Spatial phylogenetic and phenotypic patterns reveal ontogenetic shifts in ecological processes of plant community assembly

www.oikosjournal.org OIKOS Oikos Page 1 of 14 © 2022 The Authors. Oikos published by John Wiley & Sons Ltd on behalf of Nordic Society Oikos. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. Subject Editor: Sa Xiao Editor-in-Chief: Vigdis Vandvik Accepted 7 August 2022 doi: 10.1111/oik.09260 00 1–14 2022: e09260 The analysis of the spatial phylogenetic and phenotypic structure of plant communities can provide insight into the underlying processes and interactions governing their assembly, and how these may change during plant ontogeny. We used point pattern analysis to find out if saplings and adult plants are surrounded by phylogenetically and phenotypically more similar or more dissimilar neighbours than expected by chance, and whether these associations change from the sapling to the adult stage. To this end, we combined information on the phylogenetic structure and eight phenotypic traits of 15 woody plant species in two Mediterranean mixed forests of southeastern Spain. At the community level, we found that the sapling bank at both sites did not show phylogenetic or phenotypic spatial patterns, but adults showed phylogenetic clustering (i.e. heterospecific neighbours were more similar than expected). At the species level, we found frequently repulsive patterns in the sapling bank of less abundant species (i.e. heterospecific sapling or adult neighbours were more dissimilar than expected) in both, phylogenetic and phenotypic analyses. For the adult stage, we found phylogenetic attraction (i.e. more similar neighbours) in just one species and phenotypic clustering in four species. The processes driving the assembly of the communities of saplings and adults leave detectable signals in the spatial phylogenetic and phenotypic structure of our two forest communities. Our findings reinforce the existence of ontogenetic shifts in the mechanisms involved in plant community assembly. Facilitation between phylogenetically distant and phenotypically divergent species favours the recruitment of less abundant species. However, processes acting later in the ontogeny ameliorate the competition between close relatives and determine the spatial structure of adult plants. Nevertheless, the role of phenotype in shaping the interactions between adult plants was contextand trait-dependent. The use of spatial point pattern analysis allowed a nuanced interpretation of the phylogenetic and phenotypic structures of plant communities. Keywords: community assembly, competition, facilitation, ontogeny, plant–plant interactions, point pattern analysis Spatial phylogenetic and phenotypic patterns reveal ontogenetic shifts in ecological processes of plant community assembly Antonio J. Perea, Thorsten Wiegand, José L. Garrido, Pedro J. Rey and Julio M. Alcántara A. J. Perea (https://orcid.org/0000-0001-8351-9358) ✉ (aper[email protected]), P. J. Rey (https://orcid.org/0000-0001-5550-0393) and J. M. Alcántara (https://orcid.org/0000-0002-8003-7844), Depto Biología Animal, Biología Vegetal y Ecología, Univ. de Jaén, Jaen, Spain. – T. Wiegand (https://orcid. org/0000-0002-3721-2248), Dept of Ecological Modelling, Helmholtz Centre for Environmental Research (UFZ), Leipzig, Germany and German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany. – AJP and J. L. Garrido (https://orcid.org/0000-0002-6859-4234), Depto Microbiología del Suelo y Sistemas Simbióticos, Estación Experimental del Zaidín, Consejo Superior de Investigaciones Científicas (EEZ-CSIC), Granada, Spain. JLG also at: Depto Ecología Evolutiva, Estación Biológica de Doñana, Consejo Superior de Investigaciones Científicas (EBD-CSIC), Sevilla, Spain. PJR and JMA also at: Inst. Interuniversitario de Investigación del Sistema Tierra En Andalucía (IISTA), Granada, Spain. Research article 14 16000706, 2022, 12, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/oik.09260 by Csic Organización Central Om (Oficialia Mayor) (Urici), Wiley Online Library on [08/02/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License Page 2 of 14 Introduction Plant–plant interactions are one of the principal drivers of the dynamics of diverse plant communities. Accordingly, the study of interactions such as competition and facilitation is one of the fundaments of plant community ecology (Connell and Slatyer 1977, Bertness and Callaway 1994). The complexity of this topic is manifested in multiple experimental, observational, theoretical and analytical approaches trying to disentangle the processes that contribute to the assembly of diverse plant communities (Chesson 2000, Hubbell 2001, Silvertown 2004, Levineetal. 2017, Daviesetal. 2021). For example, coexistence theory outlines the importance of stabilizing mechanisms that make intraspecific competition larger than the interspecific competition, and of equalizing mechanisms that minimize differences in competitive ability among species (Chesson 2000, 2018, Barabás et al. 2018, Wiegand et al. 2021). Current efforts in the study of plant–plant interactions have also been facilitated by the availability of phylogenetic information, phenotypic information (i.e. species traits) and new computational tools (Cavender-Baresetal. 2009). Repositories of species traits (Kattgeetal. 2020), phylogenetic databases and online analytic tools (Webbetal. 