|Remote sensing of salt marsh vegetation stress|| |
|Beschikbaar in || Auteur |
In this study we investigated methods to monitor stress in salt marshes to aid management. We focused on remote sensing techniques. We found that there no single vegetation index that is likely to represent stress well in all salt marshes, and that radar-based indices may perform better than reflectance-based vegetation indices in some systems. Therefore, stress monitoring will have to remain a very area specific task, and although remote sensing will be a valuable tool for these analyses, it will have to be applied by experts who understand the caveats of techniques.We like to plea for an increased scientific usage of vegetation structure data, both in remote sensing and in situ. Further development of these techniques and an increased understanding of these techniques are required before they can be applied to support management. We would argue for similar caution when applying recovery rate to estimate system stability or system stress.To salt marsh managers we would therefore recommend:• Use remote sensing to monitor stress development in salt marshes, but be sure to have a remote sensing expert and ecologist involved to ensure proper usage of vegetation indices and their interpretation.• Biomass is still a reliable way to establish stress, however due to its labor-intensive nature, it should be reserved for monitoring very vulnerable or critically important systems. Note that potential damage to the system should be taken into account• Aim to monitor the system as a whole, and include shifts in vegetation type.And scientists we would encourage to:• support managers by helping to interpret remote sensing data;• further explore how vegetation structure can be incorporated into monitoring schemes as a stress indicator;• further validate recovery rate as potential tool to estimate stress in salt marshes;• continue to develop the tools we present here, expand them to include other sections of the salt marsh to allow for broad ecosystem monitoring.