Shape and rate of movement of the invasion front of Xylella fastidiosa spp. pauca in Puglia

Activity of natural occurring entomopathogenic fungi on nymphal and adult stages of Philaenus spumarius

The spittlebug Philaenus spumarius (Hemiptera: Aphrophoridae) is the predominant vector of Xylella fastidiosa (Xanthomonadales: Xanthomonadaceae) in Apulia, Italy and the rest of Europe. Current control strategies of the insect vector rely on mechanical management of nymphal stages and insecticide application against adult populations. Entomopathogenic fungi (EPF) are biological control agents naturally attacking spittlebugs and may effectively reduce population levels of host species. Different experimental trials in controlled conditions have been performed to i) identify naturally occurring EPF on P, spumarius in Northwestern Italy, and ii) evaluate the potential for biocontrol of the isolated strains on both nymphal and adult stages of the spittlebug. Four EPF species were isolated from dead P. spumarius collected in semi-field conditions: Beauveria bassiana, Conidiobolus coronatus, Fusarium equiseti and Lecanicillium aphanocladii. All the fungal isolates showed entomopathogenic potential against nymphal stages of P. spumarius (≈ 45 % mortality), except for F. equiseti, in preliminary trials. No induced mortality was observed on adult stage. Lecanicillium aphanocladii was the most promising fungus and its pathogenicity against spittlebug nymphs was further tested in different formulations (conidia vs blastospores) and with natural adjuvants. Blastospore formulation was the most effective in killing nymphal instars and reducing the emergence rate of P, spumarius adults, reaching mortality levels (90%) similar to those of the commercial product Naturalis®, while no or adverse effect of natural adjuvants was recorded. The encouraging results of this study pave way for testing EPF isolates against P, spumarius in field conditions and find new environmentally friendly control strategies against insect vectors of X. fastidiosa.

A Decade after the Outbreak of Xylella fastidiosa subsp. pauca in Apulia (Southern Italy): Methodical Literature Analysis of Research Strategies

In 2013, an outbreak of Xylella fastidiosa (Xf) was identified for the first time in Europe, in the extreme south of Italy (Apulia, Salento territory). The locally identified subspecies pauca turned out to be lethal for olive trees, starting an unprecedented phytosanitary emergency for one of the most iconic cultivations of the Mediterranean area. Xf pauca (Xfp) is responsible for a severe disease, the olive quick decline syndrome (OQDS), spreading epidemically and with dramatic impact on the agriculture, the landscape, the tourism and the cultural heritage of this region. The bacterium, transmitted by insects that feed on xylem sap, causes rapid wilting in olive trees due to biofilm formation, which obstructs the plant xylematic vessels. The aim of this review is to perform a thorough analysis that offers a general overview of the published work, from 2013 to December 2023, related to the Xfp outbreak in Apulia. This latter hereto has killed millions of olive trees and left a ghostly landscape with more than 8000 square kilometers of infected territory, that is 40% of the region. The majority of the research efforts made to date to combat Xfp in olive plants are listed in the present review, starting with the early attempts to identify the bacterium, the investigations to pinpoint and possibly control the vector, the assessment of specific diagnostic techniques and the pioneered therapeutic approaches. Interestingly, according to the general set criteria for the preliminary examination of the accessible scientific literature related to the Xfp outbreak on Apulian olive trees, fewer than 300 papers can be found over the last decade. Most of them essentially emphasize the importance of developing diagnostic tools that can identify the disease early, even when infected plants are still asymptomatic, in order to reduce the risk of infection for the surrounding plants. On the other hand, in the published work, the diagnostic focus (57%) overwhelmingly encompasses all other possible investigation goals such as vectors, impacts and possible treatments. Notably, between 2013 and 2023, only 6.3% of the literature reports addressing the topic of Xfp in Apulia were concerned with the application of specific treatments against the bacterium. Among them, those reporting field trials on infected plants, including simple pruning indications, were further limited (6%).

