Spatial–Temporal Correlations between Soil pH and NPP of Grassland Ecosystems in the Yellow River Source Area, China

Abstract

In recent years, ecological concerns such as vegetation destruction, permafrost deterioration, and river drying have been paid much more attention to on the Yellow River Basin in China. Soil pH is regarded to be the fundamental variable among soil properties for vegetation growth, while net primary productivity (NPP) is also an essential indicator to reflect the healthy growth of vegetation. Due to the limitation of on-site samples, the spatial–temporal variations in soil pH and NPP, as well as their intrinsic mechanisms, remain unknown, especially in the Yellow River source area, China. Therefore, it is imperative to investigate the coupling relationship between soil pH and NPP of the area. The study coupled MODIS reflectance data (MOD09A1) with on-site soil pH to estimate spatial–temporal variations in soil pH, explore the response of NPP to soil pH, and assess the extent to which they contribute to grassland ecosystems, thus helping to fill knowledge gaps. Results indicated that the surface spectral reflectance for seven bands could express the geographic pattern of soil pH by applying a multiple linear regression equation; NPP exhibited an increasing trend while soil pH was the contrary in summer from 2000 to 2021. In summer, NPP was negatively correlated with soil pH and there was a lag effect in the response of NPP to soil pH, revealing a correlation between temperate steppes > montane meadows > alpine meadows > swamps in different grassland ecosystems. In addition, contribution indices for temperate steppes and montane meadows were positive whereas they were negative for swamps and alpine meadows, which are apparent findings. The contribution index of montane and alpine meadows was greater than that of temperate steppes and swamps. The approach of the study can enable managers to easily identify and rehabilitate alkaline soil and provides an important reference and practical value for ecological restoration and sustainable development of grassland ecosystems in alpine regions.

Analysis of Spatiotemporal Evolution and Influencing Factors of Vegetation Net Primary Productivity in the Yellow River Basin from 2000 to 2022

“…The overall results indicate an increasing trend in vegetation NPP, signifying an improvement in the ecological environment. This conclusion has also been verified in relevant articles; NPP is increased in the upstream [47,50,[54][55][56]61,62], in the total basin [28,46,63], in the middle reaches [51,57,58,71], and in the downstream [43]. In our exploration of the influencing factors underlying the changes in NPP in the YRB, we have reached conclusions similar to those of other studies.…”

“…Regarding the driving mechanisms of NPP in the YRB, numerous scholars have separately studied the impacts of climate change [45][46][47]50,[55][56][57], human activities [45,50,56,[58][59][60], vegetation types [48], and precipitation [42] on NPP. Zhang et al [61] investigated the response of NPP to soil pH and evaluated their impact on grassland ecosystems. Water plays an irreplaceable role in plant growth, and some scholars have researched the relationship between water availability and changes in NPP in the YRB.…”

Evolution of Landscape Ecological Risk and Identification of Critical Areas in the Yellow River Source Area Based on LUCC

“…Due to the combined action of global warming and human activities, natural phenomena and anthropogenic behaviors can be seen as the main factors that cause desertification in the YRSA, with the increase in construction land and farmland in the north leading to increased desertification [48]. The average pH and NPP values of soils in the YRSA from 2000 to 2021 were low and showed a decreasing trend, indicating that the area has a weak carbon fixation capacity, and it was not conducive to the growth of vegetation [49,50]. The land use types in the YRSA are mainly grassland, including alpine grassland, degraded meadow, alpine meadow, and swampy meadow, and the changes in spatial structure are random and structural [51,52].…”

Spatiotemporal Variation in Carbon Emissions in China’s Tourism Industry during the COVID-19 Pandemic and Ecological Compensation Mechanism

“…Spatiotemporal changes primarily depend on the complex interactions among vegetation, soil, and climate [16], with precipitation being the main limiting factor for the net primary productivity of vegetation in China [17]. Scholars have estimated the total carbon stock of grassland ecosystems in the Three Rivers Source Region to be 53.38 × 10 8 tons, with an average carbon density of 14.94 kg/m 2 , using MODIS GPP/NPP, MODIS NDVI, and various climatic data analyses [18]. The central part of Hainan Island is characterized by high carbon density in natural rubber forests, with an average carbon density ranging from 25 to 33 t/hm 2 .…”

“…In comparison, the northern part is a low-value area with an average carbon density below 20 t/hm 2 [19]. The calculation of net primary productivity (NPP) involves two main methods: NPP inversion models [20][21][22] and direct utilization of MODIS NPP data for measuring carbon sinks [18]. Additionally, utilizing carbon as ecological compensation is an effective strategy for facilitating regional coordination and achieving carbon neutrality [23].…”