Afforestation Projects Research Articles

Evaluation and Prediction of Ecological Benefits in Song-Liao River Basin

The evaluation and prediction of ecological benefits are significant for regional resource development planning and path designing. This study established a novel ecological benefits evaluation system by integrating macro-ecosystem structure, Ecosystem service index (ESI), and ecological quality index (EQI). Based on this system, this study evaluated the spatiotemporal characteristics and changing trend of ecological benefits in Song-Liao River Basin (SRB) from 1990 to 2020. The results show that the macro-ecosystem structure in Song-Liao River Basin remains stable, and the ecosystem service and ecological quality generally show a trend of first decline and then increase. The average growth rates of ESI and EQI were 0.6% and 0.4%, respectively, during 1990–2020. The ecological benefits of natural areas with widely distributed forest areas are higher, while those of areas with frequent human activities are lower. The prediction model based on machine learning has achieved good modeling effect, which shows that the ecological benefits of SRB will be on the rise in the future. Based on the evaluation results, we suggest that more environmental protection policies on the basis of maintaining the existing development plan should be promoted to reduce the contradiction between human and nature in the development process. For the abundant natural forests in this area, reasonable forest management should be carried out to improve the carbon-fixation capacity of vegetation, and a Methodology for managing natural forests should be constructed to make full use of the existing carbon sinks. For the new afforestation project being promoted, carbon-sink afforestation projects of CCER (Chinese Certified Emission Reduction) should be promoted to realize the synergy between economic development and environmental protection.

Strong nestedness and turnover effects on stand productivity in a long-term forest biodiversity experiment.

Multispecies planting is an important approach to deliver ecosystem functions in afforestation projects. However, the importance of species richness vs specific species composition in this context remains unresolved. To estimate species or functional group richness and compositional change between two communities, we calculated nestedness, where one community contains a subset of the species of another, and turnover, where two communities differ in species composition but not in species richness. We evaluated the effects of species/functional group nestedness and turnover on stand productivity using 315 mixed plots from a pool of 40 tree species in a large forest biodiversity experiment in subtropical China. We found that the greater the differences in species or functional group nestedness and turnover, the greater the differences in stand productivity between plots. Additionally, the strong effects of both nestedness and turnover on stand productivity developed over the 11-yr observation period. Our results indicate that selection of specific tree species is as important as planting a large number of species to support the productivity function of forests. Furthermore, the selection of specific tree species should be based on functionality, because beneficial effects of functional group composition were stronger than those of species composition.

Estimating afforestation related forest cover change using data fusion and machine learning

Abstract Climate change threatens natural ecosystems, including biodiversity, and has emerged as the greatest challenge to human well-being. To support sustainable forest use, it is important to accurately map the distribution of afforestation and how the forests have changed over time. Climate change is affected by land use and land cover (LULC) since it alters biogeochemical cycles. Pakistan's declining forest cover has motivated policymakers to undertake the Green Growth Initiative (GGI). In accordance with its commitment to the Bonn Challenge, Pakistan executed the Billion Tree Afforestation Project (BTAP) to restore forests covering approxi-mately 0.35 million Ha. To estimate forest cover mapping accuracy, we developed a novel method to combine Sentinel-1, Sentinel-2 data, and vegetation indices to assess forest cover change. The methods and models were used to create forest maps for the period of 2016 to 2022. The optimal mapping approach was chosen after classifying the land cover using two machine learning-based classifiers: random forests (RF) and support vector machines (SVM). Finally, the spatiotemporal distribution of the changes induced by afforestation was generated. Based on the classifications of land cover, forest and non-forest identification was carried out. The results show that RF produces more accurate results, with kappa coefficient of 94-97% & 0.93-0.96 respectively. The classification accuracy and Kappa coefficient of the SVM model ranges from 92-94% & 0.91-0.95. Overall, forested areas in the study area increased by 3.7%. The techniques used in this study are cost-effective for accurately monitoring changes in forest cover.

