Community Differentiation and Ecological Influencing Factors along Environmental Gradients: Evidence from 1200 km Belt Transect across Inner Mongolia Grassland, China

In this work, we conducted a 1200 km belt transect for field survey in typical and meadow steppes across Inner Mongolia Plateau in 2018. The field investigation, laboratory soil analysis, and quantitative ecology methods were utilized to explore the differentiation characteristics of the plant community, and their relationships with ecological factors. The results showed that a total of 140 vascular plants within 108 quadrats mainly comprised of Asteraceae, Poaceae, Rosaceae, and Fabaceae. Two-way Indicator Species Analysis (TWINSPAN) revealed eight vegetation typologies: I: Stipa sareptana var. krylovii + Dysphania aristata, II: Stipa grandis + Leymus chinensis, III: Stipa sareptana var. krylovii + Leymus chinensis, IV: Stipa grandis + Cleistogenes squarrosa, V: Stipa grandis + Carex duriuscula, VI: Stipa baicalensis + Leymus chinensis, VII: Carex pediformis + Stipa baicalensis, VIII: Leymus chinensis + Elymus dahuricus. Detrend Correspondence Analysis (DCA) confirmed the above eight vegetation typologies and indicated a relatively small variation. Redundancy analysis (RDA) revealed that the spatial differentiation characteristics in the typical steppe were chiefly driven by precipitation, while the influencing factor in the meadow steppe was soil nutrients, followed by temperature and precipitation. The contrast between typical and meadow steppes revealed that the spatial distribution of typical steppe was influenced by precipitation, while the contribution of heat and water in the meadow steppe was equal. The conclusion revealed that the temperature and precipitation conditions coupled with soil nutrients shaped the spatial differentiation characteristics of temperate steppe vegetation in the Inner Mongolia grassland. Therefore, this study advanced our knowledge of the spatial patterns of temperate steppe along longitude and latitude gradients, providing scientific and theoretical guidance for the biodiversity conservation and sustainable ecosystem management of the Inner Mongolia grassland.

An estimation of the evapotranspiration of typical steppe areas using Landsat images and the METRIC model

Remote sensing excels in estimating regional evapotranspiration (ET). However, most remote sensing energy balance models require researchers to subjectively extract the characteristic parameters of the dry and wet limits of the underlying surfaces. The regional ET accuracy is affected by wrong determined ideal pixels. This study used Landsat images and the METRIC model to evaluate the effects of different dry and wet pixel combinations on the ET in the typical steppe areas. The ET spatiotemporal changes of the different land cover types were discussed. The results show that the surface temperature and leaf area index could determine the dry and wet limits recognition schemes in grassland areas. The water vapor flux data of an eddy covariance system verified that the relative error between the ETd,METRIC and ETd,GES of eight DOYs (day of the year) was 18.8% on average. The ETMETRIC values of the crop growth season and the ETIMS of eight silage maize irrigation monitoring stations were found to have a relative error of 11.1% on average. The spatial distribution of the ET of the different land cover types in the study area was as follows: ETwater > ETarable land > ETforest land > ETunutilized land > ETgrassland > ETurban land.

Impacts of Land Surface Conditions and Land Use on Dust Events in the Inner Mongolian Grasslands, China

Aeolian processes in temperate grasslands (TGs) are unique because the plant growth–decay cycle, soil water, and land-use interactions affect the seasonal and inter-annual changes in dust events. Land-use types in Inner Mongolian TGs are unique (settled grazing and grass mowing) compared with those in Mongolian TGs. Since 2003, land use has been controlled by grassland protection legislation, which is intended to prevent desertification and dust storms. In this study, we used process-based ecosystem (DAYCENT) and statistical modeling, along with dust event observations from March to June of 1981–2015, to (1) identify critical land surface factors controlling dust emissions (vegetation components, live grass, standing dead grass, litter, and soil moisture) at typical and desert steppe sites in Inner Mongolia and (2) estimate the impact of controlled land-use legislation on dust events. The DAYCENT model realistically simulated the dynamics of the observed vegetation components and soil moisture in 2005–2015. At both sites, similar significant correlations were obtained between spring dust events and wind speed or a combination of all surface factors that retained anomalies (memory) from the preceding year. Among the surface factors, vegetation was a critical factor that suppressed dust in Inner Mongolian TGs, similar to that in Mongolian TGs. In the desert steppe, standing dead grass had the strongest memory and was significantly correlated with dust events, whereas no significant correlations were observed in the typical steppe. This suggests that, in a typical steppe region, heavy grazing and mowing result in few dead grasses, thereby inhibiting the prevention of dust events. Moreover, the simulations of dust events under controlled (light grazing) and uncontrolled (heavy grazing) land-use conditions demonstrated that the grassland protection legislation reduced the occurrence of dust events in typical and desert steppe sites by 25 and 40%, respectively, since 2003.