Can 100% Pasture-Based Livestock Farming Produce Enough Ruminant Meat to Meet the Current Consumption Demand in the UK?
, Louise Whatford 2, Sophie Payne-Gifford 1, Richard Cooke 1, Steven Van Winden 2, Barbara Häsler 2 and David Barling 1
Round 1
Reviewer 1 Report
Congratulations for the idea and the overall project. I have also to congratulate the UK government for collecting and publishing all this data.
I would like, in the future, to see a more complex analysis including crude protein content of pastures and concentrated mixtures, to have a more “nutritional” approach.
Author Response
Dear Reviewer
Thank you for reading, reviewing and commenting on our manuscript. Your comments and suggestions were encouraging and helped us to improve the quality for the revised manuscript. Please find below are the responses and answers to the comments and questions!
We also attach the revised manuscript with changes highlighted in yellow colour.
Comments and Suggestions for Authors
Congratulations for the idea and the overall project. I have also to congratulate the UK government for collecting and publishing all this data.
I would like, in the future, to see a more complex analysis including crude protein content of pastures and concentrated mixtures, to have a more “nutritional” approach.
Response: It is indeed very pleasing to receive the congratulations from this expert reviewer. We all also feel the same that the UK governmental Department for Environment, Food and Rural Affairs has been doing an excellent job in collecting the comprehensive agricultural census data and making them available timely and publicly available. We have now acknowledged this fact in the acknowledgment, too. Thank you for this suggestion and aspiration. We agree that there is much more that can be done with the kind of approach applied in this manuscript.
Author Response File: 
Author Response.doc
Reviewer 2 Report
Dear authors, it seems to me that this is a goodmanuscript and it has relevance in the scientific world. However, major technical and/or interpretational problems affect the quality of the manuscript.
Dear authors, first of all, please do not reply to me without proofreading the manuscript. If I question the topics, it is because the text needs improvement; then change the text.
Introduction: the introduction is well-written; however, to improve the introduction, add more data, add numbers. (Only as an example: 90% of animals are in extensive systems. Native pasture production of 1000 kg/ha, 45% of the rotation pasture is sow with oat, etc)
Line 29: What does ca., M and t mean? Describes the initials the first time it appears.
Lines 116-120: Those lines are not correlated with the previous text. Fertilization was described in previous paragraphs. Try changing the writing style to correlate the ideas in the paragraph.
Lines 139-140: Answering questions is your main objective? I recommend describing a general objective considering the goals of the study and the title of the manuscript.
Material and methods: Add a statistical topic that describes the statistical methods used.
Line 166: Downloaded from where? Add the link or data needed to get this data, such as address, city, etc.
Line 179: Same as previous comment.
Line 258: Add the description of the models used or developed in more detail.
Results: The description of the results should be improved. The writing is based on a colloquial writing style and they should change it to a scientific writing style. Also, with that data, why are you using only these basic statistical methods? The CV and SD are measures that explain the basic concepts correlated with the objective of your study and not the most important ones.
Line 277-278: Information not relevant. Remove it.Same comment for lines 293-294, 329-330, and other similar texts.
Line 279: What do you mean by "relatively standard"?
Figure 2: The data seems to be similar. What is the purpose of the figure? What relevant information did you intend to show in this figure?
Line 315: There is a better way to describe this text than to use the word "stable." Use your knowledge of statistics.
Line 320: What? “did not differ much”… this type of writing style does not belong to the scientific writing style. Use the correct description of the statistic to demonstrate the variance. Change similar texts through the text.
Discussion: The discussion topic needs to be rewritten. You describe the results in the discussion and the writing style is empiric. The topic of discussion is to explain biologically how you got those results and no to describe the results.
Lines 462-469: I do not understand the relevance of this previous text to start the discussion. Remove it.
Lines 490-494: This is a description of the results. Change the position of this text to the results topic.
Lines 494-497: How?
Lines 497-500: This is a description of the results. Change the position of this text to the results topic.
Lines 506-509: I do not understand the relevance of this previous text to start the discussion. Remove it.
Lines 513-518: This is a description of the results. Change the position of this text to the results topic.
The conclusion needs to be improved. A conclusion should be concise describing a conclusion and not a compilation of results. You can add future implications in the conclusion or in another subtopic.
Author Response
Dear Reviewer
Thank you for reading, reviewing and commenting on our manuscript. Your comments and suggestions were encouraging and helped us to improve the quality for the revised manuscript. Please find below are the responses and answers to the comments and questions!
