Conversion of natural forests to farmlands and its associated woody species diversity and carbon stocks in a span of 33 years (1984 to 2016): in the case of southwestern Ethiopia [version 2; peer review: 1 approved, 2 not approved]

Background Gura-Ferda forest is one of the Afromontane rainforests in the southwestern region of Ethiopia. However, since 1984, large parts of this forest have become increasingly disturbed and fragmented due to forest conversion into forest farm interface and farmlands. The study was conducted to assess changes of woody species diversity and carbon stock in association with the conversion of natural forest to forest farm interface and farmlands. Methods Data were collected from natural forest, forest farm interface and farmland which are historically forest lands before 1984. A total of 90 nested plots (20m×20m for natural forest and forest farm interface; 50m*100m for farmland)) were established for inventory of woody species. Three 1m×1m subplots were established to collect litter and soil samples. A total of 180 soil samples were collected. The total carbon stocks were estimated by summing carbon stock in the biomass and soil (0-60 cm depth). Results Results showed that Shannon-Wiener diversity (H’) in forest farm interface (H’ = 1.42±0.49) is significantly lower than that of natural forest (H’ = 2.72±0.31) but significantly higher than farmland (H’ = 1.08±0.57). The total carbon stocks of natural forest (388.54±161.63 Mg C ha -1


Introduction
Over the last two decades, forests and forest management have changed dramatically. In 1990, the world's forest area was 4.13 billion hectares (ha) (31.6% of total land area of Earth). According to the UN's Food and Agriculture Organization, this area had shrunk to 3.99 billion hectares (30.6% of Earth's total land area) by 2015 1 . Ethiopia's ecosystem is diverse, ranging from the dry lowlands in the east to the high altitudes of the central highlands (Hurni, 1998). The country's unique ecological conditions, as well as its rich flora and fauna, have made it one of the most important biodiversity hotspots on the world 2 . The country's forest land, on the other hand, has been rapidly shrinking over time. From 1990 to 2000, forest losses were estimated to 8.3 million hectares, and from 2000 to 2010, 5.2 million hectares 3 . This day major parts of the remaining natural forests which harbor high biodiversity are located on steep slopes at high altitude and in the remote southern and southwestern parts of the country. These few remaining high forests are also threatened by anthropogenic activities and converted to agricultural and other land use systems 4 . Similarly, other remaining natural forests have also been threatened by pressure from investors and changed to industrial plantation like coffee and tea 4,5 . This reduction and conversion of natural forest to other land use systems in many parts of Ethiopia has led to the decline in number and distribution of many plant species, shortage of raw materials for wood processing industries and disturbance of ecosystem services 6 . As a consequence, forest farm interface has expanded within and around the natural forest. Subsequently, it has resulted the expansion of forest farm interface in and around the forest ecosystem.
"For this study forest farm interface is defined as an area produced by forest encroachment that is officially unclassified as either forest or agricultural lands and is found in areas where intense economic activities such as crop farming, grazing, and the use of forest products predominate. It comprises lands managed by persons with no official use rights and found between natural forest and farmlands" 7 . For the past five decades, the government of Ethiopia has attempted to reforest degraded forests 4,5 . Hundreds of aid projects have been implemented in different parts of the country to reverse deforestation and forest degradation in the country. However, the success stories were below expectations and the problems are still immense. This resulted from the lack of effective management practices and quantification of the available forest resources. This insufficiency of scientific quantitative data brought lack of responsiveness for sound management of natural resources in the country.
Gura-Ferda forest is one of the Afromontane rainforests in the southwestern region of Ethiopia and grows at altitudes from 700 to 2,300 meter above sea level. During the past decades, especially since 1984, large parts of this forest have progressively been disturbed and fragmented due to forest conversion to settlements, agriculture, and industrial plantation 8 . Nowadays, pressure produced by immigration and investors is increasing forest disturbance. However, there is no quantitative information on the change of species diversity and carbon stocks resulting from the conversion of natural forests to forest farm interface and farmlands. The overall objective of this study was, therefore, to analyze the woody species diversity and carbon stock change in association with the change of natural forests to forest farm interface and farmlands. The study hypothesized that, the conversion of natural forests to forest farm interface and farmlands affect the woody species diversity, biomass and soil organic carbon (SOC) stocks.

