Context <p>Landslide disturbances can leave long-lasting consequences for local ecosystems and slope stability. Given the likelihood of future changes in global landslide activity, identifying critical research gaps is essential for improving our ability to understand and predict such shifts.</p> Objectives <p>We aimed to evaluate the publication trends and methodological applications of landslide recovery studies, highlighting knowledge gaps and future research opportunities.</p> Methods <p>We conducted a systematic quantitative review of landslide ecology literature, identifying 205 relevant publications screened from the Web of Science and Scopus databases.</p> Results <p>Our knowledge of post-landslide vegetation recovery is limited by geographic biases and constraints in methodological applications, including the variables measured. The increase over time in landslide recovery publications coincides with a narrowing geographic focus towards Asia and an increasing reliance on remote sensing methods. Fieldwork provides critical fine-grain insight into these heterogeneous systems, but can be limited by scale, effort, and replication. Remote sensing applications are constrained by a lack of robust validation and trade-offs in sensor selection, leading to restricted spatiotemporal extents and limited use for monitoring vegetation structure and composition changes. These limitations constrain our ability to develop generalisable understandings of vegetation recovery trajectories for all regions affected by common landslide-occurrence.</p> Conclusions <p>Our review underscores the need for studies in underrepresented regions of high landslide susceptibility and increased attention to study design to develop a more robust and transferable understanding of landslide recovery trajectories. We highlight novel and improving technologies and datasets, possibilities for collaboration across disciplines, and the potential for cross-method integration as opportunities for expanding and improving future research.</p>

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Post-landslide vegetation recovery: research gaps and future opportunities

  • Elizabeth F. Williams,
  • Thomas P. F. Dowling,
  • Bruce R. Burns,
  • James M. R. Brock,
  • George L. W. Perry

摘要

Context

Landslide disturbances can leave long-lasting consequences for local ecosystems and slope stability. Given the likelihood of future changes in global landslide activity, identifying critical research gaps is essential for improving our ability to understand and predict such shifts.

Objectives

We aimed to evaluate the publication trends and methodological applications of landslide recovery studies, highlighting knowledge gaps and future research opportunities.

Methods

We conducted a systematic quantitative review of landslide ecology literature, identifying 205 relevant publications screened from the Web of Science and Scopus databases.

Results

Our knowledge of post-landslide vegetation recovery is limited by geographic biases and constraints in methodological applications, including the variables measured. The increase over time in landslide recovery publications coincides with a narrowing geographic focus towards Asia and an increasing reliance on remote sensing methods. Fieldwork provides critical fine-grain insight into these heterogeneous systems, but can be limited by scale, effort, and replication. Remote sensing applications are constrained by a lack of robust validation and trade-offs in sensor selection, leading to restricted spatiotemporal extents and limited use for monitoring vegetation structure and composition changes. These limitations constrain our ability to develop generalisable understandings of vegetation recovery trajectories for all regions affected by common landslide-occurrence.

Conclusions

Our review underscores the need for studies in underrepresented regions of high landslide susceptibility and increased attention to study design to develop a more robust and transferable understanding of landslide recovery trajectories. We highlight novel and improving technologies and datasets, possibilities for collaboration across disciplines, and the potential for cross-method integration as opportunities for expanding and improving future research.