2008) provide now access to updated information for thousands of species. However, identifying the contribution of phylogeny and species traits to ecological processes remains an ongoing task (Cadotteetal. 2019). Each species in a community may follow a different strategy to persist, and these strategies may be based on different sets of traits. Therefore, it cannot be expected that just one or a few traits govern the main processes driving the assembly of a plant community (Cornelissenetal. 2003). Uncertainty regarding the relevant set of traits involved in the assembly processes has led some authors to propose the use of phylogenetic distances as a proxy for phenotypic dissimilarity, under the assumption that more closely related plant species are phenotypically more similar (Cadotteetal. 2012, Baralotoetal. 2012, but see Gerholdetal. 2015, de Bello et al. 2017). Nevertheless, phenotype and phylogeny are not always correlated (Swenson and Enquist 2009, Cadotteetal. 2019), and other studies suggest that phylogeny does not always provide relevant information for the study of community assembly (Purschkeetal. 2013, Gerholdetal. 2015, Nuismer and Harmon 2015). However, using both phylogeny and phenotype can provide more nuanced information on the relative role of different ecological processes and interactions (Kraftetal. 2007, Cadotteetal. 2013, de Belloetal. 2017). For instance, Kraftetal. (2007, 2008) showed that the species phenotype in Amazonian forest communities is selected throughout environmental filtering, producing strong phylogenetic structures and explaining processes involved in community assembly. Other authors found evidence that phylogenetically and phenotypically close species and conspecifics have a higher chance to share antagonists (Janzen 1970, Connell 1971, Kembel and Hubbell 2006, Parkeretal. 2015). Plants usually interact with a limited set of neighbours, and statistical neighbourhood analyses found that the performance of focal plants often depends on functional and evolutionary relationships with their neighbours (Webbetal. 2006, Uriarte et al. 2010, Fortunel etal. 2018, Grossiord 2018). Thus, we expect systematic differences between the observed local biotic neighbourhood of a given species and that of other species (Webbetal. 2002, Kraft and Ackerly 2014, Wangetal. 2016). This idea can be illustrated with the ‘landscapes of phylogenetic and phenotypic neighbourhood dissimilarity’ (Wiegand and Moloney 2014, Wiegandetal. 2017), i.e. maps that represent, at each location × of a plot, the mean pairwise phylogenetic (or phenotypic) dissimilarity between a focal species f and all heterospecifics located within a given distance r of location x. This landscape will usually consist of valleys and hills (Fig. 1a), and if, for example, a species tends to be predominantly surrounded by more similar neighbours, its individuals should preferably be located in the valleys of the dissimilarity landscape (Fig. 1a, b). The location of the individuals of a species within the landscape of phylogenetic or phenotypic dissimilarity (Fig. 1a) can show three basic spatial patterns: phylogenetic or phenotypic repulsion, attraction and independence. Repulsion means here that neighbours of the focal species are more dissimilar than expected from randomly selected neighbourhoods, whereas attraction indicates the opposite. In contrast, under independence, the phylogenetic or phenotypic dissimilarity does not differ from that of randomly selected locations. Note that this definition applies to the characterization of the biotic neighbourhood of individual species, when characterizing the neighbourhoods of the whole community we use the common terms phylogenetic (or phenotypic) overdispersion, clustering and independence, respectively (Webbetal. 2002, Emerson and Gillespie 2008, Kraft and Ackerly 2014). Several mechanisms can cause phylogenetic (or phenotypic) neighbourhood patterns. First, phylogenetically (or phenotypically) overdispersed (or repulsive) neighbourhood patterns can be the consequence of several processes such as density-dependent mortality, facilitation, competition and/ or niche partition (Janzen 1970, Connell 1971, CavenderBares et al. 2004, Valiente-Banuet and Verdú 2007). For example, if the intensity of competition is related to the phylogenetic similarity of species, we expect that the biotic neighbourhood of species should be composed of species that are more dissimilar (but see Mayfield and Levine 2010). Second, if similar species share habitat requirements, habitat filtering along environmental gradients should lead to phylogenetically (or phenotypically) clustered (or aggregated) patterns (Kembel and Hubbell 2006). Finally, if the ecological processes are too noisy to establish assembly rules, or if the effects of the different processes cancel each other out, phylogenetic or phenotypic independence should emerge, indicating that species differences may not primarily drive community assembly (Kembel and Hubbell 2006, Wangetal. 2016). Spatial neighbourhood patterns, therefore, carry information about the operation of processes in the past, and they form the template for the processes operating in the future 16000706, 2022, 12, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/oik.09260 by Csic Organización Central Om (Oficialia Mayor) (Urici), Wiley Online Library on [08/02/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License Page 3 of 14 (Lawetal. 