Materials and methods
Description of the study area The study was conducted at Gura-Ferda district of southwestern Ethiopia which is located at 603 km southwest of the capital city Addis Ababa ( Figure 1). Geographically, it is positioned between 6°29'12" N and 7°13'22" N latitude and 34°52'23" E and 35°23'59" E longitude. The area coverage of this district is estimated to be 2565.42 km 2 . The annual average rainfall over the period of 1983-2012 was 1639.8 mm, with a maximum of 1946.3 mm and a minimum of 1289.8mm. The area receives a maximum rainfall in October and minimum rainfall in February. The average annual temperature is 23.4°C with a range from 16.1°C-30.6°C. The dominant soil type of the study area is nitisols with soil textural class loam to clay 9 .
As the past data of the Gura-Ferda district specified, since 1984, there was a degradation of natural forest in the area ( Table 1). The notable drivers of this forest area decrement were Amendments from Version 1 Version 1 has been updated with the following changes: The reviewers' comments and suggestions have been addressed in the updated version of this manuscript. The following changes have been made to improve the manuscript: 1.
Abstract: Statistical analysis information updated. 8. Discussion: Additional information on the potential explanations for the findings.   4,11 . Next to resettlement, the taken up of forest by investors is other key drivers for the degradation and deforestation of natural forests in the area. According to 10, there were more than 30 investors who were involved in different agricultural investment especially coffee and rubber tree plantation. These investors had been used shrub land, natural forest, and grass lands for investment.

Methodology
Data source. For the purpose of this research both primary and secondary data were employed. Primary data were obtained through field survey of the study area. Secondary data used were satellite images and publications such as articles, data from district land administration offices and censuses results. Multi-sensor and multi-temporal Landsat images were downloaded from United States Geological Survey (USGS) (https://earthexplorer.usgs.gov) ( Table 2). Accordingly, satellite images of 1984 and 2016 were used for this study. Images of the year 1984 were taken because it was the time when the government organized a resettlement program at the study area. Similarly, images from the year 2016 was selected because it was the time when recent agricultural systems were expanded and government was focused on commercial investments in the area. Since it is a time of free atmospheric cloud, satellite images in the months of December to January were used.
Stratification of study area. Before the resettlement program of 1984, all areas used for the sampling unit in this study time were covered by forest. However, nowadays, it is observed that the area has three discrete categories. These are: natural forest, forest farm interface and farmland ( Figure 2; Figure 3).
• Natural forest (NF): land with trees, shrubs and other vegetation that originally emerged on its own without  the influence or direct intervention of man covering more than 0.5 ha and growing to a height of more than 2m and a canopy cover of more than 20% 12 .
• Forest-farm interface (FFI): an area produced by forest encroachment that is officially unclassified as either forest or agricultural lands and is found in areas where intense economic activities such as crop farming, grazing, and the use of forest products predominate. It comprises lands managed by persons with no official use rights and found between natural forest and farmlands 7 .
• Farmland (FL): an area which has been converted to intensive mono cropping with few/no scattered trees due to high disturbance Sampling techniques. Three transects with a total of 30 plots (10 plots on each transect) were established on NF, FFI, and FL using a compass and a geographic positioning system (GPS). A distance of 200 meters (m) separated the transect lines and sample plots from each other 13,14 ( Figure 4). Each land use system's sample plot size was selected based on the expected density of woody species 15,16 . To collect vegetation data for both NF and FFI, a nested plot design of 400m 2 with 25m 2 and 1m 2 size was employed (tree, sapling and seedling, respectively). Plot size of 50 m × 100 m was used for FL 17 . Seedlings with a height ≤ 50 centimeter (cm) and a diameter at breast height (DBH) ≤ 2.5 cm were counted from 1 m*1 m quadrat. Individuals with a height ≥ 50 cm and a DBH ≥ 2.5 cm were classified as saplings and counted. The diameter and height of all woody species with a DBH ≥ 5 cm were measured in the 400 m 2 sample plots.
DBH of sampled dead wood was measured following the techniques used by 18 and 17. A complete list of woody species was made for each plot throughout the whole area and documented by local name. Species identification for common species was done in the field via different plant identification keys. However, for the less common species plant sample specimens were pressed and identified at the National Herbarium of Ethiopia, Addis Ababa University. Litter samples were collected from 1 m × 1 m subplot within the main plot. The collected fresh litter was weighed right on the site. Then the evenly mixed samples were taken to the laboratory and oven dried at 65°C for 24 hours to determine dry to fresh weight ratio. Soil samples were collected from the sub-plots used for litter sampling. Two sets of soil samples were taken, one set for the determination of organic carbon fraction (%C), and one set for the determination of soil bulk density. A total of 90 soil samples (layers of 0-30 and 30-60 cm) were collected for %C analysis using soil auger. In addition, similar size of undisturbed soil samples was collected separately for determination of soil bulk density.
Data analysis Diversity analysis. Shannon-Wiener index (H`) was used to determine diversity of woody species of the study area. H` was determined through the analysis of two components of species diversity. These are the species richness (the number of species in the sample plots) and evenness of species (abundance distribution among species).
Where pi, is the proportion of individuals found in the i th species, S is the total number of species, and ln is the natural logarithm Similarity measures are one of the most intuitive and often used methods for comparing two or more sites or samples in terms of species overlap. To compare the similarity and/or dissimilarity of NF, FFI, and FL, a percentage similarity index was calculated. This similarity index was chosen because it includes quantitative data (abundance) in its calculation, which overcomes the limitation of Sorenson's and Jaccard's similarity index, which only consider qualitative data (species list). A matrix of percent similarity index makes it easy to interpret when comparing more than three sites 19 .
Where yki is the abundance of k th species at compared land use i and ykj is the abundance of k th species at compared land use j Aboveground biomass of standing dead wood which has no leaves was estimated following the procedure used by 18. The biomass of felled dead wood was estimated using allometric equation developed by 23. The total biomass of the dead wood was estimated by summing up of the standing, logged and felled dead wood. Finally, estimated biomass of woody tree species in NF, FFI and FL were converted to carbon (C) stock using carbon fraction value of 0.5, 0.48, and 0.48 respectively 21,24 . The loss on ignition method was used to estimate percentage of organic matter in the litter. The amount of C in the litter was estimated through multiplying of litter organic matter by 0.50 25 .

