Source Region Of Yellow River Research Articles

Cyclical ‘Wetting’ Phenomenon in the Source Region of Yellow River under Long-term Trends from 1956 to 2022

Study regionthe source region of the Yellow River (SRYB) Study focusDue to environmental changes, the drying and wetting processes have become increasingly intricate, and it is uncertain whether the wetting phenomenon in the SRYB indicates a long-term trend or a temporary cyclic event. This study utilized monthly streamflow and precipitation records from 1956 to 2022 to calculate hydrological and meteorological-dryness/wetness, represented by the standardized streamflow and precipitation indices, respectively. This study used detrended, wavelet, and cross-wavelet methods to investigate dry-wet variability and identified the atmospheric circulation phenomena driving the dryness/wetness and cyclical changes in the region. New hydro-meteorological insights for the SRYB(i) The SRYB showed an overall fluctuating wetting trend, which intensified after 2000. (ii) There were notable oscillatory cycles at 3–5 years, 10–12 years, and approximately 20–25 years in both hydrological and meteorological dry-wet variability. (iii) Transitions from dry to wet conditions had no significant link to short-term cycles (e.g., 3–5 years), but were linked to decadal cycles (e.g., 20–25 years). (iv) Spring and winter precipitation and streamflow dominated the interannual dry-wet variability. (v) The ENSO, AMO, and PDO influenced short-term cyclic fluctuations, while the AO and PDO influenced decadal cyclic fluctuations. This indicates that the wetting trend follows a cyclic pattern, and the intensification since 2000 is consistent with a decadal cyclic signal.

Impacts of oxbow lake evolution on sediment microbial community structure in the Yellow River source region

Oxbow lake formation and evolution have significant impacts on the fragile Yellow River Basin ecosystem. However, the effects of different oxbow lake evolutionary stages on sediment microbial community structure are not yet understood comprehensively. Therefore, microbial community structure in three stages of oxbow lake succession, namely, lotic lake (early stage), semi-lotic lake (middle stage), and lentic lake (late stage), was investigated in the present study in the Yellow River Basin on the Qinghai-Tibet Plateau. Amplicon sequencing was employed to reveal differences in microbial community diversity and composition. The bacterial and fungal communities in sediment were significantly different among the three succession stages and were driven by different environmental factors. In particular, bacterial community structure was influenced primarily by nitrate-nitrogen (N), microbial biomass phosphorus, and total carbon (C) and organic C in the early, middle, and late stages, respectively. Conversely, fungal community structure was influenced primarily by ammonium-N in the early stage and by moisture content in the middle and late stages. However, the predicted functions of the microbial communities did not exhibit significant differences across the three succession stages. Both bacteria and fungi were influenced significantly by stochastic factors. Homogeneous selection had a high relative contribution to bacteria community assembly in the middle stage, whereas the relative contributions of heterogeneous selection processes to fungal community assembly increased through the three stages. As succession time increased, the total number of keystone species increased gradually, and the late succession stage had high network complexity and the highest network stability. The findings could facilitate further elucidation of the evolution mechanisms of oxbow lake source area, high-altitude river evolution dynamics, in addition to aiding a deeper understanding of the long-term ecological evolution patterns of source river ecosystems.

Improving Unsupervised Object-Based Change Detection via Hierarchical Multi-Scale Binary Partition Tree Segmentation: A Case Study in the Yellow River Source Region

Change detection in remote sensing enables identifying alterations in surface characteristics over time, underpinning diverse applications. However, conventional pixel-based algorithms encounter constraints in terms of accuracy when applied to medium- and high-resolution remote sensing images. Although object-oriented methods offer a step forward, they frequently grapple with missing small objects or handling complex features effectively. To bridge these gaps, this paper proposes an unsupervised object-oriented change detection approach empowered by hierarchical multi-scale segmentation for generating binary ecosystem change maps. This approach meticulously segments images into optimal sizes and leverages multidimensional features to adapt the Iteratively Reweighted Multivariate Alteration Detection (IRMAD) algorithm for GaoFen WFV data. We rigorously evaluated its performance in the Yellow River Source Region, a critical ecosystem conservation zone. The results unveil three key strengths: (1) the approach achieved excellent object-level change detection results, making it particularly suited for identifying changes in subtle features; (2) while simply increasing object features did not lead to a linear accuracy gain, optimized feature space construction effectively mitigated dimensionality issues; and (3) the scalability of our approach is underscored by its success in mapping the entire Yellow River Source Region, achieving an overall accuracy of 90.09% and F-score of 0.8844. Furthermore, our analysis reveals that from 2015 to 2022, changed ecosystems comprised approximately 1.42% of the total area, providing valuable insights into regional ecosystem dynamics.

