Introduction
Trees may produce millions of seeds
over their lifespan
(Moleset al. 2004), yet the vast majority of those seeds will never
become adults. Most of them will disappear in early life stages, when
mortality is high
(Valen
1975; Petit & Hampe 2006), through herbivory, disease, lack of
resources like water
(Slot
& Poorter 2007), and maladaptation to their environment
(Donohueet al. 2010). Such high mortality rates should provide ample
opportunity for the action of natural selection
(Petit
& Hampe 2006; Donohue et al. 2010). Even though one must expect
that any given seedling has much higher chances to die than to survive,
identifying signals of adaptation to local micro-environmental
conditions in young seedlings is paramount to understand species and
phenotype distribution patterns. However, the causal links between
environmental heterogeneity, spatial distribution of species and
phenotypes, and local adaptation remain elusive in trees, mainly due to
the lack of long-term studies, low statistical power, and insufficient
understanding of the environmental factors determining local adaptation.
The study of seedling survival and
growth is a straightforward way to make inferences on performance
differences among tree species and populations
(Baralotoet al. 2005). The analysis of common gardens, with or without
the experimental application of environmental stresses meant to assess
genetically driven phenotypic response variations in populations, is
common practice. They make possible to compare the performance of
individuals from different habitats
(Valladares & Sánchez-Gómez 2006;
Brousseau et al. 2013; Barton et al. 2020), populations
(Ramírez-Valiente et al. 2009;
Carsjens et al. 2014; Barton et al. 2020), or species
(Lopez & Kursar 2003; Poorter &
Markesteijn 2008; Queenborough et al. 2009) to test for local
adaptation signals in traits of interest
(de Villemereuil et al. 2016
for a review). In several cases however, adaptation is not proven
(Lopez & Kursar 2003; Lópezet al. 2009; Queenborough et al. 2009) or give
counter-intuitive (Poorter &
Markesteijn 2008; Pineda-García et al. 2011). Common gardens and
experimental stresses may nevertheless not exactly replicate conditions
experienced by seedlings in the wild, leading to possible biases in the
conclusions drawn about divergence and trait/survival response to
stress.
Reciprocal Transplant Experiments
(RTE), whereby seeds or seedlings are translocated between sites in the
field and grow in the same conditions as natural regeneration, may be a
better option to observe adaptive processes as they occur in wild
conditions, albeit sometimes with higher implementation costs and larger
variance in the estimation of parameters as experimental conditions are
less strictly controlled. RTEs are an elegant way to test the hypothesis
of a link between habitat variation and species or phenotype
distribution, because they allow observing performance variance directly
across an array of environmental factors
(Morris et al. 2007). These
differences in performance components (i.e. survival, growth, and/or
reproduction) between populations in different environments can be
interpreted directly in terms of adaptation, based on straightforward
theoretical expectations: local adaptation is found when local
populations perform better than transplanted ones (the ’local vs.foreigner’ condition) and any given population performs better in its
own provenance than elsewhere (the ’home vs. away’ condition)
(Kawecki
& Ebert 2004). Local adaptation can be further nuanced depending on the
generality of patterns across the system: if ‘local’ individuals always
outperform ‘foreign’ individuals for all populations and conditions,
then genetic trade-offs are orchestrating the patterns of local
adaptation; if, however, some populations perform better at ’home’, but
are not penalised elsewhere, then conditional neutrality may underpin
the local adaptation (Anderson
2013). The two processes are not mutually exclusive and may coexist for
different traits within a given system
(Wadgymaret al. 2017).
In trees, conclusions from RTEs on
local adaptation, mostly tested in seedlings due to the long lifecycle,
are diverse: evidence of local adaptation to particular environmental
parameters has been identified for a wide range of tree species
(Fine et al. 2006; Wright
2007; Pizano et al. 2011; Pluess & Weber 2012; Smith et
al. 2012; Baltzer & Davies 2012; Nagamitsu et al. 2015; Pluesset al. 2016; Mathiasen & Premoli 2016; Rellstab et al.2016; Barton et al. 2020); while the expected signals of local
adaptation to, at least some environmental conditions, were not observed
in other studies (Boshier & Stewart
2005; Eichhorn et al. 2006; Vizcaíno-Palomar et al. 2014;
Latreille & Pichot 2017); In addition, RTEs have also shown that stark
morphological differences between tree ecotypes may be due to purely
phenotypic plasticity with no evidence of genetic influence
(Fanget al. 2006). These results show the complexity of the
relationship between environmental conditions and phenotypic traits
through plasticity and local adaptation processes. The main constraint
in interpreting the results obtained from RTEs is that one can only
observe differential adaptation to a bundle of ecological factors that
differ between habitats. By designing RTEs that cross more than one
factor (e.g. differences in climate, soil properties,
competition, and predators) one may be able to tease apart at least
subsets of covarying ecological factors
(Wadgymaret al. 2017). Such type of approach is thus extremely useful for
understanding the mechanisms for spatial heterogeneity, which in turn is
essential for the construction of predictive models of spatial
distribution of species/phenotypes.
