Published August 16, 2024 | Version v1
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Data and code from: Species interactions amplify functional group responses to elevated CO2 and N enrichment in a 24-year grassland experiment

  • 1. University of Minnesota

Description

Plant functional groups differ in their response to global changes, although species within those groups also vary in such responses. Both species and functional group responses to global change are likely influenced by species interactions such as inter-specific competition and facilitation, which are prevalent in species mixtures but not monocultures. As most studies focus on responses of plants growing in either monocultures or mixtures, but rarely both, it remains unclear how interspecific interactions in diverse ecological communities, especially among species in different functional groups, modify functional group responses to global changes. To address these issues, we leveraged data from a 16-species, 24-year perennial grassland experiment to examine plant functional group biomass responses to atmospheric CO2, and N inputs at different planted diversity. Functional groups differed in their responses to N and CO2 treatments in monocultures. Such differences were amplified in mixtures, where N enrichment strongly increased C3 grass success at ambient CO2 and C4 grass success at elevated CO2. Legumes declined with N enrichment in mixtures at both CO2 levels and increased with elevated CO2 in the initial years of the experiment. Our results suggest that previous studies that considered responses to global changes in monocultures may underestimate biomass changes in diverse communities where interspecific interactions can amplify responses. Such effects of interspecific interactions on responses of functional groups to global change may impact community composition over time and consequently influence ecosystem functions.

Notes

Funding provided by: Division of Environmental Biology
ROR ID: https://ror.org/03g87he71
Award Number: 0620652

Funding provided by: Division of Biological Infrastructure
ROR ID: https://ror.org/04qn9mx93
Award Number: 2021898

Funding provided by: Department of Energy and Environment
ROR ID: https://ror.org/05d5hbz44
Award Number: DE-FG02-96ER62291

Funding provided by: Division of Environmental Biology
ROR ID: https://ror.org/03g87he71
Award Number: 1234162

Funding provided by: Division of Environmental Biology
ROR ID: https://ror.org/03g87he71
Award Number: 1831944

Funding provided by: Division of Environmental Biology
ROR ID: https://ror.org/03g87he71
Award Number: 1242531

Funding provided by: Division of Environmental Biology
ROR ID: https://ror.org/03g87he71
Award Number: 1753859

Funding provided by: Division of Environmental Biology
ROR ID: https://ror.org/03g87he71
Award Number: 1120064

Funding provided by: Division of Environmental Biology
ROR ID: https://ror.org/03g87he71
Award Number: 0322057

Funding provided by: Division of Environmental Biology
ROR ID: https://ror.org/03g87he71
Award Number: 2224854

Methods

From the manuscript:

Experiment design: The BioCON experiment, which manipulates Biodiversity, N and CO2, was started in 1997 at Cedar Creek Ecosystem Science Reserve (East Bethel, MN, USA, 45°40′N, 93°18′W), a Long-Term Ecological Research site. The compositionally neutral full-factorial experiment comprised 296 plots that varied in their initial planted diversity (1,4, 9 or 16 species), N (ambient or + 4 g m-2 year-1) and CO2 (ambient or +180ppm) treatments applied in a split-plot design for the CO2 treatment (Reich, Knops, et al., 2001). The diversity gradient was created by experimentally assembling plant communities with 1 species, random selection of 4 or 9 species and/or all 16 species. As 36 of the 9 species plots have since been used for a sub-experiment involving temperature and drought treatments, we excluded those plots from our analyses leaving 260 plots. The species were chosen to represent common or naturalized prairie species in the region and spanned four functional groups: C3 grasses (Bromus inermisElymus repens [formerly Agropyron repens], Koeleria macrantha [formerly Koeleria cristata], and Poa pratensis), C4 grasses (Andropogon gerardiiBouteloua gracilisSchizachyrium scoparium, and Sorghastrum nutans), legumes (Amorpha canescensLespedeza capitataLupinus perennis, and Petalostemum villosum), and non-legume forbs (Achillea millefoliumAnemone cylindricaAsclepias tuberosa, and Solidago rigida). Since the species composition was randomly chosen for the 4 and 9 species plots, each replicate for these two diversity levels differs in species and FG composition. Species found in a plot other than those originally planted there were weeded annually. Additionally, to maintain the study site in a grassland state, the plots were burnt in spring for half of the years between 2000 to 2012 (Adair et al., 2009) and every fall since 2013.

Plant biomass

Late in each growing season in August in the majority of plots in almost all years, aboveground biomass in a pre-marked 10 x 100 cm strip was clipped and sorted to the species level. The part of the plot from which biomass data were collected shifted annually to reduce potential influence of clipping on a single part of the plot. Species-specific cover data from a constant predetermined and never clipped 50 x 100 cm region of the plot were also recorded for every plot each year (except for a subset of 4 species plots during 2020 as all efforts were scaled down due to the pandemic). Using cover and biomass data we then generated species-specific correlations between the two to estimate biomass data for all years based on cover data. This step allowed us to a) impute biomass values when only cover data were available; and b) obtain a more representative estimate of biomass for the plot as cover data spanned a larger area of the plot compared to clip-strip biomass data.

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