Effect of ground-cover management on predatory mites (Acari: Phytoseiidae) in a Mediterranean vineyard

Most predatory mites belong to the family Phytoseiidae (Acari). Throughout the world, phytoseiids are involved in the biological control of phytophagous mites in vineyards. Conservative strategies, including cover-vegetation management, are essential to achieve environmentally friendly viticulture. The abundance and diversity of phytoseiid mites in the grapevine canopy and the vegetal ground cover of a Mediterranean vineyard were surveyed by weekly samplings, from early May until the end of September for two years (2016 and 2017). Three types of soil management without herbicide application were analysed and referred to as "Tillage", "Spontaneous Cover", and "Flower-driven Cover" treatments. Six phytoseiid species were collected on the grapevine canopy, with Typhlodromus pyri being the dominant species (99.5 %). Five phytoseiid species were recorded in the ground cover, with Typhlodromus and Neoseiulus as the major genera. The Flower-driven Cover treatment showed the highest abundance of phytoseiids in the grapevine canopy. However, both species richness and abundance of phytoseiid mites on the ground-cover vegetation were highest in the Spontaneous Cover treatment. These observations suggest that improving vegetation cover would promote both the abundance and diversity of phytoseiid mites in vineyards because the greater supply of pollen would enhance their survival. Therefore, the use of cover crops in vineyards represents a means of improving vineyard ecosystems by conservative biological control

Transcriptome sequencing identifies SPL7-regulated copper acquisition genes FRO4/FRO5 and the copper dependence of iron homeostasis in Arabidopsis

24 Pags., 9 Figs., 2 Tabls., with Supplemental Data (15 Figs., 3 Tabls., 1 Method, 1 Data Set).The transition metal copper (Cu) is essential for all living organisms but is toxic when present in excess. To identify Cu deficiency responses comprehensively, we conducted genome-wide sequencing-based transcript profiling of Arabidopsis thaliana wild-type plants and of a mutant defective in the gene encoding SQUAMOSA PROMOTER BINDING PROTEIN-LIKE7 (SPL7), which acts as a transcriptional regulator of Cu deficiency responses. In response to Cu deficiency, FERRIC REDUCTASE OXIDASE5 (FRO5) and FRO4 transcript levels increased strongly, in an SPL7-dependent manner. Biochemical assays and confocal imaging of a Cu-specific fluorophore showed that high-affinity root Cu uptake requires prior FRO5/FRO4-dependent Cu(II)-specific reduction to Cu(I) and SPL7 function. Plant iron (Fe) deficiency markers were activated in Cu-deficient media, in which reduced growth of the spl7 mutant was partially rescued by Fe supplementation. Cultivation in Cu-deficient media caused a defect in root-to-shoot Fe translocation, which was exacerbated in spl7 and associated with a lack of ferroxidase activity. This is consistent with a possible role for a multicopper oxidase in Arabidopsis Fe homeostasis, as previously described in yeast, humans, and green algae. These insights into root Cu uptake and the interaction between Cu and Fe homeostasis will advance plant nutrition, crop breeding, and biogeochemical research.We acknowledge postdoctoral fellowships to M.B. from the Alexander von Humboldt Foundation and the Spanish Ministry of Science and Innovation; a Deutsche Forschungsgemeinshaft Heisenberg fellowship and funding from the FRONTIERS program at the University of Heidelberg, Germany, and the European Union InP Public Health Impact of Long-Term, Low-Level Mixed Element Exposure in Susceptible Population Strata (FOOD-CT-2006-016253) to U.K.; a grant from the National Science Foundation (IOS-0919739) to E.L.C.; a postdoctoral fellowship from the Spanish Foundation of Science and Technology (MEC-FECYT) to D.C.; National Institutes of Health Grant GM42143 to S.S.M.; and support from the University of California, Los Angeles–Department of Energy Institute for Genomics and Proteomics under Contract DE-FC02-02ER63421 to M.P.Peer reviewe

Current and Future Niche of North and Central American Sand Flies (Diptera: Psychodidae) in Climate Change Scenarios

Ecological niche models are useful tools to infer potential spatial and temporal distributions in vector species and to measure epidemiological risk for infectious diseases such as the Leishmaniases. The ecological niche of 28 North and Central American sand fly species, including those with epidemiological relevance, can be used to analyze the vector’s ecology and its association with transmission risk, and plan integrated regional vector surveillance and control programs. In this study, we model the environmental requirements of the principal North and Central American phlebotomine species and analyze three niche characteristics over future climate change scenarios: i) potential change in niche breadth, ii) direction and magnitude of niche centroid shifts, iii) shifts in elevation range. Niche identity between confirmed or incriminated Leishmania vector sand flies in Mexico, and human cases were analyzed. Niche models were constructed using sand fly occurrence datapoints from Canada, USA, Mexico, Guatemala and Belize. Nine non-correlated bioclimatic and four topographic data layers were used as niche components using GARP in OpenModeller. Both B2 and A2 climate change scenarios were used with two general circulation models for each scenario (CSIRO and HadCM3), for 2020, 2050 and 2080. There was an increase in niche breadth to 2080 in both scenarios for all species with the exception of Lutzomyia vexator. The principal direction of niche centroid displacement was to the northwest (64%), while the elevation range decreased greatest for tropical, and least for broad-range species. Lutzomyia cruciata is the only epidemiologically important species with high niche identity with that of Leishmania spp. in Mexico. Continued landscape modification in future climate change will provide an increased opportunity for the geographic expansion of NCA sand flys’ ENM and human exposure to vectors of Leishmaniases

