Spodoptera eridania: current and emerging crop threats from another invasive, pesticide-resistant moth

Open Access Article; Published online: 29 Jun 2022Spodoptera eridania (Stoll), a polyphagous lepidopteran pest from the Americas, has recently invaded western and central Africa. Like its congeners, S. eridania has developed pesticide resistance. The rapid global spread and impacts of Spodoptera frugiperda (J.E. Smith) has raised concerns about whether S. eridania is set to do the same. Here we fit a CLIMEX niche model for S. eridania and apply a climate change scenario for 2050 to investigate the sensitivity of the pest threat. We find that S. eridania can potentially expand its range throughout the tropics and into the sub-tropics, threatening a range of important commercial and subsistence crops. An important feature of the pest threat posed by S. eridania is the extent of its ephemeral habitat during warmer months. Modelled climatic changes will mostly expand this species potential range poleward by around 200 km by 2050, indicating a moderate sensitivity. These areas of emerging potential expansion are mostly into subtropical climates, supporting diverse cropping systems, including at risk crops beans, groundnut, potato, soybeans, tomato and sweet potato. The potential distribution of S. eridania in the Amazon basin and the southern boundary of the Sahara Desert appear set to contract substantially due to increasing heat stress. While it may not be as invasive as some of its congeners, nor acquire pesticide resistance as readily, S. eridania does have some of these traits, and the current and emerging pest threat posed by this moth deserves closer attention, especially in relation to intercontinental phytosanitary measures to slow its spread

Combining inferential and deductive approaches to estimate the potential geographical range of the invasive plant pathogen, Phytophthora ramorum

Phytophthora ramorum, an invasive plant pathogen of unknown origin, causes considerable and widespread damage in plant industries and natural ecosystems of the USA and Europe. Estimating the potential geographical range of P. ramorum has been complicated by a lack of biological and geographical data with which to calibrate climatic models. Previous attempts to do so, using either invaded range data or surrogate species approaches, have delivered varying results. A simulation model was developed using CLIMEX to estimate the global climate suitability patterns for establishment of P. ramorum. Growth requirements and stress response parameters were derived from ecophysiological laboratory observations and site-level transmission and disease factors related to climate data in the field. Geographical distribution data from the USA (California and Oregon) and Norway were reserved from model-fitting and used to validate the models. The model suggests that the invasion of P. ramorum in both North America and Europe is still in its infancy and that it is presently occupying a small fraction of its potential range. Phytophthora ramorum appears to be climatically suited to large areas of Africa, Australasia and South America, where it could cause biodiversity and economic losses in plant industries and natural ecosystems with susceptible hosts if introduced

Predicting current and future biological invasions: both native and invaded ranges matter

The classical approach to predicting the geographical extent of species invasions consists of training models in the native range and projecting them in distinct, potentially invasible areas. However, recent studies have demonstrated that this approach could be hampered by a change of the realized climatic niche, allowing invasive species to spread into habitats in the invaded ranges that are climatically distinct from those occupied in the native range. We propose an alternative approach that involves fitting models with pooled data from all ranges. We show that this pooled approach improves prediction of the extent of invasion of spotted knapweed (Centaurea maculosa) in North America on models based solely on the European native range. Furthermore, it performs equally well on models based on the invaded range, while ensuring the inclusion of areas with similar climate to the European niche, where the species is likely to spread further. We then compare projections from these models for 2080 under a severe climate warming scenario. Projections from the pooled models show fewer areas of intermediate climatic suitability than projections from the native or invaded range models, suggesting a better consensus among modelling techniques and reduced uncertainty

Tools for controlling a major global food and feed safety risk: Non-biological post-harvest procedures to decontaminate mycotoxins in food and feeds

Mycotoxin contamination of foods and animal feeds is a worldwide problem for human and animal health. Controlling mycotoxin contamination has drawn the attention of scientists and other food and feed stakeholders all over the world. Despite best efforts targeting field and storage preventive measures, environmental conditions can still lead to mycotoxin contamination. This raises a need for developing decontamination methods to inactivate or remove the toxins from contaminated products. At present, decontamination methods applied include an array of both biological and nonbiological methods. The targeted use of nonbiological methods spans from the latter half of last century, when ammoniation and ozonation were first used to inactivate mycotoxins in animal feeds, to the novel techniques being developed today such as photosensitization. Effectiveness and drawbacks of different nonbiological methods have been reported in the literature, and this review examines the utility of these methods in addressing food safety. Particular consideration is given to the application of such methods in the developing world, where mycotoxin contamination is a serious food safety issue in staple crops such as maize and rice

Major Sex Pheromone Components of the Australian Gum Leaf Skeletonizer Uraba lugens : (10 E ,12 Z )-Hexadecadien-1-yl Acetate and (10 E ,12 Z )-Hexadecadien-1-ol

