Search Results (25)

As one of China’s largest national parks, Sanjiangyuan National Park (SNP) plays a crucial role in preserving ecological security and biodiversity. Conducting a scientific evaluation of dynamic changes in vegetation ecological quality and landscape patterns within the park is essential for ensuring its sustainable development and conservation as a national ecological security barrier. This study analyzed the spatial and temporal dynamics of vegetation ecological quality index (VEQI) and Landscape Pattern Metrics (LPM) in SNP using the VEQI model and Fragstats 4.2.1, along with spatial correlation analyses spanning from 2007 to 2022. The findings indicated an overall upward trend in VEQI, with a notable increase of approximately 38.88% over the 15-year period. Particularly in the Yangtze River Source Park, VEQI exhibited the most significant increase, reaching 48.99%. Furthermore, forest and shrub cover types displayed higher VEQI values and demonstrated an increasing trend, signifying significant ecological improvement in these ecosystems. Regarding landscape patterns, patch density (PD) and landscape shape index (LSI) demonstrated an increasing trend, while average patch area and edge density (ED) gradually decreased, indicating a rising level of landscape fragmentation. High values of the largest patch index (LPI) were primarily concentrated in the Lancangjiang source park, the Yellow River source park, and the southern part of the Yangtze River source, suggesting greater ecological connectivity in these regions. Spatial autocorrelation analysis between VEQI and LPM revealed significant spatial heterogeneity. Specifically, VEQI exhibited positive correlations with LPI and mean patch area, while showing negative correlations with PD, ED, PR, TE, NP, and mean shape index. This indicates that areas with lower vegetation ecological quality tend to exhibit higher landscape fragmentation and complexity. The study’s findings highlight the increasing trend in VEQI and changing landscape fragmentation within SNP, offering a scientific foundation for ecological protection policy formulation and sustainable park development. Full article

Rodent infestation has become one of the important factors in grassland degradation on the Qinghai–Tibet Plateau, one of the hindrances to ecological and environmental protection, and a threat to the balance and development of the ecosystem in the Sanjiangyuan region. Based on the need for the scientific planning for ecological protection, this paper designs a method for detecting rodent infestation in plateau scenarios. Firstly, data were collected and annotated, and a dataset of plateau rodent distribution in the Qinghai region was constructed. The collected data include videos captured through drone-based field surveys, which were processed using OpenCV and annotated with LabelMe. The dataset is categorized into four specific types: ungobbled rat holes, gobbled rat holes, rocks, and cow dung. This categorization allows the model to effectively differentiate between rodent-related features and other environmental elements, which is crucial for the segmentation task. Secondly, the latest segmentation algorithm provided by YOLO v8 is improved to design a segmentation algorithm that can accurately detect the distribution of rodent infestation in the plateau scene. The specific improvements are as follows: firstly, the Contextual Transformer module is introduced in YOLO v8 to improve the global modeling capability; secondly, the DRConv dynamic region-aware convolution is introduced in YOLO v8 to improve the convolutional representation capability; thirdly, the attention mechanism is incorporated in the backbone of YOLO v8 to enhance the feature extraction capability of the network capability. A comparison test with the original algorithm on the plateau rodent distribution dataset showed that the new algorithm improved the detection accuracy from 77.9% to 82.74% and MIoU from 67.65% to 72.69% on the plateau rodent distribution dataset. The accuracy of the evaluation of plateau rodent damage levels has been greatly improved. Full article

National parks play a crucial role in protecting ecosystems and biodiversity while facing challenges in balancing nature conservation and economic development. However, because of the difficulty in the unified simulation of natural protection functions and regional socioeconomic development, there is a lack of integrated prediction research on the comprehensive development pathways of national parks and their surrounding areas. This study adopts the Shared Socioeconomic Pathway (SSP) framework that links climate change research with socioeconomic development paths, taking China’s first national park—Sanjiangyuan National Park—region as an example, to conduct research on the synergistic development path of regional socioeconomic development and national parks. The model design includes five typical paths to cover a wide range of socioeconomic development possibilities. These paths are based on different assumptions, including factors such as population growth, economic development, energy use, technological progress, and policy choices. By applying scenario planning methods, optimal development pathways are identified based on environmental, economic, and social priorities. The results show that GDP growth is fastest under the sustainable development and fossil fuel development pathways. By 2050, the population difference under different pathways will approach 100,000, and the GDP gap will be close to CNY 200 billion. This study provides valuable insights for the planning, decision-making, and management of Sanjiangyuan and similar national parks and their surrounding areas, contributing to the promotion of sustainable ecological and economic development of national parks and their regions. Full article

