“Flower power”: How flowering affects spectral diversity metrics and their relationship with plant diversity

^a Department of Spatial Sciences, Czech University of Life Sciences Prague, Kamýcká 129, 165 00 Praha-Suchdol, Czech Republic

^b Department of Botany, University of South Bohemia, Na Zlaté stoce 1, 370 05 České Budějovice, Czech Republic

^c Free University of Bolzano-Bozen, Faculty of Agricultural, Environmental and Food Sciences, Universitätsplatz 5 - piazza Universita, 5, 39100 Bozen-Bolzano, Italy

^d Department of Geoinformation, Swiss National Park, Runatsch 124, Chaste Planta-Wildenberg, 7530, Zernez, Switzerland

^e Department of Botany, University of Tartu, J. Liivi 2, 50409 Tartu linn, Estonia

^f Centro de Investigaciones sobre Desertificación, Universidad de Valencia, Crta. Moncada-Náquera Km 4,5, 46113 Moncada (Valencia), Spain

^g BIOME Lab, Department of Biological, Geological and Environmental Sciences, Alma Mater Studiorum University of Bologna, Via Irnerio, 42, 40126 Bologna, Italy

^h Department of Chemistry, Physics, Mathematics and Natural Sciences, University of Sassari, Via Vienna 2, 07100 Sassari, Italy

 

Abstract

Biodiversity monitoring is constrained by cost- and labour-intensive field sampling methods. Increasing evidence suggests that remotely sensed spectral diversity (SD) is linked to plant diversity, holding promise for monitoring applications. However, studies testing such a relationship reported conflicting findings, especially in challenging ecosystems such as grasslands, due to their variety and high temporal dynamism. It follows that a thorough investigation of the key factors influencing these relationships, such as the metrics applied (i.e., continuous, categorical) and phenology (e.g., flowering), is necessary. The present study aims to assess the effect of flowering on the applicability of six different SD metrics for plant diversity monitoring at the local scale and to investigate how spatial resolution affects the results. Taxonomic diversity was calculated based on data collected in 159 plots of 1.5 m × 1.5 m with experimental mesic grassland communities. Spectral information was collected using a UAV-borne sensor measuring reflectance across six bands in the visible and near-infrared range at ~2 cm spatial resolution. Our results showed that, in the presence of flowering, the relationship between SD and plant diversity is significant and positive only when SD is calculated using categorical metrics. Despite the observed significance, the variance explained by the models was very low, with no evident differences when resampling spectral data to coarser pixel sizes. Such findings suggest that new insights into the possible confounding effects on the SD-plant diversity relationship in grassland communities are needed to use SD for monitoring purposes.

 

https://www.sciencedirect.com/science/article/pii/S1574954124001316