INTRODUCTION
Gross primary productivity (GPP)
is the rate at which solar energy is utilised by plants to capture the
greenhouse gas carbon dioxide (CO2) in the atmosphere.
Knowledge of GPP in diverse terrestrial ecosystems is critical for
quantifying the feedbacks of natural ecosystems to climate change and
predicting future climatic changes (IPCC, 2013; Falkowski et al., 2000;
Campbell et al., 2017; Quere et al., 2000).
Eddy covariance (EC) flux towers provide continuous and integrated
measurements of net ecosystem CO2 exchange from which
the ecosystem GPP can be estimated (Baldocchi et al., 2001; Baldocchi,
2003; Reichstein et al., 2005). Currently, over 900 flux sites across
the globe employ the EC technique to study carbon cycling in various
ecosystems, and much of this data can be found on the FLUXNET database
(fluxdata.org). Although the number of
sites with an EC system has been rapidly increasing in recent decades,
the monitored sites still account for only a small fraction of the
global ecosystems. This is largely due to: (1) the relatively small
footprint area of EC (i.e. usually within a radius of 1 km) and (2) the
lack of accessibility in many remote areas. Therefore, there is a need
for approaches that estimate GPP over extensive areas without EC
systems.
Process-based ecological models simulate GPP depending on environmental
variables that constrain plant photosynthesis (such as solar radiation,
temperature, precipitation, nutrient limits, etc.) and plant-specific
parameters (such as the maximum photosynthetic rate). However, these
models tend to be complex and need many parameters when compared with
empirical models (Loarie et al., 2011; Gustafson, 2013; Gitelson et al.,
2016; Jiang & Ryu, 2016; Lin et al., 2020). The different
parameterisations used in these models often result in large differences
in their estimated carbon dynamics (Cramer & Field, 1999; Lin et al.,
2017; Running et al., 2000).
Net radiation, which is the balance of total radiation input/output for
an ecosystem, indicates the energy that is retained within the system
over a given time period. In theory, the energy retained is partially
converted into heat that is transmitted throughout the system with the
rest being mostly fixed by plants through photosynthesis (Running et
al., 2004; Wu et al., 2010; Xiao et al., 2010). Therefore, we
hypothesised that a radiation index (RI) that reflects the proportion of
radiation energy fixed through photosynthesis is indicative of GPP. To
test this hypothesis, we developed an RI based on the radiation balance
and investigated its relationship with GPP at different temporal scales
using EC data from 54 sites of diverse terrestrial ecosystems. Due to
the easy access of radiation data globally through satellite-based
remote-sensing products (Monteith, 1972; Heinsch et al., 2003; Sjöström
et al., 2013; Xin et al., 2015), this radiation-based approach would be
an important alternative for GPP estimation, upscaling and prediction
and has the potential to be implemented globally.