Soil organic C stock estimation (SOC). Soil analyses were undertaken at Wondo Genet College of Forestry and Natural
Resources soil laboratory. The soil samples for bulk density were oven-dried at 105 °C for 48 hours. Bulk density was estimated by the core method 26 . The soil samples for %C were air -dried and analyzed using Walkley-Black method 27 . A SOC stock (Mg C ha -1 ) was determined through fixed depth method by multiplying of %C, bulk density (g/cm 3 ), soil organic C fraction (%C) and soil depth (cm)) 25,28 . % 100 Where: BD soil is soil bulk density (g/cm 3 ), %C is percent of organic C fraction, ODW is oven dry weight of soil (<2mm fraction) (g/cm 3 ), CV is soil core volume (cm 3 ), RF is mass of coarse fragments (g) = insignificant in our case, and PD is density of rock fragments (g/cm 3 ) = 2.65 g/cm 3 Total C stocks. Total C stock (Mg C ha -1 ) was calculated by summing up of biomass C stocks (above-and-below) and SOC stocks.

Statistical analysis
The stand structural parameter, diversity indices, biomass C stock and SOC stock data were described by mean and standard deviation. One-way ANOVA were performed (α = 0.05) to compare Shannon, Simpson, evenness, and C stocks among NF, FFI and FL. For SOC stock, two-way ANOVA was used since soil depth were considered as study factor together with land use types. Fisher's Least Significant Difference (LSD) post hoc test was used to compare means that demonstrated significant variations in SOC. All data were checked for normality prior to doing the analysis of variance using Kolmogorov-Smirnov test. The data were analyzed using Statistical Package for Social Science (SPSS version 20). All tests were conducted at 95% confidence level.

