Assessing the impact of an invasive bryophyte on plant species richness using high resolution imaging spectroscopy

Invasive species are universally understood to have a damaging impact on native biodiversity and ecosystem health when they are able to establish themselves. A cohort of 11 researchers from across Europe and Columbia collaborated and successfully applied mass spectrometry to create a model of the spread and density of established invasive species in 2020—the final visual map meant to promote effective removal operations. The invasive bryophyte, commonly known as moss or Campylopus introflexus, is a firmly established invasive species in Europe. It creates a dense and nearly impenetrable surface layer that outcompetes native moss species and makes propagation of other native species difficult, especially in coastal dunes ecosystems where this species is particularly an issue. Researchers chose the coastal dune ecosystem on the island of Sylt, off the coast of Germany, and flew a drone equipped with a mass spectrometer to collect bryophyte cover in predetermined plots. The mass spectrometer was able to differentiate between native vegetation and the invasive species by identifying differences in leaf water content and structure, so only data on the invasive species was collected. Information collected by the mass spectrometer included cover and density, stored as raster data, and later modelled into a visual representation of cover on the dunes. The result is a striking map that researchers hope will allow land managers to take more informed action and make better decisions on where and how to remove this pernicious invasive species. Even though this research produced a useful product for land management, there are questions more broadly asked of research on invasive species meant to better understand but not take action on removing invasive species as quickly as possible. As useful as more information is, it should not prevent action from being taken against their removal.


Biodiversity, Data, Ecological Modelling, Monitoring, Visual Technologies