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ABSTRACT AimThe global, human‐mediated dispersal of invasive insects is a major driver of ecosystem change, biodiversity loss, crop damage and other effects. Trade flows and invasive species propagule pressure are correlated, and their relationship is essential for predicting and managing future invasions. Invaders do not disperse exclusively from the species' native range. Instead, the bridgehead effect, where established, non‐native populations act as secondary sources of propagule, is recognised as a major driver of global invasion. The resulting pattern of global spread arises from a mixture of global interactions between invasive species, their vectors and, their invaded ranges, which has yet to be fully characterised. LocationGlobal. Time Period1997–2020. Major Taxa StudiedInsects. MethodsWe analysed 319,283 border interception records of 514 insect species from a broad range of taxa from four national‐level phytosanitary organisations. We classified interceptions as coming from species native range or from bridgehead countries and examined taxonomic autocorrelation of global movement patterns between species. ResultsWhile 65% of interceptions originated from bridgehead countries, highlighting the importance of the bridgehead effect across taxa, patterns among individual species were highly variable and taxonomically correlated. Forty per cent of species originated almost exclusively from their native range, 28% almost exclusively from their non‐native range and 32% from a mix of source locations. These patterns of global dispersal were geographically widespread, temporally consistent, and taxonomically correlated. ConclusionsDispersal exclusively from bridgeheads represents an unrecognised pattern of global insect movement; these patterns emphasise the importance of the bridgehead effect and suggest that bridgeheads provide unique local conditions that allow invaders to proliferate differently than in their native range. We connect these patterns of global dispersal to the conditions during the human driven global dispersal of insects and provide recommendations for modellers and policymakers wishing to control the spread of future invasions. 

Abstract In 1843, a hitherto unknown plant pathogen entered the US and spread to potato fields in the northeast. By 1845, the pathogen had reached Ireland leading to devastating famine. Questions arose immediately about the source of the outbreaks and how the disease should be managed. The pathogen, now known asPhytophthora infestans, still continues to threaten food security globally. A wealth of untapped knowledge exists in both archival and modern documents, but is not readily available because the details are hidden in descriptive text. In this work, we (1) used text analytics of unstructured historical reports (1843–1845) to map US late blight outbreaks; (2) characterized theories on the source of the pathogen and remedies for control; and (3) created modern late blight intensity maps using Twitter feeds. The disease spread from 5 to 17 states and provinces in the US and Canada between 1843 and 1845. Crop losses, Andean sources of the pathogen, possible causes and potential treatments were discussed. Modern disease discussion on Twitter included near-global coverage and local disease observations. Topic modeling revealed general disease information, published research, and outbreak locations. The tools described will help researchers explore and map unstructured text to track and visualize pandemics. 

Summary Powdery mildew is an economically important disease caused byc. 1000 different fungal species.Erysiphe vacciniiis an emerging powdery mildew species that is impacting the blueberry industry. Once confined to North America,E. vacciniiis now spreading rapidly across major blueberry‐growing regions, including China, Morocco, Mexico, and the USA, threatening millions in losses.This study documents its recent global spread by analyzing both herbarium specimens, some over 150‐yr‐old, and fresh samples collected world‐wide.Our findings were integrated into a ‘living phylogeny’ via T‐BAS to simplify pathogen identification and enable rapid responses to new outbreaks. We identified 50 haplotypes, two primary introductions world‐wide, and revealed a shift from a generalist to a specialist pathogen.This research provides insights into the complexities of host specialization and highlights the need to address this emerging global threat to blueberry production. 

Abstract Molecular diagnostics for crop diseases can guide the precise application of pesticides, thereby reducing pesticide usage while improving crop yield, but tools are lacking. Here, we report an in-field molecular diagnostic tool that uses a cheap colorimetric paper and a smartphone, allowing multiplexed, low-cost, rapid detection of crop pathogens. Rapid nucleic acid amplification-free detection of pathogenic RNA is achieved by combining toehold-mediated strand displacement with a metal ion-mediated urease catalysis reaction. We demonstrate multiplexed detection of six wheat pathogenic fungi and an early detection of wheat stripe rust. When coupled with a microneedle for rapid nucleic acid extraction and a smartphone app for results analysis, the sample-to-result test can be completed in ~10 min in the field. Importantly, by detecting fungal RNA and mutations, the approach allows to distinguish viable and dead pathogens and to sensitively identify mutation-carrying fungicide-resistant isolates, providing fundamental information for precision crop disease management. 