Woody species diversity
A total of 64, 27 and 21 woody species belonging to 37 families were recorded and identified in the sample plots of Gura-Ferda NF, FFI, and FL respectively (Table 4). Moraceae, with 29% of woody species, was the most well-represented woody species family in NF, followed by Rubiaceae (24%).
Only one or two woody species were found in the other families. The 3 rd and 4 th most abundant families were Olacaceae and Fabaceae, respectively. In FFI, the Moraceae and Meliaceae families were the most abundant woody species families, accounting for 45% and 27% of all woody species, respectively. Euphorbiaceae and Moraceae were the most abundant family in FL. The Simpson (D) and Shannon diversity index (H') value of NF is significantly higher (p=0.001) than that of FFI and FL. The D of FL was higher than that of FFI, but the difference was not significant. The H' in NF was 1.91 and 2.52 times higher than the H' of FFI and FL, respectively (Table 4). Evenness was significantly higher (p<0.05) in FL than that in NF and FFI.
The three land use types shared only 12 of the 70 woody plant species. The percent similarity index for NF with FFI, NF

C stocks
The basal area of woody species in NF ((61.02±46.51 m 2 ha -1 )) was 2.23 and 10.54 times higher than FFI (26.79 ± 12.16 m 2 ha -1 ) and FL (5.79±6.00 m 2 ha -1 ), respectively ( Where, AGBC is aboveground biomass C stocks, BGBC is belowground biomass C stocks, TBC is total biomass C stocks, SOC is soil organic C stocks and TCS is total C stocks. Different letters show significant (p<0.05) different between Land Uses, and similar letters not significance differences The mean aboveground biomass (tree/shrub, dead wood and litter) C stocks of FFI (63.4±30.46Mg C ha -1 ) are significantly lower than the adjacent NF (132.75±132.61 Mg C ha -1 ), but significantly higher than that of FL (14.16±15.05Mg C ha -1 ). The mean aboveground biomass C stocks of NF were approximately 2.1 and 9.37 times higher than FFI and FL ( Table 5). The mean overall dead wood C stock of the study area was 2.3 ± 2.84 Mg C ha -1 for NF and 5.6 ± 6 Mg C ha -1 for FFI ( Table 6). The mean litter biomass C stock for aboveground biomass was 0.66 ± 0.29 Mg C ha -1 for NF and 0.5 ± 0.19 Mg C ha -1 for FFI.
Different letters on similar soil parameters of different land uses indicate a significant difference across Land Uses (p<0.05), but similar letters do not show a significant difference across Land Uses.
A belowground biomass C stock in the NF was significantly higher (p< 0.001) than the belowground biomass C stocks of FFI and FL ( Table 5). The mean belowground biomass C stocks in the NF, FFI and FL were 25.96 ± 22.76 Mg C ha -1 , 11.46 ± 5.93 Mg C ha -1 and 2.83 ± 3 Mg C ha -1 respectively. The total biomass C stocks in NF was by 2 % and 18.5 % higher than FFI and FL. From the total biomass C, the contribution of dead wood and litter covers only 1.4% and 0.4% in NF, respectively, while, it covers about 6.9% and 0.6% in FFI. Where, AGBC is aboveground biomass C stocks, BGBC is belowground biomass C stocks, TBC is total biomass C stocks, SOC is soil organic C stocks and TCS is total C stocks. Different letters show significant (p<0.05) different between Land Uses, and similar letters not significance differences Within each land use, %C and SOC stock was significantly higher (p<0.001) in the top layer (0-30cm) than in the lower layer (36.9% and 0.6% 0-60 cm) (

