the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 15 Jan 2024
Yakima River Basin Water Column Respiration is a Minor Component of River Ecosystem Respiration
Abstract. Aerobic respiration of organic matter is a key metabolic process influencing carbon (C) biogeochemistry in aquatic ecosystems. Anthropogenic and environmental perturbations to stream ecosystem metabolism can have deleterious effects on downstream water quality. Various environmental features of rivers also influence stream metabolism, including physical (e.g., discharge, light, flow regimes) and chemical factors (nutrients, organic matter) and watershed characteristics (e.g., stream size or drainage area, land use). The relative proportion of surface water contact with benthic sediments has been considered the primary driver of ecosystem processes, including ecosystem respiration (ER). While aquatic ecosystem respiration occurs in the water column (ERwc) and in benthic sediments—including surficial and subsurface sediments (ERsed)—ERsed has long been assumed to be the primary contributor to whole-river ecosystem respiration (ERtot). Recent studies show, however, that somewhere along the river continuum (e.g., 5th–9th order), rivers transition from being dominated by benthic processes to being dominated by water column processes. Yet few metabolism studies have parsed contributions from the water column (ERwc) to ERtot, making it difficult to evaluate the relative magnitude and importance of ERwc across the river continuum and across biomes. In this study, we used the Yakima River basin, Washington, USA, to increase our understanding of basin-scale variation in ERwc. We collected ERwc data and water chemistry samples in triplicate at 47 sites in the Yakima River basin distributed across Strahler stream orders 2–7 and different hydrological and biophysical settings during summer baseflow conditions in 2021. We found that observed ERwc rates were consistently slow throughout the basin during baseflow conditions, ranging from −0.11–0.03 mg O2 L⁻1 d⁻1, and were generally at the very slow end of the range of published ERwc literature values. When compared to reach-scale ERtot rates predicted for rivers across the conterminous United States (CONUS), the very slow ERwc rates we observed throughout the Yakima River basin indicate that ERwc is likely a small component of ERtot in this basin. Despite these slow rates, ERwc nonetheless shows spatial variation across the Yakima River basin that was well explained by watershed characteristics and water chemistry. Multiple linear regression model results show that nitrate (NO3-N), dissolved organic carbon (DOC), and temperature together explained 41.5 % of the spatial variation in ERwc. Supporting the findings of other studies, we found that ERwc increased linearly with increasing NO3-N, increasing DOC, and increasing temperature. We hypothesize that low concentrations of nutrients, DOC, and low temperatures in the water column, coupled with low TSS concentrations, likely contribute to the slow ERwc rates observed throughout the Yakima River basin. Because ERtot measurements integrate contributions from water column respiration and sediment-associated respiration (ERsed), estimating ERtot in cold, clear, low nutrient rivers like those in the Yakima River basin with very slow ERwc will essentially measure contributions from ERsed.
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Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2023-3038', Anonymous Referee #1, 04 Mar 2024
Review of “Yakima River Basin Water Column Respiration is a Minor Component of River Ecosystem Respiration” by Fulton et al.
Summary: Fulton et al. measured ecosystem respiration in the water column (ERwc) and collected data on water chemistry (e.g. nutrients, temperature, DOC, DOM) at 46 sites across the Yakima River basin. Multiple linear regression revealed that the spatial variation of ERWC was mainly explained by temperature, nitrate and DOC concentrations. Further, authors compared measured ERwc rates to whole-river ecosystem respiration rates (ERtot) and ERwc values both derived from the literature. From this comparison they conclude that measured ERwc was comparably low and is likely a small component of ERtot.
