DOI: 10.25338/b8805v
title: Herbivores can benefit both plants and their pathogens through selective herbivory on diseased tissue

description: Infectious disease can be a key driver of community structure,
 particularly when pathogens affect foundation species. Seagrasses are
 foundation species that form meadows along coasts worldwide, controlling
 sediment deposition and biogeochemical cycling while supporting a diverse
 community of fish and invertebrates. These plants are affected by wasting
 diseases that cause necrotic tissue lesions. These lesions could alter
 seagrass value as food, habitat, and mediators of ecosystem processes,
 though biotic influences on disease dynamics are still not well
 understood. We explored the role of one eelgrass herbivore in affecting
 the development of wasting disease. We measured the severity and
 prevalence of eelgrass wasting disease in a meadow across two summers
 through repeated field surveys. We assessed the role of a common eelgrass
 herbivore in affecting disease spread and growth using microcosm and
 mesocosm experiments. We further explored herbivore preference in a choice
 feeding trial, which was paired with chemical analysis of plant tissue and
 analyzed using a structural equation model. While this herbivore
 facilitates the growth of new lesions among isolated leaves, on balance
 they reduce lesion severity by more than 50% in comparison to no-herbivore
 controls in field-realistic settings. This was likely because this
 herbivore strongly prefers to eat diseased rather than healthy tissue,
 consuming nearly twice as much lesion area in choice trials. This
 preference results from pathogen-driven changes in the host plant;
 lesioned tissue requires less force to penetrate than non-lesioned tissue.
 Additionally, as lesions increase in size, their polyphenolic
 concentrations drop, which further increases the magnitude of preference
 for lesioned tissue. Synthesis. These results suggest that these
 herbivores could help maintain disease in this system at a high prevalence
 (by facilitating disease development) but low severity (through
 preferential consumption), which is consistent with our field observations
 of nearly 100% prevalence and low severity in a natural bed where
 herbivore density is high.   Understanding such
 multi-species interactions in marine systems will advance our predictions
 of future disease states beyond current understanding, which focuses
 primarily on the influence of environmental change on pathogen outbreaks.
description: This readme file was generated on 2024-04-02 by Naomi A. Murray GENERAL
 INFORMATION Title of Dataset: Herbivores can benefit both plants and their
 pathogens through selective herbivory on diseased tissue Author
 Information Name: Naomi Murray ORCID: 0000-0002-4343-6264 Institution:
 University of California, Davis Email:
 [naomiamurray@gmail.com](mailto:naomiamurray@gmail.com) Co-author
 Information Name: Jay Stachowicz ORCID: 0000-0003-2735-0564 Institution:
 University of California, Davis Email:
 [jjstachowicz@ucdavis.edu](mailto:jjstachowicz@ucdavis.edu) Date of data
 collection: between 2019-06 and 2021-09 Geographic location of data
 collection: Bodega Bay, California, USA DATA & FILE OVERVIEW File
 List: \- Lesions_2020 - field disease severity data from summers of 2019
 and 2020 \- feeding_trial_FINAL - feeding preference data for Pentidotea
 resecata as described in the methods section \- penetrometer_2020 - leaf
 toughness data from plants used in the P. resecata feeding trial\ \-
 CN_feeding_trial - C:N data from plants used in the P. resecata feeding
 trial \- gone_wild - data on P. resecata consumption and plant traits used
 to build the structural equation model \- microcosm_redo - data from
 vectoring microcosm experiment \- mesocosm - data from vectoring mesocosm
 experiment \- green_tissue_analysis - additional measures of green tissue
 area from the mesocosm experiment METHODOLOGICAL INFORMATION Methods for
 collecting, generating, and processing the data: see [Publication DOI]
 Information needed to interpret the data: All analyses were conducted in R
 and necessary packages can be found at the top of each R-script in the
 associated Zenodo repository. DATA-SPECIFIC INFORMATION FOR: Lesions_2020
 Variable List: \- Year - Year that the plant was sampled \- Time_Point -
 Number of the sampling in time; 1 corresponds to the first sampling point,
 2 corresponds to the second, etc. \- Plant_Number - Number of each
 individual plant within each sampling point. \- Lesion_Cover - The percent
 of the plant that was lesioned \- Prevalence - either 1 (plant had some
 lesion are) or 0 (plant was completely lesion free). \- Day_Year - Day of
