Canopy-Mediated Shifts in Grassland Diversity and Heterogeneity: A Power Law Approach from China’s Loess Plateau

This study investigates the spatial heterogeneity and species diversity of grassland vegetation in the agro-pastoral ecotone of China's Loess Plateau, integrating Taylor's power law model with the minimum area concept to address scale-dependent ecological patterns. Field surveys were conducted across four vegetation types: small-leaf poplar forest (SP), pine-caragana mixed forest (PC), caragana shrubland (RC), and saline grassland (SG). Nested quadrats (0.25-8 m²) were used to establish species-area relationships (SARs), while binary occurrence frequency data fitted to Taylor's power law quantified spatial heterogeneity parameters (<i>δ_i</i>, <i>δ_c</i>, <i>CACD</i>) and derived diversity indices (<i>H</i>', <i>J</i>', <i>D</i>). the results showed that species composition differed significantly among vegetation types, with RC exhibiting the highest richness (25 species) and SG the lowest (12 species). SAR analysis showed distinct <i>z</i>-values: SP had the lowest <i>z</i> (0.14), indicating minimal area effects and high homogeneity, while SG had the highest area sensitivity. Spatial heterogeneity (<i>δ_c</i>) was highest in RC and lowest in SP. Over 82.5% of herb-layer species exhibited aggregated distributions (<i>δ_i</i> > 0). The dominant species <i>Leymus secalinus</i> (Georgi) Tzvelev shifted from regular (<i>δ_i</i> < 0) under SP/SG to aggregated (<i>δ_i</i> > 0) under PC/RC. Diversity metrics peaked in PC plots (highest <i>H</i>' and richness, lowest dominance), whereas SP showed high dominance but low diversity. <i>CACD</i> values (critical aggregation diversity) were maximized under SG. The integration of power law modeling and minimum area analysis effectively captures scale-dependent vegetation patterns. Pine-caragana mixed forests (PC) optimize biodiversity and spatial heterogeneity, suggesting moderated canopy structures enhance ecological stability. These findings provide a theoretical basis for sustainable grassland management in ecologically sensitive agro-pastoral zones.