General comments: The works strength is a reliable measure of ERwc across a broad spatial and environmental range in rivers (Strahler stream order 2-7) and its broad range of predictors derived from basic physicochemical measures to high resolution DOM data. In general, the manuscript is well written and the structure is clear. However, I have two main concerns:
- From a sentence in the abstract (line 25) I derive the two main justifications for this paper. The first one is to better understand the contribution of ERwc to ERtot. Hence, I was surprised that the authors only measured ERwc and did not simultaneously measure ERtot or/and respiration from the sediment. Obviously, this is nothing the authors can change now and they try to make up for this shortcoming with an exhaustive comparison of ERWC values to ERtot and ERwc values derived from the literature. The comparison is interesting and valuable, still, I think that the focus in this study lies too much on this first justification, without really backing it up with new data. The authors even imply in the last paragraph that they plan to address the shortcoming of not measured ERtot in future work (line 537), this might be the right time to focus on the contribution of ERwc to ERtot. I suggest to keep the comparison with the literature, but move the focus of this study to the second justification.
- The second justification was to gain a better understanding of the “relative magnitude and importance of ERwc across the river continuum and across biomes.” (line 26). A deeper investigation of ERwc shifts along the river continuum was held out in prospect but not followed through (“river continuum” was mentioned two times in the abstract, once in the introduction, but after that not anymore). Understanding the “relative magnitude” to ERtot is not possible without ERtot measurements conducted at the same time and location, however, investigating a shift of the absolute ERwc values along the river continuum might be still interesting. Anyway, discussing this topic in the Results and discussion sections is necessary, even if Strahler stream order or catchment area, which both can be used as proxies for the position of a site in the river continuum, were not significant in the multiple regression analysis. I also suspect that a potential effect of these two proxies on ERWC might have been overseen by large environmental differences among subcatchments. These differences could have created differences in intercepts of ERwc-“river continuum” relationships among subcatchments, hence, lumping together all sites without considering spatiality might blur the overall ERwc-“river continuum” relationship. Revealing a potential shift of ERwc along the river continuum needs a model accounting for spatial autocorrelation because sites within a river network are not independent from each other. Spatial stream network models account for spatial autocorrelation and might be a way to go (see e.g. Peterson, E. E. & Ver Hoef, J. M. A mixed-model moving-average approach to geostatistical modeling in stream networks. Ecology 91, 644–651 (2010))
Specific comments
17: If the word limit of the Abstract allows, I suggest to move the examples for anthropogenic and environmental perturbation mentioned in line 46 up here.
24: In case the suggested shift from benthic to water column processes by the mentioned studies occur all between 5th and 9th order, I suggest to change from “(e.g., 5th-9th order)” to “(5th-9th order)”. If this is not the case, I suggest to show the range from the smallest reported stream order to the largest reported stream order.
26: change to “along the river continuum”
48: I miss an example of how anthropogenic/environmental perturbations of GPP/ER can change downstream water quality.
86: Please rephrase, otherwise the meaning of the sentence is confusing. I suggest “… water column denitrification accounted for 0–85 % of reach-scale denitrification and water column respiration accounted for 39–85 % of reach- scale ERtot (i.e., ERwc + ERsed)”. If my suggestion is not correct, please clarify.
93: What do you mean with “direct” ERWC measurements?
126: “against ERWC and ERtot values found in the literature”
143: It is not clear why in this sentence only “the variability in hydrologic settings” is mentioned, as also biophysical attributes where used for the clustering (line 140). In line 142 you write about “similar landscape characteristics”, in line 144 “biophysical and hydrological attributes” and in line 166 “geospatial variables”. Overall, this paragraph could use a more coherent use of terms for the different variables used in the cluster analysis.
165: I suggest to write “similar properties”.
332: Somewhere around this line you should state how you checked for multicollinearity.
339: What did you do when depth data were not available?
341: Although you did not directly measure ERtot it is a very important parameter in you study, hence, I suggest to provide details in 1-2 sentences about how Appling et al. 2018c derived ERtot values. And the Results and discussion section would then need a critical evaluation of how well the two different methods for ERWC and ERtot can be compared.
424-425: You provide information on the methodology for papers with the footnotes “c” and “d”. I assume that the direct citation derives from the sources given in Table 2, but please can you also provide the reference directly here after citation. Further, please clarify which methods were used to estimate EWC in the other studies mentioned in Table 2.
434-436: Please clarify what the results of the “recent work on stream metabolism across the Yakima River basin” were. Due to the vague formulation of this sentence, the link to the next sentence is not clear. Please rephrase, preferably with avoiding the sentence starter “That is, …”.
