Biology subjects

Martinetti, D.

Publications and source records attributed to Martinetti, D..

7 recordsLinked to original sources

bioRxiv2024

Optimizing fungicide deployment in a connected crop landscape while balancing epidemic control and environmental sustainability

Bioaggressors cause significant losses in crop production, and the efficacy of control methods, primarily based on chemical compounds, comes with considerable environmental and health costs. Plant protection practices implemented locally undermine the mobility of bioaggressors, which can spread between fields, connecting different crop populations. As a consequence, the yield in a given field depends also on the management of connected fields. In this study, we evaluate the efficiency of different fungicide deployment strategies across a national-scale agriculture landscape, balancing the conflicting objectives of maximizing crop production and reducing fungicide use. We use a climate-driven metapopulation model describing the dynamics of the peach (Prunus persica)-brown rot (caused by Monilinia spp.) pathosystem in continental France. Fungicide deployment strategies are based on indices or algorithms, considering network topology, epidemic risk, territory, and stochastic sampling, which prioritize sites to be treated first. Eventually, we focus solely on the objective of maximizing harvest revenue, assuming that untreated fruit can be marketed at higher prices. The optimal strategy depends on the treatment allocation threshold: if up 20% of the area is treated, epidemic risk provides the most effective prioritization. If more than 40% of the area can be treated, a combination of random sampling and risk-based prioritization proves optimal. When considering a single objective, we find that the higher the consumers willingness to pay for untreated fruit, the larger the proportion of untreated sites becomes. Fungicide use could be avoided if untreated fruit were sold at 2.9 times the price of treated fruit.

ecology↗

bioRxiv2024

Exploring the role of cultivar, year and plot age in the incidence of grapevine trunk diseases: insights from 20 years of regional surveys in France

Grapevine trunk diseases cause yield losses and vine mortality in vineyards worldwide. However, there have been few quantitative studies evaluating grapevine dieback on a large spatial and temporal scale. Here, we consolidated and standardized databases from the 13 main wine regions of France, compiling records of leaf symptoms associated with esca and Eutypa dieback from 2082 plots and 36 cultivars over a 20-year period. This large dataset was used (a) for quantitative analysis of the prevalence (number of plots with at least one symptomatic plant) and incidence (percentage of symptomatic plants) of esca and Eutypa dieback; and (b) to decipher the effects of cultivar, year and plot age on both the prevalence and incidence of esca leaf symptoms by temporal Bayesian modelling. Esca was present on a mean of 74 {+/-} 2% plots annually, with an incidence of 3.1 {+/-} 0.1%. Eutypa dieback occurred in 41 {+/-} 3% of the plots, with an incidence of 1.4 {+/-} 0.1%. Our modelling approach revealed that the cultivar had a significant impact on the prevalence of esca, but not on its incidence when prevalence is greater than zero. Esca prevalence remained stable, whereas esca incidence was higher than the mean value in six of the years after 2012. We also found a significant non-linear effect of plot age, with 10- to 30-year-old plots significantly more susceptible, depending on the cultivar. This study clearly illustrates the importance of considering extensive and continuous monitoring to improve our understanding of the impact and evolution of crop diseases.

plant biology↗

bioRxiv2023

A hitchhiker's guide to Europe: mapping human-mediated dispersal of the invasive Japanese beetle

Early detection of hitchhiking pests requires the identification of strategic entry points via transport. We propose a framework for achieving this in Europe using the Japanese beetle (Popillia japonica) as a case study. Human-mediated dispersal has been responsible for its introduction into several continents over the last century, including Europe where it is listed as a priority pest. Furthermore, interceptions far from the infested area confirm the risk of unintentional transport within continental Europe. Here, we analyse how three modes of transport - air, rail and road - connect the infested area to the rest of Europe. We ranked all European regions from most to least reachable from the infested area. We identified border regions and distant major cities that are readily reachable and observed differences between modes. We propose a composite reachability index combining the three modes, which provides a valuable tool for designing a continental surveillance strategy and prioritising highly reachable regions, as demonstrated by recent interceptions. Significance statementSpecies can be moved long distances by unintentional human transport. Such events can lead to their introduction into non-native areas where they can cause biological invasions. Using the case study of the Japanese beetle, a hitchhiker invasive insect, we propose a framework for identifying entry points for human-transported pests within Europe. We consider how the European infested area is connected to the rest of the continent by three modes of transport: air, rail and road. We propose a methodology that considers the three modes to identify potential entry points. This framework could assist authorities in designing surveillance strategies to achieve early detection of pests in Europe.

ecology↗

bioRxiv2023

A metapopulation framework integrating landscape heterogeneity to model an airborne plant pathogen: the case of brown rot of peach in France