Lowland Neotropical forest, such as
those in French Guiana, show a highly variable and complex mosaic of
microhabitats linked to variations in topography and soil
characteristics. Differences in water drainage has been long identified
as a main ecological factor driving the tree community composition on
the Guiana shield (Barthes 1991; ter
Steege et al. 1993; Sabatier et al. 1997), allowing to
position the species along a gradient of tolerance to prolonged water
saturation of soil porosity and a gradient of tolerance to temporary
water saturation (Pélissier et
al. 2002). All these studies show that the most striking variations in
tree species distribution at local scale result from the widespread
gradient between seasonally flooded (SF) habitats along streams and all
other surrounding habitats on slopes and hilltops (HT). These studies
also showed that congeneric species often display opposite niche
preferences across such gradients, as was pointed out by Allié et
al. (2015). A typical example is
provided by the genus Symphonia of African origin, with the
species S. globulifera, widespread across the Neotropics, and a
morpho-taxon of yet undetermined status, currently identified asS. sp1 , which is known to occur in the Guiana shield. Adults of
the two taxa, referred hereafter as ’ecotypes’, are found in sympatry,
often with intermingled crowns, but are environmentally segregated, withS. globulifera being strongly linked to SF habitats, whileS. sp1 is found on both HT and SF
(Alliéet al. 2015; Schmitt et al. a. in review ;),
The two ecotypes are differentiated by the size of their leaves,
flowers, and fruits, the texture of their bark, the presence of
pneumatophores or prop roots
(;
Baraloto et al. 2007 Schmitt et al. b. in review ), as well
as differences in maximum diameter at breast height and growth rates
(Héraultet al. 2011). Whether these morphological differences are the
product of environmentally driven phenotypic plasticity or genetically
determined is not yet known. The system constitutes an extreme case of
microgeographic differentiation, and potentially, adaptation
(Richardson et al. 2014), as
trees of the two ecotypes are distributed in mosaic patches smaller than
the pollen dispersal potential (20-50m)
(Degen et al. 2004). The two
ecotypes are genetically differentiated based on nuclear microsatellites
(FST =0.086), although less so than African and
South American population of S. globulifera(FST =0.31)
(Torroba-Balmori et al.2017), or even than Neotropical population of S. globulifera(FST =0.138)
(Dick & Heuertz 2008)The two
ecotypes follow thus different evolutionary paths and may show genetic
variants associated with adaptations to different habitats, but,
genetically intermediate individuals (F1, F2, etc.) have been observed
(N. Tysklind – unpublished data) suggesting that some mixing of the two
ecotypes occurs in the field, leading us to believe thatSymphonia operates as a syngameon in French Guiana. Syngameons
were defined by botanists during the XXth century
(Lotsy 1917; Grant 1971) to describe
closely related plant species that are interfertile despite the presence
of morphologically distinct groups classified as different species. This
term covers today the most inclusive interbreeding evolutionary unit
(Suarez-Gonzalez et al.2018), of which oak is one of the best representatives
(Cannon & Petit
2019). The genetic differentiation
between Symphonia ecotypes is smaller than among members of the
oak syngameon (FST (SNPs)=0.13
(Lang et al. 2018).
Previous shadehouse common garden experiments
(Baralotoet al. 2007) could not pinpoint differential physiological
responses to drought and flooding between the two ecotypes, and thus the
heterogeneous spatial distribution of Symphonia is not explained
by these alone, at least as far as experiments in artificial conditions
can tell. Nevertheless, mortality was higher in S . sp1after six weeks of controlled flooding, and wild S. globuliferaseedlings tended to survive better in SF areas in the
wild
(Baraloto et al. 2007). To
dissect the causes of the observed association of the two ecotypes with
habitats, we established an RTE, considering both habitat and provenance
region, in the field under the natural canopy. We hypothesise that
germination, growth, herbivory defence, and survival, or a combination
of these factors, are better for each ecotype and provenance in its
habitat of origin than in other habitats; we argue that such differences
contribute to explain the niche distribution patterns observed in the
wild.
Materials and Methods
Experimental design and data collection:
The experimental design aimed to
collect seeds from mother trees from two contrasting habitats and the
associated ecotypes: SF-S. globulifera and HT-S. sp1; and
from two broad regions with markedly different rainfall patterns:
’east’, with the highest rainfall in French Guiana, and ’west’, the
driest part of French Guiana (Fig. 1). Seeds were transplanted onto
experimental gardens installed on HT and SF habitats at two field sites
in the ’east’ and ’west’ regions, respectively, which were not among the
sampled sites for the seeds.
Seeds were collected between September
2008 and April 2009, due to largely unequal flowering times, from nine
mother trees belonging to both ecotypes in the ’western’ region and from
five mother trees in the ’eastern’ region, composing the variables
“Provenance region” and “Ecotype” (Table 1). From each mother tree,
35-39 seeds were collected and sown in polypropylene germination plates
with soil in a common shadehouse at the Kourou Agronomic Campus prior to
transplantation into field sites between May and July 2009. This meant
that seeds spent between 27 and 315 days in the shadehouse, depending on
the seed collection and transplant dates. This introduced substantial
differences among groups in the number of days spent in the shadehouse
(Fig. 2a), the proportion of seeds that had germinated (i.e. at
least cotyledons emerged from ground), as well as in the developmental
stage reached by the germinated seedlings, at transplantation time.
Although such differences among groups are likely to originate from
ecological differences in flowering time, they can be viewed as biases
in analyses. First of all, comparisons of germination trends among
groups must be interpreted according to this bias; secondly, germination
rates themselves must be included as an important cofactor, in its turn
carrying information about amount of time spent in shadehouse, in the
life history and growth-associated traits analyses. See below for how
biases in seed collection were incorporated into the analysis of
germination rates, and for how differences in germination status were
considered in the analyses of other traits. Whether seeds had germinated
at the moment of transplant or not was stored in the variable
“transplant status”. The moment at which individual seeds were first
recorded as seedlings (e.g. moment of transplant, year 1, year 2,
year 3, etc.) was stored as “germination timing”. To avoid confusion,
we hereafter refer to “seed” when discussing aspects regarding the
phase prior to germination, “seedling” for those aspects regarding the
phase after germination, and “individual” for those aspects regarding
both seed and seedling phases.
Individuals (i.e. seed or seedling) were transplanted to gardens
established at each field site (i.e. east vs. west) and
habitat: three in SF and three in HT conditions in each site, totalling
12 gardens. Field site plantation and habitat compose the variables
“Plantation region” and “Habitat”, respectively (Table 2; Fig. 1).
