaction rates are expected to double following a 10 °C increase in temperature within 0–40 °C, that is, the ‘biological range’ (Apple et al., 2006; Chapra, 2008). Because streams experience diel temperature fluctuations, we would like to understand how such changes control biochemical reaction rates, which, in turn, affect the cycling of carbon and major nutrients. Current methods to estimate stream metabolism are based on a dissolved oxygen (DO) mass balance. These methods quantify spatial variations in DO, and such *Correspondence to: Ricardo González-Pinzón, Department of Civil Engineering, MSC01 1070, University of New Mexico, Albuquerque, NM 87131, USA. E-mail:
[email protected]
Copyright © 2015 John Wiley & Sons, Ltd.
variations are related to fluxes of community respiration (CR), primary production (PP), stream–atmosphere mass transfer (reaeration) and stream–groundwater mass transfer. Because PP is zero at nighttime conditions, independent estimates of DO fluxes among the atmosphere–stream– ground water interfaces are used to ‘close’ the system, thus allowing an estimate of CR (and respiration rates). Once CR is estimated through nighttime DO mass balance, CR is either assumed effectively constant for daytime conditions, or temperature-corrected respiration rates are used to estimate CR at daytime conditions. To account for diel temperature fluctuations in kinetic processes, ecohydrology models typically adopt chemical models developed for systems that reach a sustained net change in temperature and that have effectively negligible temperature fluctuations (Thornton and Lessem, 1978). These models, including the van’t Hoff equation or Q10 formulation, have been widely used to correct respiration rates in stream ecosystems. Commonly, diel temperature fluctuations measured above the streambed are used in combination with a Q10-type formulation to correct respiration rates (Tobias et al., 2007; Holtgrieve et al., 2010; Demars et al., 2011), and it has been shown that correcting respiration rates for temperature fluctuations
might yield significantly different estimates of metabolic fluxes (Riley and Dodds, 2012). However, correcting respiration rates with these methods in headwater streams might be incorrect because of the following: (1) a steady-state model (Q10 formulation) is used to correct a dynamic process with fast cycling time scales (diel temperature fluctuations) and (2) temperature fluctuations are typically measured in a compartment where the least amount of respiration is expected to occur (i.e. on or above the streambed). Despite that previous experiments using oxygen stable isotopes have suggested that instantaneous respiration changes with stream temperature measured above the streambed, such relationship is not biunique and does not follow a one-loop hysteresis pattern either (cf. figure 7 in Tobias et al., 2007). Therefore, correcting respiration rates for diel temperature fluctuations might be misleading, and accounting for this may only add extra error to this already highly uncertain estimation. In this study, changes in respiration across night and daytime (i.e. half-day time scale) in a headwater stream were investigated. We used the resazurin–resorufin system in our experiments. Briefly, resazurin is a bioreactive tracer that can be used as a proxy-tracer to quantify aerobic respiration in stream ecosystems (Haggerty et al., 2008; González-Pinzón et al., 2012, 2014; González-Pinzón and Haggerty, 2013). Resazurin (Raz) is a redox-sensitive phenoxazine that under appropriate reducing conditions irreversibly loses an oxygen ion to become resorufin (Rru). Our experimental design considered two reaches with different riparian canopy densities [i.e. different photosynthetically active radiation (PAR) incoming fluxes] to broaden the effects of PAR in diel temperature fluctuations. We conducted consecutive nighttime and daytime experiments in each of the two reaches to compare respiration rate coefficients. We found that even though stream water temperatures were significantly different at nighttime and daytime conditions, respiration rate coefficients were not significantly different.
