Data from: Partitioning the effects of plant diversity on ecosystem functions at different trophic levels
Data files
Feb 15, 2022 version files 638.54 KB
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Abundance.csv
185.02 KB
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Biomass.csv
196.46 KB
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Insect_herbivory.csv
112.06 KB
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Pathogen_infection.csv
122.80 KB
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Plot_information.csv
16 KB
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README.txt
5.47 KB
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Species_information.csv
732 B
Feb 15, 2022 version files 636.82 KB
-
Abundance.csv
185.02 KB
-
Biomass.csv
196.46 KB
-
Insect_herbivory.csv
112.06 KB
-
Pathogen_infection.csv
122.80 KB
-
Plot_information.csv
16 KB
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README.md
3.75 KB
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Species_information.csv
732 B
Abstract
Biodiversity effects on ecosystem functioning can be partitioned into complementarity effects, driven by many species, and selection effects, driven by few. Selection effects occur through interspecific abundance shifts (dominance) and intraspecific shifts in functioning. Complementarity and selection effects are often calculated for biomass, but very rarely for secondary productivity, i.e. energy transfer to higher trophic levels. We calculated diversity effects for three functions: aboveground biomass, insect herbivory and pathogen infection, the latter two as proxies for energy transfer to higher trophic levels, in a grassland experiment (PaNDiv) manipulating species richness, functional composition, nitrogen enrichment and fungicide treatment. Complementarity effects were on average positive and selection effects negative for biomass production and pathogen infection and multiple species contributed to diversity effects in mixtures. Diversity effects were on average less pronounced for herbivory. Diversity effects for the three functions were not correlated, because different species drove the different diversity effects. Benefits (and costs) from growing in diverse communities, be it reduced herbivore or pathogen damage or increased productivity either due to abundance increases or increased productivity per area were distributed across different plant species, leading to highly variable contributions of single species to diversity effects on different functions. These results show that different underlying ecological mechanisms can result in similar overall diversity effects across functions.
README: Data from: Partitioning the effects of plant diversity on ecosystem functions at different trophic levels
https://doi.org/10.5061/dryad.zs7h44jbp
Description of the data and file structure
This data is from the PaNDiv experiment. Methodological details can be found in the associated manuscript.
Files and variables
File: Plot_information.csv
Description: Treatment information for the plots
Variables
- Bock: unique Block number(1-4)
- Plot: unique plot number (1-336)
- Nitrogen: fertilization information (0 = no fertilizer, 1 = nitrogen added)
- Fungicide: pathogen exclusion treatment (0 = control, 1 = fungicide)
- composition: plant species composition index (string indicating species richness (first number), unique species combination (second number), and whether the comination of species was assembled from the fast (f), slow (s) or mixed (m) species pool). Monocultures have the species abbreviation to indicate composition.
- Species_diversity: number of species sown in a plot. (1, 4, 8 or 20)
- Sown sla: Mean SLA of sown species
- Sown mpd sla: Mean pairwise difference in SLA of sown species.
- Notes: Excluded monocultures for the analysis are flagged.
File: Species_information.csv
Description: Information on plant species in PaNDiv
Variables
- Species: Species abbreviation
- Binomial_ name: Binomial species name
- Pool: Species pool to which the species belongs (F: fast growing species, S: slow growing species)
- Notes: Species that were excluded for the analysis in the associated manuscript are flagged
File: Abundance.csv
Description: relative abundance (cover) of species per plot and timepoint
Variables
- Plot: unique plot number (1-336)
- Harvest: time point when the data was collected (J17 = June 2017, A17 = August 2017, J18 = June 2018, A18 = August 2018)
- Species: Species abbreviation (full name can be found in the species information data sheet)
- Abundance: relative abundance of the species (proportion of cover. visually estimated)
File: Biomass.csv
Description: plant biomass collected 5cm above ground in each plot and time point
Variables
- Plot: unique plot number (1-336)
- Harvest: time point when the data was collected (J17 = June 2017, A17 = August 2017, J18 = June 2018, A18 = August 2018)
Species: Species abbreviation (full name can be found in the species information data sheet)
Biomass: Species biomass calculated based on plot biomass and relative abundance [g/m^2]
Notes: notes
File: Pathogen_infection.csv
Description: Pathogen infection measured as proportion of individuals with disease symptoms per species, plot and timepoitn
Variables
- Plot: unique plot number (1-336)
- Harvest: time point when the data was collected (J17 = June 2017, A17 = August 2017, J18 = June 2018, A18 = August 2018)
Species: Species abbreviation (full name can be found in the species information data sheet)
Infection: Proportion of individuals with diseases symptoms
Notes: notes
File: Insect_herbivory.csv
Description: Herbivory measured as proportion of individuals with herbivory symptoms per species, plot and timepoitn
Variables
- Plot: unique plot number (1-336)
- Harvest: time point when the data was collected (J17 = June 2017, A17 = August 2017, J18 = June 2018, A18 = August 2018)
Species: Species abbreviation (full name can be found in the species information data sheet)
Herbivory: Proportion of individuals with herbivory symptoms
Notes: notes
Access information
Other publicly accessible locations of the data:
- NA
Data was derived from the following sources:
- own data
Methods
For full details on data collection see the associated publication.
Usage notes
Please see the readme file for a description of the datasets included and meta data on the variables.