Each garden was fenced from large herbivores with chicken wire. Prior to
transplanting, all understory vegetation (i.e. up to 5 cm D.B.H.) was
removed; the canopy was left undisturbed. Regeneration other than the
transplanted seedlings was removed yearly by hand. Individuals were
distributed over the twelve gardens as follows: each garden was arranged
in 44 ten-seedling slots. In each garden, six slots were randomly
attributed to Symphonia (the remaining slots were used for other
experiments), and then three individuals per mother plant were assigned
to random positions within those slots in each garden. Individuals were
allocated to different gardens depending on their provenance, ecotype,
plantation region, and habitat without differentiating between those
that had germinated in the shadehouse and transplanted as germinated
seedlings or those transplanted as ungerminated seed (Table 2). Data for
each individual (i.e. germination status at transplantation,
germination year, survival, growth-associated traits, and herbivory)
were collected at transplant date and then yearly in September from 2009
until 2014, except for 2012 (Suppl. Table 1). Individual survival was
recorded as follows: 1 for seedlings found alive and 0 for ungerminated
seeds transplanted to field sites and yet to germinate, and for
seedlings previously living but found dead. Seedling height was measured
in centimetres between the apical bud and the collar. Stem diameter was
measured in millimetres at the collar in two orthogonal directions and
estimated as the mean of the two measures. As an architectural trait, we
selected “total number of leaves”, an indicator of seedling leafiness.
Herbivory was determined as follows: each leaf was assigned one of five
classes of percentage of damaged area (0-20%; 20-40%; 40-60%;
60-80%; 80-100%) and then seedling herbivory attack level was
estimated as the average of the percentage of damaged area of all its
leaves (Suppl. Table 1).
Data analyses:
Two complementary analytical strategies were applied to the data to
extract the biological significance of individual germination, survival,
and performance depending on the studied predictor variables: a) random
forest methods were used to explore variable importance, untangle and
understand the structure of interactions among the covariates, and
graphically visualise their effects on the dependent variables; and b)
Linear model and Generalized linear model (GLM) were used to find
general effects of predictor variables on the dependent variables. More
specifically, we introduce a test based on the least-squares means, also
named adjusted means (Searleet al. 1980), which allows us to compare the effect of growing in
their ‘home’ habitat vs. ‘away’ habitat and of being ‘local’vs. ‘foreigner’ in a given habitat, while averaging for other
potential effects to make such comparisons meaningful and reduce the
confusion of effects.
Random forest analyses:
Random forest methods and
classification trees were applied to evaluate relative variable
importance in explaining germination, survival, growth, leafiness, and
herbivory on individuals at the end of the experiment (year 6) and the
average yearly relative growth rate (RGR), untangle interactions among
the predictor variables, and graphically visualise their effects on each
of the responses. Random forest methods
(Breiman
2001) are particularly suited for data where nonlinear relationships and
complex interactions among variables are expected
(Cutleret al. 2007). Classification trees visualize predictive models of
responses significantly dependent on predictor variables. This is
achieved by recursive binary classification of the data, where
independence of the response (i.e. here germination, survival, growth,
leafiness, and herbivory) and the covariates (i.e. here provenance
region, ecotype, plantation region, habitat, and transplant status) is
tested; then, if a significant dependence is found, the best split value
for the predictor variable with the strongest effect is retained and
used to divide the response in two groups. The process is then repeated
with each of the groups, recursively, until no significant dependence
between covariates and response can be found
(Hothornet al. 2006). In a random forest, the above classification
tree is performed on a bootstrap subset of the data and a reduced number
of predictor variables to obtain response predictions based on a
majority vote of the whole forest. Such methodology allows assessing
relative variable importance, by identifying those covariates which,
when removed, ensue a significant drop of prediction power
(Stroblet al. 2007). In our case, it allows us to identify if certain
combinations of variables (e.g. S. globulifera in SF) lead to
significant improvement of performance of ‘home’ or ‘local’ individuals.
We repeated the analyses including all the predictor variables as
explanatory variables and removing transplant status (i.e. seed
or seedling) to check if transplant status confounded the analysis of
the impact of the covariates of interest (i.e. provenance region,
ecotype, plantation region, and habitat). Furthermore, we evaluated the
effects of provenance region and ecotype on shadehouse germination
rates, and of all predictor variables on the germination rates of
individuals planted as seeds in the field (Supplementary material 1).
For the random forest analyses of growth performance and
herbivory, only individuals germinated in 2009, whether in the
shade-house or in the field and having a final measure in 2014 were
analysed. Therefore, each individual has a unique discrete value for
each trait in 2014, that is at age 5 (i.e. year 6). The average yearly
relative growth rate (RGR) in height, diameter, and leafiness as well as
the average herbivory were also summarised over the life of the
individual, giving each individual a single value over the course of the
experiment.
All analyses were run in the R
statistical environment (R Core Team
2020) with the package ‘party’
(Hothornet al. 2006; Strobl et al. 2009). Conditional inference
trees were also grown in party with an α = 0.05 and a minimum of 2
observations in each branch.