Abstract Non‐native plant pests and pathogens threaten biodiversity, ecosystem function, food security, and economic livelihoods. As new invasive populations establish, often as an unintended consequence of international trade, they can become additional sources of introductions, accelerating global spread through bridgehead effects. While the study of non‐native pest spread has used computational models to provide insights into drivers and dynamics of biological invasions and inform management, efforts have focused on local or regional scales and are challenged by complex transmission networks arising from bridgehead population establishment. This paper presents a flexible spatiotemporal stochastic network model called PoPS (Pest or Pathogen Spread) Global that couples international trade networks with core drivers of biological invasions—climate suitability, host availability, and propagule pressure—quantified through open, globally available databases to forecast the spread of non‐native plant pests. The modular design of the framework makes it adaptable for various pests capable of dispersing via human‐mediated pathways, supports proactive responses to emerging pests when limited data are available, and enables forecasts at different spatial and temporal resolutions. We demonstrate the framework using a case study of the invasive planthopper spotted lanternfly (Lycorma delicatula). The model was calibrated with historical, known spotted lanternfly introductions to identify potential bridgehead populations that may contribute to global spread. This global view of phytosanitary pandemics provides crucial information for anticipating biological invasions, quantifying transport pathways risk levels, and allocating resources to safeguard plant health, agriculture, and natural resources. 

Volatile organic compounds (VOCs) are common constituents of fruits, vegetables, and crops, and are closely associated with their quality attributes, such as firmness, sugar level, ripeness, translucency, and pungency levels. While VOCs are vital for assessing vegetable quality and phenotypic classification, traditional detection methods, such as Gas Chromatography-Mass Spectrometry (GC-MS) and Proton Transfer Reaction Mass Spectrometry (PTR-MS) are limited by expensive equipment, complex sample reparation, and slow turnaround time. Additionally, the transient nature of VOCs complicates their detection using these methods. Here, we developed a paper-based colorimetric sensor array combined with needles that could: 1) induce vegetable VOC release in a minimally invasive fashion, and 2) analyze VOCs in situ with a smartphone reader device. The needle sampling device helped release specific VOCs from the studied vegetables that usually require mechanic stimulation, while maintaining the vegetable viability. On the other hand, the colorimetric sensor array was optimized for sulfur compound-based VOCs with a limit of detection (LOD) in the 1–25 ppm range, and classified fourteen different vegetable VOCs, including sulfoxides, sulfides, mercaptans, thiophenes, and aldehydes. By combining principal components analysis (PCA) nalysis, the integrated sensor platform proficiently discriminated between four vegetable subtypes originating from two major categories within 2 min of testing time. Additionally, the sensor demomstrated the capability to distinguish between different types of tested fruits and vegetables, including garlic, green pepper, and nectarine. This rapid and minimally invasive sensing technology holds great promise for conducting field-based vegetable quality monitoring. 

Phytophthora is a long-established, well known and globally important genus of plant pathogens. Phylogenetic evidence has shown that the biologically distinct, obligate biotrophic downy mildews evolved from Phytophthora at least twice. Since, cladistically, this renders Phytophthora ‘paraphyletic’, it has been proposed that Phytophthora evolutionary clades be split into multiple genera (Runge et al. 2011; Crous et al. 2021; Thines et al. 2023; Thines 2024). In this letter, we review arguments for the retention of the generic name Phytophthora with a broad circumscription made by Brasier et al. (2022) and by many delegates at an open workshop organized by the American Phytopathological Society. We present our well-considered responses to this proposal in general terms and to the specific proposals for new genera; together with new information regarding the biological properties and mode of origin of the Phytophthora clades. We consider that the proposals for new genera are mostly non-rigorous and not supported by the scientific evidence. Further, given (1) the apparent lack of any distinguishing biological characteristics (synapomorphies) between the Phytophthora clades; (2) the fundamental monophyly of Phytophthora in the original Haeckelian sense; (3) the fact that paraphyly is not a justification for taxonomic splitting; and (4) the considerable likely damage to effective scientific communication and disease management from an unnecessary break-up of the genus, we report that Workshop delegates voted unanimously in favour of preserving the current generic concept and for seeking endorsement of this view by a working group of the International Commission on the Taxonomy of Fungi. 

