Spatiotemporal Distribution and Influencing Factors of the Net Primary Productivity in the Datai Mine in Western Beijing
Round 1
Reviewer 1 Report (Previous Reviewer 1)
Dear Editor in Chief of Sustinability
As the original reviewer of the manuscript entitled as ‘ Spatiotemporal distribution characteristics and influencing 2 factors of net primary productivity in Western Beijing Datai 3 Mine ", I went through the manuscript and found that it has merits to publish in an international Journal and it is in line with scopes of your Journal. The authors have improved the manuscript properly that is ready for publication at the present form.
Yours .
Author Response
Thank you provided comments and supported my article!
Reviewer 2 Report (Previous Reviewer 2)
The manuscript “Spatiotemporal distribution characteristics and influencing factors of net primary productivity in Western Beijing Datai Mine” by the authors was very well done. It is an impressive and well-thought-out manuscript. I have mostly minor suggestions and may be a bigger one that I think will improve an already good manuscript but needs to be revised before being accepted.
i. Can the authors remove the characteristics from the title “Spatiotemporal distribution and influencing factors of net primary productivity in Western Beijing Datai Mine"?
ii. Line 17: research object must be replaced by a research area or study area as the coal mine in western Beijing is a site name, not an object.
iii. Line 19: too long sentence and many words are repeated. Would be better to revise the sentence as
“Based on the meteorological, remote sensing images and land use data of the mining area, the improved Carnegie-Ames-Stanford Approach (CASA) was used to calculate the net primary productivity (NPP) of vegetation in Datai Mine area from 2013 to 2021, to analyze its temporal and spatial distribution in relation to meteorological factors”.
iv. Line 20: if Carnegie-Ames-Stanford Approach (CASA) is written then I don’t think to write a model in this sentence.
v. Line 23: The results show that in the past 9 years, the NPP in the Datai mining area has generally increased from 546 gC/m² and 601 gC/m². The NPP in Mentougou district has generally decreased whereas Mentougou area NPP has a significant relationship with precipitation, temperature, and solar radiation. Mentougou area NPP change has a significant positive correlation with precipitation change (please give the R2-value here). The Mentougou area NPP change has no significant relationship with temperature (r =??) and solar radiation fluctuations (r = ??). In conclusion, the vegetation NPP in Datai Mine changes regularly over one year, where the annual vegetation NPP was about 2-times of Mentougou area probably due to low-intensity mining of Datai Mine, as we did not record a significant impact on the vegetation carbon sequestration capacity in this area.
vi. The introduction is good enough but the connectivity between paragraphs is not clear. I suggest focusing your introduction on the main idea.
vii. Could the authors expand on why the authors tested Boltzmann function, Gauss function Logistic function, Sine function, and Exponential function for fitting the coefficient? I think the authors need to focus on the final function best suited to these analyses.
viii. Generally, spatiotemporal distribution characteristics and influencing factors of net primary productivity is a long-term temporal perspective, why the authors only considered and analysed the data for 9 years only? I am not saying this wrong what the authors have already done, just want some more information to justify how authors placed the short-term data in a historical context. What were the author's considerations?
ix. To quantify the NPP the authors used the destructive method or the indirect method. It is not clear to me.
x. The manuscript shows a comparatively novel methodology but how the authors chose the trend analysis method with specific regression (like univariate linear regression) to analyze the inter-annual NPP from 2013 to 2021. Prior the author needs to test other regressions and finally needs to use the appropriate based on optimal or robust results.
xi. In addition, the paper could be more interesting if compare with other recent studies on NPP in relation to environmental variables.
xii. The conclusion reflects the finding of the results. I suggest that possible limitations and recommendations of the research must be added. It will be more helpful.
Author Response
- Can the authors remove the characteristics from the title “Spatiotemporal distribution and influencing factors of net primary productivity in Western Beijing Datai Mine"?
Response: Thanks for your comments, I would like to accept your advice, and the new title is: “Spatiotemporal distribution and influencing factors of net primary productivity in Western Beijing Datai Mine".
- Line 17: research object must be replaced by a research area or study area as the coal mine in western Beijing is a site name, not an object.
