Signals of climate change in butterfly communities in a Mediterranean protected area.

Journal ArticleResearch Support, Non-U.S. Gov'tCopyright: © 2014 Zografou et al.The European protected-area network will cease to be efficient for biodiversity conservation, particularly in the Mediterranean region, if species are driven out of protected areas by climate warming. Yet, no empirical evidence of how climate change influences ecological communities in Mediterranean nature reserves really exists. Here, we examine long-term (1998-2011/2012) and short-term (2011-2012) changes in the butterfly fauna of Dadia National Park (Greece) by revisiting 21 and 18 transects in 2011 and 2012 respectively, that were initially surveyed in 1998. We evaluate the temperature trend for the study area for a 22-year-period (1990-2012) in which all three butterfly surveys are included. We also assess changes in community composition and species richness in butterfly communities using information on (a) species' elevational distributions in Greece and (b) Community Temperature Index (calculated from the average temperature of species' geographical ranges in Europe, weighted by species' abundance per transect and year). Despite the protected status of Dadia NP and the subsequent stability of land use regimes, we found a marked change in butterfly community composition over a 13 year period, concomitant with an increase of annual average temperature of 0.95°C. Our analysis gave no evidence of significant year-to-year (2011-2012) variability in butterfly community composition, suggesting that the community composition change we recorded is likely the consequence of long-term environmental change, such as climate warming. We observe an increased abundance of low-elevation species whereas species mainly occurring at higher elevations in the region declined. The Community Temperature Index was found to increase in all habitats except agricultural areas. If equivalent changes occur in other protected areas and taxonomic groups across Mediterranean Europe, new conservation options and approaches for increasing species' resilience may have to be devised.ESFGreek national funds (NSRF

Combined organic and inorganic source apportionment on yearlong ToF-ACSM dataset at a suburban station in Athens

The current improvements in aerosol mass spectrometers in resolution and sensitivity, and the analytical tools for mass spectra deconvolution, have enabled the in-depth analysis of ambient organic aerosol (OA) properties. Although OA constitutes a major fraction of ambient aerosol, its properties are determined to a great extent by the mixing characteristics of both organic and inorganic components of ambient aerosol. This work applies a new methodology to a year-long ACSM dataset to assess the sources of organic and total non-refractory species in the Athens background aerosol and provides insights into the interactions between organic and inorganic species. The use of innovative tools for applying positive matrix factorization (PMF, rolling window) enables the study of the temporal variability of the contribution of these sources and seasonal changes in their composition. The mass spectra of both organic and inorganic aerosol were obtained by a time-of-flight aerosol mass spectrometer (ToF-ACSM) for PMF analysis. The results revealed five factors when organic aerosol was analysed separately. Three of them were primary OA factors: hydrocarbon-like organic aerosol (HOA), cooking-related organic aerosol (COA) and biomass burning organic aerosol (BBOA). The remaining two were secondary, less and more oxidized oxygenated organic aerosol (LO-OOA and MO-OOA respectively). The relative contributions of these factors were HOA 15 %, COA 18 %, BBOA 9 %, MO-OOA 34 % and LO-OOA 24 % (yearly averaged). When a combined organic and inorganic aerosol matrix was analysed, two additional factors were identified that were mainly composed of ammonium sulfate (83.5 %) and ammonium nitrate (73 %). Moreover, two secondary factors were resolved, containing both organics and inorganics and were named more (MOA) and less oxidized aerosol (LOA). The relative contributions on a yearly average of these factors were HOA 7 %, COA 9 %, BBOA 3 %, ammonium nitrate 3 %, ammonium sulfate 28 %, MOA 24 % and LOA 26 %

Microfluidic characterisation reveals broad range of SARS-CoV-2 antibody affinity in human plasma.

