Socio-Economic Analysis of Wood Charcoal Production as a Significant Output of Forest Bioeconomy in Africa
Round 1
Reviewer 1 Report
This paper discusses wood charcoal production in Africa over three decades. It is appropriate for the journal and will be of interest to readers. Overall, I found the paper to be well written and easy to follow. Specific comments are below. I wish the authors luck in this process. -Title: Consider adding "in Africa" at the end of your title.
-Abstract: Appropriate -Introduction: Well written. Introduces the problem and the need to study it.
–Methods: Overall easy to follow. A couple of minor typographical errors. -Methods: "Qualitative methods used were percentages, sum, and average..." Consider changing qualitative to descriptive. Methods: "The quantitative and geospatial data analysis methods used were correlation, multivariate analysis..." Correlation is multivariate analysis.
-"The results of the average wood charcoal production for the last three decades (1990-2019) among the African countries revealed that the production was not evenly distributed (Figure 1a, 1b, and 1c)." You did not test for distributional differences. Observing the figures alone does not necessarily lead me to that conclusion. Please verify. Perhaps with a table of top five or ten countries by decade? Or could you add abbreviated titles to the countries?
-Results: When reporting tonnes, there are no commas in the values? Is this journalistic style? If not, please add appropriate commas.
-Results: when mentioning East Africa, it is called a country instead of a region. -Results (Methods): Were incomes adjusted for inflation to real dollars? If so, what was teh base year. To compare these values across time, they should be reported in inflation-adjusted dollars instead of nominal dollars.
-Results: "It is important to state that income per citizen was highly associated with wood charcoal production and deforestation." Please provide a measure of correlation or other appropriate statistic to support this statement. I cannot see it directly from the figures. Refer to Table 3 if appropriate. I cannot see from Table 3 that forest cover and income are significantly correlated?
-Results Table 3: Please describe the meaning of the asterisks in the table.
-Results Page 13: "As human population increases with decrease in income,..." Please add you r correlation coefficient from Table 3, or refer to Table 3.
-Figure 6. Please add axis titles. Please add some depth here to better give the reader insight into the figure's meaning. Using one country as an example to describe the graph would be a plus.
-Figure 6 and Implications: The implications are very interesting. Would the authors consider making the softwood species identified in Figure 6 a red font (or some other color) to highlight for the reader the implication of burning more softwood species?
-Conclusions: Appear to be supported by the Results
Author Response
REVIEWER 1 REPORT AND AUTHORS’ RSPONSES
Comments and Suggestions for Authors
Reviwer’s Comments and Suggestions: This paper discusses wood charcoal production in Africa over three decades. It is appropriate for the journal and will be of interest to readers. Overall, I found the paper to be well written and easy to follow. Specific comments are below. I wish the authors luck in this process.
Authors’ Response: Thank you, with great pleasure we receive the above commendation.
Reviwer’s Comments and Suggestions: -Title: Consider adding "in Africa" at the end of your title.
Authors’ Response: ‘in Africa’ has been added to the paper title as suggested by the reviewer.
Reviwer’s Comments and Suggestions: -Abstract: Appropriate -Introduction: Well written. Introduces the problem and the need to study it.
Authors’ Response: Thank you, for this remark.
Reviwer’s Comments and Suggestions: –Methods: Overall easy to follow. A couple of minor typographical errors. -Methods: "Qualitative methods used were percentages, sum, and average..." Consider changing qualitative to descriptive. Methods: "The quantitative and geospatial data analysis methods used were correlation, multivariate analysis..." Correlation is multivariate analysis.
Authors’ Response: ‘Qualitative methods’ has been replaced with ‘descriptive methods’, while ‘correlation’ has been corrected as a ‘multivariate analysis’.
Reviewer’s Comments and Suggestions: -"The results of the average wood charcoal production for the last three decades (1990-2019) among the African countries revealed that the production was not evenly distributed (Figure 1a, 1b, and 1c)." You did not test for distributional differences. Observing the figures alone does not necessarily lead me to that conclusion. Please verify. Perhaps with a table of top five or ten countries by decade? Or could you add abbreviated titles to the countries?
Authors’ Response: As suggested by the reviewer, Table A1 has been added. This together with the figure 1 will give the readers a clearer understanding that: “The results of the average wood charcoal production for the last three decades (1990-2019) among the African countries revealed that the production was not evenly distributed (as shown in Figure 1a, 1b, and 1c)."
Reviewer’s Comments and Suggestions: -Results: When reporting tonnes, there are no commas in the values? Is this journalistic style? If not, please add appropriate commas.
Authors’ Response: Commas have been added in the values where appropriate.