2009). In particular, ecological processes that occur in early life stages can leave long-lasting footprints in the spatial structure of adults (Pereaetal. 2020, 2021b). Then, comparisons of their spatial patterns, and the phylogenetic and phenotypic structure of their surrounding neighbourhoods, may improve our understanding of the processes and legacy effects involved in shaping plant communities (Moeur 1997, Plotkinetal. 2002, Getzinetal. 2008, Wangetal. 2016, Wiegandetal. 2017, Chun and Lee 2019). However, few studies have investigated if processes occurring during early life stages, such as seed dispersal, facilitation and competition, are related to the phylogenetic and phenotypic neighbourhood of adults (Wangetal. 2013, 2015, Wiegandetal. 2017). One approach to advance in this issue is the use of point pattern analysis together with the landscape of phylogenetic or phenotypic dissimilarity that allows for detecting spatial patterns in the dissimilarity of heterospecific neighbours within a given distance of the individuals of a focal species (Wiegand and Moloney 2014). Applying this method across life stages will provide a nuanced approach to finding out whether species experience different processes during ontogeny. In this study, we applied recent methods of phylogenetic spatial point pattern analysis (Wiegandetal. 2017) to data of two fully-mapped Mediterranean mixed pine–oak forest communities and information on eight phenotypic traits and phylogenetic structure of 15 woody plant species to find out if 1) saplings and adult plants of given focal species (and from the Figure1. Landscape of phylogenetic dissimilarity for the MFJ community of large trees and the corresponding point pattern summary functions. (a) The non-normalized landscape ΔP f (x, r = 5 m) measures at each location × of the plot the mean pairwise phylogenetic dissimilarity between the focal species C. monogyna and all heterospecifics located within 5 m of the location x. The phylogenetic distances were scaled between 0 and 1, and the mean pairwise phylogenetic dissimilarity between the individuals of the focal species C. monogyna (black circles) and all heterospecifics yields MPDf = 0.591. Green to blue indicate locations with larger than expected dissimilarity (peaks) and locations ranging from brown to green indicate locations with smaller than expected dissimilarity (valleys). Dark brown (values of 0) corresponds to areas without heterospecific neighbours. (b) Histogram of the distribution of values of the landscape ΔP f(xi, r = 5 m) at the locations xi of the focal species C. monogyna (bars), the availability of the landscape (dots) and the vertical line indicates the normalization constant MPDf. (c) The cumulative individual phylogenetic mark correlation function mark Kd,f(r) gives the normalized mean pairwise dissimilarity between the typical individual of the focal species f and all heterospecifics within distance r, normalized with MPDf. Dots: observed Kd,f(r), lines: pointwise simulation envelopes (25th lowest and highest values of the 999 simulations of the toroidal shift null model). (d) Standardized effect sizes of Kd,f(r) (dots), simulation pointwise envelopes (black lines; approximately −1.96 and 1.96) and global envelopes for the interval 1–4 m (red lines). 16000706, 2022, 12, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/oik.09260 by Csic Organización Central Om (Oficialia Mayor) (Urici), Wiley Online Library on [08/02/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License Page 4 of 14 community average) are surrounded at smaller spatial scales by phylogenetically and phenotypically more similar of more dissimilar neighbours than expected by chance, and whether these associations were consistent across life stages, species and study sites (Table 1). More specifically, we hypothesized that 1) the biotic neighbourhoods of saplings of focal species should show patterns of phylogenetic (or phenotypic) attraction or repulsion, and that 2) the corresponding patterns of adults should be weaker and show different patterns. We also expect that 3) less abundant species may show neighbourhood patterns that differ from the average community-level patterns. Overall, we expect to find evidence that ecological processes shift during plant ontogeny and leave a phylogenetic and/or phenotypic footprint in the spatial structure of the community. Methods Study systems This study was conducted in two pine-oak Mediterranean mixed forests in the southeastern Iberian Peninsula, Sierra de Jaén and Sierra de Segura (MFJ and MFS, hereafter). The first community belong to the Iberian sclerophyllous and semi-deciduous forests ecoregion, whereas the second community belong to Iberian conifer forests. The two communities occur in calcareous areas. Rainfalls are moderate in both forests during spring and autumn (mean annual rainfall: 535.4 mm at MFJ and 611.7 mm at MFS), whereas the summer season is quite dry in both places. The coldest month is January (mean temperature: 10°C in MFJ and 6°C in MFS), whereas the warmest months are July and August (mean temperature 27°C in MFJ and 24°C in MFS). Both sites have a mild climate compared to the south of Spain. MFJ is located at lower altitudes ( 37°38'8.44"N, 3°44'24.27"W; 850 m a.s.l.) than MFS ( 38°17'55.90"N, 2°33'27.21"W; 1420 m a.s.l.), and has higher species richness (see Pulgaretal. 