Spatial and temporal variations and significance identification of ecosystem services in the Sanjiangyuan National Park, China

Analysis of lake changes and their influence factors in the three river regions from 2000 to 2020 in the Sanjiangyuan Region, China

An important factor for investigating climate change in the Sanjiangyuan is the evolution of the spatio-temporal pattern of lakes in this region. The present study used the Google Earth Engine (GEE) platform to extract lakes from 2000 to 2020. The present approach created a lake distribution dataset yearly and analyzed spatial and temporal patterns over 20 years. The analysis of lakes focused on the reaction of the Sanjiangyuan Lakes area to changes in climate, glaciers, and permafrost. The findings indicated that the Sanjiangyuan region contains 143 lakes, the majority of which are predominantly small, measuring 1-10 km2. The small lakes account for 60.14 % of the total and are primarily located in the source regions of the Yangtze River and Yellow River. The findings demonstrated that the Sanjiangyuan lakes experienced a significant expansion over the past two decades, particularly from 2011 to 2020. These lakes are divided into expanded, atrophic, and stable categories. Expanded lakes showed significant inter-annual trends in expansion, while atrophic lakes showed smaller fluctuations. The area of stable lakes experienced a consistent decline after 2010, despite a consistent expansion tendency from 2001 to 2010. Moreover, the results indicated that alterations in the size of glaciers and ice reserves in the Sanjiangyuan region have had the greatest influence on the fluctuation in lake area. Among the factors that affect the climate, temperature had the most significant effect on the change in lake area, followed by precipitation.

The impact of China's urbanization on ecosystem service value from the perspective of gross ecosystem product: a case study of Beijing-Tianjin-Hebei region

Gross ecosystem product (GEP) is an aggregate measure of the monetary value of final ecosystem services, or the direct benefits that people derive from nature. GEP can provide decision makers with clear and competing evidence of the monetary value of ecosystem services. However, the relationship between GEP and urbanization has not been clarified which is not conducive to the decision-making role of GEP in the process of urban sustainable development. This work focused on the 'Beijing-Tianjin-Hebei' (BTH) urban agglomeration as a case study of the dynamics of ecological production amidst rapid economic and urban development, and coupled a spatial-temporal analysis of regional ecological change based on GIS (Geographic Information System) with economic valuation methods using official statistics and survey data. Results showed that from 2000 to 2020, the GEP increased from 1.55 trillion to 2.36 trillion, the value of provisioning services and cultural services increased from 0.51 to 0.71 trillion to 0.10-0.65 trillion. The value of regulation services showed an upward and downward trend (0.94-1.03-0.98) due to the rapid economic development in the Beijing-Tianjin-Hebei region. There were obvious spatial differences in the distribution of the GEP, in which Beijing, Tianjin, Tangshan, Cangzhou GEP accounted for 15%, 14%, 16% and 11%, respectively. During 2000-2020, there is a significant correlation between urbanization index (UI) and GEP in BTH, but the correlation between GEP and UI shows a trend of first increasing and then decreasing. The correlation between UI and EPS and ERS gradually decreases, and the impact of UI on ETS shows a significant positive correlation. In the future, it can be foreseen that urbanization will suppress the increase of GEP.

Spatial predictions of groundwater potential using automated machine learning (AutoML): a comparative study of feature selection and training sample size in Qinghai Province, China

Predicting groundwater potential is crucial for identifying the spatial distribution of groundwater in a region. It serves as an essential guide for the development, utilization, and protection of groundwater resources. Previous studies have primarily emphasized finding the most accurate prediction model for groundwater potential while giving less attention to the selection of training features and sample sizes. This study aims to predict groundwater potential within Qinghai Province using automated machine learning technology and assess the influence of sample sizes and feature selection on prediction accuracy. Sixteen groundwater conditioning factors were categorized into categorical and numerical variables. Four feature selection modes were utilized as input in training the model. The results indicated that, except for correlations between evaporation and landforms (- 0.8) and precipitation and normalized difference vegetation index (0.8), the Pearson correlation coefficients among the remaining sixteen factors were ≤ 0.5 or ≥  - 0.5. The models XGB-ALL, RF-Entropy, ET-CRITIC, and XGB-PCA yielded accuracy scores of 0.783, 0.685, 0.745, and 0.703, and area under curve (AUC) of 0.819, 0.724, 0.779, and 0.747, respectively. If enough samples are available with the tree model, an increased number of features can improve prediction accuracy. The principal component analysis method showed difficulty in reducing the dimensionality of the input space, while the Entropy method proved efficient. The accuracy and AUC value of the prediction model improved with an increasing number of samples. Training with 8 features and 200 data points achieved an accuracy of 0.745, sufficient to evaluate regional groundwater potential. As for training with 600 samples, the model's performance accuracy rose to 0.9, enabling precise groundwater potential prediction. The outputs of this research can provide decision-makers in groundwater resource management in Qinghai Province with crucial theoretical and practical support. The lessons learned can have future applications in similar situations.