Assessing the driving role of the anthropogenic landscape on the distribution of the Xylella fastidiosa-driven "olive quick decline syndrome" in Apulia (Italy)

The plant pathogen Xylella fastidiosa (Xf) is a significant threat to various economically important tree cash crops. Although previously found only in the Americas, the bacterium responsible for olive quick decline syndrome was detected in Apulia, Italy, in 2013. Since then, it has spread to approximately 54,000 ha of olive trees in the region, causing dramatic concern throughout the Mediterranean basin. As a result, it is crucial to comprehend its distribution and forecast its potential diffusion. The effect of the anthropogenic component of the landscape on the distribution of Xf remains little explored. The present study used an ecological niche model to identify how different land uses, used as proxies of different levels of human pressure across the Apulia territory, impacted the distribution of the Xf-infected olive trees in 2015-2021. Results demonstrated that the anthropogenic component significantly contributed to the epidemic, with the road system representing the main driver of diffusion and natural/seminatural areas hampering Xf spread at the landscape scale. This evidence highlighted the importance of explicitly considering the effects of the anthropogenic landscape when modelling Xf distribution and support the design of landscape-informed monitoring strategies to prevent Xf spread in Apulia and other Mediterranean countries.

Bioecological Traits of Spittlebugs and Their Implications for the Epidemiology and Control of the Xylella fastidiosa Epidemic in Apulia (Southern Italy)

Spatial-temporal dynamics of spittlebug populations, together with transmission biology, are of major importance to outline the disease epidemiology of Xylella fastidiosa subsp. pauca in Apulian olive groves. The spread rate of X. fastidiosa is mainly influenced by (i) the pathogen colonization of the host plant; (ii) the acquisition of the pathogen by the vector from an infected plant, and its inoculation to healthy plants; (iii) the vector population dynamics and abundance at different spatial scales; and (iv) the dispersal of the vector. In this contribution we summarize the recent advances in research on insect vectors' traits-points ii, iii, and iv-focusing on those most relevant to X. fastidiosa epidemic in Apulia. Among the vectors' bioecological traits influencing the X. fastidiosa epidemic in olive trees, we emphasize the following: natural infectivity and transmission efficiency, phenological timing of both nymphal and adult stage, the role of seminatural vegetation as a vector reservoir in the agroecosystem and landscape, and preferential and directional dispersal capabilities. Despite the research on X. fastidiosa vectors carried out in Europe in the last decade, key uncertainties on insect vectors remain, hampering a thorough understanding of pathogen epidemiology and the development of effective and targeted management strategies. Our goal is to provide a structured and contextualized review of knowledge on X. fastidiosa vectors' key traits in the Apulian epidemic, highlighting information gaps and stimulating novel research pathways on X. fastidiosa pathosystems in Europe. [Formula: see text] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Forecasting Pathogen Dynamics with Bayesian Model-Averaging: Application to Xylella fastidiosa

Forecasting invasive-pathogen dynamics is paramount to anticipate eradication and containment strategies. Such predictions can be obtained using a model grounded on partial differential equations (PDE; often exploited to model invasions) and fitted to surveillance data. This framework allows the construction of phenomenological but concise models relying on mechanistic hypotheses and real observations. However, it may lead to models with overly rigid behavior and possible data-model mismatches. Hence, to avoid drawing a forecast grounded on a single PDE-based model that would be prone to errors, we propose to apply Bayesian model averaging (BMA), which allows us to account for both parameter and model uncertainties. Thus, we propose a set of different competing PDE-based models for representing the pathogen dynamics, we use an adaptive multiple importance sampling algorithm (AMIS) to estimate parameters of each competing model from surveillance data in a mechanistic-statistical framework, we evaluate the posterior probabilities of models by comparing different approaches proposed in the literature, and we apply BMA to draw posterior distributions of parameters and a posterior forecast of the pathogen dynamics. This approach is applied to predict the extent of Xylella fastidiosa in South Corsica, France, a phytopathogenic bacterium detected in situ in Europe less than 10 years ago (Italy 2013, France 2015). Separating data into training and validation sets, we show that the BMA forecast outperforms competing forecast approaches.

