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How communities of living organisms assemble has long been a central question in ecology. The impact of habitat filtering and limiting similarity on plant community structures is well known, as both processes are influenced by individual responses to environmental fluctuations. Yet, the precise identifications and quantifications of the potential abiotic and biotic factors that shape community structures at a fine scale remains a challenge. Here, we applied null model approaches to assess the importance of habitat filtering and limiting similarity at two spatial scales. We used 63 natural vegetation plots, each measuring 5 × 5 m, with three nested subplots measuring 1 × 1 m, from the 2021 field survey, to examine the alpha diversity as well as beta diversity of plots and subplots. Linear mixed‐effects models were employed to determine the impact of environmental variables on assembly rules. Our results demonstrate that habitat filtering is the dominant assembly rules at both the plot and subplot levels, although limiting similarity assumes stronger at the subplot level. Plot‐level limiting similarity exhibited a positive association with fine‐scale partitioning, suggesting that trait divergence originated from a combination of limiting similarity and spatial partitioning. Our findings also reveal that the community assembly varies more strongly with the mean annual temperature gradient than the mean annual precipitation. This investigation provides a pertinent illustration of non‐random assembly rules from spatial scale and environmental factors in plant communities in the loess hilly region. It underscores the critical influence of spatial and environmental constraints in understanding the assembly of plant communities. [ABSTRACT FROM AUTHOR]

The grasslands in high-latitude areas are sensitive to climate warming and drought. However, the drought stress effect on the long-term variability of grassland productivity at the continental scale still hinders our understanding. Based on aboveground net primary production (ANPP) surveys, satellite remote sensing Normalized Difference Vegetation Index (NDVI), and meteorological data, we comprehensively analyzed three Aridity metrics and their effect on ANPP in Eurasian grassland from 1982 to 2020. Our results showed that the ANPP had an overall uptrend from 1982 to 2020, increasing most in the Tibetan Plateau alpine steppe subregion (TPSSR). Among three Aridity indicators, vapor pressure deficit (VPD) had an overall uptrend, while the trend of Aridity and soil moisture (SM) was insignificant from 1982 to 2020. Soil drought had negative effects on ANPP for all Eurasian grassland, while the atmospheric VPD had a positive effect on ANPP for TPSSR and the Mongolian Plateau steppe subregion (MPSSR), but a negative effect for the Black Sea–Kazakhstan steppe subregion (BKSSR) which was the driest subregion. SM had been the predominant driving factor for the interannual variability of ANPP in MPSSR since 1997. The increasing VPD had facilitated grassland productivity in alpine grasslands due to its cascading effect with an increasing temperature after 2000. The cascading effects networks of climate factors—drought factors (VPD, Aridity, and SM)—ANPP (CDA–CENet) indicated that SM was the predominant driving factor of the interannual variability of ANPP in MPSSR and BKSSR, and the dominance of SM had enhanced after the year 1997. The inhibitory effect of VPD on ANPP transformed into a facilitating effect after 1997, and the facilitating effect of SM is weakening in TPSSR. [ABSTRACT FROM AUTHOR]