Short-term restoration effects of ecological projects detected using the turning point method in the Three River Headwater Region, China

The Three River Headwater Region (TRHR) is an important river source area providing important ecological functions. Decades ago, climate change and human activities severely degraded the ecosystem in the TRHR. To restore vegetation, a series of ecological projects have been implemented since 1989. Using net primary productivity (NPP) data from 1988 to 2012, a sequential Mann-Kendall trend test (SQ-MK) method was applied to identify the turning point of vegetation NPP. This approach was able to represent the critical response time of the vegetation to important disturbances. A 3-year time window was set after the implementation of one ecological project to detect and analyze its short-term effects. The ecological projects included the Yangtze River Basin Shelterbelt System Construction Project (YRCP), the TRHR Nature Reserve Construction Project (TNR), the Returning Grazing Land to Grassland Project (RGLGP), and the first phase of the Ecological Conservation and Restoration Project of the TRHR (ECRP). Our results showed that the vegetation in the TRHR responded positively to restoration: 89% of pixels showed an increasing trend and 54% of pixels underwent an abrupt change. The accelerated growth type accounted for the highest proportion among all types of detected turning points. In the ECRP's window, the positive turns rose rapidly, from 41% in 2005 to 86% in 2008, and it showed the most balanced restoration effects across grasslands. The alpine meadow and montane meadow restoration was largely influenced by the ECRP and the RGLGP (both >40%). The alpine steppe restoration was mainly attributed to the ECRP (68%). On the county scale, the positive turns in Yushu at the source of the Yangtze River mainly benefited from the RGLGP (56%), while the positive turns in Maduo at the source of the Yellow River benefited from the ECRP (77%). Nangqian, Tanggula and Zaduo County were still in need of intervention for restoration (< 3%). The results of the study can enhance our understanding of the spatio-temporal distribution of the short-term ecological benefits of different ecological projects, thus provide a scientific and timely reference for future planning and adjustment of the conservation and restoration projects.

Dynamic Response and Adaptation of Grassland Ecosystems in the Three-River Headwaters Region under Changing Environment: A Review

The Three-River Headwaters Region (TRHR) is crucial to the sustainable development of China and Southeast Asia. The sustainability of grassland ecosystems in the region has been seriously challenged in recent years. This paper reviewed the changes in the grasslands of the TRHR and their responses to climate change and human activities. The review showed that accurate monitoring of grassland ecological information is the basis for effective management. Although alpine grassland coverage and the above-ground biomass of the alpine grassland have generally increased in the region over the past 30 years, the degradation has not been fundamentally curbed. Grassland degradation substantially reduced topsoil nutrients and affected their distribution, deteriorated soil moisture conditions, and aggravated soil erosion. Grassland degradation led to loss of productivity and species diversity, and this is already harming the well-being of pastoralists. The "warm and wet" trend of the climate promoted the restoration of alpine grasslands, but widespread overgrazing is considered as one of the main reasons for grassland degradation, and related differences still exist. Since 2000, the grassland restoration policy has achieved fruitful results, but the formulation of the policy still needs to integrate market logic effectively and strengthen the understanding of the relationship between ecological protection and cultural protection. In addition, appropriate human intervention mechanisms are urgently needed due to the uncertainty of future climate change. For mildly and moderately degraded grassland, traditional methods are applicable. However, the severely degraded "black soil beach" needs to be restored by artificial seeding, and the stability of the plant-soil system needs to be emphasized to establish a relatively stable community to prevent secondary degradation.

