Link to home

The Plant Health Instructor

Volume: 24 |
Year: 2024
Article Type: Focus Article

​Studying Phytobiomes as Complex Systems: A New Framework for Learners to Scaffold Understanding​​

​Laura Super,1,2 Melody Fu,1 Robert Guy,1 Patrick von Aderkas,3 and Santokh Singh4

1 Department of Forest and Conservation Sciences, Faculty of Forestry, University of British Columbia, Forest Sciences Centre, 3041-2424 Main Mall, Vancouver, BC, Canada, V6T 1Z4

2 Corresponding author: Laura Super; E-mail: leslaura@gmail.com

3 Centre for Forest Biology, Department of Biology, University of Victoria, PO Box 3020, Station CSC, Victoria, BC, Canada, V8W 3N5

4 Department of Botany, Faculty of Science, University of British Columbia, Biosciences Building, 3156-6270 University Blvd., Vancouver, BC, Canada V6T 1Z4

Date Accepted: 15 Mar 2024
|
 Date Published: 15 Jun 2024
|

Keywords: ​higher-order thinking skills, metacognition, plant pathology, plant science

View article​​​




​Appendix

Supplementary Table S1. Plant(s), environment(s), associated organisms and/or viruses, and interaction(s) (PEAI) model table as a tomato bacterial speck disease example (described in text)

This table simulates an undergraduate student filling it in before class, including adding notes to clarify with their teaching assistant (TA) in the upcoming lab. The students were told to complete the table in their own words, as a brief (several hours total) prelab activity. They were asked to note areas they found unclear, as well as state hypotheses—ones they found in the article or more implicit ones—in every section, using the paper and its cited references as guides for information. The course instructors and TAs also made a table together and a rubric so they could help students in the lab fill in the table, have a discussion, and foster critical thinking.

PE​AI Part Scale (Taxonomy, Spatial, Temporal) Structure and Part of Whole (Part, Spatial, Temporal) Hypothesis and Prediction Discipline Assumptions Five T's
Plant(s) (P)Tomato (Solanum lycopersicum); scale: complex, something to ask my TA in class to clarify.Plant structure (habit): herbaceous; part of whole: shoot and shoot-like part for assessment of plant leaves for tomato bacterial speck disease. Spatial and temporal: something to ask my TA in class to clarify (multistep experiment).The researchers hypothesized they could suppress disease of tomato shoots through a multistep method.Botany, plant pathology, agroecology; topics related to the paper given in the course: Ehau-Taumaunu, H., and Hockett, K. L. (2023): https://doi.org/10.1094/PBIOMES-05-22-0030-FI
The researchers assumed the plants they collected microbes from were representative of other tomato plants.Model pathosystem (tomato and Pseudomonas syringae), lots more—ask TA how much detail.
Environment(s) (E)Unclear conditions in the experimental set up—ask TA for clarification.Unclear scale—ask TA for clarification on how much detail.The researchers assumed they could change the biotic environment, which I hypothesize would affect the microenvironment of the tomatoes.Topics related to the paper given.The environmental conditions (controlled and manipulated) in the experiments would impact the plants and their associates.Growth chamber and other techniques to modify the larger scale abiotic environment and change the biotic composition, which could also affect the microscale biotic and abiotic environment on the leaf.
Associate(s) (A) Pseudomonas syringae and other microbiome organisms; conditions that result in bacterial leaf speck disease.Unclear scale—ask TA for clarification on how much detail.The researchers hypothesized they could shift the microbial community in such a way they would suppress tomato disease with a multistep method.Microbiology; topics related to the paper given.Microbes measured were impacted by the treatments and representative of the microbial communities. Disease severity was accurately detectable and due to experimental manipulation.Phyllosphere community after passage methods, filters, sampling tubes, way to record data, equipment for sonification, centrifuge, broth for microbes, DNA extraction and PCR methods.
Interaction(s) (I)Plant-microbe-environment interactions.Unclear scale, microscopic to the scale of a whole leaf—ask TA for clarification.The researchers hypothesized they could change, through a multistep process, the interactions of the microbiome to impact disease of the tomato shoots.Plant-microbe-environment interactions; topics related to the paper given.Disease severity measured indicates more disease interaction due to the pathogens and environmental manipulation.Join a working group on phyllosphere microbiomes given different environmental conditions; email the authors to ask follow-up questions about their results.