Mechanisms of isotopic control of precipitation in the Yellow River source region

AbstractThe study of water vapour sources and water cycle patterns in the Yellow River source region is of great significance for ensuring water resource security in the arid and semi‐arid regions of northern China. We established a precipitation stable isotope observation system in the Yellow River source region for three consecutive years (2020–2022), systematically analysed the spatial and temporal distribution characteristics of precipitation stable isotopes 2H and 18O in the Yellow River source region and their interrelationships with environmental factors and topography, and explored the regional water vapour transport pathways by using the HYSPLIT model and combining with the global reanalysis data. The results show that: (1) the δ18O and δ2H values of precipitation in the Yellow River source region follow the seasonal pattern, with the first half of the year being richer than the second half of the year; (2) the spatial variations of δ18O of precipitation in the Yellow River source region show a low in the southwest and a high in the northeast; (3) the water vapour source in the source area is basically stable, and the complex transport paths and the cross‐effects of the local factors determine the stable isotope characteristics of the water, and the stable isotope characteristics of the water are determined by the cross‐effects of the local factors, because the source of the water vapour and the local factors such as the height will not change significantly in the short term. Since the source of water vapour and local elevation factors will not change significantly in the short term, the precipitation pattern in the source area of the Yellow River can be considered to be basically stable.

Analysis and partitioning of terrestrial water storage in the Yellow River source region

AbstractIn order to increase the capability to understand and quantify the spatial differences in terrestrial water storage (TWS), and to reflect the unique energy balance processes and soil freeze–thaw mechanisms in the Qinghai‐Tibet Plateau (QTP), this study improved the energy balance processes of the water and energy transfer processes model, including its surface radiation calculations and snowmelt module. By integrating these improvements, a water and energy transfer processes model in Qinghai‐Tibet Plateau (WEP‐QTP) for the Yellow River source region (YRSR) is developed. Using the improved WEP‐QTP model to perform simulations, we assessed the daily changes in snow cover, soil moisture (SM), permafrost (PM), and groundwater storage (GWS) in the YRSR. Our analysis revealed an increase in TWS of 0.24 mm/yr from 1961 to 2020. Snow water equivalent (SWE), SM, PM, and GWS have proportional contributions of 8.33%, 216.67%, −154.17%, and 29.17% to the increased TWS, respectively. SM is the primary component of TWS. Temperature (T), precipitation (P), evapotranspiration (E), and solar radiation (Rs) influence the spatiotemporal variations in TWS, as well as those of its components. The increase in P is the primary cause for the rise in TWS, SWE, and SM, while the increase in T predominantly contributes to the decrease in PM. Furthermore, permafrost degradation and climate‐induced warming and humidification lead to increased infiltration, resulting in elevated GWS.

Influence of below‐cloud evaporation on stable isotopes of precipitation in the Yellow River source region

AbstractThe study of below‐cloud evaporation effects under clouds in the Yellow River source region is of great significance for regional water resource generation as well as for water resource security in the arid and semi‐arid regions of northern China. In this study, we quantitatively assessed the evapotranspiration effect in the Yellow River source region from March to November based on the improved Stewart model. The study concluded that: (1) below‐cloud evaporation was slightly higher in summer than in other seasons (residual fractions of raindrop evaporation were 80.57% in summer, 81.12% in spring, and 84.2% in autumn, respectively); and (2) sub‐cloud evaporation diminishes with increasing altitude (residual fractions of raindrop evaporation were 83.09% in the western part of the area, 81.82% in the central part of the area, and 81.36% in the eastern part of the area, respectively). (3) The total linear index between study areas f and ∆d is 2.24, where f > 95%, it is 1.19; that is, the evaporation of raindrops increases by 1% and the reduction in the excess of mercury by about 2‰. (4) Local meteorological factors (temperature, precipitation, and relative humidity) and raindrop diameter have a cross‐influence on below‐cloud evaporation, with relative humidity having the most significant effect, with the highest correlation coefficient of 3.03 when relative humidity is less than 70%. The results of the study can provide a parameter basis for hydrological and climatic models in the Yellow River Basin.

