Delaying selection for fungicide insensitivity by mixing fungicides at a low and high risk of resistance development: a modeling analysis

This study used mathematical modeling to predict whether mixtures of a high-resistance-risk and a low-risk fungicide delay selection for resistance against the high-risk fungicide. We used the winter wheat and Mycosphaerella graminicola host–pathogen system as an example, with a quinone outside inhibitor fungicide as the high-risk and chlorothalonil as the low-risk fungicide. The usefulness of the mixing strategy was measured as the “effective life”: the number of seasons that the disease-induced reduction of the integral of canopy green area index during the yield forming period could be kept &lt;5%. We determined effective lives for strategies in which the dose rate (i) was constant for both the low-risk and high-risk fungicides, (ii) was constant for the low-risk fungicide but could increase for the high-risk fungicide, and (iii) was adjusted for both fungicides but their ratio in the mixture was fixed. The effective life was highest when applying the full label-recommended dose of the low-risk fungicide and adjusting the dose of the high-risk fungicide each season to the level required to maintain effective control. This strategy resulted in a predicted effective life of ≤12 years compared with 3 to 4 years when using the high risk fungicide alone. </jats:p

Derivation and testing of a model to predict selection for fungicide resistance

A mathematical model was derived to predict selection for fungicide resistance in foliar pathogens of cereal crops. The model was tested against independent data from four field experiments quantifying selection for the G143A mutation conferring resistance to a quinone outside inhibitor (QoI) fungicide in powdery mildew (Blumeria graminis f.sp. hordei) on spring barley (Hordeum vulgare). Fungicide treatments with azoxystrobin differed in the total applied dose and spray number. For each treatment, we calculated the observed selection ratio as the ratio of the frequency of the resistant strain after the last and before the first spray. The model accurately predicted the variation in observed selection ratios with total applied fungicide dose and number of sprays for three of the four experiments. Underprediction of selection ratios in one experiment was attributed to the particularly late epidemic onset in that experiment. When the equation representing epidemic development was modified to account for the late epidemic, predicted and observed selection ratios at that site were in close agreement. On a scatter plot of observed selection ratios on predicted selection ratios, for all four experiments, the 1:1 line explained 89-92% of the variance in the mean of observed selection ratios. To our knowledge, this is the first fungicide resistance model for plant pathogens to be rigorously tested against field data. The model can be used with some degree of confidence, to identify anti-resistance treatment strategies which are likely to be effective and would justify the resources required for experimental testing

Minimalistic control of biped walking in rough terrain

Toward our comprehensive understanding of legged locomotion in animals and machines, the compass gait model has been intensively studied for a systematic investigation of complex biped locomotion dynamics. While most of the previous studies focused only on the locomotion on flat surfaces, in this article, we tackle with the problem of bipedal locomotion in rough terrains by using a minimalistic control architecture for the compass gait walking model. This controller utilizes an open-loop sinusoidal oscillation of hip motor, which induces basic walking stability without sensory feedback. A set of simulation analyses show that the underlying mechanism lies in the “phase locking” mechanism that compensates phase delays between mechanical dynamics and the open-loop motor oscillation resulting in a relatively large basin of attraction in dynamic bipedal walking. By exploiting this mechanism, we also explain how the basin of attraction can be controlled by manipulating the parameters of oscillator not only on a flat terrain but also in various inclined slopes. Based on the simulation analysis, the proposed controller is implemented in a real-world robotic platform to confirm the plausibility of the approach. In addition, by using these basic principles of self-stability and gait variability, we demonstrate how the proposed controller can be extended with a simple sensory feedback such that the robot is able to control gait patterns autonomously for traversing a rough terrain.National Science Foundation (U.S.) (grant 0746194)Swiss National Science Foundation (grant PBZH2-114461)Swiss National Science Foundation (grant PP00P2_123387/1

Spatially Explicit Analysis of Metal Transfer to Biota: Influence of Soil Contamination and Landscape

Concepts and developments for a new field in ecotoxicology, referred to as “landscape ecotoxicology,” were proposed in the 1990s; however, to date, few studies have been developed in this emergent field. In fact, there is a strong interest in developing this area, both for renewing the concepts and tools used in ecotoxicology as well as for responding to practical issues, such as risk assessment. The aim of this study was to investigate the spatial heterogeneity of metal bioaccumulation in animals in order to identify the role of spatially explicit factors, such as landscape as well as total and extractable metal concentrations in soils. Over a smelter-impacted area, we studied the accumulation of trace metals (TMs: Cd, Pb and Zn) in invertebrates (the grove snail Cepaea sp and the glass snail Oxychilus draparnaudi) and vertebrates (the bank vole Myodes glareolus and the greater white-toothed shrew Crocidura russula). Total and CaCl2-extractable concentrations of TMs were measured in soils from woody patches where the animals were captured. TM concentrations in animals exhibited a high spatial heterogeneity. They increased with soil pollution and were better explained by total rather than CaCl2-extractable TM concentrations, except in Cepaea sp. TM levels in animals and their variations along the pollution gradient were modulated by the landscape, and this influence was species and metal specific. Median soil metal concentrations (predicted by universal kriging) were calculated in buffers of increasing size and were related to bioaccumulation. The spatial scale at which TM concentrations in animals and soils showed the strongest correlations varied between metals, species and landscapes. The potential underlying mechanisms of landscape influence (community functioning, behaviour, etc.) are discussed. Present results highlight the need for the further development of landscape ecotoxicology and multi-scale approaches, which would enhance our understanding of pollutant transfer and effects in ecosystems

Mutagenesis and Functional Studies with Succinate Dehydrogenase Inhibitors in the Wheat Pathogen Mycosphaerella graminicola

A range of novel carboxamide fungicides, inhibitors of the succinate dehydrogenase enzyme (SDH, EC 1.3.5.1) is currently being introduced to the crop protection market. The aim of this study was to explore the impact of structurally distinct carboxamides on target site resistance development and to assess possible impact on fitness

Contribution for the derivation of a soil screening value (SSV) for uranium, using a natural reference soil

In order to regulate the management of contaminated land, many countries have been deriving soil screening values (SSV). However, the ecotoxicological data available for uranium is still insufficient and incapable to generate SSVs for European soils. In this sense, and so as to make up for this shortcoming, a battery of ecotoxicological assays focusing on soil functions and organisms, and a wide range of endpoints was carried out, using a natural soil artificially spiked with uranium. In terrestrial ecotoxicology, it is widely recognized that soils have different properties that can influence the bioavailability and the toxicity of chemicals. In this context, SSVs derived for artificial soils or for other types of natural soils, may lead to unfeasible environmental risk assessment. Hence, the use of natural regional representative soils is of great importance in the derivation of SSVs. A Portuguese natural reference soil PTRS1, from a granitic region, was thereby applied as test substrate. This study allowed the determination of NOEC, LOEC, EC20 and EC50 values for uranium. Dehydrogenase and urease enzymes displayed the lowest values (34.9 and ,134.5 mg U Kg, respectively). Eisenia andrei and Enchytraeus crypticus revealed to be more sensitive to uranium than Folsomia candida. EC50 values of 631.00, 518.65 and 851.64 mg U Kg were recorded for the three species, respectively. Concerning plants, only Lactuca sativa was affected by U at concentrations up to 1000 mg U kg1. The outcomes of the study may in part be constrained by physical and chemical characteristics of soils, hence contributing to the discrepancy between the toxicity data generated in this study and that available in the literature. Following the assessment factor method, a predicted no effect concentration (PNEC) value of 15.5 mg kg21dw was obtained for U. This PNEC value is proposed as a SSV for soils similar to the PTRS1