2017 for further details). Both studied communities are the same used in Pereaetal. (2021a, b). Quercus faginea and Pinus halepensis dominate in the MFJ community, whereas Pinus nigra subsp. salzmannii dominates in the MFS community. The MFJ community also owns other abundant species such as Juniperus oxycedrus, Crataegus monogyna, Pistacia lentiscus, Phillyrea latifolia, Quercus ilex and Rhamnus lycioides among others (see the Supporting information in Pereaetal. 2021b). At the MFS community, we found Acer granatense, Crataegus laciniata, C. monogyna, Juniperus communis, Q. faginea, Q. ilex and Quercus pyrenaica, but also there are other less abundant species in this community (see the Supporting information table in Pereaetal. 2021b). Sampling design Mapping of plants In each forest, we selected an environmentally homogeneous plot of 100 × 100 m (large plot, hereafter), where coordinates and DBH of every adult were taken (i.e. DBH > 10 cm for upper-canopy species). Concentrically to the large plot, we settled on a 50 × 50 m plot (small plot, hereafter), where we took the same variables for saplings (see Pereaetal. 2021b for further details). We considered saplings as plants with a DBH higher than 1 mm but lower than 1 cm, and without symptoms of being a reproductive individual (flower and/or fruits). Phenotypic and phylogenetic dissimilarity matrices We collected traits for 30 saplings and 15 adults of each species, separated by at least 10 m along a 100 m transect parallel to the plots (Pereaetal. 2021a). These traits were categorized into three categories: structural, morphological leaf and chemical leaf traits. Structural traits included height, equivalent basal diameter (EBD), canopy area and branch density, assuming that canopy area and branch density were the same for all the saplings. Morphological leaf traits included leaf area and specific leaf area (SLA), whereas chemical leaf traits included the C:N ratio and leaf hydrogen. These traits represent essential characteristics involved in canopy–recruit interactions (Pereaetal. 2021a) and other ecological processes involved Table 1. Scheme of the analyses conducted in this study. All analyses were conducted by using spatial point pattern analysis. Columns represent the aim for each analysis, the null models and summary functions used in each analysis, and the last column show the question for each analysis. Aim Null models Summary functions Question 1. Are saplings surrounded by phylogenetically or phenotypically more similar or more dissimilar heterospecific saplings, and do the species-level patterns differ from the overall community-level patterns? Toroidal shift of the focal species Focal species Kd,f(r) What processes govern the placement of recruitment in the Mediterranean forests? Toroidal shift of each species Community Kd(r) 2. Are saplings surrounded by phylogenetically or phenotypically more similar or more dissimilar heterospecific adults, and do the species-level patterns differ from the overall community-level patterns? Toroidal shift of the saplings of the focal species, adults remain unchanged Focal species Kd,f(r) What processes govern sapling-adult associations? Are they similar to the recruitment pattern? Toroidal shift of the saplings of each species, adults remain unchanged Community Kd(r) 3. Are adults surrounded by phylogenetically or phenotypically more similar or more dissimilar heterospecific adults, and do the species-level patterns differ from the overall community-level patterns? Toroidal shift of the focal species Focal species Kd,f(r) What processes govern the co-occurrence of adult plants? Are they similar to the recruitment patterns? Toroidal shift of each species Community Kd(r) 16000706, 2022, 12, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/oik.09260 by Csic Organización Central Om (Oficialia Mayor) (Urici), Wiley Online Library on [08/02/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License Page 5 of 14 in plant–plant interactions (Weldenetal. 1991, Ackerlyetal. 2002, Schädleretal. 2003, Bussotti 2008). Measures of these traits have been stored in TRY Database (Kattgeetal. 2020). A summary of the data collection, trait measurements and trait-related processes are provided in Pereaetal. (2021a) and the corresponding Supplementary material. For all traits, we calculated the mean values for each species, at each plot and at each life stage. By using this information, we calculated species dissimilarity matrices using Gower measures for each phenotypic category (i.e. structural, morphological and chemical) across life stages (i.e. adult– adult, adult–sapling and sapling–sapling) by using the FD R-package (gowdis function) in the R environment (Gower 1971, Laliberté et al. 2014, <www.r-project.org>). Our data set did not show evidence for a disproportional contribution of individual traits, so no correction was needed (de Belloetal. 2021). We included in the dissimilarity matrix all species that were present in the large and small plots, independently if they were used or not as focal species in the point pattern analyses. Finally, the phylogenetic dissimilarity matrix was taken from a previous study conducted in the same sites (Alcántaraetal. 