Revealing the response of vegetation on the Qinghai-Tibet Plateau (QTP) to climate change and human activities is crucial for ensuring East Asian ecological security and regulating the global climate. However, the current research rarely explores the time-lag effects of climate on vegetation growth, leading to considerable uncertainty in analyzing the driving mechanisms of vegetation changes. This study identified the main driving factors of vegetation greenness (vegetation index, EVI) changes after investigating the lag effects of climate. By analyzing the trends of interannual variation in vegetation and climate, the study explored the driving mechanisms behind vegetation changes on the QTP from 2000 to 2020. The results indicate that temperature and precipitation have significant time-lag effects on vegetation growth. When considering the lag effects, the explanatory power of climate on vegetation changes is significantly enhanced for 29% of the vegetated areas. About 31% of the vegetation on the QTP exhibited significant “greening”, primarily in the northern plateau. This greening was attributed not only to improvements in climate-induced hydrothermal conditions but also to the effective implementation of ecological projects, which account for roughly half of the significant greening. Only 2% of the vegetation on the QTP showed significant “browning”, sporadically distributed in the southern plateau and the Sanjiangyuan region. In these areas, besides climate-induced drought intensification, approximately 78% of the significant browning was due to unreasonable grassland utilization and intense human activities. The area where precipitation dominates vegetation improvement was larger than the area dominated by temperature, whereas the area where precipitation dominates vegetation degradation is smaller than that where temperature dominates degradation. The implementation of a series of ecological projects has resulted in a much larger area where human activities positively promoted vegetation compared to the area where they negatively inhibited it. Full article

The Sanjiangyuan region, situated on the Qinghai–Tibetan Plateau, constitutes an exceptionally delicate ecological environment. Alterations in the region’s ecological landscape stem not only from natural factors but also from significant anthropogenic influences, exerting a notable impact on the sustainable economic and social development of the region’s middle and lower reaches. Consequently, investigating changes in the landscape pattern of Sanjiangyuan National Park holds paramount importance for comprehending the formation mechanism of spatial landscape distribution in the area. This study analyzes the ecological sensitivity and landscape pattern of Sanjiangyuan National Park in Qinghai Province, China, utilizing ArcGIS 10.8 and Fragstats 4.2. Employing the bivariate spatial autocorrelation analysis method, the research uncovers the spatial distribution characteristics between ecological sensitivity and landscape pattern, along with their aggregated change traits. The findings reveal that ecological sensitivity areas within the park encompass varying degrees, ranging from extremely sensitive to insensitive. The area of moderately sensitive zones in the Yellow River source region is 7279.67 km² (39.17%), whereas the corresponding area in the Yangtze River source region is 32,572.34 km² (36.30%). The eastern and northern parts of the Sanjiangyuan National Park exhibit significant landscape fragmentation. Ecological sensitivity varies markedly across different regions, with the southern and some northern areas showing higher sensitivity. In the Lancang River source park and the southern part of the Yellow River source park, the Largest Patch Index (LPI) and Ecological Sensitivity Index exhibit a high–high (HH) clustering pattern, indicating strong ecological connectivity in these areas. These regions also feature high Total Edge (TE), Number of Patches (NP), Patch Density (PD), and Edge Density (ED), indicating a complex landscape structure and abundant habitat edge areas. The study recommends restoring ecological connectivity in highly fragmented areas and implementing strict protection measures in sensitive regions to maintain ecosystem health and biodiversity. These findings provide a foundation for developing targeted ecological protection measures to enhance ecosystem health and biodiversity conservation in the area. This research aligns with several Sustainable Development Goals (SDGs), including Climate Action, Life on Land, and Clean Water and Sanitation, by promoting sustainable ecosystem management and biodiversity conservation. Full article

