About

Andrew J. Johnson is an Assistant Research Scientist in Forest Entomology at the School of Forest, Fisheries, and Geomatics Sciences, University of Florida. His research focuses on improving the global capacity to manage invasive bark and ambrosia beetles (Scolytinae). He coordinates forest health projects, resolves taxonomic issues to ensure meaningful naming of beetles, and collaborates with international researchers to address taxonomic challenges among potential pest species. Johnson employs phylogenetics and genomics to investigate evolutionary questions related to bark beetles. He is the principal identifier for the UF Forest Entomology Lab’s identification service, which involves identifying bark and ambrosia beetles for stakeholders in Florida, UF extension agents, state monitoring schemes, and global emerging threats. His work has led to the discovery of several species new to science and three new introduced species in the US. Johnson manages and curates the world’s largest cryo-preserved collection of Scolytinae, containing over 150,000 beetles from nearly every continent. He is actively developing a comprehensive data catalog for this collection and supports projects studying the symbiosis between ambrosia beetles and fungi. Additionally, he develops best practices for research involving these beetles, promoting accurate taxonomy and voucher use as part of the Bark Beetle Mycobiome Research Coordination Network.

Research topics

• Botany
• Biology
• Ecology
• Zoology

Selected publications

• Progress in developing a bark beetle identification tool

  PLoS ONE · 2025-06-05 · 3 citations

  articleOpen accessCorresponding

  This study presents an initial model for bark beetle identification, serving as a foundational step toward developing a fully functional and practical identification tool. Bark beetles are known for extensive damage to forests globally, as well as for uniform and homoplastic morphology which poses identification challenges. Utilizing a MaxViT-based deep learning backbone which utilizes local and global attention to classify bark beetles down to the genus level from images containing multiple beetles. The methodology involves a process of image collection, preparation, and model training, leveraging pre-classified beetle species to ensure accuracy and reliability. The model's F1 score estimates of 0.99 and 1.0 indicates a strong ability to accurately classify genera in the collected data, including those previously unknown to the model. This makes it a valuable first step towards building a tool for applications in forest management and ecological research. While the current model distinguishes among 12 genera, further refinement and additional data will be necessary to achieve reliable species-level identification, which is particularly important for detecting new invasive species. Despite the controlled conditions of image collection and potential challenges in real-world application, this study provides the first model capable of identifying the bark beetle genera, and by far the largest training set of images for any comparable insect group. We also designed a function that reports if a species appears to be unknown. Further research is suggested to enhance the model's generalization capabilities and scalability, emphasizing the integration of advanced machine learning techniques for improved species classification and the detection of invasive or undescribed species.

  PublisherDOI

• Scolytine beetle diversity along an altitudinal gradient in Papua New Guinea

  Insect Conservation and Diversity · 2025-04-03 · 4 citations

  articleOpen access

  Abstract Tropical elevation gradients support highly diverse assemblages, but competing hypotheses suggest either peak species richness in lowland rainforests or at mid‐elevations. We investigated scolytine beetles—phloem, ambrosia and seed‐feeding beetles—along a tropical elevational gradient in Papua New Guinea. Highly standardised sampling from 200 to 3700 m above sea level (asl) identified areas of highest and lowest species richness, abundance and other biodiversity variables. Using passive flight intercept traps at eight elevations from 200 to 3500 m asl, we collected over 9600 specimens representing 215 species. Despite extensive sampling, species accumulation curves suggest that diversity was not fully exhausted. Scolytine species richness followed a unimodal distribution, peaking between 700 and 1200 m asl, supporting prior findings of highest diversity at low‐to‐mid elevations. Alternative models, such as a monotonous decrease from lowlands to higher elevations and a mid‐elevation maximum, showed lesser fit to our data. Abundance is greatest at the lowest sites, driven by a few extremely abundant species. The turnover rate—beta diversity between elevation steps—is greatest between the highest elevations. Among dominant tribes—Dryocoetini, Xyleborini and Cryphalini—species richness peaked between 700 and 2200 m asl. Taxon‐specific analyses revealed distinct patterns: Euwallacea spp. abundance uniformly declined with elevation, while other genera were driven by dominant species at different elevations. Coccotrypes and phloem‐feeding Cryphalus have undergone evolutionary radiations in New Guinea, with many species still undescribed. Species not yet known to science are most likely to be found at lower and middle elevations, where overall diversity is highest.

