Round 1

Reviewer 1 Report

I enjoyed reading your paper. Based on the GLASS dataset, the vegetation change of The Three-North Shelter Forest from 1982 to 2018 was analyzed, and the contribution of climate change and human activities to vegetation change was quantified through residual analysis. This article is detailed and can provide reference data and technical support for the ecological engineering evaluation of the study area in the future.

I would suggest including the following aspects to the paper while revising it:

1. In the overview of the study area, please supplement the climatic characteristics of the study area appropriately. Figure 1b is not mentioned here. Please introduce the vegetation distribution and vegetation types.

2. Lines120-121, temperature (the template spline function method) and precipitation (the kriging interpolation method) data use different interpolation methods. What is the purpose of this?

3. Lines 187-188, it is recommended to give the specific value of the division

4.Lines 202-204, here some place names cannot be compared in the study area map, it is recommended to mark all the area names appearing in the article in the study area map, or modify the expression

5. The conclusion part needs to be strengthened, and the spatial change of vegetation coverage needs to be further described; the analysis results of vegetation response to climate change need to be supplemented; lines 332-336 are more like the content of the discussion and need to be summarized.

Author Response

# Reviewer 1:

I enjoyed reading your paper. Based on the GLASS dataset, the vegetation change of The Three-North Shelter Forest from 1982 to 2018 was analyzed, and the contribution of climate change and human activities to vegetation change was quantified through residual analysis. This article is detailed and can provide reference data and technical support for the ecological engineering evaluation of the study area in the future.

 

I would suggest including the following aspects to the paper while revising it:

Point 1: In the overview of the study area, please supplement the climatic characteristics of the study area appropriately. Figure 1b is not mentioned here. Please introduce the vegetation distribution and vegetation types.

Response 1: Figure 1b has been revised, and relevant content has been added in lines 108-118

“Annual cumulative precipitation shows a decreasing pattern from south to north and from east to west. Majority of the study area has an annual mean air temperature ranging from 2°C to 11°C. The primary land coverage is desert and sandy land, while meadow vegetation is mainly distributed in Inner Mongolia, Gansu, Qinghai, and Xinjiang. Culti-vated vegetation is mostly located in the eastern portion of the study area, scarely in the Tianshan Mountains and Jungar Basin in Xinjiang. Forest and shrub clumps are primari-ly found in the middle and south temperate zones, growing in areas such as the Greater Khingan Mountains, Taihang Mountains, Qinling Mountains, Tianshan Mountains, and Altai Mountains. Alpine vegetation occurs mainly in the Kunlun Mountains region (Figure 1b).”

 

Point 2:  Lines120-121, temperature (the template spline function method) and precipitation (the kriging interpolation method) data use different interpolation methods. What is the purpose of this?

Response 2: In Section 2.2 of the revised draft, we added reasons for choosing the climate interpolation method for temperature and precipitation, and described the data processing process.

“Accuracy of spatial interpolation of the meteorological data is affected by two primary factors: spatial distribution of meteorological stations and spatial interpolation method of data. Air temperature and precipitation data were collected from 217 meteorological sta-tions over the TNSFP region, which were evenly distributed. For interpolation of the pre-cipitation data, the commonly used Inverse Distance Weighted(IDW) and Kriging meth-ods were used in northern China[25][26], After comparing their accuracies, the Kriging method was selected for sole use in this study. On the other hand, air temperature is closely related to altitude or topography[27]. Thus the ANUSPLINE interpolation method that incorporates altitude as a covariate was chosen for the spatial interpolation of air temperature data[28]. The spatial resolution of the interpolated meteorological data was standardized to 5000 × 5000 m.”

 

Point 3：Lines 187-188, it is recommended to give the specific value of the division

Response 3: We have added the specific values of the division in line 220-224. “we divided the FVC into extremely low(<0.1), low(0.1~0.29), medium(0.3~0.49), high(0.5~0.69), and extremely high(> 0.7) conforming with the desertification standard specified in Land Desertification Monitoring Method of the People’s Republic of China.”

