DOI: 10.5061/dryad.905qftv04
title: Plant functional diversity does not dilute virus infection, but community virus prevalence positively correlates with net C<sub>3</sub> grass production

description: Plant diversity in wild and agricultural plant communities has been shown
 to protect plant communities from pathogens, and the effects of many
 aspects of diversity (genetic diversity, species richness, evenness, and
 their combination) on plant pathogen epidemiology have been examined.
 Diversity among plant functional groups (e.g., grasses, legumes, and
 non-leguminous forbs) is known to reduce plant diseases in natural and
 agricultural plant communities. However, potential interactions among
 plant functional groups and their effects on plant virus infection
 dynamics have not been examined. Insect-vectored plant virus infection
 dynamics may differ among distinct plant host functional types (C3 vs. C4)
 due to differences in their palatability to aphid vectors, and plant
 physiological responses to environmental factors. Here, we evaluated the
 role of plant functional group diversity (richness and composition), and
 host functional type (three C3 and three C4 species), on plant virus
 infection in experimental annual plant communities that were inoculated
 with aphids carrying barley yellow dwarf virus (BYDV), a widespread and
 economically important generalist grass virus. We also assessed the
 relationships between community-level virus prevalence and the
 productivity of the total community (grasses + forbs+ legumes), as well as
 the component plant functional types. In this study, virus infection was
 not mitigated or amplified by increasing functional group richness or
 altered functional group composition, nor did virus infection vary between
 C3 and C4 grasses. However, we found a positive correlation between
 community-level virus prevalence and C3 grass production (but not C4
 production). Synthesis. Our findings indicated that plant virus infection
 in grasses was not diluted by plant functional group diversity. However,
 we found a positive relationship between community-level virus prevalence
 and C3grass productivity. Together, these findings suggest that while
 plant diversity did not reduce the infection levels of a cryptic plant
 virus, mutualistic plant-virus interactions may contribute to enhanced
 ecosystem functioning via increased productivity.
description: # Plant functional diversity does not dilute virus infection, but
 community virus prevalence positively correlates with net C~3~ grass
 production Dataset DOI:
 [10.5061/dryad.905qftv04](https://doi.org/10.5061/dryad.905qftv04) ##
 Description of the data and file structure We evaluated the role of plant
 functional group diversity (richness and composition), and host functional
 type (three C~3~ and three C~4~ species), on plant virus infection in
 experimental annual plant communities that were inoculated with aphids
 carrying barley yellow dwarf virus (BYDV), a widespread and economically
 important generalist grass virus. We also assessed the relationships
 between community-level virus prevalence and the productivity of the total
 community (grasses + forbs+ legumes), as well as the component plant
 functional types. ### Files and variables #### File: biomass.data.csv
 **Description:** This dataset contains the net aboveground production of
 each plant species within each experimental plot for each study year.
 Biomass was collected from plots that varied in plant functional group
 composition and richness. Each plot is nested within a block and was
 assigned a grass functional type (C~3~ or C~4~) and plant functional group
 diversity treatment. ##### Variables * Year: Year in which the biomass was
 collected.  * Block: Experimental block in which the plot was located.  *
 Plot: Unique identifier for each experimental plot within a block. *
 Species: Plant species name for which biomass was recorded. *
 GrassType: Grass functional type present in the plot (C~3~ or C~4~). *
 PlantType: Functional group to which the species belongs (e.g. grass,
 legume or forb). * FuncDiversity: Functional diversity treatment (G, G+L,
 G+F, G+L+F) of the plot. * planted_fg_richness: Number of plant functional
 groups planted in the plot. * Biomass_grams.m2:  Measured aboveground
 biomass of the species (g/m^2^). #### File: virus.data.csv
 **Description:** This dataset includes virus infection data for individual
 grass host samples collected from experimental plots differing in plant
 functional group diversity and grass host functional type. Each row
 represents a sample tested for barley yellow dwarf virus (BYDV-PAV)
 infection status. ##### Variables * Year: Year in which grass hosts were
 sampled for virus infection. * Block: Experimental block in which the plot
 was located.  * Plot: Unique identifier for each experimental plot within
 a block. * FunctionalDiversity: Functional diversity treatment (G, G+L,
 G+F, G+L+F) of the plot. * GrassType: Grass functional type present in the
 plot (C~3~ or C~4~). * Species: Plant species name that was sampled for
 BYDV-PAV infection. * PAV_Infection: Binary infection status of the sample
 (0=uninfected, 1=infected with BYDV-PAV) * fg_richness: Number of plant
 functional groups planted in the plot. #### File: Precip_data.csv
 **Description:**  This dataset includes precipitation data in inches for
 the two years of this study, 2021 and 2022. ##### Variables * Year: Year
 in which the precipitation data was recored. * Month: Month in which the
 precipitation data was recored. * MonthlySum_inches: Total monthly
 precipitation in inches. * DepartureFromNormal: Precipitation difference
 in inches of total monthly precipitation from the normal  average monthly
 precipitation from 1991 to 2020.  * PercentOfNormal: Precipitation percent
 of the normal average monthly precipitation from 1991 to 2020.  *
 Normal_1991to2020: The average monthly precipitation from 1991 to 2020. 
 #### File: climate_data.csv **Description:** This dataset includes
 temperature, relative humidity and VPD data for the two years of this
 study, 2021 and 2022. ##### Variables * year: Year in which the data was
 recored. * date: Date (mm/dd/yy) in which the data was recored. * month:
 Month in which the data was recored. * date_num: Numeric date in which the
 data was recored. * hour: Hour in which the data was recored (0-23h). *
 Temp_c: Temperature in celcius. * RH: Relative humidity in percent. *
 VPD_kpa: Vapor Pressure Deficit in kilopascal. * Prec: Precipitation in
 inches. ## Code/software The code is available on Zenodo:
 [https://doi.org/10.5281/zenodo.17561785](https://doi.org/10.5281/zenodo.17561785) (Aguirre et al. 2025).  Code in written in R. ## Access information Precipitation and climate data from the Ithaca Airport Weather Station was requested and obtained from the Northeast Regional Climate Center.