  PublisherOA PDFDOI

• First record of <scp> <i>Euwallacea fornicatus</i> </scp> Eichhoff (Coleoptera: Curculionidae: Scolytinae) in Spain

  EPPO Bulletin · 2025-01-17 · 3 citations

  articleOpen accessSenior author

  Abstract The invasive polyphagous shot hole borer Euwallacea fornicatus (Eichhoff, 1868) was recorded in a public garden in Granada province, Andalusia, Southern Spain in April, 2022. This is the first record of a self‐sustaining population of this pest in an outdoor environment in Europe. This paper describes the morphological and molecular identification of the haplotype found in Spain. A recommended regulatory response is described, including a delimiting survey and an eradication program. The Spanish government is taking action to eradicate the pest.

  PublisherOA PDFDOI

• Objective risk assessment of bark and ambrosia beetles non‐indigenous to North America

  Ecological Applications · 2025-07-01 · 2 citations

  articleOpen access1st authorCorresponding

  Pest risk assessment informs regulatory decisions to facilitate safe trade while also protecting a country's agricultural and environmental resources. The first step in pest risk assessment is pest categorization which can help determine whether an in-depth examination is needed. We created a model to predict the potential impact of non-indigenous bark and ambrosia beetles (Curculionidae: Scolytinae). This model uses biological variables derived from extensive assessment of alien species and produces a five-point scale of impact prediction. We accommodate uncertainty and missing data using random decision tree forests with Monte Carlo simulations. Non-indigenous bark beetles include both invasive species with significant ecological impacts, such as widespread tree death, and others that pose little risk. We assembled a comprehensive list of 60 introduced non-native bark beetle species in the continental United States as the training set. Forty-two potentially predictive variables were chosen from reports on behaviors, pestilence, recorded damage/interpretations in literature, biological traits, and interactions with fungi including plant pathogens. The model builds upon strategies used by USDA-APHIS in existing risk assessments, specifically the Objective Prioritization of Exotic Pests (OPEP) model, with changes in the following: (1) a transparent dataset for building and training the model enabling future updates and use in other systems, (2) uncertainty simulations using values derived from an extensive natural history matrix rather than an assumed equal distribution, and (3) predictions made on the probability of multiple impact levels, allowing users to decide based on acceptable risk. The model is designed for pest risk analysis for Scolytinae in the continental United States but can be adapted to other pests or regions. We tested the model's performance by iteratively removing each species from the training set and retraining the model. The retrained models accurately predicted the removed species. To demonstrate the model's application, we predicted the impact of scolytine beetles not yet present in the continental United States, Xylosandrus morigerus and Hypoborus ficus, plus an additional hypothetical species with no known data. Our model predicts that these species are likely to have moderate impacts and unlikely to have high impacts if they were introduced.

  PublisherOA PDFDOI

• New records and taxonomic changes for the bark and ambrosia beetles (Coleoptera: Curculionidae: Scolytinae) of Florida

  Florida Entomologist · 2025-01-02 · 2 citations

  articleOpen access1st authorCorresponding

  Abstract Recent surveys of bark and ambrosia beetles (Coleoptera: Curculionidae: Scolytinae) in Florida, both in natural environments and in collections, allowed us to record species new to the state or the continent, clarify the taxonomic status of rarely studied species, and propose taxonomic changes. Five new synonymys are proposed: Dryocoetoides vexans (Schedl, 1972) (= Dryocoetoides reticulatus Atkinson, 2009 syn. nov. ); Hypothenemus atomus Hopkins, 1915 (= Stephanoderes buscki Hopkins, 1915 syn. nov. ); Hypothenemus californicus Hopkins, 1915 (= Stephanoderes gossypii Hopkins, 1915, syn. nov. , Hypothenemus beameri Wood, 1954, syn. nov. ); Xyleborinus gracilis (Eichhoff, 1868) (= Xyleborus quercus Hopkins, 1915: p. 63 syn. nov. ). Hypothenemus brunneus (Hopkins, 1915) stat. res. and Monarthrum praeustum (Eggers, 1941) stat. res. are removed from synonymy and reinstated as valid species. Ambrosiophilus osumiensis (Murayama, 1934) is reported for the first time in Florida. New records to the continental United States are reported for four species: Chramesus annectens (Wood, 1956) (native to Mexico), Hypothenemus suspectus Wood, 1974 (native to Central and South America), Hypothenemus villosus Bright, 2019, Monarthrum praeustum (Eggers, 1941), and Xyleborinus subgranulatus (Eggers, 1930).

  PublisherOA PDFDOI

• Introduction and establishment of <i>Euwallacea fornicatus</i> (Coleoptera: Curculionidae: Scolytinae) in Brazil

  Journal of Economic Entomology · 2024-04-19 · 4 citations

  articleOpen access

  Euwallacea fornicatus is an invasive tree pest able to infest healthy plants and cause damage to many host plants. This beetle has become established in several countries where it was introduced. It has now become established in Brazil, and while the original introduction site remains uncertain, there is a possibility of multiple introductions. We report the first evidence for the establishment of E. fornicatus with molecular confirmation, as well as its distribution, and host plants in Brazil. Euwallacea fornicatus has spread to main commercial avocado groves, other monocultures, and native vegetation in the country, and its pest status puts it as a threat, mainly to Brazilian avocado producers.

