Optical traits perform equally well as directly-measured functional traits in explaining the impact of an invasive plant on litter decomposition.
Functional traits can help elucidate and predict the impact of invasive plant species on ecosystem functioning. Yet, this approach requires comprehensive and labour-intensive trait collection campaigns, covering intraspecific trait variation of both the invader and native species in the invaded community. One potential way to overcome these logistic constraints is using hyperspectral remote sensing technology to efficiently quantify functional trait values. Although such spectrally derived or 'optical' traits are known to closely link to directly measured functional traits, little research has explored how well these optical traits perform in assessing invader-induced ecosystem impact. Here, we explored the trait-mediated impact of the invasive Rosa rugosa on litter decomposition and evaluated whether optical traits perform equally well as directly measured traits in predicting litter decomposition variation. We collected data on species-specific functional traits, leaf hyperspectral reflectance and standardized 'tea bag index' litter decomposition across 25 invaded and 25 uninvaded coastal grassland plots. The selected traits were all potentially related to litter decomposition and covered the leaf economics spectrum, additional leaf structural components and competitive ability. Optical traits were quantified through a combination of a physical radiative transfer model inversion and vegetation indices calculations. Invasion significantly increased the stabilization factor, i.e. the amount of resulting recalcitrant litter. Invader impact on litter decomposition could be entirely explained by changes it induced in the functional traits of the native community, rather than by the invader's traits itself. More specifically, the invader pushed the invaded community towards traits associated with high litter quality. Optical traits performed equally well as directly measured traits in explaining the invasion impact on the stabilization factor (R2 = 41.9% vs. 38.5%). Furthermore, the interpretation of the results based on optical traits resulted in a similar functional understanding of the invader impact. Synthesis. Our results indicate the potential of hyperspectral data to explain changes in ecosystem functioning. The combination of radiative transfer models and vegetation indices allowed to extract all relevant trait information from the hyperspectral data. This framework thus presents a practical shortcut to assess relevant leaf traits, requiring only a limited amount of field trait measurements.