Between 2020 and 2023, rust fungus specimens were collected from the primary forested regions of the Sanjiangyuan area in Qinghai Province, resulting in over 300 samples. A taxonomic and phylogenetic study of the rust fungi from these forests was conducted using morphological and molecular biological techniques. The investigation identified rust fungi from 7 families, 12 genera, 56 species and varieties, including 10 new host records, 1 new record for China, and 2 novel species. The host plants involved belonged to 26 families, 48 genera, and 78 species. Pucciniaceae and Coleosporiaceae were the dominant families, with the genera Puccinia, Melampsora, and Gymnosporangium being prevalent. The rust fungi in the Sanjiangyuan forests showed a biogeographical affinity with the North Temperate Zone. Floristic comparisons revealed a higher similarity with rust fungi from Inner Mongolia, Gansu, and Tibet and a lower similarity with those from Hainan. An analysis of the life forms of rust fungus host plants indicated that herbaceous plants were the most common, followed by shrubs and trees. In different regions of Sanjiangyuan, rust fungi were found as follows: Golog Prefecture with 6 families, 9 genera, and 28 species; Yushu Prefecture with 5 families, 8 genera, and 31 species; Huangnan Prefecture with 5 families, 9 genera, and 26 species; and Hainan Prefecture with 4 families, 5 genera, and 10 species. The families Pucciniaceae, Melampsoraceae, and Coleosporiaceae were common across all four regions. Moreover, the families Rosaceae, Asteraceae, Ranunculaceae, Salicaceae, and Caprifoliaceae were shared among the host plants in these regions. Full article

The wild large herbivores inhabiting the Yellow-River-Source National Park (YRSNP) are confronted with a significant threat from climate change and human activities. In response to these detrimental influences, measures have been proposed by the government, such as the Ecological Conservation and Restoration Project in the Sanjiangyuan Region (ECRPSR) and the establishment of the Sanjiangyuan National Park (SNP). To advance species diversity, it is crucial to investigate the spatial distribution of large herbivores, identify factors influencing their distribution, and address conflicts arising from divergent plans within the YRSNP. In this study, unmanned aerial vehicles were employed for surveying the distribution of the Tibetan wild ass (Equus kiang) and Tibetan gazelle (Procapra picticaudata). The findings indicate that the optimal habitat area for Tibetan wild ass is 437.16 km², while for Tibetan gazelle, it is 776.46 km². Precipitation and the human footprint index emerge as the primary factors influencing the habitat distribution of large herbivores within the YRSNP. Under the influence of the ECRPSR, there was a noteworthy expansion of the habitat area for Tibetan wild ass by 791.25 km², and for Tibetan gazelle, it expanded by 1612.94 km². From a wildlife conservation standpoint, this study proposes the establishment of a wildlife refuge in the YRSNP, effective coordination of conflicts between various functional zones and plans, preservation of suitable habitats for large herbivores, and the provision of a scientific foundation to reconcile development and conservation conflicts in the region, while concurrently fostering biodiversity conservation. Full article

With further urbanization, household consumption firmly plays a key role in China’s national carbon emissions. However, current research concerning carbon issues has mainly focused on urban household consumption, and few studies have paid attention to herder households, leading to a research gap in the field of low-carbon shifting related to nomadic economies. In this study, we interviewed more than one-thousand herder households in the Sanjiangyuan region of the Qinghai–Tibet Plateau in China. The household carbon emissions and their influencing factors were investigated across the herder households of 15 counties. Our findings revealed the following: (1) There exist differences in the amounts of household carbon emissions and their compositions in the Sanjiangyuan region. From the perspective of spatial distribution, the emission hotspots are mainly concentrated in the eastern part of the Sanjiangyuan region. (2) At the prefecture level, average personal emissions were larger in the Hainan Prefecture (3.26 t ce/year), while they were approximately 1.36 times that of the Huangnan Prefecture (2.4 t ce/year), though with smaller personal emissions. The indirect carbon emissions of the four prefectures all occupied larger percentages of household carbon emissions that were mainly contributed by food consumption and housing. (3) Family type was the main diver influencing personal carbon emissions in the Huangnan Prefecture, Guoluo Prefecture, and Yushu Prefecture. The more people living in the household, the lower the per capita carbon emissions. However, the effect size of potential carbon reductions was weakened when the number of family members rose to over three. (4) We propose that grazing prohibitions and low-carbon dietary shifts would contribute to low-carbon herder livelihoods, especially for small-sized households that should be peer-to-peer targeted by regional government propaganda, which may help to strengthen the implementation of in-depth low-carbon promotions across the Sanjiangyuan region and even the overall Qinghai–Tibet Plateau. Full article