Determination of priority conservation areas in the Yellow River source region based on ecosystem integrity evaluations

The conservation of the ecosystem in the Yellow River source region (YRSR) has become a crucial national strategy in China, emphasizing the need for evaluating ecosystem integrity to identify priority conservation areas (PCAs). Current research has primarily employed a limited number of indicators or a single dimension to assess ecosystem integrity, which may overlook comprehensive considerations required for effective conservation planning. To address this, a multidimensional approach was adopted in this study to evaluate ecosystem integrity, incorporating three dimensions: biological diversity, ecosystem function, and stress components. The MaxEnt and Fragstats models were employed to create an ecosystem integrity map and Marxan was used to identify priority conservation areas within the YRSR. Our results showed that (1) the index of ecosystem integrity gradually declined from east to west, consistent with the spatial distribution of biodiversity and ecosystem function, whereas the stress component exhibits a decreasing trend from northeast to southwest. (2) the priority protected areas were distributed in Maduo, Ruoergai, Maqu, Maqin, Henan, Gande, and Jiuzhi Counties. Furthermore, to address existing protection gaps and enhance connectivity, it was recommended to incorporate an additional 27,644 km2 of southwest and central YRSR into the PCAs. Overall, the study offered practical recommendations for the conservation of the ecosystem in the YRSR. In addition, the method of PCAs determination in this study could provide a reference for the government’s growing nature conservation affairs, which will contribute to sustainable development.

Retracted: Research on the Characteristics of Surface Flux and Surface Parameters of Meadow Underlying Surface in the Source Region of Yellow River

Retracted: Research on the Characteristics of Surface Flux and Surface Parameters of Meadow Underlying Surface in the Source Region of Yellow River

Variability in soil nematode communities across recovery patches in degraded Alpine meadows of the Yellow River source region

Summary Accurate measurements of soil nematode communities are important for an in-depth understanding of the ecological functions of soil nematodes. High throughput sequencing (HTS) has been reported extensively, but the concordance between HTS and morphological identification results is still lacking. To compare two methods, we selected bare patches (BP), short-term recovery patches (SP), middle-term recovery patches (MP) and long-term recovery patches (LP) of different restoration succession stages in three sample sites to survey the nematode characteristics. In addition to nematode community structure and community ecological function, common nematode genera in BP, SP, MP and LP were compared by two methods: HTS and morphological identification. The results show that the number of species identified in the morphological analysis was lower than using HTS. The soil nematode diversity in different recovery patches was LP > MP > SP > BP. The indices of Shannon-Wiener, Pielou, Simpson and species number of different recovery patches based on HTS reflected the biodiversity of nematode communities, which was consistent with the results of morphological identification. Of the common nematode genera, Coslenchus, Aphelenchus and Leptonchus showed a significant correlation by the two methods. Although both methods have limitations, the HTS provides a more effective means of observing soil nematode biodiversity levels for rapid insight across recovery patches in degraded alpine meadows of the Yellow River source region in our results.

Characteristics of Solar-Induced Chlorophyll Fluorescence in the Three River Headwaters Region, Qinghai-Tibetan Plateau during 2001 to 2020

The ecology of the Three River Headwaters Region (TRHR) is related to the long-term sustainable development of Qinghai Province and the whole of China. The change in chlorophyll fluorescence is an important index to measure the ecological environment. Therefore, it is of great significance to study the spatial and temporal distributions of Solar-induced chlorophyll fluorescence (SIF)and the related influencing factors in the TRHR. In this study, a high-resolution SIF dataset (2001–2020) was selected to be averaged on a time scale of years and months to investigate the annual and seasonal SIF characteristics, and the influencing climate factors were analyzed in combination with meteorological data by statistical method. The results showed that the SIF values ranged from 0.05 to 0.073 during 2001–2020, with a peak value of 0.073 in 2005 and 2009 and a minimum value of 0.05 in 2002. The averages of SIF values were higher in the source regions of the Yellow River source region (YR) and Langcang (Mekong) River source region (LCR) than in the source region of the Yangtze River source region (YZR). The SIF values of the TRHR in July, August and September were significantly higher than those in other months. The maximum value occurred in August at 0.11, and the minimum value was 0.008 in December. The precipitation had greater effect on the inter-annual variations in SIF. The monthly variation of SIF is influenced by precipitation, temperature and relative humidity. In addition, the influence of human activities and altitude on SIF should not be ignored. The results have certain reference value for protecting vegetation in the TRHR, and provide a reference for other regions to analyze the spatiotemporal changes and influencing factors by using SIF data.