Potential and Investment Attractiveness of Implementing Climate Projects on Disturbed Lands

Forest restoration projects can be categorized as climate projects, investments in the implementation of which exceed the investment costs of forest-climate projects, which reduces their attractiveness to investors. An algorithm for assessing investment costs of climate reforestation projects on disturbed lands has been developed. The potential of territories for the implementation of such project initiatives is available in all regions of Russia and amounts to more than 381 thousand hectares. For five studied polygons of disturbed lands (Kuzbass basin, Moscow basin, Western Siberia basin, as well as basins of Chelyabinsk and Belgorod Regions), the aggregated costs for the implementation of measures to create carbon-depositing plantations and ground cover were calculated. Investment costs for restoration of 1 hectare of disturbed land under the climate project vary from 82.6 thousand rubles to 116.9 thousand rubles. Cost analysis shows that the carbon intensity of investment in such projects on disturbed lands is quite high (Ccii > 1.0). The highest investment potential is observed in the Kuzbass basin, where Ccii is 2.01. To organize and implement the afforestation project on disturbed lands of the Kemerovo Region, investments in the amount of 66.7 thousand rubles/ha for capital expenditures and 24.7 thousand rubles/ha for current expenses will be required. The payback period of such an investment project, taking into account the discount rate, is 13.1 years, and during the study period (20 years) the income from the project will cover 228% of the spent funds. These data confirm that the investment potential of forest-climatic projects on disturbed lands is quite high.

From case study to general principle: An analysis of the development mechanism and policy optimization of mangrove carbon sinks

Mangroves, as a crucial coastal ecosystem, possess significant carbon sink functions and play a key role in mitigating global climate change. This paper, based on the Zhanjiang Mangrove Afforestation Project in Guangdong, explores the development mechanisms and economic and ecological benefits of mangrove carbon sink projects through the lens of collective action theory and system dynamics modeling. The study finds that the primary reason for the unsustainable progression of mangrove carbon sink projects is the lack of intrinsic motivation among local villagers to engage in collective action. By constructing a system dynamics model, this paper quantifies the long-term impacts of mangrove carbon sink projects on local socio-economic welfare and proposes policy optimization recommendations. These recommendations include expanding income sources for local villagers, establishing carbon trading and ecological compensation mechanisms, and involving international non-governmental organizations. The findings of this study not only provide guidance for mangrove carbon sink projects in China but also offer valuable insights for the promotion of similar projects globally.

Machine Learning-Based Remote Sensing Inversion of Non-Photosynthetic/Photosynthetic Vegetation Coverage in Desertified Areas and Its Response to Drought Analysis

Determining the responses of non-photosynthetic vegetation (NPV) and photosynthetic vegetation (PV) communities to climate change is crucial in illustrating the sensitivity and sustainability of these ecosystems. In this study, we evaluated the accuracy of inverting NPV and PV using Landsat imagery with random forest (RF), backpropagation neural network (BPNN), and fully connected neural network (FCNN) models. Additionally, we inverted MODIS NPV and PV time-series data using spectral unmixing. Based on this, we analyzed the responses of NPV and PV to precipitation and drought across different ecological regions. The main conclusions are as follows: (1) In NPV remote sensing inversion, the softmax activation function demonstrates greater advantages over the ReLU activation function. Specifically, the use of the softmax function results in an approximate increase of 0.35 in the R2 value. (2) Compared with a five-layer FCNN with 128 neurons and a three-layer BPNN with 12 neurons, a random forest model with over 50 trees and 5 leaf nodes provides better inversion results for NPV and PV (R2_RF-NPV = 0.843, R2_RF-PV = 0.861). (3) Long-term drought or heavy rainfall events can affect the utilization of precipitation by NPV and PV. There is a high correlation between extreme precipitation events following prolonged drought and an increase in PV coverage. (4) Under long-term drought conditions, the vegetation in the study area responded to precipitation during the last winter and growing season. This study provides an illustration of the response of semi-arid ecosystems to drought and wetting events, thereby offering a data basis for the effect evaluation of afforestation projects.