Plant disease dynamics are driven by the concurrent interplay of host susceptibility, pathogen presence, and environmental conditions. While host susceptibility and local environmental conditions can readily be characterised, the transmission of an airborne pathogen depends on the biotic and abiotic conditions of the surrounding environment. Here, we propose an original metapopulation framework integrating landscape heterogeneity, in terms of climate and host density, where local populations of plant hosts are connected via air-masses which allow pathogen dispersal. We explicitly account for climatic drivers affecting pathogen release and survival while modelling aerial dispersal using Lagrangian simulations, as well as host phenology and infection. We calibrate the model parameters according to the literature and using Approximate Bayesian Computation against observations of brown rot incidence in French peach orchards from 2001-2020 across an area of 50,000 km2. We used the model to produce maps of risk, distinguishing site dangerousness (risk of causing secondary infection in other sites) and vulnerability (risk of becoming infected) across the our study area. We find that most dangerous and vulnerable sites are located along the Rhone Valley, due to the concurrence of high density of peach cultivation, a suitable climate and persistent airborne connections. Our work represents a first step to integrate metapopulation theory, epidemiology and air-mass movements to inform plant protection strategies, and could be adapted to optimize crop protection under future climate projections.

ecology↗

bioRxiv2022

A new chapter of the Japanese beetle invasion saga: predicting suitability from long-infested areas to inform surveillance strategies in Europe

The Japanese beetle (Popillia japonica) is a polyphagous pest that spreads rapidly and is estimated to cost more than 460 M$/year in damage and control in the USA alone. This study provides risk maps to inform surveillance strategies in Continental Europe, following the beetles introduction and successive spread in the last decade. We developed a species distribution model using a machine-learning algorithm, considering factors relevant to the beetles biology, climate, land use and human-related variables. This analysis was performed using presence-only data from native and invaded ranges (Japan, North America, Azores archipelago - Portugal). We gathered more than 30 000 presence data from citizen science platforms and standardized surveys, and generated pseudo-absences using the target-group method. We used the environmental structure of data to randomly sample pseudo-absences, and evaluate model performance via a block cross-validation strategy. Our results show that climate, in particular seasonal trends, and human-related variables, are major drivers of the Japanese beetle distribution at the global scale. Risk maps show that Central Europe can be considered as suitable, whereas Southern and Northern European countries are at lower risk. The region currently occupied is among the most suitable according to our predictions, and represents less than 1% of the highest suitable area in Europe. A major cluster of high suitability areas is located near the currently infested zone, whereas others are scattered across the continent. This highlights the importance of designing surveillance strategies considering both active insect dispersal and the possibility of hitchhiking to reach distant areas.

ecology↗

bioRxiv2022

Benefits and costs of a global cooperative surveillance strategy to control trans-boundary crop pathogens

Trans-boundary diseases are extremely complex to control and can cause global socioeconomic damages. In the context of crop protection, surveillance strategies are usually designed according to administrative boundaries. In this study, we investigate to which extent this geographical scale of surveillance is suitable for long-distance dispersed pathogens. We lever on a global epidemic network, presented in a previous work, describing worldwide potential transport of P. graminis, the causal agent of stem rust of wheat. We conceive two surveillance strategies: "Country-based" and "Cooperative" and we compare their performances, in terms of minimizing the number of sentinels deployed, to achieve given surveillance targets, both at the global and country level. As expected, we find that a "Cooperative" strategy is more efficient at the global scale, and this is particularly true for intermediate targets of surveillance. However, costs and benefits of adopting a "Cooperative" strategy are not equally distributed among countries. Medium size countries in central Europe and Asia are those that would benefit most from a cooperative strategy. On the other hand, Greece and Finland, having a small wheat production but placed in important Puccinia pathways, are those that should deploy, in the global interest, more sentinels than they would place in the national interest. Among the major wheat producers, China is the only country that would have a cost from a cooperative strategy, while India, Russia, United States, France and Ukraine would have the most benefits. It follows that the acknowledgement of these discrepancies could help to achieve general stakeholder support for a global international cooperative surveillance system.

plant biology↗

bioRxiv2021

Surveillance of airborne plant disease dissemination at continental scale using air mass trajectory analysis and network theory

Sustainable management of plant disease outbreaks in agriculture is one of the main challenges of the next years to restore economic and environmental viability of farming practices. Improving early-detection capabilities and disease surveillance is increasingly seen as an obligate step to design appropriate and effective prophylactic measures. In this context, plant diseases caused by wind-dispersed pathogens represent an interesting case of study, since they are particularly complex and hard to observe directly, especially if compared to other dissemination means, and demand for a multidisciplinary approach to be dealt with. Wind dispersal could imply a geographic differentiation in pathogens spreading potential, due to the emerging of local meteorological features. In this work we analyze the spatio-temporal patterns of wind connectivity in Europe and the Mediterranean basin in order to identify possible pathways of Puccinia graminis spores, the causal agent of stem rust of wheat. By running backwards Lagrangian simulations merging a biological layer coupled with a pathogen viability model, we investigate possible long-distance connections between regions in the study area across different seasons. We characterized these regions in terms of network centrality indicators to identify possible spreaders of stem rust of wheat, founding that Central and Western European regions appears to provide highest connectivity for the spread of P. graminis.

plant biology↗