About

Thomas M. Chappell is an Associate Professor in the Department of Plant Pathology & Microbiology at Texas A&M University. His research focuses on antagonistic interactions between plants and their enemies, emphasizing epidemiological and phenological processes that can be modeled to improve agricultural management. His work involves studying diverse pathogens and pests, with a particular theme of modeling environmentally-dependent processes such as inoculum dynamics, pest and vector phenology, dissemination, and plant susceptibility. He teaches graduate and undergraduate courses in epidemiology and data analysis, serves as the undergraduate research coordinator for his department, and is a senior editor of the journal Phytopathology. His background includes a B.S. in Biology and a B.M. in Performance from the University of Michigan, a Ph.D. in Biology from Duke University, and post-doctoral training in Entomology at North Carolina State University.

Research topics

• Biology
• Machine Learning
• Artificial Intelligence
• Data Mining
• Computer Science
• Agronomy
• Ecology
• Geography
• Virology
• Mathematics
• Remote sensing
• Agroforestry

Selected publications

• Editorial: Pest-smart strategies for improved eco-efficiency in agriculture, forestry and communities

  Frontiers in Insect Science · 2026-03-03

  articleOpen access

  The concept of economic thresholds in IPM (the pest density where control measures should be implemented to prevent economic injury) begins with a powerful argument: the cost of pesticide applications should not exceed the economic losses the applications prevent. Under IPM, knowledge of agronomic and biological systems substitutes for chemicals, increasing farm income. This can produce external benefits, as pesticides have ecological and human health costs. IPM can be a "win-win" strategy: improving farming productivity and profitability, while reducing environmental damage. Yet the U.S. General Accounting Office found problems with federal IPM initiatives (GAO 2001). Despite a 70% IPM adoption rate on U.S. crop acreage, "USDA counts a wide variety of farming practices without distinguishing between those that tend to reduce chemical pesticide use from those that may not" and "USDA and EPA suggested that an appropriate objective for IPM could be reduction in pesticide risk to human health and the environment, but neither agency adopted that objective." Further, "IPM […] has not yet yielded nationwide reductions in chemical pesticide use."What went wrong? USDA and EPA were aware that the pertinent issue was harm, not the physical quantity of pesticides used. But harm (such as acute toxicity, chronic health effects, biodiversity loss, water contamination, or resistance development) is harder to predict and measure. Instead, IPM was treated as a technology standard, not a performance standard (Luken 1990, Luken & Clark 1991, Stavins 2003), with progress measured in terms of practice adoption. But linkages between adoption and environmental outcomes can be tenuous. The case of water conservation illustrates. The policy consensus is that improving efficiency conserves water, with progress measured in terms of adopting "efficient" irrigation (Pérez-Blanco et al. 2021). Yet, the scientific consensus is that, under most conditions, improving irrigation efficiency increases water consumption (Pérez-Blanco et al. 2020). A performance goal (reducing harm from pesticides) would allow producers to achieve that goal in the most cost-effective manner. With a goal of prescribed practice adoption, there is no incentive to innovate to reduce harm. Also, voluntary adoption relies on farmers weighing private costs and benefits. There is no reason such private calculations would address external costs of pesticide use.The Federal Insecticide, Fungicide, and Rodenticide Act (FIFRA) requires the U.S. Environmental Protection Agency (EPA) to evaluate risks and benefits of pesticides before they are registered for use. Pesticides must not cause "unreasonable adverse effects on the environment" defined as unreasonable risk to humans or the environment, considering economic, social, and environmental costs and benefits, and unacceptable dietary risk from pesticide residues (EPA 1996). EPA conducts risk-benefit evaluations. Risks are measured in terms of human health (e.g., toxicity and exposure) and environmental damage (e.g., toxicity to non-target species and ecosystem harm). Benefits to pesticide users are measured in terms of crop yield and quality, and farm costs and returns. This system attempts to quantify tradeoffs between agricultural productivity and profitability and ecological and health risks in pesticide use.There are limits to how well the FIFRA framework balances these tradeoffs. It is a framework for managing pesticide use, not one for managing pests. It establishes a minimum standard of environmental protection for how and where pesticides can be used with limited consideration of nonchemical options. Because it sets minimum standards, it doesn't encourage additional innovation to reduce harm further. The framework has difficulties managing risks ex-post. Risks are often unanticipated (e.g., resistance to glyphosate ( The USDA National Roadmap for IPM shifted toward assessing performance, not just practice adoption (USDA 2018). It recommended cost-benefit analysis, including external environmental and health costs. Economists have developed non-market valuation techniques one, in theory, could apply to such analysis. A report to EPA's Pesticide Program Dialogue Committee, however, found, "It is not feasible […] for EPA to conduct such analyses for every pesticide (or even large numbers of them)," recommending developing a priority system to evaluate a subset of compounds (EPA 2024). Eco-efficiency measures have been proposed to quantify economic and environmental performance of pest management in a single index: a ratio of agricultural output to a measure of potential for environmental harm (based on quantity and toxicity of pesticides used) (Kreick et al. 2025, Love et al. 2025, Magarey et al. 2019). Such indexes measure outcomes, not practices. They may inform environmental certification programs to internalize externalities, allowing farmers to capture higher prices for environmentally friendly practices (Magarey et al. 2019). Index values can be developed for major production systems across wide areas, accounting for most pesticide use (Love et al. 2025). We propose research opportunities concerning eco-efficiency and IPM.• Measure more than what is easy to measure (e.g., natural enemy population densities). This requires increasing the efficiency of observation. • Integrate results from the above opportunities into frameworks that can be enhanced by data science and/or artificial intelligence (AI). Eco-efficiency can be a critical part of a Pest-Smart Agriculture strategy (analogous to Climate-Smart Agriculture) to communicate, identify, quantify, track, and incentivize (via market price premiums, for example) ecologically friendly pest management. Eco-efficiency is not a replacement for IPM, but a means to better communicate the impacts and benefits of IPM (Figure 1). Advances in AI and data science can improve observation of pest and natural enemy systems, integrating diverse cost and benefit metrics, supporting longitudinal evaluation of performance. Eco-efficiency can improve pest management at multiple scales. On the scale of individual fields, eco-efficiency metrics can help guide farmer decision-making. At state, regional, or national levels, they can inform research, regulatory, and extension priorities, and support investments to reduce the environmental and health costs of pest management. By providing measurable metrics, Pest-Smart Agriculture could address the concerns outlined by the GAO (GAO 2001) regarding the lack of metrics for evaluating economic and environmental outcomes of IPM. It could also better reflect the USDA IPM Roadmap's call for greater emphasis on performance and more comprehensive measurement of that performance (USDA 2018).