 the year on which the plant was sampled DATA-SPECIFIC INFORMATION FOR:
 feeding_trial_FINAL Variable List: \- Cup_Number - each cup contained one
 section of green tissue, one section of lesion tissue, and one bug \-
 Leaf_Health - G = green tissue, L = lesion tissue \-
 Percent_Total_Consumed - The percent of each leaf section that was
 consumed \- Actual_Area_Consumed - The area (in cm2) of each leaf section
 that was consumed DATA-SPECIFIC INFORMATION FOR: penetrometer_2020
 Variable List: \- Plant_ID - The plant ID number corresponds with the
 feeding trial cup number (Plant 1 was in Cup 1) \- Leaf_Health - G = green
 tissue, L = lesion tissue \- Penetrometer_Mass - The amount of sand (g)
 needed to pierce the leaf tissue (see methods). DATA-SPECIFIC INFORMATION
 FOR: CN_feeding_trial Variable List: \- Sample_Name - unique identifier
 for each sample \- Plant_ID - The plant ID number corresponds with the
 feeding trial cup number (Plant 1 was in Cup 1) \- Health - G = green
 tissue, L = lesion tissue \- Nitrogen - percent nitrogen in the tissue
 sample \- Carbon - percent carbon in the tissue sample \- C_N - C:N ratio
 of each sample DATA-SPECIFIC INFORMATION FOR: gone_wild \** denotes
 variables used in the published analysis. Variable List: \- Cup_Number -
 the same as in the feeding_trial_FINAL dataset; trait data were taken for
 each plant in the trial. \- Percent_Green_Consumed = The percent of the
 green leaf section that was consumed (relative to the total area of the
 leaf section) \- Percent_Lesion_Consumed = The percent of the lesion leaf
 section that was consumed (relative to the total area of the leaf section)
 \- Green_Lesion = the ratio of "Percent Total Consumed Green" to
 "Percent Total Consumed Lesion. Measure of the preference for lesion
 tissue. \- Percent_Total_Consumed_Green = The percent of green tissue
 consumed relative to the total area of tissue consumed \**
 Percent_Total_Consumed_Lesion - The percent of lesion tissue consumed
 relative to the total area of tissue consumed \- Clip_Lesion_Cover = The
 percent of the lesion leaf section that was actually lesioned. \- Plant
 Area = The total leaf area of the entire plant used in each replicate. \**
 Plant_Lesion_Cover - The percent of the entire plant that was lesioned. \-
 Total_Detritus = The percent of the entire plant that was either lesioned
 or decaying. \- Green_Penetrometer = The mass of sand (g) required to
 pierce the green leaf tissue of the plant. \** Lesion_Penetrometer - The
 mass of sand (g) required to pierce the lesion leaf tissue of the plant.
 \- G_L_Penetrometer = The ratio of the green penetrometer mass to lesion
 penetrometer mass. \- Green Phenolics = Phenolic acid content of the green
 tissue of the plant (given as a percent of dry weight). \**
 Lesion_Phenolics - Phenolic acid content of the lesion tissue of the plant
 (given as a percent of dry weight). \- G_L_Phenolics = The ratio of the
 green phenolics to lesion phenolics. \- Green_Carbon = The percent carbon
 of the green tissue of the plant. \- Green_Nitrogen = The percent nitrogen
 of the green tissue of the plant. \- Green_C_N = The ratio of C:N in the
 green tissue of the plant. \- Lesion_Carbon = The percent carbon of the
 lesion tissue of the plant. \- Lesion_Nitrogen = The percent nitrogen of
 the lesion tissue of the plant. \** Lesion_C_N - The ratio of C:N in the
 lesion tissue of the plant. \- G_L_C_N = The ratio of C:N in green tissue
 to C:N in lesion tissue. \- Green_Clip_Width = Width (in cm) of the green
 leaf section \** Lesion_Clip_Width - Width (in cm) of the lesion leaf
 section \- Isopod Length = Length (in mm) of the isopod in each replicate.
 Missing data is left blank. DATA-SPECIFIC INFORMATION FOR: micro_redo \**
 denotes variables used in the published analysis. Variable List: \** Tank
 - unique identifier for each replicate \** Number - replicate number
 within each treatment \** Treatment - denotes the imposed treatment (bug
 for added isopod, clip for artificial damage, or con for control) \-
 BEFORE_disease = lesion area (cm2) on the central, lesioned leaf section
 before the experiment began \- AFTER_disease = lesion area (cm2) on the
 central, lesioned leaf section at the end of the experimental period \**
 section_ID - identifier for each clip in each microcosm. "FOCAL"
 is the central, lesioned section, and "1" and "2" are
 the two surrounding clips. \- AFTER_total = lesion area (cm2) in the whole
 microcosm (across all three leaf sections) at the end of the experiment \-
 AFTER_total_change = change in total change in lesion area (cm2) during
 the experiment; "BEFORE_disease" minus "AFTER_total"
 \- AFTER_change = the change in lesion area (cm2) for each leaf section.
