Predicting potential global and future distributions of the African armyworm (Spodoptera exempta) using species distribution models.

Invasive species have historically been a problem derived from global trade and transport. To aid in the control and management of these species, species distribution models (SDMs) have been used to help predict possible areas of expansion. Our focal organism, the African Armyworm (AAW), has historically been known as an important pest species in Africa, occurring at high larval densities and causing outbreaks that can cause enormous economic damage to staple crops. The goal of this study is to map the AAW's present and potential distribution in three future scenarios for the region, and the potential global distribution if the species were to invade other territories, using 40 years of data on more than 700 larval outbreak reports from Kenya and Tanzania. The present distribution in East Africa coincides with its previously known distribution, as well as other areas of grassland and cropland, which are the host plants for this species. The different future climatic scenarios show broadly similar potential distributions in East Africa to the present day. The predicted global distribution shows areas where the AAW has already been reported, but also shows many potential areas in the Americas where, if transported, environmental conditions are suitable for AAW to thrive and where it could become an invasive species.

Institutional and policy bottlenecks to IPM.

This paper summarises institutional and policy bottlenecks to IPM in Africa. Agricultural policy in Africa generally prioritises production and productivity above environmental sustainability, so the use of synthetic pesticides for controlling pests is encouraged. Funding for research in IPM is limited, and extension systems struggle to provide the level of farmer support that adoption of IPM often needs. Improved research and extension policies could facilitate uptake of IPM. Public and private food-safety standards can incentivise adoption, but currently this is mainly in production for export. Pesticide and other input regulatory systems unintentionally constrain adoption of IPM, through expensive registration procedures, weak compliance monitoring and limited regional harmonisation. IPM must be seen as a key element of food-system transformation.

Comparing, evaluating and combining statistical species distribution models and CLIMEX to forecast the distributions of emerging crop pests.

BACKGROUND: Forecasting the spread of emerging pests is widely requested by pest management agencies in order to prioritise and target efforts. Two widely used approaches are statistical Species Distribution Models (SDMs) and CLIMEX, which uses ecophysiological parameters. Each have strengths and weaknesses. SDMs can incorporate almost any environmental condition and their accuracy can be formally evaluated to inform managers. However, accuracy is affected by data availability and can be limited for emerging pests, and SDMs usually predict year-round distributions, not seasonal outbreaks. CLIMEX can formally incorporate expert ecophysiological knowledge and predicts seasonal outbreaks. However, the methods for formal evaluation are limited and rarely applied. We argue that both approaches can be informative and complementary, but we need tools to integrate and evaluate their accuracy. Here we develop such an approach, and test it by forecasting the potential global range of the tomato pest Tuta absoluta. RESULTS: The accuracy of previously developed CLIMEX and new statistical SDMs were comparable on average, but the best statistical SDM techniques and environmental data substantially outperformed CLIMEX. The ensembled approach changes expectations of T. absoluta's spread. The pest's environmental tolerances and potential range in Africa, the Arabian Peninsula, Central Asia and Australia will be larger than previous estimates. CONCLUSION: We recommend that CLIMEX be considered one of a suite of SDM techniques and thus evaluated formally. CLIMEX and statistical SDMs should be compared and ensembled if possible. We provide code that can be used to do so when employing the biomod suite of SDM techniques. © 2021 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Fall armyworm from a maize multi-peril pest risk perspective.

We assembled 3,175 geo-tagged occurrences of fall armyworm worldwide and used that data in conjunction with information about the physiological requirements of the pest to spatially assess its global climate suitability. Our analysis indicates that almost the entire African maize crop is grown in areas with climates that support seasonal infestations of the insect, while almost 92% of the maize area supports year-round growth of the pest. In contrast, rich-country maize production largely occurs in temperate areas where only 2.3% of the area may allow the pest to survive year-round, although still subject to worrisome seasonal risks. This means the African maize crop is especially susceptible to damaging infestation from fall armyworm, on par with the risk exposure to this pest faced by maize producers throughout Latin America. We show that the maize grown in Africa is also especially vulnerable to infestations from a host of other crop pests. Our multi-peril pest risk study reveals that over 95% of the African maize area deemed climate suitable for fall armyworm, can also support year-round survival of at least three or more pests. The spatial concurrence of climatically suitable locations for these pests raises the production risk for farmers well above the risks posed from fall armyworm alone. Starkly, over half (52.5%) of the African maize area deemed suitable for fall armyworm is also at risk from a further nine pests, while over a third (38.1%) of the area is susceptible to an additional 10 pests. This constitutes an exceptionally risky production environment for African maize producers, with substantive and complex implications for developing and implementing crop breeding, biological, chemical and other crop management strategies to help mitigate these multi-peril risks.