Linear models and general linear model
analyses:
Linear model (LM) and generalized
linear model (GLM) were additionally used to test the potential effects
of different predictor variables on traits (i.e. germination,
survival, growth, architecture, and herbivory), and most importantly to
define an ad-hoc procedure to test local adaptation by subsuming in a
single test both the ‘home vs. away’, and the ‘local vs.foreigner’ tests of Kawecki and Ebert
(2004),
while averaging over all possible other effects to disentangle the
effect of the unbalanced final design. Our approach, as described below,
aims at synthetically observing the effect of having been planted in the
environment of provenance or in a different environment, in itself, on
traits taken as proxies for individual performance. This contrasts with
previous strategies for the detection of local adaptation, which rest on
the separate analysis of the “home vs. away” and “localvs. foreigner” effects and deduce the presence of the effect
from slope comparisons (i.e. , they test for population x
environment interactions). In the wording of Kawecki and Ebert
(2004),
our method is tantamount to comparing the means of “‘sympatric’ and
‘allopatric’ deme-habitat combinations”. While confounding the effects
of “true” local adaptation and of global superiority of one population
relative to all others
(Kawecki
& Ebert 2004), our LM/GLM approach has the comparative advantage of
better coping with unbalanced design and, possibly, having greater
power.
We denote e the ecotype (e = 1 for S. globuliferaand e = 2 for S. sp1 ), h the habitat (h = 1
for SF, and h = 2 for HT, so that individuals growing at ’home’
are specified by 11 or 22), o for provenance region (o = 1
for east and o = 2 for west), r for the plantation region
(r = 1 for east and r = 2 for west), s for the
transplantation status (s = 1 if transplanted as a seed ors = 2 for transplanted as a seedling), and finally, a for
the age of the considered individual (a = 1, …, 5). The full
model for growth-associated traits (i.e. seedling height, stem
diameter, leafiness, and herbivory) might be expressed as a normal
response Yehorsa ~ N(
μehorsa , σ2), while binary responses
like the life history traits, germination and survival, are expressed as
a Bernoulli distribution with probability of successpehorsa. In the following text, we show the
development of formulas for the ecotype/habitat case, with subscriptse for ecotype and h for habitat, as described above;
formulas for the provenance region / plantation region case are
identical, except that they bear subscripts o for provenance
region and r for plantation region, as described above, and will
not be further described here.
Germination success in the shadehouse and
overall germination (G ):
In the evaluation of the difference in germination success (G ) in
the shadehouse, individuals have not yet been transplanted, therefore,
the only effects to account for were genetic effects: ecotype and
provenance region. However, the time spent in the shadehouse depends on
the collection and should be accounted for. The logit of the probability
of germination (G ) of the kth seed is
given by:
\begin{equation}
\text{logit}\left(p_{\text{eok}}^{G}\right)=u^{G}+\alpha_{e}^{G}+\delta_{o}^{G}+\varepsilon_{\text{eo}}^{G}+\nonumber \\
\end{equation}
Where t stands for the time spent in the shadehouse.
To correct the effects of unbalanced design and difference in time in
the shadehouse, the effect of ecotype (e ) on the difference in
germination success (G ) in the shadehouse, has been studied by a
comparison of the classical least square means of ecotype:
\begin{equation}
{\text{logit}\left(p\middle|\middle|adj,G\middle|\middle|e\right)}=u^{G}+{\alpha^{G}}_{e}+\left(\beta\middle|\middle|G+{\gamma^{G}}_{e}\right)\acute{t}+\frac{1}{2}\sum_{o}{\delta^{G}}_{o}+{\xi^{G}}_{\text{eo}}+{\eta^{G}}_{o}\acute{t},\left(2\right)\nonumber \\
\end{equation}
where (\(\acute{t}\)) is the average time spent in the shadehouse.
The same approach using least square means is used to study the overall
germination except that we don’t account for the time in the shadehouse.
In case of germination success, a GLM approach is used to study the time
of germination. The response is modelled through a geometric
distribution and the log link function. Least Square Means are used to
compare the expected time of germination.
Survival
(S ):
To evaluate differences in survival (S ) among ’home’ and ’away’
groups, we developed the following approach: assuming the survival
probability is constant over a year, the observed maximal age might be
modelled as a geometric distribution whose probability of success,pSehors , depends on ecotype
(e) , habitat (h ), provenance region (o ), plantation
region (r ), and the transplantation status (s ). The
least-squares means for the log odd ratio of such probability is given
by:
\begin{equation}
\text{logit}\left(p\middle|\middle|adj,S\middle|\middle|\text{eh}\right)=u^{S}+{\alpha^{S}}_{\text{eh}}+\frac{1}{8}\sum_{o,r,s}{\delta^{S}}_{\text{ots}}+{\zeta^{S}}_{\text{ehors}},\left(3\right)\nonumber \\
\end{equation}
where αSeh stands for the joint
effect of ecotype and habitat,δSors stands for all other
effects like the provenance region, plantation region, and the
transplantation status, and \({\zeta^{S}}_{\text{ehors}}\)the
interaction between those different effects on the survival probability.
Growth-associated traits:
As the aim of the analysis of growth-associated traits is identifying
the potential effect of the growing ’home’ vs. ’away’, the meanμehorsa has to reveal the joint effect of ecotype
and habitat; the joint effect of provenance region, plantation region,
and transplantation status; and the age effect as well as all
interactions between any two of these variables. Therefore, for any
growth-associated trait (Y), μehorsa might be
expressed as:
\({u^{Y}}_{\text{ehorsa}}=u^{Y}+{\alpha^{Y}}_{\text{eh}}+{\delta^{Y}}_{\text{ors}}+\left(\beta\middle|\middle|Y+{\gamma^{Y}}_{\text{eh}}+{\theta^{Y}}_{\text{ors}}\right)a\)(4)
where
- \({\alpha^{Y}}_{\text{eh}}\) stands for the joint effect of ecotype
and habitat, with a total of 4 possible different combination of ecotype
x habitat
- \({\delta^{Y}}_{\text{ors}}\)stands for all other controlled effect
like the provenance region, the plantation region, and transplantation
status for a total of 8 possible different levels,
- \(\beta^{Y}\) is the effect of age,
- \({\gamma^{Y}}_{\text{eh}}\) is the differential effect of age
according to the ecotype/habitat level,
- \({\theta^{Y}}_{\text{ors}}\) is the differential effect of age
according to the provenance/plantation region/transplantation status
levels.