Divergent responses of permafrost degradation to precipitation increases at different seasons on the eastern Qinghai–Tibet Plateau based on modeling approach

The Qinghai–Tibet Plateau (QTP) has responded to remarkable climate warming with dramatic permafrost degradation over the past few decades. Previous studies have mostly focused on permafrost responses to rising air temperature, while the effects of accompanying increases in precipitation remain contentious and largely unknown. In this study, a distributed process-based model was applied to quantify the impacts of increased precipitation on permafrost thermal regimes in a warming climate by employing model experiments in the source region of Yellow River (SRYR) on the eastern QTP. The results showed that the active layer thickness (ALT) of permafrost increased by 0.25 m during 2010–2019 compared to 2000 across the SRYR, which was primarily driven by climate warming. In contrast, the increased annual precipitation played a relatively limited role and just slightly mitigated active layer thickening by 0.03 m. Intriguingly, increased precipitation in the cold and warm seasons exerted opposite effects on permafrost across the SRYR. The increased precipitation in the cold season mainly promoted ALT increases, while the increased precipitation in the warm season mitigated ALT increases. In ∼81.0% of the permafrost across the SRYR, the cooling effects of warm season wetting outweighed the warming effects of cold season wetting; while at the transition zone where permafrost was unstable and degrading to seasonally frozen ground, the warming effects of cold season wetting played a relatively larger role which contributed to permafrost degradation. This study explored the physical mechanisms of permafrost thermal responses to climate wetting, thus providing a better understanding of permafrost change in a warmer and wetter climate on the QTP.

Soil Moisture Estimation by Assimilating In‐Situ and SMAP Surface Soil Moisture Using Unscented Weighted Ensemble Kalman Filter

AbstractHighly accurate soil moisture information is necessary to understand land surface processes. However, observational techniques do not produce adequately accurate spatial‐temporal continuous regional soil moisture data. The data assimilation method can be used to improve the soil moisture estimations by merging multi‐source observed data, but its performance is affected by error covariance and the quality of assimilated data. We designed eight numerical experiments to analyze how to improve the filter performance through soil moisture assimilation using the unscented weighted ensemble Kalman filter (UWEnKF) and 1‐D Richards equation at Maqu and Erlinghu (ELH) observational sites in the source region of Yellow River (SRYR), China. The experimental results show that the filter performance improves as the quality of assimilated data increases in the soil moisture assimilation experiment when assimilating in‐situ surface soil moisture (SSM) observations, SMAP SSM data and downscaled SMAP SSM data. In other aspects, filter performance is readily affected by model and observation error covariances in soil moisture assimilation. If the SMAP SSM data are taken to be perfect (i.e., small bias), UWEnKF performs differently between different sites because of the underestimation or overestimation of SMAP SSM and model simulations compared to the in‐situ observations. Additionally, different soil moisture assimilation results can be obtained with different initial values at the beginning of the assimilation period. Overall, filter performance can be improved primarily by improving the quality of assimilated data (e.g., downscaling the remote sensing data), and by creating a reasonable and effective method for determining error covariance.

Identification of priority protected areas in Yellow River Basin and detection of key factors for its optimal management based on multi-scenario trade-off of ecosystem services