Satellite monitoring of bio-fertilizer restoration in olive groves affected by Xylella fastidiosa subsp. pauca

Xylella fastidiosa subsp. pauca (Xfp), has attacked the olive trees in Southern Italy with severe impacts on the olive agro-ecosystem. To reduce both the Xfp cell concentration and the disease symptom, a bio-fertilizer restoration technique has been used. Our study applied multi-resolution satellite data to evaluate the effectiveness of such technique at both field and tree scale. For field scale, a time series of High Resolution (HR) Sentinel-2 images, acquired in the months of July and August from 2015 to 2020, was employed. First, four spectral indices from treated and untreated fields were compared. Then, their trends were correlated to meteo-events. For tree-scale, Very High Resolution (VHR) Pléiades images were selected at the closest dates of the Sentinel-2 data to investigate the response to treatments of each different cultivar. All indices from HR and VHR images were higher in treated fields than in those untreated. The analysis of VHR indices revealed that Oliarola Salentina can respond better to treatments than Leccino and Cellina cultivars. All findings were in agreement with in-field PCR results. Hence, HR data could be used to evaluate plant conditions at field level after treatments, while VHR imagery could be used to optimize treatment doses per cultivar.

Landscape and Vegetation Patterns Zoning Is a Methodological Tool for Management Costs Implications Due to Xylella fastidiosa Invasion

Philaenus spumarius (Linnaeus 1758, hereafter Ps) is considered one of the main insect vectors responsible for the spread of an alien biota, Xylella fastidiosa (Wells 1987, hereafter Xf), in the Salento area, Apulia region (Southern Italy). Effective management of this biological invader depends on the continuous surveillance and monitoring of its insect vector. As such, this research elicits the invasion drivers (i.e., landscape and vegetation indicators) that influence the abundance and the dynamics of this vector and, consequently, the spatial spread of this bacterium in this Italian region. For this purpose, a spatial pattern clustering methodological approach is considered. The results reveal that spatial variation and territorial differentiation may differ from zone to zone in the same invaded area, for which effective management and monitoring planning should be addressed. Further, six agro-ecosystems zones have been identified with respect to five indicators: (i) vegetation index, (ii) intensity of cultivation, (iii) cultural diversity, (iv) density of agricultural landscape elements, and (v) altitude. This paper has public implications and contributes to an understanding of how zoning of an infected area, by an alien biota, into homogenous zones may impact its effective management costs. This approach could also be applied in other countries affected or potentially affected by the phenomenon of Xf invasion.

Epidemiologically-based strategies for the detection of emerging plant pathogens

Emerging pests and pathogens of plants are a major threat to natural and managed ecosystems worldwide. Whilst it is well accepted that surveillance activities are key to both the early detection of new incursions and the ability to identify pest-free areas, the performance of these activities must be evaluated to ensure they are fit for purpose. This requires consideration of the number of potential hosts inspected or tested as well as the epidemiology of the pathogen and the detection method used. In the case of plant pathogens, one particular concern is whether the visual inspection of plant hosts for signs of disease is able to detect the presence of these pathogens at low prevalences, given that it takes time for these symptoms to develop. One such pathogen is the ST53 strain of the vector-borne bacterial pathogen Xylella fastidiosa in olive hosts, which was first identified in southern Italy in 2013. Additionally, X. fastidiosa ST53 in olive has a rapid rate of spread, which could also have important implications for surveillance. In the current study, we evaluate how well visual surveillance would be expected to perform for this pathogen and investigate whether molecular testing of either tree hosts or insect vectors offer feasible alternatives. Our results identify the main constraints to each of these strategies and can be used to inform and improve both current and future surveillance activities.

Modeling the Spatial Distribution of Xylella fastidiosa: A Nonstationary Approach with Dispersal Barriers

Spatial species distribution models often assume isotropy and stationarity, implying that spatial dependence is direction-invariant and uniform throughout the study area. However, these assumptions are violated when dispersal barriers are present. Despite this, the issue of nonstationarity has been little explored in the context of plant health. The objective of this study was to evaluate the influence of barriers in the distribution of Xylella fastidiosa in the demarcated area in Alicante, Spain. Occurrence data from 2018 were analyzed through spatial Bayesian hierarchical models. The stationary model, illustrating a scenario without control interventions or geographical features, was compared with three nonstationary models: a model with mountains as physical barriers, and two models with a continuous and discontinuous perimeter barrier representing hypothetical control interventions. In the stationary model, the posterior mean of the spatial range, as the distance where two observations are uncorrelated, was 4,030 m 95% credible interval (2,907 to 5,564). This distance can be used to define the buffer zone in the demarcated area. The predicted probability of X. fastidiosa presence in the area outside the barrier was 0.46 with the stationary model, whereas it was reduced to 0.29 and 0.36 with the continuous and discontinuous barrier models, respectively. Differences between the discontinuous and continuous barrier models showed that breaks, where no control interventions were implemented, resulted in a higher predicted probability of X. fastidiosa presence in the areas with low sampling intensity. These results may help authorities prioritize the areas for surveillance and disease control.[Formula: see text] Copyright © 2022 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.