  PublisherOA PDFDOI

• Considerations for Inferring Remote Sources of Inoculum, Vectors, or Pests in Agroecosystems Using Spatial Data When Dispersal Kernels Are Uncertain and Landscapes Are Heterogeneous

  Phytopathology · 2025-11-19

  articleSenior author

  Spatial heterogeneity influences processes in agriculture and can be configured optimally for production and disease management. Landscape composition can be analyzed to infer sources of inoculum or vectors influencing points of interest such as crop fields and to estimate risk to improve management. Substantial research in plant ecology and disease epidemiology has addressed the importance of the dispersal kernel to spatial epidemic dynamics, but a methodological knowledge gap remains for situations in which the magnitude of dispersal from different landscape types varies. This knowledge gap is important to the study of emerging pathosystems in which inoculum sources or reservoirs may not be well characterized, as well as to vectored-disease systems in which transmitting arthropods are polyphagous with unknown host preference. Using simulated data, we describe issues that arise from the practice of summarizing spaces as concentric rings to infer dispersal kernels or identify influential landscape classes, and we demonstrate the utility of instead analyzing variation at a point of interest as a sum of simultaneously distance- and class-weighted remote sources. Of particular interest are scenarios in which the form of the true dispersal kernel is unknown and the goal is to rank landscape types depending on their magnitude of influence. The results emphasize that nonlinear regression methods are necessary for simultaneously fitting distance-weighting functions and estimating the relative influence of landscape types, and they show that ring-based descriptions of landscapes for analysis can lead to misapprehensions about dispersal processes. Methodological development is needed in plant disease epidemiology research in which dispersal kernels may vary depending on biological considerations.