Woody species diversity
The degree of human interference and disturbance caused by overexploitation of forest resources, overgrazing, the establishment of new settlements, and the conversion of forest to coffee plantation for long periods could be attributed to the variation in species composition among the NF, FFI, and FL of Gura-Ferda district. Almost all of the woody species found in the FFI and FL were not planted, but rather were left over from the conversion of the NF to the FFI and FL. The Gura-Ferda NF is floristically low when compared to other moist afromontane forests like Jibat humid Afromontane forest (183 species), Sirso moist evergreen Afromontane forest (74 species) 29 , and Bonga forest (243 species) 30 . It is, however, higher than Gendo moist afromontane forest (38 species) 31 and Gole Forest (46 species) in Kamba district, Southern Ethiopia 32 .
As shown in Table (1), FFI which emerged after the resettlement program of 1984 accounts for 23.28% of the NF within 1984-2016-year interval. As reported by 11, and 10, the main problem related to land use land cover change at Gura-Ferda district was agricultural investment, fuel wood collection, wood for house construction and farm implementation, wildfire, resettlement, land certification, poor governance within the district, and subsistence agricultural land expansion.
According to Gura-Ferda district land administration report, large areas of extra land were recorded for each farmer. The farmers had expanded their farmland into nearby forest, shrub/bush land and grass land and used those land uses for commercial crop production. Therefore, this increment of unregistered or unplanned farms and FL resulted from above mentioned drivers are the main causes for the loss of woody species diversity in the study area.
The main reason for the lower woody species diversity in FFI in relation to NF in the study area is due to the application of intensive thinning of different woody species in the system in order to reduce shading effect. 33 also reported that, managing forest for coffee production has resulted in significant changes in species diversity, composition and vegetation structure in coffee forests of southwestern Ethiopia. The number of woody species recorded in Gura-Ferda NF is comparable to the Komba-Daga moist evergreen forest in southwestern Ethiopia (62 woody species) 34 . For instance, the number of woody species recorded in the Gura-Ferda NF of the current study area is substantially higher than those reported for Agama tropical Afromontane forest of Ethiopia (39 woody species) 35 . However, the number of woody species in the current studied NF is lower than the woody species recorded for Wondo Genet Afromontane forest in the central highlands of Ethiopia (72 woody species) 36 .
Our results also indicated that, the woody species richness in FFI of the current study is comparatively lower than woody of species in agroforestry system of south-central and southern highlands of Ethiopia 37,38 . Since maximizing coffee production is the main goal, most of the native trees have been cleared by cultivators and few shade plant species are retained in highly populated coffee shrubs.

C stocks
The study showed how C stocks in biomass and soils were varied across different land use systems. NF had higher biomass C stocks compared to FFI and that of the FL. 39 and 40 reported higher biomass C in forest land use system as compared to other land cover types in northwestern Himalaya and northern Ethiopia, respectively. From the studied land use systems of this area, most of the C was stocked in NF. The accumulation of high C stock in NF was attributed by the presence of diversified woody species in the NF in comparison with FFI and FL. Additionally, the NF has found to accumulate larger aboveground biomass in the litter compared with that of FFI. This result is in line with the result of 40 which stated that tree density, diversity and diameter have an effect on biomass C.
Case studies have showed as different land use systems stocked different amounts of C in their biomass component. Accordingly, the biomass C stocks recorded in the NF of the current study area is substantially lower than the biomass C stocks of Adaba-Dodola community forest, southeastern Ethiopia 41 . The biomass C stocks of NF of the current study area was approximately three times lower than the biomass C stocks reported for woody plants of Mount Zequalla Monastery in Ethiopia 42 . Similarly, the biomass C stocks of FFI in this study was higher than that of the coffee based agroforestry system in Gera, Jimma Zone, South-West Ethiopia 43 . The difference in biomass C stocks might be due to various factors such as difference in diversity of trees (woody and non woody) of larger sizes, the used allometric equation, soil condition and climate factors. For instance, in the coffee based agroforestry system studied by 43, trees aboveground biomass was determined using 44 allometric equations. But, for this study, the generic equation developed by 20 and 21 were used for woody tree species. The biomass C stocks of the FFI of the current study area was relatively equivalent with the total biomass C stocks of fruit coffee system of indigenous agroforestry systems of the south-eastern Rift Valley escarpment, Ethiopia 45 .
The average mean above ground biomass C stock of the FFI was higher than the mean biomass C stocks of organic polyculture coffee, non-organic polyculture coffee and organic Inga species in Chiapas, Mexico 46 . The variability among these systems in this respect might be because of differences in species composition, site characteristics, management practices, land holding sizes, ancillary factors (e.g. soil condition, climate, system age, land-use history), and adopted allometric model for biomass estimation 47 .

