Structural complexity and adaptability
Mature (complex) ecosystems are also said to have a higher exergystorage when compared to immature (less complex) systems
(Jørgensen 1992, Ludovisi 2014). Schneider and Kay (1994), based on data
from Luvall and Holbo (1989) provided evidence for this hypothesis based
on calculations of the exergy storage derived from remote sensing data
of forests in different stages of development. They showed that along
the gradient from a quarry without significant amounts of vegetation,
through a clear-cut site, a Douglas fir plantation, a natural secondary
forest to a 400-year-old Douglas fir-dominated forest the percent of net
incoming solar radiation not used for increasing the system’s
temperature, increased with the degree of ecosystem maturity. It was
argued that biological systems, through the optimization of processes in
terms of thermodynamic efficiency, reach a maximized capacity to store
exergy, which supposedly translates into a maximized ‘buffer capacity’
of the system or a maximized ability of the system to adapt to changing
conditions (e.g. Mejer and Jørgensen 1979, Jørgensen and Mejer 1981,
Jørgensen 2002). If so, this would have important implications for the
adaptation of forests to climate change. We hypothesize that
structurally complex forests can more easily adapt to changing climate
conditions than less complex ones. It remains to be tested whether they
are even less vulnerable and thus more resilient to climate changes.
However, the buffer capacity and the adaptive capacity (adaptability) do
not necessarily mean the same thing. While often used interchangeably in
literature, here we argue that ‘buffer capacity’ should be used when
referring to the ability to resist an external effect or disturbance
without system collapse or significant changes in system functions and
structure, e.g. a storm event that did not result in a large wind-throw.
Buffer capacity may therefore be the synonym to ‘ecological stability’,
originally defined in the 70’s as the ability to resist changes from the
outside (cf. Rutledge 1974, Rutledge et al. 1976). In contrast,
‘adaptability’, in our understanding, refers to the potential of a
system to adapt to a disturbance or altered conditions without losing
its integrity, e.g. a mixed-forests survives a bark-beetle infestation
since only a few percent of the tree species in the stand are
susceptible to the pest, the overall stand, however, continues to exist
as a modified version of its previous self. However, buffer capacity and
adaptability share that they are considered positive properties of an
ecosystem.
In any case, the question remains how a greater buffer capacity or
adaptive capacity of structurally complex forests may be explained. We
hypothesize that in case of a forest, complex structures are usually
related to the presence of many plant organs of different size, e.g.
leaves, twigs, regeneration, dominant trees, intermediate trees and
small trees in a given space. A large biomass is not necessarily related
to a high complexity, since most biomass is stored in the stems, which
contribute little to the stand level complexity. That is why previous
research in primary forests around the world showed that the structural
complexity and the basal area (as a proxy for biomass) of a forest, do
not necessarily correlate (Ehbrecht et al. 2021). Also, biomass alone is
not a satisfying proxy for the buffering or adaptive capacity of a
forest. In contrast, it was shown that beside climatic changes high
growing stock was an important factor when explaining the increased
disturbances in forests (Seidl et al. 2011). While maximization of
exergy storage might be achieved through ecosystem maturity (sensu
Ludovisi 2014), it is important to consider that large biomass combined
with low exergy storage was also described as an indication for a
sub-optimal system (Jørgensen et al. 1995, Bendoricchio and Jørgensen
1997). Note that optimal in terms of maximizing exergy capture is not
equivalent to the optimal in the sense of timber production where exergy
is usually low since biomass is preferentially allocated to stemwood.
Considering only the amount of biomass present in a forest is hence
likely not a suitable measure to quantify the efficiency of the energy
conversion in a forest system or its adaptive capacity.
For a high energetic efficiency, the amount of green (photosynthetically
active material) is likely a better proxy than the wooden biomass
stocked in the stand, since it is the leaves that capture the light,
delivering exergy to the tree while woody biomass deals with the energy
storage. Even for the quantification of energy storage it is unlike that
biomass alone is a good proxy, since wood-bound biomass does not contain
particularly much exergy that could be used for adaptational processes.
Wood rather stores anergy (energy not usable in the system; sensu
Nielsen et al. 2020) that cannot be mobilized easily, unless
decomposition takes over or the trees catch fire, releasing large
amounts of energy in the form of heat, not usable by the tree itself. In
contrast, fine roots, younger shoots, twigs and leaves possess a greater
ability to respond to altered conditions or disturbances, for example by
changing the growing direction or growing angle, halting or increasing
lateral growth, etc. Leaves and fine roots can even respond by modifying
the efficiency of resource use (Shipley and Meziane 2002). In addition,
it is in the leaves where trees perform stress relief through enzymatic
feedback systems when drought and high temperatures that result in
oxidative stress, need to be compensated by an antioxidant system
(Rennenberg et al. 2006) which requires exergy.