Assessing the Potential of Inoculative Field Releases of Telenomus remus to Control Spodoptera frugiperda in Ghana.

In response to the threat caused by the fall armyworm to African maize farmers, we conducted a series of field release studies with the egg parasitoid Telenomus remus in Ghana. Three releases of ≈15,000 individuals each were conducted in maize plots of 0.5 ha each in the major and minor rainy seasons of 2020, and compared to no-release control plots as well as to farmer-managed plots with chemical pest control. No egg mass parasitism was observed directly before the first field release. Egg mass parasitism reached 33% in the T. remus release plot in the major rainy season, while 72-100% of egg masses were parasitized in the minor rainy season, during which pest densities were much lower. However, no significant difference in egg mass parasitism was found among the T. remus release plots, the no-release control plots and the farmer-managed plots. Similarly, no significant decrease in larval numbers or plant damage was found in the T. remus release fields compared to the no-release plots, while lower leaf and tassel damage was observed in farmer-managed plots. Larval parasitism due to other parasitoids reached 18-42% in the major rainy season but was significantly lower in the minor rainy season, with no significant differences among treatments. We did not observe significant differences in cob damage or yield among the three treatments. However, the lack of any significant differences between the release and no-release plots, which may be attributed to parasitoid dispersal during the five weeks of observation, would require further studies to confirm. Interestingly, a single application of Emamectin benzoate did not significantly affect the parasitism rates of T. remus and, thus, merits further investigation in the context of developing IPM strategies against FAW.

Regional and seasonal activity predictions for fall armyworm in Australia.

Since 2016, the fall armyworm (FAW), Spodoptera frugiperda, has undergone a significant range expansion from its native range in the Americas, to continental Africa, Asia, and in February 2020, mainland Australia. The large dispersal potential of FAW adults, wide host range of immature feeding stages, and unique environmental conditions in its invasive range creates large uncertainties in the expected impact on Australian plant production industries. Here, using a spatial model of population growth and spread potential informed by existing biological and climatic data, we simulate seasonal population activity potential of FAW, with a focus on Australia's grain production regions. Our results show that, in Australia, the large spread potential of FAW will allow it to exploit temporarily favourable conditions for population growth across highly variable climatic conditions. It is estimated that FAW populations would be present in a wide range of grain growing regions at certain times of year, but importantly, the expected seasonal activity will vary markedly between regions and years depending on climatic conditions. The window of activity for FAW will be longer for growing regions further north, with some regions possessing conditions conducive to year-round population survival. Seasonal migrations from this permanent range into southern regions, where large areas of annual grain crops are grown annually, are predicted to commence from October, i.e. spring, with populations subsequently building up into summer. The early stage of the FAW incursion into Australia means our predictions of seasonal activity potential will need to be refined as more Australian-specific information is accumulated. This study has contributed to our early understanding of FAW movement and population dynamics in Australia. Importantly, the models established here provide a useful framework that will be available to other countries should FAW invade in the future. To increase the robustness of our model, field sampling to identify conditions under which population growth occurs, and the location of source populations for migration events is required. This will enable accurate forecasting and early warning to farmers, which should improve pest monitoring and control programs of FAW.

Understanding smallholders' responses to fall armyworm (Spodoptera frugiperda) invasion: Evidence from five African countries.

Fall armyworm (FAW) is a new invasive pest that is causing devastating effects on maize production and threatening the livelihoods of millions of poor smallholders across sub-Saharan Africa and Asia. Using unique survey data from 2356 maize-growing households in Ghana, Rwanda, Uganda, Zambia and Zimbabwe, we examined how smallholder farmers are fighting this voracious pest. In particular, we assessed the FAW management strategies used by smallholders, socio-economic factors driving the choice of the management options, the complementarities or tradeoffs among the management options, and the (un)safe pesticide use practices of farmers. Results showed that smallholder farm households have adopted a variety of cultural, physical, chemical and local options to mitigate the effects of FAW, but the use of synthetic pesticides remains the most popular option. Results from multivariate probit regressions indicated that the extensive use of synthetic pesticides is driven by household asset wealth, and access to subsidised farm inputs and extension information. We observed that farm households are using a wide range of pesticides, including highly hazardous and banned products. Unfortunately, a majority of the households do not use personal protective equipment while handling the pesticides, resulting in reports of acute pesticide-related illness. Our findings have important implications for policies and interventions aimed at promoting environmentally friendly and sustainable ways of managing invasive pests in smallholder farming systems.