Two sex pheromone components of the gum leaf skeletonizer, Uraba lugens (Lepidoptera: Nolidae), recently established in New Zealand, were identified. Gas chromatography (GC) electroantennographic detection analyses of female pheromone gland extracts gave three compounds that consistently elicited antennal responses. Chemical analyses, using GC and GC–mass spectrometry, in conjunction with 4-methyl-1,2,4-triazoline-3,5-dione and dimethyldisulfide derivatizations, identified these compounds as (10E,12Z)-hexadecadien-1-yl acetate (E10,Z12–16:Ac), (10E,12Z)-hexadecadien-1-ol (E10,Z12–16:OH), and (Z)-11-hexadecen-1-yl acetate (Z11–16:Ac). A trapping trial in Queensland, Australia, in 2002, indicated that a blend of the two major components E10,Z12–16:Ac and E10,Z12–16:OH could attract gum leaf skeletonizer males. In the same trial, E10,Z12–16:Ac alone trapped large numbers of an unidentified nolid, Nola spp. Further trials in Auckland, New Zealand established that these two components were sufficient and necessary for trap catch of males; adding minor gland components, (10E,12E)-hexadecadien-1-yl acetate (E10,E12–16:Ac), Z11–16:Ac, or octadecan-1-ol (18:OH), to the two-component lure did not result in increased trap catches. Behavioral observations and gland analyses of the Auckland population revealed that female moths begin calling soon after emergence, with peak calling and pheromone production occurring 7 hr into the scotophase. Analysis of gland extract at two-hourly intervals during the first activity period showed that the ratio of E10,Z12–16:Ac to E10,Z12–16:OH (mean of 86: 14, respectively) and pheromone titer were fairly constant. No qualitative or quantitative differences in pheromone components were detected between gland extracts from Tasmanian univoltine and Auckland bivoltine populations of U. lugens

Population dynamics and management of diamondback moth (Plutella xylostella) in China: the relative contributions of climate, natural enemies and cropping patterns

Diamondback moth or DBM is the major pest of Brassica vegetable production worldwide. Control has relied on insecticides, and DBM resistance to these compounds has evolved rapidly. We review and summarize data on DBM population dynamics across a large latitudinal gradient from southwest to northeast China: DBM is, on average, more common in southern locations than in northern locations. The species' phenology is consistent: in southern and central locations there is a decline during hot summer months, while in the north, the species can only exist in the summer following migrations from the south. A cohort-based discrete-time model, driven by daily maximum and minimum temperatures and rainfall, which was built using the DYMEX modelling software, captures the age-structured population dynamics of DBM at representative locations, with year round cropping and threshold-based insecticide applications. The scale of the simulated pest problem varies with cropping practices. Local production breaks and strict post-harvest crop hygiene are associated with lower DBM populations. Biological control appears to improve the management of DBM. Of the management strategies explored, non-threshold based applications of insecticides with reduced spray efficacy (due to poor application or resistance) appear the least effective. The model simulates the phenology and abundance patterns in the population dynamics across the climatic gradient in China reasonably well. With planned improvements, and backed by a system of field sampling and weather inputs, it should serve well as a platform for a local pest forecast system, spanning the range of DBM in China, and perhaps elsewhere

Modelling horses for novel climate courses: Insights from projecting potential distributions of native and alien Australian acacias with correlative and mechanistic models

Aim Investigate the relative abilities of different bioclimatic models and data sets to project species ranges in novel environments utilizing the natural experiment in biogeography provided by Australian Acacia species. Location Australia, South Africa. Methods We built bioclimatic models for Acacia cyclops and Acacia pycnantha using two discriminatory correlative models (MaxEnt and Boosted Regression Trees) and a mechanistic niche model (CLIMEX). We fitted models using two training data sets: native-range data only ('restricted') and all available global data excluding South Africa ('full'). We compared the ability of these techniques to project suitable climate for independent records of the species in South Africa. In addition, we assessed the global potential distributions of the species to projected climate change. Results All model projections assessed against their training data, the South African data and globally were statistically significant. In South Africa and globally, the additional information contained in the full data set generally improved model sensitivity, but at the expense of increased modelled prevalence, particularly in extrapolation areas for the correlative models. All models projected some climatically suitable areas in South Africa not currently occupied by the species. At the global scale, widespread and biologically unrealistic projections by the correlative models were explained by open-ended response curves, a problem which was not always addressed by broader background climate space or by the extra information in the full data set. In contrast, the global projections for CLIMEX were more conservative. Projections into 2070 indicated a polewards shift in climate suitability and a decrease in model interpolation area. Main conclusions Our results highlight the importance of carefully interpreting model projections in novel climates, particularly for correlative models. Much work is required to ensure bioclimatic models performed in a robust and ecologically plausible manner in novel climates. We explore reasons for variations between models and suggest methods and techniques for future improvements. © 2011 Blackwell Publishing Ltd.Articl

Modelling horses for novel climate courses: insights from projecting potential distributions of native and alien Australian acacias with correlative and mechanistic models

Aim Investigate the relative abilities of different bioclimatic models and data sets to project species ranges in novel environments utilizing the natural experiment in biogeography provided by Australian Acacia species. Location Australia, South Africa. Methods We built bioclimatic models for Acacia cyclops and Acacia pycnantha using two discriminatory correlative models (MaxEnt and Boosted Regression Trees) and a mechanistic niche model (CLIMEX). We fitted models using two training data sets: native-range data only (‘restricted’) and all available global data excluding South Africa (‘full’). We compared the ability of these techniques to project suitable climate for independent records of the species in South Africa. In addition, we assessed the global potential distributions of the species to projected climate change. Results All model projections assessed against their training data, the South African data and globally were statistically significant. In South Africa and globally, the additional information contained in the full data set generally improved model sensitivity, but at the expense of increased modelled prevalence, particularly in extrapolation areas for the correlative models. All models projected some climatically suitable areas in South Africa not currently occupied by the species. At the global scale, widespread and biologically unrealistic projections by the correlative models were explained by open-ended response curves, a problem which was not always addressed by broader background climate space or by the extra information in the full data set. In contrast, the global projections for CLIMEX were more conservative. Projections into 2070 indicated a polewards shift in climate suitability and a decrease in model interpolation area. Main conclusions Our results highlight the importance of carefully interpreting model projections in novel climates, particularly for correlative models. Much work is required to ensure bioclimatic models performed in a robust and ecologically plausible manner in novel climates. We explore reasons for variations between models and suggest methods and techniques for future improvements.Centre of Excellence for Invasion Biolog