METHODOLOGY Study sites This study was conducted in two reaches of the stream Fuirosos, located in Catalonia (NE Spain). This headwater stream drains a 10·5 km2 catchment. The lithology composition is granodiorite and biotitic granodiorite (21% of total); leucogranite (51%); sericitic schists (24%); slate, mudstone, and limestone (2%); and an alluvial zone (2%) (Bernal, 2006). The two stream reaches are referred to as ‘Shaded’ and ‘Open’ (Table I, Figure 1), terms that are used as qualitative descriptors of the quantity of sunlight reaching the stream water. The Shaded reach has a high-density riparian forest. The riparian vegetation in the Open reach (located 3 km downstream of the Shaded reach) is sparser, primarily as a result of watershed management programmes for agriculture. We conducted similar experiments in both reaches. First, we conducted consecutive nighttime and daytime experiments in the downstream Open reach to avoid experimental interferences. We conducted similar, paired (night and day) experiments in the Shaded reach 4 days after the nighttime injection in the Open reach. The short time elapsed between the experiments and the dry conditions observed in the watershed during this period allowed us to compare the stream reaches under similar hydrological conditions (Table I). The experiments were conducted in the first 10 days of May 2012, and deciduous vegetation was at about 15% total foliage. The estimated Leaf Area Index [LAI = leaf area (L2)/ground area (L2)], which ranges from 0 (bare ground) to over 10 (dense conifer forests), was 4·2 ± 1·1 (mean ± SD) in the Shaded reach and 1·7 ± 0·7 in the Open reach. LAI was calculated from above and below riparian canopy readings of PAR using a Sunfleck PAR ceptometer (ICT international, Australia) and from reach-specific estimations of solar declination. Calculations were carried out following the gap fraction analysis proposed by Norman and Campbell (1989).
Table I. Sampling locations and type of subreach bedforms. Shaded reach, discharge = 7 Ls1 Station Inj. S1 S2 S3 S4 S5 S6 S7 Average
Open reach, discharge = 13 Ls1
Distance (m) % riffles – % pools Width (m) – depth (cm) Distance (m) % riffles – % pools Width (m) – depth (cm) 0 42 68 95 123 156 216 264
46 20 62 0 88 38 33
2·1 – 10 3·9 – 8 2·3 – 6 2·9 – 6 3·2 – 7 3·2 – 9 3·6 – 12
59 – 41
3·0 – 8·7
54 80 38 100 12 62 67
– – – – – – –
Copyright © 2015 John Wiley & Sons, Ltd.
0 41 61 75 139 214 293 359
23 33 33 7 36 65 18
2·7 – 7 2·7 – 6 2·7 – 4 2·7 – 5 3·6 – 7 3·6 – 15 2·7 – 7
68 – 32
3·1 – 8·2
77 67 67 93 64 35 82
– – – – – – –
Ecohydrol. (2015)
NIGHTTIME AND DAYTIME RESPIRATION IN A HEADWATER STREAM
Figure 1. Field map of two study sites located 3 km apart in the stream Fuirosos (Catalonia, Spain). (a) Shaded reach and (b) Open reach. Paired night and daytime experiments were first conducted in the Open reach to avoid experimental interferences. Background imagery was acquired from Google Earth.
PAR and stream temperature records We recorded paired PAR and stream water temperature every 30 min above the streambed with waterproof temperature and light data loggers (HOBO Pendant® UA-002-64). This information was recorded at representative sites in both reaches throughout the experiments (Table II). PAR data were used to distinguish between night and daytime conditions and to quantify the differences in incoming radiation reaching the Shaded and Open reaches at daytime conditions. A one-way analysis of variance (ANOVA) and Fisher’s least significant difference (LSD) (analysis of means) and Mood’s tests (analysis of medians) were used to determine statistically significant differences at the 95% confidence level (STATGRAPHICS® Centurion XVI). For the PAR data, the populations compared were the Shaded/day versus Open/day data. For the temperature data, we compared the six pairs formed by Shaded/day, Shaded/night, Open/day and Open/night. Stream tracer experiments We coinjected the bioreactive tracer resazurin (Raz) and the conservative tracer NaCl continuously for 3·0 h in the Open
reach and for 2·0 h in the Shaded reach. We attempted to increase Raz up to a maximum plateau concentration of 250 ppb and to increase the specific conductance by ~70 μS/cm from its background signal (~180 μS/cm). We took discrete Raz–Rru samples manually at stations S1–S4 in the Open reach, and S2–S5 in the Shaded reach (Table II, Figure 1). These samples were filtered (0·7 μm pore size GF/F) and refrigerated (iced water in the field and 4 °C in the lab) and read within 48 h with a Shimadzu RF lab spectrofluorometer. We also took semi-continuous (every 10 s) Raz–Rru readings with three on-line GGUNFL30 field fluorometers (Lemke et al., 2013) at stations S4–S5–S6 (Open reach) and S5–S6–S7 (Shaded reach). The field fluorometers were calibrated immediately before the nighttime injections, and the samples at S4 (Open reach) and S5 (Shaded) were used as a guide to match the readings of the lab and field fluorometers. Specific conductance was recorded with WTW (Weilheim, Germany) 3110 conductivity meters. The mean travel time τ between two sampling locations was estimated with the absolute, zeroth-order (m0) and first-order (m1) temporal moments of the conservative tracer breakthrough curves (BTCs) as follows:
Table II. Resazurin, photosinthetically active radiation (PAR) and temperature sampling scheme. Shaded reach Station S1 S2 S3 S4 S5 S6 S7
Open reach
Raz–Rru
PAR/temp.(# sites sampled)
Raz–Rru
PAR/temp.(# sites sampled)
M–L M–L M–L M–L, F–O F–O F–O –
2 (1R, 1P) 2 (1R, 1P) 1R 1P 1R 1R –
– M–L M–L M–L M–L, F–O F–O F–O
2 (1R, 1P) 2 (1R, 1P) 3R 3P 1R (failed) 1R –
M–L, manual sampling and lab reading; F–O, field sampling, on-line reading; P, pool; R, riffle. Copyright © 2015 John Wiley & Sons, Ltd.