444-448: At first read, this sentence is difficult to understand. I suggest to rephrase in a way that variables included in the full model and selected variables do not directly follow each other and that you mention “multiple regression model” already at the beginning of the sentence. (But see my doubts regarding the multiple regression model in the general comments.)
475-478: I suggest to split this sentence up into two, to improve understandability and get rid of one “although”.
487-488: change “nitrite+nitrate” to “nitrite and nitrate”
478-488: At the end of this section it needs a final concluding mark which links the information about the nutrients status in the catchment to your results to loop back to the begin of the paragraph.
490: The second sentence (“We observed faster… “), which summarizes the results of the regression model, would make more sentence in the previous paragraph.
514: Please review this part of the sentence: “… we infer that it is likely all four of these factors that combined to cause extremely …”.
Citation: https://doi.org/10.5194/egusphere-2023-3038-RC1 -
RC2: 'Comment on egusphere-2023-3038', Anonymous Referee #2, 06 Mar 2024
Fulton et al. aimed to assess the magnitude and spatial variability of water column respiration in the Yakima River basin and its contribution to ecosystem respiration. The third objective was to decipher environmental factors and watershed characteristics that explain the spatial variability of ERwc. The authors measured very slow respiration rates in the water column that were mainly related to DOC, NO3, and temperature. There are several aspects that make this manuscript valuable: it is clearly structured and well written. It is easy to follow the arguments. The methods are well detailed and explained and the main message of the study is interesting and important to point out especially for the outlook and future studies. The weakest point I have is the positive oxygen changes that are included in all the analyses.
The authors state that more than a third of the ERwc data was positive: this is somewhat critical for me and needs a little more explanation or attention. The criteria for inclusion of data generally also include that the change in oxygen concentration is negative and higher than the accuracy of the sensors (for oxygen, an accuracy of 5% is given for this type of sensor), despite the linearity of the slope for the calculations (line 315 and following). I therefore have a number of questions and suggestions as to what the authors could do.
I suggest a more critical discussion about the negative numbers that were all included into the analyses (regressions). For example, I was wondering if the authors checked whether their results also hold true when they excluded all positive values. How does the result shown in table 3 look like when the positive numbers are excluded? If the pattern still holds true and they find the same explanatory variables in their regression model, it is much stronger a statement to make! No matter if you exclude, set to zero or include the negative numbers, the general statement that ERwc is slow holds true and I like the major message of the manuscript.
Given the "weak" results obtained by measuring respiration with oxygen changes, I wonder if it wouldn't be good to suggest and discuss alternative methods here. Or maybe even the lack thereof? There are methods to assess aerobic respiration using resazurin or tetrazolium salt (2-(p-iodophenyl)-3-(p-nitrophenyl)-5- phenyl tetrazolium chloride (INT) as a tracer (González‐Pinzón et al. 2012; Packard 1971). They are often more sensitive, but also provide only an approximate value, must be converted to in situ respiration rates by empirically determined relationships or are relatively laborious. In my opinion, we need more sensitive methods for this type of analysis if we want to reliably measure the contributions of "slow processes" such as respiration in the water column. This could be an interesting discussion to have here.
Refs: González‐Pinzón, Ricardo, Roy Haggerty, and David D. Myrold. "Measuring aerobic respiration in stream ecosystems using the resazurin‐resorufin system." Journal of Geophysical Research: Biogeosciences 117.G3 (2012).
Packard, T. T. 1971. The measurement of respiratory electron transport activity in marine phytoplankton. Journal of Marine Research, 29: 235–244.
Additional comments:
Line 97: One letter missing in the word chlorophyll
Fig. 1: I believe that a and b were mixed up in the legend of this figure.
Line 445: The authors state that the spatial variability of ERwc was "well explained" by environmental factors. How did the authors assess this? What criterion did they use to assess the explanatory power of the independent variables? And where is the boundary between "well explained" and "less well explained"?
