Natural ¹⁵N abundance provides integrated information about nitrogen (N) input, transformation and output, indirectly reflecting N cycling traits within terrestrial ecosystems. However, relationships between natural ¹⁵N abundance and N cycling processes are poorly understood in China. Here, our primary objectives were to (i) examine the effects of grazing at varying levels of intensity on δ¹⁵N of soils and plants in a semi-arid grassland; (ii) detect the relationships between δ¹⁵N of soils and four major N cycling processes (i.e. mineralization, nitrification, denitrification and ammonia volatilization); and (iii) determine whether δ¹⁵N of soils can be used as an indicator of N cycling in this semi-arid grassland. The field experiment was conducted within the long-term (17-year) grazing enclosures in a semi-arid grassland in Inner Mongolia. Five grazing intensities (0.00, 1.33, 2.67, 4.00 and 5.33 sheep ha⁻¹) were designed. δ¹⁵N values of topsoils (0–10 cm), surface soils (0–2 cm) and plants were measured in 2006. Differences in δ¹⁵N of soils and plants between the five grazing intensities were examined. Rates of four soil N cycling processes were measured periodically during the 2005 and 2006 growing seasons. The δ¹⁵N values of topsoils were linked to the four N cycling processes to investigate their relationships. The δ¹⁵N values of topsoils (5.20–5.96‰) were substantially higher than the δ¹⁵N values of plants (2.51–2.93‰) and surface soils (1.44–2.92‰) regardless of grazing intensities. The ¹⁵N-depleted N losses during microbial decomposition of organic matter in concert with the downward movement of residual substrate over time are the possible causes of higher δ¹⁵N values in topsoils than in surface soils. In addition, the δ¹⁵N values of topsoils were positively correlated with the δ¹⁵N values of both plants and surface soils. Grazing, especially the high-intensity grazing (5.33 sheep ha⁻¹), resulted in a significant decrease in δ¹⁵N of surface soils. However, no statistically significant variations in δ¹⁵N of topsoils and plants were found in response to grazing. The δ¹⁵N values of topsoils exhibited significant dependence on the cumulative rates of NH₃ volatilization, net nitrification and denitrification in 2005 but not in 2006.

The net primary productivity (NPP) of vegetation is an essential factor of ecosystem functions, including the biological geochemical carbon cycle, which is often impacted by climate change and human activities. It plays a significant role in comprehending the nature of carbon balance in an ecosystem and demonstrates the global and regional carbon cycle dynamics. The present study used an upgraded CASA model to calculate the NPP in the Yellow River Basin (YRB), China. The model’s simulation ability was improved by changing the model parameters. Further, the CASA model was validated by comparing with MODIS-NPP and in situ observed NPP, wherein the accuracy of the CASA model estimation was found satisfactory to estimate NPP changes in the study area. The simulated results of the improved CASA model showed that the mean annual NPP value of vegetation in the YRB was 283.4 gC m^–2 a^–1 from 2001 to 2020, with a declining trend in spatial distribution from south to north. In contrast, the NPP appeared as an increasing trend in the YRB temporally from 212 gC m^–2 a^–1 in 2001 to 342 gC m^–2 a^–1 in 2020, with a mean annual growth rate of 4.6 gC m^–2 a^–1. The total NPP in the YRB increased by 40,088.3 GgC between 2001 and 2020, from 226.06 TgC to 266.15 TgC. This rise can be attributed to the increase in forests. The average grassland area has reduced by 4651 km² during the last two decades, significantly impacting the total NPP of grasslands. Although the increase in NPP in wetlands was minimal, accounting for 815.53 GgC, the highest change percentage of 79.78%, could be observed among the six vegetation types due to the anthropogenic influences and climate change. The conditions favorable for vegetation growth and a sustained environment were enhanced by the increased precipitation and temperature and the reinforced ecological protection by the government.

Ecosystem services are the basis of human survival and development and play an irreplaceable role in maintaining the dynamic balance of the earth’s life support system and environment. This study evaluated the annual forest ecosystem service values (ESVs) and their spatial evolution characteristics from 2001 to 2020 in China and revealed the impact of climatic factors as well. The equivalent factor method was applied to calculate ESVs in combination with net primary productivity (NPP) calculated by the CASA model. The water conservation results based on the InVEST model and equivalent factor method were compared to test the reliability of the method. From 2001 to 2020, the annual forest ESVs ranged from RMB 9.17 trillion to 10.81 trillion, with an average of RMB 9.99 trillion in China. The forest ESVs increased from the northwest to the southeast regions of China with the lowest values of less than RMB 3 million per square kilometer and relatively high values of more than RMB 9 million per square kilometer. In the past 20 years, the forest ESVs have shown a significant increasing trend, especially in the Northeast Forest Region and Southeast Forest Region. The ESVs have decreased only in very few forest areas such as Cuona and Motuo counties on the southern edge of Tibet Province in Southwest China and Pingtung and Kaohsiung counties in southern Taiwan. The mean annual forest ESV was necessarily higher in the recent 10 years (2011–2020, RMB 10.43 trillion) than in the previous 10 years (2001–2010, RMB 9.55 trillion), while the spatial growth rate was usually less than 20%. The annual forest ESVs were significantly correlated with temperature, precipitation and evapotranspiration but not with sunshine hours and relative humidity across the 20 years. In most areas (>60%), the positive impact of various climatic factors was dominant, and the area positively affected by precipitation was the largest (76%). The mean annual forest water conservation from 2001 to 2020 was RMB 1.46 trillion based on the InVEST model and was RMB 1.77 trillion based on the equivalent factor method. Overall, the results obtained by the two methods are roughly equal and mostly spatially matched. This study has some guiding significance for utilizing resources rationally, strengthening ecological environment protection and improving adaptability to climate change.

The assessment of ecosystem services provides an intuitive source of information on the benefits humans derive from ecosystems. The equivalent factor method was applied to calculate the ecosystem service value (ESV) in combination with net primary productivity (NPP) calculated by the process-based Carnegie–Ames–Stanford approach (CASA) model. This study evaluated grassland ESV and its spatial evolution characteristics in China from 2001 to 2020 and revealed the impact of climate factors. For 2001–2020, the annual grassland ESV ranged from 1.17 × 10¹² to 1.51 × 10¹² yuan (renminbi, China yuan—the same below; $0.15 × 10¹²–$0.20 × 10¹², US dollar), with an average of 1.37 × 10¹² yuan ($0.18 × 10¹²). The spatial pattern of ESV per unit area of grassland was notably characterized by an increase from northwest to southeast. However, the value of grassland ecosystem services was relatively large (exceeding 10 × 10⁶ yuan; $1.30 × 10⁶) in northern and western provinces and was the lowest (less than 0.2 × 10⁶ yuan; $0.03 × 10⁶) in eastern and southern provinces. In the last 20 years, grassland ESV has increased in most areas of China and has decreased only in some western and northern areas. Compared with the first 10 years, the average ESV of grassland in most areas increased in the last 10 years, usually by less than 20%. However, it decreased in the western and northern parts of China, mainly concentrated in the alpine meadow and alpine grassland of the Qinghai–Tibet Plateau and the grassland around the Yili region of Xinjiang. Precipitation was the main regulating factor of grassland ESV and had a positive impact in 79% grassland areas, especially in northern China. Evapotranspiration and sunshine hours exhibited a marginal impact on ESV, but temperature and relative humidity had no significant effect. Overall, this study contributes to exploring the spatiotemporal patterns of grassland ecosystem service value and the impact of climate factors in China, thereby providing reliable guidance for grassland ecosystem management.