Ecohydrol. (2015)
τ¼
mn ¼
k X
mdn 1; cons mdn 0; cons
mup 1; cons mup 0; cons
(1) λresp
ð0:5 t i þ 0:5 t iþ1 Þn ð0:5 C i þ 0:5 C iþ1 Þ ðt iþ1 t i Þ
i 8h Raz Raz Raz > λ K ; λ ; if K Raz > DO DO ¼ ½< 1; < 1 θ; sz θ; sz min > > 1 > > h i > > : λRaz ; λRaz K Raz ; if K Raz ¼ ½> 1; > 1 DO θ; sz θ; sz DOmax
i¼1
(2) where τ (T) is the mean travel time between two sampling locations; C(t) (ML3) is the measured concentration at time t (T); i (–) is an index; k (–) is the total number of observations in the concentration BTCs; and ‘up’ and ‘dn’ indicate the upstream and downstream boundaries of the reach, respectively. Our consecutive injections [2 × 2 h (or 3 h)] and numerical analysis (temporal moments) allowed us to estimate lumped respiration patterns at the half-day time scale. With this experimental design, we cannot resolve rapid metabolic responses to fluctuations in stream temperature (e.g. 8 mm
% organic matter
1 2 3 4 5 6
Shaded Shaded Shaded Open Open Open
Pool Riffle Riffle Pool Riffle Riffle
29·8 38·3 62·0 7·2 67·9 60·5
0·6 0·5 0·6 0·5 0·5 0·7
Ecohydrol. (2015)
NIGHTTIME AND DAYTIME RESPIRATION IN A HEADWATER STREAM 100%
0.125 mm
70%
0.25 mm
60%
0.355 mm
50%
0.5 mm
40% 30%
S2
S1
600
2 mm 10% > 8 mm 0%
Ch 1
Ch 2
Ch 3
Ch 4
Ch 5
Ch 6
Figure 2. Size distribution of the sediments used in the closed chamber experiments (i.e. Ch 1–Ch 6). Colours in the bars represent different sieve diameters and percentages reflect the fraction of mass retained by the sieves.
information recorded. This information suggests that there is a 3:1 ratio between the mean PAR in the Open and Shaded reaches (respectively) and a 4:1 ratio between the ranges of PAR available. Furthermore, Fisher’s LSD and Mood’s tests suggest that there are statistically significant differences between the means and medians of the PAR recorded at both reaches.
S4
S5
S6
Rd
Rd
200 0 Rd
Pd
Rd
Pd
Rd
Pd
b) Open reach
1 mm
20%
S3
400
0.71 mm
PAR [μ mol m -2 s -1 ]
Sediment size distribution
< 0.125 mm
80%
PAR [μ mol m -2 s -1 ]
a) Shaded reach
90%
2500
S2
S1
S4
S3
S6
2000 1500 1000 500 0 Pd
Rd
Pd
Rd
Rd
Rd
Rd
Pd
Pd
Pd
Rd
Figure 3. Photosynthetically active radiation (PAR) recorded at representative sites near the sampling stations (e.g. S1, S2) during daytime injections (cf. Tables I and II). (a) Shaded reach; (b) Open reach. Mean and median PAR values in both reaches are significantly different at the 95% confidence level (Fisher’s LSD and Mood’s median test). P: pool; R: riffle; d: day.
tures were significantly different for the consecutive (night and daytime) experiments, as well as across reaches (i.e. Open vs. Shaded).