Publisher Correction: Science diplomacy for plant health.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Why don't smallholder farmers in Kenya use more biopesticides?

BACKGROUND: Although Kenya has a relatively high number of registered biopesticide products, little is known about biopesticide use by smallholders. This paper documents farmers' current use and perception of chemical pesticides and biopesticides, their willingness to pay for biopesticides, and the key challenges to biopesticide uptake. RESULTS: A survey found that chemical pesticides are used widely by smallholders despite awareness of the risks to human health and the environment. Almost half of respondents showed awareness of biopesticides, but current use in the survey localities was low (10%). Key reasons for the low use of biopesticides by smallholders in this study are: perceptions of effectiveness, primarily speed of action and spectrum of activity, availability and affordability. Smallholders who used biopesticides cited effectiveness, recommendation by advisory services and perception of safety as key reasons for their choice. Although farmers viewed both pesticides and biopesticides as costly, they invested in the former due to their perceived effectiveness. Average willingness to pay, above current chemical pesticide expenditures per cropping season was 9.6% (US$5.7). Willingness to pay differed significantly between counties, and was higher among farmers with more education or greater awareness of the health risks associated with pesticide use. CONCLUSION: This study confirms the low use of biopesticide products in the survey areas, alongside high use of conventional chemical pesticides. In order to promote greater uptake of biopesticides, addressing farmers' awareness and their perceptions of effectiveness is important, as well as increasing the knowledge of those providing advice and ensuring registered products are available locally at competitive prices. © 2020 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Parasitoid Complex of Fall Armyworm, Spodoptera frugiperda, in Ghana and Benin.

Keywords: biological control; Chelonus bifoveolatus; Coccygidum luteum; Telenomus remus; Trichogramma; West Africa.

Evidence of Leaf Consumption Rate Decrease in Fall Armyworm, Spodoptera frugiperda, Larvae Parasitized by Coccygidium luteum.

Biological control is one of the best options for the sustainable management of the invasive maize pest Spodoptera frugiperda in Africa. However, there is limited knowledge of the efficacy of native natural enemies of S. frugiperda and their potential use in integrated pest management. The endoparasitoid wasp Coccygidium luteum is one of the natural enemies of S. frugiperda in Africa. This study assessed, under laboratory conditions, the effect of C. luteum on the leaf consumption rate of its host. Fifty first instar S. frugiperda larvae were exposed to C. luteum for oviposition and the maize leaf consumption rate of parasitized larvae was assessed and compared to 50 unparasitized larvae from the same cohort. Coccygidium luteum completed a generation, from egg to adult emergence, in 16.7 days. The leaf consumption rate of parasitized S. frugiperda larvae declined gradually compared to unparasitized larvae and the overall consumption reduction by parasitized S. frugiperda larvae was 89%. Our findings show that C. luteum could reduce damage caused by S. frugiperda to maize farms but, prior to its use in biological control programmes, further studies are needed to assess potential parasitism rates in field conditions and develop a cost-effective mass production system.

Farmer perception of fall armyworm (Spodoptera frugiderda J.E. Smith) and farm-level management practices in Zambia.

BACKGROUND: This paper documents farmer perceptions and management practices for fall armyworm (Spodoptera frugiderda J.E. Smith), providing a baseline for the development of sustainable pest management strategies. RESULTS: 91% of farmers correctly identified fall armyworm, and reported it as the most important maize pest during 2016/2017 cropping season, affecting nearly half of cultivated area. Estimated maize yield loss during the season, attributed to fall armyworm was 28%. A majority of farmers (60%) used pesticides for fall armyworm control, along with other cultural/physical practices - hand picking and crushing egg masses/caterpillars (36%), and application of ash/sand in the funnel (19%). Farmers used various pesticide active ingredients, and protective measures were inadequate; >50% of farmers did not use any protective measures while spraying. Significantly more male than female farmers used pesticides (P = 0.05), and the reverse was true for cultural practices. Significant maize yield differences (P = 0.001) were observed by gender, attributed to differences in utilization of production inputs/practices. At least 77% of farmers received and shared agricultural advice, which can be optimized to spread information on fall armyworm management options. CONCLUSION: Increased use of pesticides to manage fall armyworm poses health and environmental risks, besides the high cost for farmers and governments. Research into cultural and indigenous practices used by farmers will offer opportunities for alternative and sustainable management practices. Research efforts should pay attention to gender differences in access to resources and inputs. Tackling fall armyworm at the farm level, and averting yield losses will require integrated messaging addressing other production risks. © 2019 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Next generation sequencing of PD-L1 for predicting response to immune checkpoint inhibitors.

