Can remotely sensed vegetation patterns signal dryland restoration success?

Samenvatting

Active restoration is frequently implemented to restore degraded drylands globally, yet predicting the overall success of these restoration projects remains challenging. Here, we aim to explore if vegetation spatial patterns can be used to monitor ecosystem recovery and anticipate the success of restoration practices. We combined field surveys and high-resolution drone images to analyze how vegetation spatial patterns change after the large-scale straw checkerboards restoration projects in the sand dune systems of the Tengger Desert in northern China. We found that vegetation cover, plant species richness, and diversity increased rapidly, approaching the level of the naturally vegetated sand dunes, after 5 years of restoration. Soil fertility remained low despite the positive vegetation change. Along with the recovery process, we found a larger diversity of patch sizes (i.e. spatial variance) with an increasing proportion of large-size patches. These patterns, combined with a constant positive recovery rate in vegetation cover, are consistent with theoretical predictions used to anticipate transitions to alternative ecosystem states. Although some indicators may be masked by the artificial planting scheme and community succession process during recovery, our results show that vegetation spatial patterns can be used to forecast and monitor the possible recovery of drylands.