BackgroundIn gene-for-gene models of plant-pathogen interactions, the existence of fitness costs associated with unnecessary virulence factors still represents an issue, both in evolutionary biology and agricultural sciences. Measuring such costs experimentally has proven difficult, especially in pathogens not readily amenable to genetic transformation, since the creation of isogenic lines differing only by the presence or absence of avirulence genes cannot be achieved in many organisms. Here, we circumvented this difficulty by comparing fitness traits in groups of Phytophthora infestans isolates sharing the same multilocus fingerprint, but differing by their virulence/avirulence spectrum.ResultsFitness was assessed from calculations derived from the basic reproduction number, combining several life history traits (latent period, spore density and lesion growth rate) evaluated on leaflets of the potato cultivar Bintje, which is free of resistance genes. A statistically significant fitness cost was found in isolates virulent to the R10 resistance gene. That cost was due to a lower spore production in virulent isolates; however, the latent period was shorter in virulent isolates. Similar trends, although not statistically significant, were observed for the other genes tested.ConclusionThe data likely reflect the adaptive response of the pathogen to the cost associated with virulence. They suggest strong trade-offs between life history traits related to pathogenicity and adaptive biology of pathogens.

This paper deals with the state and input observability analysis for structured linear systems with unknown inputs. The proposed method is based on a graph-theoretic approach and assumes only the knowledge of the system's structure. Using a particular decomposition of the systems into two subsystems, we express, in simple graphic terms, necessary and sufficient conditions for the generic state and input observability. These conditions are easy to check because they are based on comparison of integers and on finding particular subgraphs in a digraph. Therefore, our approach is suited to study large scale systems.

No abstract

The coexistence of closely related plant parasites is widespread. Yet, understanding the ecological determinants of evolutionary divergence in plant parasites remains an issue. Niche differentiation through resource specialization has been widely researched, but it hardly explains the coexistence of parasites exploiting the same host plant. Time-partitioning has so far received less attention, although in temperate climates, parasites may specialize on either the early or the late season. Accordingly, we investigated whether seasonality can also promote phenotypic divergence. For plant parasites, seasonality generally engenders periodic host absence. To account for abrupt seasonal events, we made use of an epidemic model that combines continuous and discrete dynamics. Based on the assumption of a trade-off between in-season transmission and inter-season survival, we found through an "evolutionary invasion analysis" that evolutionary divergence of the parasite phenotype can occur. Since such a trade-off has been reported, this study provides further ecological bases for the coexistence of closely related plant parasites. Moreover, this study provides original insights into the coexistence of sibling plant pathogens which perform either a single or several infection cycles within a season (mono- and polycyclic diseases, or uni- and multivoltine life cycles).

An important issue in fault diagnosis research is the design of methods for robust residual generation. In this framework, systems described by uncertain models and subject to unknown input disturbances are studied in this article. A nominal model of the system is first considered for residual generation using an H∞ parameterized output observer. The design procedure is based on the optimization of a performance index which is solved via linear matrix inequalities (LMI). Unstructured uncertainties due to parameter variations are then considered in the system model. In order to take the worst effect of uncertainties into account, the determination of an optimal threshold depending on the operating conditions is suggested for residual evaluation. This is achieved via the introduction of Kharitonov polynomials and the associated geometry of uncertain polytopic families. A simulation example illustrates the proposed approach. Copyright © 2000 John Wiley & Sons, Ltd.

If pathogen species, strains, or clones do not interact, intuition suggests the proportion of coinfected hosts should be the product of the individual prevalences. Independence consequently underpins the wide range of methods for detecting pathogen interactions from cross-sectional survey data. However, the very simplest of epidemiological models challenge the underlying assumption of statistical independence. Even if pathogens do not interact, death of coinfected hosts causes net prevalences of individual pathogens to decrease simultaneously. The induced positive correlation between prevalences means the proportion of coinfected hosts is expected to be higher than multiplication would suggest. By modelling the dynamics of multiple noninteracting pathogens causing chronic infections, we develop a pair of novel tests of interaction that properly account for nonindependence between pathogens causing lifelong infection. Our tests allow us to reinterpret data from previous studies including pathogens of humans, plants, and animals. Our work demonstrates how methods to identify interactions between pathogens can be updated using simple epidemic models.

No abstract

Understanding how often individuals should move when foraging over patchy habitats is a central question in ecology. By combining optimality and functional response theories, we show analytically how the optimal movement rate varies with the average resource level (enrichment) and resource distribution (patch heterogeneity). We find that the type of functional response predicts the effect of enrichment in homogeneous habitats: enrichment should decrease movement for decelerating functional responses, but increase movement for accelerating responses. An intermediate resource level thus maximises movement for type-III responses. Counterintuitively, greater movement costs favour an increase in movement. In heterogeneous habitats predictions further depend on how enrichment alters the variance of resource distribution. Greater patch variance always increases the optimal rate of movement, except for type-IV functional responses. While the functional response is well established as a fundamental determinant of consumer-resource dynamics, our results indicate its importance extends to the understanding of individual movement strategies.