  PublisherDOI

• Bayesian Optimization of insect trap distribution for pest monitoring efficiency in agroecosystems

  Frontiers in Insect Science · 2025-01-22 · 2 citations

  articleOpen access

  Insect trap networks targeting agricultural pests are commonplace but seldom optimized to improve precision or efficiency. Trap site selection is often driven by user convenience or predetermined trap densities relative to sensitive host crop abundance in the landscape. Monitoring for invasive pests often requires expedient decisions based on dispersal potential and ecology to inform trap placement. Optimization of trap networks using contemporary analytical approaches can help users determine the distribution of traps as information accumulates and priorities change. In this study, a Bayesian optimization (BO) algorithm was used to learn more about the optimal distribution of a fine-scale trap network targeting Helicoverpa zea (Boddie), a significant agricultural pest across North America. Four years of pheromone trap monitoring was conducted at the same 21 locations distributed across ~7,000 square kilometers in a five-county area in North Carolina, USA. Three years of data were used to train a BO model with a fourth year designated for testing. For any quantity of trap locations, the approach identified those that provide the most information, allowing optimization of trapping efficiency given either a constraint on the number of locations, or a set precision required for pest density estimation. Results suggest that BO is a powerful approach to enable optimized trap placement decisions by practitioners given finite resources and time.

  PublisherOA PDFDOI

• Identification of microbial communities associated with Phymatotrichopsis omnivora sclerotia in two Texas fields

  Frontiers in Microbiomes · 2025-11-28

  articleOpen access

  The soilborne fungus Phymatotrichopsis omnivora causes a mid- to late-season disease known as cotton root rot (CRR). In the United States, P. omnivora is primarily found in Arizona, New Mexico, Oklahoma, and Texas in soils that are alkaline, calcareous, and rarely freeze deeply. This fungus has a wide host range, and can cause substantial losses in cotton crops. In Texas, not all cotton-producing soils have widespread CRR despite having the characteristics to support P. omnivora . Considering the lack of CRR in some Texas soils, we hypothesize that this absence could be due to the microbial composition associated with sclerotia of P. omnivora . The objective of this study was to identify the taxa that make up microbial communities associated with P. omnivora sclerotia in different soils during both the cotton-growing and off seasons. The microbiota associated with P. omnivora sclerotia were identified by burying lab-generated sclerotia in cotton-producing soils. These sclerotia were recovered, along with soil samples for metabarcoding targeting the 16S rRNA gene and the internal transcribed spacer region. When compared to bulk soil, microbial communities associated with sclerotia differed in community composition and taxa relative abundance between a soil with widespread CRR and one in which the disease is absent. Within these soil communities, potential bacterial and fungal biomarkers that reduce CRR were identified. Furthermore, microbial communities of P. omnivora sclerotia changed seasonally. This study presents the first detailed characterization of microorganisms associated with P. omnivora sclerotia in different cotton-producing soils. Our findings support the view that P. omnivora sclerotia serve as ecological hubs, shaping microbial communities with possible implications for disease suppression. Several enriched taxa are culturable, offering candidates for future biocontrol studies that could inform disease management strategies that focus on increased microbial competition.

  PublisherOA PDFDOI

• Integrated metabarcoding and culture-dependent assessments reveal Pseudomonas as dominant hyphosphere-pathobiont in Race 4 Fusarium wilt pathogen of cotton

  Frontiers in Microbiology · 2025-09-04 · 1 citations

  articleOpen access

  The hyphosphere, the microhabitat surrounding fungal hyphae, hosts complex microbial interactions that can influence fungal biology, yet the microbial community in hyphospheres of pathogenic fungi are seldom characterized. In this study, we investigated the hyphosphere of Fusarium oxysporum f. sp. vasinfectum Race 4 (FOV4), a major fungal pathogen threatening cotton, to characterize its bacterial community and assess potential functional roles. An integrated approach was employed combining confocal time-lapse microscopy, 16S rRNA metabarcoding, culture-dependent bacterial isolation, whole genome sequencing, and fungal-bacterial coculture assays. Microscopy confirmed hyphosphere association, and the bacterial predisposition towards the growing hyphal tips. Metabarcoding showed a stable hyphosphere community dominated by a single Pseudomonas ASV accounting for over 95% of relative abundance, with strong negative correlations to most other taxa. To evaluate the functions, ten representative bacterial isolates were sequenced, revealing enrichment in metabolic pathways related to carbon, nitrogen, and sulfur cycling. In particular, Pseudomonas laurylsulfatiphila showed high counts of oxidoreductases and hydrolases. Coculture assays demonstrated that several bacterial isolates significantly promoted FOV4 hyphal extension, while having limited or inconsistent effects on other Fusarium strains, indicating strain-specific interactions. Together, the findings reveal a stable and functionally enriched bacterial community in the FOV4 hyphosphere, with potential implications for fungal fitness and virulence. These results support the emerging concept of a hyphosphere-pathobiome and highlight microbial associations as targets for future plant disease management strategies.