2018). Statistical analysis Summary functions of point pattern analyses Our objective is to conduct a detailed analysis of the spatial arrangement of individuals regarding the (phylogenetic or phenotypic) dissimilarity to heterospecific neighbours. This can be done by analysing how the individuals of a focal species f are located within the landscape of phylogenetic or phenotypic dissimilarity (Fig. 1). One possible summary function for doing this, and that accounts for abundance information, is the (individual) cumulative phylogenetic mark correlation function Kf,d(r) (Wiegandetal. 2017). In the ‘univariate’ case we have Nf adult (or juvenile) individuals of the focal species and N individuals in the entire community, and the summary function Kf,d(r) determines for each individual i of the focal species all heterospecific neighbours j of species spj that have a distance smaller than r, estimates the mean of their associated dissimilarities d(f, spj), averaged over all individuals i of the focal species and normalizes by the non-spatial expectation MPDf. More formally, the Kf,d(r) is estimated as: Kr N dfsp If sp Ix xr fd ff i N j N ijij j N f , ,( ) () = () ¹ () -< = = = åå å 11 1 1 1 MPDIIf sp Ix xr jij ¹ () -< é ë ê ê ê ê ù û ú ú ú ú () (1) where I(.) is an indicator function with a value of 1 if the argument is true and zero otherwise, xi and yi are the locations of individuals i and j, respectively. The indicator function I(f ≠ spj) selects only heterospecifics, and I(xi − xj < r) selects pairs of individuals closer than distance r. The ratio in brackets in Eq. 1 is the value of the non-normalized dissimilarity landscape ΔP f(xi, r) at the location xi of individual i of the focal species (Fig. 1). The normalization constant MPDf is the mean pairwise dissimilarity between the individuals of the focal species and all heterospecifics in the plot. The Kf,d(r) has therefore the straightforward interpretation of the mean pairwise dissimilarity between the typical individual of the focal species f and all heterospecifics within distance r, normalized with the mean pairwise dissimilarity MPDf between the typical individual of the focal species f and all heterospecifics within the entire plot (Wiegandetal. 2017). Values of Kf,d(r) = 1 serve as a dividing line between spatial phylogenetic or phenotypic attraction (< 1) where neighbours of the focal individuals are more similar than expected, and phylogenetic or phenotypic repulsion (> 1) where neighbours are more dissimilar than expected (Shenetal. 2013, Wiegandetal. 2017). For the ‘bivariate’ adult-sapling analysis we slightly modified Eq. 1, by using only saplings as individuals i and only adults as individuals j. We, therefore, test how the saplings are located within the dissimilarity landscapes of adults. For the community-level analysis we used the cumulative phylogenetic mark correlation function Kd(r), Kr dspspIsp sp Ix xr d i N j N ii ijij i N j () = () ¹ () -< == == åå å 111 11 MPD ,( ) NN ijij IspspIxx r å¹ () -< () (2) (Shenetal. 2013, Wiegandetal. 2017) where the normalization constant MPD is the mean pairwise dissimilarity between all heterospecific i – j pairs of individuals of species spi and spj, respectively. The Kd(r) has therefore the interpretation of the expected dissimilarity between two randomly selected heterospecifics separated by spatial distances smaller than r, normalized by the expected dissimilarity MPD of two heterospecifics taken randomly from the plot. The value of Kd(r) = 1 serves as dividing line between small-scale spatial phylogenetic (or phenotypic) neighbourhood clustering [Kd(r) < 1] and spatial phylogenetic (or phenotypic) neighbourhood overdispersion [Kd(r) > 1]. Non-significant values of Kd(r) may arise if all species are independently located from each other, or if the effect of focal species showing clustering or overdispersion averages out. For the bivariate adult-sapling analyses we used the same convention as for the species-level analyses above. Note that Kf,d(r) and Kd(r) are independent of the overall phylogenetic structure of the community, and only driven by the small-scale spatial arrangement of individuals and their dissimilarities (Shenetal. 2013, Wiegandetal. 2017). Testing for significance We conducted multivariate spatial point pattern analyses to test if the locations of a focal species are independent of the landscape of phylogenetic (or phenotypic) neighbourhood 16000706, 2022, 12, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/oik.09260 by Csic Organización Central Om (Oficialia Mayor) (Urici), Wiley Online Library on [08/02/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License Page 6 of 14 dissimilarity (Shenetal. 2013, Wiegandetal. 2017). To test for spatial independence, we simulated 999 realizations of a toroidal shift null model that is sometimes called random shift null model (Lotwick and Silverman 1982, Wiegand and Moloney 2014, Tsakalos et al. 2022). It involves random shifts of the whole of the pattern of the focal species relative to the patterns of the heterospecifics that are left unchanged. In practice, the shifted pattern is reassembled by wrapping it on a torus (Wiegand and Moloney 2014). This procedure breaks the potential spatial association between the pattern of the focal species and the dissimilarity landscape formed by heterospecifics and maintains the spatial structure of the focal species in good approximation. In the case of the ‘bivariate’ adult–sapling analysis, we applied the toroidal shift to the sapling pattern of the focal species and kept the dissimilarity landscapes formed by the heterospecific adults unchanged. For community-wide analyses, we applied independent toroidal shifts to each species present in the plot, but in the adult–sapling analyses, we kept the adults unchanged. We evaluated the departures from the null model using the pointwise simulation envelopes (Fig. 1c) (i.e. the 25th lowest and highest values of the 999 simulations of the toroidal shift null model), and standardised effect size (SES) of the normalised summary statistics based on pointwise and global envelopes tests (Wiegandetal. 