Interaction between main effects of interest (i.eecotype/habitat) and other controlled effects have not been incorporated
as not all combinations have been observed.
To detect signals of local adaptation in growth-associated traits, we
compared the effects of growing at the ecotype’s (or provenance’s)
’home’ habitat vs. growing in the ’away’ habitat. Such comparison
was achieved by defining least-squares means at age aμehadj(a) (Russell V. Lenth,
2016) to account for the unbalanced design:
\begin{equation}
{u^{adj,Y}}_{\text{eh}}\left(a\right)=u^{Y}+{\alpha^{Y}}_{\text{eh}}+\left(\beta\middle|\middle|Y+{\gamma^{Y}}_{\text{eh}}\right)a+\frac{1}{8}\sum_{o,t,s}\left({\delta^{Y}}_{\text{ors}}+{\theta^{Y}}_{\text{ors}}a\right)\left(5\right)\nonumber \\
\end{equation}
The comparison between ‘home’ and ‘away’ habitat-ecotype pairs is
performed age by age by forming the following contrast:
\(C_{a}=\left(u_{11}^{adj,Y}\left(a\right)+u_{22}^{adj,Y}\left(a\right)\right)-\left(u_{12}^{adj,Y}\left(a\right)+u_{21}^{adj,Y}\left(a\right)\right)\)\(\left(6\right)\)
which quantifies the difference of an average individual growing at
’home’ (combination 11 or 22) and an average individual growing ’away’
(combination 12 or 21).
All GLM analyses were run in the R
statistical environment with the packages ‘car’
(Fox
& Weisberg 2010), ‘multcomp’
(Hothornet al. 2008), ‘emmeans’
(Lenth 2016, 2018), and visualized
using ‘ggplot2’
(Wickham
2009).
Results
Description of the data:
A total of 510 individual Symphonia were followed over the course
of 6 years. Of these, 36.1% had germinated at the time of transplant
and were transplanted as seedlings. The remainder were transplanted as
seeds. Overall germination reached 61.2% by the end of the experiment
(Table 1). At the end of the experiment 37% of seedlings were alive,
and survival was lowest in western SF gardens (Table 2). Summary
statistics of growth-associated traits (i.e. height, diameter, total
number of leaves) and average herbivory over the course of the 6 years
for those individuals germinated in 2009 and still alive at the end of
the experiment are reported in Table 3.
Impact of the transplant status on survival: seeds vs.
seedlings.
The classification tree analysis of the success of germination
(Supplementary material 1) indicated strong effects of the provenance
region independently of the transplant status: seeds having germinated
in the shadehouse or seeds having germinated in the field. The same
result was observed using GLM when considering the global success of
germination (i.e. whatever the transplant status, all the seeds
that have germinated at some point, during the 6 years of the
experiment). Since the main effect tested was observed in both the seeds
that have germinated in shadehouse and the seeds that have germinated in
the field, the two transplant statuses were merged together for the rest
of the analyses.
Effects of covariates on germination and survival of
Symphonia
seedlings
To overcome the bias in duration of time at the shadehouse among the
different ecotype x provenance groups (Fig. 2a), we compared the
probability of germination success in the shadehouse of the two ecotypes
depending on the region of provenance after the average time in the
shade house (i.e. 89 days). A significantly lower probability of
germination success in the shadehouse was identified for westernS. sp1 compared to all other groups (Fig. 2b), even when
accounting for the difference in time in the shadehouse. However, the
analysis of overall germination (i.e. shadehouse and field
combined) indicated that provenance and plantation habitat, rather than
ecotype, were the main drivers of the variance in germination success
(Fig. 2c and Fig. 3). The analysis of the delay on germination showcases
that provenance also had a strong impact on the timing of germination
(Fig. 2d), where seeds from the west germinate significantly later than
those from the east (west: 13 months vs. east: 3 months).
In terms of overall germination and survival, classification trees
identified that provenance region, plantation region, habitat, and
ecotype as significant variables explaining overall germination and
survival of individuals at the 5% threshold, exposing the complexity of
the interactions among predictor variables (Fig. 3). Provenance had the
strongest impact, where most individuals from the east (Fig. 3, nodes 9,
10, 11) had germinated, while those from the west systematically
suffered from lower germination rates (Fig. 3, nodes 2, 3, 4, 5, 6, 7
and 8). Eastern provenance individuals planted in the east plantations
survived significantly better than when planted in the west (Fig. 3,
node 9). Western provenance individuals survived better in the east than
in the west (Fig. 3, node 2). Germination and survival were lowest for
western provenance individuals, planted in the west in SF habitats,
regardless of ecotype (Fig. 3, node 4). Finally, for western provenance
individuals, planted in the west, in HT habitats, there is a significant
ecotype effect, where S. sp1 (i.e. ‘local’) germinates and
survives significantly better (Fig. 3, node 6) than S.
globulifera (i.e. ‘foreign’) (Fig.3, node 7).
Effects of predictor variables on growth-associated
traits of Symphonia
seedlings
According to the classification trees, ecotype had the strongest
significant effect on 5 out of 7 growth-associated traits and herbivory:
average RGR height, diameter, total number of leaves, and average RGR in
number of leaves, and average relative herbivory, separating S.
globulifera from S. sp1 (Fig. 4). S. sp1 grew faster
(Fig. 4b, 5a,b), was thinner (Fig. 4c, 5e,f) but leafier (Fig. 4e,
5i,j), and suffered less herbivory than S. globulifera (Fig. 4g,
5n). Habitat also had significant effects on four growth-associated
traits, revealing that: individuals were taller on average in SF than in
HT (Fig. 4a), that S. globulifera grew faster and was leafier in
SF than in HT (Fig. 4b node 3, 4e node 3), and that S. sp1suffered the least herbivory when planted in SF habitats (Fig. 4g, 5n).
