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Background <p>Extreme ice storms (EIS) can severely disrupt forest productivity and stability, yet their differential impacts across forest types remain poorly understood, particularly in subtropical regions. Here, we assessed changes in gross primary productivity (GPP), resistance (Rt), and resilience (Rs) across evergreen needle-leaved forest (ENF), evergreen broad-leaved forest (EBF), deciduous broad-leaved forest (DBF), and mixed forest (MF) in mid-to-north subtropical China following two unexpected EIS events in early 2008 and 2018. Random Forest and Partial Least Squares Structural Equation Modeling (PLS-SEM) were used to identify key drivers and disentangle their underlying causal pathways.</p> Results <p>Except for DBF, both EIS events led to declines in forest GPP, with the stronger 2008 event exerting a more pronounced suppressive effect. Forest stability exhibited a clear Rt–Rs trade-off across forest types—the 2008 event was characterized by lower Rt but higher Rs, whereas the opposite pattern was observed in 2018. Among forest types, DBF showed the highest stability, while EBF exhibited the lowest. Freezing duration had contrasting effects between the two events: prolonged freezing duration significantly reduced Rt and Rs in 2008, but enhanced both in 2018. Moreover, freezing intensity, particularly minimum-temperature stress and cumulative precipitation, was the foremost determinant of forest stability, whereas geographical factors acted mainly indirectly through climate interannual variability, freezing intensity, and phenology. Furthermore, biological attributes made relatively modest overall contributions but provided important insights into forest-type-specific stability mechanisms. Specifically, phenology dominated DBF stability, whereas forest structure acted primarily through leaf area index in DBF and MF and through stand age in ENF and EBF.</p> Conclusions <p>Subtropical forest responses to EIS are highly heterogeneous and jointly controlled by disturbance intensity, forest composition, and spatial environmental context. By revealing the mechanisms underlying forest-type-specific stability responses to EIS, this study provides useful insights for differentiated risk-resilience management aimed at enhancing ecosystem stability and sustainable development.</p>

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Subtropical forests exhibit contrasting resistance and resilience to unexpected extreme ice storms

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年6月2日

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  • Yipei Zhao,
  • Qi Wang,
  • Wen Nie,
  • Shaowei Yang,
  • Xiangfen Cheng,
  • Yuanwen Kuang,
  • Jianfeng Liu

摘要

Background

Extreme ice storms (EIS) can severely disrupt forest productivity and stability, yet their differential impacts across forest types remain poorly understood, particularly in subtropical regions. Here, we assessed changes in gross primary productivity (GPP), resistance (Rt), and resilience (Rs) across evergreen needle-leaved forest (ENF), evergreen broad-leaved forest (EBF), deciduous broad-leaved forest (DBF), and mixed forest (MF) in mid-to-north subtropical China following two unexpected EIS events in early 2008 and 2018. Random Forest and Partial Least Squares Structural Equation Modeling (PLS-SEM) were used to identify key drivers and disentangle their underlying causal pathways.

Results

Except for DBF, both EIS events led to declines in forest GPP, with the stronger 2008 event exerting a more pronounced suppressive effect. Forest stability exhibited a clear Rt–Rs trade-off across forest types—the 2008 event was characterized by lower Rt but higher Rs, whereas the opposite pattern was observed in 2018. Among forest types, DBF showed the highest stability, while EBF exhibited the lowest. Freezing duration had contrasting effects between the two events: prolonged freezing duration significantly reduced Rt and Rs in 2008, but enhanced both in 2018. Moreover, freezing intensity, particularly minimum-temperature stress and cumulative precipitation, was the foremost determinant of forest stability, whereas geographical factors acted mainly indirectly through climate interannual variability, freezing intensity, and phenology. Furthermore, biological attributes made relatively modest overall contributions but provided important insights into forest-type-specific stability mechanisms. Specifically, phenology dominated DBF stability, whereas forest structure acted primarily through leaf area index in DBF and MF and through stand age in ENF and EBF.

Conclusions

Subtropical forest responses to EIS are highly heterogeneous and jointly controlled by disturbance intensity, forest composition, and spatial environmental context. By revealing the mechanisms underlying forest-type-specific stability responses to EIS, this study provides useful insights for differentiated risk-resilience management aimed at enhancing ecosystem stability and sustainable development.