2016). The standardised effect size is given by SES(r) = (Fobs(r) − E[Fi(r)])/SD[Fi(r)], where Fobs(r) and Fi(r) are summary functions of the observed data and ith realization of the null model, respectively, and the operators E[.] and SD[.] indicate the expectation and standard deviation of the summary functions Fi(r), respectively. In case that the standardised effect size of the observed summary functions was lower than −1.96, or higher than 1.96, we obtained significant departures (p < 0.05) from the null model at the particular neighbourhood distance r (i.e. a point-wise test), indicating phylogenetic (or phenotypic) attraction (clustering) for positive departures or repulsion (overdispersion), respectively (otherwise there was independency; p > 0.05). Finally, we evaluated significant departures of the pattern up to 4 m for the adult–adult, and up to 3 m for the sapling–sapling and the sapling–adult schemes (i.e. a global test; Wiegandetal. 2016), since these distances are the mean values of the typical spatial cluster sizes of the focal species at these life stages (Pereaetal. 2021b). Note that cluster size allows for estimating mean values of the statistics in clusters with abundant species (i.e. patches of species). All analyses were conducted across life stages, at the community and species level, for both phylogeny and phenotype (i.e. phylogenetic dissimilarity and structural, morphologicalleaf and chemical-leaf dissimilarity). By using this approach, we assume that the current spatial structure of early life stages would be similar to the spatial structure of early life stages in the past, for example, the one that gave rise to the current structure of adult plants. This assumption is justified in old-stand forests without severe perturbations and homogeneous environments (Perea et al. 2021b). We used the software Programita (Wiegand and Moloney 2004, 2014, Wiegandetal. 2017) for spatial point pattern analysis. Results A total of 15 and 10 woody plant species were found in the small plots of MFJ and MFS, respectively. However, the surrounding community in their corresponding large plots was also composed of other less abundant species (see Supporting information in Pereaetal. 2021b). The number of individuals of each species allowed for point pattern analyses of nine species in each community. MFJ showed 3159 individuals, of which 17.7% were adults and 82.3% were saplings. MFS showed 2233 individuals, 36.3% adults and 63.7% saplings (Table 2). Phylogenetic and phenotypic landscape of the sapling neighbourhood The community-wide analyses indicated a lack of overall phylogenetic or phenotypic spatial structure of the sapling community (Fig. 2a, b), and saplings relative to the community of heterospecific adults (Fig. 3a, b). Thus, the mean dissimilarity of two randomly selected saplings less than the distance r apart cannot be distinguished from that expected from null communities of independently placed species. Despite the lack of overall phylogenetic or phenotypic spatial structure, we found for several species significant patterns of phylogenetic and/or phenotypic repulsion in the small-scale (3 m) saplings–saplings or saplings–adults analyses (Table 2). Examples include the species C. monogyna, P. lentiscus and Q. ilex at the MFJ plot, and C. laciniata, P. nigra, Q. ilex and Q. pyrenaica at the MFS plot). This result indicates that saplings of these species tend to be surrounded by ecologically more distant neighbours. Interestingly, several species (such as P. lentiscus and Q. ilex at MFJ, and C. laciniata, P. nigra, P. spinosa and Q. pyrenaica at MFS) showed consistently overdispersion in most sapling and sapling–adult analyses. However, only a single case of clustering occurred for the case of morphological traits and the species P. latifolia at the MFJ plot (Fig. 2e, Table 2). Phylogenetic and phenotypic landscape of the adult neighbourhood At the community level, adult locations depended on the phylogenetic landscape in both study sites (Fig. 4), we found in both plots significant phylogenetic clustering (Table 2). However, this clustering disappeared in neighbourhoods larger than 5 m in MFJ, whereas it persisted also at larger neighbourhoods in MFS (Fig. 4). Species-level results showed that the neighbourhood of adults of most species was not phylogenetically structured, with the only exception of C. monogyna, which showed phylogenetic clustering in both sites (Fig. 4a, b, Table 2). We found no spatial phenotypic structuring of the adult neighbourhoods regarding structural traits, and most of the species did not show an association to the landscape of structural traits dissimilarity, except for Pistacia lentiscus, which was usually surrounded by species more similar than expected 16000706, 2022, 12, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/oik.09260 by Csic