Predicting current and future potential distributions of the greater bandicoot rat (Bandicota indica) under climate change conditions

BACKGROUND

Rodent infestation is a global problem. Rodents cause huge harm to agriculture, forestry, and animal husbandry around the world and spread various zoonoses. In this study, we simulated the potentially suitable habitats of Bandicota indica and predicted the impact of future climate change on its distribution under different socio-economic pathway scenarios of CMIP6 using a parameter-optimized maximum entropy (MaxEnt) model.

RESULTS

The average area under the receiver operating characteristic curve (AUC) value (0.958 ± 0.006) after ten repetitions proved the high accuracy of the MaxEnt model. Model results show that the annual mean temperature (≥ 15.93 °C), isothermality (28.52-80.49%), annual precipitation (780.13-3863.13 mm), precipitation of the warmest quarter (≥ 204.37 mm), and nighttime light (≥ 3.38) were important limiting environmental variables for the distribution of B. indica. Under current climate conditions, the projected potential suitable habitats for B. indica were mainly in India, China, Myanmar, Thailand, and Vietnam, which cover a total area of 301.70 × 104  km2 . The potentially suitable areas of B. indica in the world will expand under different future climate change scenarios by 1.61-17.65%.

CONCLUSIONS

These results validate the potential influence of climate change on the distribution of B. indica and aid in understanding the linkages between B. indica niches and the relevant environment, thereby identifying urgent management areas where interventions may be necessary to develop feasible early warning and prevention strategies to protect against this rodent's spread. © 2023 Society of Chemical Industry.

Quantitative Trait Locus Mapping for Resistance Against Pyrenopeziza brassicae Derived From a Brassica napus Secondary Gene Pool

Use of host resistance is the most economical and environmentally safe way to control light leaf spot disease of oilseed rape (Brassica napus). The causal organism of light leaf spot, Pyrenopeziza brassicae, is one of the most economically damaging pathogens of oilseed rape in the United Kingdom and it is considered to have a high potential to evolve due to its mixed reproduction system and airborne ascospores. This necessitates diverse sources of host resistance, which are inadequate at present to minimize yield losses caused by this disease. To address this, we screened a doubled haploid (DH) population of oilseed rape, derived from a secondary gene pool (ancestral genomes) of B. napus for the introgression of resistance against P. brassicae. DH lines were phenotyped using controlled-environment and glasshouse experiments with P. brassicae populations obtained from three different geographic locations in the United Kingdom. Selected DH lines with different levels of resistance were further studied in a controlled-environment experiment using both visual (scanning electron microscope - SEM) and molecular (quantitative PCR) assessment methods to understand the mode/s of host resistance. There was a clear phenotypic variation for resistance against P. brassicae in this DH population. Quantitative trait locus (QTL) analysis identified four QTLs with moderate to large effects, which were located on linkage groups C1, C6, and C9. Of these, the QTL on the linkage group C1 appeared to have a major effect on limiting P. brassicae asexual sporulation. Study of the sub-cuticular growth phase of P. brassicae using qPCR and SEM showed that the pathogen was able to infect and colonise both resistant and susceptible Q DH lines and control B. napus cultivars. However, the rate of increase of pathogen biomass was significantly smaller in resistant lines, suggesting that the resistance segregating in this DH population limits colonisation/sporulation by the pathogen rather than eliminating the pathogen. Resistance QTLs identified in this study provide a useful resource for breeding cultivar resistance for effective control of light leaf spot and form a starting point for functional identification of the genes controlling resistance against P. brassicae that can contribute to our knowledge on mechanisms of partial resistance of crops against pathogens.

Marine Macroalgae, a Source of Natural Inhibitors of Fungal Phytopathogens

Fungal phytopathogens are a growing problem all over the world; their propagation causes significant crop losses, affecting the quality of fruits and vegetables, diminishing the availability of food, leading to the loss of billions of euros every year. To control fungal diseases, the use of synthetic chemical fungicides is widely applied; these substances are, however, environmentally damaging. Marine algae, one of the richest marine sources of compounds possessing a wide range of bioactivities, present an eco-friendly alternative in the search for diverse compounds with industrial applications. The synthesis of such bioactive compounds has been recognized as part of microalgal responsiveness to stress conditions, resulting in the production of polyphenols, polysaccharides, lipophilic compounds, and terpenoids, including halogenated compounds, already described as antimicrobial agents. Furthermore, many studies, in vitro or in planta, have demonstrated the inhibitory activity of these compounds with respect to fungal phytopathogens. This review aims to gather the maximum of information addressing macroalgae extracts with potential inhibition against fungal phytopathogens, including the best inhibitory results, while presenting some already reported mechanisms of action.

