Herbivory and nutrients shape grassland soil seed banks
Data files
Jun 21, 2023 version files 266.97 KB
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aboveground_biomass_data.csv
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NutNet_seedbank_aboveground_all.csv
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plot_info.csv
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README.md
Abstract
Anthropogenic nutrient enrichment and shifts in herbivory can lead to dramatic changes in the composition and diversity of aboveground plant communities which, in turn, can alter cryptic biodiversity storage, seed banks, in the soil. We used data from seven Nutrient Network grassland sites on four continents, encompassing a range of climatic and environmental conditions, to test the joint effects of fertilization and aboveground mammalian herbivory on seed banks and on the similarity between aboveground plant communities and seed banks. Fertilization decreased plant species richness and diversity in seed banks, and homogenized composition between aboveground and seed bank communities. Fertilization increased seed bank abundance especially in the presence of herbivores, while this effect was smaller in the absence of herbivores. Our findings highlight that nutrient enrichment can weaken the temporal storage effect as a diversity maintaining mechanism and that herbivory needs to be considered when assessing nutrient enrichment effects on seed bank abundance.
Methods
There are several datasets associated with this work.
- A dataset that contains plant community composition data, in two parts
- A seedbank dataset that was collected from sites, seeds were grown from the soil, counted and identified.
- An aboveground plant community dataset where plant cover was collected in m2 quadrats. Within these quadrats plants were identied to the lowest taxonomic unit, and then the percent cover was estimated
- a plot information dataset that contains all the treatment data for each plot across all the sites in the experiment
- A dataset that contains biomass sorted to functional group for each plot in the dataset. Biomass was collected in two 0.1 m2 plots, combined, sorted to functional group (forbs, graminoids, legumes and litter), then scaled to the m2 scale.
Usage notes
We use R and R Studio to run these files. All are open source.