Seasonal changes in GPP/SIF ratios and their climatic determinants across the Northern Hemisphere

Abstract

Satellite-derived sun-induced chlorophyll fluorescence (SIF) has been increasingly used for estimating gross primary production (GPP). However, the relationship between SIF and GPP has not been well defined, impeding the translation of satellite observed SIF to GPP. Previous studies have generally assumed a linear relationship between SIF and GPP at daily and longer time scales, but support for this assumption is lacking. Here, we used the GPP/SIF ratio to investigate seasonal variations in the relationship between SIF and GPP over the Northern Hemisphere (NH). Based on multiple SIF products and | INTRODUC TI ONAccurately quantifying the dynamics of plant photosynthetic carbon inputs into ecosystems (e.g., gross primary production; GPP) at broad geographical scales is fundamental to understanding how global changes are influencing the Earth system (Beer et al., 2010;

Spatial and Temporal Effects of Wind Speed on Global Vegetation Growth

“…where slope is the change in SIF or GPP per year, x i is the value of SIF or GPP, n is the total number of years under investigation (n =18), and t i denotes the year from 2001 to 2018 (1)(2)(3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18). A positive (negative) slope value represents increase (decrease) in SIF or GPP.…”

“…The effects of meteorological factors on SIF and GPP are complicated. In the literature, there are lot of studies on analyzing the relationship between SIF/GPP and temperature, precipitation, or radiation at different scales (Chen et al 2021;Liu et al 2018;Xu et al 2021). SIF and GPP may be used as measures to study vegetation growth (Magney et al 2019;Guanter et al 2014) To provide a holist picture of wind speed effects on plants, SIF and GPP are used to evaluate wind effects on the growth of global vegetations in this work based on the Global Land Data Assimilation System (GLDAS)data, SIF and GPP data, and the Terra and Aqua combined Moderate Resolution Imaging Spectroradiometer (MODIS) Land Cover Climate Modeling Grid (CMG) (MCD12C1) Version 6 data product.…”

Exploring the Best-Matching Plant Traits and Environmental Factors for Vegetation Indices in Estimates of Global Gross Primary Productivity

“…The primary climate variables used in this study are shown in Table 1, either directly from this product or calculated from the variables provided by this product. It has been demonstrated that climatic circumstances might influence vegetation growth [38,[56][57][58][59], thus the climate factors for the current month, the previous month, and the previous two months were considered as input variables for the model.…”

“…This finding provides new insight for estimating ecosystem-scale GPP and encourages us to utilize SIF in carbon cycle research as a reliable proxy for GPP. However, as SIF products have only been available since 2000, the reasons for the variations in the relationship between SIF and GPP over time and space need to be clarified [37][38][39].…”

“…Accumulating evidence suggests that ecosystem-scale GPP is influenced by a combination of vegetation's biophysical properties [37,38,[40][41][42][43] and environmental factors [12,44,45]. Data-driven models based on machine learning are good at handling the interaction of individual factors and can achieve excellent prediction accuracy.…”