Carbon Stock Estimation of Compensatory Afforestation Plantation Work in Balod District of Chhattisgarh, India

This paper encapsulates the findings of carbon stock assessment of compensatory afforestation work done in Balod District of Chhattisgarh. Under the State CAMPA (Compensatory Afforestation Fund Management and Planning Authority) scheme, the afforestation project aims to enhance the local environment, create employment opportunities for the villagers of Armarikala, and provide fodder for nearby farmers' cattle. This initiative not only address the ecological impact of the power transmission line construction but also align with sustainable development goals by providing socio-economic benefits to the local community. The study aimed to quantify the biomass and carbon sequestration potential of diverse tree species in the Compensatory Afforestation Plantation Work in Balod District of Chhattisgarh. The carbon stock data highlights the significance of different tree species, with Terminalia arjuna emerging as a major contributor, sequestering 3,814.2 kg followed by Dalbergia sissoo with 2616.7 kg of carbon in the surveyed area. The carbon stock assessment in Balod District of Chhattisgarh demonstrates the significant ecological and socio-economic benefits of the compensatory afforestation project under the State CAMPA scheme. The findings underscore the project's alignment with sustainable development goals, enhancing both environmental health and local livelihoods.

A Pan-Asian Energy Transition? The New Rationale for Decarbonization Policies in the World’s Largest Energy Exporting Countries: A Case Study of Qatar and Other GCC Countries

Climate change has become a major agenda item in international relations and in national energy policy-making circles around the world. This review studies the surprising evolution of the energy policy, and more particularly the energy transition, currently happening in the Arabian Gulf region, which features some of the world’s largest exporters of oil and gas. Qatar, Saudi Arabia, and other neighboring energy exporters plan to export blue and green hydrogen across Asia as well as towards Europe in the years and decades to come. Although poorly known and understood abroad, this recent strategy does not threaten the current exports of oil and gas (still needed for a few decades) but prepares the evolution of their national energy industries toward the future decarbonized energy demand of their main customers in East and South Asia, and beyond. The world’s largest exporter of Liquefied Natural Gas, Qatar, has established industrial policies and projects to upscale CCUS, which can enable blue hydrogen production, as well as natural carbon sinks domestically via afforestation projects.

Optimizing land use for climate mitigation using nature based solution (NBS) strategy: a study on afforestation potential and carbon sequestration in Rajasthan, India

Rajasthan faces significant environmental challenges, including the pressing need for effective climate change mitigation strategies. Recognizing afforestation as a vital tool in this endeavor, this study leverages the latest in remote sensing and geospatial analysis to map out the state's afforestation potential. The goal is to assess land suitability across Rajasthan for afforestation projects and evaluate the potential carbon sequestration capabilities of different tree species. This aims to inform sustainable land management strategies that can contribute to climate change mitigation. By integrating satellite imagery, land cover data, terrain analysis, and vegetation indices, the study evaluates environmental factors such as slope, soil moisture, and vegetation health to identify areas optimal for tree planting. A carbon sequestration model was also developed to estimate sequestration rates based on species-specific growth patterns. Findings indicate that approximately 40% of Rajasthan is suitable for afforestation, with potential carbon sequestration rates ranging from 2 to 8 tons per hectare per year. Species such as Azadirachta indica (Neem) and Prosopis cineraria (Khejri) are identified as particularly effective for short-term sequestration, while Phyllanthus emblica (Amla) and Ziziphus mauritiana (Ber) are better suited for long-term carbon capture. This research highlights the importance of targeted afforestation using suitable tree species as a nature-based solution (NBS) for climate change mitigation in Rajasthan. The study offers a data-driven approach to enhancing ecosystem resilience and supports decision-making for climate adaptation in arid regions, highlighting the significant potential of Rajasthan's land for carbon sequestration through afforestation.