Global Plant Virus Disease Pandemics and Epidemics

The world's staple food crops, and other food crops that optimize human nutrition, suffer from global virus disease pandemics and epidemics that greatly diminish their yields and/or produce quality. This situation is becoming increasingly serious because of the human population's growing food requirements and increasing difficulties in managing virus diseases effectively arising from global warming. This review provides historical and recent information about virus disease pandemics and major epidemics that originated within different world regions, spread to other continents, and now have very wide distributions. Because they threaten food security, all are cause for considerable concern for humanity. The pandemic disease examples described are six (maize lethal necrosis, rice tungro, sweet potato virus, banana bunchy top, citrus tristeza, plum pox). The major epidemic disease examples described are seven (wheat yellow dwarf, wheat streak mosaic, potato tuber necrotic ringspot, faba bean necrotic yellows, pepino mosaic, tomato brown rugose fruit, and cucumber green mottle mosaic). Most examples involve long-distance virus dispersal, albeit inadvertent, by international trade in seed or planting material. With every example, the factors responsible for its development, geographical distribution and global importance are explained. Finally, an overall explanation is given of how to manage global virus disease pandemics and epidemics effectively.

Biotic Yield Losses in the Southern Amazon, Brazil: Making Use of Smartphone-Assisted Plant Disease Diagnosis Data

Pathogens and animal pests (P&A) are a major threat to global food security as they directly affect the quantity and quality of food. The Southern Amazon, Brazil's largest domestic region for soybean, maize and cotton production, is particularly vulnerable to the outbreak of P&A due to its (sub)tropical climate and intensive farming systems. However, little is known about the spatial distribution of P&A and the related yield losses. Machine learning approaches for the automated recognition of plant diseases can help to overcome this research gap. The main objectives of this study are to (1) evaluate the performance of Convolutional Neural Networks (ConvNets) in classifying P&A, (2) map the spatial distribution of P&A in the Southern Amazon, and (3) quantify perceived yield and economic losses for the main soybean and maize P&A. The objectives were addressed by making use of data collected with the smartphone application Plantix. The core of the app's functioning is the automated recognition of plant diseases via ConvNets. Data on expected yield losses were gathered through a short survey included in an "expert" version of the application, which was distributed among agronomists. Between 2016 and 2020, Plantix users collected approximately 78,000 georeferenced P&A images in the Southern Amazon. The study results indicate a high performance of the trained ConvNets in classifying 420 different crop-disease combinations. Spatial distribution maps and expert-based yield loss estimates indicate that maize rust, bacterial stalk rot and the fall armyworm are among the most severe maize P&A, whereas soybean is mainly affected by P&A like anthracnose, downy mildew, frogeye leaf spot, stink bugs and brown spot. Perceived soybean and maize yield losses amount to 12 and 16%, respectively, resulting in annual yield losses of approximately 3.75 million tonnes for each crop and economic losses of US$2 billion for both crops together. The high level of accuracy of the trained ConvNets, when paired with widespread use from following a citizen-science approach, results in a data source that will shed new light on yield loss estimates, e.g., for the analysis of yield gaps and the development of measures to minimise them.

Disease Pandemics and Major Epidemics Arising from New Encounters between Indigenous Viruses and Introduced Crops

Virus disease pandemics and epidemics that occur in the world’s staple food crops pose a major threat to global food security, especially in developing countries with tropical or subtropical climates. Moreover, this threat is escalating rapidly due to increasing difficulties in controlling virus diseases as climate change accelerates and the need to feed the burgeoning global population escalates. One of the main causes of these pandemics and epidemics is the introduction to a new continent of food crops domesticated elsewhere, and their subsequent invasion by damaging virus diseases they never encountered before. This review focusses on providing historical and up-to-date information about pandemics and major epidemics initiated by spillover of indigenous viruses from infected alternative hosts into introduced crops. This spillover requires new encounters at the managed and natural vegetation interface. The principal virus disease pandemic examples described are two (cassava mosaic, cassava brown streak) that threaten food security in sub-Saharan Africa (SSA), and one (tomato yellow leaf curl) doing so globally. A further example describes a virus disease pandemic threatening a major plantation crop producing a vital food export for West Africa (cacao swollen shoot). Also described are two examples of major virus disease epidemics that threaten SSA’s food security (rice yellow mottle, groundnut rosette). In addition, brief accounts are provided of two major maize virus disease epidemics (maize streak in SSA, maize rough dwarf in Mediterranean and Middle Eastern regions), a major rice disease epidemic (rice hoja blanca in the Americas), and damaging tomato tospovirus and begomovirus disease epidemics of tomato that impair food security in different world regions. For each pandemic or major epidemic, the factors involved in driving its initial emergence, and its subsequent increase in importance and geographical distribution, are explained. Finally, clarification is provided over what needs to be done globally to achieve effective management of severe virus disease pandemics and epidemics initiated by spillover events.