Line 452: “may not always be expected” instead of “we expected”
Citation: https://doi.org/10.5194/egusphere-2023-3038-RC2
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2023-3038', Anonymous Referee #1, 04 Mar 2024
Review of “Yakima River Basin Water Column Respiration is a Minor Component of River Ecosystem Respiration” by Fulton et al.
Summary: Fulton et al. measured ecosystem respiration in the water column (ERwc) and collected data on water chemistry (e.g. nutrients, temperature, DOC, DOM) at 46 sites across the Yakima River basin. Multiple linear regression revealed that the spatial variation of ERWC was mainly explained by temperature, nitrate and DOC concentrations. Further, authors compared measured ERwc rates to whole-river ecosystem respiration rates (ERtot) and ERwc values both derived from the literature. From this comparison they conclude that measured ERwc was comparably low and is likely a small component of ERtot.
General comments: The works strength is a reliable measure of ERwc across a broad spatial and environmental range in rivers (Strahler stream order 2-7) and its broad range of predictors derived from basic physicochemical measures to high resolution DOM data. In general, the manuscript is well written and the structure is clear. However, I have two main concerns:
- From a sentence in the abstract (line 25) I derive the two main justifications for this paper. The first one is to better understand the contribution of ERwc to ERtot. Hence, I was surprised that the authors only measured ERwc and did not simultaneously measure ERtot or/and respiration from the sediment. Obviously, this is nothing the authors can change now and they try to make up for this shortcoming with an exhaustive comparison of ERWC values to ERtot and ERwc values derived from the literature. The comparison is interesting and valuable, still, I think that the focus in this study lies too much on this first justification, without really backing it up with new data. The authors even imply in the last paragraph that they plan to address the shortcoming of not measured ERtot in future work (line 537), this might be the right time to focus on the contribution of ERwc to ERtot. I suggest to keep the comparison with the literature, but move the focus of this study to the second justification.
- The second justification was to gain a better understanding of the “relative magnitude and importance of ERwc across the river continuum and across biomes.” (line 26). A deeper investigation of ERwc shifts along the river continuum was held out in prospect but not followed through (“river continuum” was mentioned two times in the abstract, once in the introduction, but after that not anymore). Understanding the “relative magnitude” to ERtot is not possible without ERtot measurements conducted at the same time and location, however, investigating a shift of the absolute ERwc values along the river continuum might be still interesting. Anyway, discussing this topic in the Results and discussion sections is necessary, even if Strahler stream order or catchment area, which both can be used as proxies for the position of a site in the river continuum, were not significant in the multiple regression analysis. I also suspect that a potential effect of these two proxies on ERWC might have been overseen by large environmental differences among subcatchments. These differences could have created differences in intercepts of ERwc-“river continuum” relationships among subcatchments, hence, lumping together all sites without considering spatiality might blur the overall ERwc-“river continuum” relationship. Revealing a potential shift of ERwc along the river continuum needs a model accounting for spatial autocorrelation because sites within a river network are not independent from each other. Spatial stream network models account for spatial autocorrelation and might be a way to go (see e.g. Peterson, E. E. & Ver Hoef, J. M. A mixed-model moving-average approach to geostatistical modeling in stream networks. Ecology 91, 644–651 (2010))
Specific comments
17: If the word limit of the Abstract allows, I suggest to move the examples for anthropogenic and environmental perturbation mentioned in line 46 up here.
24: In case the suggested shift from benthic to water column processes by the mentioned studies occur all between 5th and 9th order, I suggest to change from “(e.g., 5th-9th order)” to “(5th-9th order)”. If this is not the case, I suggest to show the range from the smallest reported stream order to the largest reported stream order.
26: change to “along the river continuum”
48: I miss an example of how anthropogenic/environmental perturbations of GPP/ER can change downstream water quality.
86: Please rephrase, otherwise the meaning of the sentence is confusing. I suggest “… water column denitrification accounted for 0–85 % of reach-scale denitrification and water column respiration accounted for 39–85 % of reach- scale ERtot (i.e., ERwc + ERsed)”. If my suggestion is not correct, please clarify.
93: What do you mean with “direct” ERWC measurements?
