Key stress indicators from chlorophyll fluorescence in five desert plant species

Chuan Jin; Tianshan Zha; Charles P.-A. Bourque; Peng Liu; Xin Jia; Yun Tian; Xinhao Li; Xinyue Liu; Xiaonan Guo; Mingze Xu; Xiaoyu Kang; Zifan Guo; Ning Wang

Ecological Indicators (Dec 2022)

Key stress indicators from chlorophyll fluorescence in five desert plant species

Chuan Jin,
Tianshan Zha,
Charles P.-A. Bourque,
Peng Liu,
Xin Jia,
Yun Tian,
Xinhao Li,
Xinyue Liu,
Xiaonan Guo,
Mingze Xu,
Xiaoyu Kang,
Zifan Guo,
Ning Wang

Affiliations

Chuan Jin: Yanchi Research Station, School of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, China
Tianshan Zha: Yanchi Research Station, School of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, China; Key Laboratory for Soil and Water Conservation, State Forestry and Grassland Administration, Beijing Forestry University, Beijing 100083, China; Corresponding author at: Yanchi Research Station, School of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, China.
Charles P.-A. Bourque: Yanchi Research Station, School of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, China; Faculty of Forestry and Environmental Management, 28 Dineen Drive, University of New Brunswick, Fredericton, New Brunswick E3B 5A3, Canada
Peng Liu: Yanchi Research Station, School of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, China
Xin Jia: Yanchi Research Station, School of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, China; Key Laboratory for Soil and Water Conservation, State Forestry and Grassland Administration, Beijing Forestry University, Beijing 100083, China
Yun Tian: Yanchi Research Station, School of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, China; Key Laboratory for Soil and Water Conservation, State Forestry and Grassland Administration, Beijing Forestry University, Beijing 100083, China
Xinhao Li: Yanchi Research Station, School of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, China
Xinyue Liu: Yanchi Research Station, School of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, China
Xiaonan Guo: School of Land Science and Space Planning, Hebei GEO University, Shijiazhuang 050031, China
Mingze Xu: Yanchi Research Station, School of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, China
Xiaoyu Kang: Faculty of Forestry and Environmental Management, 28 Dineen Drive, University of New Brunswick, Fredericton, New Brunswick E3B 5A3, Canada
Zifan Guo: Yanchi Research Station, School of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, China
Ning Wang: Yanchi Research Station, School of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, China

Journal volume & issue: Vol. 145
p. 109679

Abstract

Read online

Pulse-amplitude modulated chlorophyll fluorescence (ChlF) is widely used to measure environmental stress in plants. Yet, its continuous, long-term usage in situ is challenged due to the lack of appropriate daytime indicators. We investigated the prospect of creating new daytime indicators based on an application of linear regression on daily measurements of photochemical efficiency (ФPSII) and photosynthetically active radiation acquired in situ at 30-minute intervals. Daily regression parameters, thus generated, were subsequently used in a broader context of desert-plant response to environmental change. Here, we compared parametric and non-parametric methods to test the feasibility of daytime-based regression parameters, i.e., maximal quantum yield of photosystem II photochemistry (Fv/Fm) and daily mean ФPSII, in gauging physiological response in three shrub and two herb species as influenced by eight environmental variables. Results demonstrated that: (i) Random Forest (RF; a non-parametric method) provided the best assessment of interaction between ChlF-based parameters and environmental variables, compared with multiple linear regression (MLR; a conventional parametric method); (ii) variable importance and partial dependence plots indicated that the daily regression parameters of the ФPSII-to- photosynthetic photon flux density relationship (y-intercept and slope) were superior to those of ФPSII and Fv/Fm; and (iii) compared with Fv/Fm, the y-intercept and slope improved discrimination of interspecific differences (p < 0.05). Our research showed that the regression y-intercept and slope can serve as practical daytime indicators of desert-plant photosynthetic physiology in field applications of continuous ChlF measurements. RF is extremely skilled at capturing nonlinearities in eco-environmental interactions compared with standard parametric methods. This new method provides a basis for the collection of key ecological information in assessing desert-plant physiological response to environmental variability.

Published in Ecological Indicators

ISSN: 1470-160X (Print); 1872-7034 (Online)
Publisher: Elsevier
Country of publisher: United Kingdom
LCC subjects: Science: Biology (General): Ecology
Website: https://www.sciencedirect.com/journal/ecological-indicators

About the journal

Abstract

Keywords