Finally, plantation region had an impact on the height of individuals
planted in HT (Fig. 4a node 3) and on the RGR in diameter (Fig. 4d),
with individuals planted in the west being taller and thicker than those
in the east.
The Linear Model analyses, where LS Means were used to correct for
unbalanced design, of the growth-associated traits comparing ‘home’vs. ‘away’ (i.e. ecotype x habitat and provenance x
plantation combinations) corroborated the RF results but focused on a
yearly comparison to provide a contrasting view. Figure 5 illustrates
the significantly better growth performances (e.g. height,
diameter, and TNL, as well as their relative growth compared to
reference measures at age 0) of individuals grown in their ‘home’
ecotype x habitat combination compared to those in ‘away’ ecotype x
habitats combination, and that the differences increase with age (Fig.
5a,b,e,f,i,j).
The provenance x plantation analyses showed significant, or near
significant, effects in the early ages for height, diameter, and total
number of leaves, where ‘home’ individuals outperformed ‘away’
individuals, but the significance disappeared in later years (Fig.
5c,g,k). Individuals grown in their ‘home’ provenance x plantation
combination, had significantly larger diameters at ages 3-5 relative to
their diameter at age 0 compared to individuals in ‘away’ provenances x
plantation combination (Fig. 5h).
Discussion
Local genetic differentiation and its
adaptive significance are widely recognised in plants and evidence of
microgeographic adaptive processes is accumulating for trees
(Wright 2007; Ramírez-Valienteet al. 2009; Brousseau et al. 2013, 2015, 2018; Carsjenset al. 2014; Pluess et al. 2016; Rellstab et al.2016; Barton et al. 2020). Differences in seedling performances
along ecological gradients are typically interpreted as underlying
observed interspecific differences in the distribution of mature trees;
in a way, our two ecotypes in the Symphonia syngameon behave in a
species-like way relative to habitat preferences, given that they can
grow in mixed or neighbouring stands, where morphological and genetic
hybrids are occasionally found, and yet they retain their respective
ecological properties.
Superior performances of ’home’ and ’local’ individuals in life-history
and growth-associated traits suggest that Symphonia trees have
locally adapted to different environmental conditions across French
Guiana. We find both ‘home’ vs. ‘away’, and ’local’ vs.’foreigner’ examples of local adaptation (sensuKawecki & Ebert 2004)). The
patterns are, however, complex; revealing that the measured traits are
not exclusively caused by genetic trade-offs in the underlying genes
coding for the patterns of local adaptation.
Patterns of germination:
The classification trees and the
estimated shadehouse and overall probability of germination (Fig. 2 and
Suppl. Fig. 3, 4, 5) exposed some unexpected patterns: Western S.
sp1 seeds have a significantly lower probability of germination under
the controlled conditions of the shadehouse after 89 days than all other
groups (Fig. 2b). However, overall germination at the end of the
experiment of western S. sp1 planted in HT in the west was
relatively high (~70%, Fig. 2c), indicating that
germination for western S. sp1 in western HT recovered while in
the field. The germination of western S. sp1 in other
habitat-region combinations remained very low till the end of the
experiment (Fig. 2c). In stark contrast, all four eastern provenance
combinations of ecotype and habitat planted in the east had nearly 100%
overall germination success. Western seeds germinated significantly
later than eastern seeds (Fig. 2d: 1 year later on average). Such
differential success rate and timing of germination among
ecotype-provenance combinations could be due to differences in local
adaptation to germination timing and cues. Matching germination with the
best possible conditions for seedling growth is paramount for seedling
survival, and the timing and environmental cues underpinning such
favourable conditions may vary across a species range. Variation in seed
dormancy duration, and the genetic basis for such variation, has been
reported as evidence for local adaptation among populations ofArabidopsis thaliana(Donohue
2009; Postma et al. 2015, 2016). Similarly, the regional
differences in germination success over the course of our study may
indicate evolutionary advantages for delayed germination ofSymphonia in the west or rapid germination of Symphonia in
the east (Fig. 2d). A higher seed quiescence or dormancy level, or
tighter environmental requirements for germination, may have emerged as
a local adaptation in western Symphonia , especially in S.
sp1¸ as a means to cope with a drier environment
(Dallinget al. 2011), and spreading seedling mortality risk across
several years
(Gremer
& Venable 2014). Supporting such hypothesis, we observe reduced
survival of eastern provenance-individuals in the west (Fig. 3)
indicating that the western plantations are in a harsher environment
overall. Conversely, a quicker germination time may be a local
adaptation in response to differences in seed mortality rate
(e.g. herbivory, disease, or ageing) between regions or ecotypes
(Dallinget al. 2011; Postma et al. 2015)
Patterns of growth-associated traits:
The LSMeans analyses exposed how individuals in their home habitat
significantly outperformed individuals in away habitats in terms of
growth-associated traits, and the classification trees pinpointed how
that signal was dominated by significant decreases in growth-associated
traits for S. globulifera when planted in HT, indicating a
reduction in competitive growth performance of individual S.
globulifera in HT. Conversely, we did not detect any significant effect
of habitat for S. sp1 , suggesting a capacity to perform well
regardless of habitat. Individual tree
vigour, as in the difference between observed and expected growth, has
been shown to have a pervasive effect on Neotropical tree survival,
where variance in individual vigour along the tree’s life was the most
important variable predicting survival, well above ontogenetic status or
species membership
(Aubry-Kientzet al. 2015). Variance in growth performance, such as seen inS. globulifera, can be interpreted as variance in vigour, which
could be one of the mechanisms explaining the variance in survival
patterns we observed among Symphonia seedlings. The observed
variance in growth is indeed in accordance with the rarity of adultS. globulifera in HT habitats, and the more generalist
distribution of S. sp1 across habitats
(Alliéet al. 2015; S. Schmitt, unpublished data).
