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Geographical variation in the trait-based assembly patterns of multitrophic invertebrate communities

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NIAID Data Ecosystem2026-03-13 收录
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http://datadryad.org/dataset/doi%253A10.5061%252Fdryad.vt4b8gtv4
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It has been argued that the mechanisms structuring ecological communities may be more generalizable when based on traits than on species identities. If so, patterns in the assembly of community-level traits along environmental gradients should be similar in different places in the world. Alternatively, geographic change in the species pool and regional variation in climate might result in site-specific relationships between community traits and local environments. These competing hypotheses are particularly untested for animal communities. Here we test the geographic constancy of trait-based assembly patterns using a widespread multi-trophic community: aquatic macroinvertebrates within bromeliads. We used data on 615 invertebrate taxa from 1656 bromeliads in 26 field sites from Mexico to Argentina. We summarized invertebrate traits with four orthogonal axes, and used these trait axes to examine trait convergence and divergence assembly patterns along three environmental gradients: detrital biomass and water volume in bromeliads, and canopy cover over bromeliads. We found no overall signal of trait-based assembly patterns along any of the environmental gradients. However, individual sites did show trait convergence along detrital and water gradients, and we built predictive models to explore these site differences. Sites that showed trait convergence along detrital gradients were all north of the Northern Andes. This geographic pattern may be related to phylogeographic differences in bromeliad morphology. Bromeliads with low detritus were dominated by detritivorous collectors and filter feeders, where those with high detritus had more sclerotized and predatory invertebrates. Sites that showed the strongest trait convergence along gradients in bromeliad water were in regions with seasonal precipitation. In such sites, bromeliads with low water were dominated by soft-bodied, benthic invertebrates with simple life cycles. In less seasonal sites, traits associated with short-term desiccation resistance, such as hard exoskeletons, were more important. In summary, we show that there are strong geographic effects on the trait-based assembly patterns of this invertebrate community, driven by the biogeography of their foundational plant species as well as by regional climate. We suggest that inclusion of biogeography and climate in trait-based community ecology could help make it a truly general theory. (excerpted from Srivastava, DS et al. 2022. Geographical variation in the trait-based assembly patterns of multitrophic invertebrate communities. Functional Ecology) Methods Bromeliad and macroinvertebrate data We compiled data on the aquatic macroinvertebrates in tank bromeliads previously sampled in 26 different sites throughout the natural distribution of the tank bromeliads (Bromeliaceae family). Field sites were distinct from each other in space, elevation and the species composition of invertebrate communities. For every bromeliad, all water and detritus contained in the plant were removed, either by dissecting the plant or by pipetting. The water and detritus were examined for aquatic macroinvertebrates in small size-fractioned aliquots in white trays. Macroinvertebrates were identified to morphospecies in the field, and subsequently to the lowest possible taxonomic level. The detritus was oven-dried and weighed to determine dry mass. Bromeliads were sampled across a range of habitats, from exposed restinga (coastal sand-based shrub habitat) in Brazil to cloud forests on Caribbean mountaintops to rainforests in Central America. As no bromeliad genus was found in all field sites, we sampled the most common genera in sites. Our analysis included three environmental characteristics of each sampled bromeliad: (1) the dry mass of all detritus in the bromeliad (hereafter “detritus”, measured in grams); (2) the volume of standing water in each bromeliad on the day of sampling (hereafter “water”, measured in mL); (3) the openness of the canopy above the bromeliad (hereafter “canopy”, a binary variable with 1 = open canopy and 0 = closed canopy). These variables were chosen because previous site-specific research had established that they were important environmental drivers of community structure and function. Trait data Our analysis considers interspecific, but not intraspecific, differences in traits. In Céréghino et al. (2018), each bromeliad invertebrate morphospecies was scored in terms of twelve traits: aquatic developmental stage, body form, maximum body size, cohort production interval, dispersal mode, food, feeding group, locomotion, morphological defence, reproduction mode, resistance forms and respiration mode.Each trait was represented by several modalities or categories (e.g. the modalities for the trait “dispersal mode” were passive and active), and the affinity of the taxa for each modality was fuzzy coded. In total, the 12 traits were represented by 64 modalities.  Céréghino et al. (2018) reduced these 64 trait modalities to four orthogonal axes using PCA (original data:https://knb.ecoinformatics.org/view/doi:10.5063/F1VD6WMF). Since then, there have been modest updates to the trait data: some trait scores were improved, the number of missing values reduced, a few microscopic or terrestrial species were removed, and the taxonomic resolution of some species identifications was improved. We therefore reran the PCA analysis on the updated trait matrix, using the same R script as in Céréghino et al. (2018), and used the first four axes in our current study. Site information We collated information on biogeographic, bioclimatic, and sampling characteristics of each field site in order to better contextualize differences among sites. Biogeographic characteristics included position north and north west versus south and southeast of the Northern Andes (simplified hereafter as north versus south of Andes). The Northern Andes are known to be a dispersal barrier for both bromeliads  and bromeliad invertebrates. Although the Southern and Central Andes could be a potential barrier between the west coast and center of South America, we have no bromeliad data from the former and so do not analyse these mountain ranges. We examined species pool richness, estimated with Chao’s method (implemented in the vegan R package), to test if richer sites had stronger trait-environment matching. From the WorldClim database, we extracted site-specific estimates of four bioclimatic variables that a previous study (Guzman et al., 2020) found to underlie spatial variation in bromeliad macroinvertebrate traits: mean diurnal range in temperature (BC2), temperature annual seasonality (BC4), precipitation annual seasonality (BC15) and precipitation of the driest quarter (BC17). WorldClim data was extracted at the 1km2 scale; when field sites exceeded 1 km2 in size we averaged data over the relevant 1 km2 pixels. Finally, we examined sampling characteristics of each site, including the number of bromeliads sampled (which affects the power of tests) and the site mean of the focal environmental gradient (in case trait-environment relationships differ with site position on gradient). Data processing We organized the abundance data using the R package fwdata (developed by A.A.M.M, https://github.com/SrivastavaLab/fwdata). We then converted abundances to biomass by multiplying abundance by the estimated per capita biomass of each morphospecies, based on taxon-specific allometric relationships, using the hellometry R package (provided courtesy of P. Rogy, https://github.com/pierrerogy/hellometry). Summary In sum, the dataset consists of information on environmental attributes of bromeliads (n = 1656), macroinvertebrate morphospecies (n = 615), macroinvertebrate traits (n = 64), local environmental gradients (n = 3) and field sites (n = 26). (text excerpted from Srivastava, DS et al. 2022. Geographical variation in the trait-based assembly patterns of multitrophic invertebrate communities. Functional Ecology)
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2022-05-23
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