We also attach the revised manuscript with changes highlighted in yellow colour.
Comments and Suggestions for Authors
1 Dear authors, it seems to me that this is a good manuscript, and it has relevance in the scientific world. However, major technical and/or interpretational problems affect the quality of the manuscript.
Dear authors, first of all, please do not reply to me without proofreading the manuscript. If I question the topics, it is because the text needs improvement; then change the text.
Response: We are happy that the manuscript was well regarded and thank you for the positive feedback. We determined to look deep into the questions and try to respond to them as in full as possible while we were learning from this revision process.
2 Introduction: the introduction is well-written; however, to improve the introduction, add more data, add numbers. (Only as an example: 90% of animals are in extensive systems. Native pasture production of 1000 kg/ha, 45% of the rotation pasture is sown with oat, etc)
Response: The current introduction was already long enough and sufficiently comprehensive. We have added few additional lines in the beginning of the introduction. We are happy to include more data and numbers but are puzzled with what they should be and where to find them. We wish the comment was more specific/informative (i.e., known references or reports) and then we can act on it.
3 Line 29: What does ca., M and t mean? Describes the initials the first time it appears.
Response: In the context of this manuscript, “ca.” is short for “approximately” and M stands for “million”, “t” for metric “tonne”. These are now made clear in the revised manuscript. We also changed “ca.” into “approximately” where it was used in other places in the revised manuscript.
4 Lines 116-120: Those lines are not correlated with the previous text. Fertilization was described in previous paragraphs. Try changing the writing style to correlate the ideas in the paragraph.
Response: We have made the context change so that it can make the idea clearer that the higher the grass yields by enhancing the soil fertility, the longer the grazing season.
4 Lines 139-140: Answering questions is your main objective? I recommend describing a general objective considering the goals of the study and the title of the manuscript.
Response: This is a very good advice. We have now provided the overall objective in the revised manuscript as below.
The overall objective was to assess the potential livestock carrying capacity on all grasslands for cattle and sheep and the arithmetical grass forage utilisation rates required to produce enough ruminant meat to meet the current mean consumption level during 2011-2020 in the UK.
5 Material and methods: Add a statistical topic that describes the statistical methods used.
Response: Thank you for this suggestion. We have added a heading 2.5 on data analysis in the Materials and Methods.
6 Line 166: Downloaded from where? Add the link or data needed to get this data, such as address, city, etc.
Response: We have specified the link that was already given in the early part of the main text in the revised manuscript.
7 Line 179: Same as previous comment.
Response: This was the same issue as stated in Line 166 above. We have specified the link that was already given in the early part of the main text in the revised manuscript.
8 Line 258: Add the description of the models used or developed in more detail.
Response: We have added a description how the UK-wide average grass forage dry matter yields were calculated for each grassland type as below.
“This was done first by calculating the total grass forage dry matter production at each 1 km square grid for respective grassland type using the estimated herbal dry matter yield and grassland area of the related grassland type. Then, all the grass forage dry matter yields and grassland areas related to the respective grassland type were aggregated across the UK. The UK-wide average herbal dry matter yield was calculated by dividing the respective total grass forage dry matter production by the respective total areas of respective grassland type. Further details on the development of models and calculating herbal dry matter yields using the models at 1 km square grid were referred to Qi et al. (2017, 2018).”
9 Results: The description of the results should be improved. The writing is based on a colloquial writing style and they should change it to a scientific writing style. Also, with that data, why are you using only these basic statistical methods? The CV and SD are measures that explain the basic concepts correlated with the objective of your study and not the most important ones.
Response: Thank you for all these thoughts. The writing style can depend on each induvial person. We will learn to improve this skill as we read and write more scientific literature. By the way, three other referees reviewed the manuscript and they have not reacted to the writing style of the manuscript. Regarding the analyses to the data, we recognise that these are mostly nature of time series. Since they are of time series, it may be useful to see whether there was any trend behind the data using a regression analysis or moving averages. However, considering the questions and aim of the study, we feel that these statistical measures in means, SD and CV% were fit for purpose. Annual means measure the annual magnitude of a data item, SDs measure the interannual variation and CV%s measures the relative interannual variation accounting for the difference in the mean magnitude. Since the magnitudes in SD measure the interannual variation, it can be an indicator for presence of trend. If SD was small, it means the less interannual variation and the trend was weak.
