Sex-driven neighborhood effects on herbivory in the dioecious Mediterranean palm Chamaerops humilis L.

Although it is well recognized that the strength of plant–herbivore interactions can vary with the plant sex, the distance, and the density of conspecific neighbors, no study has yet assessed their combined influence. Here, we filled this knowledge gap by focusing on the dioecious palm Chamaerops humilis L., and its two main herbivores, the invasive moth Paysandisia archon Burmeister and the feral goat Capra hircus L. We evaluated levels and spatial patterns of herbivory, as well as those of plant size and number of inflorescences in two palm populations in Mallorca (Balearic Islands, Spain). Our spatial point pattern analyses revealed that palms not affected by moth herbivory or goat florivory were spatially aggregated, goats fed more strongly upon inflorescences in palms with more neighbors, but they consumed more leaves in isolated palms. Interestingly, we could reveal for the first time that plant sex is a key plant trait modulating neighborhood effects. For instance, whereas aggregated female palms experienced lower intensity of goat florivory than isolated ones, male palms showed the opposite pattern. Palm size and number of inflorescences also showed sex-related differences, suggesting that sexual dimorphism is a key driver of the observed neighborhood effects on herbivory. Our study highlights the importance of considering relevant plant traits such as sex when investigating plant neighborhood effects, calling for further research to fully understand the dynamics governing plant–herbivore interactions in dioecious systems. Supplementary Information The online version contains supplementary material available at 10.1007/s00442-023-05457-z.

