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ABSTRACT Tropical deforestation is occurring at alarming rates, creating an urgent need for global prioritization of restoration efforts. One potential forest recovery strategy is to boost seed‐dispersing animal activity (e.g., fruit‐eating bats) to increase seed availability in degraded areas. In this study, we investigated the efficacy of synthetic chemical lures in attracting fruit bats and enhancing seed rain in northeastern Costa Rica. The chemical lures were composed of a few volatile organic compounds commonly found in ripe bat‐dispersed fruits. Daily deployment of the chemical lures resulted in a significant increase in the capture ofCarolliaspp., a key neotropical seed disperser, but no detectable effect on other fruit bats. The 15‐day deployment of chemical lures also increased the average of total seeds collected in seed traps. However, the effect of lures explained only a small portion of the total variance in seed rain, highlighting the potential context‐dependency of these results. Still, in contrast to the previously studied essential oil‐based lures, synthetic lures hold the potential to be applied across a broader spectrum of restoration initiatives due to simplified manufacturing and improved reproducibility. Although additional research is essential to understand the full potential for use in restoration efforts, our study demonstrates the effectiveness of synthetic chemical lures in attracting fruit bats and potentially augmenting seed rain. 

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. 

Abstract Frugivore foraging behavior is largely influenced by two key groups of chemical traits: nutrients and secondary metabolites. Many secondary metabolites function in plant defense, but their consumption can negatively impact both mutualistic and antagonistic frugivores, often due to toxic properties of the metabolites or through nutrient absorption interference. Frugivores are assumed to maximize nutrient acquisition while avoiding or minimizing toxic metabolite intake, but the relative roles of co‐occurring nutrients and secondary metabolites in foraging behavior are not well understood. Here, we used a neotropical fruit bat to investigate the interactive effects of nutrients and a broadly bioactive fruit secondary metabolite, piperine, on two essential processes in nutrient acquisition, namely foraging behavior and nutrient absorption. Through the manipulation of nutrient and piperine concentrations in artificial diets, we showed that captive fruit bats prioritize nutrient concentrations regardless of the levels of piperine, even though piperine is a strong deterrent on its own. Furthermore, our findings reveal that while piperine has no detectable influence on total sugar absorption, it reduces protein absorption, which is a crucial and limited nutrient in the frugivore diet. Overall, our results demonstrate the importance of considering the interaction between co‐occurring chemical traits in fruit pulp to better understand frugivore foraging and physiology. 

Abstract Ripe fleshy fruits contain not only nutrients but also a diverse array of secondary metabolites. Nutrients serve as a reward for mutualists, whereas defensive metabolites protect the fruit against pests and predators. The composition of these chemical traits is highly variable, both across different plants and even within repeating structures on the same individual plant. This intraspecific and intraindividual variation has important fitness consequences for both plants and animals, yet patterns of variation and covariation in nutrients and secondary metabolites are not well understood, especially at smaller scales. Here, we investigate the multiscale variation and covariation between nutrients and defensive metabolites inPiper sancti‐felicisripe fruits. Means and measures of variation of sugars, proteins, phenolics, and alkenylphenols vary greatly among plants, and at least 50% of the trait variation occurs at the intraindividual level. Also, we found that proteins, but not sugars, were correlated with phenolics and alkenylphenols at multiple scales, suggesting trait variation in protein content may be more constrained than sugars. Our findings emphasize the importance of examining patterns across scales and provide the groundwork to better understand how complex patterns of variation and covariation in nutrients and defensive metabolites shape ecological interactions surrounding fruits. 

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. 

Data from: Interactions between nutrients and fruit secondary metabolites shape bat foraging behavior and nutrient absorption; by Gelambi, M., Morales-M. E., & Whitehead, S. R. Published in Ecosphere, 2024. The study was conducted at La Selva Biological Station, Costa Rica during June-July 2021. We employed neotropical fruit bats (Carollia perspicilla) as a model to investigate how nutrients and a broadly bioactive fruit secondary metabolite, piperine (Sigma-Aldrich), interact and influence two critical aspects of nutrient acquisition: foraging behavior and nutrient absorption. By manipulating nutrient and piperine concentrations in artificial diets, we reveal that captive fruit bats prioritize nutrient concentrations, even in the presence of piperine's potent deterrent effects. Additionally, our findings indicate that while piperine exerts no detectable influence on total sugar absorption, it significantly reduces protein absorption. 

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. 

Interactions between plants and herbivores are central in most ecosystems, but their strength is highly variable. The amount of variability within a system is thought to influence most aspects of plant-herbivore biology, from ecological stability to plant defense evolution. Our understanding of what influences variability, however, is limited by sparse data. We collected standardized surveys of herbivory for 503 plant species at 790 sites across 116° of latitude. With these data, we show that within-population variability in herbivory increases with latitude, decreases with plant size, and is phylogenetically structured. Differences in the magnitude of variability are thus central to how plant-herbivore biology varies across macroscale gradients. We argue that increased focus on interaction variability will advance understanding of patterns of life on Earth. 

Original data and R code accompanying our paper in Ecology & Evolution by Gelambi M. & Whitehead, S. R. (2023).  Ripe fleshy fruits contain not only nutrients but also a diverse array of many secondary metabolites. Nutrients serve as a reward for mutualists, whereas defensive metabolites protect the fruit against pests and predators. The composition of these chemical traits is highly variable, both across different plants and even within repeating structures on the same individual plant. This intraspecific and intraindividual variation has important fitness consequences for both plants and animals, yet patterns of variation and covariation in nutrients and secondary metabolites are not well understood, especially at smaller scales. Here, we investigate the multiscale variation and covariation between nutrients and defensive metabolites in Piper sancti-felicis ripe fruits. Means and variances of sugars, proteins, phenolics, and alkenylphenols vary greatly among plants, and at least 50% of the trait variation occurs at the intraindividual level. Also, we found that proteins, but not sugars, were correlated with phenolics and alkenylphenols at multiple scales, suggesting trait variation in protein content may be more constrained than sugars. Our findings emphasize the importance of examining patterns across scales and provide the groundwork to better understand how complex patterns of variation and covariation in nutrients and defensive metabolites shape ecological interactions surrounding fruits.