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1. Frugivore Traits Predict Plant–Frugivore Interactions Using Generalized Joint Attribute Modeling

   https://doi.org/10.1002/ece3.70772  

   Yohe, Laurel_R; Leiser‐Miller, Leith_B; Kaliszewska, Zofia_A; Whitehead, Susan_R; Santana, Sharlene_E; Dávalos, Liliana_M (January 2025, Ecology and Evolution)

   ABSTRACT Under an adaptive hypothesis, the reciprocal influence between mutualistic plants and frugivores is expected to result in suites of matching frugivore and plant traits that structure fruit consumption. Recent work has suggested fruit traits can represent adaptations to broad groups of functionally similar frugivores, but the role of frugivore traits and within‐species variation in structuring fruit consumption is less understood. To address these knowledge gaps, we assess the presence of reciprocal trait matching for the mutualistic ecological network comprising ofCarolliabats that feed on and dispersePiperseeds. We used generalized joint attribute modeling (GJAM), a Bayesian modeling approach that simultaneously accounts for multiple sources of variance across trait types. In support of frugivore adaptation to their dietary composition and suggesting niche partitioning amongCarolliabats, we find differential consumption of a suite ofPiperspecies influenced by bat traits such as body size; however, thePipermorphological traits considered had no effect on bat consumption. Slow evolutionary rates, dispersal by other vertebrates, and unexamined fruit traits, such asPiperchemical bouquets, may explain the lack of association between batPiperconsumption and fruit morphological traits. We have identified a potential asymmetric influence of frugivore traits on plant–frugivore interactions, providing a template for future trait analyses of plant–animal networks. As intraspecific trait variation is rarely included in studies on trait matching, this paper contributes to closing that important knowledge gap. 

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2. Fruit odorants mediate co-specialization in a multispecies plant–animal mutualism

   https://doi.org/10.1098/rspb.2021.0312  

   Santana, Sharlene E.; Kaliszewska, Zofia A.; Leiser-Miller, Leith B.; Lauterbur, M. Elise; Arbour, Jessica H.; Dávalos, Liliana M.; Riffell, Jeffrey A. (August 2021, Proceedings of the Royal Society B: Biological Sciences)

   null (Ed.)

   Despite the widespread notion that animal-mediated seed dispersal led to the evolution of fruit traits that attract mutualistic frugivores, the dispersal syndrome hypothesis remains controversial, particularly for complex traits such as fruit scent. Here, we test this hypothesis in a community of mutualistic, ecologically important neotropical bats ( Carollia spp.) and plants ( Piper spp.) that communicate primarily via chemical signals. We found greater bat consumption is significantly associated with scent chemical diversity and presence of specific compounds, which fit multi-peak selective regime models in Piper . Through behavioural assays, we found Carollia prefer certain compounds, particularly 2-heptanol, which evolved as a unique feature of two Piper species highly consumed by these bats. Thus, we demonstrate that volatile compounds emitted by neotropical Piper fruits evolved in tandem with seed dispersal by scent-oriented Carollia bats. Specifically, fruit scent chemistry in some Piper species fits adaptive evolutionary scenarios consistent with a dispersal syndrome hypothesis. While other abiotic and biotic processes likely shaped the chemical composition of ripe fruit scent in Piper , our results provide some of the first evidence of the effect of bat frugivory on plant chemical diversity. 

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3. Data from: "Testing the effectiveness of synthetic chemical lures to increase fruit bat-mediated seed dispersal in a tropical forest"

   https://doi.org/10.5281/zenodo.14336713  

   Gelambi, Mariana; Whitehead, Susan R (January 2024, Zenodo)