Differences in night and day time stream water temperatures
Raz and DO uptake rates as a function of stream bedforms
We tracked stream water temperature above the streambed to determine the impacts of diel temperature changes on respiration rate coefficients. Nighttime and daytime stream temperatures during the tracer experiments were monitored for 8 h, that is, from 9 PM to 5 AM and from 11 AM to 7 PM, respectively. The range of stream water temperatures (considering both night and daytime) was 3·6 °C in the Shaded reach and 7·6 °C in the Open reach. Figure 4 and Table IV summarize the information recorded in both reaches. Results indicate that mean and median tempera-
We investigated the variability of K Raz DO within and across our stream reaches with chamber experiments. We used the ratios Δ DO/Δ Raz from each chamber experiment to 2 analyse the variability of K Raz DO (Figure 5). R ·> 0·92 in all regressions, suggesting a strong linear relationship between the transformation of Raz and respiration. In summary, K Raz DO ¼ ½0:85; 1:40 for the experiments with sediments from the Shaded reach and K Raz DO ¼ ½0:68; 1:30 for the Open reach. K Raz DO ¼ ½0:68; 0:85 for the experiments with sediments from pools and K Raz DO ¼ ½0:82; 1:40 for riffles.
Table IV. Photosinthetically active radiation (PAR) and stream water temperature values recorded during each of the experiments in both reaches. Reach/experiment
Mean
Standard deviation
Coeff. of variation (%)
PAR[μmol m-2 s-1]
Shaded/ dayb Open/dayb
119·3 323·4
91·1 403·9
76·3 124·9
Stream water temperature [°C]
Shaded/nightc Shaded/dayb
14·1 15·9
0·4 0·8
2·5 5·3
1·8 2·8
Yes
Open/nightc Open/dayb
14·9 18·0
0·8 1·4
5·7 7·7
4·3 6·8
Yes
Range
Significant differencea
681 2752
Yes Yesd
a
A one-way analysis of variance (ANOVA), and Fisher’s least significant difference (LSD) (analysis of means) and Mood’s tests (analysis of medians) were used to determine statistically significant differences at the 95% confidence level. b Daytime information recorded is from 11 a.m. (injection) to 7 p.m., that is, 8 h total. c Nighttime information recorded is from 9 p.m. (injection) to 5 a.m., that is, 8 h total. d All six possible pairs are significantly different.
Copyright © 2015 John Wiley & Sons, Ltd.
Ecohydrol. (2015)
Water temperature [°C] Water temperature [°C]
a) Shaded reach
respiration rate coefficients using Raz as a proxy-tracer were bounded by the values of K Raz DO (cf. Equation (4)). Fisher’s (LSD) test suggest that chambers 1, 4 and 6 form a homogeneous group of samples, with mean K Raz DO values that are not significantly different at the 95% confidence level. Chambers 4 and 6 were filled with sediments from riffles, whereas chamber 1 was filled with sediments from a pool. Chambers 2, 3 and 5 form another homogeneous group. Chambers 2 and 3 were filled with sediments from pools and chamber 5 with sediments from a riffle. Although our results suggest the presence of microbial communities with differences in the metabolism of Raz and DO, our sampling strategy was not sufficiently extensive to draw conclusions regarding spatial patterns in the arrangement of such communities (i.e. bedform type vs. light availability). Nonetheless, the differences observed in values did not affect our comparison between K Raz DO nighttime and daytime respiration patterns because it is unlikely that the microbial communities had changed within the timeframe of each of our experiments.
18 S2
S1
S4
S3
S6
S5
17 16 15 14 Rn Rd Pn Pd Rn Rd Pn Pd Rn Rd Pn Pd Rn Rd Rn Rd
b) Open reach 20
S2
S1
S4
S3
S6
18 16 14 Pn Pd Rn Rd Pn Pd Rn Rd Rn Rd Rn Rd Rn Rd Pn Pd Pn Pd Pn Pd Rn Rd
Figure 4. Stream water temperature recorded at representative sites near the sampling stations (e.g. S1, S2) during night and daytime consecutive injections (cf. Tables I and II). Recording times span from the beginning of the injection up to 8 h later. Day and night mean and median temperatures are significantly different at the 95% confidence level (Fisher’s LSD and Mood’s median test). P, pool; R, riffle; n, night; d, day.