Identifying priority protected areas based on ecosystem services (ESs) is a key step to realize the integrated allocation and optimal management of ecosystems in Yellow River Basin (YRB). However, balance the trade-offs between ESs is still a challenge in protected area planning. In this study, based on CASA, InVEST, RWEQ, and RUSLE, we quantified the spatial and temporal fluctuations in carbon sequestration, water yield, sandstorm fixation, and soil conservation in the YRB from 2000 to 2018. Then we introduced ordered weighted averaging (OWA) operator to simulate multiple scenarios, and identified priority protected areas at the basis of ESs trade-offs. Finally, the dominant influencing factors in the management of ESs in priority protected areas were identified by the Geo-Detector. Our results indicate that: (1) From 2000 to 2018, carbon sequestration, water yield and soil conservation in the YRB increased by 37.47%, 53.99% and 86.04% respectively, while sandstorm fixation decreased by 9.55%. Carbon sequestration, water yield and soil conservation all present a spatial pattern of “high in the southwest and low in the northwest”, while the high value areas for sandstorm fixation are concentrated in the northwest and east of the YRB. (2) The location and conservation effectiveness of protected areas differ across multiple decision-making scenarios, and S3, with optimal protection effectiveness, is chosen as the priority protection scenario. The selected priority protected areas are primarily located in the Yellow River source region, the Loess Plateau, and portions of the lower reaches of the YRB, covering a total area of 161.747 × 103 km2. Under this scenario, the conservation efficiency of carbon sequestration, water yield, sandstorm fixation and soil conservation are 1.371, 1.455, 1.644 and 2.371, respectively, which can realize the efficient protection of multiple ESs at the same time. (3) In priority protected areas, natural environmental factors explain ES to a greater extent than factors of human activity. NDVI and precipitation are the main factors influencing carbon sequestration, water yield and sandstorm fixation, while slope has the strongest influence on soil conservation. The interaction between the factors will significantly enhance the explanatory power of the driving factors. Our findings can provide theoretical support to the sustainable management of ecosystems and the optimization of the ecological barrier function in the Yellow River Basin.

Spatiotemporal evolution and attribution analysis of grassland NPP in the Yellow River source region, China

The protection of the environment and promotion of sustainable development in the Yellow River Basin (YRB) is a major national strategy in China. Madoi County (MC), at the headwaters of the YRB, plays a crucial role in ensuring the ecological security and sustainable development of the middle and lower reaches of the river. Vegetation net primary productivity (NPP) is a critical indicator for assessing the structure and function of the ecosystem. Therefore, studying the spatiotemporal evolutionary characteristics of grassland net primary productivity (GNPP) in MC and its driving mechanisms is of the utmost importance. We employed linear regression analysis, optimal parameters-based geographical detector (OPGD), multiscale geographic weighted regression (MGWR), and residual analysis to investigate the spatiotemporal change of GNPP in MC under the influence of climate change (CC) and policies in different periods based on MOD17A3 NPP data. Additionally, we explored the natural and anthropogenic factors affecting GNPP and their spatiotemporal processes on global and grid scales. Lastly, we quantified the relative contributions of CC and human activity (HA) to the observed changes in GNPP. The results were as follows: 1) GNPP in MC has demonstrated a fluctuating and increasing trend since 2000, with an average annual growth rate of 1.58 gC·m−2·a−1 and a maximum growth rate of 6.29 gC·m−2·a−1 in 2017–2021. 2) Spatial variation in GNPP has been evident since 2000, with a gradual increase in GNPP from the northwest to southeast. Regions with notable increases in grassland were predominantly located in areas with eco-engineering. 3) The OPGD was used to identify key driving factors (DFs), revealing that climate factors had stronger explanatory powers for the GNPP at each phase. MGWR results indicated that the effect of key DFs exhibited clear spatiotemporal heterogeneity. Annual cumulative solar radiation and annual cumulative precipitation had the most significant effect on GNPP. Regions with positive effects (PEs) of grassland area change and grassland cover change were mostly located in eco-engineering zones. The PEs of DFs on GNPP increased. 4) The contribution of CC to GNPP changes and the dominant area share were greater than those of HA. However, areas with PEs of HA increased gradually. The synergies between eco-protection policies and natural regulation are therefore critical to the eco-environmental protection in the YRB.

Seasonal ice-covered lake surface likely caused the spatial heterogeneity of aeolian sediment grain-size in the source region of Yellow River, northeastern Tibetan Plateau, China