Point 4：Lines 202-204, here some place names cannot be compared in the study area map, it is recommended to mark all the area names appearing in the article in the study area map, or modify the expression

Response 4: In order to accurately depict the geographical location of the study area, Figure 1 has been revised to include all provincial administrative regions and their respective provincial capitals, while retaining the names of significant mountains, rivers, and lakes.

 

Point 5：The conclusion part needs to be strengthened, and the spatial change of vegetation coverage needs to be further described; the analysis results of vegetation response to climate change need to be supplemented; lines 332-336 are more like the content of the discussion and need to be summarized.

Response 5:

We have revised the Conclusions section as below:

The interannual spatial-temporal change of the FVC in the TNSF region from 1982 to 2018 were analyzed, and the main driving factors were identified, which sparked a new insight into the regional FVC increase or decrease and the underlining cause. Results showed that the FVC in the TNSF region of China showed a spatial distribution pattern of increasing from the west to the east. Spatially, the FVC was significantly improved, and the multi-year average value showed a growing trend. The implementation of six nation-al-level ecological governance projects had a positive impact, and anthropogenic activities were found to significantly contribute to the FVC improvement in 46.81% of the TNSFP re-gion. The greater the number of ecological projects were implemented, the greater the areal proportion of FVC improvement was found. Climate change affects the effectiveness of ecological governance projects to a certain degree. A warm and humid climate is more conducive to the FVC increase than a warm and dry climate. Ecological governance pro-jects implemented in areas with an annual cumulative precipitation above 300mm are more effective than those implemented in areas with less precipitation. Regional water resource capacity should be considered when implementing any ecological governance in low-precipitation areas. It is expected that world-wide ecological restoration projects should be continuously encouraged to ensure sustainable vegetation improvement if the synergy between climate change and anthropogenic activities is considered.

 

In Section 3.1, the description of spatial changes in vegetation cover has been added, and an analysis of the FVC variation coefficient and future change trend during 1982-2018 has been supplemented.

Results of the variation coefficient analysis showed an average value of 0.3, indicating a strong fluctuation of vegetation in the TNSFP region. The spatial distribution of vegetated area with extreme stability was found to be congruent with the areas of high vegetation coverage, accounting for 37.22% in area and primarily composed of cultivated vegetation, shrub, and forest covers (Figure 3a). The proportion of areas with high stability was 30.86%, mostly located in Inner Mongolia, Shaanxi, Ningxia, Gansu, and Xinjiang, encompassing most of the meadow regions in the study area. Meadows lands exhibiting strong stability were predominantly located in the high-altitude region of the Qilian Mountains, Tianshan Mountains, and Altai Mountains. The coefficients of variation of other land types accounted for about 10% each (Figure 4a).

The mean value of the Hurst index was found to be 0.73, indicating that the trend of the FVC variation in the TNSFP region over the past 37 years is likely to persist. By combining the results of the Hurst index and Theil-Sen trend analysis, we determined the future trend of FVC in the study area. Results showed that 69% of the areadisplayed a trend of continuous improvement in FVC, with a distribution range similar to that of the significant improvement area (Figure 3b). About 28% of the area displayed a continuous degradation trend, These areas are concentrated in central and northern Inner Mongolia, in Beijing and Tianjin, with sporadic occurrences in other regions (Figure 4b). In the future, it is expected that only 1% and 2% of the region will show degradation and improvement in FVC, respectively, with no centralized distribution (Figure 4b).

 

Figure 4. Distribution map of FVC stability(a) and future change trend(b) in the study area

 

We have analyzed the relationships between vegetation types and climate in the study area in Section 3.3 of the manuscript.

“The partial correlation between the FVC of cultivated vegetation, shrubs, and forests and climate factors was significant and positive, while the correlation between the FVC of meadows and temperature varied by region. The relationship between the FVC of mead-ows lands and climate factors was mostly insignificant in Xinjiang, while in Inner Mon-golia, the FVC of most of the meadows lands were negatively or significantly negatively correlated with the temperature. In contrast, the FVC of meadows lands in the Qilian Mountains displayed a significantly positive correlation with the temperature (Figure 6a).”