Moving forward from escaping the poverty trap in China's greenest regions: Examining four decades of socioecological evolution to re-orient sustainable development policies

Afforestation is an important aspect of ecosystem restoration (ER) and poverty alleviation (PA) through direct and indirect social, economic, and environmental effects. However, the existing afforestation projects worldwide have mainly viewed economic benefits through the narrow lens of subsistence and livelihood, thereby underestimating both indirect PA and the associated negative effects on agricultural production when formulating long-term solutions to global poverty. This study aimed to systematically examine the ecological, agricultural, and economic effects of ecosystem restoration in southeastern China over four decades based on biophysical models and statistical records, and further proposed an upgraded strategy for sustainable PA through ER that addresses conservation objectives and resource needs. We found that ER promoted vegetation growth and enhanced carbon sequestration and soil retention. Meanwhile, industrial transformation improved the economic scale and livelihood diversity (i.e., disposable income), which alleviated poverty and improved social services and infrastructure conditions. Nevertheless, the secondary and tertiary industries gradually replaced the primary industry in terms of output, and increased animal husbandry and forestry development weakened crop planting. Planting structure adjustments further threatened the stability of the grain supply, particularly after 1999, which could potentially lead to a grain crisis. Therefore, we propose upgraded forest management and coordinated development policies to avoid a grain crisis, improve livelihood diversity, balance multidimensional benefits, and facilitate sustainable development. Study results serve as a valuable reference for policy formulation and ER measures for more inclusive, resilient, and sustainable PA.

The inclusion of improved forest management in strategic forest planning and its impact on timber harvests, carbon and biodiversity conservation

In forestry, although the so-called nature-based climate solutions have usually been focused on the calculation of carbon captured in new afforestation projects, it should be noted that the increase in carbon associated with improvements in their management (Improved Forest Management) can also be computed. This type of carbon is not usually integrated into strategic forest planning models, nor has its possible degree of conflict with other regulation ecosystemic services, like biodiversity conservation, been verified. In this research, those two issues have been approached by calculating a baseline in an emblematic forest with an extensive forestry history. For this purpose, we have designed two scenarios, i.e., one linked to its current management (Business As Usual, BAU) and another justified by the inclusion of Improved Forest Management (IFM). The results reveal a notable conflict between the carbon captured and the values of the indicators used to measure biodiversity. In order to reach a compromise between both scenarios, a multi-criteria model has been proposed that could be more attractive than the above ones. In addition, the carbon profit credits in the first ten years have been computed under the IFM scenario; the latter could be, a priori, an object of transaction in a voluntary carbon market. In conclusion, our model generates feasible solutions that allow the integration of IFM into strategic planning. Besides, those solutions show interesting tradeoffs between carbon and biodiversity. This discord must be distinguished by the current state of the forest and its expected growth, as well as their influence on the values associated with provision ecosystem services, such as the present net value associated with timber harvests.

Monitoring the Billion Trees Afforestation Project in Khyber Pakhtunkhwa, Pakistan Through Remote Sensing

Monitoring the Billion Trees Afforestation Project in Khyber Pakhtunkhwa, Pakistan Through Remote Sensing

Climate Change-Induced Growth Decline in Planted Forests of Quercus variabilis Blume near Beijing, China