Response: Thanks for your comments, I have replayed the “research object” to “study area”. The new sentence has rewrote as: In order to quantitatively study the vegetation carbon sequestration, this article uses Net Primary Productivity (NPP) as the indicator to measure it. This research takes the Datai coal mine in western Beijing as the study area.
- Line 19: too long sentence and many words are repeated.
Response: Thanks for your comments, I would like to accept your advice and revise the sentence as: “Based on the meteorological, remote sensing images and land use data of the mining area, the improved Carnegie-Ames-Stanford Approach (CASA) was used to calculate the net primary productivity (NPP) of vegetation in Datai Mine area from 2013 to 2021, to analyze its temporal and spatial distribution in relation to meteorological factors”.
- Line 20: if Carnegie-Ames-Stanford Approach (CASA) is written then I don’t think to write a model in this sentence.
Response: Thanks for your comments, I would like to accept your advice and remove the word “model”.
- Line 23: Lake of r (Correlation coefficient):
Response: Thanks for your comments, I added the data at this part: The results show that in the past 9 years, the NPP in the Datai mining area has generally increased from 546 gC/m² and 601 gC/m². The NPP in Mentougou district has generally decreased whereas Mentougou area NPP has a significant relationship with precipitation, temperature, and solar radiation. Mentougou area NPP change has a significant positive correlation with precipitation change (R²=0.8). The Mentougou area NPP change has no significant relationship with temperature (R²=0.98) and solar radiation fluctuations (R²=0.75). In conclusion, the vegetation NPP in Datai Mine changes regularly over one year, where the annual vegetation NPP was about 2-times of Mentougou area probably due to low-intensity mining of Datai Mine, as we did not record a significant impact on the vegetation carbon sequestration capacity in this area.
- The introduction is good enough but the connectivity between paragraphs is not clear. I suggest focusing your introduction on the main idea.
Response: Thanks for your comments, I added some connectives at each paragraph and highlighted the main idea of the article. Firstly, I displayed the significance to study the calculation of vegetation carbon sequestration. Then I introduced direct observation method and its’ defects. Driving by comparing four main tapes models, the article combines the improved CASA model to analysis the NPP characters and provides the research aim in the end.
- Could the authors expand on why the authors tested Boltzmann function, Gauss function Logistic function, Sine function, and Exponential function for fitting the coefficient? I think the authors need to focus on the final function best suited to these analyses.
Response: Thanks for your comments, the relationship between climate factors and NPP change rule is consistent with Boltzmann and Gauss models. For example, the change of vegetation NPP-Temperature shows a law of slowly increase, sharply increase, and then slowly increase, so that the Boltzmann function is used for fitting. What is more, the Boltzmann model and Gauss model are selected from 21 models, the maximum value of R² is selected as the relationship between vegetation NPP and climate factors. To focus final functions, I analyzed the NPP and each climate factor’s gradient curve based on Gauss function and Logistic function. By determining the derivative, it has been found the best environment for vegetation to provide the maximum NPP values. The further analysis is at section 3.3.1.
- Generally, spatiotemporal distribution characteristics and influencing factors of net primary productivity is a long-term temporal perspective, why the authors only considered and analyzed the data for 9 years only? I am not saying this wrong what the authors have already done, just want some more information to justify how authors placed the short-term data in a historical context. What were the author's considerations?
Response: Thanks for your comments, based on the study area covered, it is necessary to use the data at least 30m resolution ratio. One reason I analyzed NPP from year 2013 is that the Landsat 8 was launched in February 2013. The NDVI data that used to calculate NPP is from the Landsat 8. Therefore, I can only calculate and analyze the NPP value from 2013. Secondly, because the Datai Mining was closed at September 17, 2019, this study wanted to focus the environmental change characteristics before and after the mine closure.
- To quantify the NPP the authors used the destructive method or the indirect method. It is not clear to me.
Response: Thanks for your comments, this article divides the methods for calculating NPP into two categories: direct observation methods (destructive method) and model measurement methods (indirect method). The main model measurement methods include: climate-productivity relationship models, Eco-physiological process models, remote sensing application models and light utilization efficiency models. In the article I used the improved CASA model of the light utilization efficiency models to quantify the NPP.
