Global warming significantly increases the risk of Pierce's disease epidemics in European vineyards.

Pierce's disease (PD) is a vector-borne disease caused by the bacteria Xylella fastidiosa, which affects grapevines in the Americas. Currently, vineyards in continental Europe, the world's largest producer of quality wine, have not yet been affected by PD. However, climate change may alter this situation. Here we incorporate the latest regional climate change projections into a climate-driven epidemiological model to assess the risk of PD epidemics in Europe for different levels of global warming. We found a significant increase in risk above + 2 ∘ C in the main wine-producing regions of France, Italy and Portugal, in addition to a critical tipping point above + 3 ∘ C for the possible spread of PD beyond the Mediterranean. The model identifies decreasing risk trends in Spain, as well as contrasting patterns across the continent with different velocities of risk change and epidemic growth rates. Although there is some uncertainty in model projections over time, spatial patterns of risk are consistent across different climate models. Our study provides a comprehensive analysis of the future of PD at multiple spatial scales (country, Protected Designation of Origin and vineyard), revealing where, why and when PD could become a new threat to the European wine industry.

Degree-day-based model to predict egg hatching of Philaenus spumarius (Hemiptera: Aphrophoridae), the main vector of Xylella fastidiosa in Europe.

Philaenus spumarius L., the main vector of Xylella fastidiosa (Wells) in Europe, is a univoltine species that overwinters in the egg stage, and its nymphs emerge in late winter or spring. Predicting the time of egg hatching is essential for determining the precise times for deploying control strategies against insect pests. Here, we monitored P. spumarius eggs from oviposition to egg hatching together with the daily temperatures and relative humidities at four field locations that were located at different altitudes in central Spain. The collected data were used to build a growing degree day (GDD) model to forecast egg hatching in the Iberian Peninsula. Furthermore, the model was validated with field observations that were conducted in Spain. The model was then used as a decision-support tool to calculate the optimum timing for applying control actions against P. spumarius. Our results suggest that controlling nymphs at two different dates would target the highest percentages of nymphal populations present in the field. Our model represents a first step for predicting the emergence of nymphs and adopting timely control actions against P. spumarius. These actions could limit disease spread in areas where X. fastidiosa is present.

A Compartmental Model for Xylella fastidiosa Diseases with Explicit Vector Seasonal Dynamics.

The bacterium Xylella fastidiosa is mainly transmitted by the meadow spittlebug Philaenus spumarius in Europe, where it has caused significant economic damage to olive and almond trees. Understanding the factors that determine disease dynamics in pathosystems that share similarities can help to design control strategies focused on minimizing transmission chains. Here, we introduce a compartmental model for X. fastidiosa-caused diseases in Europe that accounts for the main relevant epidemiological processes, including the seasonal dynamics of P. spumarius. The model was confronted with epidemiological data from the two major outbreaks of X. fastidiosa in Europe, the olive quick disease syndrome in Apulia, Italy, caused by the subspecies pauca, and the almond leaf scorch disease in Mallorca, Spain, caused by subspecies multiplex and fastidiosa. Using a Bayesian inference framework, we show how the model successfully reproduces the general field data in both diseases. In a global sensitivity analysis, the vector-to-plant and plant-to-vector transmission rates, together with the vector removal rate, were the most influential parameters in determining the time of the infectious host population peak, the incidence peak, and the final number of dead hosts. We also used our model to check different vector-based control strategies, showing that a joint strategy focused on increasing the rate of vector removal while lowering the number of annual newborn vectors is optimal for disease control. [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.

Global predictions for the risk of establishment of Pierce's disease of grapevines.