Reviewer’s Comments and Suggestions: -Results: when mentioning East Africa, it is called a country instead of a region. -Results (Methods): Were incomes adjusted for inflation to real dollars? If so, what was the base year. To compare these values across time, they should be reported in inflation-adjusted dollars instead of nominal dollars.
Authors’ Response: -Results: Mentioning East Africa as country instead of a region has been corrected in the text. –Results (Methods): The income per citizens was in inflation-adjusted dollars in 2010. Though, most countries in Africa has been recording inflation rates before 2010, but this year (2010) was used as the base year because the inflation rates for more than 80% of countries in the continent became high from 2010. This information is in the main text under material and method, section 2.3.
Reviewer’s Comments and Suggestions: -Results: "It is important to state that income per citizen was highly associated with wood charcoal production and deforestation." Please provide a measure of correlation or other appropriate statistic to support this statement. I cannot see it directly from the figures. Refer to Table 3 if appropriate. I cannot see from Table 3 that forest cover and income are significantly correlated?
Authors’ Response: It was an error on our part for omitting the significant correlation between income and forest cover (r = 0.40*) which we have in our result. It has been addressed. The correlation between income and wood charcoal production covering the whole study period (Decade 1-3; i.e. 1990-2019) was also significant (r = 0.53*). Though, we acknowledged it and did not omit it as in the case of income and forest cover. Therefore, our result revealed that income per citizen was significantly correlated with both the forest cover and the wood charcoal production (Table 3). The statement: "It is important to state that income per citizen was highly associated with wood charcoal production and deforestation" has been supported with a statistical result. It has been addressed and well written as included in ‘section 3.2’ of the manuscript.
Reviewer’s Comments and Suggestions: -Results Table 3: Please describe the meaning of the asterisks in the table.
Authors’ Response: The meaning of the asterisks in Table 3 has been described. In addition, the abbreviated study parameters have also been described for more clarity and understanding by the readers.
Reviewer’s Comments and Suggestions: -Results Page 13: "As human population increases with decrease in income,..." Please add you r correlation coefficient from Table 3, or refer to Table 3.
Authors’ Response: The correlation coefficient (r = - 0.58) has been added to support the statement: “As human population increases with decrease in income”.
Reviewer’s Comments and Suggestions: -Figure 6. Please add axis titles. Please add some depth here to better give the reader insight into the figure's meaning. Using one country as an example to describe the graph would be a plus.
Authors’ Response: Figure 6 was a multivariate analysis performed with RDA using CANOCO 5.0. In this kind of analysis, the software does not represent results using titles for axis, but it uses negative (–) values and positive (+) values for the axes (vertical and horizontal). All the information needed to read and understand the figure are shown in the figure. For example, Figure 8a showed the distribution of species and their pollution emission (fumes and CO2) status for each decade. Wood/tree species in Decade 3 had high fumes and CO2 emission, those commonly found in Decade 2 had moderate GHG emission, while the wood or tree species in Decade 1 produced relatively low pollutant gases. The list of wood or tree species common in each decade is indicated. For instance, Decade 3 was dominated by Gmelina arborea, Juniperus procera, Pinus halepensis, Pinus pinaster, Cedrus atlantica, etc, Decade 2 had Cleistanthus mildbraedii, Cylicodiscus gabonensis, Klainedoxa gabonensis, etc, while the primary species found in Decade 1 were Pentaclethra macrophlla, Diospyros spp., Letestua durissima, Milicia excels, etc.
Reviewer’s Comments and Suggestions: -Figure 6 and Implications: The implications are very interesting. Would the authors consider making the softwood species identified in Figure 6 a red font (or some other color) to highlight for the reader the implication of burning more softwood species?
Authors’ Response: We guess that the reviewer is referring to Figure 6(b). It might not be ideal to do such because that will deviate the object/concept of the work. This figure (6b) showed the proportion of species for each decade. But it is possible to display the species (e.g., Extremely hardwood, Hardwood, Softwood, etc) as in Table 4 with different colours but that will mean a duplication of result since the Table 4 already has such information.
Reviewer’s Comments and Suggestions: -Conclusions: Appear to be supported by the Results
Authors’ Response: Thank you.
Bottom of Form
Author Response File: 
Author Response.pdf
Reviewer 2 Report
This work aimed at quantifying the volume of WCH production as well as appraising its socio economics, including environmental impacts, especially the impact of long-term deforestation and forest degradation in Africa.
The paper’s subject is very practical and interesting. The research procedure has been logically carried out. I have some few comments on the text:
Comments:
1)The novelty of work should be highlighted in introduction section.
2)There is a blank page between pages 2 and 4. Please delete it.