- The manuscript shows a comparatively novel methodology but how the authors chose the trend analysis method with specific regression (like univariate linear regression) to analyze the inter-annual NPP from 2013 to 2021. Prior the author needs to test other regressions and finally needs to use the appropriate based on optimal or robust results.
Response: Thanks for your comments, to use the univariate linear regression I searched some studies before to analyze the inter-annual NPP. What is more, I have analyzed the Manner-Kendall trend test before, to compare the results and the character of NPP ‘s spatiotemporal dynamic analysis, I chosen the slope linear regression to analyze inter-annual NPP from 2013 to 2022. Here is the result of M-K trend result and related literature:
Table 2 Statistics of NPP Change M-K Trend of Vegetation in Mentougou District
|
Grading of change trend slope |
Grading |
Area/km2 |
|
Z＜-1.92 |
Significant reduction |
151 |
|
-1.92≤Z<-0.01 |
Slight decrease |
33 |
|
-0.01≤Z<0.01 |
Basically unchanged |
791 |
|
0.01≤Z<1.92 |
Slight increase |
461 |
|
Z≥1.92 |
Significant increase |
12 |
- He H, Ma B, Jing J, et al. Spatial and temporal changes of vegetation NPP and geographical exploration of natural factors in karst areas of southwest China in recent 20 years [J]. Research on Water and Soil Conservation, 2022,29 (03): 172-178+188.
- Ma B, Jing J, Xu Yet al. Study on the temporal and spatial changes of vegetation NPP in karst areas of Yunnan, Guizhou and Guangxi from 2000 to 2019 and its relationship with climate change [J]. Journal of Ecological Environment, 2021,30 (12): 2285-2293.
- Cui B, Zheng Jh, Tuerxun Hasmu, et al. Study on the Spatial and Temporal Differentiation Characteristics of Grassland Net Primary Productivity in the Tarim River Basin [J]. Journal of Grassland Industry, 2020,29 (06): 1-13.
- Zhang Y, Tang M, Chen X. Spatial and temporal distribution of net primary productivity of vegetation in Hainan Island from 2000 to 2019 [J]. Journal of Hainan University (Natural Science Edition), 2022,40 (02): 158-167.
- Li C, Yang S, Wu F, et al. The temporal and spatial differentiation of China's energy consumption carbon emissions and vegetation carbon sequestration in the context of "dual carbon" [J]. China Environmental Science, 2022,42 (04): 1945-1953.
- Wang L, Zhang Hx, Liu Z, et al. A coupling model for simulation and prediction of net primary productivity pattern [J]. Journal of Wuhan University (Information Science Edition), 2021,46 (11): 1756-1765.
- Hong Lele, Shen Yan, Ma Hongbin, Zhang Peng, Huo Xinru, Wen Huachen. Temporal and spatial changes of net primary productivity of vegetation in Ningxia from 2000 to 2019 and its driving factors [J/OL]. Chinese Journal of Applied Ecology, 2022, 1-10.
- In addition, the paper could be more interesting if compare with other recent studies on NPP in relation to environmental variables.
Response: Thanks for your comments, in discussion part, I compared the effect of climate variables om NPP with other four studies, some proved the similar result with this article, and some are not: When studying the effect of climate factors (temperature, precipitation and solar radiation) on NPP, most studies have proved that the NPP changes are crucial impacted by precipitation [41-42], which is consistent with this article. Some studies, however, announced that NPP changes are impacted by precipitation and temperature [43-44]. The reasons for different results be suggested were based on the various database or different research cycles.
- The conclusion reflects the finding of the results. I suggest that possible limitations and recommendations of the research must be added. It will be more helpful.