The Yellow River Source Area is located in the ecological protection and restoration area of the Sanjiangyuan in China, which has been deteriorating as a result of human-caused overgrazing and the grassland destruction caused by plateau rats and rabbits, as well as the influence of other natural factors. The Yellow River Source Area is an important area that implements ecological restoration and protection in the Three Rivers Source Region, where the ecologically vulnerable areas that are of great significance to the implementation of ecological restoration in national land space should be identified and the early warning should be extended. This measure can help us identify potential ecological problems and take timely and targeted protection measures to ensure the health and sustainable development of the ecosystem in the Yellow River Source Area. Therefore, an in-depth understanding of the ecological vulnerability of the Yellow River Source Area and the establishment of an early warning mechanism are of vital importance for the protection and restoration of the ecology of the national space in the Yellow River Source Area. Aiming to comprehensively delimit ecological restoration areas in the Yellow River Source Area and provide an early warning, this study applies the MSPA method to identify ecological source areas and uses a patch importance index to identify the importance of ecological source areas, along with extracting potential ecological corridors by using the MCR model, screening important ecological corridors by using the gravity model as a criterion, and simulating land cover changes in 2030 under the limitations of ecological security pattern by using the PLUS model. The results show that: (1) 154 potential ecological corridors were extracted based on the MCR model, with a total length of 7891.90. (2) The total area of the landscape types in the Yellow River Source Area was 12,301 based on MSPA analysis, including the 6899.57 of core area. (3) Based on the PLUS model, the area of farmland and forest in the study area will decrease, while the grassland area will increase. According to the studies, the grassland in the study area expands in a circular pattern towards the surrounding wetland and water area, threatening the ecological sources and corridors. In summary, the study delimits one protection zone in the ecological source land and two core ecological restoration zones and points out the early warning points in the ecological protection space. The delimitation and instruction provide specific spatial guidance for the protection and restoration of ecosystems in order to promote ecological sustainability. Full article

The official establishment of China’s national parks marks a new stage in the construction of China’s ecological civilization system. National parks systematically protect the areas with the richest biodiversity and the most complete ecosystem processes in China. This is beneficial not only for China’s natural conservation work, but also for the world’s response to environmental issues, such as climate change. Based on remote sensing images of land use in the four periods 1990, 2000, 2010, and 2020, this study calculated the land use changes in each national park during the corresponding period. Using the Plus model LEAS module, the driving factors of land use change in the national parks were studied and explored. In addition, the study used the InVEST model carbon storage module, using remote sensing images from different periods and the corresponding carbon pools of each national park as the basic data for model operation, to obtain the carbon storage changes in each national park over the past 30 years. Based on the hotspot analysis function, the hotspot areas of carbon storage changes in the national parks in the past 30 years were determined. Consequently, based on the CARS module of the PLUS model, the carbon storage in Northeast Tiger and Leopard National Park in 2030 was estimated under different scenarios. Research suggested that, except for Sanjiangyuan National Park where grassland is the main land use type, the other four national parks are all dominated by forests, and the expansion and changes in the main land use types were due to human activities. In the past 30 years, the carbon storage in China’s national park ecosystem has mainly shown a trend of first increasing and then gradually decreasing. Based on the changes in carbon storage in the national park, restoration scenarios were simulated for the core protected and generally controlled areas of Northeast Tiger and Leopard National Park. Under the ideal scenario, the highest value of carbon storage would be achieved by 2030, which would be 7,468,250 t higher than that in 2020. The present study provides a reference for the regional management of China’s national parks and further confirms that the implementation of the national park system can enhance China’s ability to achieve carbon peaking and neutrality goals. Full article

Vegetation water consumption in the Sanjiangyuan Region is of direct significance to the utilization of local water resources. To measure the actual evapotranspiration of various typical vegetation with different vegetation types in the Sanjiangyuan Region, a Lysimeter was used between November 2019 and October 2020. Additionally, the Penman–Monteith equation was used to estimate the condensation water of different vegetation types. Based on the measured data, this paper analyzes the spatial distribution of annual water consumption and annual runoff of various vegetation types. Furthermore, the spatial and temporal distribution of monthly water consumption of vegetation types on different underlying surfaces are discussed. To establish the relationship between the precipitation and runoff of various vegetation types, an artificial rainfall test was conducted. This study’s results reveal several key findings: (1) Condensation water is widespread and can be observed throughout the year. The annual condensation water volume ranges between 28.47 and 56.88 mm, which is particularly significant for the growth of alpine desert steppe and alpine steppe vegetation. (2) The annual water consumption in the Sanjiangyuan Region was higher in the south than in the north. Shrub water consumption was found to be 58.1–73.3 mm higher than that of grasses. Water consumption primarily occurred during the growing season, spanning from May to October. (3) The total water consumption in the growing season of the alpine meadow was less affected by precipitation compared to the non-growing season (from November to the next April). (4) The runoff yield can be ignored in the non-growing season when calculating water balance. However, during the growing season, the calculation of runoff cannot be ignored due to its significant impact on vegetation water consumption. Full article