10 Line 277-278: Information not relevant. Remove it. Same comment for lines 293-294, 329-330, and other similar texts.
Response: We responded to these comments by deleting these introductory lines.
11 Line 279: What do you mean by "relatively standard"?
Response: we gathered that you asked the question by “relative stable” here. We were supposed to mean that the annual mean area of rough-grazing grassland showed small interannual variation. We have now modified the text here and these similar descriptions somewhere else throughout the revised manuscript, too.
12 Figure 2: The data seems to be similar. What is the purpose of the figure? What relevant information did you intend to show in this figure?
Response: Thank you for this observation! We felt pleased that you have noted the small interannual variations in these data. We think this Figure 2 not only gave the magnitudes of cattle population in various gender/age groups but also showed how small the interannual variation was during the 10 years in 2011-2020.
13 Line 315: There is a better way to describe this text than to use the word "stable." Use your knowledge of statistics.
Response: We were sorry that we caused this confusion here. In a way, small interannual variation indicates interannual stability even though we did not know what forces/factors maintained this small interannual variation. We have revised the texts where these confusions have occurred in the revised manuscript.
14 Line 320: What? “did not differ much”… this type of writing style does not belong to the scientific writing style. Use the correct description of the statistic to demonstrate the variance. Change similar texts through the text.
Response: Again we were sorry that we caused this confusion here. It was the cattle population and its interannual variation was small. This has been phrased in the revised manuscript.
15 Discussion: The discussion topic needs to be rewritten. You describe the results in the discussion and the writing style is empiric. The topic of discussion is to explain biologically how you got those results and no to describe the results.
Response: Thank you for these observations and good suggestions. We will improve our scientific writing style and skills in these aspects by reading more subject literature and writing more manuscripts for scientific journals.
16 Lines 462-469: I do not understand the relevance of this previous text to start the discussion. Remove it.
Response: This information may not be relevant to the subject contents. However, we would just want to convey the information to other researchers in this area that this was indeed the first time these UK agricultural survey data on cattle and sheep livestock were analysed in this way with the idea proposed in the manuscript.
17 Lines 490-494: This is a description of the results. Change the position of this text to the results topic.
Response: We heeded this suggestion and moved these to the results topic describing the Table 5 with results related to cattle and Table 7 with results related to sheep, respectively.
18 Lines 494-497: How?
Response: When we designed the framework to examine whether and how the grass-fed diets for cattle and sheep can produce enough ruminant meat to meet the current consumption level in the UK, we were not sure how the various statistics in cattle and sheep varied from year to year. If the interannual variations were all too large, the use of calculated meat productivity per standard livestock unit (SLU) cannot be robust and the uncertainty in meat productivity per SLU can be large. Since the interannual variations were all small in total standard livestock unit and meat production of dressed carcass weight, this was why we were satisfied and confident with the robustness of this estimated meat productivity per SLU. This parametric meat productivity per SLU can then be applied in the scenario analyses for ruminant production and consumption in the UK.
19 Lines 497-500: This is a description of the results. Change the position of this text to the results topic.
Response: Thank you for this suggestion. Although this description assimilated message from the result topic on meat productivity in dressed carcass weight, we feel that this pre-context provided the contrasting difference between dressed carcass weight meat and crude protein productivity per standard livestock unit (SLU) in cattle and sheep farming sector in the same place of the manuscript.
20 Lines 506-509: I do not understand the relevance of this previous text to start the discussion. Remove it.
Response: We are a bit confused with this question in relation to the comments made for Lines 490-494 above. The previous text of Lines 506-509 was about the comparison in crude protein productivity per standard livestock unit between cattle and sheep farming sector. We believe this information can be interesting when productivity per SLU was examined in another dimension of product component (i.e., the crude protein here).
21 Lines 513-518: This is a description of the results. Change the position of this text to the results topic.
Response: These calculated values seemed to read like results. We have not covered dressed carcass weights per different groups of slaughtered cattle and sheep in the results. We calculated these additional comparative indicators from the data in the UK agricultural survey census as evidence to support our argument that the improvements in cattle and sheep genetic performance were small in the ten years from 2011 to 2020. We revised the text by adding the reference where these new data were available.
22 The conclusion needs to be improved. A conclusion should be concise describing a conclusion and not a compilation of results. You can add future implications in the conclusion or in another subtopic.
Response: Thank you for this observation. We have shortened and improved the conclusion by removing the content of results in the revised manuscript as below.
