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Peer review report 2 on “Methane balance of an intensively grazed pasture and estimation of the enteric methane emissions from cattle”
Agricultural and Forest Meteorology 217 (2016) 496–497
Contents lists available at ScienceDirect
Agricultural and Forest Meteorology journal homepage: www.elsevier.com/locate/agrformet
Peer Review Report
Peer review report 2 on “Methane balance of an intensively grazed pasture and estimation of the enteric methane emissions from cattle”
1. Original Submission 1.1. Recommendation Decline with option to Resubmit
I thus recommend major revisions and re-review of the manuscript. Alternatively, I see a hint that this work may be part of a bigger study that will eventually address some of my concerns – on page 14 and in the final paragraph of the conclusions we are informed that the authors are developing/employing cattle position monitoring devices to validate the present measurements.
2. Comments to Author: 3. Comments Review of manuscript, “Methane balance of an intensively grazed pasture and estimation of the enteric methane emissions from cattle”, by Dumortier et al. submitted to Agricultural and Forest Meteorology. This work uses eddy covariance (EC) measurements to estimate methane fluxes from a grazed landscape (where both enteric emissions and soil fluxes are important). It is interesting work and deals with an important subject matter for agriculturalists. This was a difficult paper to evaluate. On the positive side, the measurements described in the paper appear to be good quality, evaluated with the proper techniques, and analyzed carefully. However, as to an ultimate evaluation – are the measurements accurate – it is inconclusive. I find it frustrating that this work was not really designed to answer that important question. One would have hoped the authors would have made an alternative measurement of enteric emissions, or used alternative calculations (e.g., a different footprint model), or monitored animal positions in order to validate the calculation assumptions, so that we would have some evidence as to whether the emission calculations were reasonable. I thus find it difficult to draw any solid conclusions from this paper. In this form I do not think the paper should be published in Agriculture and Forest Meteorology – I don’t think it rises to the standard of advancing knowledge in this field (e.g., does EC work for estimating enteric emissions). I struggled as to whether there is anything the authors could do to change my opinion. Without an alternative measurement of enteric emissions, and without some measure of actual animal positions, I think the only avenue forward would be a more careful consideration of the flux footprint model. Here I envision something like a sensitivity study, where the authors might tinker with the Korman & Meixner model (e.g., following the example of Wilson (2015) described below) and/or introduce an alternative footprint model. How would these choices change the estimates of enteric emissions?
DOI of published article: http://dx.doi.org/10.1016/j.agrformet.2016.09.010. http://dx.doi.org/10.1016/j.agrformet.2016.11.216 0168-1923/
In my comments below I’ve focused mostly on enteric methane calculations of the study. I think this is the more challenging, original, and important part of the work. 3.1. Major comments: 1 Line 55-83 (Section 3.1). Much of the discussion in this section relates to the flux footprint (e.g., its size and position on the landscape), but there has been no substantive discussion of what is a flux footprint, or its characteristic size and shape. Many readers will need some guidance. I suggest some substantive discussion defining the flux footprint and giving some indication of the typical size and shape of the footprint in this study. Maybe add a subsection on the flux footprint to start this section, or making that the 2nd subsection? 2 Line 156 (Section 3.3.2, Flux contamination). This is an interesting section, and I don’t really disagree with the conclusion that the barn is contaminating the EC signal. But being > 200 m from the tower, I expect that in many cases (unstable and neutral stratification) the flux footprint does not extend to the barn. Is there any other possibilities? 