Herbivores can benefit both plants and their pathogens through selective herbivory on diseased tissue
Cite this dataset
Murray, Naomi (2024). Herbivores can benefit both plants and their pathogens through selective herbivory on diseased tissue [Dataset]. Dryad. https://doi.org/10.25338/B8805V
Abstract
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.
README
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
Co-author Information
Name: Jay Stachowicz
ORCID: 0000-0003-2735-0564
Institution: University of California, Davis
Email: 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"
Funding
National Science Foundation, Award: OCE 18-9976
National Science Foundation, Award: OCE 18-9992