A progressive decline in tree growth may be induced by global warming, affecting tree health and eventually resulting in death, particularly for trees growing in rocky mountainous regions where seasonal droughts have become more pronounced. However, tree growth dynamics in areas experiencing pronounced climate change have received little attention. In this study, a total of 100 (10 m × 10 m) grid plots were investigated in planted forests of Chinese cork oak (Quercus variabilis Blume), which were established in the 1960s and 1970s in a rocky mountainous area near Beijing, northern China. Furthermore, the radial growth of Q. variabilis (a total of 843 trees sampled from the dominant [D], co-dominant [CD], and suppressed [S] crown classes) was analyzed using retrospective dendrochronology and generalized additive models. The effects of meteorological changes between 1962 and 2020 on radial growth across the three crown classes were examined using correlation analysis. The results indicated that the growth of Q. variabilis initially increased and then decreased after 2010 at the regional level, and these trends varied according to crown class. The radial growth of the D trees responded more positively to an increase in temperature and drought severity index (<0 for dry and >0 for wet conditions) compared with that of the CD and S trees. The growth of the D and CD trees continuously increased under higher temperatures during the rainy seasons (June to September); however, the increases were higher for D than for CD trees. In contrast, the radial growth of S trees declined. We confirmed the historical effects of rising temperatures on tree growth and health, which are linked to water availability. Our data suggested that Q. variabilis trees will be considerably affected by intensified droughts. This study furthers our knowledge regarding the impact of climate change on tree and forest growth and provides management strategies for afforestation projects in rocky mountainous areas that are facing climate change.

The Long-Term Effects of Barren Land Afforestation on Plant Productivity, Soil Fertility, and Soil Moisture in China: A Meta-Analysis.

As global ecological degradation intensifies, the long-term impacts of afforestation on productivity and soil fertility in barren lands have become critical in improving global ecological security and productivity. Through meta-analysis, this study integrates data from 109 barren land afforestation sites across China, aiming to comprehensively analyze the effects on plant productivity and soil fertility while identifying the key environmental drivers of these changes. We found that afforestation consistently enhances plant productivity across 60 years. However, soil fertility and moisture initially surged significantly after afforestation but gradually declined after the first decade, indicating the limited long-term benefits. Climatic factors, namely precipitation and humidity index, are crucial in enhancing plant productivity, while geographic factors, specifically lower elevations and gentler slopes, are associated with greater increases in soil fertility. Elevation and slope are two key factors that influence soil moisture after afforestation. These findings highlight the need for ongoing soil management and ecological maintenance in afforestation projects to sustain the soil fertility benefits. Our study provides a robust scientific foundation for afforestation strategies aimed at barren land restoration and offers valuable insights for policy formulation in barren land afforestation.

Assessment of eco‐environmental changes along roads in the Qinghai‐Tibetan Plateau based on remote sensing data: A case study of the Sino‐Nepalese Transport Corridor

AbstractUnderstanding the evolutionary patterns of ecological quality in transport corridor areas and their driving mechanisms is essential for maintaining regional sustainable development. However, an integrated assessment of the ecology of plateau transport corridors is still lacking. This study focuses on the Sino‐Nepalese Transport Corridor (SNTC) and comprehensively evaluates the spatio‐temporal patterns and evolution of eco‐environmental quality from 2000 to 2021 based on remote sensing data and quantifies and explores the potential driving factors. The results indicate significant spatial heterogeneity in the eco‐environmental quality of the SNTC, with an overall bipolar “northeast‐southwest” distribution pattern. The area of poor and worse quality is the largest (32,471.75 km2), accounting for about 47.20% of the total area of the SNTC, distributed in the plateau bare land and the Yarlung Tsangpo River valley. From 2000 to 2021, the eco‐environmental quality showed an initial decline and then an increase, with a relatively gentle overall trend. The increase in the remote sensing ecological index in Region (I) from 0.314 in the first 10 years to 0.334 in the second 10 years, an increase of 6.37%, was mainly attributed to afforestation projects in the “One River and two tributaries Nature Reserve” region. The eco‐environmental quality of the SNTC is influenced by multiple factors including human activities, climate, and topography. Grazing intensity, population density, and digital elevation model are the main negative disturbance factors, while temperature, precipitation, gross domestic product, and afforestation areas promote eco‐environmental quality. In particular, afforestation projects partially offset the negative impact of human activities. These results will provide useful information for understanding the complex effects of human activities and natural factors on the eco‐environmental quality in the plateau transport corridor region and for formulating ecological conservation policies.