Organización Central Om (Oficialia Mayor) (Urici), Wiley Online Library on [08/02/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License Page 7 of 14 Table 2. Results of the spatial phylogenetic and phenotypic analyses, separately for the MFJ and the MFS plot, for the entire community and individual species. The table shows the species, the number of sapling and adult individuals (and their sum) in each community and for each species, and the outcome of the null model analysis based on the cumulative phylogenetic mark correlation functions Kd,f(r) and Kd(r) that have the interpretation of the normalized mean pairwise dissimilarity between the typical individual of the focal species f, or the entire community, and all heterospecifics within distance r, respectively. Phy refers to the results of the analysis based on phylogenetic dissimilarity, whereas Str, Mor and Che refer to that structural, morphological and chemical phenotypic dissimilarity, respectively. Shown are the result of a global envelope test evaluated up to 3 m for sapling–sapling and sapling–adult analyses, and up to 4 m for adult–adult analyses. Significant positive (repulsion/overdispersion) and negative (attraction/clustering) departures from the toroidal shift null model are indicated by ‘+’ and ‘−’, respectively. ‘0’ indicates no significant departures and grey shaded cells indicate at species were not evaluated due to their low number of occurrence (i.e. adults of P. angustifolia, P. spinosa and Q. pyrenaica, and saplings of R. lycioides and J. communis). Plot Species No. of saplings No. of adults Total no. of individuals Landscape of dissimilarity (Kd,f(r) and Kd(r)) Saplings–saplings Saplings–adults Adults–adults Phy Str Mor Che Phy Str Mor Che Phy Str Mor Che MFJ Community 2601 547 3148 0 0 0 0 0 0 0 0 −0 0 0 R. lycioides 1 38 38 0 0 + 0 P. angustifolia 31 12 31 + 0 0 0 0 0 0 0 Q. ilex 48 27 75 + + + + + + + + 0 0 0 0 J. oxycedrus 65 75 140 0 + 0 0 0 + 0 0 0 0 0 0 P. lentiscus 93 84 177 + 0 0 + + + 0 + 0 −0 0 C. monogyna 153 52 205 0 0 0 0 + 0 + + −0 0 0 P. latifolia 417 47 464 0 0 −0 0 0 0 0 0 0 0 0 P. halepensis 489 133 622 0 0 0 0 0 0 0 0 0 0 0 0 Q. faginea 1305 91 1396 0 0 0 0 0 0 0 0 0 0 0 0 MFS Community 1422 787 2209 0 0 0 0 0 0 0 0 −0− − J. communis 1 23 23 0 0 −0 P. spinosa 20 14 20 + + + + + + + + Q. pyrenaica 42 9 42 + + + + + + + + C. laciniata 48 20 68 + + + + + + + + 0 0 0 0 P. nigra 55 460 515 0 + + + + + 0 + 0 0 0 0 Q.ilex 119 21 140 + 0 + + 0 0 0 0 0 0 0 − C. monogyna 265 220 485 0 0 0 0 0 0 0 0 −0−0 Q. faginea 355 22 377 0 0 + 0 0 0 0 0 0 0 0 0 A. grantense 518 21 539 0 0 0 0 0 0 0 0 0 0 0 0 16000706, 2022, 12, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/oik.09260 by Csic Organización Central Om (Oficialia Mayor) (Urici), Wiley Online Library on [08/02/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License Page 8 of 14 Distance (m) Saplings Phylogenetic dissimilarity Structural traits dissimilarity Chemical leaf trait dissimilarity 0.02.5 5.0 7.5 10.0 -4.0 0.0 4.0 8.0 12.0 1.96 -1.96 0.02.5 5.0 7.5 10.0 -4.0 0.0 4.0 8.0 12.0 1.96 -1.96 0.02.5 5.0 7.5 10.0 -4.0 0.0 4.0 8.0 12.0 1.96 -1.96 0.02.5 5.0 7.5 10.0 -4.0 0.0 4.0 8.0 12.0 1.96 -1.96 Morphological leaf trait dissimilarity Crataegus monogyna Juniperus oxycedrus Phillyrea angustifolia Phillyrea latifolia Pinus halepensis Pistacia lenticus Quercus faginea Quercus ilex MFJ Communit y SES of Kd (r) or Kdf(r) 0.02.5 5.0 7.5 10.0 -4.0 0.0 4.0 8.0 12.0 1.96 -1.96 0.02.5 5.0 7.5 10.0 -4.0 0.0 4.0 8.0 12.0 1.96 -1.96 0.02.5 5.0 7.5 10.0 -4.0 0.0 4.0 8.0 12.0 1.96 -1.96 0.02.5 5.0 7.5 10.0 -4.0 0.0 4.0 8.0 12.0 1.96 -1.96 Acer granatense Crataegus laciniata Crataegus monogyna Pinus nigra Prunus spinosa Quercus faginea Quercus ilex Quercus pyrenaica MFS Communit y SES of Kd (r) or Kdf(r) (a) (b) (d) (f) (h) (c) (e) (g) Figure2. Sapling–sapling analysis. Standardized effect sizes of the cumulative phylogenetic mark correlation functions Kd,f(r) and Kd(r) that have the interpretation of the normalized mean pairwise dissimilarity between the typical sapling of the focal species f, or of the entire community, and all heterospecific saplings within distance r, respectively. The panels show the results of phylogenetic (a, b), structural traits (c, d), morphological leaf traits (e, f) and chemical leaf traits (g, h) for the MFJ community (first row) and the MFS community (second row). Thick black lines represent the community pattern (Kd(r)), and coloured lines that of individual species (Kdf(r)). Significant departures from the toroidal shift null model (p < 0.05) occurred if the standardized effect sizes were higher or lower than 1.96 and −1.96 (red-dashed lines), indicating overdispersion (repulsion) or clustering (attraction), respectively (i.e. point-wise test). 0.02.5 5.0 7.5 10.0 -4.0 0.0 4.0 8.0 12.0 1.96 -1.96 0.02.5 5.0 7.5 10.0 -4.0 0.0 4.0 8.0 12.0 1.96 -1.96 0.02.5 5.0 7.5 10.0 -4.0 0.0 4.0 8.0 12.0 1.96 -1.96 0.02.5 5.0 7.5 10.0 -4.0 0.0 4.0 8.0 12.0 1.96 -1.96 Phylogenetic dissimilarity Structural traits dissimilarity Chemical leaf trait dissimilarity Morphological leaf trait dissimilarity 0.02.5 5.0 7.5 10.0 -4.0 0.0 4.0 8.0 12.0 1.96 -1.96 0.02.5 5.0 7.5 10.0 -4.0 0.0 4.0 8.0 12.0 1.96 -1.96 0.02.5 5.0 7.5 10.0 -4.0 0.0 4.0 8.0 12.0 1.96 -1.96 0.02.5 5.07.5 10.0 -4.0 0.0 4.0 8.0 12.0 1.96 -1.96 Distance (m) Saplings-Adults Crataegus monogyna Juniperus oxycedrus Phillyrea angustifolia Phillyrea latifolia Pinus halepensis Pistacia lenticus Quercus faginea Quercus ilex MFJ Community Acer granatense Crataegus laciniata Crataegus monogyna Pinus nigra Prunus spinosa Quercus faginea Quercus ilex Quercus pyrenaica MFS Communit y SES of Kd (r) or Kdf(r) SES of Kd (r) or Kdf(r) (a) (c) (e) (g) (f) (h)(d)(b) Figure3. Sapling–adult analysis. Same as Fig. 2, but for the normalized mean pairwise dissimilarity between the typical sapling of the focal species f, or of the entire sapling community, and all heterospecific adults within distance r, respectively. 