  PublisherOA PDFDOI

• Investigating the Effects of Misinformation as Infopathogens: Developing a Model and Thought Experiment

  Social Sciences · 2024-05-31

  articleOpen access

  Previously, it has been shown that transmissible and harmful misinformation can be viewed as pathogenic, potentially contributing to collective social epidemics. In this study, a biological analogy is developed to allow investigative methods that are applied to biological epidemics to be considered for adaptation to digital and social ones including those associated with misinformation. The model’s components include infopathogens, tropes, cognition, memes, and phenotypes. The model can be used for diagnostic, pathologic, and synoptic/taxonomic study of the spread of misinformation. A thought experiment based on a hypothetical riot is used to understand how disinformation spreads.

  PublisherOA PDFDOI

• Key Challenges in Plant Pathology in the Next Decade

  Phytopathology · 2024-05-01 · 34 citations

  articleOpen access

  Plant diseases significantly impact food security and food safety. It was estimated that food production needs to increase by 50% to feed the projected 9.3 billion people by 2050. Yet, plant pathogens and pests are documented to cause up to 40% yield losses in major crops, including maize, rice, and wheat, resulting in annual worldwide economic losses of approximately US$220 billion. Yield losses due to plant diseases and pests are estimated to be 21.5% (10.1 to 28.1%) in wheat, 30.3% (24.6 to 40.9%) in rice, and 22.6% (19.5 to 41.4%) in maize. In March 2023, The American Phytopathological Society (APS) conducted a survey to identify and rank key challenges in plant pathology in the next decade. Phytopathology subsequently invited papers that address those key challenges in plant pathology, and these were published as a special issue. The key challenges identified include climate change effect on the disease triangle and outbreaks, plant disease resistance mechanisms and its applications, and specific diseases including those caused by Candidatus Liberibacter spp. and Xylella fastidiosa. Additionally, disease detection, natural and man-made disasters, and plant disease control strategies were explored in issue articles. Finally, aspects of open access and how to publish articles to maximize the Findability, Accessibility, Interoperability, and Reuse of digital assets in plant pathology were described. Only by identifying the challenges and tracking progress in developing solutions for them will we be able to resolve the issues in plant pathology and ultimately ensure plant health, food security, and food safety.

  PublisherOA PDFDOI

• Duplicated Copy Number Variant of the Maize 9-Lipoxygenase ZmLOX5 Improves 9,10-KODA-Mediated Resistance to Fall Armyworms

  Genes · 2024-03-25 · 4 citations

  articleOpen access

  Extensive genome structure variations, such as copy number variations (CNVs) and presence/absence variations, are the basis for the remarkable genetic diversity of maize; however, the effect of CNVs on maize herbivory defense remains largely underexplored. Here, we report that the naturally occurring duplication of the maize 9-lipoxygenase gene ZmLOX5 leads to increased resistance of maize to herbivory by fall armyworms (FAWs). Previously, we showed that ZmLOX5-derived oxylipins are required for defense against chewing insect herbivores and identified several inbred lines, including Yu796, that contained duplicated CNVs of ZmLOX5, referred to as Yu796-2×LOX5. To test whether introgression of the Yu796-2×LOX5 locus into a herbivore-susceptible B73 background that contains a single ZmLOX5 gene is a feasible approach to increase resistance, we generated a series of near-isogenic lines that contained either two, one, or zero copies of the Yu796-2×LOX5 locus in the B73 background via six backcrosses (BC6). Droplet digital PCR (ddPCR) confirmed the successful introgression of the Yu796-2×LOX5 locus in B73. The resulting B73-2×LOX5 inbred line displayed increased resistance against FAW, associated with increased expression of ZmLOX5, increased wound-induced production of its primary oxylipin product, the α-ketol, 9-hydroxy-10-oxo-12(Z),15(Z)-octadecadienoic acid (9,10-KODA), and the downstream defense hormones regulated by this molecule, 12-oxo-phytodienoic acid (12-OPDA) and abscisic acid (ABA). Surprisingly, wound-induced JA-Ile production was not increased in B73-2×LOX5, resulting from the increased JA catabolism. Furthermore, B73-2×LOX5 displayed reduced water loss in response to drought stress, likely due to increased ABA and 12-OPDA content. Taken together, this study revealed that the duplicated CNV of ZmLOX5 quantitively contributes to maize antiherbivore defense and presents proof-of-concept evidence that the introgression of naturally occurring duplicated CNVs of a defensive gene into productive but susceptible crop varieties is a feasible breeding approach for enhancing plant resistance to herbivory and tolerance to abiotic stress.

