Computational protocol: Frugivory in Canopy Plants in a Western Amazonian Forest: Dispersal Systems, Phylogenetic Ensembles and Keystone Plants

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Protocol publication

[…] We constructed a community matrix where each cell Xij represents the number of fruits of plant j manipulated by the frugivore i. We used non-metric multidimensional scaling (NMDS) to examine subsets of plant species consumed by frugivores, and a canonical analysis to explore the fruit traits associated with the ordination. In order to test some predictions regarding the hypothesis on the existence of generalized vs. specialized dispersal systems, we used a nonparametric ordination of plants, mainly based on plant traits such as seed width, % of lipids in the pulp, crop size, and crop duration [], using the vegan package in R. In addition, we used simple regression models to test seven predictions from this theory: pulp quality (i.e. lipid content) should be positively associated with 1) crop duration, 2) seed size, 3) frugivore size, and negatively associated with 4) crop size, 5) visitation rate, 6) the number of visiting species, and 7) the probability to recruit below parents []. In addition, a non-parametric ordination based on the percentage of fruits manipulated by each frugivore species was generated to examine potential grouping of plants based on frugivore types.To assess pulp quality per fruit, we measured the proportion of lipids. Seed width was considered as a proxy of seed size []. Information on crop size and duration was extracted from phenological studies including four years of phenological sampling []. The degrees of freedom for these analyses varied, depending mainly on the number of species with nutritional information (N = 15–39). We also used regression models to explain feeding times from the abundance of each frugivore. Primate densities were estimated using line transect methods []. Avian abundance was extrapolated from the relationship between the density estimates on line transects (measured for Pipile pipile, Penelope jaquacu, and Psophia crepitans) and the frequency of observations of bird species in the study site (n = 3075) [].Potential plant filters to exclude frugivores were analyzed using the phylogenetic community indices: net relatedness index and nearest taxon index (NRI and NTI, respectively). These indices measure the evolutionary distance of co-occurring species in terms of the length of connecting branches in phylogenetic trees, comparing the mean distance among all species in the assemble (NRI) or the distance among the near taxon (NTI) with a null random distribution []. We used a swap model to avoid the influence of species richness and frequency in our estimates. In both indices, negative values represent phylogenetic overdispersion and positive values represent phylogenetic aggregation.The phylogeny of frugivore assemblages was reconstructed using mitochondrial DNA sequences published in GenBank. We aligned these sequences using the Muscle algorithm with default parameters. Then we reconstructed a phylogenetic tree using BEAST software. Also, we used node age estimates to calibrate our tree from previous phylogenetic studies.On the other hand, we obtained a phylogenetic tree to plant species in our dataset from Phylomatic [], using the Angiosperm Phylogeny Group’s consensus tree (R2010829). We calibrated this phylogeny based on Wilkstrom et al. [] node dates applying bladj algorithm in Phylocom []. NRI and NTI were calculated in Picante package in R.To explore potential keystone plant species in terms of well connected nodes or hub nodes important for network’s stability, we used the community consumption matrix () as input to compute weighted and un-weighted network indices of the bipartite network with the Bipartite 2.05 package from R []. Computed indices are based on connectivity and centrality of a node in relation to the remaining nodes in the network [–] and in addition ecological information was used to identify keystone species. Selected un-weighted indices consider merely structural and connective features for each species, while weighted indices consider interaction strength as the number of manipulated fruits (). For instance, closeness indices identify the shortest paths connecting one node to the rest of the nodes in the network []. Likewise, betweenness quantifies how many times a node is on the shortest path between all other node pairs in the network []. Nodes densely connected that are often intermediate between two other nodes in the network are thought to modulate and propagate stability and extinction processes within a community by being the central connection between two or more sections [–]. Nestedness of the binary matrix was calculated using the NODF metric (Nestedness metric based on Overlap and Decreasing Fill, []) and compared with the CE (row-column probability) and the ER (absolute random) models with 1000 replicates implemented in Aninhado 3.0 [], and the species’ nestedness rank calculated using Bipartite 2.05 []. To simplify value interpretation, values of d’ i, d, nestedness rank (NR) and species specificity index (SSP) were converted as 1-i. The specialization index for the matrix (H2’) was calculated using the Bipartite 2.05 package from R []. The resulting index was compared with the distribution of the H2’ values obtained from a set of 500 null matrices generated using the function null model under the vasnull method implemented in Bipartite. Using the Mass package for R [], NMDS and correlation tests were performed to search for redundancy among all indices excepting NODF and H2’. Additionally, species were classified as peripheral or core species (lower and higher number of interactions compared with other nodes in the same trophic level, respectively) following Dáttilo and coworkers [].To measured cumulative secondary extinctions (Bipartite, R) at the plant and frugivore trophic level, we replicated the matrix and from each manually removed one-plant nodes with higher connectance and betweenness indexes values. We subsequently estimated robustness of each matrix using Bipartite and randomly removing species from the matrix. Robustness, the area beneath the secondary extinction slope, estimates the resistance of the network to extinction.Finally, we compared all these network indices with an approach of energy flow through ecosystem levels, which estimates the amount of dry pulp biomass going from each plant to the herbivore level. This estimate was based on the rate of consumption for each species (fruits.h-1.tree-1), proportion of pulp in the fruit, crop duration (mo), and adult plant density (trees.ha-1). All information from plant traits and plant demography can be found in [, ]. We also compared with a list of potential keystone species in the area based on its production on scarcity periods, temporal consistency and the number of consumers []. […]

Pipeline specifications

Software tools Phylomatic, Phylocom, Picante
Application Phylogenetics