" Vegetation growth in the northwestern part of the study area was generally limited by in-sufficient precipitation, and the cultivated vegetation and meadows in the Hulun Lake area of Inner Mongolia and the Loess Plateau responded most strongly to precipitation, showing a significant positive correlation[19]. In the east and south areas with abundant precipitation, however, excessive rainy days was not conducive to plant photosynthesis [30], and consequently, there was no significant correlation between cultivated vegetation and precipitation (Figure 6b)."

Author Response File: Author Response.pdf

Reviewer 2 Report

The topic of the paper is good but shows no innovation, this work is very simple and done across the world many a time, this is not a significant publication for a journal like Remote Sensing.

Simple time series doesn't have much value therefore needs to see the time series using several other models

 

Author Response

# Reviewer 2:

Point 1: The topic of the paper is good but shows no innovation, this work is very simple and done across the world many a time, this is not a significant publication for a journal like Remote Sensing.

Simple time series doesn't have much value therefore needs to see the time series using several other models

Response 1: This research utilized the GLASS AVHRR FVC data, meteorological data, and spatial distribution of ecological engineering to analyze spatiotemporal variation of FVC and climate in the TNSF program region of China during 1982-2018. In this revised version, we have added an analysis of the coefficient of variation and future trends of vegetation change. We also revised the sections of Abstract and Conclusions and rewritten the Discussion section.

Author Response File: Author Response.docx

Reviewer 3 Report

 

 The Three-North Shelter Forest (TNSF) region is an important ecological zone in Northern China. The authors in this paper investigated the spatial and temporal patterns of Fraction Vegetation Cover (FVC) as impacted by climate, anthropogenic management, and a combination thereof.

The paper can contribute to our understanding of the pattern of vegetation dynamics as it responds to climate and management. However, the paper is not ready for publication in its current form.

The paper needs basic information about the TNSF, and the management practices or anthropogenic practices that the authors refer to, how did these spatially and temporarily change over time. The results associated with the relative contribution of climate vs management don’t mean much because we don’t know what these anthropogenic management are and how they are distributed spatially and temporally. For instance, if planting was happening in the eastern more humid areas than the western drier areas, then by default FVC is going to be higher in the east, but without running the analysis on per management practice * climate, it will be difficult to separate the cause from the effect, all we have is correlations. These analysis need to happen address goal 3 of the paper.

The paper also needs some editing for English especially the introduction. The discussion is brief and in large a repetition of the results. The discussion needs to be restructured to address the goals that were presented in the paper.

Author Response

Point 1: The paper needs basic information about the TNSF, and the management practices or anthropogenic practices that the authors refer to, how did these spatially and temporarily change over time. The results associated with the relative contribution of climate vs management don’t mean much because we don’t know what these anthropogenic managements are and how they are distributed spatially and temporally. For instance, if planting was happening in the eastern more humid areas than the western drier areas, then by default FVC is going to be higher in the east, but without running the analysis on per management practice * climate, it will be difficult to separate the cause from the effect, all we have is correlations. These analysis need to happen address goal 3 of the paper.

Response 1: Six major national ecological projects have been executed within the framework of the Three-North Shelterbelt Project. However, these efforts were characterized by inconsistent initiation times, varying durations, and overlapping geographical coverage, making it challenging to accurately map the extent of their implementation. Furthermore, the reported planting area does not necessarily guarantee the survival of all vegetation. To conduct quantitative analysis of effects by each ecological project, a significant amount of field data is required. Unfortunately, such data were not available for this study. As a result, we could not isolate the impact of each ecological project.

In an attempt to assess the extent of implementation of the six major ecological projects, we collected relevant data and created Figure 6. Then the relative contribution of human activities to climate change during the study period was estimated through residual analysis. Finally, the objective 3 was re-evaluated based on the overlaid implementation scope.

 

Point 2: The paper also needs some editing for English especially the introduction. The discussion is brief and in large a repetition of the results. The discussion needs to be restructured to address the goals that were presented in the paper.

Response 2: Thanks to the reviewer’s suggestion, we modified the structure of the paper and processed the newly collected data to get Figure 7 and Table 1. On this basis, sections 4.1 and 4.2 were added.