Conclusion
FFI in the southwestern part of Ethiopia plays an important role in maintaining more woody species and sinks of C. The higher contribution of NF to climate change mitigation is mainly due to the higher diversity and density of larger woody species in the system as compared to the adjacent FFI and FL. Trees in particular play substantial roles for enhancing biomass C stocks in forests and any other land use systems. However, the increment of FL found adjacent to the NF and FFI showed a lower role of biodiversity conservation and C stock. This shows that sustainability of the system is questionable. If the NF is not sustainably managed and certification of land is not carried out in the area, there will be expansion of FFI and FL which will cause further deforestation and forest degradation. Therefore, it needs to recognize FFI as part of climate change mitigation strategies, as it can also provide much benefit to the community and a potential to reduce pressure on adjacent NF. The quantified C stocks would be beneficial to Ethiopia's economy and environment, encouraging the country to contribute even more to global warming mitigation while also providing income. The estimated C sequestration potentials of NF, FFI, and FL along the natural forest to farmland conversion gradient will necessitate the implementation of sustainable strategies, collaboration among actors, and promotion of best sustainable land management practices in order to improve marketing channels and institutional settings for effective C trading.

Girma Shumi
Social-ecological Systems Institute (SESI), Faculty of Sustainability, Leuphana University, Lüneburg, Germany I read the manuscript carefully, and appreciate authors attempt to integrate ecological and GIS skills for analyzing the change in woody plant diversity and carbon sequestration potential in Gura-Ferda moist evergreen Afromontane forest. Nevertheless, the manuscript has many limitations to be considered for indexing, see my comments under each specific section below.
Title "Conversion of natural forests to farmlands and its associated woody species diversity and carbon stocks in a span of 33 years (1984 to 2016): in the case of southwestern Ethiopia"-it is not fit with or well represent the contents of the manuscript. The inconsistency can be illustrated, for example, from: The title reads "Conversion of natural forests to farmlands", but in the text starting from introduction up to the conclusion, the authors deal with Forest land use, forest farm interface land use and farmland use, although forest farm interface land use is not yet known in Ethiopia and elsewhere in the world.
○ Again, the title reads "its associated woody species diversity and carbon stocks in a span of 33 years (1984 to 2016)", but the authors analyse the current woody species diversity and carbon stocks across land use gradients, i.e. not change of species and carbon stock in a span of 33 years (from 1984 to 2016). The authors did not conduct any analysis that shows woody plant species and carbon stocks change across the land use gradients (the change could be positive (e.g. species gain or native species conservation) or negative (e.g. loss of species)) within specified period of time. Second, what is forest farm interface land use? Is it degraded forest or agroforestry system or what? Somewhere in the text (I think in the discussion section), is treated as coffee management system, authors can use it for stratifying the study site (as they did it in methods section), but as to me it is confusing to use it as a land use. I suggest you find other universally known or acceptable term, at least from Ethiopian perspective. For study area stratification, it is okay to use "forest farm interface" ○ Third, the authors did not conduct analysis that show or revealed changes in species diversity and carbon stocks across the land-use gradients; See your methods and results and other related studies. Off course, you did land cover change analysis but not woody plant species and carbon stocks change (see my comment above also).
○ Thus, these need attention and clarification to improve the abstract and its conclusion.