Note: Five T's refers to techniques, training, teamwork, technology and tools.


Supplementary Table S2. Plant(s), environment(s), associated organisms and/or viruses, and interaction(s) (PEAI) model table as a beach leaf disease example (described in text)

This table simulates an undergraduate filling it out partially beforehand and then in the field. There was a lecture in class before the field day on key topics and to announce teaching assistant (TA) office hours. TAs and instructors also pointed students to a suggested reading list provided to help prime the undergraduates before filling in the table. Images of obvious types of disease on beech trees were provided in lecture slides; the material was reviewed in lecture and in office hours. In the stand of trees visited by the students, there were long-term data loggers measuring climate, including temperature. The students surveyed trees as diseased or not and also took soil samples.

PEAI Part Scale (Taxonomy, Spatial, Temporal) Structure and Part of Whole (Part, Spatial, Temporal) Hypothesis and Prediction Discipline Assumptions Five T's
Plant(s) (P)Taxonomy: beech of the ornamental and native varieties (Fagus spp.) at least 15 cm in diameter at breast height; 0–5 cm in at least three locations along the whole tree (estimate size of tree), length of the survey 15–20 min; diseased (has symptoms) or undetected.

Plant structure (habit): leaf and leaf-like parts, as well as dead or senescing parts (bark); leaves and trunks with and without disease (leaf interveinal darkening, leaf shape alteration thickening; thinner crowns and branch dieback).

Scale: 0–5 cm; 15–20 min/tree.

Beech trees adjacent to infected trees and in more stressful environments will show more disease.Botany, plant pathology, plant physiological ecology, forest ecology.Using visual symptoms can help determine healthy (undetected) versus diseased trees; in other words, visual symptoms are clear on trees in the survey.Transect equipment (30-m tapes), camera, GPS unit for location, data sheets, survey teams.
Environment(s) (E)Soil properties and temperature measurements, represents transects, 15–20 min for soils and longer-term temperature measurements (years at several-times-a-day intervals).

Structure: lithosphere or solid (soil pH) and energy (temperature, degrees Celsius).

In the transects, 15–20 min sampling for soil sampling and years (with several measurements a day) for temperature measurement.

More stressful environments (unfavorable temperature, pH) will help facilitate more disease if there are infected trees in the vicinity.Soil science, climate science (especially in relation to temperature).The soil and light samples are representative of the transects.

Soil corer, soil sampling bags, survey team, small temperature probes, camera, GPS unit for location, data sheets, labeling equipment to keep samples clearly identified.

Analytical chemists in a laboratory (shipping samples to them) to help with analysis of soil pH.

Associate(s) (A)

Taxonomy: visual inspection of diseased versus undetected.

From 0–5 cm in at least three locations along the whole tree (estimate size of tree).

Length of the survey 15–20 min during tree survey, through disease scoring and photographs.

Structure: disease showing on leaves.

Indirect measurement of nematode-caused disease (species: Litylenchus crenatae subsp. mccannii, phylum: Nematoda).

More stressful environments (unfavorable temperature, pH) will help facilitate more disease if there are infected trees in the vicinity.Community ecology, population ecology, nematology.There will be a detectable relationship between the leaf, other symptoms found, and the actual disease condition of trees surveyed.

Camera, GPS unit, data sheets, survey teams.

Experts on identifying beech leaf disease.

Interaction(s) (I)Plant-nematode-environment interactions (visual inspection, macrosc​opic, snapshot; indirect, as disease agent is in the ground and symptoms are measured aboveground).

Structure:

Plant-nematode-environment interactions.