Construction of a DNA Fingerprint Map and a Core Collection of Platycladus orientalis

Platycladus orientalis is one of the main species used in afforestation projects in the arid mountains of north and northwest China, meaning that the species has high ecological and economic value. Studying its genetic diversity and obtaining a core germplasm base and genetic fingerprint data are important for the screening, development, and utilization of the species. This can provide the core materials for the preservation and evaluation and mining of germplasm resources and can provide superior gene resources for breeding programs. In this study, the genetic diversity among 104 P. orientalis germplasm resources was examined using simple sequence repeat (SSR) markers, and a core germplasm containing 31 accessions was constructed that represents the most genetic diversity of P. orientalis accessions. Each of 20 pairs of primers showed polymorphism, and 117 alleles were identified. The average number of alleles at each locus was six, and the mean effective allele number was 2.607. The average Shannon’s information index was 0.983, and the average polymorphism information content was 0.445. There is thus a significant amount of genetic variation within P. orientalis germplasm, yielding a rich genetic diversity. The constructed core germplasm accounted for 30% of the original germplasm. There was no significant difference in genetic diversity between the core germplasm and the original germplasm resources, indicating that the obtained core germplasm resources could fully represent the original germplasm. Using 17 SSR primers with high polymorphism, the DNA fingerprints of 104 P. orientalis germplasm resources were constructed. The results showed that 98 had specific DNA fingerprints. The results of this study provide a valuable basis for the collection, preservation, and utilization of P. orientalis germplasm resources, and the methods adopted in this study have important reference value for the construction of core germplasm of other perennial woody plants.

Environmental and social impacts of carbon sequestration.

Climate change requires major mitigation efforts, mainly emission reduction. Carbon sequestration and avoided deforestation are complementary mitigation strategies that can promote nature conservation and local development but may also have undesirable impacts. We reviewed 246 articles citing impacts, risks, or concerns from carbon projects, and 78 others related to this topic. Most of the impacts cited focus on biodiversity, especially in afforestation projects, and on social effects related to avoided deforestation projects. Concerns were raised about project effectiveness, the permanence of carbon stored, and leakage. Recommendations include accounting for uncertainty, assessing both mitigation and contribution to climate change, defining permanence, creating contingency plans, promoting local projects, proposing alternative livelihoods, ensuring a fair distribution of benefits, combining timber production and carbon sequestration, ensuring sustainable development and minimizing leakage. A holistic approach that combines carbon sequestration, nature conservation, and poverty alleviation must be applied. The potential occurrence of negative impacts does not invalidate carbon projects but makes it advisable to conduct proper environmental impact assessments, considering direct and indirect impacts, minimizing the negative effects while maximizing the positive ones, and weighing the trade-offs between them to guide decision-making. Public participation and transparency are essential. Integr Environ Assess Manag 2024;20:1812-1838. © 2024 SETAC.

Impact of greening trends on biogenic volatile organic compound emissions in China from 1985 to 2022: Contributions of afforestation projects

The rapid expansion of green areas in China has enhanced carbon sinks, but it also presents challenges regarding increased biogenic volatile organic compound (BVOC) emissions. This study examines the impact of greening trends on BVOC emissions in China from 1985 to 2001 and from 2001 to 2022, focusing on evaluating long-term trends in BVOC emissions within eight afforestation project areas during these two periods. Emission factors for 62 dominant tree species and provincial Plant Functional Types were updated. The BVOC emission inventories were developed for China at a spatial resolution of 27 km × 27 km using the Model of Emissions of Gases and Aerosols from Nature. The national BVOC emissions in 2018 were estimated at 54.24 Tg, with isoprene, monoterpenes, sesquiterpenes, and other BVOC contributing 26.94 Tg, 2.29 Tg, 0.44 Tg, and 24.57 Tg, respectively. Over the past 37 years, BVOC emissions experienced a slow growth rate of 1.7 % (0.79 Tg) during 1985–2001, followed by a significant increase of 12 % (6 Tg) from 2001 to 2022. BVOC emissions in the eight afforestation project areas increased by 2 % and 20 % during the two periods. From 2001 to 2022, at the regional scale, the Shelterbelt program for the middle reaches of the Yellow River area exhibited the largest rate of increase (43 %) in BVOC emissions. The Shelterbelt program for the upper and middle reaches of the Yangtze River made the most largest contribution (45 %) to the national increase in BVOC emissions. Afforestation projects have shifted towards planting more broadleaf trees than needleleaf trees from 2001 to 2022, and there also showed a change from herbaceous plants to broadleaf trees. These trends have led to higher average emission factors for vegetation, resulting in increased BVOC emissions. It underscores the importance of considering BVOC emissions when evaluating afforestation initiatives, emphasizing the need to balancing ecological benefits with potential atmospheric consequences.

