Data and code from: Similar trait-based successional assembly in native and introduced plants despite species pool differences
Data files
Mar 21, 2024 version files 7.24 MB
-
composition_formatted.csv
-
composition_raw.csv
-
fields.csv
-
README.md
-
sampling_history.csv
-
sampling_years.csv
-
species_info_metadata.csv
-
species_info.csv
-
traits_metadata.csv
-
traits.csv
Abstract
What drives the composition of invaded communities and the local abundance of introduced species are key questions in ecology. Community-assembly theory provides a useful framework for addressing these questions. Specifically, the environmental filtering model of community assembly predicts that a species’ presence and abundance in a community depends on the interaction between its functional traits and the local environmental filters. However, for introduced species, larger-scale dispersal and introduction-related filters may restrict their regional trait pool. Here we tested this framework using long-term data from 50+ years of old-field vegetation succession. We asked whether native and introduced plant assemblages followed the same trait-based assembly rules. We also asked whether local functional dissimilarities between the two can be explained by regional species pool differences, a possibility that has rarely been addressed. We found strong similarities in the assembly processes of native and introduced plants. Average height and seed mass of both groups increased over time, consistent with previous studies of old-field succession. Moreover, the two showed similar trait-abundance relationships. While there were also some differences, particularly in their trait-incidence relationships, these differences appeared to be minor.Further, we identified species pool constraints on introduced species, and found that the exotic species pool was biased towards early successional traits. Lastly, we found that highly invasive exotic species were also likely to deviate from the expected trait-abundance relationship, suggesting a link between the two. These results suggest that introduced species generally follow the same assembly rules as native species. They also indicate that species pool differences can result in local functional composition differences, even when the two groups follow the same assembly rules. Moreover, there may be a link between species invasiveness and deviation from assembly rules, which, if further confirmed, provides a potential method of identifying strong invaders.
README: Data & Code From: Similar trait-based successional assembly in native and introduced plants despite species pool differences
https://doi.org/10.5061/dryad.gxd2547ss
This dataset contains the community composition data from the Buell-Small Succession study (https://www.caryinstitute.org/science/research-projects/past-projects/buell-small-succession-study), along with trait data gathered by Li et al. (2015) and Duffin et al. (2019), and code from Poddar et al., (in press). Older versions of the Buell-Small dataset, along with partial trait data, are available at: 1) https://doi.org/10.5061/dryad.fn5g2 , 2) https://datadryad.org/stash/dataset/doi:10.5061/dryad.j968847 . The code available here have not been previously archived.
Duffin, K.I., Li, S.P. and Meiners, S.J., 2019. Species pools and differential performance generate variation in leaf nutrients between native and exotic species in succession. Journal of Ecology, 107(2), pp.595-605.
Li, Shao peng, Marc W. Cadotte, Scott J. Meiners, Zheng shuang Hua, Lin Jiang, and Wen sheng Shu. 2015. “Species Colonisation, Not Competitive Exclusion, Drives Community Overdispersion over Long-Term Succession.” Ecology Letters 18 (9): 964–73. https://doi.org/10.1111/ELE.12476.
Description of the data and file structure
Data files:
composition_raw.csv - raw community composition data from the Buell-Small Succession study. Each row corresponds to an observation of a species in a given plot in a given year. Column names: DATAID - unique ID number for each row; YEARID - ID number of sampling year (see sampling_years.csv for list of sampling years and their respective ID numbers), FIELDID - ID number of the field in which the observation took place (see fields.csv for list of fields and their respective ID numbers), PLOTID - ID number of the plot in which the observation took place, SPECIESID - species ID number (see species_info.csv for list of species names and their respective ID numbers), COVER - percentage cover of the given species in the given plot (maximum possible value= 200), STEMS - number of stems of the given species, for tree species only; empty cells in this column mean that the number of stems was not counted for the corresponding species, as it was not a tree species.
composition_formatted.csv - formatted composition data, used in the analyses presented in Poddar et al. Data from all plots in a field (in a given year) were combined by summing over the cover of each species in each plot. Column names: Year_Field - the year and field where each observation took place (year and field combined into a single column for ease of analysis); Year - year of observation; Field - name of field in which the observation took place; all other column names represent abbreviated species names (see species_info.csv for names of species and their corresponding abbreviations), and values in these columns are the cover of the corresponding species in the corresponding field and year (maximum possible value = 9600). The code in 0_Data_Formatting.R was used for converting raw composition data to formatted composition data.