Estimating the movements of terrestrial animal populations using broad-scale occurrence data

As human and automated sensor networks collect increasingly massive volumes of animal observations, new opportunities have arisen to use these data to infer or track species movements. Sources of broad scale occurrence datasets include crowdsourced databases, such as eBird and iNaturalist, weather surveillance radars, and passive automated sensors including acoustic monitoring units and camera trap networks. Such data resources represent static observations, typically at the species level, at a given location. Nonetheless, by combining multiple observations across many locations and times it is possible to infer spatially continuous population-level movements. Population-level movement characterizes the aggregated movement of individuals comprising a population, such as range contractions, expansions, climate tracking, or migration, that can result from physical, behavioral, or demographic processes. A desire to model population movements from such forms of occurrence data has led to an evolving field that has created new analytical and statistical approaches that can account for spatial and temporal sampling bias in the observations. The insights generated from the growth of population-level movement research can complement the insights from focal tracking studies, and elucidate mechanisms driving changes in population distributions at potentially larger spatial and temporal scales. This review will summarize current broad-scale occurrence datasets, discuss the latest approaches for utilizing them in population-level movement analyses, and highlight studies where such analyses have provided ecological insights. We outline the conceptual approaches and common methodological steps to infer movements from spatially distributed occurrence data that currently exist for terrestrial animals, though similar approaches may be applicable to plants, freshwater, or marine organisms.

Csp1, a Cold Shock Protein Homolog in Xylella fastidiosa Influences Cell Attachment, Pili Formation, and Gene Expression

Bacterial cold shock-domain proteins are conserved nucleic acid binding chaperones that play important roles in stress adaptation and pathogenesis. Csp1 is a temperature-independent cold shock protein homolog in Xylella fastidiosa, a bacterial plant pathogen of grapevine and other economically important crops. Csp1 contributes to stress tolerance and virulence in X. fastidiosa. However, besides general single-stranded nucleic acid binding activity, little is known about the specific function(s) of Csp1. To further investigate the role(s) of Csp1, we compared phenotypic differences and transcriptome profiles between the wild type and a csp1 deletion mutant (Δcsp1). Csp1 contributes to attachment and long-term survival and influences gene expression. We observed reduced cell-to-cell attachment and reduced attachment to surfaces with the Δcsp1 strain compared to those with the wild type. Transmission electron microscopy imaging revealed that Δcsp1 was deficient in pili formation compared to the wild type and complemented strains. The Δcsp1 strain also showed reduced survival after long-term growth in vitro. Long-read nanopore transcriptome sequencing (RNA-Seq) analysis revealed changes in expression of several genes important for attachment and biofilm formation in Δcsp1 compared to that in the wild type. One gene of interest, pilA1, which encodes a type IV pili subunit protein, was upregulated in Δcsp1. Deleting pilA1 in X. fastidiosa strain Stag's Leap increased surface attachment in vitro and reduced virulence in grapevines. X. fastidiosa virulence depends on bacterial attachment to host tissue and movement within and between xylem vessels. Our results show that the impact of Csp1 on virulence may be due to changes in expression of attachment genes. IMPORTANCE Xylella fastidiosa is a major threat to the worldwide agriculture industry. Despite its global importance, many aspects of X. fastidiosa biology and pathogenicity are poorly understood. There are currently few effective solutions to suppress X. fastidiosa disease development or eliminate bacteria from infected plants. Recently, disease epidemics due to X. fastidiosa have greatly expanded, increasing the need for better disease prevention and control strategies. Our studies show a novel connection between cold shock protein Csp1 and pili abundance and attachment, which have not been reported for X. fastidiosa. Understanding how pathogenesis-related gene expression is regulated can aid in developing novel pathogen and disease control strategies. We also streamlined a bioinformatics protocol to process and analyze long-read nanopore bacterial RNA-Seq data, which will benefit the research community, particularly those working with non-model bacterial species.