Assessment and spatial partitioning of ecosystem services importance in Giant Panda National Park: To provide targeted ecological protection

Giant Panda National Park is crucial for China's ecological security strategic pattern known as "two screens and three belts." The importance assessment and classification of ecosystem services in giant panda national parks has an important guiding role in the protection of giant panda national park ecosystems. In this study, we examined four indicators of habitat quality: carbon storage, water conservation, and soil and water conservation. Combined with data analysis were used to evaluate and classify the importance of ecosystem services in the study area. The results showed that: (1) the overall habitat quality index in the study area was relatively high, and the index was generally greater than 0.5. The total carbon storage was 60.5 × 106 t, and the highest carbon storage in the region was 16.9533 t. The area with the highest water conservation reached 715.275 mm. The total soil conservation was 2555.7 × 107 t. (2) From the perspective of spatial characteristics, the habitat quality in the study area presented a spatial distribution pattern of high-low from west to east. The carbon storage presented a spatial distribution pattern of high-low from east to west. The soil conservation presented a spatial pattern of decreasing from west to east, and the water conservation increased from west to east. (3) We divided the research into four levels of importance: The area of general importance in the study site accounted for 1017.58 km2 and was distributed in the northwest of the study site. The moderately important areas were distributed in the east of the study site, with an area of 1142.40 km2. The highly important areas were distributed in the west of the study site, totaling 2647.84 km2. Extremely important areas were distributed in the middle, with an area of 1451.32 km2. (4) The grid cell scale of the study area was used as the dataset to determine the weighting. This makes the weighting more objective and ensures that the spatial distribution of areas with different degrees of importance will be more accurate.

Challenges and Opportunities in Aligning Conservation with Development in China's National Parks: A Narrative Literature Review

As part of its effort to balance economic development with environmental objectives, China has established a new national park system, with the first five locations formally established in 2021. However, as the new parks all host or are proximate to human populations, aligning the socioeconomic needs and aspirations of local communities with conservation aims is critical for the long-term success of the parks. In this narrative review, the authors identify the ecological priorities and socioeconomic stakeholders of each of the five national parks; explore the tensions and synergies between these priorities and stakeholders; and synthesize the policy recommendations most frequently cited in the literature. A total of 119 studies were reviewed. Aligning traditional livelihoods with conservation, limiting road construction, promoting education and environmental awareness, and supporting the development of a sustainable tourism industry are identified as important steps to balance conservation with economic development in the new national parks.

A Meta-Analysis on Degraded Alpine Grassland Mediated by Climate Factors: Enlightenment for Ecological Restoration

Alpine grassland is the main ecosystem on the Qinghai-Tibet Plateau (QTP). Degradation and restoration of alpine grassland are related to ecosystem function and production, livelihood, and wellbeing of local people. Although a large number of studies research degraded alpine grassland, there are debates about degradation patterns of alpine grassland in different areas and widely applicable ecological restoration schemes due to the huge area of the QTP. In this study, we used the meta-analysis method to synthesize 80 individual published studies which were conducted to examine aboveground and underground characteristics in non-degradation (ND), light degradation (LD), moderate degradation (MD), heavy degradation (HD), and extreme degradation (ED) of alpine grassland on the QTP. Results showed that aboveground biomass (AGB), belowground biomass (BGB), Shannon-Wiener index (H'), soil moisture (SM), soil organic carbon (SOC), soil total nitrogen (TN), and available nitrogen (AN) gradually decreased along the degradation gradient, whereas soil bulk density (BD) and soil pH gradually increased. In spite of a tendency to soil desertification, losses of other soil nutrients and reduction of enzymes, there was no linear relationship between the variations with degradation gradient. Moreover, the decreasing extent of TN was smaller in areas with higher precipitation and temperature, and the decreasing extent of AGB, SOC, and TN was larger in areas with a higher extent of corresponding variables in the stage of ND during alpine grassland degradation. These findings suggest that in areas with higher precipitation and temperature, reseeding and sward cleavage can be used for restoration on degraded alpine grassland. Fencing and fertilization can be used for alpine grassland restoration in areas with lower precipitation and temperature. Microbial enzymes should not be used to restore degraded alpine grassland on a large scale on the QTP without detailed investigation and analysis. Future studies should pay more attention to the effects of climate factors on degradation processes and specific ecological restoration strategies in different regions of the QTP.

Spatial-Temporal Variation Characteristics and Influencing Factors of Vegetation in the Yellow River Basin from 2000 to 2019

Vegetation is a crucial and intuitive index that can be used to evaluate the ecological status. Since the 20th century, land use has changed significantly in Yellow River Basin (YRB), along with great changes of vegetation, serious soil erosion, and gradual ecological deterioration. To improve the ecological environment in the YRB, China has carried out a series of ecological protection projects since the 1970s. Therefore, long-term sequence monitoring of vegetation in YRB is necessary to show the conservation effect and better support the further protection and restoration. This study analysed vegetation changes from 2000 to 2019 based on an annual mean fractional vegetation cover (FVC) dataset. The Theil–Sen median trend analysis method was used to analyse trends in FVC. The results showed that the vegetation in the YRB has improved significantly, with an average annual growth rate of 0.65%, and the ‘green line’ of vegetation has moved approximately 300 km westward. The influence of climate on vegetation is essential; therefore, this study also analysed the influence of temperature and precipitation on vegetation over time and space. Ecological control and afforestation are important anthropogenic factors that affect vegetation. The growth trend (0.6%/a) in key ecological function regions (KEFRs) was the fastest, and even though the protection measures are not strict, they provide space for afforestation. The China Ecological Conservation Red Line (CECRL) and the national nature reserves (NNRs) showed relatively flat trends. Ecological afforestation projects were closely correlated with the growth trend of the FVC. The correlation between FVC and the intensity of ecological engineering was significant in typical areas.