“This study has shown that the total availability of herbage dry matter on all grasslands can support a national potential carrying capacity for cattle and sheep to produce sufficient ruminant meat to meet the UK domestic needs with undemanding pasture utilisation rates if consumption per capita stayed at the current levels. Pastures not only supply sustainable feed to ruminants but also play a potential role in greenhouse gas mitigation, preserving soil fertility, and combatting soil erosion on steep slopes due to their ecosystem services. The adoption of grass-fed only diets for cattle and sheep farming should offer to support the transitional pathway of the UK government to net zero greenhouse gas emission target by 2050. However, it is important to remember that this analysis may provide a useful pathway but implementing and practicing grass-fed only cattle and sheep farming systems may be complicated because it can involve major changes for governmental policies and the farmers such as land use, livestock products certifications and herd characteristics. The adopted approach in the paper can be expanded by including nutritional aspects such as crude protein content in the pastures for a more complex analysis with these large, interrelated sets of long-term time-series data collected by the UK government.”
Author Response File: Author Response.doc
Reviewer 3 Report
The theme of the manuscript is complex and actual. However, I have the following notes to this manuscript that should be added/repaired in the text:
- Incorrect writing of the numbers with units in the case of km and kg at more places.
- The missing scale and compass rose on the map in Fig. 1
- Inconsistent citations in the text – instead of following numbering the names of authors are only inserted in the sentences many times – e.g., Craig, 2018; Defra, 2021; PFLA, 2022; Wilkinson, 2011; etc. PFLA, 2022 is not mentioned in the References. Please, check very carefully if all cited publications in the text are in the References and vice versa – all References are cited in the text.
- Missing in Materials and Methods the information about used statistical software (calculation of CV), map software and software used for graphs.
- The real number of the year in the legend of the graphs on Fig. 4 and Fig. 5 or declared it in the title or description of these graphs. What did the authors mean under “current”? Is it data from the year 2020? Fig. 5 – try to find another alternative for the dotted line – it is not visible when it is covered with the dashed line.
- Line 216 – missing space between kg and DM
- line 475 – please, delete the dot after the word “Then”
- line 486 – correct is ‘standard livestock unit (SLU)”
- References - Why is the first one not numbered?
Author Response
Dear Reviewer
Thank you for reading, reviewing and commenting on our manuscript. Your comments and suggestions were encouraging and helped us to improve the quality for the revised manuscript. Please find below are the responses and answers to the comments and questions!
We also attach the revised manuscript with changes highlighted in yellow colour.
Comments and Suggestions for Authors
The theme of the manuscript is complex and actual. However, I have the following notes to this manuscript that should be added/repaired in the text:
1 Incorrect writing of the numbers with units in the case of km and kg at more places. The missing scale and compass rose on the map in Fig. 1
Response: We have searched km and kg in the manuscript and corrected the unit consistency with the expression style such as leaving a space between the number and the unit. Figure 1 is an illustrative map of ceremonial counties of the UK which was used to annotate in yellow to indicate the regions where the predominant livestock farming system types are taking place. We now added the scale and the north arrows for readers who may be less familiar with the UK map.
2 Inconsistent citations in the text – instead of following numbering the names of authors are only inserted in the sentences many times – e.g., Craig, 2018; Defra, 2021; PFLA, 2022; Wilkinson, 2011; etc. PFLA, 2022 is not mentioned in the References. Please, check very carefully if all cited publications in the text are in the References and vice versa – all References are cited in the text.
Response: It is much appreciated that these inconsistencies have been spotted. This has happened because the references were all first written and then inserted and cited by the reference manager Mendeley later. During the manual insertion using Mendeley, few references were missed. Now we have corrected these inconsistent citations in the revised manuscript. We also added the missing reference PFLA (2022).
3 Missing in Materials and Methods the information about used statistical software (calculation of CV), map software and software used for graphs.
Response: We have followed this advice and added an additional section 2.5 for data analysis in the revised manuscript as below:
“The mean, standard deviation (SD) and coefficient of variation (CV%) were calculated in Microsoft Excel for all selected statistical items for the ten years of annual UK agricultural census data from 2011 to 2020. The mean value indicates the magnitude, SD value indicates the interannual variation from the mean value and CV% value indicates the relative interannual variation normalised by the mean value. The illustrative graph figures were made using Sigmaplot 14.0 and the illustrative map was prepared in ArcMap10.8.1.”