Inference from statistical analysis of data.

Inference from map of disease (with GIS map).

More disease will be in environments with higher pathogen load from weakened trees due to abiotic stress and tree already infected or adjacent to infected trees.Disease ecology, multitrophic interaction ecology.The leaf and other symptoms indicate actual interactions between the disease agent and the trees. The disease agents are still active and impacted by the environmental conditions.

Join a plant pathogen working group that has access to monitoring information on beach leaf disease.

Statistical and subject matter experts to help analyze data.

Note: Five T's refers to techniques, training, teamwork, technology, and tools.​


​Supplementary Table S3. Plant(s), environment(s), associated organisms and/or viruses, and interaction(s) (PEAI) model table as a forest microbiome example (described in text)

This table simulates graduate student filling it out after initial feedback from a professor.

PEAI Part Scale (Taxonomy, Spatial, Temporal) Structure and Part of Whole (Part, Spatial, Temporal) Hypothesis and Prediction Discipline Assumptions Five T's
Plant(s) (P)Understory forest plants (variety of biological taxonomy, to species level); 1-m2 quadrat sampling; 5–10 min visual search.Plant structure (habit): herbaceous and other plants in the understory; part of whole: aboveground visible shoot and shoot-like part to then calculate richness of community of understory plants (richness is total number of plants in 1-m2 quadrat).Understory plant richness will relate to soil, light, and microbiome. With higher pH, light and richness of microbiome there will be greater richness in understory plants and less disease.Botany, plant pathology, forest ecology, community ecology, biogeography.Plant richness in the observational study is related to light, pH, microbiome richness, and plant health.Quadrats for each 1-m2 sampling area, field guides of plant species, plant presses (for samples), camera, GPS unit for location, data sheets, survey teams.
Environment(s) (E)Soil properties and light levels; represents 1 m2, 5-10 min.Structure: lithosphere or solid (soil pH) and energy (light, flux); in the quadrat of 1 m2; 5–10 min sampling.Higher light and pH conditions will be less stressful for plants, subsequently promoting higher plant health and productivity that results in higher richness patterns.Soil science, climate science, ecophysiology.Soil and light samples are representative of the quadrat.Soil corer, soil sampling bags, survey team, light meter, labeling equipment to keep samples clearly identified.
Associate(s) (A)Taxonomy based on amplicon sequence variants (ASVs) for microbiomes, microscopic, snapshot; microbiome, more broadly and including organisms causing forest plant disease.

Structure (varied), eukaryotes: plant-associated fungi and protists; microscopic and snapshot.

Structure (varied), prokaryotes: plant-associated bacteria; microscopic and snapshot.

Microbiome richness will reflect plant richness. Higher plant richness will have more beneficial plant associates than pathogens given there will be lower pathogen load compared to the other microbiome taxa.Microbiology, molecular biology, community ecology, plant pathology.There is a detectable relationship between the richness of the plants with the richness of the plant-associated microbes; if present, the species are interacting with one another and the plant. The ASV and bioinformatics pipeline approach more or less accurately represents the taxa.DNAse free sampling tubes to capture the microbiome; gloves and sterilization equipment to prevent contamination of microbe samples.
Interaction(s) (I)Plant-microbe-environment interactions; microscopic snapshot.Structure: Plant-microbe-environment interactions; network analyses when data are collected (infer microscopic, snapshot interactions from analyses).The light environment stimulates plant growth and physiology that interacts with plant nutrition and simultaneously interacts with the microbiome of the plants in the plant community, and the plants with one another, in linear and nonlinear complexity.Complexity theory, network theory, systems biology, multitrophic interaction ecology.If the leaf microbe species are present on a plant species, they are interacting with one another and the plant. Not all interactions will be beneficial for the plant or microbes. There will be positive, negative, and neutral interactions.If possible, join a phytobiome working group around plant-microbe interactions, plant disease more broadly and focused on forest understory plants with their associates.

Note: Five T's refers to techniques, training, teamwork, technology, and tools.​​