3 Line 189 (Section 3.3.3, Footprint correction). This is an important section. Very briefly − tell us a bit about the Neftel/Korman&Meixner model (e.g., is it a full 3-D model, is it an analytical solution, is it an LS model?). How was the 60% pasture contribution chosen? 4 Line 256-262 (Section 4.2, Enteric emissions). I think this is a critical part of the manuscript. The authors need to be clearer regarding the conditions that would be required for an accurate 30-min estimate of the enteric emission rate, i.e., 1) that cattle be located within the 30-min flux footprint, and 2) that those cattle are even spread across the footprint with a spatial density corresponding to the assumed average stocking rate (=impossible in reality). And if it is therefore practically impossible that a single 30-min measurement be correct, what assumptions are needed
Peer Review Report / Agricultural and Forest Meteorology 217 (2016) 496–497
so that a long-term average estimate is correct? For example, that over time the integrated flux footprint over the pasture overlays the cattle positions in a manner such that the animals are distributed with the average stocking density of the pasture. The authors need to be clear − this is a difficult problem! 5 Line 270-272, 340-342 (Enteric emissions). The enteric emission values calculated are relatively low. When expressed as methane yield (g CH4/kg DMI), grazing animals typically have values > 20. The value of ∼17 reported here is more typical of feedlot animals having a higher quality feed. The authors acknowledge this underestimate when they compare their calculations to the IPCCbased calculations. Could the authors’ lower emission values be correct? This should lead to a deeper discussion of the possibility of a bias in the EC estimates. The most fruitful discussion would consider the possibility of errors in the Korman and Meixner (KM) footprint model. Wilson (2015, “Computing the flux footprint”, Boundary Layer Meteorology, 156:1-14) has a useful comparison of the KM model to more rigorous models, which indicates a bias in the KM calculations. Could the differences that Wilson documents between KM and more rigorous models explain an underprediction?
14
15
16
17
18
3.2. Minor comments: 6 Line 24: “. . . methane dry molar fraction rose from 0.722 to 1.8 pm . . .”. “pm” should be “ppm” 7 Line 25: “. . .This radical increase in methane concentration accounted for almost 30% of the total greenhouse gas (GHG) radiative forcing . . .”. Not clear. Does the increase (1.80-0.722) account for 30% of the forcing (increase?), or does the 1.80 ppm level account for 30% of the forcing? Clarify. 8 Line 41: “. . . fluxes originating from a zone (footprint area) situated upwind of the measurement point . . .”. The footprint can also extend a short distance downwind of the measurement point (for a near-surface measurement in unstable conditions). 9 Line 45: “. . .can be identified by separating cattle-free periods . . .”. The first mention of cattle. Up to this point the introduction has discussed ruminants. Either keep the subject as ruminants, or have some transition to a discussion on cattle. 10 Line 80: “. . .In addition, there were four 1-day confinement times during which the cattle were confined to about a third of the pasture, roughly covering the flux source area (footprint) in the main wind direction . . .”. At this point there has been no discussion of how the footprint is quantified. Give some indication of how this is done, or reference a later section of the paper. 11 Line 81: “During this period, only those half-hours when more than 60% of the footprint came . . .”. Because there has been no prior indication of what a measurement is (e.g., a 30-min EC flux), it would be better to say “. . . only those measurements when more than 60% . . .”. 12 Line 109-122. “A large proportion of the methane fluxes being very small (between −0.5 and 0.5 nmol m-2 s-1) and linked with moving methane sources, the classical block averaging with stationarity test approach could not be used . . .” This subject (stationarity test) seems quite important. Please indicate what the purpose of this test is, and why it is important. 13 Line 154. “In half the cases, relative uncertainty about methane fluxes was below 50%, with decreasing uncertainty and increasing relative uncertainties for fluxes below 5 nmol m-2 s-1.”