Effectiveness of Billion Trees Tsunami Afforestation Projects in restoration of forests in Pakistan

AbstractThe history of forest cover dynamics in Pakistan reveals an unsatisfactory environmental situation. In the past 5 decades, particularly during the period between 1990 and 2010, the country lost an average of 41,100 hectares of green cover with a deforestation rate of 1.6% per year. The factors behind that this high deforestation rate is numerous including socio-economic transformation after the major political change during the 1970s in the mountainous areas of Pakistan, demographic changes, accessibility improvements, and land use changes. Several social forestry campaigns have been launched over time to cope with this socioecological and environmental issue. However, most of them have not been very effective due to certain shortcomings. This study aims to evaluate the effectiveness of the most recent and history’s biggest forest restoration program initiated by the government of the Khyber Pakhtunkhwa Province called the Billion Trees Tsunami Afforestation Project (BTTAP). This project was announced in 2013 when a new political party, Pakistan Tehreek-e-Insaf, came into power. The study is focused on one of the main forest hubs of the country in the Hindukush Mountains spanning five districts. Forest cover in this study area decreased from 20 to 2% between 1990 and 2010. After the launch of the BTTAP, the forest cover increased considerably from 2 to 35% by the year 2021. This growth was achieved through planting new trees, banning forest cutting, practicing surveillance, and enhancing community participation. If the project continues and the protection measures are not suspended, it can play a historical role in forest restoration.

Artificial afforestation increased the distribution area and landscape complexity of planted forests in Tibet over the past 30 years

Afforestation plays an important role in improving the ecological environment and promoting local economic development in countries around the world. Although the artificial afforestation project in Tibet has been conducted for more than 30 years since in 1990 s, few studies have examined the dynamic changes in landscape patterns of planted forests in this region since the implementation of the project. This study used Google Earth Engine (GEE) and Landsat data from 1990, 2000, 2010 and 2020 to construct a Normalized Difference Vegetation Index (NDVI) time series curves and an optimal classification model based on the Jeffries-Matusita (J-M) distance. Then, the changes in landscape indices of planted forests in the Tibet Autonomous Region over the past 30 years were examined. The results showed that the area of planted forests increased from 9889.20 ha to 165,879.36 ha by artificial planting, with an average annualized growth rate of about 9.86%. In terms of the landscape pattern, the connectivity and aggregation degree of planted forests increased; the Cohesion (COH) and Aggregation Index (AI) increased by 44.60% and 26.03%, respectively. However, the fragmentation indices also increased to a certain extent due to the increased area and discontinuous planting; the Number of Patches (NP), Patch Density (PD) and Landscape Shape Index (LSI) increased by 32,262, 0.03 and 138.88, respectively. Among the seven regions of Tibet, these changes were most obvious in Lhasa, Qamdo and Shannan regions. Our results indicate that the planted forest area has significantly increased over the past 30 years although the landscape complexity has also increased because of discontinuous planting. These findings highlight the remarkable achievements of the Tibetan afforestation project over the past 30 years.