The vector-borne bacterium Xylella fastidiosa is responsible for Pierce's disease (PD), a lethal grapevine disease that originated in the Americas. The international plant trade is expanding the geographic range of this pathogen, posing a new threat to viticulture worldwide. To assess the potential incidence of PD, we have built a dynamic epidemiological model based on the response of 36 grapevine varieties to the pathogen in inoculation assays and on the vectors' distribution when this information is available. Key temperature-driven epidemiological processes, such as PD symptom development and recovery, are mechanistically modelled. Integrating into the model high-resolution spatiotemporal climatic data from 1981 onward and different infectivity (R0) scenarios, we show how the main wine-producing areas thrive mostly in non-risk, transient, or epidemic-risk zones with potentially low growth rates in PD incidence. Epidemic-risk zones with moderate to high growth rates are currently marginal outside the US. However, a global expansion of epidemic-risk zones coupled with small increments in the disease growth rate is projected for 2050. Our study globally downscales the risk of PD establishment while highlighting the importance of considering climate variability, vector distribution, and an invasive criterion as factors to obtain better PD risk maps.

Vector-borne diseases with nonstationary vector populations: The case of growing and decaying populations.

Since the last century, deterministic compartmental models have emerged as powerful tools to predict and control epidemic outbreaks, in many cases helping to mitigate their impacts. A key quantity for these models is the so-called basic reproduction number, R_{0}, that measures the number of secondary infections produced by an initial infected individual in a fully susceptible population. Some methods have been developed to allow the direct computation of this quantity provided that some conditions are fulfilled, such that the model has a prepandemic disease-free equilibrium state. This condition is fulfilled only when the populations are stationary. In the case of vector-borne diseases, this implies that the vector birth and death rates need to be balanced. This is not fulfilled in many realistic cases in which the vector population grows or decreases. Here we develop a vector-borne epidemic model with growing and decaying vector populations that in the long term converge to an asymptotic stationary state, and study the conditions under which the standard methods to compute R_{0} work and discuss an alternative when they fail. We also show that growing vector populations produce a delay in the epidemic dynamics when compared to the case of the stationary vector population. Finally, we discuss the conditions under which the model can be reduced to the Susceptible, Infectious, and/or Recovered (SIR) model with fewer compartments and parameters, which helps in solving the problem of parameter unidentifiability of many vector-borne epidemic models.

Bifurcation structure of traveling pulses in type-I excitable media.

We study the scenario in which traveling pulses emerge in a prototypical type-I one-dimensional excitable medium, which exhibits two different routes to excitable behavior, mediated by a homoclinic (saddle-loop) and a saddle-node on the invariant cycle bifurcations. We characterize the region in parameter space in which traveling pulses are stable together with the different bifurcations behind either their destruction or loss of stability. In particular, some of the bifurcations delimiting the stability region have been connected, using singular limits, with the two different scenarios that mediated type-I local excitability. Finally, the existence of traveling pulses has been linked to a drift pitchfork instability of localized steady structures.

Spatial effects in parasite-induced marine diseases of immobile hosts.

Emerging marine infectious diseases pose a substantial threat to marine ecosystems and the conservation of their biodiversity. Compartmental models of epidemic transmission in marine sessile organisms, available only recently, are based on non-spatial descriptions in which space is homogenized and parasite mobility is not explicitly accounted for. However, in realistic scenarios epidemic transmission is conditioned by the spatial distribution of hosts and the parasites' mobility patterns, calling for an explicit description of space. In this work, we develop a spatially explicit individual-based model to study disease transmission by waterborne parasites in sessile marine populations. We investigate the impact of spatial disease transmission through extensive numerical simulations and theoretical analysis. Specifically, the effects of parasite mobility into the epidemic threshold and the temporal progression of the epidemic are assessed. We show that larger values of pathogen mobility imply more severe epidemics, as the number of infections increases, and shorter timescales to extinction. An analytical expression for the basic reproduction number of the spatial model, R ~ 0 , is derived as a function of the non-spatial counterpart, R 0, which characterizes a transition between a disease-free and a propagation phase, in which the disease propagates over a large fraction of the system.

pH trends and seasonal cycle in the coastal Balearic Sea reconstructed through machine learning.

