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<p>Reliable assessment of ecosystem quality is essential for managing plantation systems, yet uncertainty persists about how indicator selection and scoring methods affect ecological interpretation. Here, we evaluated soil and vegetation quality across contrasting plantation types using total data sets (TDS) and reduced minimum data sets (MDS), combined with linear and non-linear scoring methods. Across seasons, soils under <i>Ulmus pumila</i> consistently exhibited higher nutrient availability and carbon stocks than those under <i>Pinus tabuliformis</i>, reflecting contrasting plant functional strategies. Despite substantial data reduction, MDS-based indices closely matched TDS-derived values (<i>R</i><sup>2</sup> = 0.65–0.86), indicating that a limited set of indicators captured the dominant variation in ecosystem quality. Linear scoring methods further showed greater sensitivity in resolving species and seasonal differences, with stronger correlations than non-linear approaches, such as SQI: <i>R</i> = 0.81 vs 0.65 in <i>Pinus</i>; <i>R</i> = 0.93 vs 0.91 in <i>Ulmus</i>. In contrast, non-linear models tended to dampen intermediate variation and reduce discriminatory power. These findings suggest that simplified assessment frameworks can effectively characterize ecosystem quality when variation follows structured, trait-related ecological gradients. This study provides an analytical framework that can be applied and evaluated across broader forest systems to support ecosystem assessment and management.</p>

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Ecological structure determines the performance of simplified approaches for assessing soil and vegetation quality in plantation systems

  • 期刊论文

  • 发表日期：

    2026年7月16日

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  • Jian Feng,
  • Jiannan Liu,
  • Yin Wang,
  • Min Wang,
  • Ziying Zheng,
  • Wei Zhang,
  • Can Wang,
  • Zhijun Yu,
  • Abolfazl Masoudi,
  • Jingze Liu

摘要

Reliable assessment of ecosystem quality is essential for managing plantation systems, yet uncertainty persists about how indicator selection and scoring methods affect ecological interpretation. Here, we evaluated soil and vegetation quality across contrasting plantation types using total data sets (TDS) and reduced minimum data sets (MDS), combined with linear and non-linear scoring methods. Across seasons, soils under Ulmus pumila consistently exhibited higher nutrient availability and carbon stocks than those under Pinus tabuliformis, reflecting contrasting plant functional strategies. Despite substantial data reduction, MDS-based indices closely matched TDS-derived values (R2 = 0.65–0.86), indicating that a limited set of indicators captured the dominant variation in ecosystem quality. Linear scoring methods further showed greater sensitivity in resolving species and seasonal differences, with stronger correlations than non-linear approaches, such as SQI: R = 0.81 vs 0.65 in Pinus; R = 0.93 vs 0.91 in Ulmus. In contrast, non-linear models tended to dampen intermediate variation and reduce discriminatory power. These findings suggest that simplified assessment frameworks can effectively characterize ecosystem quality when variation follows structured, trait-related ecological gradients. This study provides an analytical framework that can be applied and evaluated across broader forest systems to support ecosystem assessment and management.