The area of lakes in Tibetan Plateau (TP) is 36522 km2, accounting for nearly half (49.1%) of the total lake surface area in China, and the lakes in TP are seasonally ice-covered for 4–5 months per year. In such a high-cold Third Pole with extensive lakes, how does aeolian sediment transport on ice cover and to what extent can seasonal ice-covered lake cause sediment redistribution by providing pathways for sediment migration is rarely studied. The source region of Yellow River (SRYR) is located in the northeastern TP with an altitude above 4000 m, is home to large area of seasonal frozen lakes. Nine sections of aeolian sediments were collected from SRYR for grain-size study. The end-member modeling analysis (EMMA) provides a greater chance of resolving aeolian sediment sources since it can quantitatively separate the particle size components of various sedimentary dynamic processes and sources in the sediment. The result shows great spatial difference of the mean grain sizes (mainly varying between 70 and 230 μm). Parametric EMMA is applied to study the provenance tracing of aeolian sediment, combining with remote sensing images and wind data. Aeolian processes were analyzed by separating and extracting the grain size end-members of nine sections, and four statistical end-members (modal grain size is 8.9, 79.5, 141.6, and 251.8 μm, respectively) were classified from the grain size distribution. It shows that the sedimentary sequences in sections 7 and 8 have high EM2 and EM3 fractions and very low EM4 content at all depths. Based on comprehensive analysis of aeolian sediment grain-size, phenology of ice lake, wind regime and remote sensing images, it revealed that the fine aeolian sediments (sections 7 and 8) on the downwind shore of Ngoring Lake likely transported from the upwind shore, which were blown across the ice-covered lake surface by prevailing west wind in winter and spring, but the coarse sediments could be trapped by ice cracks. Therefore, it’s concluded that the aeolian sediment transport on seasonal ice-covered lakes may lead to the spatial heterogeneity of aeolian sediment grain-size in the SRYR.

A study of the effects of climate change and human activities on NPP of marsh wetland vegetation in the Yellow River source region between 2000 and 2020

Quantitative assessment of the impacts of climate change and human activities on marsh wetland is essential for the sustainable development of marsh wetland ecosystem. This study takes the marsh wetland in the Yellow River source region (YRSR) as the research object, using the method of residual analysis, the potential net primary productivity (NPPp) of marsh wetland vegetation in the YRSR between 2000 and 2020 was stimulated using the Zhou Guangsheng model, and the actual primary productivity (NPPa) of marsh wetland vegetation was download from MOD17A3HGF product, and the difference between them was employed to calculate the NPP affected by human activities, the relative contribution of climate change and human activities to the change of NPPa of marsh wetland vegetation was quantitatively evaluated. The results revealed that between 2000 and 2020, NPPa of marsh wetland vegetation increased in the YRSR by 95.76%, among which climate-dominated and human-dominated NPP change occupied by 66.29% and 29.47% of study areas, respectively. The Zoige Plateau in the southeast accounted for the majority of the 4.24% decline in the NPPa of the marsh wetland vegetation, almost all of which were affected by human activities. It is found that the warming and humidifying of climate, as well as human protective construction activities, are the important reasons for the increase of NPPa of marsh wetland vegetation in the YRSR. Although climate change remains an important cause of the increase in NPPa of marsh wetland vegetation, the contribution of human activities to the increase in NPPa of marsh wetland vegetation is increasing.

Construction and Optimization of an Ecological Network in the Yellow River Source Region Based on MSPA and MCR Modelling.

The source region of the Yellow River (SRYR) is an important water conservation and farming area in China. Under the dual influence of the natural environment and external pressure, ecological patches in the region are becoming increasingly fragmented, and landscape connectivity is continuously declining, which directly affect the landscape patch pattern and SRYR sustainable development. In the SRYR, morphological spatial pattern analysis (MSPA) and landscape index methods were used to extract ecologically important sources. Based on the minimum cumulative resistance model (MCR), Linkage Mapper was used to generate a potential corridor, and then potential stepped stone patches were identified and extracted by the gravity model and betweenness centrality to build an optimal SRYR ecological network. The distribution of patches in the core area of the SRYR was fragmented, accounting for 80.53% of the total grassland area. The 10 ecological sources based on the landscape connectivity index and 15 important corridors identified based on the MCR model were mainly distributed in the central and eastern regions of the SRYR. Through betweenness centrality, 10 stepped stone patches were added, and 45 planned ecological corridors were obtained to optimize the SRYR ecological network and enhance east and west connectivity. Our research results can provide an important reference for the protection of the SRYR ecosystem, and have important guiding significance and practical value for ecological network construction in ecologically fragmented areas.

