DOI: 10.5061/dryad.j9kd51ct2
title: Are they two seeds in a pod? Comparing seed rain recovery in grasslands using artificial grass carpets versus sticky traps

description: Premise: Seed dispersal is a critical process for plant community
 assembly; however, natural rates of seed arrival are rarely quantified
 compared with other assembly mechanisms, especially in herbaceous
 communities. Methods: Here we compare the utility of artificial grass
 carpet squares (“artificial grass”) for capturing seed rain with classic
 “sticky trap” methods. We placed paired sticky traps and artificial grass
 squares in two grassland ecosystems, added known numbers of seeds of
 multiple species to each trap, and recovered seeds at one-week, one-month,
 and two-month intervals. Results: We found that both trap types lost seeds
 through time at similar rates, but each trap type had advantages and
 disadvantages. Overall, sticky traps retained more seeds and measured
 primary dispersal, but recovering seeds was difficult and hindered by
 debris stuck to the traps. Alternatively, artificial grass traps measured
 effective dispersal as more seeds were lost through time to secondary
 dispersal and granivory, but recovered seeds could be handled easily and
 retained for long-term storage and germination. Discussion: We encourage
 the broad adoption of seed rain studies to improve links between
 theoretical and empirical community ecology. Both sticky traps and
 artificial grass traps are useful in measuring seed rain in grasslands but
 vary in the types of information they provide.  
description: # Are they two seeds in a pod? Comparing seed rain recovery in grasslands
 using artificial grass carpets versus sticky traps Dataset DOI:
 [10.5061/dryad.j9kd51ct2](https://doi.org/10.5061/dryad.j9kd51ct2) ##
 Description of the data and file structure Seed recovery data was
 collected from two trap types (artificial turf and sticky traps) at two
 sites (Colorado and Missouri) over the course of one week, one month, and
 two months. ### Files and variables #### File:
 Carpet_Methods_Code_Dryad.Rmd **Description:** .Rmd code to run analyses
 and create figures, and produce an .html file to display results. ####
 File: seed_recovery_all.csv **Description:** Data from the seed recovery
 experiment ##### Variables * site: Location where the experiment was
 conducted (mo = Missouri, co = Colorado) * block: Block randomization
 factor and random effect (1-10) * plot: The specific plot that seed
 recovery was measured at * time_month: How long the traps were left in the
 field (0.25 = 1 week, 1 = 1 month, 2 = 2 months) * treatment: the type of
 seed arrival trap used (carpet = artificial turf, sticky = sticky trap,
 post-sticky = sticky trap sat in the field for a month, then had seeds
 distributed on it). * species: The plant species code for the seed species
 we used in the experiment. Plant codes are the first three letters of the
 genus name and the first three letters of the species name. Running the
 full code here provides the full names of the species. * number_recovered:
 The number of seeds recovered for each species. * number_original: The
 number of seeds of each species placed on each trap * number_herbivorized:
 The number of seeds that showed evidence of herbivory * notes: any sort of
 note we might need to take. * pct_recovered: the percent of recovered
 seeds (number recovered/number original) * mean_1seed: the average weight
 of one seed of that species in mg * sd_1seed: the standard deviation of
 seed weight of on seed of that species in mg * number_lost: the number of
 seeds removed in the experiment (number_original - number_recovered) ####
 File: Carpet-Methods-Code_Dryad.html **Description:** an .html print out
 of the code that runs all analyses and figures. ## Code/software The file
 "Carpet Methods Code_Dryad.Rmd" runs all the data in R version
 4.3.3 and R Studio version 2024.12.0+467. This file describes all the
 working directories used to create the output files.  They are also listed
 below: ``` library(tidyverse) library(RColorBrewer) library(viridis)
 library(cowplot) library(glmmTMB) library(ggeffects) library(emmeans) ``` 
 
 The basic protocol includes: 1. Reading data in  2. Creating exploratory
 figures (Figures 2 and 3 in the manuscript) 3. Running analyses and
 creating Figure 4 and 5 4. Running analyses for the supplemental materials
 
 
 ## Access information Other publicly accessible locations of the data: *
 [https://github.com/Sullivan-Lab/project_CarpetMethods](https://github.com/Sullivan-Lab/project_CarpetMethods)