  PublisherOA PDFDOI

• Progress in Developing a Bark Beetle Identification Tool

  bioRxiv (Cold Spring Harbor Laboratory) · 2024-09-10 · 2 citations

  preprintOpen access

  Abstract This study presents an initial model for bark beetle identification, serving as a foundational step toward developing a fully functional and practical identification tool. Bark beetles are known for extensive damage to forests globally, as well as for uniform and homoplastic morphology which poses identification challenges. Utilizing a MaxViT-based deep learning backbone which utilizes blocked local and dilated global attention to classify bark beetles down to the genus level from images containing multiple beetles. The methodology involves a comprehensive process of image collection, preparation, and model training, leveraging pre-classified beetle species to ensure accuracy and reliability. The model’s F1 score estimates of 0.99 and 1.0 indicates a strong ability to accurately classify genera in the collected data, including those previously unknown to the model. This makes it a valuable first step towards building a tool for applications in forest management and ecological research. While the current model distinguishes among 12 genera, further refinement and additional data will be necessary to achieve reliable species-level identification, which is particularly important for detecting new invasive species. Despite the controlled conditions of image collection and potential challenges in real-world application, this study provides the first model capable of identifying the bark beetle genera, and by far the largest training set of images for any comparable insect group. We also designed a function that reports if a species appears to be unknown. Further research is suggested to enhance the model’s generalization capabilities and scalability, emphasizing the integration of advanced machine learning techniques for improved species classification and the detection of invasive or undescribed species.

  PublisherOA PDFDOI

• Pre-invasion assessment of potential invasive wood-borers on North American tree species in Chinese sentinel gardens

  Figshare · 2024-01-01

  datasetOpen access

  Table S1 To maximize transparency and utility of the data, here we include the full record of wood-borers and the colonized plant hosts. Vitality corresponds to tree scores evaluated by standards in Table 2. The 28S and COI represent the partial sequences of large subunit ribosomal RNA gene and the partial sequences of mitochondrial cytochrome c oxidase subunit I gene. Tissues correspond to the specific tissue colonized by the sampled wood borers. The IncidenceID corresponds to the supplementary folder names of the insect's images and sequences.Data for the manuscript titled "Pre-invasion assessment of potential invasive wood borers on North American tree species in Chinese sentinel gardens"<br>

  PublisherDOI

• Pre-invasion assessment of potential invasive wood borers on North American tree species in Chinese sentinel gardens

  Figshare · 2024-01-01

  datasetOpen access

  Table S1 To maximize transparency and utility of the data, here we include the full record of wood-borers and the colonized plant hosts. Vitality corresponds to tree scores evaluated by standards in Table 2. The 28S and COI represent the partial sequences of large subunit ribosomal RNA gene and the partial sequences of mitochondrial cytochrome c oxidase subunit I gene. Tissues correspond to the specific tissue colonized by the sampled wood borers. The IncidenceID corresponds to the supplementary folder names of the insect's images and sequences.https://www.dropbox.com/scl/fo/081jgmg0ccpykzobx4gjz/h?rlkey=9hwgt7k1tghk97287b162wfuw&amp;dl=0Data for the manuscript titled "Pre-invasion assessment of potential invasive wood borers on North American tree species in Chinese sentinel gardens"<br>

  PublisherDOI

• Yet Another New Exotic Ambrosia Beetle (Coleoptera: Scolytinae: Xyleborini) in Florida: Cyclorhipidion japonicum (Nobuchi, 1981)

  The Coleopterists Bulletin · 2023-03-13 · 2 citations

  articleOpen access1st authorCorresponding

  Johnson, Andrew J., Smith, Sarah M. (2023): Yet Another New Exotic Ambrosia Beetle (Coleoptera: Scolytinae: Xyleborini) in Florida: Cyclorhipidion japonicum (Nobuchi, 1981). The Coleopterists Bulletin 77 (1): 148-151, DOI: 10.1649/0010-065X-77.1.148, URL: http://dx.doi.org/10.1649/0010-065x-77.1.148

  PublisherOA PDFDOI

Frequent coauthors

• You Li

  China Agricultural University

  35 shared

• Jiří Hulcr

  29 shared

• Esteban Ceriani-Nakamurakare

  16 shared

• Demian F. Gómez

  US Forest Service

  14 shared

• Robert Sochon

  GlaxoSmithKline (United Kingdom)

  12 shared

• Paul D. I. Fletcher

  10 shared

• James Skelton

  10 shared

• Bernard P. Binks

  University of Hull

  9 shared