Differences in respiration rate coefficients Finally, ¼ ½0:68; 1:40 when all the experiments are considered. From the chamber experiments, we were able to define uncertainty bounds for the estimation of respiration rate coefficients for the daytime and nighttime experiments. Because generally K Raz DO ¼ ½< 1; > 1 , the estimates of K Raz DO
Pool − Shaded, Ch 1
Besides using oxygen stable isotopes, which are logistically challenging (Tobias et al., 2007), current methods do not allow independent estimates of respiration rates (and fluxes) at nighttime and daytime because of the multiple and parallel pathways for oxygen production and consumption, that is, respiration, PP, stream–atmosphere mass
Riffle − Shaded, Ch 2
0.2 0.18
Riffle − Shaded, Ch 3
0.8
0.7
0.7
0.6
0.16 0.6
0.5
0.1
0.5
ΔDO
0.12
ΔDO
ΔDO
0.14
0.4
0.4 0.3
0.08
0.3
0.06
0.2 0.2
0.04
data
0.02 0
K 0
0.05
0.1
0.1
= 0.85; R = 0.98
0.15
0.2
ΔRaz
K 0
0.25
0
0.1
0.2
Pool − Open, Ch 4
0.3
0.4
0.5
ΔRaz
1
0.4
0.9
0.6
K 0
0.7
0
0.05
0.1
0.15
0.2
0.25
0.3
= 1.2; R = 0.96
0.35
0.4
0.45
0.5
ΔRaz Riffle − Open, Ch 6 0.7 0.6
0.8 0.5
0.7
0.25
0.6
ΔDO
ΔDO
0.3
0.5
0.2 0.3
0.1
0.4 0.3
0.4 0.15
0.2
0.2
data
0.05
K 0
data
= 1.4; R = 0.92
Riffle − Open, Ch 5
0.45
0.35
ΔDO
0.1
data
0
0.1
0.2
0.3
0.4
ΔRaz
0.5
0.6
0.7
0
0.1
data
0.1
= 0.68; R = 0.99
K 0
0.1
0.2
0.3
0.4
ΔRaz
0.5
data
= 1.3; R = 0.92 0.6
0.7
K 0.8
0
0
0.1
0.2
0.3
0.4
ΔRaz
= 0.82; R = 0.99 0.5
0.6
0.7
Figure 5. Molar uptake ratio of DO consumed (Δ DO) to Raz consumed (Δ Raz), K Raz DO , in different chamber (Ch) experiments. Sediment samples were taken from representative pools and riffles. Top panel shows results with sediments from the Shaded reach (Ch 1, Ch 2 and Ch 3); bottom panel from the Open reach (i.e. Ch 4, Ch 5 and Ch 6).
Copyright © 2015 John Wiley & Sons, Ltd.
Ecohydrol. (2015)
NIGHTTIME AND DAYTIME RESPIRATION IN A HEADWATER STREAM
transfer (reaeration) and stream–groundwater interactions (McCutchan et al., 2002; Bott, 2007; Reichert et al., 2009). Raz might be a suitable proxy-tracer for estimating diel fluctuations of respiration because there is a nearly perfect linear relationship between oxygen consumption and Raz uptake (cf. Figure 5 and González-Pinzón et al., 2012). Furthermore, Raz is not naturally present (or produced) in groundwater systems or in the atmosphere. However, the rate of transformation of Raz and oxygen consumption has to be found via calibration, that is, K Raz DO has to be estimated. Figure 6a shows the estimated respiration rates (λresp.) for the nighttime and daytime consecutive experiments in the Shaded reach. This figure shows the estimated rates considering the minimum and maximum K Raz DO values found in the chambers with sediments from the Shaded reach. Figure 6b shows the estimated λresp. for the consecutive experiments conducted in the Open reach. Fisher’s (LSD) and Mood’s statistical test of the results presented in Figure 6 indicates that the mean and median rate coefficients estimated at nighttime and daytime conditions in each of the Open and Shaded reaches are not different at the 95% confidence level. Similar results were found when the minimum and maximum K Raz DO values found in all chamber experiments were used to estimate λresp.. Also, respiration rates in the Shaded and Open reaches were in the same order of
magnitude. Despite that PAR and stream water temperature above the streambed are significantly different between night and daytime experiments (Table IV and Figures 3 and 4), such differences did not significantly affect respiration rate coefficients at the half-day timescale (Figure 6). Most likely, the bulk of stream respiration takes place in the hyporheic zone, where diel fluctuations of stream temperature and PAR are considerably attenuated (Constantz, 2008) and where temperature is not measured in routine investigations of stream metabolism. Therefore, ‘correcting’ respiration rates (and fluxes) to compensate for the observed fluctuations in stream water temperature above the streambed might be misleading and may lead to incorrect estimates of metabolism in headwater streams. Finally, because of the tight coupling between metabolism and nutrient cycling in streams (Fellows et al., 2006), our findings of constant respiration rate coefficients at daytime and nighttime support previous results suggesting that autotrophs might be primarily responsible for the larger diurnal uptake rates of nutrients observed in forested streams (Burns, 1998; Mulholland et al., 2006). These studies argue that the additional energy provided by photosynthates increase nutrient uptake, but because respiration rates were not measure at daytime and nighttime conditions, differences in respiration could not be ruled out.
