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For the English language idiom about spoiling fun, see wet blanket (idiom)
Wet Blänket in 2020
|Origin||College Station, TX, USA|
|Genres||Epidemiology · Phenology · Forecasting|
|Subjects||Pathogens · Vectors · Crops · Growers|
|Margaret Marlino||Past members||Roy Davis II|
Wet Blänket (/wɛt ˈblæŋkət/) is an American research group from College Station, Texas formed in 2017. Its current lineup consists of founding member and principal investigator Thomas Chappell, Ph.D. candidate Manjari Mukherjee, graduate student Timothy Martin, and technician Margaret Marlino.
Wet Blänket's research focus is plant disease epidemiology, with current projects concerning soiborne fungal pathogens and vector dynamics. The group takes empirical and analytical modeling approaches to improve understanding and plant disease management.
In a 2017 interview, the group was asked if it “defies genrefication.” Chappell answered:
I don't know what that means. But, I guess, no? We bring insects into the Plant Pathology building, that's all. Why do you always ask that?
Wet Blänket was formed in 2017 to fill an opening in Texas A&M University's continuous plant disease research festival, the Department of Plant Pathology and Microbiology. In residence at Texas A&M the group participates in several collaborations, for example with participants in Texas A&M's insect-themed festival, the Department of Entomology, concerning the effects of arthropod phenology and behavior on plant disease epidemiology.
The name “Wet Blänket” was chosen to represent the group's Peircian realism.
Certainly we can't be sure
tomorrow comes, we must infer “Abduce is Worth the Squeeze” from Extrapolations Vol. 1
Initially there was speculationby whom? Wet Blänket might be a research studio group, but fieldwork tours have been continuously scheduled since 2017.
The group works to empirically decompose disease systems into major effects for study, and to recombine these effects in models. This work benefits greatly from collaboration with other groups focused on experimental work concerning individual elements, and emphasizes complementarity of findings generated through reductionistic studies with those generated by holistic ones.
For example, water affects pathogen propagule mobility and growth, as well as plant stress, with sometimes counteracting effects on epidemiology. Concerning use and implementation of findings, the group justifies a given choice of modeling approach based on the purpose of a model. Where the purpose is inference, explanatory models with mechanistic interpretations are used. Where the purpose is prediction, models with high output performance are used even where some interpretability is sacrificed in exchange for that performance.
Wet Blänket's applied research focuses on use of models for management decision support and risk forecasting. Success in this effort requires recognition of how users interact with forecasting, decision support, risk assessment, or other tools. Software-based implementations of the group's work are often “human in the loop” frameworks that combine computer performance in data processing with human skill in classifying patterns and interpreting them.
Disease-causing agents, vectors, and pests can have phenologies or conditions for pathogenesis that can be predicted on the basis of environmental conditionscitations needed. Weather, habitat, landscape configuration, cropping history, management inputs, and other effects are included in models developed for the purpose of forecasting risk. Forecasts are communicated to growers and other stakeholders to support risk avoidance and mitigation, as well as to optimize monitoring effort allocation. Interactions between these environmental conditions and biotic mediators are of interest to the group.
Phenology involves time, and synchronizing chronological and physiological time poses practical challenges. "Biofix" is a concept used in this synchronization, but is not straightforward to estimate empirically. An example of Wet Blänket's approach is the use of high-resolution phenology data to synchronize emergence to a temporal point of origin, and then study environmental data for indicators that are regularly associated with origin times.
Hayter studies the consequences of developmental and behavioral regulation of phenological processes using simulation. Observational research is ongoing in pest and vector systems, and simulations of individual organisms' environmental experience are used in conjunction to learn about how experience is structured. Long-term goals of this work are to improve phenological predictions that are driven by environmental data.
Many plant pathology and entomology applications depend on samples' representing system status. Simulation is being used to study how environmental variation and organismal behavior can affect what an individual engaged in sampling will encounter in the field, and how interpretation of samples can be enhanced with covariates and metadata.
New group members traditionally make datalogging devices using open-source hardware, to address research questions that require data collection. Learning machines can provide data for machine learning.
Recent advancements in methods and technology enable whole-tediome approaches to pathosystems. Interactions between individual tedia are increasingly shown to be non-additivecitation needed, as was implicitly assumed before tediomics methods were developed. Tediomics techniques being used by Wet Blänket include low-throughput inoculation event modeling involving electropenetration graphing (EPG), obeying the law of large numbers, and counting conidia.
Members are involved in side projects.