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20 21
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497
Meaning what? That the detection limit is assumed to be 5 nmol m-2 s-1? Give a clear statement of what is concluded. Line 163: “During the growing period . . .”. The Figure caption (Fig. 5) identifies the “summer”. Be consistent − either “growing period” or “summer”. Line 173: Fig. 5. Is the reader supposed to take away a message regarding the standard error lines (dashed)? If not, eliminate for clarity. Line 192: “ . . . the footprint was calculated using a homemade version . . .” What does “homemade version” mean? Is it mathematically identical? Some new assumptions? Confusing. Line 215: “During free-ranging periods, the fluxes were highly variable, even over short time periods. This variability could be explained by changes in cow digestion rhythm, leading to a change in source intensity . . .”. As a remark to the authors: I find this possibility highly unlikely. While studies of enteric cattle emissions do show highly variable emission rates at short timescales (e.g., 1-min) for individual animals, at larger timescales (30-min) the variability is relatively low (particularly for a herd). Line 231: “One of the biggest advantages of the EC method is its fine temporal resolution . . .” Given the methodology employed here, this is probably not true. Because the possibility that any individual measurement is accurate is zero (due to the nearimpossibility of the footprint assumptions on a 30-min basis), then the enteric emission rate from any 30-min period is in error. Only through the averaging of large numbers of observations is there hope for a reasonable estimate. So I don’t see how one could conclude there is fine temporal resolution? Line 251 (Fig. 8). I think this graph is essentially a re-formulation of Fig. 7a − high concentrations are seen at night when the wind decreases. I don’t think this graph, or the discussion in lines 247-250 is worth the trouble. Line 263 (Fig. 9). This is a very encouraging graph . . . Line 275: “In order to obtain an estimate of the annual cumulated fluxes, missing data . . . were gap filled . . .”. Because the authors report annual emission rates before this statement (e.g., line 270), it is unclear if the earlier estimates used a gap-filled record. Clarify Line 328: “This value . . .”. It’s unclear what value the authors are discussing − the random uncertainty or the methodological uncertainty. Clarify. Line 329: “Errors linked with methodological choices . . . difficult to quantify.” Because these errors could be very large, the study should make more effort to understand the potential for errors. Some answers to this question could be indicated through the use of alternative footprint models (as suggested earlier). Line 349: “The agreement between confinement and free ranging periods was surprisingly good . . .” Yes it is! Line 360-363: “Ìn the morning a peak occurred for both measurement methods but differed in timing and magnitude . . .”. I think this is reading too much into a highly error-prone dataset. Given that reasonable results only come about by averaging large amounts of data (over long periods of time), one should be careful about analyzing only small portions of the data, e.g., a certain hour of the day (particularly if animal behavior has a time of day component). Anonymous Available online 5 December 2016
Contents lists available at ScienceDirect
Agricultural and Forest Meteorology journal homepage: www.elsevier.com/locate/agrformet
Peer Review Report
Peer review report 2 on “Methane balance of an intensively grazed pasture and estimation of the enteric methane emissions from cattle”
1. Original Submission 1.1. Recommendation Decline with option to Resubmit
I thus recommend major revisions and re-review of the manuscript. Alternatively, I see a hint that this work may be part of a bigger study that will eventually address some of my concerns – on page 14 and in the final paragraph of the conclusions we are informed that the authors are developing/employing cattle position monitoring devices to validate the present measurements.
2. Comments to Author: 3. Comments Review of manuscript, “Methane balance of an intensively grazed pasture and estimation of the enteric methane emissions from cattle”, by Dumortier et al. submitted to Agricultural and Forest Meteorology. This work uses eddy covariance (EC) measurements to estimate methane fluxes from a grazed landscape (where both enteric emissions and soil fluxes are important). It is interesting work and deals with an important subject matter for agriculturalists. This was a difficult paper to evaluate. On the positive side, the measurements described in the paper appear to be good quality, evaluated with the proper techniques, and analyzed carefully. However, as to an ultimate evaluation – are the measurements accurate – it is inconclusive. I find it frustrating that this work was not really designed to answer that important question. One would have hoped the authors would have made an alternative measurement of enteric emissions, or used alternative calculations (e.g., a different footprint model), or monitored animal positions in order to validate the calculation assumptions, so that we would have some evidence as to whether the emission calculations were reasonable. I thus find it difficult to draw any solid conclusions from this paper. In this form I do not think the paper should be published in Agriculture and Forest Meteorology – I don’t think it rises to the standard of advancing knowledge in this field (e.g., does EC work for estimating enteric emissions). I struggled as to whether there is anything the authors could do to change my opinion. Without an alternative measurement of enteric emissions, and without some measure of actual animal positions, I think the only avenue forward would be a more careful consideration of the flux footprint model. Here I envision something like a sensitivity study, where the authors might tinker with the Korman & Meixner model (e.g., following the example of Wilson (2015) described below) and/or introduce an alternative footprint model. How would these choices change the estimates of enteric emissions?