4.1 Implementation Effect of Ecological Governance

In the past 44 years, the Chinese government has implemented six major ecological governance programs in the TNSFP region(Figure 7), including the Three-North Shelter Forest Development Program, the Beijing-Tianjin Sand Source Control Program (BSSCP), the Nature Forest Conservation Program (NFCP), the Sanjiangyuan Ecological Protection and Construction Program (SEPCP), the Grazing to Grassland Program (GTGP), and the Grain to Green Program (GTGP). One of the goals of these programs are to improve vege-tation coverage. To achieve the goals of these programs across multiple areas, the govern-ment has adopted a phased approach and has maintained long-term substantial invest-ment in ecological governance[7]. The Three-North Shelter Forest Program, initiated in 1978, was the first significant program carried out[35]. Over the past 40 years, a total area of 317,400 km2 of forest has been preserved and afforested, providing valuable experience and technology for future large-scale ecological governance programs that began around 2000 [36]. Additional information on these programs can be found in the relevant litera-ture [37][38][39][40][41].

Figure 7. Locations of the Quantity of Ecological Governance Projects

A minimum of three ecological improvement projects have been executed in 80% of the county-level administrative regions. Regions with implementation of 4-5 governance engineering projects are the focus of governance and are located in the Greater Hinggan Mountains, the western part of Inner Mongolia, the Loess Plateau, the Qilian Mountains, the Sanjiangyuan and the Tian Shan, Altai Mountains and Kunlun Mountains in Xinjiang. The more ecological engineering projects were implemented in the region and the more the comprehensive of the governance measures were, the more obvious the trend of im-proving vegetation coverage were observed. However, with an increase in governance projects, the proportion of areas where anthropogenic activities significantly increased FVC showed a decreasing trend, which indicated that the governance of focus areas was extremely challenging. Furthermore, the increase in surface vegetation coverage is strongly correlated with the capital investment in ecological engineering [7][41].

Table 1 The proportion of different types of driving factors in the ecological superposition area

spatial pattern types	2 Program	3 Program	4 Program	5 Program
CCSFD	2.07%	1.50%	2.45%	1.84%
CFSFD	0.75%	0.51%	0.71%	0.78%
AASFD	6.67%	4.70%	4.28%	0.52%
CCSD	4.74%	2.41%	1.06%	0.80%
CFSD	1.07%	0.92%	0.36%	0.33%
AASD	1.99%	5.26%	2.30%	0.97%
AASI	2.82%	7.24%	7.00%	4.84%
CFSI	0.59%	1.38%	1.46%	1.18%
CCSI	1.26%	3.88%	5.02%	3.85%
AASFI	63.55%	47.99%	41.75%	29.57%
CFSFI	4.57%	10.88%	14.30%	29.33%
CCSFI	9.92%	13.32%	19.32%	26.00%

Note: (CCSFI)Climate Change lnduced Significant Increase, (CFSFI)Comperhensive Factors Induced Significant Increase, (AASFI)Anthropogenic Activies Induced Significant Increase, (CCSI)Climate Change lnduced Slight Increase, (CFSI)Comperhensive Factors Induced Slight Increase, (AASI)Anthropogenic Activies Induced Slight Increase, (CCSD)Climate Change induced Slight Decrease, (CFSD)Comperhensive Factors Induced Slight Decrease, (AASD)Anthropogenic  Activies Induced Slight Decrease, (CCSFD)Climate Change Induced Significant Decrease, (CFSFD) Comperhensive Factors Induced Significant Decrease, (AASFD)Anthropogenic Activies Induced Significant Decrease

 

4.2 Effects of Climate Change and Anthropogenic Activities on FVC Variation

The relative contributions of climatic factors and anthropogenic activities to the FVC in the TNSFP region were calculated based on residual analysis results. In this research, the contribution rate greater than 55% were defined as the driving factors of climate changes or anthropogenic activities, and 45%-55% were defined as comprehensive driving factors. Moreover, relative contributions and FVC variation trend types were superposed to acquire 12 driving types, aiming to intuitively distinguish the spatial distribution of cli-mate changes and anthropogenic activities-driven FVC in the TNSFP region since 1982(Figure 8). Results indicated that vegetation increased in 86.4% of the TNSFP region, with 74.86% of these areas showing a significant increase(Table 2). Areas with a significant increase in vegetation driven by anthropogenic activities were the most widely dis-tributed (about 46.81% of the total area).