Understanding the mechanisms of diversity–productivity relationships is a central question in community ecology. Grazing is the main driving force affecting biodiversity, function, and stability of grassland ecosystems, and thus should play an important role in mediating diversity-productivity relationships. In this study, we examined the effect of grazing intensity on both aboveground biomass and biodiversity and explored the relationship between them in alpine meadow ecosystems in Sanjiangyuan, which is the source of the Yangtze, Yellow, and Lancang rivers. The results showed that the aboveground biomass and species richness decreased significantly due to multi-state succession in alpine meadows caused by long-term grazing, while the Shannon–Wiener index and Pielou evenness index decreased and then increased with increasing grazing intensity. The relationship between the aboveground biomass and biodiversity was U-shaped. Our results highlighted the opposite pattern of the diversity–productivity relationship under low and medium grazing intensity versus an extremely high grazing intensity; evenness contributed largely to this pattern. This study provided a new perspective on grassland management and the relationship between productivity and biodiversity. Attention should be paid to rational grazing to restore biodiversity and ecosystem functions and services in alpine meadows. Full article

Personal injury and property damage caused by wildlife can worsen the relationship between humans and wildlife. In recent years, conflicts between herders and Tibetan brown bears (Ursus arctos pruinosus) (human–bear conflicts; HBCs) on the Qinghai-Tibetan Plateau have increased dramatically, severely affecting community motivation for the conservation of brown bears and other species. Understanding the types, effectiveness, and flaws of current HBC mitigation measures is critical to develop effective strategies to alleviate HBC. From 2017 to 2019, we conducted a systematic field survey regarding HBCs on the Qinghai-Tibetan Plateau. In addition, we invited bear specialists and multiple interest groups to hold an HBC seminar and proposed some potential mitigation strategies. We surveyed 312 families via semi-structured interviews and documented 16 types of HBC mitigation measures. A total of 96% of respondents were using more than two mitigation measures simultaneously. The effectiveness evaluation of HBC mitigation measures showed that: (1) removing food from winter homes while herders were at their summer pastures and asking people to keep watch of winter homes were effective at protecting food and houses; (2) traditional grazing methods (human guarding of livestock all day) and solar soundboxes (attached to livestock) were effective at protecting free-range livestock; (3) solar street lights had a deterrent effect on brown bears and were effective in protecting livestock, houses, and people; and (4) due to the unstable power supply of photovoltaic cells and improper installation of ground wires, electric fences were not ideal in practice. Evaluation of the potential mitigation measures at the seminar showed that upgrading electric fence technology, expanding electric fence pilot areas, installing diversionary feeders, and introducing bear spray were the most optimal solutions. This study provides a scientific basis for creating human–bear coexistence plans on the Qinghai-Tibet Plateau. Full article

This paper uses remote sensing data from the Sanjiangyuan National Park (SNP) to explore the divergence between the boundaries of national parks and the distribution of natural habitats. Results are used to argue that these discrepancies evolve along with the potential impact of global warming. Using the example of the habitat change of snow leopards and the conflicts between local people and snow leopards, we reflect on the consequences of this divergence. Results show that divergence between the political boundaries and natural habitats as well as the consequent influence on the living conditions of local people are strikingly visible, and the effects of global warming on such conflicts are apparent. The authors conclude that both notions of ‘political boundaries’ and ‘natural habitats’ are expected to come together as the SNP region is spatially configured, while ‘global warming’ seems to be relevant as an essential reference when delimiting the region in the future. Finally, the proposal for the establishment of cooperative conservation areas is presented, emphasizing the role of cooperative governance in/around national parks. Full article

Monitoring the extent of plateau forests has drawn much attention from governments given the fact that the plateau forests play a key role in global carbon circulation. Despite the recent advances in the remote-sensing applications of satellite imagery over large regions, accurate mapping of plateau forest remains challenging due to limited ground truth information and high uncertainties in their spatial distribution. In this paper, we aim to generate a better segmentation map for plateau forests using high-resolution satellite imagery with limited ground-truth data. We present the first 2 m spatial resolution large-scale plateau forest dataset of Sanjiangyuan National Nature Reserve, including 38,708 plateau forest imagery samples and 1187 handmade accurate plateau forest ground truth masks. We then propose an few-shot learning method for mapping plateau forests. The proposed method is conducted in two stages, including unsupervised feature extraction by leveraging domain knowledge, and model fine-tuning using limited ground truth data. The proposed few-shot learning method reached an F1-score of 84.23%, and outperformed the state-of-the-art object segmentation methods. The result proves the proposed few-shot learning model could help large-scale plateau forest monitoring. The dataset proposed in this paper will soon be available online for the public. Full article