The decreasing seawater pH trend associated with increasing atmospheric carbon dioxide levels is an issue of concern due to possible negative consequences for marine organisms, especially calcifiers. Globally, coastal areas represent important transitional land-ocean zones with complex interactions between biological, physical and chemical processes. Here, we evaluated the pH variability at two sites in the coastal area of the Balearic Sea (Western Mediterranean). High resolution pH data along with temperature, salinity, and also dissolved oxygen were obtained with autonomous sensors from 2018 to 2021 in order to determine the temporal pH variability and the principal drivers involved. By using environmental datasets of temperature, salinity and dissolved oxygen, Recurrent Neural Networks were trained to predict pH and fill data gaps. Longer environmental time series (2012-2021) were used to obtain the pH trend using reconstructed data. The best predictions show a rate of [Formula: see text] pH units year[Formula: see text], which is in good agreement with other observations of pH rates in coastal areas. The methodology presented here opens the possibility to obtain pH trends when only limited pH observations are available, if other variables are accessible. Potentially, this could be a way to reliably fill the unavoidable gaps present in time series data provided by sensors.

Traveling pulses in type-I excitable media.

We consider a general model exhibiting type-I excitability mediated by a homoclinic and a saddle node on the invariant circle bifurcations. We show how the distinct properties of type-I with respect to type-II excitability confer unique features to traveling pulses in excitable media. They inherit the characteristic divergence of type-I excitable trajectories at threshold exhibiting analogous scalings in the spatial thickness of the pulses. Our results pave the way to identify basic underlying mechanisms behind type-I excitable pulses based solely on the characteristics of the pulse.

Formation of localized structures in bistable systems through nonlocal spatial coupling. I. General framework.

The present work studies the influence of nonlocal spatial coupling on the existence of localized structures in one-dimensional extended systems. We consider systems described by a real field with a nonlocal coupling that has a linear dependence on the field. Leveraging spatial dynamics we provide a general framework to understand the effect of the nonlocality on the shape of the fronts connecting two stable states. In particular we show that nonlocal terms can induce spatial oscillations in the front tails, allowing for the creation of localized structures, that emerge from pinning between two fronts. In parameter space the region where fronts are oscillatory is limited by three transitions: the modulational instability of the homogeneous state, the Belyakov-Devaney transition in which monotonic fronts acquire spatial oscillations with infinite wavelength, and a crossover in which monotonically decaying fronts develop spatial oscillations with a finite wavelength. We show how these transitions are organized by codimension 2 and 3 points and illustrate how by changing the parameters of the nonlocal coupling it is possible to bring the system into the region where localized structures can be formed.

Formation of localized structures in bistable systems through nonlocal spatial coupling. II. The nonlocal Ginzburg-Landau equation.

We study the influence of a linear nonlocal spatial coupling on the interaction of fronts connecting two equivalent stable states in the prototypical 1-dimensional real Ginzburg-Landau equation. While for local coupling the fronts are always monotonic and therefore the dynamical behavior leads to coarsening and the annihilation of pairs of fronts, nonlocal terms can induce spatial oscillations in the front, allowing for the creation of localized structures, emerging from pinning between two fronts. We show this for three different nonlocal influence kernels. The first two, mod-exponential and Gaussian, are positive definite and decay exponentially or faster, while the third one, a Mexican-hat kernel, is not positive definite.

Spectrum of genetic diversity and networks of clonal organisms.

Clonal reproduction characterizes a wide range of species including clonal plants in terrestrial and aquatic ecosystems, and clonal microbes such as bacteria and parasitic protozoa, with a key role in human health and ecosystem processes. Clonal organisms present a particular challenge in population genetics because, in addition to the possible existence of replicates of the same genotype in a given sample, some of the hypotheses and concepts underlying classical population genetics models are irreconcilable with clonality. The genetic structure and diversity of clonal populations were examined using a combination of new tools to analyse microsatellite data in the marine angiosperm Posidonia oceanica. These tools were based on examination of the frequency distribution of the genetic distance among ramets, termed the spectrum of genetic diversity (GDS), and of networks built on the basis of pairwise genetic distances among genets. Clonal growth and outcrossing are apparently dominant processes, whereas selfing and somatic mutations appear to be marginal, and the contribution of immigration seems to play a small role in adding genetic diversity to populations. The properties and topology of networks based on genetic distances showed a 'small-world' topology, characterized by a high degree of connectivity among nodes, and a substantial amount of substructure, revealing organization in subfamilies of closely related individuals. The combination of GDS and network tools proposed here helped in dissecting the influence of various evolutionary processes in shaping the intra-population genetic structure of the clonal organism investigated; these therefore represent promising analytical tools in population genetics.