  PublisherOA PDFDOI

• Sewing Brand Messages on Social Media: A Content Analysis of Cotton Incorporated’s Instagram Content Stimuli

  Journal of Applied Communications · 2024-08-16 · 1 citations

  articleOpen access

  Cotton is the most significant natural fiber in the world and an important part of the global economy. Yet, the cotton industry faces several challenges in securing its place in the global fiber market share, reaching new consumers, and maintaining relationships with current consumers. Furthermore, the cotton industry has a unique opportunity to share evidence-based information with followers through its product marketing on social media. The study described herein used content analysis to explore Instagram content on the @discovercotton profile. Content included categories of promoted products (i.e. women, men, children, or home); comments, posts, and caption stimuli; and most frequently used word, hashtag, and retail partner stimuli. We analyzed 434 Instagram stimuli (244 single photos, 142 carousels, and 48 videos) from March 2, 2021, to March 2, 2023. Across all stimuli, there were 110,143 likes and 5,799 comments with total response (engagement: likes and comments) reaching 115,942. We found that women’s products were promoted most often followed by men, home, and children—only 8.48% of stimuli depicted cotton, a cotton plant, or the seal of cotton. We identified six major themes in caption stimuli on @discovercotton: qualities of cotton, style, sustainability, check the label, women, and cotton production. Cotton was the most frequently used word stimuli in captions, and cotton as a fabric was the most promoted theme.

  PublisherDOI

• Age and calorific restriction impact immature black soldier fly (Diptera: Stratiomyidae) thermal tolerance and preference

  Journal of Insects as Food and Feed · 2024-07-25 · 4 citations

  article

  Abstract Thermal tolerance and preference are traits commonly considered when mass-producing farmed animals as temperature impacts production. In this study, the impact of age and calorific restriction of immature black soldier fly, Hermetia illucens (L.) (Diptera: Stratiomyidae) on associated thermal tolerance and preference was examined. Both age (7-d-old for young larvae and 14-d-old for old larvae) and calorific restriction (led to size differentiation, small for calorific restriction and large for non-restriction) within a given stage influenced thermal tolerance (i.e. KR 50 ) and thermal preference. Results indicate the interaction between age and calorific restriction was significant on both larval and prepupal thermal tolerance but not thermal preference. Median heat tolerance KR 50 ranged from 46.4 °C (large, old prepupae) to 48.4 °C (large, young larvae). Median cold tolerance KR 50 ranged from 21.6 °C (small, young larvae) to 32.1 °C (small, old larvae). Young larvae preferred median temperatures ∼3.0 °C greater than old larvae. Large larvae preferred median temperatures ∼2.0 °C lower than small larvae. Results from this study indicate ontogeny (i.e. stage of development) and calorific restriction have significant impacts on black soldier fly thermal tolerance and preference. Precise regulation of temperature in an industrial setting is necessary for optimal batch production of the black soldier fly (e.g. survival) and for colony maintenance (e.g. prepupae producing adults and potentially eggs). The same can be said with regards to maintaining consistent age and calorific restriction of immatures produced within each batch as variation in such traits impacts thermal tolerance and preference (e.g. survival to harvest for producing protein or adults for colony) as well. The methods and temperatures used in this study could serve as a foundation for developing standard operating procedures for regulating temperatures experienced by black soldier fly larvae industrially produced.

  PublisherDOI

Frequent coauthors

• Thomas Keller

  University of Salzburg

  21 shared

• Thomas Keller

  Federal Office for Agriculture

  13 shared

• George G. Kennedy

  11 shared

• Elsa R. Hirvela

  California State University, East Bay

  9 shared

• Virgil L. Williams

  Alameda Health System

  9 shared

• Lawrence J. Goldstein

  6 shared

• Travis W. Rusch

  Center for Grain and Animal Health Research

  5 shared

• Roger D. Magarey

  North Carolina State University

  5 shared

Education

• B.S., Biology

  University of Michigan

• Other, Performance

  University of Michigan

• Ph.D., Biology

  Duke University

• Other, Entomology

  North Carolina State University