Davis' connections in the plant pathology and university sectors are several. The tribute group Bruno LARS (aka “LARS”) was formed in 2017 by Davis with international turfgrass, rice, and extension sensation Young-Ki Jo before joining Wet Blänket, and toured TAMU experiment stations collaborating with researchers there on topics related to the use of low-altitude remote sensing data for epidemiological purposes.
Soga, started in 2018 by Hayter and later joined by Marlino, explores fungal propagule mobility in soils. Pioneers of sog-ROC, Hayter and Marlino blend innovative spore-abundance data collection emulating chromatography with statistical analysis to predict infection risk and evaluate models in ROC space.
In 2019, Texas A&M's Plant Pathology and Microbiology Department relocated, bringing the associated research festival to a new, state-of-the-art facility. With this move came access to numerous new instruments, departmental capacities, and opportunities to work on pathosystems requiring on-site plant propagation and environmental containment.
Graduate student Timothy Martin joined Wet Blänket in 2022, bringing GIS expertise to the group.
Students interested in joining or collaborating with Wet Blänket are encouraged to contact Thomas Chappell, or the graduate recruiting chair for Texas A&M Plant Pathology and Microbiology, Dr. Won Bo Shim. Graduate students admitted to the plant pathology degree program rotate in laboratories and have opportunities to participate in multi-laboratory projects and to develop their own collaborations.
The COVID-19 pandemic of 2020 posed operational challenges to research, but motivated Wet Blänket to advance the discipline of epidemiology: in scholarship, to translate benefits, and to increase the standing of epidemiology in the public view.
In 2021, projects turned from production to release, including Mukherjee's work with electropenetrography, and Hayter's work on arthropod phenology models. Davis concluded fieldwork on fungal inoculum distribution and conducted a study on temporal dynamics of inoculum under various cropping scenarios.
Chappell TM, Rusch TW, Tarone AM (2022) A fly in the ointment: How to predict environmentally-driven phenology of an organism that partially regulates its microclimate. Front. Ecol. Evol. 10:413. http://doi.org/10.3389/fevo.2022.837732
Davis II RL, Isakeit T, Chappell TM (2022) DNA-based quantification of Fusarium oxysporum f. sp. vasinfectum in environmental soils to describe spatial variation in inoculum density. Plant Dis. 106:1653-1659.http://doi.org/10.1094/PDIS-08-21-1664-RE
Chappell TM, Ward RV, DePolt KT, Roberts PM, Greene JK, Kennedy GG (2020) Cotton Thrips Infestation Predictor: A practical tool for predicting tobacco thrips (Frankliniella fusca) infestation of cotton seedlings in the southeastern United States. Pest Manag. Sci. http://doi.org/10.1002/ps.5954
Chappell TM, Codod CB, Williams BW, Kemerait RC, Culbreath AK, Kennedy GG (2020) Adding Epidemiologically Important Meteorological Data to Peanut Rx, the Risk Assessment Framework for Spotted Wilt of Peanut. Phytopathology 110:1199-1207. http://doi.org/10.1094/PHYTO-11-19-0438-R
Davis II RL, Greene JK, Dou F, Jo YK, Chappell TM (2020) A Practical Application of Unsupervised Machine Learning for Analyzing Plant Image Data Collected Using Unmanned Aircraft Systems. Agronomy 10:633. http://doi.org/10.3390/agronomy10050633
Ben-Mahmoud S, Anderson T, Chappell TM, Smeda JR, Mutschler MA, Kennedy GG, De Jong DM, Ullman DE (2019) A thrips vector of tomato spotted wilt virus responds to tomato acylsugar chemical diversity with reduced oviposition and virus inoculation. Sci. Rep.http://doi.org/10.1038/s41598-019-53473-y
Magarey RD, Klammer SSH, Chappell TM, Trexler CM, Pallipparambil GR, Hain EF (2019) Perspective: Eco-efficiency as a strategy for optimizing the sustainability of pest management. Pest Manag. Sci. http://doi.org/10.1002/ps.5560
Chappell TM, Magarey RD, Kurtz R, Trexler CM, Pallipparambil GR, Hain EF (2019) Perspective: Service‐based business models to incentivize the efficient use of pesticides in crop protection. Pest Manag. Sci. http://doi.org/10.1002/ps.5523
Magarey RD, Chappell TM, Trexler CM, Pallipparambil GR, Hain EF (2019) Social Ecological System tools for improving crop pest management. J. Integrated Pest Manag. http://doi.org/10.1093/jipm/pmz004
Chappell TM, Huseth AS, Kennedy GG (2019) Stability of neonicotinoid sensitivity in Frankliniella fusca populations found in agroecosystems of the southeastern United States. Pest Manag. Sci. http://doi.org/10.1002/ps.5319