BACKGROUND: PD-L1 immunohistochemistry (IHC) has been traditionally used for predicting clinical responses to immune checkpoint inhibitors (ICIs). However, there are at least 4 different assays and antibodies used for PD-L1 IHC, each developed with a different ICI. We set to test if next generation RNA sequencing (RNA-seq) is a robust method to determine PD-L1 mRNA expression levels and furthermore, efficacy of predicting response to ICIs as compared to routinely used, standardized IHC procedures. METHODS: A total of 209 cancer patients treated on-label by FDA-approved ICIs, with evaluable responses were assessed for PD-L1 expression by RNA-seq and IHC, based on tumor proportion score (TPS) and immune cell staining (ICS). A subset of serially diluted cases was evaluated for RNA-seq assay performance across a broad range of PD-L1 expression levels. RESULTS: Assessment of PD-L1 mRNA levels by RNA-seq demonstrated robust linearity across high and low expression ranges. PD-L1 mRNA levels assessed by RNA-seq and IHC (TPS and ICS) were highly correlated (p < 2e-16). Sub-analyses showed sustained correlation when IHC results were classified as high or low by clinically accepted cut-offs (p < 0.01), and results did not differ by tumor type or anti-PD-L1 antibody used. Overall, a combined positive PD-L1 result (≥1% IHC TPS and high PD-L1 expression by RNA-Seq) was associated with a 2-to-5-fold higher overall response rate (ORR) compared to a double negative result. Standard assessments of sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) showed that a PD-L1 positive assessment for melanoma samples by RNA-seq had the lowest sensitivity (25%) but the highest PPV (72.7%). Among the three tumor types analyzed in this study, the only non-overlapping confidence interval for predicting response was for "RNA-seq low vs high" in melanoma. CONCLUSIONS: Measurement of PD-L1 mRNA expression by RNA-seq is comparable to PD-L1 expression by IHC both analytically and clinically in predicting ICI response. RNA-seq has the added advantages of being amenable to standardization and avoidance of interpretation bias. PD-L1 by RNA-seq needs to be validated in future prospective ICI clinical studies across multiple histologies.

Predicting response to checkpoint inhibitors in melanoma beyond PD-L1 and mutational burden.

BACKGROUND: Immune checkpoint inhibitors (ICIs) have changed the clinical management of melanoma. However, not all patients respond, and current biomarkers including PD-L1 and mutational burden show incomplete predictive performance. The clinical validity and utility of complex biomarkers have not been studied in melanoma. METHODS: Cutaneous metastatic melanoma patients at eight institutions were evaluated for PD-L1 expression, CD8+ T-cell infiltration pattern, mutational burden, and 394 immune transcript expression. PD-L1 IHC and mutational burden were assessed for association with overall survival (OS) in 94 patients treated prior to ICI approval by the FDA (historical-controls), and in 137 patients treated with ICIs. Unsupervised analysis revealed distinct immune-clusters with separate response rates. This comprehensive immune profiling data were then integrated to generate a continuous Response Score (RS) based upon response criteria (RECIST v.1.1). RS was developed using a single institution training cohort (n = 48) and subsequently tested in a separate eight institution validation cohort (n = 29) to mimic a real-world clinical scenario. RESULTS: PD-L1 positivity ≥1% correlated with response and OS in ICI-treated patients, but demonstrated limited predictive performance. High mutational burden was associated with response in ICI-treated patients, but not with OS. Comprehensive immune profiling using RS demonstrated higher sensitivity (72.2%) compared to PD-L1 IHC (34.25%) and tumor mutational burden (32.5%), but with similar specificity. CONCLUSIONS: In this study, the response score derived from comprehensive immune profiling in a limited melanoma cohort showed improved predictive performance as compared to PD-L1 IHC and tumor mutational burden.