Response: Thanks for your comments, in conclusion (5) there has two deficiencies, and I added one recommendation for further study:
There are still some deficiencies in this study that need to be improved. First, when acquiring data from meteorological station, a few meteorological observation stations have data missing in some daily periods. This article uses data from adjacent meteorological stations to supplement (like daily temperature or precipitation). Second, the influencing factors of vegetation NPP are not only environmental factors, but also the influence of vegetation characteristics and human activities on the changes of vegetation NPP. And further study should also combine coal-output, ground surface settlement and some mining elements to analyze. What is more, the fluctuation of coal mining NPP is a multivariate process on meteorological change, the results of repair projects and the impact of mining. Meanwhile, the process of repair projects and the influence of mining factors have no obvious regularity. Combined with climate factors, it is hard to distinguish which area is dominated by different impact factors. The future study will build an integrated computational model of coal mining NPP based on meteorological and mining elements to analyze the impact of various factors on NPP.
Author Response File: 
Author Response.docx
Reviewer 3 Report (Previous Reviewer 3)
I have attached the comments.
Comments for author File: 
Comments.pdf
Author Response
Thank you very much for your valuable comments. I have replyed all the comments and made some changes based on the comments. I submited the document at below.
Author Response File: Author Response.pdf
Round 2
Reviewer 3 Report (Previous Reviewer 3)
I have checked authors' response to my comments. It is acceptable at the present format.
This manuscript is a resubmission of an earlier submission. The following is a list of the peer review reports and author responses from that submission.
Round 1
Reviewer 1 Report
Dear Editor in Chief of Sustinability
As the reviewer of the manuscript entitled as ‘Spatial and temporal distribution characteristics and influenc-ing factors of vegetation carbon sequestration in Western Bei-jing Datai MineI went through the manuscript and found that it has merits to publish in an international Journal. It suffers from minor shortcomings that I have highlighted on the attached PDF manuscript file. In overall, I am recommending for publication after minor revision. Moreover, I am strongly suggesting to be improved linguistically and grammatically by a native in English.
Sincerely Yours .
Comments for author File: Comments.pdf
Reviewer 2 Report
Climate is a global issue and carbon sequestration can surely aid in mitigating the changes. In this regard the manuscript is very interesting and focuses an important climatic issue. The models used are very comprehensive and interesting and well to the point. However, I have some concerns
1. The manuscript is ill structured need to be properly arranged
2. The distribution data of vegetation is missing
3. Discussion is almost nil or missing
4. Very little literature citation, need to add valid and Upto date literature from research articles in every section of the paper for improvement of the subject matter in research.
The authors need to work on these points and improve the manuscript for attracting the broader readers.
Specific comments are follows
Title: The title can be more attractive e.g. Spatiotemporal distribution characteristics ……………..
Abstract
The abstract length is sufficient but need thorough language improvement and revision especially the importance/need of the current research; objective and conclusion need to be properly addressed
-Line 11. Comprehensively effected... very much exaggerated please remove the comprehensively.
-Line 13-15. Very poor language please revises
- Line 17 CASA model? No abbreviation when word appears first
-Line 15-20. Very haphazardly written, not clear
-Results are written without numerical evidences
-Conclusion is completely missing
-Keywords can be modified
Introduction
The introduction section is written well, but it lacks the proper literature citation.
-Line 44-57. The two methods of carbon sequestration methods are valuable can you evaluate the needs and situation to use these methods properly.
-Line 58-62. Please justify why net primary productivity is considered and gross is not considered
-Line 62. CO2 make 2 as subscript please
-Lien 90. CASA model… please don’t use abbreviation on first appearance
-Proper research hypothesis, its need and importance are lacking which are vital to be addressed
-Research objective are not properly elaborated
Material and method
The methodology used is valid but it lack proper arrangement… I would suggest describing the study area before the method.
Results and analysis
The results are interested but completely lack vegetation spatial and temporal distribution. So change the title or add vegetation characteristics data.
-Vegetation distribution is almost missing in the results as well in the methodology
-Can you justify that NPP is net carbon sequestration. As the product may be used for many other purposes.
Conclusion and Discussion
Very poorly written, discussion need to be properly written with the result or separated from the result having proper literature and justification of the result in favor or against. The conclusion is the repetition of the results. The conclusion needs to be refined and provide recommendations for further studies.
In addition, reduces the similarity index as its 22%.
Comments for author File: Comments.pdf
Reviewer 3 Report
Comments for author File: Comments.pdf