a) Shaded reach
b) Open reach
Figure 6. Respiration rate coefficients (λresp.) at night (n) and daytime (d) estimated from the Raz–Rru system for different subreaches in the (a) Shaded and (b) Open reaches. Subreaches are defined by two Raz–Rru sampling stations (e.g. S1–S2). Upper and bottom whiskers represent the uncertainty in λresp. considering only the molar processing ratio of DO to Raz (K Raz DO ) from experiments in each of the respective reaches (cf. Equation (4)). Circles represent the estimated value of the transformation rate coefficient of Raz (λRaz θ; sz ). Copyright © 2015 John Wiley & Sons, Ltd.
Ecohydrol. (2015)
ACKNOWLEDGEMENTS
This work was funded by NSF grants EAR 09-38338 and IIA-1301346, and by the Spanish Ministry of Science and Innovation through the ISONEF (ref: CGL2008-05504-C0202/BOS) project. We thank Stephanie Merbt, Clara Romero González-Quijano, Sandra Serra, Miquel Ribot, Toraf Keller and Eduardo Martín Sanz for lab and field assistance. REFERENCES Apple JK, del Giorgio PA, Kemp WM. 2006. Temperature regulation of bacterial production, respiration, and growth efficiency in a temperate salt-marsh estuary. Aquatic Microbial Ecology 43(3): 243–254. Bernal S 2006. Nitrogen storm responses in an intermittent mediterranean stream, PhD dissertation: Universitat de Barcelona. Bott TL 2007. Primary productivity and community respiration. In: Methods in Stream Ecology, Academic Press: Burlington, MA USA; 663–390. Burns DA. 1998. Retention of NO3/- in an upland stream environment: a mass balance approach. Biogeochemistry 40: 73–96. Chapra SC 2008. Surface Water-Quality Modeling Waveland Press Inc.: Long Grove, IL USA; 24–42. Constantz J. 2008. Heat as a tracer to determine streambed water exchanges. Water Resources Research 44, W00D10, Doi:10.1029/ 2008WR006996. Demars BOL, Manson JR, Olafsson JS, Gislason GM, Gudmundsdottir R, Woodward G, Reiss J, Pichler DE, Rasmussen JJ, Friberg N. 2011. Temperature and the metabolic balance of streams. Freshwater Biology 56(6): 1106–1121. Fellows CS, Valett HM, Dahm CN. 2001. Whole-stream metabolism in two montane streams: contribution of the hyporheic zone. Limnology and Oceanography 46(3): 523–531. Fellows CS, Valett HM, Dahm CN, Mulholland PJ, Thomas SA. 2006. Coupling nutrient uptake and energy flow in headwater streams. Ecosystems 9(5): 788–804. Genereux DP, Hemond HF. 1992. Determination of gas exchange rate constants for a small stream on Walker Branch Watershed, Tennessee. Water Resources Research 28(9): 2365–2374. Gillooly JF, Brown JH, West GB, Savage VM, Charnov EL. 2001. Effects of size and temperature on metabolic rate. Science 293(5538): 2248–2251. González-Pinzón R, Haggerty R. 2013. An efficient method to estimate processing rates in streams. Water Resources Research 49, 6096–6099, doi:10.1002/wrcr.20446. González-Pinzón R, Haggerty R, Myrold DD. 2012. Measuring aerobic respiration in stream ecosystems using the resazurin–resorufin system. Journal of Geophysical Research, Biogeosciences 117(G3): doi:10.1029/2012JG001965.
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