126: “against ERWC and ERtot values found in the literature”
143: It is not clear why in this sentence only “the variability in hydrologic settings” is mentioned, as also biophysical attributes where used for the clustering (line 140). In line 142 you write about “similar landscape characteristics”, in line 144 “biophysical and hydrological attributes” and in line 166 “geospatial variables”. Overall, this paragraph could use a more coherent use of terms for the different variables used in the cluster analysis.
165: I suggest to write “similar properties”.
332: Somewhere around this line you should state how you checked for multicollinearity.
339: What did you do when depth data were not available?
341: Although you did not directly measure ERtot it is a very important parameter in you study, hence, I suggest to provide details in 1-2 sentences about how Appling et al. 2018c derived ERtot values. And the Results and discussion section would then need a critical evaluation of how well the two different methods for ERWC and ERtot can be compared.
424-425: You provide information on the methodology for papers with the footnotes “c” and “d”. I assume that the direct citation derives from the sources given in Table 2, but please can you also provide the reference directly here after citation. Further, please clarify which methods were used to estimate EWC in the other studies mentioned in Table 2.
434-436: Please clarify what the results of the “recent work on stream metabolism across the Yakima River basin” were. Due to the vague formulation of this sentence, the link to the next sentence is not clear. Please rephrase, preferably with avoiding the sentence starter “That is, …”.
444-448: At first read, this sentence is difficult to understand. I suggest to rephrase in a way that variables included in the full model and selected variables do not directly follow each other and that you mention “multiple regression model” already at the beginning of the sentence. (But see my doubts regarding the multiple regression model in the general comments.)
475-478: I suggest to split this sentence up into two, to improve understandability and get rid of one “although”.
487-488: change “nitrite+nitrate” to “nitrite and nitrate”
478-488: At the end of this section it needs a final concluding mark which links the information about the nutrients status in the catchment to your results to loop back to the begin of the paragraph.
490: The second sentence (“We observed faster… “), which summarizes the results of the regression model, would make more sentence in the previous paragraph.
514: Please review this part of the sentence: “… we infer that it is likely all four of these factors that combined to cause extremely …”.
Citation: https://doi.org/10.5194/egusphere-2023-3038-RC1 -
RC2: 'Comment on egusphere-2023-3038', Anonymous Referee #2, 06 Mar 2024
Fulton et al. aimed to assess the magnitude and spatial variability of water column respiration in the Yakima River basin and its contribution to ecosystem respiration. The third objective was to decipher environmental factors and watershed characteristics that explain the spatial variability of ERwc. The authors measured very slow respiration rates in the water column that were mainly related to DOC, NO3, and temperature. There are several aspects that make this manuscript valuable: it is clearly structured and well written. It is easy to follow the arguments. The methods are well detailed and explained and the main message of the study is interesting and important to point out especially for the outlook and future studies. The weakest point I have is the positive oxygen changes that are included in all the analyses.
The authors state that more than a third of the ERwc data was positive: this is somewhat critical for me and needs a little more explanation or attention. The criteria for inclusion of data generally also include that the change in oxygen concentration is negative and higher than the accuracy of the sensors (for oxygen, an accuracy of 5% is given for this type of sensor), despite the linearity of the slope for the calculations (line 315 and following). I therefore have a number of questions and suggestions as to what the authors could do.
I suggest a more critical discussion about the negative numbers that were all included into the analyses (regressions). For example, I was wondering if the authors checked whether their results also hold true when they excluded all positive values. How does the result shown in table 3 look like when the positive numbers are excluded? If the pattern still holds true and they find the same explanatory variables in their regression model, it is much stronger a statement to make! No matter if you exclude, set to zero or include the negative numbers, the general statement that ERwc is slow holds true and I like the major message of the manuscript.
Given the "weak" results obtained by measuring respiration with oxygen changes, I wonder if it wouldn't be good to suggest and discuss alternative methods here. Or maybe even the lack thereof? There are methods to assess aerobic respiration using resazurin or tetrazolium salt (2-(p-iodophenyl)-3-(p-nitrophenyl)-5- phenyl tetrazolium chloride (INT) as a tracer (González‐Pinzón et al. 2012; Packard 1971). They are often more sensitive, but also provide only an approximate value, must be converted to in situ respiration rates by empirically determined relationships or are relatively laborious. In my opinion, we need more sensitive methods for this type of analysis if we want to reliably measure the contributions of "slow processes" such as respiration in the water column. This could be an interesting discussion to have here.