Human activities dominant the distribution of Kobresia pygmaea community in alpine meadow grassland in the east source region of Yellow River, China

Kobresia pygmaea is the endemic and one of the most important species in the alpine meadow in the Qinghai-Tibet Plateau. It is the key stage in the management of degraded grassland, and irreversible degradation will take place after the degradation succession phases of the Kobresia pygmaea community. However, knowledge about the spatial distribution and driving factors were still unknown. In this study, the potential distribution of the Kobresia pygmaea community was determined using the BIOMOD niche model. Combine with the reality distribution based on remote sensing classification, the driving factors of climate and human activities were identified. The findings revealed that: (1) among all environmental factors, the maximum radiation, monthly temperature difference, driest period precipitation were the main climate influencing factors for the Kobresia pygmaea community distribution, and random forest model achieved the highest prediction accuracy and best stability of any niche model. (2) The potential distribution area of Kobresia pygmaea community was 653.25 km2 (account for 3.28% of the study area), and mostly located in northern and central of Zeku County, northeast of Henan County, and northeast, central, and eastern parts of Maqu County. (3) Climate factors driven 21.12% of Kobresia pygmaea community reality distribution, while human activities driven for 79.98%. Our results revealed that human activities dominant the reality distribution of Kobresia pygmaea community in alpine meadow grassland in the east source region of Yellow River, China.

Analysis of factors influencing spatiotemporal differentiation of the NDVI in the upper and middle reaches of the Yellow River from 2000 to 2020

Surface vegetation represents a link between the atmosphere, water, and human society. The quality of the ecological environment in the upper and middle reaches of the Yellow River (UMRYR) has a direct impact on the downstream basin. However, only few studies have investigated vegetation changes in the UMRYR. Therefore, we used the coefficient of variation and linear regression analyses to investigate spatiotemporal variations in the normalized difference vegetation index (NDVI). Further, we used the geographical detector model (GDM) to determine the spatial heterogeneity of the NDVI and its driving factors and then investigated the factors driving the spatial distribution of the NDVI in different climatic zones and vegetation types. The results showed that the NDVI in the UMRYR was high during the study period. The NDVI was distributed in a spatially heterogeneous manner, and it decreased from the southeast to the northwest. We observed severe degradation in the southeast, mild degradation in the northwest and the Yellow River source region, and substantial vegetation recovery in the central basin. Precipitation and vegetation type drove the spatial distribution of the NDVI. Natural factors had higher influence than that of anthropogenic factors, but the interactions between the natural and anthropogenic factors exhibited non-linear and bivariate enhancements. Inter-annual variations in precipitation were the main natural factor influencing inter-annual NDVI variations, while precipitation and anthropogenic ecological restoration projects jointly drove NDVI changes in the UMRYR. This study provides a better understanding of the current status of the NDVI and mechanisms driving vegetation restoration in the UMRYR.

Impact of climate change and land use change on ecosystem net primary productivity in the Yangtze River and Yellow River Source Region, China

Net ecosystem productivity (NEP) is an important indicator of the capacity of terrestrial ecosystems to absorb carbon. For the purpose of developing adaptation and mitigation strategies, it is essential to investigate the effect of climatic changes and anthropogenic activities on NEP. This study analyzed the spatiotemporal properties of NEP in the Yangtze River and Yellow River Source Region (SRYY) using remote sensing images, climate variable data, and land use data. Then it was examined at how climatic change affected carbon sinks and sources and how changes in land use affected carbon storage. According to the results, the SRYY contributed a carbon sink worth 35.26 Tg C annually from 2001 to 2019 (1 Tg = 1012 g). Influenced by climate, soil and vegetation, NEP displayed regional differences in space. The spatial distribution of NEP gradually increased from Northwest to Southeast. In recent twenty years, the NEP of SRYY slightly increased with a rate of 3.24 Tg C per decade. The NEP with an increasing trend accounted for 78.9% of the whole study area, which were widely distributed and especially significant in the west, such as Tuotuo River Basin. The correlation analysis between NEP and climate variables suggested that temperature was the dominant control of NEP in the SRYY. About 54.4% of the NEP variance across the entire SRYY was contributed by temperature. However, there was no significant linear relationship between NEP and annual precipitation. In recent two decades, built-up land expansion and ecological degradation reduced carbon sink by 28.61 Gg C (1 Gg = 109 g) and 1.94 Tg C, respectively. Grassland degradation caused by rodent infestation and grazing was the main factor of carbon sink reduction in some areas. The restoration of vegetation and wetland areas resulted in a 0.75 Tg C increase in the carbon sink. It might be benefited from warmer climate condition and ecological protection measures.