Assessing plant biodiversity by remote sensing at different ecological scales

Michela Perrone

Doctoral thesis

Abstract:

Biodiversity monitoring is essential for ecosystem conservation, yet traditional field methods are often limited by high costs and labour intensity. The Spectral Variation Hypothesis (SVH) assumes a positive correlation between spectral diversity from optical remote sensing and species richness, based on the premise that areas with high spectral heterogeneity contain more ecological niches. Over the past two decades, SVH has been rigorously tested across various ecosystems using diverse remote sensing data, revealing both its potential and limitations. Through a systematic review and two empirical studies, this thesis aims to provide further insights into the relationship between spectral diversity and biodiversity, highlighting the factors and conditions that influence such a relationship, and propose guidelines for researchers to navigate the complexities of using spectral diversity for biodiversity monitoring across different ecosystems and spatial scales. Specifically, in this dissertation I 1) review and discuss recent methodological developments and uncertainties in applying the Spectral Variation Hypothesis (SVH) for biodiversity estimation, 2) investigate the applicability of SVH for monitoring plant diversity at the landscape scale by comparing different spectral diversity metrics, and 3) assess the impact of flowering and spatial resolution on the effectiveness of various spectral diversity metrics for plant diversity monitoring in grasslands. The findings of the studies presented in this thesis confirm the potential of spectral diversity when used to estimate biodiversity, but also highlight the limitations and weaknesses of SVH. Notably, its variable success depends on data characteristics and contexts. Moreover, the results of the empirical studies showed that the relationship between spectral and plant diversity is context-dependent and influenced by habitat type, phenology, and the metrics used to quantify spectral diversity. These findings underscore the need for careful consideration of specific factors and conditions when envisaging the use of spectral diversity for biodiversity monitoring.

Keywords

spectral variation hypothesis, biodiversity monitoring, UAV, grasslands, functional diversity, phenology

Language used: English

Date on which the thesis was submitted / produced: 3. 8. 2024

Thesis defence

• Supervisor: doc. Ing. Vítězslav Moudrý, Ph.D.
• Reader: Lucie Kupková, externi, Giovani Bacaro, externi, Anna Cord, externi

Czech University of Life Sciences Prague

Faculty of Environmental Sciences

Doctoral programme / specializace:
Environmental Earth Sciences / Spatial Sciences