Discussion
The analysis on C. chinensis shows that the contributions of
various biotic and abiotic factors to individual physiological states
and population structure can be quantified by integrating various
information on population with DNA methylation analysis, and then the
population dynamics can be narrowly estimated.
During population development from expansion or early stage maturation
(in the recovering stand) to the top stage of maturation (in the native
stand), accompanied by the change of habitat environment and individual
DBH range, relative contribution of soil and spatial factors to
methylation decreased, and MVPS variation spatial autocorrelation of low
DBH subpopulations disappeared (Fig. 4a–d, Table 1). All of that
indicates that, following the development of C. chinensispopulation, the effects of soil and spatial factors on individual
development decline and population structure tends to disorder. The
spatial epigenetic and genetic autocorrelation represents the
aggregation distribution of functional group and kin individuals,
respectively (Wang et al ., 2012; Huang et al ., 2015). The
disappearance of epigenetic spatial autocorrelation, which accompanied
the decline in individual amount but increase in mean DBH (Fig. 1d-e),
indicates a functional self-thinning process. This functional
self-thinning may result from the competitive exclusion between same
functional individuals, then a functional diversity distribution around
high DBH individuals forms.
At an individual level, the positive and negative correlations of DBH
with the full-methylation rate and hemi-methylation rate are consistent
with the result that the relative growth rates decline as the DBH
increases in C. chinensis (Fig. 3a,b), because full-methylation
and hemi-methylations determine the repressed degree of individual
vitality and the potential of development reprogramming. Furthermore,
following the increase of edaphic N concentration and decrease of
edaphic AP concentration from the recovering stand to the native stand,
soil AP constraints aggravate (Fig. 1c) (Hou et al . 2014; Chenet al ., 2016; Turner, Brenes-Arguedas & Condit, 2018). However,
AP lost its significant effect on DNA methylation variation in the
native stand, in which over 75% individuals’ DBH is over 40 cm and the
DBH effect on total full-methylation rate rises to 8.3% through
interactions with environmental factors (Fig. 2b–g,
Table
1). DBH as an important plant phenotypic indicator may affect individual
physiological characteristics (Bustos‐Segura et al ., 2017). The
transformation of plant nutritional needs provides a new way for us to
redefine nutrient limitations during primary succession of soil
formation in subtropical forests (Fig. 2b–g, Table 1) (Turner et
al ., 2018). The temporal change on both from individual active to
inactive and the transformation of plant nutritional needs are
favourable for population maintenance.
The presented approach has several advantages. First, the statistical
data of genome-wide, methylation rates that determine individual
physiological state and the MVPS that determines the reaction model
represent individual characteristics well enough (Suzuki & Bird, 2008).
In addition, because the variation of methylation rate and MVPS are
direct-acting results of biotic and abiotic factors on individuals and
are the direct reason for individual physiological adjustment and
population structure change (Schubeler, 2015), all analyses do not
create uncertainty because of indirect relationships between variables.
Thus, the parsing results and their variation trends of the contribution
of various biotic and abiotic impact factors on individual DNA
methylation are the closest presentation for a logical and a time
relationship of individual development fitness to microhabitat.
Similarly, epigenetic spatial autocorrelation analysis results are the
intuitive description of population functional group structure.
Second, both the MRM analysis and multivariate variation-partitioning
analysis can be employed in non-parametric or non-linear analysis, and
their analytical precision can be improved by expanding the number of
explanatory matrices, allowing more environmental variables to be
represented by their own distance matrices (Goslee & Urban, 2007;
Oksanen, 2015). For example, as a stable influencing factor, topography
abidingly affects surface runoff and the distribution of soil elements
(Latiff, 2009) and also relates to light, humidity and temperature in
microhabitats. How topographic factors affect plant physiological
characteristics can be illuminated by adding those microenvironmental
and microclimate factor matrices into analysis after permutational
forward model selection.
Third, DNA methylation contains both instantaneous and cumulative
information (Suzuki & Bird, 2008; Heard & Martienssen, 2014;
Schubeler, 2015; Harrison et al ., 2016; Heer et al ., 2018;
Moler et al ., 2018). DNA methylation parameters in this research
were obtained from leaf organisation, which renewed their response
mechanism to both the instantaneous environmental condition and
age-related DBH indicator. The implications of this bilayer extend the
range of methylation research to individuals and populations on time
scales.
Many studies on the relationship between genetic structure and
epigenetic structure have reached different conclusions (Herrera,
Medrano, Mónica & Bazaga, 2016; Heer et al ., 2018; Moleret al ., 2018). For different spatial scales and different
species, the contribution of genetic background to DNA methylation may
be different. Therefore, that contribution should always be a noted in
research. On the other hand, C. chinensis has many common
characteristics of constructive species of a subtropical, evergreen,
broad-leaved forest, such as being perennial, outcrossing and occupying
the top space of the community. All those characteristics may reduce
genetic diversity within the population, and then the relationship
between genetic structure and epigenetic structure (Herrera et
al ., 2016; Moler et al ., 2018). Thus, the functional
self-thinning and its effect on population development and community
construction, which appears in C. chinensis populations, may
provide enlightenment in within-population research of other subtropical
constructive species.
The presented approach still has some room for improvement. First, DNA
methylation analysis can join with a next-generation sequencing platform
(Xia et al ., 2014). The new method can eliminate constraints
associated with the methylation-resolving power of the gel and explain
adaptive variation at gene level. Secondly, besides the three most
distinctive DNA methylation indicators used in this study, other DNA
methylation indicators, such as epigenetic distance between individuals,
also represent some detailed information on population function
diversity (Herrera et al ., 2016). How to integrate more DNA
methylation indicators into this presented approach is an interesting
topic.