 For each microcosm there are three values for "AFTER_change" --
 one corresponding to the central, lesioned section ("focal") and
 one for each of the two surrounding sections.\ \** AFTER_pclean - sum of
 the final lesion area on the two surrounding leaf sections (cm2). \**
 AFTER_pclean_redo - sum of the final lesion area on the two surrounding
 leaf sections (cm2) -- Jay was concerned that Naomi's lesion area
 measurements were off (many are very close to zero), so she redid them and
 this is the new sum. \- Infection_Points = number of distinct lesions in
 the tank. \- Associated_with_Damage = number of infection points
 associated with either clipping (both notches cut out of blades as the
 "clipping" treatment, as well as at the ends of each clip in all
 treatments) or herbivory. \- Proportion_Associated_Damage = ratio of
 infection points associated with any sort of clipping damage to the total
 number of infection points Missing data is left blank. DATA-SPECIFIC
 INFORMATION FOR: mesocosm \** denotes variables used in the published
 analysis. Variable List: \** Number - replicate number within each
 treatment \** Treatment - denotes the imposed treatment (bug for added
 isopod, clip for artificial damage, or con for control) \- BEFORE_Disease
 = percent lesion cover on the central, unclipped plant before the
 experiment began \- BEFORE_Lesion = number of distinct lesions on the
 central, unclipped plant before the experiment began \- AFTER_Disease =
 percent lesion cover on the central, unclipped plant after the
 experimental period \** AFTER_Lesion = number of distinct lesions on the
 central, unclipped plant after the experimental period \- AFTER_p1 = the
 percent lesion cover on focal plant 1 after the experimental period \-
 p1_Lesion = number of distinct lesions on focal plant 1 after the
 experimental period \- AFTER_p2 = the percent lesion cover on focal plant
 1 after the experimental period \- p2_Lesion = number of distinct lesions
 on focal plant 1 after the experimental period \- AFTER_p3 = the percent
 lesion cover on focal plant 1 after the experimental period \- p3_Lesion =
 number of distinct lesions on focal plant 1 after the experimental period
 \- AFTER_total = total percent lesion area after the experimental period
 (summed across all four plants) \- AFTER_total_change = percent lesion
 after the experiment (summed across all four plants), minus the initial
 percent lesion; "AFTER_total" - "BEFORE_Disease" \-
 AFTER_disease_change = final percent lesion on the central, unclipped
 plant after the experimental period minus the initial percent lesion on
 the central, unclipped plant; "AFTER_Disease" -
 "BEFORE_Disease" \- AFTER_pclean = area of lesion tissue (cm2)
 that formed on the focal plants during the experimental period (summed
 across the three focal plants) \- AFTER_pclean_lesion = number of distinct
 lesions that formed on the focal plants during the experimental period
 (summed across the three focal plants) \- AFTER_total_lesion_change =
 change in the total number of lesions during the experimental period
 (across all four plants) \- BEFORE_Lesion_Area = initial lesion area
 (cm2), summed across all four plants \- AFTER_Lesion_Area = final lesion
 area (cm2) after the experimental period, summed across all four plants
 \** Lesion_Area_Change = total lesion area (cm2) after the experimental
 period (summed across all four plants), minus the initial lesion area
 (cm2); "AFTER_Lesion_Area" - "BEFORE_Lesion_Area"
 Missing data is left blank. DATA-SPECIFIC INFORMATION FOR:
 green_tissue_analysis \** denotes variables used in the published
 analysis. Variable List: \** Number - replicate number within each
 treatment \** Treatment - denotes the imposed treatment (bug for added
 isopod, clip for artificial damage, or con for control) \-
 before_focal_healthy_tissue = area (cm2) of green (non-lesioned) tissue on
 the central, unclipped plant in each mesocosm \- estimate_healthy_1 =
 estimate of total green tissue on the three focal plants at the start of
 the experimental period; area of each shoot estimated using the recorded
 shoot width * 15cm (length to which all blades were clipped) * 3 (as a
 uniform average estimate of the number of leaves) \- estimate_healthy_2 =
 estimate of total green tissue on the three focal plants at the start of
 the experimental period; area of each shoot estimated using the recorded
 shoot width * 15cm (length to which all blades were clipped) * estimated
 number of leaves based on images of the shoots at the end of the
 experimental period \- estimate_healthy_3 = estimate of total green tissue
 on the three focal plants at the start of the experimental period; area of
 each shoot estimated using the recorded shoot width * 15cm (length to
 which all blades were clipped) * the number of clipped leaves at the start
 of the experimental period \- total_healthy_before_1 = total area (cm2) of
 green tissue area in each mesocosm at the start of the experimental
 period; "before_focal_healthy_tissue" +
 "estimate_healthy_1" \- total_healthy_before_2 = total area
 (cm2) of green tissue area in each mesocosm at the start of the
 experimental period; "before_focal_healthy_tissue" +
 "estimate_healthy_2" \- total_healthy_before_3 = total area
 (cm2) of green tissue area in each mesocosm at the start of the
 experimental period; "before_focal_healthy_tissue" +
 "estimate_healthy_3" \- after_total_healthy = total area (cm2)
 of green tissue across all (both focal and central) shoots in each
 mesocosm, measured in ImageJ from photos taken at the end of the
 experimental period \- change_1 = the change in green tissue area (cm2)
 using the first estimation method; "after_total_healthy" -
 "estimate_healthy_1" \- change_2 = the change in green tissue
 area (cm2) using the second estimation method;
 "after_total_healthy" - "estimate_healthy_2" \**
 change_3 = the change in green tissue area (cm2) using the first
 estimation method; "after_total_healthy" -
 "estimate_healthy_3"