DOI of published article: http://dx.doi.org/10.1016/j.agrformet.2016.09.010. http://dx.doi.org/10.1016/j.agrformet.2016.11.216 0168-1923/
In my comments below I’ve focused mostly on enteric methane calculations of the study. I think this is the more challenging, original, and important part of the work. 3.1. Major comments: 1 Line 55-83 (Section 3.1). Much of the discussion in this section relates to the flux footprint (e.g., its size and position on the landscape), but there has been no substantive discussion of what is a flux footprint, or its characteristic size and shape. Many readers will need some guidance. I suggest some substantive discussion defining the flux footprint and giving some indication of the typical size and shape of the footprint in this study. Maybe add a subsection on the flux footprint to start this section, or making that the 2nd subsection? 2 Line 156 (Section 3.3.2, Flux contamination). This is an interesting section, and I don’t really disagree with the conclusion that the barn is contaminating the EC signal. But being > 200 m from the tower, I expect that in many cases (unstable and neutral stratification) the flux footprint does not extend to the barn. Is there any other possibilities? 3 Line 189 (Section 3.3.3, Footprint correction). This is an important section. Very briefly − tell us a bit about the Neftel/Korman&Meixner model (e.g., is it a full 3-D model, is it an analytical solution, is it an LS model?). How was the 60% pasture contribution chosen? 4 Line 256-262 (Section 4.2, Enteric emissions). I think this is a critical part of the manuscript. The authors need to be clearer regarding the conditions that would be required for an accurate 30-min estimate of the enteric emission rate, i.e., 1) that cattle be located within the 30-min flux footprint, and 2) that those cattle are even spread across the footprint with a spatial density corresponding to the assumed average stocking rate (=impossible in reality). And if it is therefore practically impossible that a single 30-min measurement be correct, what assumptions are needed
Peer Review Report / Agricultural and Forest Meteorology 217 (2016) 496–497
so that a long-term average estimate is correct? For example, that over time the integrated flux footprint over the pasture overlays the cattle positions in a manner such that the animals are distributed with the average stocking density of the pasture. The authors need to be clear − this is a difficult problem! 5 Line 270-272, 340-342 (Enteric emissions). The enteric emission values calculated are relatively low. When expressed as methane yield (g CH4/kg DMI), grazing animals typically have values > 20. The value of ∼17 reported here is more typical of feedlot animals having a higher quality feed. The authors acknowledge this underestimate when they compare their calculations to the IPCCbased calculations. Could the authors’ lower emission values be correct? This should lead to a deeper discussion of the possibility of a bias in the EC estimates. The most fruitful discussion would consider the possibility of errors in the Korman and Meixner (KM) footprint model. Wilson (2015, “Computing the flux footprint”, Boundary Layer Meteorology, 156:1-14) has a useful comparison of the KM model to more rigorous models, which indicates a bias in the KM calculations. Could the differences that Wilson documents between KM and more rigorous models explain an underprediction?
