Selection of chlorophyll fluorescence parameters as indicators of photosynthetic efficiency in large scale plant ecological studies

Many morphological, chemical and physiological indicators have been proposed to evaluate the conditions of plants in ecological systems. Among them, the analysis of the prompt fluorescence (PF) of chlorophyll is considered a powerful tool that combines the richness of the achievable information with the operational quickness. This technique is especially suitable in large ecological surveys, where it is required to screen many samples in a brief time. The PF allows evaluating photochemical properties and functionalities of photosynthetic organisms utilizing a set of parameters, known as ‘JIP-test’. The distinct phases of the photochemical processes in terms of energy absorption, trapping and electron transport can be described by these parameters. In this paper, we re-analyse large PF datasets obtained in past researches, carried out in field conditions (forests, plantations and pasture meadows) and in experimental setups (semi-controlled conditions). The aim was to explore the relationships (redundancy and independence) among the JIP-test parameters to select the most suitable ones to capture the variability of plant photosynthetic efficiency and their responses to environmental pressures. The Principal Component Analysis (PCA) was applied to 43,987 measurements. The overall PCA results evidenced that the variability of the PF parameters is explicated mainly by two factors, connected respectively to the processes of photon capture and first photochemical events, and to the efficiency of the electron transport around the photosystem I. This result suggests that, in ecological studies, the photosynthetic functioning of the member of a population can be effectively described with two parameters representative of these two phases: the maximum quantum yield of primary photochemistry of a dark-adapted sample (FV/FM) and the amplitude of the I-P phase (ΔVIP). FV/FM and ΔVIP probed to be independent and their correlation in various datasets may be either positive or negative in relation to the environmental factors considered. The physiological significance of the correlations between these parameters is discussed.