Post-landslide vegetation recovery: research gaps and future opportunities
摘要
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.
ObjectivesWe aimed to evaluate the publication trends and methodological applications of landslide recovery studies, highlighting knowledge gaps and future research opportunities.
MethodsWe conducted a systematic quantitative review of landslide ecology literature, identifying 205 relevant publications screened from the Web of Science and Scopus databases.
ResultsOur 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.
ConclusionsOur 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.