Impacts of climate change on fractional vegetation coverage of temperate grasslands in China from 1982 to 2015

Global Dynamics of Grassland FVC and LST and Spatial Distribution of Their Correlation (2001-2022)

Fractional Vegetation Cover (FVC) and Land Surface Temperature (LST) are critical indicators for assessing grassland ecosystems. Based on global remote sensing data for FVC and LST from 2001 to 2022, this study employs the Mann-Kendall trend test and Spearman correlation analysis to explore the dynamic changes in and spatial distribution patterns of both variables. The results indicate that the FVC is increasing in regions such as Europe, the eastern southern Sahara, western India, eastern South America, western and southern North America, and central China. However, it is decreasing in southern Canada, the central United States, and northern Australia. Significant increases in LST are observed in subarctic regions and the Tibetan Plateau, attributed to polar warming effects associated with global climate change. Conversely, the LST is decreasing in central China, eastern coastal Australia, and southern Africa. The global FVC-LST relationship exhibits the following four distinct spatial distribution patterns: (1) FVC increase and LST increase (Type 1), (2) FVC increase and LST decrease (Type 2), (3) FVC decrease and LST increase (Type 3), and (4) FVC decrease and LST decrease (Type 4). Type 1, covering 33.72%, is primarily found in high-latitude and high-altitude areas, such as subarctic regions and the Tibetan Plateau. Type 2, the largest group (46.98%), is mainly located in eastern North America, eastern South America, and southern Africa. Type 3, which comprises 18.72%, is concentrated in arid and semi-arid regions, while Type 4, representing only 0.59%, lacks clear spatial distribution patterns.

Within-season estimates of 10 m aboveground biomass based on Landsat, Sentinel-2 and PlanetScope data

Monitoring within-season dynamics of aboveground biomass (AGB) is critical for adaptive decision-making in grasslands to respond to changing conditions caused by frequent disturbances (e.g., grazing activities, fires, climate variations). This study trained the random forest model based on intensive observations from harmonious remote sensing data (Landsat, Sentinel-2, Sentinel-1) and an accurate date grassland sample database. Then we used monthly average remote sensing data to estimate monthly AGB at 10 m across three distinct grassland types in China: temperate meadow steppe, temperate typical steppe, and temperate desert steppe. Considering all the grassland types, the mean predicted AGB values were 83.02 g/m2 in June, 103.02 g/m2 in July, 108.49 g/m2 in August, and 106.89 g/m2 in September. The overall prediction accuracy was evaluated as R2 = 0.68, RMSE = 47.87 g/m². Additionally, the comparison of our monthly AGB maps with 3 m PlanetScope images and the published 30 m yearly AGB map shows the significant advantages of monthly 10 m products to capture the spatial and within-season dynamics of grassland AGB.

A new method to quantify the impacts of human activity on soil conservation service

Human activities and climate change impact ecosystem services, thereby affecting economic and social sustainable development. Measuring the heterogeneity in space and time of how human activities affect ecosystem services poses a challenge for the sustainable management of land resources. Based on "human appropriation of net primary production (HANPP) - Fractional Vegetation Cover (FVC) - Soil Conservation Service (SCS)" cascading effect, first, a geographically and temporally weighted regression (GTWR) model was employed to assess the impact of HANPP in percent of potential NPP (hereafter HANPP%) on the FVC; second, changes in the FVC caused by human activities were quantified; and third, the potential soil conservation service (SCSp) and actual soil conservation service (SCSa) were estimated using the Revised Universal Soil Loss Equation (RUSLE) model, and the difference between them represented the changes in soil conservation service caused by human activities (SCSh). Taking the Qinghai-Tibet Plateau as a case study, we found that the GTWR model was well suited for analyzing the relationship between the HANPP% and the FVC (R2 = 0.897). The HANPP resulted in a decrease in the FVC from 0.222 in 2001 to 0.199 in 2019 and correspondingly resulted in a decrease in the ratio of SCSh to SCSp from 8.95% to 7.24%. This study provides a quantitative method that allows quantifying the influence of human activity on ecosystem services closely related to the FVC.

Simulation of the nutritional requirements and energy balance of adult cows in a northern temperate grassland

The forage-livestock balance is an important component of natural grassland management, and realizing a balance between the nutrient energy demand of domestic animals and the energy supply of grasslands is the core challenge in forage-livestock management. This study was performed at the Xieertala Ranch in Hulunbuir City, Inner Mongolia. Using the GRAZPLAN and GrazFeed models, we examined the forage-livestock energy balance during different grazing periods and physiological stages of livestock growth under natural grazing conditions. Data on pasture conditions, climatic factors, supplemental feeding, and livestock characteristics, were used to analyze the metabolizable energy (ME), metabolizable energy for maintenance (MEm), and total metabolizable energy intake (MEItotal) of grazing livestock. The results showed that the energy balance between forage and animals differed for adult cows at different physiological stages. In the early lactation period, although the MEItotal was greater than MEm, it did not meet the requirement for ME. MEItotal was greater than ME during mid-lactation, but there was still an energy imbalance in the early and late lactation periods. In the late lactation period, MEItotal could meet ME requirements from April-September. Adult gestational lactating cows with or without calves were unable to meet their ME requirement, especially in the dry period, even though MEItotal was greater than MEm. Adult cows at different physiological stages exhibited differences in daily forage intake and rumen microbial crude protein (MCP) metabolism, and the forage intake by nonpregnant cows decreased as follows: early lactation > mid-lactation > late lactation, pregnant cows' lactation > dry period. For the degradation, digestion and synthesis of rumen MCP, early-lactation cows were similar to those in the mid-lactation group, but both were higher than those in the late-lactation group, while pregnant cows had greater degradation, digestion, and synthesis of MCP in the lactation period relative to the dry period. For lactating cows, especially those with calves, grazing energy requirements, methane emission metabolism and heat production were highest in August, with increased energy expenditure in winter. Overall, grazing energy, methane emissions and heat production by dry cows were low. In the context of global climate change and grassland degradation, managers must adopt different strategies according to the physiological stages of livestock to ensure a forage-livestock balance and the sustainable utilization and development of grasslands.

Predicted changes in distribution and grazing value of Stipa-based plant communities across the Eurasian steppe

The Eurasian steppe is one of the world's largest continuous areas of grassland and has an important role in supporting livestock grazing, the most ubiquitous land use on Earth. However, the Eurasian steppe is under threat, from irrational grazing utilization, climate change, and resource exploitation. We used an ensemble modeling approach to predict the current and future distribution of Stipa-dominated plant communities in three important steppe subregions; the Tibetan Alpine, Central Asian, and Black Sea-Kazakhstan subregions. We combined this with an assessment of the grazing value of 22 Stipa species, the dominant grassland species in the area, to predict how grazing value might change under future climate change predictions. We found that the effects of changing climates on grazing values differed across the three subregions. Grazing values increased in the Tibetan alpine steppe and to a lesser extent in Central Asia, but there were few changes in the Black Sea-Kazakhstan subregion. The response of different species to changing climates varied with environmental variables. Finally, our trait-based assessment of Stipa species revealed variations in grazing value, and this had major effects on the overall grazing value of the region. Our results reinforce the importance of trait-based characteristics of steppe plant species, how these traits affect grazing value, and how grazing values will change across different areas of the Eurasian steppe. Our work provides valuable insights into how different species will respond to changing climates and grazing, with important implications for sustainable management of different areas of the vast Eurasian steppe ecosystem.