:  Mark connection functions p ij (r) are the adapted summary functions of quantitatively marked patterns.In this data structure each point carries a point, either of type 1 or of type 2 (e.g., attacked vs. unattacked).The interest in the analysis of qualitatively marked patterns is e.g., to find out how strongly attacked palms are aggregated within the joined pattern of all palms.This requires to remove the confounding spatial effect of the unmarked pattern (i.e., formed by all palms of type 1 and type 2), which is contained in the corresponding pair correlation functions g ij (r).Mark connection functions accomplish this by dividing g ij (r) by the pair correlation function g 1+2,1+2 (r) of the unmarked pattern: where m i is the quantitative mark of the focal plant i, µ is the mean quantitative mark of the population, λ the overall density of plants in the study area, λg i (r) the density of neighbors around the focal plant i at distance r, and λg(r) the mean density of neighbors at distance r for all trees.The g i (r) is basically a 'local' g-function, and the average over all g i (r)'s yields the well-known pair-correlation function g(r).Estimation of g i (r) requires an edge correction factor w i if the neighborhood around plant i is not fully within the observation window.The density correlation function C m,g (r) is normalized by the product of the standard deviations σ m σ g of the marks m i and the individual g-functions g i (r), respectively.'C' stands for correlation, 'm' for the first mark m i and 'g' for the second mark g i (r). Figure S3.The correlation between the intensity of moth herbivory (blue), goat florivory (yellow) and goat folivory (green) on focal palms and the density of their conspecific neighbors at distance r depending on the palm sex (female vs. male) in the EB plot.The univariate density correlation functions C m1,g1 (r) and C m2,g2 (r) estimate the correlation between the herbivore-attack intensity of female or male palms, respectively, and the number of neighbors of the same sex at distance r.The bivariate density correlation functions C m1,g2 (r) and C m2,g1 (r) estimate the correlation between the herbivore-attack intensity of female or male palms, respectively, and the number of neighbors of the opposite sex at distance r.The grey dashed lines represent the expected functions of the null models, the dotted lines are the functions for the observed data, and the colored shades show the global simulation envelopes for each type of herbivory.P values from the GoF test are shown only for significant effects.Note that Figures S3a-c refer to Figure 3a (female-female), Figures S3d-f to Figure 3b (female-male), Figures S3g-i to Figure 3c (male-male), and Figures j-l to Figure 3d (male-female) from the main document.
Figure S4.The correlation between the intensity of moth herbivory (blue), goat florivory (yellow) and goat folivory (green) on focal palms and the density of their conspecific neighbors at distance r depending on the palm sex (female vs. male) in the PF plot.The univariate density correlation functions C m1,g1 (r) and C m2,g2 (r) estimate the correlation between the herbivore-attack intensity of female or male palms, respectively, and the number of neighbors of the same sex at distance r.The bivariate density correlation functions C m1,g2 (r) and C m2,g1 (r) estimate the correlation between the herbivore-attack intensity of female or male palms, respectively, and the number of neighbors of the opposite sex at distance r.The grey dashed lines represent the expected functions of the null models, the dotted lines are the functions for the observed data, and the colored shades show the global simulation envelopes for each type of herbivory.P values from the GoF test are shown only for significant effects.Note that Figures S4a-c refer to Figure 3e (female-female), Figures S4d-f to Figure 3f (female-male), Figures S4g-i to Figure 3g (male-male), and Figures S4j-l to Figure 3h (malefemale) from the main document.
Figure S5.Conspecific neighborhood effects on key plant traits influencing herbivory such as the number of inflorescences (yellow circles) and palm size (i.e. the total number of stems, green triangles) depending on the palm sex (female vs. male) in EB (ad) and PF (eh).The univariate density correlation functions C m1,g1 (r) and C m2,g2 (r) estimate the correlation between the plant trait of female or male palms, respectively, and the number of neighbors of the same sex at distance r.The bivariate density correlation functions C m1,g2 (r) and C m2,g1 (r) estimate the correlation between the plant trait of female or male palms, respectively, and the number of neighbors of the opposite sex at distance r.The grey dashed lines represent the expected functions of the null models, the dotted lines are the functions for the observed data, and the colored shades show the global simulation envelopes for each plant trait.P values from the GoF test are indicated only for significant effects.
() =       ()  1+2,1+2()    where the g ij(r)  are partial or bivariate pair correlation function that quantifies the relative density of type j plants around type i plants (where i and j can have values of 1 or 2), g 1+2,1+2 (r) is the pair correlation function of the unmarked pattern, and p i is the proportion of type i plants among all plants.Specifically, the mark connection function p11(r) measures the conditional probability that both of two plants separated by distance r have the qualitative mark 1.If plants of type 1 are a random sample of all plants, we expect p 11 (r) = p 1 p 1 .If they are aggregated within all plants, we find p 11 (r) > p 1 p 1 .If they are isolated within all plants, we find p 11 (r) < p 1 p 1 .The mark connection function p22(r) measures the conditional probability that both of two plants separated by distance r have the qualitative mark 2. To calculate it, we use the same equation as for p 11 (r). Test statistic g1,1+2(r) -g2,1+2(r): It indicates whether plants of type 1 are preferentially located in areas of overall high plant density (i.e.clusters).This test statistic compares the density of plants (i.e.1+2) around plants of type 1 [g 1,1+2 (r)] with the density of plants (i.e.1+2) around plants of type 2 [g 2,1+2 (r)].The expected value of this test statistics is zero under random labelling, but if plants of type 1 occur disproportionately within plant clusters we expect g 1,1+2 (r) > g 2,1+2 (r) .Given that this summary statistic still conserves the signal of the underlying unmarked pattern, we also normalize it by the pair correlation function of the unmarked pattern [(g 1,1+2 (r)g 2,1+2 (r))/g 1+2,1+2 (r)].In this way, the difference is expressed as fraction of the average neighborhood density of palms at the given distance r.This allows for a more direct interpretation of the strength of the density effect because the normalized difference factors out the effect of underlying spatial pattern of all palms. Density correlation function C m,g (r): It estimates the classical Pearson correlation coefficient between the quantitative mark m i of a plant and the number of neighbors at distance r [=λg i (r)].Thus, the density correlation function is based on the following test function:

Figure S2 .
Figure S2.The probability and intensity of moth herbivory (blue), goat florivory (yellow) and goat folivory (green) on focal palms related to the distance and density of their conspecific neighbors in the PF plot.The normalized difference function (g 1,1+2 (r) -g 2,1+2 (r))/g 1+2, 1+2 (r) investigates if attacked palms have at distance r more palm neighbors (i.e., attacked + unattacked) than unattacked palms; and the univariate density correlation function C m,g (r) estimates the correlation between the herbivoreattack intensity suffered by palms and the number of their neighbors.The grey dashed lines represent the expected functions of the null models, the dotted lines are the functions for the observed data, and the colored shades show the global simulation envelopes for each type of herbivory.P values from the GoF test are shown only for significant effects.Note that Figures S2a-c and Figures S2d-f refer to Figure 1g and Figure 1h from the main document, respectively.