Material and
Methods
Study
sites
This study was conducted in two Mediterranean mixed pine-oak forest
communities of the Southeastern of Spain, Mixed Forest of Jaen (MFJ) and
Mixed Forest of Segura (MFS, hereafter). The climate is typically
Mediterranean, with mean temperatures varying between 6º C in January
and 27ºC in July, and scattered rainfall concentrated during autumn and
spring (535.4 mm to 611.7 mm). Both forests belong to semi-deciduous and
sclerophyllous Mediterranean ecoregion.
Both communities are dominated by Quercus and Pinus spp.Quercus spp. are more abundant in MFJ than in MFS, with Q.
faginea being highly abundant in MFJ, Q. ilex common to both
sites, and Q. pyrenaica occurring only at MFS. Pinus
halepensis also shows high densities in MFJ, but they are lower thanPinus nigra subsp. salzmannii in MFS, which dominates all
the canopy layer. The highest species diversity of both communities is
located in the sub-canopy and shrub layers. MFJ contains Crataegus
monogyna, Juniperus oxycedrus, Phillyrea angustifolia, Phillyrea
latifolia, Pistacia Lentiscus and Rhamnus lycioides , among other
less abundant species. In turn, Acer granatensis , Crataegus
laciniata , Juniperus communis , Prunus spinosa are present
in MFS. Although both communities are located relatively close each
other, MFJ has almost twice the species richness of woody plants than
MFS, being 29 vs 17 respectively (for further information, see
Perea et al., 2021a).
Sampling
design
At each community we installed a permanent plot of 100×100 m, where the
coordinates of all adult tree and shrub individuals were taken.
Concentrically to this plot, we located a 50×50 m plot, where we took
the coordinates of all saplings. Saplings were individuals with basal
diameter > 1cm, without symptoms of being reproductive
(i.e. flowers and fruits), and with a size lower than 25% of the
typical size of an adult of the species (Alcántara et al., 2019; Verdú
et al., 2022). Coordinates for adult plants in the large plots were
taken to the closest meter (i.e. 1m), but in the smaller plots they were
taken to the closest 0.33m to detect spatial signatures at smaller
scales.
At both communities we collect data to characterise for each plant
species the organisms of the phyllosphere that are potentially involved
in plant community dynamics, both depressing the recruitment (i.e.
antagonists such as fungal pathogens, sap sucking insects and chewing
insects) or fostering it (i.e. mutualists like fungal epiphytes and
endophytes) (Bastida et al., under review , Pajares-Murgó et al.,
2022). For further details about data collection and sequencing see
supplementary information.
Data
analyses
Correlation among plant-associated
organisms
We conducted a Mantel test for each plant community to find out if the
guilds of plant-associated organisms showed collinear responses. We used
the Kendall approach (τ) to add more robustness to this test (not
assuming linearity, outlier’s absence or homoscedasticity). This
analysis allowed us to assess whether two plant species that share e.g.,
more pathogens have also a higher probability to share also more
epiphytes, sucker insects and/or chewers insects.
Spatial
analysis
Our objective is to conduct a
spatial analysis of how different guilds of plant-associated organisms
are shared between focal plants and their neighbours. To this end we
used multivariate techniques of spatial point pattern analysis (Wiegand
et al., 2017; Wiegand & Moloney 2014) that allow for such analyses at
the level of the entire plant community, and for groups of focal species
only (e.g., only dry-fruited and fleshy-fruited species). For the
community-level analysis, we used a summary function that is the
expected number of plant-associated organisms common to two randomly
selected plants that are closer than distance r of each other.
This summary function is called “community-level cumulative
phylogenetic Simpson index” αphy (r )
(Wiegand et al., 2017) and can be estimated by using standard summary
functions of spatial point pattern analysis as:
\(\ \alpha_{\text{phy}}\left(r\right)=\ \sum_{f=1}^{S}{\sum_{i=1}^{S}\delta_{\text{fi}}\frac{\lambda_{f}}{\text{λ\ }}\frac{\lambda_{i}K_{\text{fi}}(r)}{\lambda\ K(r)}}\).
(eq.1)
where the similarity index δfi gives the number
of OTUs of fungi or insect species shared between the focal speciesf and a second species i , and \(\delta_{\text{ff}}\ \)is
the number of unique fungi or insect species hosted by species f .
The ratio λi /λ is the relative abundance
of species i in the community,Kfi (r ) the bivariate K -function of
species i with respect to the focal species f , andK (r ) the univariate K -function of the entire
community (Wiegand & Moloney, 2014). Note that the quantity\(\frac{\lambda_{f}}{\text{λ\ }}\frac{\lambda_{i}K_{\text{fi}}(r)}{\lambda\ K(r)}\)in equation 1 is the fraction of pairs of individuals with distance
< r where the first plant is of the focal speciesf and the second of species i .
Slight reordering of equation 1 leads to the definition of the
corresponding species-level summary function
\(\alpha_{f,phy}\left(r\right)=\ \sum_{i=1}^{S}\delta_{\text{fi}}\frac{\lambda_{i}K_{\text{fi}}(r)}{\lambda\ K(r)}\), (eq.2)
which is the expected number of plant-associated organisms common to two
randomly selected plant that are closer than distance r of each
other, but where the first plant is of the focal species f .
Equations 1 and 2 allows us to define “partial” summary functions
where the first plant is e.g., a fleshy-fruited plant. This is
accomplished by abundance-weighed averaging (as in equation 1), but only
over fleshy-fruited focal species f (Wiegand & Moloney, 2014).
To better interpret our results, we also estimated the partial
cumulative spatial Simpson index \(\alpha_{f,S}\left(r\right)\) that
gives the proportion of heterospecifics located within distance rof individuals of species (or type) f (Wiegand et al., 2017). It
follows from equations 2 by using δfi = 1 forf ≠ i and δfi = 0 for f =i .
We want to assess, for example, if saplings of a focal species fshare on average fewer pathogen species with their neighbours than
expected. To this end, we compared the actual neighbourhoods of the
saplings with that of randomly selected neighbourhoods, testing for
independent placement of saplings of species f with respect to
their heterospecific neighbours (i.e., sapling-sapling analysis) or with
respect to the adult community (i.e., sapling-adult analysis). Because
our summary functions include conspecifics, we implemented the
independent placement hypothesis as a toroidal shift null model (Lotwick
& Silverman, 1982; Wiegand & Moloney, 2014) that conserves the spatial
pattern (e.g., aggregation) of conspecifics. To test for significant
departures from spatial independence, we conducted 999 simulations of
the null models and used standardised effect size (SES) of the
normalised summary functions. In case that the standardised effect size
is lower than −1.96, or higher than 1.96, we obtain significant
departures (p < 0.05) from the null model at the
particular neighbourhood distance r (i.e. a point-wise test). IfSES (r ) < −1.96, the mean similarity is smaller
than expected, for SES (r ) > 1.96 the
similarity is larger than expected, and otherwise they were similar
(p > 0.05). To assess the overall significance of
departures from the null model for the distance interval of 1 to 10m, we
used a global envelopes test based on the standardized effect sizes
(Wiegand et al., 2016).