   This repository contains scripts, information, and figures related to the statistical analyses conducted for the research paper “Testing the effectiveness of synthetic chemical lures to increase fruit bat-mediated seed dispersal in a tropical forest.” Our research explores the effectiveness of synthetic chemical lures as a novel strategy to attract fruit bats and enhance seed rain in a lowland rainforest in northeastern Costa Rica (La Selva Biological Station). We investigated the impact of chemical lures on increasing bat activity and seed rain. All the analyses were performed in R v. 4.2.1. Scripts 1. Objective 1: Assess the effectiveness of the chemical lure to increase bat activity in open and semi-open areas (script1.R and script2.R) These scripts details the process of analyzing the impact of chemical lures on bat activity. script1.R compares bat communities across different sites and treatments. Non-metric multidimensional scaling (NMDS) was employed for visualization. Homogeneity of variances was checked using the ‘betadisper()’ function, followed by permutational multivariate analysis of variance (PERMANOVA) using the ‘adonis2()’ function with 999 permutations. In script2.R GLMMs were employed using the glmmTMB package. The models included the bat abundance as fixed effect, and site and capture date as random effects. The analysis was performed using various count data distributions from the glmmTMB package Overdispersion and zero inflation were assessed using the ‘check_overdispersion()’ and ‘check_zeroinflation()’ functions from the performance package. Effect sizes were computed based on estimated marginal means using the ‘emmeans()’ function from the emmeans package. We performed an autocorrelation analysis on the residuals of each model fitted. First, we performed a Durbin-Watson (DW) using the function ‘dwtest()’ from the lmtest package to test to assess temporal autocorrelation in these residuals. Then, we generated a visual representation of the autocorrelation function (ACF). Our results indicate that there is no temporal autocorrelation present in our bat data. 1. Objective 2: Assess the effectiveness of the chemical lure to increase seed rain of open and semi-open areas (script3.R) This script outlines the analysis of the impact of chemical lures on seed rain NMDS was used for visualization, and homogeneity of variances was checked with ‘betadisper()’. PERMANOVA was conducted using the ‘adonis2()’ function with 999 permutations to test for statistical significance.   Data Files Folder Objective 1: data.csv and data_nodates.csv Contains the data used for analyzing bat activity. The columns in the dataset are as follows: date: The date of bat capture. site: The site where the capture took place. bats: Total number of bats captured. fruit_bats: Total number of captured fruit bats. cperspicillata: Number of captured Carollia perspicillata bats. csowelli: Number of captured Carollia sowelli bats. ccastanea: Number of captured Carollia castanea bats. carollia_spp: Total number of captured bats from the Carollia genus. uroderma_spp: Number of captured bats from the Uroderma genus. sturnira_spp: Number of captured bats from the Sturnira genus. ectophylla_alba: Number of captured Ectophylla alba bats. artibeus_spp: Number of captured bats from the Artibeus genus. desmodus_rotundus: Number of captured Desmodus rotundus bats. nectarivorous_bats: Number of captured nectarivorous bats. insectivorous_bats: Number of captured insectivorous bats. treatment: The treatment applied (“control” or “lures”). hours: Total hours of mist nesting. nets: Total number of nets used for bat capture. Folder Objective 2: seed_data.csv Contains the data used for analyzing seed rain. The columns in the dataset are as follows: week: The week of the seed collection. Seeds were collected every 15 days. site_name: The name of the site where the observation took place at La Selva (“Zompopa”, “Lab”, “STR - Sendero Tres Rios”, “PS - Parcelas de Sucesion”). site_letter: The site’s letter designation (“A”, “B”, “C”, “D”) collection_date: The date of seed collection. treatment: The treatment applied (“baseline”, “control”, “treatment”). Columns for various plant species/plant families, indicating the count of seeds for each species. total: The total count of seeds for all plant species per collection week. comments: Additional comments or notes about the observation. Figures folder The ‘Figures’ folder contains various output files generated from the analyses conducted in the main scripts. These figures represent the results and insights obtained from the data exploration and statistical modeling. 

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4. Untargeted Metabolomics Reveals Fruit Secondary Metabolites Alter Bat Nutrient Absorption

   https://doi.org/10.1007/s10886-024-01503-z  

   Gelambi, Mariana; Whitehead, Susan_R (May 2024, Journal of Chemical Ecology)

   Abstract The ecological interaction between fleshy fruits and frugivores is influenced by diverse mixtures of secondary metabolites that naturally occur in the fruit pulp. Although some fruit secondary metabolites have a primary role in defending the pulp against antagonistic frugivores, these metabolites also potentially affect mutualistic interactions. The physiological impact of these secondary metabolites on mutualistic frugivores remains largely unexplored. Using a mutualistic fruit bat (Carollia perspicillata), we showed that ingesting four secondary metabolites commonly found in plant tissues affects bat foraging behavior and induces changes in the fecal metabolome. Our behavioral trials showed that the metabolites tested typically deter bats. Our metabolomic surveys suggest that secondary metabolites alter, either by increasing or decreasing, the absorption of essential macronutrients. These behavioral and physiological effects vary based on the specific identity and concentration of the metabolite tested. Our results also suggest that a portion of the secondary metabolites consumed is excreted by the bat intact or slightly modified. By identifying key shifts in the fecal metabolome of a mutualistic frugivore caused by secondary metabolite consumption, this study improves our understanding of the effects of fruit chemistry on frugivore physiology. 

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5. Data from: "Untargeted Metabolomics Reveals Fruit Secondary Metabolites Alter Bat Nutrient Absorption"

   https://doi.org/10.5281/zenodo.11002933  

   Gelambi, Mariana; Whitehead, Susan (January 2024, Zenodo)

   Data from: Untargeted Metabolomics Reveals Fruit Secondary Metabolites Alter Bat Nutrient Absorption; by Gelambi, M. & Whitehead, S. R. Published in the Journal of Chemical Ecology, 2024. Using a mutualistic fruit bat (Carollia perspicillata), our research explores how four secondary metabolites (piperine, tannin acid, eugenol, and phytol) commonly found in plant tissues affect the foraging behavior and induce changes in the fecal metabolome. In this study, bats were captured and housed in flight cages. Nightly trials exposed them to varying concentrations of secondary metabolites. Objective 1 involved non-choice trials to measure food consumption, while Objective 2 evaluated the impact of metabolite consumption on the bat fecal metabolome. Fecal samples were collected, stored, and later analyzed to understand how secondary metabolites influence bat behavior and metabolism. All the analyses were performed in R v. 4.2.1. 

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