fields.csv - list of fields in the Buell-Small study, along with information about their initial conditions, i.e. season of abandonment (SEASON column, F=fall, S=spring), last crop (CROP column; R=row crop, H=hay crop), whether they were plowed before abandonment (PLOWING column; B=bare, i.e. plowed, L=intact litter, i.e., not plowed), and whether they are fenced (as of 2019; FENCE column; Y=fenced, N=not fenced). FIELDNAME = name of each field (the letter and number in each field's name is based on the field's location relative to survey coordinates, but this location information is not relevant for this study. Further information about field locations/the meaning of each field's name can be obtained by contacting Scott Meiners: sjmeiners@eiu.edu ).
sampling_history.csv - sampling history of each field, i.e., the years in which each field was sampled. Also contains information about the year of abandonment of each field (FIRSTYEAR column), and the successional age of the field (i.e., the number of years since abandonment) during each sampling year (AGE column). The columns Age_Field (age and field name combined) and Year_Field (year and field name combined) were created for the analyses.
sampling_years.csv - list of sampling years and their respective ID numbers.
species_info.csv - information about each species observed in the Buell-Small study, along with a list of species abbreviations (ABBR) and species ID numbers (SPECIESID). Includes information on scientific name, taxonomy, species origin (native or exotic), functional group and life-form, etc. See species_info_metadata.csv for information on each column. Missing data indicated by empty cells, except in the ORIGIN column (denoted by "X" in this column).
traits.csv - functional traits of each species. Leaf traits and leaf nutrient traits were measured by authors of previous studies (see Sharing/Access information section). All other data were gathered from published literature and databases, by the authors of previous studies. Only SLA, height, and seed mass data was used in this study. Column names and data units are explained in traits_metadata.csv. Also see Duffin et al. (2019) and Li et al. (2015) for details (full citations in Sharing/Access Information section). Empty cells = missing data.
species_info_metadata.csv - Explanation for each column in the species_info.csv file.
traits_metadata.csv - Explanation for each column in the traits.csv file.
Code files:
0_Data_Formatting.R - code for formatting composition data
1_Trait_Composition_Regressions.R - code for the trait-composition regression analysis (results presented in figures 2 and 3 of Poddar et al.)
2_Functional_Composition_Trends.R - code for the analysis on trends in functional composition (results presented in figure 4 and tables 1 and 2 in Poddar et al.)
3_Species_Pool_Analysis.R - code for the analysis on species pool differences and their effect on functional composition (results presented in figures 5 and 6, and tables S1 and S2)
Supp1a_2a_Spatial_Convergence_Taxonomic.R - code for the analysis on taxonomic beta diversity (presented in Supplement 2), and the relative cover of introduced species over time (figure S1).
Supp2b_Temporal_Turnover_Taxonomic.R - code for the analysis on rate of turnover in taxonomic composition (presented in Supplement 2)
Supp3a_Trait_Composition_Relationship_Year.R - code for the analysis on trait composition relationship using calendar year instead of field age (presented in Supplement 3).
Supp3b_Functional_Composition_by_Year.R - code for the analysis on functional composition, using calendar year instead of field age (presented in Supplement 3)
Supp3c_Species_Pool_Analysis_by_Year.R - code for the species pool analysis, using calendar year instead of field age (presented in Supplement 3)
Supp4_Overall_trait_composition_relationships.R - code for the ANCOVAs testing the overall relationship between traits and composition, and for differences between native and introduced species in their trait-composition relationships. (presented in Supplement 4)
Supp5_Identifying_Rule_Breakers.R - code for the analysis on identifying rule-breaking introduced species (presented in Supplement 5)
Sharing/Access information
The community composition and trait data presented here is also partially available at:
Trait data was originally gathered for (and used in) the following studies:
Duffin, K.I., Li, S.P. and Meiners, S.J., 2019. Species pools and differential performance generate variation in leaf nutrients between native and exotic species in succession. Journal of Ecology, 107(2), pp.595-605.
Li, Shao peng, Marc W. Cadotte, Scott J. Meiners, Zheng shuang Hua, Lin Jiang, and Wen sheng Shu. 2015. “Species Colonisation, Not Competitive Exclusion, Drives Community Overdispersion over Long-Term Succession.” Ecology Letters 18 (9): 964–73. https://doi.org/10.1111/ELE.12476.
All code and formatted data files are original and not available elsewhere.
Code/Software
All code was written and run in R version 4.2.0.