3)What kind of software/tool has been used for mathematical/statistical/numerical analysis in this?
4)Numbering of these sections(2.4. Data collection, 2.5. Data Analysis) should be changed in this way: 2.3. Data collection, 2.4. Data Analysis
5) In recent years, many researchers have investigated economic impacts in field of forestry and environment. I recommend the authors to add some more new references in this field in the paper. It would be certainly interesting for the readers of the journal. Some suitable references that are highly recommended are listed in the following:
[1] Udali, A., Andrighetto, N., Grigolato, S. and Gatto, P., 2021. Economic Impacts of Forest Storms—Taking Stock of After-Vaia Situation of Local Roundwood Markets in Northeastern Italy. Forests, 12(4), p.414.
[2]Liu Y, Li S, Wang Y, et al. De novo assembly of the seed transcriptome and search for potential EST-SSR markers for an endangered, economically important tree species: Elaeagnus mollis Diels[J]. Journal of Forestry Research, 2020, 31(3): 759-767.
Author Response
REVIEWER 2 REPORT AND AUTHORS’ RESPONSES
Comments and Suggestions for Authors
This work aimed at quantifying the volume of WCH production as well as appraising its socio economics, including environmental impacts, especially the impact of long-term deforestation and forest degradation in Africa.
The paper’s subject is very practical and interesting. The research procedure has been logically carried out. I have some few comments on the text:
Comments:
Reviewer’s Comments and Suggestions: 1) The novelty of work should be highlighted in introduction section.
Authors’ responses: In the last paragraph of the introduction, the novelty of the work has been highlighted as follows:
Most of the studies on WCH production in Africa focused on either one to few countries, or their studies were only related with a singly selected parameter such as biofuel implication [4,5], tree species and wood quality [20,21], political issues and policies [22,23], environmental and health implications [4,8,17,18,24], impacts on food safety [25], and socioeconomic [6-11]. A study with a holistic approach that integrates most of these factors as they relate with WCH production is lacking in Africa. Therefore, the novelty of this work is obvious because it aimed at quantifying the volume of WCH production in Africa as well as appraising its socio-economics, including environmental impacts, especially the impact of long-term deforestation and forest degradation. The inclusion of multiple variables (such as, areas of forest cover, export quantity, export value, GDP, human population, climate season, average income per citizen, and literacy rate) which were simultaneously examined in relation to WCH production was also remarkable. At present, there is no record of any studies that have performed such robust investigation on this topical issue in the region (Africa).
Reviewer’s Comments and Suggestions: 2) There is a blank page between pages 2 and 4. Please delete it.
Authors’ responses: The blank page has been deleted.
Reviewer’s Comments and Suggestions: 3) What kind of software/tool has been used for mathematical/statistical/numerical analysis in this?
Authors’ responses: All statistical analyses were performed using the following software/tools: EXCEL, CANOCO version 5.0 and STATISTICA version 13.0, while the spatial analysis and mapping were done using ArcGIS 10.7.1. The descriptive statistics performed in Excel included percentages, sum and average for WCH productions, forest area cover, export quantity and export value. The multivariate methods performed were correlation, principal component analysis (PCA) and redundancy analysis (RDA). For the geospatial data analysis, we employed spatial analytical tools of ArcGIS which was used to map the distributional trend during the years.
Reviewer’s Comments and Suggestions: 4) Numbering of these sections(2.4. Data collection, 2.5. Data Analysis) should be changed in this way: 2.3. Data collection, 2.4. Data Analysis
Authors’ responses: The numbering in the sections has been corrected.
Reviewer’s Comments and Suggestions: 5) In recent years, many researchers have investigated economic impacts in field of forestry and environment. I recommend the authors to add some more new references in this field in the paper. It would be certainly interesting for the readers of the journal. Some suitable references that are highly recommended are listed in the following:
[1] Udali, A., Andrighetto, N., Grigolato, S. and Gatto, P., 2021. Economic Impacts of Forest Storms—Taking Stock of After-Vaia Situation of Local Roundwood Markets in Northeastern Italy. Forests, 12(4), p.414.
[2]Liu Y, Li S, Wang Y, et al. De novo assembly of the seed transcriptome and search for potential EST-SSR markers for an endangered, economically important tree species: Elaeagnus mollis Diels[J]. Journal of Forestry Research, 2020, 31(3): 759-767.
Authors’ responses: The above references have been added as recommended by the reviewer. Furthermore, additional references have been included/cited. Example [47-51] as shown in Page 11
Bottom of Form
Author Response File: Author Response.pdf
Round 2
Reviewer 2 Report
All the comments have been addressed correctly. The paper is ready for publication in the present form.