Pest risk assessment of Spodoptera frugiperda for the European Union.

EFSA was asked for a partial risk assessment of Spodoptera frugiperda for the territory of the EU focussing on the main pathways for entry, factors affecting establishment, risk reduction options and pest management. As a polyphagous pest, five commodity pathways were examined in detail. Aggregating across these and other pathways, we estimate that tens of thousands to over a million individual larvae could enter the EU annually on host commodities. Instigating risk reduction options on sweetcorn, a principal host, reduces entry on that pathway 100-fold. However, sweetcorn imports are a small proportion of all S. frugiperda host imports, several of which are already regulated and further regulation is estimated to reduce the median number entering over all pathways by approximately 10%. Low temperatures limit the area for establishment but small areas of Spain, Italy and Greece can provide climatic conditions suitable for establishment. If infested imported commodities are distributed across the EU in proportion to consumer population, a few hundreds to a few thousands of individuals would reach NUTS 2 regions within which suitable conditions for establishment exist. Although S. frugiperda is a known migrant, entry directly into the EU from extant populations in sub-Saharan Africa is judged not feasible. However, if S. frugiperda were to establish in North Africa, in the range of thousands to over two million adults could seasonally migrate into the southern EU. Entry into suitable NUTS2 areas via migration will be greater than via commercial trade but is contingent on the establishment of S. frugiperda in North Africa. The likelihood of entry of the pest via natural dispersal could only be mitigated via control of the pest in Africa. If S. frugiperda were to arrive and become a pest of maize in the EU, Integrated Pest Management (IPM) or broad spectrum insecticides currently used against existing pests could be applied.

Planning clinically relevant biomarker validation studies using the "number needed to treat" concept.

PURPOSE: Despite an explosion of translational research to exploit biomarkers in diagnosis, prediction and prognosis, the impact of biomarkers on clinical practice has been limited. The elusiveness of clinical utility may partly originate when validation studies are planned, from a failure to articulate precisely how the biomarker, if successful, will improve clinical decision-making for patients. Clarifying what performance would suffice if the test is to improve medical care makes it possible to design meaningful validation studies. But methods for tackling this part of validation study design are undeveloped, because it demands uncomfortable judgments about the relative values of good and bad outcomes resulting from a medical decision. METHODS: An unconventional use of "number needed to treat" (NNT) can structure communication for the trial design team, to elicit purely value-based outcome tradeoffs, conveyed as the endpoints of an NNT "discomfort range". The study biostatistician can convert the endpoints into desired predictive values, providing criteria for designing a prospective validation study. Next, a novel "contra-Bayes" theorem converts those predictive values into target sensitivity and specificity criteria, to guide design of a retrospective validation study. Several examples demonstrate the approach. CONCLUSION: In practice, NNT-guided dialogues have contributed to validation study planning by tying it closely to specific patient-oriented translational goals. The ultimate payoff comes when the report of the completed study includes motivation in the form of a biomarker test framework directly reflecting the clinical decision challenge to be solved. Then readers will understand better what the biomarker test has to offer patients.

Improving Cancer Gene Expression Data Quality through a TCGA Data-Driven Evaluation of Identifier Filtering.

Data quality is a recognized problem for high-throughput genomics platforms, as evinced by the proliferation of methods attempting to filter out lower quality data points. Different filtering methods lead to discordant results, raising the question, which methods are best? Astonishingly, little computational support is offered to analysts to decide which filtering methods are optimal for the research question at hand. To evaluate them, we begin with a pair of expression data sets, transcriptomic and proteomic, on the same samples. The pair of data sets form a test-bed for the evaluation. Identifier mapping between the data sets creates a collection of feature pairs, with correlations calculated for each pair. To evaluate a filtering strategy, we estimate posterior probabilities for the correctness of probesets accepted by the method. An analyst can set expected utilities that represent the trade-off between the quality and quantity of accepted features. We tested nine published probeset filtering methods and combination strategies. We used two test-beds from cancer studies providing transcriptomic and proteomic data. For reasonable utility settings, the Jetset filtering method was optimal for probeset filtering on both test-beds, even though both assay platforms were different. Further intersection with a second filtering method was indicated on one test-bed but not the other.