Shared component modelling as an alternative to assess geographical variations in medical practice: gender inequalities in hospital admissions for chronic diseases

<p>Abstract</p> <p>Background</p> <p>Small area analysis is the most prevalent methodological approach in the study of unwarranted and systematic variation in medical practice at geographical level. Several of its limitations drive researchers to use disease mapping methods -deemed as a valuable alternative. This work aims at exploring these techniques using - as a case of study- the gender differences in rates of hospitalization in elderly patients with chronic diseases.</p> <p>Methods</p> <p>Design and study setting: An empirical study of 538,358 hospitalizations affecting individuals aged over 75, who were admitted due to a chronic condition in 2006, were used to compare Small Area Analysis (SAVA), the Besag-York-Mollie (BYM) modelling and the Shared Component Modelling (SCM). Main endpoint: Gender spatial variation was measured, as follows: SAVA estimated gender-specific utilization ratio; BYM estimated the fraction of variance attributable to spatial correlation in each gender; and, SCM estimated the fraction of variance shared by the two genders, and those specific for each one.</p> <p>Results</p> <p>Hospitalization rates due to chronic diseases in the elderly were higher in men (median per area 21.4 per 100 inhabitants, interquartile range: 17.6 to 25.0) than in women (median per area 13.7 per 100, interquartile range: 10.8 to 16.6). Whereas Utilization Ratios showed a similar geographical pattern of variation in both genders, BYM found a high fraction of variation attributable to spatial correlation in both men (71%, CI95%: 50 to 94) and women (62%, CI95%: 45 to 77). In turn, SCM showed that the geographical admission pattern was mainly shared, with just 6% (CI95%: 4 to 8) of variation specific to the women component.</p> <p>Conclusions</p> <p>Whereas SAVA and BYM focused on the magnitude of variation and on allocating where variability cannot be due to chance, SCM signalled discrepant areas where latent factors would differently affect men and women.</p

Income level and regional policies, underlying factors associated with unwarranted variations in conservative breast cancer surgery in Spain

<p>Abstract</p> <p>Background</p> <p>Geographical variations in medical practice are expected to be small when the evidence about the effectiveness and safety of a particular technology is abundant. This would be the case of the prescription of conservative surgery in breast cancer patients. In these cases, when variation is larger than expected by need, socioeconomic factors have been argued as an explanation. Objectives: Using an ecologic design, our study aims at describing the variability in the use of surgical conservative versus non-conservative treatment. Additionally, it seeks to establish whether the socioeconomic status of the healthcare area influences the use of one or the other technique.</p> <p>Methods</p> <p>81,868 mastectomies performed between 2002 and 2006 in 180 healthcare areas were studied. Standardized utilization rates of breast cancer conservative (CS) and non-conservative (NCS) procedures were estimated as well as the variation among areas, using small area statistics. Concentration curves and dominance tests were estimated to determine the impact of income and instruction levels in the healthcare area on surgery rates. Multilevel analyses were performed to determine the influence of regional policies.</p> <p>Results</p> <p>Variation in the use of CS was massive (4-fold factor between the highest and the lowest rate) and larger than in the case of NCS (2-fold), whichever the age group. Healthcare areas with higher economic and instruction levels showed highest rates of CS, regardless of the age group, while areas with lower economic and educational levels yielded higher rates of NCS interventions. Living in a particular Autonomous Community (AC), explained a substantial part of the CS residual variance (up to a 60.5% in women 50 to 70).</p> <p>Conclusion</p> <p>The place where a woman lives -income level and regional policies- explain the unexpectedly high variation found in utilization rates of conservative breast cancer surgery.</p

Using Biotic Interaction Networks for Prediction in Biodiversity and Emerging Diseases

Networks offer a powerful tool for understanding and visualizing inter-species ecological and evolutionary interactions. Previously considered examples, such as trophic networks, are just representations of experimentally observed direct interactions. However, species interactions are so rich and complex it is not feasible to directly observe more than a small fraction. In this paper, using data mining techniques, we show how potential interactions can be inferred from geographic data, rather than by direct observation. An important application area for this methodology is that of emerging diseases, where, often, little is known about inter-species interactions, such as between vectors and reservoirs. Here, we show how using geographic data, biotic interaction networks that model statistical dependencies between species distributions can be used to infer and understand inter-species interactions. Furthermore, we show how such networks can be used to build prediction models. For example, for predicting the most important reservoirs of a disease, or the degree of disease risk associated with a geographical area. We illustrate the general methodology by considering an important emerging disease - Leishmaniasis. This data mining methodology allows for the use of geographic data to construct inferential biotic interaction networks which can then be used to build prediction models with a wide range of applications in ecology, biodiversity and emerging diseases