Figure 5 . The feedback loop of plant response to complete
submergence. Here we consider floodwater with high turbidity so that the
light intensity for underwater photosynthesis is limited. The general
plant responses shown in black arrows deteriorate plant oxygen status
during complete submergence and may even lead to carbon starvation. The
“escape” strategy (pink box and pink arrows) imposes an overall
negative feedback loop on shoot oxygen but an overall positive feedback
loop on carbohydrate and energy reserve, while “quiescence” strategy
(purple box and purple arrows) imposes an overall negative feedback loop
on carbohydrate and energy reserve. Depending on the species and
ecotype, plants can either self-rescue through “escape” strategy or
self-preserve through “quiescence” strategy.
Discussion and concluding remarks
Our proposed model framework
considers the Soil-Plant-Atmosphere-Continuum as a “backbone”,
coupling hormone-mediated flooding-response processes to extend the
theoretical framework to the flooding scenarios, including waterlogging
and complete submergence. Efforts of integrating flooding response to
plant hydraulic and photosynthetic model have been made previously.
Compared to these efforts, e.g. , the model developed by Feddes
(1982) that phenomenologically simulated stomatal activity in response
to soil water content from drought to waterlogging and extended by more
process-based knowledge on oxygen stress (e.g. Bartholomeus,
2009), our proposed model framework attempts to step further by
introducing biological mechanistic processes under both drought and
flooding stress. These processes include oxygen dynamics in the root and
shoot and consequences for metabolism in these organs. Also, we include
hormonal signaling processes, in which the central hormone ethylene
accumulates within a couple of hours after waterlogging or submergence,
prior to occurrence of plant oxygen deficit. The hormonal signaling
processes resulting in either “escape” or “quiescence” impose a
negative feedback loop upon the main skeleton or abate the positive
feedback loop of the main skeleton, indicating a self-rescuing mechanism
or self-preservation mechanism, respectively.
For simplicity, plants in the proposed framework were assumed to be
mature. Except for adventitious root development and shoot elongation
that serve as specialized flooding-response morphological developments,
the growth of root and shoot is currently not considered. Furthermore,
we included a simplified set of hormonal signaling processes. The plant
stress response signaling network involved is highly complex, involving
a diverse set of hormones, secondary messengers, and genes, between
which there is a complex network of crosstalk (Sasidharan et al., 2018).
Classically the major phytohormones are subdivided into two categories,
the stress response hormones ABA, ethylene, salicylic acid (SA), and
jasmonate (JA), and the growth hormones gibberellin, cytokinin, and
auxin (Verma et
al.,
2016).
Phenotypically plastic stress responses often arise through the
crosstalk between these two categories of hormones. For instance, auxins
play a key role in root development, and their transport and signaling
is affected by ABA under drought
(Rock & Sun,
2005),
while under flooding stress, ethylene directly and/or indirectly affects
gibberellin signaling, triggering “escape” or “quiescence”
strategies, respectively
(Bashar et al.,
2019).
Here we propose to model the dynamics of the stress response hormones
and secondary messengers explicitly, incorporating their effects on
auxin, cytokinin, and gibberellin only implicitly. Specifically, we
propose to incorporate ABA, ethylene, and ROS, since the stress hormones
JA and SA mainly function against biotic stresses
(Verma et al.,
2016).
Given the aforementioned simplifications, we suggest that the proposed
framework can be used to model short-term (i.e. , days to a couple
of weeks) responses to drought and flooding stress. A key hypothesis we
propose this framework can test is that prior exposure to water stress
alters future stress responses through the occurrence of a “memory”,
which can be formed through both plant morphological changes and
preconditioning of hormone levels. For instance, when soil water
conditions shift from waterlogging to drought, aerenchyma formed during
waterlogging still exist inside the plant and are expected to impact
water transport
(Van der Weele et
al., 1996; Yang et al.,
2012).
Importantly, hormonal and physiological crosstalk is highly tissue and
species specific. As an example, it is found that an ethylene
pre-treatment enhances ROS scavenging capacity and thereby tolerance to
ROS mediated oxidative stress in roots
(Peng et al.,
2014).
On the other hand, in aerenchyma forming species, ethylene reduces ROS
scavenging to enhance ROS levels and induce aerenchyma formation in
specific cell types
(Steffens et al.,
2011).
It is exactly this complexity that makes predicting plant responses and
their potential dependence on prior conditions soil moisture conditions
across the full spectrum from drought to flooding impossible without
modeling the processes presented in our mechanistic framework.
A possible future extension of the mechanistic framework is to
incorporate the life history of plants and the changes in plant
architecture and physiology this results in, thus enabling the
simulation at longer time scales, say months to years or even decades.
Besides this extension on the temporal scale, we also envision
straightforward extensions one the spatial scale. This proposed
framework can serve to represent individuals within individual-based
models that scale up to the community and ecosystem level. Incorporating
only horizontal water transport this would already enable one to
investigate competition for water and the impact of species composition
and distribution on ecosystem water stress responses. Additionally,
these models can be extended to incorporate, e.g. , interplant
differences in their efficiency of nutrient and light acquisition and
their competition for these resources.
A natural application for our model framework is its incorporation into
land-surface models. So far, the incorporation of plant hydraulics into
land-surface models has been used to investigate the feedback between
climate and vegetation in terms of water cycle during non-stressed
conditions and drought, yet mechanistic plant responses to excessive
soil water content are still lacking in these models (Li et al., 2021;
Nguyen et al., 2020). With climate change expected to enhance surface
evaporation and atmospheric vapor accumulation, the intensity and
duration of droughts as well as the chances of flooding are both
increased, underlining the demand for a framework capable of integrating
both drought and flooding responses of plants (Trenberth, 2011).
Therefore, through incorporation of the model framework proposed here or
simplifications thereof into larger-scale land-surface models we aim to
contribute to the improvement of our understanding of how plants help
shape the climate.
Acknowledgements
This work was supported by the funding from the Complex Systems Fund of
Utrecht University, with special thanks to Dr. Peter Koeze.ORCID
Siluo Chen https://orcid.org/0000-0003-2152-9109
Kirsten H.W.J. ten Tusscherhttps://orcid.org/0000-0002-1945-7858
Rashmi Sasidharan https://orcid.org/0000-0002-6940-0657
Stefan C. Dekker https://orcid.org/0000-0001-7764-2464
Hugo J. de Boer https://orcid.org/0000-0002-6933-344X