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Integrating multi-source datasets in exploring the covariation of gross primary productivity (GPP) and solar-induced chlorophyll fluorescence (SIF) at an Indian tropical forest flux site

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Abstract

Accurate measurement and monitoring of ecosystem productivity play a pivotal role in comprehending the intricate dynamics of the Earth system, particularly in the light of anthropogenic forcing. Sun-induced chlorophyll fluorescence (SIF), serving as a proxy, has garnered attention for its potential to elucidate the dynamics of terrestrial productivity by the existence of its mechanistic link with photosynthesis. Nevertheless, physiological mechanisms that regulate the relationship between the dynamics of gross primary productivity (GPP) and SIF remain shrouded in mystery. To better accommodate the research community on GPP–SIF relation, our study attempts to offer potential results by integrating multi-source Earth observation SIF and in-situ eddy flux datasets at an ecosystem level in India. The results elucidate that the studied ecosystem consistently acted as a steady CO2 sink over the observed period, displaying a prominent double-hump seasonality and a solid correlation with SIF. Notably, this correlation was synchronous with the daily transitions of GPP. The integration of multi-source carbon fluxes and SIF datasets demonstrated a strong agreement with the in-situ data, reinforcing the reliability of our results. Our redundancy analysis by threshold binning underscores the significant positive influence of vapour pressure deficit (VPD) and photosynthetically active radiation (PAR), critical factors driving GPP and SIF, across a spectrum of temporal scales, ranging from the transient fluctuations of a day to annual panoramas. In essence, our study advocates for the synergistic utilisation of diverse datasets to unravel the underlying processes governing the relationship between GPP and SIF at multiple temporal scales. Our results and analyses are poised to propel interdisciplinary research forward by introducing novel dimensions to the GPP–SIF relationship in the Indian subcontinent.

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Data availability

Except for the in-situ eddy covariance data, which were processed with EddyPro (version 7.0.6, LI-COR Inc.) and TOVI (version 2.9.0, LI-COR Inc.), all the datasets used in this study are publicly available and can be accessed from the following web links. SMAP L4C data products: https://n5eil01u.ecs.nsidc.org/SMAP/SPL4CMDL.007/ (Kimball et al. 2021); CSIF: https://osf.io/8xqy6‌/files/ (Zhang et al. 2018); GOSIF‌: https://data.globalecology.sr.unh.edu/data/GOSIF_v2/8day/ (Li and Xiao 2019); SIF_LUE: https://jeodpp.jrc.ec.europa.eu/ftp/jrc-opendata/ECOCLIM/Downscaled-GOME2-SIF/v2.0/ (Duveiller et al. 2020); MODIS LAI: https://lpdaac.usgs.gov/products/mcd15a3hv061/ (Myneni et al. 2021). The SCOPE model (van der Tol et al. 2014) was accessed from https://github.com/‌Christiaanvandertol/SCOPE/ and processed with the ARTMO toolbox (Verrelst et al. 2016), available at https://artmotoolbox.‌com/radiative-transfer‌-‌models/88-rtm-leaf-canopy/17-scope.‌html. Landsat 8 accessed via the Google Earth Engine (GEE) platform, was used to perform land-use classification in Fig. 1.

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Acknowledgements

The authors are grateful to the Indian Institute of Space science and Technology (IIST) for providing the eddy covariance dataset. Additionally, the authors would like to acknowledge the National Institute of Technology Rourkela for their research support for this work and the doctoral fellowship provided to MH. The authors would like to thank Dr. Yunfei Wu and three anonymous reviewers for their constructive feedback and suggestions in improving the manuscript.

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Authors and Affiliations

  1. Department of Earth and Atmospheric Sciences, National Institute of Technology Rourkela, Rourkela, India

    Manoj Hari & Bhishma Tyagi

  2. Terrestrial Sciences Section, Climate and Global Dynamics, National Center for Atmospheric Research, Boulder, USA

    Manoj Hari

  3. Department of Earth and Space Sciences, Indian Institute of Space Science and Technology, Thiruvananthapuram, India

    Govindan Kutty

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  1. Manoj Hari
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Contributions

MH: conceptualization, writing—original draft preparation, review and editing, and visualization; GK: writing—review and editing, and supervision; BT: Conceptualization, writing—review and editing, and supervision. All the authors have read and approved the final manuscript

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Correspondence to Bhishma Tyagi.

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Hari, M., Kutty, G. & Tyagi, B. Integrating multi-source datasets in exploring the covariation of gross primary productivity (GPP) and solar-induced chlorophyll fluorescence (SIF) at an Indian tropical forest flux site. Environ Earth Sci 83, 232 (2024). https://doi.org/10.1007/s12665-024-11528-y

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