Funder: Herchel Smith FundFunder: St John’s College CambridgeFunder: Centre for Misfolding Diseases, CambridgeFunder: Swiss FCS and the Forschungskredit of the University of ZurichFunder: Frances and Augustus Newman FoundationFunder: BBRSCFunder: NOMIS FoundationThe clinical outcome of SARS-CoV-2 infections, which can range from asymptomatic to lethal, is crucially shaped by the concentration of antiviral antibodies and by their affinity to their targets. However, the affinity of polyclonal antibody responses in plasma is difficult to measure. Here we used microfluidic antibody affinity profiling (MAAP) to determine the aggregate affinities and concentrations of anti-SARS-CoV-2 antibodies in plasma samples of 42 seropositive individuals, 19 of which were healthy donors, 20 displayed mild symptoms, and 3 were critically ill. We found that dissociation constants, K d, of anti-receptor-binding domain antibodies spanned 2.5 orders of magnitude from sub-nanomolar to 43 nM. Using MAAP we found that antibodies of seropositive individuals induced the dissociation of pre-formed spike-ACE2 receptor complexes, which indicates that MAAP can be adapted as a complementary receptor competition assay. By comparison with cytopathic effect-based neutralisation assays, we show that MAAP can reliably predict the cellular neutralisation ability of sera, which may be an important consideration when selecting the most effective samples for therapeutic plasmapheresis and tracking the success of vaccinations

Continuous population-level monitoring of SARS-CoV-2 seroprevalence in a large European metropolitan region

Effective public health measures against SARS-CoV-2 require granular knowledge of population-level immune responses. We developed a Tripartite Automated Blood Immunoassay (TRABI) to assess the IgG response against three SARS-CoV-2 proteins. We used TRABI for continuous seromonitoring of hospital patients and blood donors (n = 72'250) in the canton of Zurich from December 2019 to December 2020 (pre-vaccine period). We found that antibodies waned with a half-life of 75 days, whereas the cumulative incidence rose from 2.3% in June 2020 to 12.2% in mid-December 2020. A follow-up health survey indicated that about 10% of patients infected with wildtype SARS-CoV-2 sustained some symptoms at least twelve months post COVID-19. Crucially, we found no evidence of a difference in long-term complications between those whose infection was symptomatic and those with asymptomatic acute infection. The cohort of asymptomatic SARS-CoV-2-infected subjects represents a resource for the study of chronic and possibly unexpected sequelae

Continuous population-level monitoring of SARS-CoV-2 seroprevalence in a large European metropolitan region.

Effective public health measures against SARS-CoV-2 require granular knowledge of population-level immune responses. We developed a Tripartite Automated Blood Immunoassay (TRABI) to assess the IgG response against three SARS-CoV-2 proteins. We used TRABI for continuous seromonitoring of hospital patients and blood donors (n = 72'250) in the canton of Zurich from December 2019 to December 2020 (pre-vaccine period). We found that antibodies waned with a half-life of 75 days, whereas the cumulative incidence rose from 2.3% in June 2020 to 12.2% in mid-December 2020. A follow-up health survey indicated that about 10% of patients infected with wildtype SARS-CoV-2 sustained some symptoms at least twelve months post COVID-19. Crucially, we found no evidence of a difference in long-term complications between those whose infection was symptomatic and those with asymptomatic acute infection. The cohort of asymptomatic SARS-CoV-2-infected subjects represents a resource for the study of chronic and possibly unexpected sequelae

A GIS-based integrated approach predicts accurately post-fire Aleppo pine regeneration at regional scale

Context: This study investigates post-fire natural regeneration of Aleppo pine (Pinus halepensis) forests at Ilia region (Peloponnesus, Greece) following the catastrophic fire of 2007. Aims: The objective of this study is the prediction of P. halepensis post-fire regeneration at a regional scale through an integrated geographic information systems (GIS) model as a basis for post-fire management plans. Methods: The model was developed in three interconnected stages: (1) field data collection, (2) development of two prediction models (based on interpolation of field data and multicriteria evaluation (MCE) that combined factors known to affect regeneration), and (3) combination of applied models using Bayesian statistics. Results: Post-fire pine regeneration presented high variation among the studied plots. Redundancy analysis revealed the positive effect of fallen branches and a negative correlation with altitude. Both modeling approaches (geostatistical and MCE) predicted the post-fire pine regeneration with high accuracy. A very significant correlation (r00.834, p<0.01) was found between the combined final model and the actual number of counted seedlings, illustrating that less than 10 % of the studied area corresponds to sites of very low post-fire pine regeneration. Conclusion:s The combination of GIS models increased the prediction success of different levels of pine regeneration. Lowaltitude areas with low grass cover overlying tertiary deposits were proved the most suitable for pine regeneration, while stands developing on limestone proved least suitable. The proposed methodology providesmanagement authoritieswith a sound tool to quickly assess Aleppo pine post-fire regeneration potential. © INRA /Springer-Verlag France 2012