4 The real number of the year in the legend of the graphs on Fig. 4 and Fig. 5 or declared it in the title or description of these graphs. What did the authors mean under “current”? Is it data from the year 2020? Fig. 5 – try to find another alternative for the dotted line – it is not visible when it is covered with the dashed line.
Response: We have now added the years of 2011-2020 in the respective graph description to referrer the mean values to the current time dimension. This should make the current context more conspicuous. We appreciate the point that the green dotted line was overlapped with the green dashed line in Figure 5 because the UK annual mean sheep meat production and annual mean sheep meat consumption were almost the same. This has been now made it clearer in the graph description in the revised manuscript.
5 Line 216 – missing space between kg and DM
Response: Corrected.
6 line 475 – please, delete the dot after the word “Then”
Response: We have deleted the dot. We thank the reviewer’s focus on details to spot this typo!
7 line 486 – correct is ‘standard livestock unit (SLU)”
Response: We have deleted the letter “s” in “units”.
8 References - Why is the first one not numbered?
Response: We corrected this in the revised manuscript.
Author Response File: Author Response.doc
Reviewer 4 Report
The paper shows many results, maybe some of these (figures or tables) could be included as supplementary material, once into discussion and conclusion, just a few tables are used.
All tables should be clear and self-explanatory. In Table 1, is not clear how was calculated the daily metabolizable energy (ME, MJ d-1) and the daily intake (kg d-1) of forage herbal dry matter. Table 2 is not clear if DMY is for year or season.
The conclusion section is too long and should be concise and focused on summarizing the main findings and their implications. Including the materials and methods as well as results in the conclusion is not standard practice and could confuse readers.
Author Response
Dear Reviewer
Thank you for reading, reviewing and commenting on our manuscript. Your comments and suggestions were encouraging and helped us to improve the quality for the revised manuscript. Please find below are the responses and answers to the comments and questions!
We also attach the revised manuscript with changes highlighted in yellow colour.
Comments and Suggestions for Authors
1 The paper shows many results, maybe some of these (figures or tables) could be included as supplementary material, once into discussion and conclusion, just a few tables are used.
Response: The cattle and sheep livestock production systems are indeed a complex subject. This manuscript covered a range of topics from grass forage feed production on different grasslands to cattle and sheep farming, ruminant meat production, trade and consumptions. Thank you for these suggestions, but we feel that the inclusion of all tables and figures should make the story more fluent to flow without interruptions to look for the supplementary materials for facts to validate statements in the main text.
2 All tables should be clear and self-explanatory. In Table 1, is not clear how was calculated the daily metabolizable energy (ME, MJ d-1) and the daily intake (kg d-1) of forage herbal dry matter. Table 2 is not clear if DMY is for year or season.
Response: We have used the benchmark daily metabolisable energy requirement per standard livestock unit from the reference Craig (2018). We have revised the Table 1 title description to make the calculations clearer. Table 2 is grass forage dry matter yield per year, and we have made it clear in the revised Table 2.
3 The conclusion section is too long and should be concise and focused on summarizing the main findings and their implications. Including the materials and methods as well as results in the conclusion is not standard practice and could confuse readers.
Response: Thank you for these observations. We have now shortened and improved the conclusion by removing the content of results in the revised manuscript as below.
“This study has shown that the total availability of herbage dry matter on all grasslands can support a national potential carrying capacity for cattle and sheep to produce sufficient ruminant meat to meet the UK domestic needs with undemanding pasture utilisation rates if consumption per capita stayed at the current levels. Pastures not only supply sustainable feed to ruminants but also play a potential role in greenhouse gas mitigation, preserving soil fertility, and combatting soil erosion on steep slopes due to their ecosystem services. The adoption of grass-fed only diets for cattle and sheep farming should offer to support the transitional pathway of the UK government to net zero greenhouse gas emission target by 2050. However, it is important to remember that this analysis may provide a useful pathway but implementing and practicing grass-fed only cattle and sheep farming systems may be complicated because it can involve major changes for governmental policies and the farmers such as land use, livestock products certifications and herd characteristics. The adopted approach in the paper can be expanded by including nutritional aspects such as crude protein content in the pastures for a more complex analysis with these large, interrelated sets of long-term time-series data collected by the UK government.”
Author Response File: Author Response.doc
Round 2
Reviewer 2 Report
Dear authors, it seems to me that this manuscript has relevance in the scientific world. I think the authors made the suggested changes; therefore, I recommend approval.