Introduction
The introduction is hard to follow and to identify research gap/s. b) In the introduction, the authors stated that "Ethiopia's ecosystem is diverse, ranging from the dry lowlands in the east to the high altitudes of the central highlands (Hurni, 1998). The country's unique ecological conditions, as well as its rich flora and fauna, have made it one of the most important biodiversity hotspots on the world", I suggest getting out of such notions, especially in higher education system of Ethiopia, as we are in era of Anthropocene and those kind of approaches are misleading biodiversity conservation and land management practices. E.g. see Jackson and Sax (2010): Balancing biodiversity in a changing environment: extinction debt, immigration credit and species turnover 2 . c) After introducing southwestern biodiverse forest, the authors stated "Similarly, other remaining natural forests have also been threatened by pressure from investors and changed to industrial plantation like coffee and tea", this breaks the flow of idea. As far as the study is conducted in southwestern Ethiopia, I would suggest if the narratives of introduction could start with global aspects of biodiversity loss, then, in Ethiopia, and finally specific in southwestern Ethiopia. d) Then, they wrote "This reduction and conversion of natural forest to other land use systems in many parts of Ethiopia has led to the decline in number and distribution of many plant species, shortage of raw materials for wood processing industries and disturbance of ecosystem services 6 . As a consequence, forest farm interface has expanded within and around the natural forest.
Subsequently, it has resulted the expansion of forest farm interface in and around the forest ecosystem.", here, one can ask or raise concerns such as: A contradicting arguments, loss of species at local or landscape level in southwestern Ethiopia (or ???) and lack of raw materials for industries -large plantation or advocating for land use intensification.
○ I do not think that the cited reference (6) is the correct one here.  e) The authors stated: "Hundreds of aid projects have been implemented in different parts of the country to reverse deforestation and forest degradation in the country. However, the success stories were below expectations and the problems are still immense. This resulted from the lack of effective management practices and quantification of the available forest resources. This insufficiency of scientific quantitative data brought lack of responsiveness for sound management of natural resources in the country.". According to these statements, the problem of biodiversity loss is not land use change (i.e. deforestation, forest degradation and agricultural intensification), rather it is lack of monitoring of restoration, and existing forest management in the country. I suggest to clearly focus on what to be studied in the region.
f) What is the need of bringing "Gura-Ferda forest is one of the Afromontane rainforests in the southwestern region of Ethiopia and grows at altitudes from 700 to 2,300 meter above sea level." into introduction? Better to take it to methods section.
g) The reason why the authors analyze the woody species diversity and carbon stock change in Gura-ferda forest (i.e. the research gap/s) is not indicated or stated clearly. Specifically, why carbon stock? The hypothesis is also weak or, obvious, i.e. change in woody plant species diversity and carbon stock from forest to degraded forest and then, to farmland is obvious, so what makes their hypothesis unique?

Materials and methods
1) If I am not mistaken Gura-Ferda district is situated in Bench-Majii zone, in SNNP region, I do not know why the authors afraid to mention this give clear information of about their study area.
2) I suggest taking " Table 1" under methodology. 3) Under methodology, instead of "Data source", I suggest land use mapping and stratification of study area". Then, remove " Table 2 f) I suggest taking "Where, AGBC is aboveground biomass C stocks, BGBC is belowground biomass C stocks, TBC is total biomass C stocks, SOC is soil organic C stocks and TCS is total C stocks. Different letters show significant (p<0.05) different between Land Uses, and similar letters not significance differences" to " Table 5" caption. g) Again, "Different letters on similar soil parameters of different land uses indicate a significant difference across Land Uses (p<0.05), but similar letters do not show a significant difference across Land Uses." to " Table 6".
h) Take "The total C stock of the study area was calculated by summing up all the C value of each pool." to the methods section.

Discussions
1) The discussion opened by statement: "The degree of human interference and disturbance caused by overexploitation of forest resources, overgrazing, the establishment of new settlements, and the conversion of forest to coffee plantation for long periods could be attributed to the variation in species composition among the NF, FFI, and FL of Gura-Ferda district. Almost all of the woody species found in the FFI and FL were not planted, but rather were left over from the conversion of the NF to the FFI and FL.". What about species adaptation to different environment or land uses? See my comment above.
2) It is not clear why the authors compare this forest, "moist evergreen Afromontane forest" with Jibat humid Afromontane forest, "Dry Afromontane forest". The same with Gendo moist afromontane forest, Gole Forest, and Wondo Genet Afromontane forest. Here, not only the biophysical conditions of the forests, but also the methods used by matters. Maybe check this?
3) The authors said "As shown in Table (1), FFI which emerged after the resettlement program of 1984 accounts for 23.28% of the NF within 1984-2016-year interval. As reported by 11, and 10, the main problem related to land use land cover change at Gura-Ferda district was agricultural investment, fuel wood collection, wood for house construction and farm implementation, wildfire, resettlement, land certification, poor governance within the district, and subsistence agricultural land expansion.", here, they want to discuss species diversity change -forest degradation or land cover change? How does land certification and poor governance within the district affect land cover change? 4) While their analysis did not quantify species loss, why the authors reported species loss in "Therefore, this increment of unregistered or unplanned farms and FL resulted from above mentioned drivers are the main causes for the loss of woody species diversity in the study area.", is not clear.