Refs: González‐Pinzón, Ricardo, Roy Haggerty, and David D. Myrold. "Measuring aerobic respiration in stream ecosystems using the resazurin‐resorufin system." Journal of Geophysical Research: Biogeosciences 117.G3 (2012).
Packard, T. T. 1971. The measurement of respiratory electron transport activity in marine phytoplankton. Journal of Marine Research, 29: 235–244.
Additional comments:
Line 97: One letter missing in the word chlorophyll
Fig. 1: I believe that a and b were mixed up in the legend of this figure.
Line 445: The authors state that the spatial variability of ERwc was "well explained" by environmental factors. How did the authors assess this? What criterion did they use to assess the explanatory power of the independent variables? And where is the boundary between "well explained" and "less well explained"?
Line 452: “may not always be expected” instead of “we expected”
Citation: https://doi.org/10.5194/egusphere-2023-3038-RC2
Data sets
Spatial Study 2021: Sensor-Based Time Series of Surface Water Temperature, Specific Conductance, Total Dissolved Solids, Turbidity, pH, and Dissolved Oxygen from across Multiple Watersheds in the Yakima River Basin, Washington, USA (v2) Stephanie G. Fulton, Morgan Barnes, Mikayla A. Borton, Xingyuan Chen, Yuliya Farris, Brieanne Forbes, Vanessa A. Garayburu-Caruso, Amy E. Goldman, Samantha Grieger, Matthew H. Kaufman, Xinming Lin, Sophia A. McKever, Allison Myers-Pigg, Opal Otenburg, Aaron Pelly, Huiying Ren, Lupita Renteria, Timothy D. Scheibe, Kyongho Son, Joshua M. Torgeson, and James C. Stegen https://doi.org/10.15485/1892052
Spatial Study 2021: Sample-Based Surface Water Chemistry and Organic Matter Characterization across Watersheds in the Yakima River Basin, Washington, USA (v2) Samantha Grieger, Morgan Barnes, Mikayla A. Borton, Xingyuan Chen, Rosalie Chu, Yuliya Farris, Brieanne Forbes, Stephanie G. Fulton, Vanessa A. Garayburu-Caruso, Amy E. Goldman, Brianna I. Gonzalez, Matthew H. Kaufman, Sophia A. McKever, Allison Myers-Pigg, Opal Otenburg, Aaron Pelly, Lupita Renteria, Timothy D. Scheibe, Kyongho Son, Joshua M. Torgeson, Jason G. Toyoda, and James C. Stegen https://doi.org/10.15485/1898914
Geospatial Information, Metadata, and Maps for Global River Corridor Science Focus Area Sites (v2) Matthew H. Kaufman, Morgan Barnes, Xingyuan Chen, Brieanne Forbes, Vanessa A. Garayburu-Caruso, Amy E. Goldman, James C. Stegen, Allison Myers-Pigg, and Timothy D. Scheibe https://doi.org/10.15485/1971251
Model code and software
Yakima River Basin Water Column Respiration Manuscript GitHub Repository Stephanie G. Fulton, Morgan E. Barnes, Mikayla A. Borton, Xingyuan Chen, Yuliya Farris, Brieanne Forbes, Vanessa G. Garayburu-Caruso, Amy E. Goldman, Samantha Grieger, Xinming Lin, Sophia A. McKever, Allison Myers-Pigg, Opal C. Otenburg, Aaron C. Pelly, Huiying Ren, Erin McCann, Lupita Renteria, Timothy D. Scheibe, Kyongho Son, Jerry Tagestad, Joshua M. Torgeson, Robert O. Hall, Jr., Matthew H. Kaufman, and James C. Stegen https://github.com/river-corridors-sfa/YRB_Water_Column_Respiration
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