Modeling Yield Losses and Fungicide Profitability for Managing Fusarium Head Blight in Brazilian Spring Wheat

Fusarium head blight (FHB) and wheat yield data were gathered from fungicide trials to explore their relationship. Thirty-seven studies over 9 years and 11 locations met the criteria for inclusion in the analysis: FHB index in the untreated check ≥ 5% and the range of index in a trial ≥ 4 percentage points. These studies were grouped into two baseline yields, low (Yl ≤ 3,631 kg ha^-1) or high (Yh > 3,631 kg ha^-1), defined based on the median of maximum yields across trials. Attainable (disease-free) yields and FHB index were predicted using a wheat crop and a disease model, respectively, in 280 simulated trials (10 planting dates in a 28-year period, 1980 to 2007) for the Passo Fundo location. The damage coefficient was then used to calculate FHB-induced yield loss (penalizing attainable yield) for each experiment. Losses were compared between periods defined as before and after FHB resurge during the early 1990s. Disease reduction from the use of one or two sprays of a triazole fungicide (tebuconazole) was also simulated, based on previous meta-analytic estimates, and the response in yield was used in a profitability analysis. Population-average intercepts but not the slopes differed significantly between Yl (2,883.6 kg ha^-1) and Yh (4,419.5 kg ha^-1) baseline yields and the damage coefficients were 1.60%^-1 and 1.05%^-1, respectively. The magnitudes and trends of simulated yield losses were in general agreement with literature reports. The risk of not offsetting the costs of one or two fungicide sprays was generally higher (>0.75) prior to FHB resurgence but fungicide profitability tended to increase in recent years, depending on the year. Our simulations allowed us to reproduce trends in historical losses, and may be further adjusted to test the effect and profitability of different control measures (host resistance, other fungicides, etc.) on quality parameters such as test weight and mycotoxin contamination, should the information become available.

Impact of Powdery Mildew and Leaf Rust on Milling and Baking Quality of Soft Red Winter Wheat

Changes in milling and baking quality (especially flour yield) of soft red winter wheat can have a large economic impact on flour mills. To determine the relationship between early-season powdery mildew and late-season leaf rust on flour yield, flour protein, alkaline water retention capacity, and kernel texture (softness equivalent), a study was conducted over 2 years at Kinston and Plymouth, NC. Different levels of powdery mildew and leaf rust developed on three winter wheat cultivars that varied in levels of disease resistance, the presence of seed treatment, and the presence and timing of foliar fungicide application. In Kinston and Plymouth in 1989-90, where leaf rust occurred early, the softness equivalent score was lower in wheat grown from seed treated with triadimenol. The following year, when the leaf rust epidemic increased later, foliar fungicide application reduced disease and resulted in lower softness equivalent scores in both Plymouth and Kinston for cv. Saluda and in Kinston for cv. Coker 983. A regression model was developed to describe the relationship between the log of the area under the disease progress curves and adjusted flour yield (AFY). The AFY of Saluda was reduced in the presence of powdery mildew such that %AFY = 103.96 - 0.92 (log AUMPC).

Influence of Population Densities of Heterodera schachtii on Sugar Beets Grown in Microplots

High initial population densities of Heterodera schachtii larvae (36 and 108/gm of soil) greatly retarded the seedling emergence of sugar beet 'Monogerm CSF 1971' in Vineland fine sandy loam. In comparison with controls, initial population densities (P(i)'s) of 1.7, 3.0, 6.2, and 14.4 larvae/gm of soil respectively reduced the weight of storage roots by 38, 56, 64, and 92%. Weights of tops also decreased with increases in P(i); weights of tap and small feeder roots tended to be higher at all P(i)'s except the highest. Sucrose percentage was not affected by any initial nematode density. The populations were lower at midseason than at seeding, and at harvest had increased greatly, with respective populations of 339, 402, 222, and 140 larvae/gm of soil. At harvest, cysts/gm of soil and cysts/gm of root were respectively 4.4 and 72, 6.1 and 99, 6.1 and 191, and 5.8 and 140. The maximum rate of multiplication was 150-200. and maximum density was 400 larvae/gm of soil. The high pathogenicity and multiplication rate of the nematode was attributed to optimum temperature conditions and soil type.

Effects of population densities of Meloidogyne hapla on growth and yield of tomato

Growth and yield of 'Veebrite' tomato were studied in 20-cm (i.d.) clay-tile microplots containing initially 260, 1,840, 6,120, or 27,950 Meloidogyne hapla larvae/kg of soil. Low nematode numbers stimulated, and the highest nematode population suppressed, vegetative plant growth. More tomatoes, with a higher total weight, were harvested from plants infested with 260 and 1,840 nematode larvae at planting than from those with initial densities of 6,120 and 27,950 larvae. At the two highest densities, the cumulative fruit production (weight) was suppressed by 10% and 40%, respectively. The increase in growth and yield at the lower densities appeared to be due to an increase in the size of the root systent. However, at the higher densities, yield was no longer directly related to root weight. The reproduction factor of M. hapla was negatively correlated with initial density; for the lowest and highest initial densities, it was 96X and 7X at midseason, and 354X and 3X at harvest, respectively. The equilibrium density was 63,000 larvae/kg of soil; initial densities larger than 2,000 larvae/kg of soil may require control.