5)
Why are farmers blamed here? Alternatively, are they investors? Very contradicting statement "According to Gura-Ferda district land administration report, large areas of extra land were recorded for each farmer. The farmers had expanded their farmland into nearby forest, shrub/bush land and grass land and used those land uses for commercial crop production." 6) Is there coffee management systems in the area? If so, I suggest to discuss or brining in this issue in the introduction also.
7) The discussion on carbon stocks also needs attention, including justification -clearly stating problem statement in the introduction for conducting carbon stock study in the area.

Conclusion
Authors suggest the needs for land use certification for the system to be sustainable, i.e. "If the NF is not sustainably managed and certification of land is not carried out in the area, there will be expansion of FFI and FL which will cause further deforestation and forest degradation.". But, in Ethiopia, particularly in southwestern Ethiopia, land use certification did not guarantee land tenure security and biodiversity conservation. See my paper Shumi et al. (2019a): Woody plant use and management in relation to property rights: a social-ecological case study from southwestern Ethiopia 4 .
The authors call for landscape commodification than biodiversity conservation. As I read it from the manuscript, although not yet clearly stated, carbon stock assessment for landscape commodification seems to be the main essence of this study. In emerging social-ecological system research, however, researchers in this field argued that landscape commodification or marketing has an impact on both the ecosystem services (biodiversity protection) and human, particularly local people well-being, for example, see Go´mez-Baggethun and Naredo (2015)

Mulugeta Betemariyam
Dear Sigit D. Sasmito We are grateful for insightful and constructive comments on our manuscript, "Conversion of natural forests to farmlands and associated woody species diversity and carbon stocks in southwestern Ethiopia during 33 years (1984 to 2016)." We have attempted to address all comments in this revised manuscript and believe that the manuscript, especially the language, has substantially improved. Track changes for changes made to the original version were added to the page where specific changes were required. Our responses to the specific comments are presented below.
I have a few suggestions below which may be used to improve the current manuscript.

I'd suggest providing carbon stocks value across land-use change in the abstract's result section
Thank you for your comments; the carbon stock values have been added to the revised manuscript abstract.

I'd drop the current first paragraph in the intro. It is too broad and you have to be direct to the Ethiopia case.
Thank you for your constructive comment. We kindly revised accordingly.
○ Some references may be needed for the following statement "For the past five decades, the government of Ethiopia has attempted to reforest degraded forests." and other few next sentences in this paragraph. Thanks for the information; the suggested paragraph for removal from the introduction section has been removed. Thank you for sharing us with the sources from which we can obtain additional information. In this study, we employed the fixed depth method to determine the soil organic carbon. As stated in the results section, there was no significant variation in bulk density among the land uses. The estimation of soil organic carbon by employing fixed depth is recommended by authors who were cited in our paper method section if the bulk density is not indicated as a significant difference.

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In the conclusion section, I'd suggest adding a few sentences describing how your study could support current literature on this topic and carbon monitoring in the context of climate change mitigation strategy in Ethiopia.
Thank you for your suggestion. We include a statement in the conclusion section outlining how our research could contribute to current literature on the issue and carbon monitoring in the context of Ethiopia's climate change mitigation strategy.
○ structure and biomass using structural equation models or multiple linear mixed effect models. Otherwise, it is hard to understand results and hence hard to get right conclusions.
In the statistical analysis section, we apologize for not explicitly expressing which types of statistical tests we utilized for the investigated parameters. We explicitly detailed how we test parameters in the revised manuscript. On comparison, the authors agreed that differences in sample sizes (plot size) affect carbon stocks, species richness, and structure. However, even if the sample size (plot size) for Farmland and other land uses for which comparison was made (NF, FFI) were different, the authors reached the comparison result after the individual plot size for each land use was converted to Ha (hectare) base, which the ANOVA can do for statistical differences. So, after similarizing the unit (ha) for each land use, we compared carbon stocks, diversity indices, and structural parameters among the three land uses following the ANOVA procedures.