We examined the evolutionary history ofPhytophthora infestansand its close relatives in the 1c clade. We used whole genome sequence data from 69 isolates ofPhytophthoraspecies in the 1c clade and conducted a range of genomic analyses including nucleotide diversity evaluation, maximum likelihood trees, network assessment, time to most recent common ancestor and migration analysis. We consistently identified distinct and later divergence of the two MexicanPhytophthoraspecies,P.mirabilisandP.ipomoeae, fromP.infestansand other 1c clade species.Phytophthora infestansexhibited more recent divergence from other 1c clade species ofPhytophthorafrom South America,P.andinaandP.betacei. Speciation in the 1c clade and evolution ofP.infestansoccurred in the Andes.P.andina–P.betacei–P.infestansformed a species complex with indistinct species boundaries, hybridizations between the species, and short times to common ancestry. Furthermore, the distinction between modern Mexican and South AmericanP.infestansproved less discrete, suggesting gene flow between populations over time. Admixture analysis indicated a complex relationship among these populations, hinting at potential gene flow across these regions. HistoricP.infestans, collected from 1845–1889, were the first to diverge from all otherP.infestanspopulations. Modern South American populations diverged next followed by Mexican populations which showed later ancestry. Both populations were derived from historicP.infestans. Based on the time of divergence ofP.infestansfrom its closest relatives,P.andinaandP.betaceiin the Andean region, we consider the Andes to be the center of origin ofP.infestans, with modern globalization contributing to admixture betweenP.infestanspopulations today from Mexico, the Andes and Europe. 

Phytophthora infestans is a major oomycete plant pathogen, responsible for potato late blight, which led to the Irish Potato Famine from 1845–1852. Since then, potatoes resistant to this disease have been bred and deployed worldwide. Their resistance (R) genes recognize pathogen effectors responsible for virulence and then induce a plant response stopping disease progression. However, most deployed R genes are quickly overcome by the pathogen. We use targeted sequencing of effector and R genes on herbarium specimens to examine the joint evolution in both P. infestans and potato from 1845–1954. Currently relevant effectors are historically present in P. infestans, but with alternative alleles compared tomodern reference genomes. The historic FAM-1 lineage has the virulent Avr1 allele and the ability to break the R1 resistance gene before breeders deployed it in potato. The FAM-1 lineage is diploid, but later, triploid US-1 lineages appear. We show that pathogen virulence genes and host resistance genes have undergone significant changes since the Famine, from both natural and artificial selection. 

Rapid detection of plant diseases before they escalate can improve disease control. Our team has developed rapid nucleic acid extraction methods with microneedles (MN) and combined these with LAMP assays for pathogen detection in the field. In this work, we developed LAMP assays for early blight (Alternaria linariae, A. alternata, and A. solani) and bacterial spot of tomato (Xanthomonas perforans) and validated these LAMP assays and two previously developed LAMP assays for tomato spotted wilt virus and late blight. Tomato plants were inoculated and disease severity was measured. Extractions were performed using MN and LAMP assays were run in tubes (with hydroxynaphthol blue) on a heat block or on a newly designed microfluidic slide chip on a heat block or a slide heater. Fluorescence on the microfluidic chip slides was visualized using EvaGreen and photographed on a smartphone. Plants inoculated with X. perforans or tomato spotted wilt virus tested positive prior to visible disease symptoms, while P. infestans and A. linariae were detected at the time of visual disease symptoms. LAMP assays were more sensitive than PCR and the limit of detection was 1 pg of DNA for both A. linariae and X. perforans. The LAMP assay designed for early blight detected all three species of Alternaria that infect tomato and is thus an Alternaria spp. assay. This study demonstrates the utility of rapid MN extraction followed by LAMP on a microfluidic chip for rapid diagnosis of four important tomato pathogens.