The relationship between species and spectral diversity in grassland communities is mediated by their vertical complexity. Issue 3 (13th August 2021)

• Record Type: Journal Article
• Authors: Conti, Luisa; Malavasi, Marco; Galland, Thomas; Komárek, Jan; Lagner, Ondřej; Carmona, Carlos P.; de Bello, Francesco; Rocchini, Duccio; Šímová, Petra
• Editors: Feilhauer, Hannes
• Is Part Of: Applied vegetation science. Volume 24:Issue 3(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-08-13
• Subjects: community scale -- grasslands -- height diversity -- mixed‐effect models -- multi‐spectral sensor -- remote sensing -- species diversity -- spectral diversity -- taxonomic diversity -- unmanned aerial vehicle (UAV) -- vertical stratification; Plant ecology -- Periodicals; Plant communities -- Periodicals; Plant populations -- Periodicals; Nature -- Effect of human beings on -- Periodicals; 581.705
• DOI: 10.1111/avsc.12600
• Languages: English
• ISSNs: 1402-2001

Abstract

Abstract: Aims: The link between spectral diversity and in‐situ plant biodiversity is one promising approach to using remote sensing for biodiversity assessment. Nevertheless, there is little evidence as to whether this link is maintained at fine scales, as well as to how it is influenced by vegetation's vertical complexity. Here we test, at the community level in grasslands, the link between diversity of the spectral signal ( S Div ) and taxonomic diversity ( T Div ), and the influence of vertical complexity. Methods: We used 196 1.5 m × 1.5 m experimental communities with different biodiversity levels. To measure vertical complexity, we quantified height diversity ( H Div ) of the most abundant species in the community. T Div was calculated using the Shannon index based on species cover. Canopy spectral information was gathered using an unmanned aerial vehicle (UAV) mounted with a multi‐spectral sensor providing spectral information via six 10‐nm bands covering the visible and near‐infrared region at a spatial resolution of 3 cm. We measured S Div in a core area of 1 m ×1 m within the communities as mean Euclidean distance of all pixels in a feature space spanned between the two first components of a PCA calculated for the complete raster stack. We modelled S Div through mixed‐effect linear models, using T Div, H Div, and their interaction as fixed‐effect predictors. Results: Contrary to our expectations, T Div was negatively linked to S Div . The diversity in plant height was positively related to S Div . More importantly, diversity in plant height and T Div had a significant negative interaction, meaning the more complex the vegetation was in terms of height, the more the S Div – T Div relationship became negative. Conclusions: Our results suggest that in order to exploit the S Div – T Div link for monitoring purposes, it needs to be contextualized. Moreover, the results highlight that communities' functional characteristics (i.e. plant height) mediate such a link, calling for new insights into the relation between S Div and functional diversity. Abstract : Can we use spectral diversity (SDiv) to estimate plant taxonomic biodiversity (TDiv) at fine scales? How is canopy vertical complexity (HDiv) influencing this relationship? Using grassland communities and UAV‐derived spectral information we found that TDiv negatively interacts with HDiv to explain SDiv. The more vertical complexity, the more the SDiv–TDiv relationship became negative, highlighting the importance of contextualizing the relationship.