14
15
16
17
18
3.2. Minor comments: 6 Line 24: “. . . methane dry molar fraction rose from 0.722 to 1.8 pm . . .”. “pm” should be “ppm” 7 Line 25: “. . .This radical increase in methane concentration accounted for almost 30% of the total greenhouse gas (GHG) radiative forcing . . .”. Not clear. Does the increase (1.80-0.722) account for 30% of the forcing (increase?), or does the 1.80 ppm level account for 30% of the forcing? Clarify. 8 Line 41: “. . . fluxes originating from a zone (footprint area) situated upwind of the measurement point . . .”. The footprint can also extend a short distance downwind of the measurement point (for a near-surface measurement in unstable conditions). 9 Line 45: “. . .can be identified by separating cattle-free periods . . .”. The first mention of cattle. Up to this point the introduction has discussed ruminants. Either keep the subject as ruminants, or have some transition to a discussion on cattle. 10 Line 80: “. . .In addition, there were four 1-day confinement times during which the cattle were confined to about a third of the pasture, roughly covering the flux source area (footprint) in the main wind direction . . .”. At this point there has been no discussion of how the footprint is quantified. Give some indication of how this is done, or reference a later section of the paper. 11 Line 81: “During this period, only those half-hours when more than 60% of the footprint came . . .”. Because there has been no prior indication of what a measurement is (e.g., a 30-min EC flux), it would be better to say “. . . only those measurements when more than 60% . . .”. 12 Line 109-122. “A large proportion of the methane fluxes being very small (between −0.5 and 0.5 nmol m-2 s-1) and linked with moving methane sources, the classical block averaging with stationarity test approach could not be used . . .” This subject (stationarity test) seems quite important. Please indicate what the purpose of this test is, and why it is important. 13 Line 154. “In half the cases, relative uncertainty about methane fluxes was below 50%, with decreasing uncertainty and increasing relative uncertainties for fluxes below 5 nmol m-2 s-1.”
19
20 21
22
23
24 25
497
Meaning what? That the detection limit is assumed to be 5 nmol m-2 s-1? Give a clear statement of what is concluded. Line 163: “During the growing period . . .”. The Figure caption (Fig. 5) identifies the “summer”. Be consistent − either “growing period” or “summer”. Line 173: Fig. 5. Is the reader supposed to take away a message regarding the standard error lines (dashed)? If not, eliminate for clarity. Line 192: “ . . . the footprint was calculated using a homemade version . . .” What does “homemade version” mean? Is it mathematically identical? Some new assumptions? Confusing. Line 215: “During free-ranging periods, the fluxes were highly variable, even over short time periods. This variability could be explained by changes in cow digestion rhythm, leading to a change in source intensity . . .”. As a remark to the authors: I find this possibility highly unlikely. While studies of enteric cattle emissions do show highly variable emission rates at short timescales (e.g., 1-min) for individual animals, at larger timescales (30-min) the variability is relatively low (particularly for a herd). Line 231: “One of the biggest advantages of the EC method is its fine temporal resolution . . .” Given the methodology employed here, this is probably not true. Because the possibility that any individual measurement is accurate is zero (due to the nearimpossibility of the footprint assumptions on a 30-min basis), then the enteric emission rate from any 30-min period is in error. Only through the averaging of large numbers of observations is there hope for a reasonable estimate. So I don’t see how one could conclude there is fine temporal resolution? Line 251 (Fig. 8). I think this graph is essentially a re-formulation of Fig. 7a − high concentrations are seen at night when the wind decreases. I don’t think this graph, or the discussion in lines 247-250 is worth the trouble. Line 263 (Fig. 9). This is a very encouraging graph . . . Line 275: “In order to obtain an estimate of the annual cumulated fluxes, missing data . . . were gap filled . . .”. Because the authors report annual emission rates before this statement (e.g., line 270), it is unclear if the earlier estimates used a gap-filled record. Clarify Line 328: “This value . . .”. It’s unclear what value the authors are discussing − the random uncertainty or the methodological uncertainty. Clarify. Line 329: “Errors linked with methodological choices . . . difficult to quantify.” Because these errors could be very large, the study should make more effort to understand the potential for errors. Some answers to this question could be indicated through the use of alternative footprint models (as suggested earlier). Line 349: “The agreement between confinement and free ranging periods was surprisingly good . . .” Yes it is! Line 360-363: “Ìn the morning a peak occurred for both measurement methods but differed in timing and magnitude . . .”. I think this is reading too much into a highly error-prone dataset. Given that reasonable results only come about by averaging large amounts of data (over long periods of time), one should be careful about analyzing only small portions of the data, e.g., a certain hour of the day (particularly if animal behavior has a time of day component). Anonymous Available online 5 December 2016