Identifying and Zoning Key Areas of Ecological Restoration for Territory in Resource-Based Cities: A Case Study of Huangshi City, China

Resource-based cities are cities that depend on the exploitation and primary processing of natural resources, such as minerals, metals, and oil, and whose rise and development are highly dependent on resources. Due to over exploitation, many problems related to ecosystem degradation have been caused. Ecological restoration of land space is urgent. One of the difficulties in carrying out ecological restoration of territorial space lies in the identification of key areas for ecological restoration and diagnosis of regional ecological problems. In this study, we applied the spatial assessment of ecological sensitivity and the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model to quantitatively analyze the overall ecosystem in Huangshi city so as to delimit the ecological restoration division of Huangshi City. The results showed that: (1) The overall distribution rule is that vegetation, such as that in mountains and forests, is dense, the sensitivity around water and wetlands is high, and the distribution of mines in Huangshi is high. (2) For the period 1980–2018, the habitat quality index of Huangshi was good, with a slight decreasing trend. The simulated habitat quality distribution was consistent with the region-dominated land cover type. (3) Huangshi formed a spatial pattern with natural protected areas as the priority protection areas, mining areas as the key restoration areas, and natural protected areas and mining areas as the general restoration areas. (4) During the period of 1980–2018, the water management of Huangshi generally improved, which indicates that the water pollution control in Huangshi had a positive effect. The results of this study can provide some reference for the green transformation development and ecological restoration of resource-based cities.

Multi-Time Scale Evaluation of Forest Water Conservation Function in the Semiarid Mountains Area

Forest water conservation function is an important part of forest ecosystem services. The discontinuous distribution of forests in semiarid areas brings difficulties to the quantitative evaluation of forest water conservation functions at the basin scale. In this paper, we took the upstream of Xiong’an New Area (Zijingguan—ZJG, Zhongtangmei—ZTM and Fuping—FP basins) as an example and combine the soil and water assessment tool (SWAT) and the water balance method to calculate the amount of forest water conservation (AFWC) at annual, monthly and daily scales from 2007 to 2017, and analyzed the changes of AFWC. The results showed that the hydrological response unit (HRU) generated with the threshold area zero can accurately reflect the forest patch distribution in the three basins. On an annual scale, the annual AFWC were all positive in ZJG and ZTM basins from 2007 to 2017. While, the annual AFWC in the FP basin was negative in 2009, 2013, 2014 and 2017. On a monthly scale, the positive values of AFWC mainly appear from June to September, and the negative values of AFWC mainly appear from December to March. On a daily scale, the AFWC during extreme precipitation was positive, while that was negative during extreme drought. The annual and monthly AFWC in the three basins was positively correlated with the wetness index, and FP basin needs more humid climate conditions than ZJG and ZTM basins to make the forest store water and keep in a stable water storage state. The above results can not only provide important insight into sustainable forest and water resources management in the region, but also serve as reference cases for other regions to carry out relevant research work.

Analysis of regional economic development based on land use and land cover change information derived from Landsat imagery

The monitoring of economic activities is of great significance for understanding regional economic development level and policymaking. As the carrier of economic activities, land resource is an indispensable production factor of economic development, and economic growth leads to increased demand for land as well as changes in land utilization form. As an important means of earth observation, remote-sensing technology can obtain the information of land use and land cover change (LUCC) related to economic activities. This study proposes a method for analysing regional economic situations based on remote-sensing technology, from which LUCC information extraction, sensitivity factor selection, model construction and accuracy evaluation were implemented. This approach was validated with experiments in Zhoushan City, China. The results show that the economic statistical index is most sensitive to the construction land area, and the average correlation coefficient between the actual data and the predicted data is 0.949, and the average of mean relative error is 14.21%. Therefore, this paper suggests that LUCC could be utilised as an explanatory indicator for estimating economic development at the regional level, and the potential applications of remotely-sensed image in economic activity monitoring are worth pursuing.