Phase-space structure of two-dimensional excitable localized structures.

In this work we characterize in detail the bifurcation leading to an excitable regime mediated by localized structures in a dissipative nonlinear Kerr cavity with a homogeneous pump. Here we show how the route can be understood through a planar dynamical system in which a limit cycle becomes the homoclinic orbit of a saddle point (saddle-loop bifurcation). The whole picture is unveiled, and the mechanism by which this reduction occurs from the full infinite-dimensional dynamical system is studied. Finally, it is shown that the bifurcation leads to an excitability regime, under the application of suitable perturbations. Excitability is an emergent property for this system, as it emerges from the spatial dependence since the system does not exhibit any excitable behavior locally.

Experimental study of the transitions between synchronous chaos and a periodic rotating wave.

In this work we characterize experimentally the transition between periodic rotating waves and synchronized chaos in a ring of unidirectionally coupled Lorenz oscillators by means of electronic circuits. The study is complemented by numerical and theoretical analysis, and the intermediate states and their transitions are identified. The route linking periodic behavior with synchronous chaos involves quasiperiodic behavior and a type of high-dimensional chaos known as chaotic rotating wave. The high-dimensional chaotic behavior is characterized, and is shown to be composed actually by three different behaviors. The experimental study confirms the robustness of this route.

Comment on "Periodic phase synchronization in coupled chaotic oscillators".

Kye [Phys. Rev. E 68, 025201 (2003)] have recently claimed that, before the onset of chaotic phase synchronization in coupled phase coherent oscillators, there exists a temporally coherent state called periodic phase synchronization (PPS). Here we give evidence that some of their numerical calculations are flawed, while we provide theoretical arguments that indicate that PPS is not to be expected generically in this type of systems.

Excitability mediated by localized structures in a dissipative nonlinear optical cavity.

We find and characterize an excitability regime mediated by localized structures in a dissipative nonlinear optical cavity. The scenario is that stable localized structures exhibit a Hopf bifurcation to self-pulsating behavior, that is followed by the destruction of the oscillation in a saddle-loop bifurcation. Beyond this point there is a regime of excitable localized structures under the application of suitable perturbations. Excitability emerges from the spatial dependence since the system does not exhibit any excitable behavior locally. We show that the whole scenario is organized by a Takens-Bogdanov codimension-2 bifurcation point.

Rare events and scale-invariant dynamics of perturbations in delayed chaotic systems.

We study the dynamics of perturbations in time-delay dynamical systems. Using a suitable space-time coordinate transformation, we find that the time evolution of the linearized perturbations (Lyapunov vector) can be described by the linear Zhang surface growth model [J. Phys. (France) 51, 2129 (1990)]], which is known to describe surface roughening driven by power-law distributed noise. As a consequence, Lyapunov vector dynamics is dominated by rare random events that lead to non-Gaussian fluctuations and multiscaling properties.

Universal scaling of Lyapunov exponents in coupled chaotic oscillators.

We have uncovered a phenomenon in coupled chaotic oscillators where a subset of Lyapunov exponents, which are originally zero in the absence of coupling, can become positive as the coupling is increased. This occurs for chaotic attractors having multiple scrolls, such as the Lorenz attractor. We argue that the phenomenon is due to the disturbance to the relative frequencies with which a trajectory visits different scrolls of the attractor. An algebraic scaling law is obtained which relates the Lyapunov exponents with the coupling strength. The scaling law appears to be universal.