Figure 8 Spatial pattern of the effect of climate change and anthropogenic activities on the vegetation dynamics in TNSFP region. spatial pattern types: (CCSFI)Climate Change lnduced Significant Increase, (CFSFI)Comperhensive Factors Induced Significant Increase, (AASFI)Anthropogenic Activies Induced Significant Increase, (CCSI)Climate Change lnduced Slight Increase, (CFSI)Comperhensive Factors Induced Slight Increase, (AASI)Anthropogenic Activies Induced Slight Increase, (CCSD)Climate Change induced Slight Decrease, (CFSD)Comperhensive Factors Induced Slight Decrease, (AASD)Anthropogenic Activies Induced Slight Decrease, (CCSFD)Climate Change Induced Significant Decrease, (CFSFD) Comperhensive Factors Induced Significant Decrease, (AASFD)Anthropogenic Activies Induced Significant Decrease

 

From a spatial distribution perspective, governance engineering has performed well in the northeastern plains, Loess Plateau, and some areas of Xinjiang(Figure 7). The effect is closely tied to the distribution of climate patterns[9][42]. The significant increase in the vegetation coverage driven by anthropogenic activities and is also closely related to the distribution of climatic patterns, indicating a synergy between the climate change and anthropogenic actions. In the northeastern plains and Loess Plateau, there are generally 2 to 3 governance projects, and areas with significant increase in vegetation coverage are mainly located in regions with more than 300mm of precipitation. Adequate rainfall supports the effectiveness of tree planting, reforestation, and grassland protection [7]. In Xinjiang, where the annual precipitation is far less than 300mm, the growth of vegetation mainly depends on the water source from snow and ice melting [43][44]. At the same time, temperature and precipitation in the region are increasing, and the ecological governance of the warm and moist climate has achieved good results [7][45]. Three ecological gov-ernance projects have been implemented in the central and northern part of Inner Mongo-lia, but the implementation effect was poorer. This is mainly due to the obvious decrease in precipitation, while the temperature showed a rising trend, Therefore, the warm and dry climate has led to possible degradation trend of FVC in parts of Inner Mongolia [46], which has increased the challenge of ecological governance [47]. In addition, as the grass-lands being most extensively distributed in China, overgrazing by the animal husbandry may have also caused degradation of grasslands [48].

In the future, implementation of new ecological governance projects in the TNSFP region should take into account the regional climate pattern. Large-scale ecological governance in areas with annual cumulative precipitation less than 300 mm may not suitable effective [40]. Area such as Xinjiang that have achieved positive results, but excessive planting of trees and grass and increased cultivation of vegetation may accelerate consumption of water resources and may cause water shortage [49][50][51]. Implementation of any ecological governance in areas with precipitation above 300mm may benefit from previous experience in gaining the greatest ecological outcomes.

 

Table2  Driving factors of FVC and its proportion

Types of drving factors	Proportion(%)	Types of drving factors	Proportion (%)
Climate Change lnduced Significant Increase(CCSFI)	15.58	Climate Change Induced Significant Decrease(CCSFD)	1.88
Comperhensive Factors Induced Significant Increase(CFSFI)	12.47	Comperhensive Factors Induced Significant Decrease(CFSFD)	0.62
Anthropogenic  Activies Induced Significant Increase(AASFI)	46.81	Anthropogenic  Activies Induced Significant Decrease(AASFD)	4.53
Climate Change lnduced Slight Increase(CCSI)	3.85	Climate Change induced Slight Decrease(CCSD)	2.20
Comperhensive Factors Induced Slight Increase(CFSI)	1.29	Comperhensive Factors Induced Slight Decrease(CFSD)	0.73
Anthropogenic  Activies Induced Slight Increase(AASI)	6.40	Anthropogenic  Activies Induced Slight Decrease(AASD)	3.64

Author Response File: Author Response.docx

Round 2

Reviewer 3 Report

Authors addressed the comments. There are minor editorial errors that can be checked prior to publication.

Author Response

Thanks for your suggestion, we have checked the paper again.