Patterns of survival and contributions towards
understanding the patterns of species distribution:
The classification trees of combined
germination and survival reveal complex interactions among the predictor
variables, not only explaining the patterns of survival ofSymphonia individuals in our experiment, but also potentially
explaining patterns of species distribution in French Guiana and the
maintenance of ecological differences between ecotypes within theSymphonia syngameon.
The groups with the highest survival
(>50% after 6 years) were western-provenance S. sp1planted in western HT, and eastern-provenance individuals planted in the
east regardless of ecotype and habitat (Fig. 3). These two high survival
groups also had high germination rates (Fig. 2c). The first group is
suggestive of very specific local adaptation. It is the only group
planted in the west with a relatively high survival (i.e.>50% survival at age 5, compared to <25% for
the rest of groups transplanted in the west). S. sp1 is common in
hilltops throughout French Guiana and may therefore be able to cope
better in the drier west. Furthermore, it is only western S. sp1which significantly separate from all others in terms of survival,
perhaps indicative not only of an ecotype adaption to drier HT, but also
a regional effect where eastern S. sp1 are particularly drought
tolerant. This case constitutes a double example of a ‘local vs.foreign’ evidence of local adaptation across two variables (both habitat
and regional), stressing the efficacy of the selection pressures in
eastern HT habitats. Variations in survival and germination in S.
sp1 are furthermore accompanied with an overall lower performance ofS. globulifera seedlings when planted in HT; both probably
contributing to contrasted distributions between the two ecotypes. We
did not detect an adaptive cost for S. sp1 in the form of lower
survival in either eastern gardens nor in SF habitats, suggesting that
either 1) conditional neutrality (i.e. whereby an adaptation conveys a
performance advantage in one environment without costs in alternative
environments) is at play in the genetic basis underlying its improved
performance in dryer conditions
(Anderson
2013; Wadgymar et al. 2017), or that 2) our experimental design
did not capture the selective pressures penalising S. sp1 in
wetter conditions, such as those found in SF habitats or eastern
gardens. The latter could be related to environmental variables we did
not account for in the experiment or related to stages we missed across
the trees’ life history
(Migliaet al. 2005).
The second group with comparatively high survival confirms a better
performance of eastern individuals in eastern field sites compared to
western field sites, indicative of either local adaptation at the
regional level to heavier rainfalls, or alternatively, poor drought
tolerance, as the survival of eastern-provenance individuals, regardless
of ecotype, planted in the west drops significantly. This constitutes an
example of ‘home vs. away’ pattern of local adaptation, but not
‘local vs. foreign’ as western-provenance individuals have a high
survival in the east once germinated. Given the general high survival of
individuals in east plantation gardens, and the non-appearance of other
factors significantly affecting survival in these gardens, we infer a
less stressful environment in the eastern field site forSymphonia in general. We did not capture evidence of differences
in survival between ecotypes or habitats in the east, which exemplifies
the potential confusion between divergent selection and differences in
habitat quality.
Overall, we find evidence that S. sp1 has better survival in the
driest conditions, suffers less herbivory, and has no penalisation on
other environments, which suggests a habitat generalist behaviour, and
matches the extant species distribution. Conversely, S.
globulifera is triple penalised out of SF (i.e. lower TNL, lower
RGR in height, and higher herbivory), suggesting that it is a habitat
specialist limited to SF habitats. The apparent limitation in habitat
availability for S. globulifera could be compensated by the
faster adult growth rate and a potentially higher reproductive output
because of the larger maximum sizes in S. globulifera thanS. sp1 allowing the coexistence of both ecotypes. The variance in
juvenile performance in the two habitats also helps explain the
maintenance of the ecological differences between ecotypes, which could
contribute to the preservation of the genetic integrity of each ecotype
even when occasional hybridisation occurs between them.
Selective pressures behind the signals of local
adaptation:
The experimental setup was designed to
detect adaptation patterns to the combined effects of the contrasted
habitats, with a focus on soil factors influencing hydric regime. Our
results show a pattern consistent with an adaptive advantage of westernS. sp1 to the driest conditions included in the experiment (i.e.
western HT), potentially mediated through improved water use efficiency
(Baltzeret al. 2005).
Beyond the sharp variations in water regime, many other variables covary
across the microhabitats presented here (i.e. east vs.west, SF vs. HT): access to resources such as light and soil
nutrients, the risk of death, the floristic and soil microbiota
community, and presence of herbivores vary significantly between HT and
SF.
SF habitats have a higher fertility and
access to light than HT habitats, however, trees living in SF habitats
double their risk of death through tree fall
(Ferryet al. 2010), creating a high-risk high-gain environment. Species
specializing in SF habitats must therefore adapt their resource
allocations accordingly. S. globulifera seedlings in SF were the
tallest (Fig. 5a) and had the largest diameters after 6 years (Fig. 5e),
potentially indicative of an ecotype adaptation towards a strategy
maximising growth in a risky environment.