16000706, 2022, 12, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/oik.09260 by Csic Organización Central Om (Oficialia Mayor) (Urici), Wiley Online Library on [08/02/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License Page 9 of 14 (Table 2). At the MFJ plot, we found a similar lack of spatial phenotypic structuring for morphological and chemical leaf traits at the community and the species level (Table 2). However, in the MFS plot, we found spatial phenotypic clustering of the adult neighbourhoods concerning morphological and chemical leaf traits up to 4 m (Fig. 4f, h, Table 2). At the species level, C. monogyna and J. communis showed clustering concerning morphological traits and Q. ilex showed clustering concerning chemical leaf traits (Table 2). Discussion In this study, we explored the phylogenetic and phenotypic dissimilarity of saplings and adults to their neighbours in two Mediterranean mixed pine–oak forest communities to gain insight into the mechanisms driving their assembly. To this end, we analysed data of two fully mapped plots with recent techniques of spatial point pattern analyses (Wiegandetal. 2017) to quantify the observed spatial phylogenetic and phenotypic structure across life stages, and to compare it to null expectations. At the community level (i.e. the average structure across species), saplings did not show any spatial phylogenetic or phenotypic neighbourhood structure, nor to heterospecific saplings or heterospecific adults (i.e. they showed phylogenetical/phenotypic independence). In contrast, adults were surrounded by phylogenetically more similar neighbours (i.e. phylogenetic clustering) and we found at the MSF community phenotypic clustering of adults regarding morphological and chemical leaf traits. A review by Cadotte et. al (2019) shows that patterns of phylogenetic and functional dispersion do not necessarily agree. Accordingly, we have found under-dispersed phylogenetic and phenotypic patterns at MFS, while the under-dispersed phylogenetic patterns at MFJ occurred in the absence of significant dispersion in functional traits (Table 2). At the species level, saplings were frequently surrounded by phylogenetically and phenotypically more dissimilar neighbours from both, the saplings and the adults community. However, adults showed only for a few species phylogenetical and phenotypic structures, and in these cases, we found mostly phylogenetic and phenotypic attraction. These general differences between life stages, both at the community and species levels, were consistent at both study sites, and provide clues about the mechanisms that may determine the spatial assembly of these communities. Methodological issues We applied here the relatively recent point pattern framework of diversity metrics that integrates a spatially explicit perspective with information on functional and phylogenetic relationships (Shenetal. 2013, Pelissier and Goreaud 2015, Wangetal. 2015, 2016, Wiegandetal. 2017) to quantify phylogenetic or phenotypic spatial structures in the neighbourhood of individual plants as a function of spatial scale. This allowed us to take a more nuanced approach to spatial analyses on diversity metrics compared to the more traditional quadrat-based approach (Webbetal. 2002, Kembel and Hubbell 2006, Kraftetal. 2007) that neglect the full smaller-scale spatially explicit information inside quadrats, which was important for our analyses. The community-level cumulative phylogenetic mark correlation function Kd(r) is closely related to spatially-explicit extensions of commonly used measures of Crataegus monogyna Juniperus oxycedrus Phillyrea latifolia Pinus halepensis Pistacia lenticus Quercus faginea Quercus ilex Rhamnus lycioides MFJ Community Adults 0.02.5 5.0 7.5 10.0 -4.0 0.0 4.0 8.0 12.0 1.96 -1.96 0.02.5 5.0 7.5 10.0 -4.0 0.0 4.0 8.0 12.0 1.96 -1.96 Structural traits dissimilarity 0.02.5 5.0 7.5 10.0 -4.0 0.0 4.0 8.0 12.0 1.96 -1.96 Chemical leaf trait dissimilarity 0.02.5 5.0 7.5 10.0 -4.0 0.0 4.0 8.0 12.0 1.96 -1.96 Morphological leaf trait dissimilarity Phylogenetic dissimilarity Acer granatense Crataegus laciniata Crataegus monogyna Juniperus communis Pinus nigra Quercus faginea Quercus ilex MFS Community 0.02.5 5.0 7.5 10.0 -4.0 0.0 4.0 8.0 12.0 1.96 -1.96 0.02.5 5.0 7.5 10.0 -4.0 0.0 4.0 8.0 12.0 1.96 -1.96 0.02.5 5.0 7.5 10.0 -4.0 0.0 4.0 8.0 12.0 1.96 -1.96 0.02.5 5.0 7.5 10.0 -4.0 0.0 4.0 8.0 12.0 1.96 -1.96 Distance (m) SES of Kd (r) or Kdf(r) SES of Kd (r) or Kdf(r) (a) (c) (c) (g) (b) (f)(d) (h) Figure4. Adult–adult analysis. Same as Fig. 2, but for the community of adults. 16000706, 2022, 12, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/oik.09260 by Csic Organización Central Om (Oficialia Mayor) (Urici), Wiley Online Library on [08/02/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License