Influence of environment and climate on occurrence of the cixiid planthopper Hyalesthes obsoletus, the vector of the grapevine disease 'bois noir'.

Species distribution models (SDMs), which are well established in many fields of biological research, are still uncommon in the agricultural risk analysis of pest insects. To exemplify the use of SDMs, we investigated the influence of environmental factors on the occurrence of Hyalesthes obsoletus Signoret (Hemiptera: Cixiidae). The planthopper is the only known vector of the grapevine yellows disease 'bois noir'. The study was conducted in 145 locations in the Baden region of southwest Germany. The planthopper was surveyed on host plant patches, consisting of stinging nettle and/or bindweeds. We used a stratified modelling framework where (1) species presence-absence data were related to an extensive environmental dataset using logistic regressions; and (2) different types of average models were developed based on an information theoretic method. The results show that the incidence of H. obsoletus is associated to above- as well as below-ground environmental factors, particularly to the amount of fine soil and average annual precipitation. This result was consistent across all average models. The relative importance of other environmental variables was dependent upon the average model under consideration and thus may vary according to their intended use, either the explanation of habitat requirements or the prediction and mapping of occurrence risks. The study showed that SDMs offer a quantification of species' habitat requirements and thus, could represent a valuable tool for pest management purposes. By providing examples of current issues of grapevine pests in viticulture, we discuss the use of SDMs in agricultural risk analysis and highlight their advantages and caveats.

Annual plants under cyclic disturbance regime: better understanding through model aggregation.

In their application for conservation ecology, "classical" analytical models and individual-based simulation models (IBMs) both entail their specific strengths and weaknesses, either in providing a detailed and realistic representation of processes or in regard to a comprehensive model analysis. This well-known dilemma may be resolved by the combination of both approaches when tackling certain problems of conservation ecology. Following this idea, we present the complementary use of both an IBM and a matrix population model in a case study on grassland conservation management. First, we develop a spatially explicit IBM to simulate the long-term response of the annual plant Thlaspi perfoliatum (Brassicaceae), claspleaf pennycress, to different management schemes (annual mowing vs. infrequent rototilling) based on field experiments. In order to complement the simulation results by further analyses, we aggregate the IBM to a spatially nonexplicit deterministic matrix population model. Within the periodic environment created by management regimes, population dynamics are described by periodic products of annual transition matrices. Such periodic matrix products provide a very conclusive framework to study the responses of species to different management return intervals. Thus, using tools of matrix model analysis (e.g., loop analysis), we can both identify dormancy within the age-structured seed bank as the pivotal strategy for persistence under cyclic disturbance regimes and reveal crucial thresholds in some less certain parameters. Results of matrix model analyses are therefore successfully tested by comparing their results to the respective IBM simulations. Their implications for an enhanced scientific basis for management decisions are discussed as well as some general benefits and limitations of the use of aggregating modeling approaches in conservation.

Evolving clinical application of cardiac MRI.

Over the past decade, cardiac magnetic resonance imaging (MRI) has emerged as a new technology representing the next major advance in noninvasive cardiac imaging. It provides unique and accurate data representative of cardiac structure, function, and perfusion at both the gross anatomical and myocardial levels. Cardiac MRI proves to be highly accurate and reproducible in many challenging areas in clinical cardiology, including diagnosis of constrictive pericarditis, differentiation of ischemic from dilated cardiomyopathy, confirmation of the diagnosis of myocarditis, and definition and quantification of myocardial viability. As compelling studies support its clinical utility, the evolution of cardiac MRI is gaining speed. In many cases, such as the diagnosis of anomalous origin of the coronary arteries, it is the gold standard diagnostic technique.