Arthropod assemblages in French Guiana
SF and HT habitats are significantly different, where leaf feeders in
particular are more abundant in HT than in SF
(Lamarreet al. 2016). Herbivory was highest for S. globuliferaregardless of all other covariates, and lowest for S. sp1 in SF
habitats, suggesting different predator avoidance strategies between
ecotypes. Our herbivory analyses are in agreement with those of previous
studies, where similar patterns are
observed in RTEs between species specializing in high and low herbivory
pressure environments: species which are normally exposed to a higher
herbivory environment (i.e. similar to S. sp1 ),
experienced reduced herbivory in low herbivory environments (i.e.similar to SF) compared to their ‘home’ environment and species from
low-herbivory environments (Fineet al. 2004, 2006; Baltzer & Davies 2012). S. globuliferatissues are rich in secondary metabolites of the b is-xanthone
family, known to have insecticidal properties in other organisms
(Ondeyka et al. 2006; Wezemanet al. 2015); the leaves are particularly rich in globulixanthone
E
(Cottetet al. 2014), which has strong anti-microbial activity
(Nkengfacket al. 2002). S. globulifera populations from Cameroon and
French Guiana differ for their content in anti-microbial and
anti-parasitic compounds
(Cottetet al. 2017), suggesting that chemical differences may also occur
between S. globulifera and S. sp1. Under this hypothesis,S. sp1 may have adapted to a higher herbivory environment (HT) by
increasing the production of unpalatable and toxic compounds to
compensate for a potential limitation in resources in HT habitats
(Bryantet al. 1985; Fine et al. 2004, 2006). Such scenario would
also explain the lower herbivory rate of S. sp1 in SF habitats
compared to HT habitats.
Limitations of the
study:
The power of our tests and the meaning
of their results may suffer from multiple biases. Differences in
germination successes lead to unbalances. While the analytical method we
developed is meant to compensate them, they may still affect the
results. Maternal effects (e.g. maternal provision to seeds) may
still influence seedling growth and resources, because seedling mass is
probably still in the same order of magnitude as seed mass. Epigenetic
inheritance may also contribute to differences in seedling reactions to
environmental cues. In the absence of precise information about genetic
divergence and gene expression / regulation differences between
ecotypes, it is hard to tell which mechanism is at play in theSymphonia system. Finally, as stressed by Miglia et al.(2005), to gain a comprehensive
understanding of the ecological factors driving survival and performance
of related taxa across environmental variables, multi-life-stage
comparisons including germination, som
atic growth, and reproduction should be included.
Conclusion:
The critical importance of natural
selection on genetic differences expressed during early life stages,
when trees experience the highest mortality, has been recognised
(Donohueet al. 2010; Postma & Ågren 2016). Our RTE experiment has given
us insights into the ecological mechanisms governing differential
germination and survival of cohorts of individuals in their own and
foreign natural environments. We have revealed significant life-history
and growth-associated trait differences between ecotypes and between
provenances, that match with known environmental constraints
(i.e. hydric regimes, nutrient availability, death risk, and
herbivory risks), and may be the result of coevolution of germination
phenology and seedling survival. S. globulifera seedlings were
penalised in HT habitats with reduced growth and higher herbivory,
however, in SF habitats they outgrew other such groups (ecotypes x
habitat), a pattern also observed in adults Symphonia , suggesting
that S. globulifera has a specialized competitive advantage in SF
habitats, which may results in higher reproductive output if greater
adult biomass is attained, and thus, allowing the coexistence for both
ecotypes and the maintenance of the syngameon. Our results therefore
suggest a link between differential growth and survival in seedlings, on
the one hand, and adult tree distribution, on the other hand, and
indicates that processes occurring at early life stages, far from being
of an exclusively stochastic nature, contribute in a significant way to
the selective processes and ecological filters that determine a species’
pattern of distribution across habitats. Furthermore, our results
suggest that even relatively small environmental differences, such as
those between HT and SF, can lead to the evolutionary differentiation
and maintenance of distinct taxa in sympatry with different life-history
traits to suit such mosaic environmental heterogeneity despite
occasional geneflow. Overall, the Symphonia model furthers our
comprehension of the eco-evolutionary processes underpinning the
diversity and the spatial structuring of Neotropical tree communities as
well furthering our understating of the processes involved in the
maintenance of syngameons in sympatry.
Acknowledgements:
This manuscript is posthumously
dedicated to MC, who started the RTE experiment and analysed the first
years of measurements in part of his thesis “Genetic of the divergence
within closely related species of tropical trees”. This manuscript also
includes part of AT’s thesis. We thank the many AgroParisTech master
students from the “Forets Tropicales Humides” module that helped
measure the seedlings (years 2009-2014). We are thankful to Sylvain
Schmitt and Myriam Heuertz for comments on previous drafts that have
greatly improved this manuscript. We kindly thank the Agence National de
la Recherche grant “Investissement d’Avenir” (Labex CEBA, ref.
ANR-10-LABX-25-01) and the European Union (PO-FEDER ENERGIRAVI) for
financial support. MC Thesis was financed by the CNRS (BDI) and the
Region Guyane, AT thesis was financed by UE FEDER and Labex CEBA. Both
theses were carried out at the Université de Guyane.
Author contributions:
IS and CSS conceived the idea and
designed the experiment. MC, VT and SOC established the RTE experiment.
MC, AT, LB, VT and SOC coordinated the field measurement campaigns. BF
contributed with soil and habitat characterisation. NT and MPE conducted
the data analyses; NT, IS, CSS, and MPE wrote the manuscript. All
authors contributed critically to previous drafts and gave their final
approval for publication.
Data availability:
The data will be submitted to the TRY plant database upon acceptance of
the manuscript.
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Tables:
Table 1 : Symphonia individual information: theMother tree from which the seed was collected, thesampling site and latitude and longitudewhere the mother tree was found. Two general provenance regionsare indicated (e.g. east and west), as well as the ecotype to
which the mother belonged (S. globulifera or S. sp1 ) and
the type of habitat the mother tree was found: seasonally
flooded (SF ) and hilltops (HT ). The number of seeds
collected (Ni ), the number of seeds germinated at the time of
transplant (Gt ), and that had germinated overall at the end of
the experiment (Go ), and the number of seedlings alive at year
6 (Alive Y6 ) are also tabulated.