Potential flight range of Snow Buntings Plectrophenax nivalis occurring in the Azores in late March : a first analysis.

It has been known for many decades that Snow Buntings occur with some regularity in the Azores archipelago in winter, with flocks numbering up to 20 individuals on occasion. The majority of records are from the islands of Corvo and Faial. The origin and fate of these individuals is unknown and it is unclear whether the regular occurrence of such groups represents a wintering strategy, or rather, whether these birds have been blown off the course of their usual migration route. Seven individuals from a flock of ten Snow Buntings known to have been present on the island of Faial between 20th March and early May 2000 were trapped on March 30th 2000. Plumage characteristics indicated they were of the Greenland P.n. nivalis race. Measurements of body mass indicated that the fat reserves of these individuals were similar to those of Snow Buntings wintering in Scotland U.K. at the same time of year, just prior to departure to the breeding grounds. However the calculated potential flight range of the individuals from Faial varied from 500 km to 1.800 km, averaging 1.150 km for females and 1.640 km for males. Whilst these average ranges would be sufficient to make continental landfall if the birds followed an easterly route, such a heading is considered improbable, given their racial characteristics. The calculated energy reserves would be insufficient to sustain continuous flight on a northerly course to continental landfall. The presence of potentially suitable breeding habitat on the neighbouring island of Pico is highlighted

Harmonising regulatory information on wine protected designation of origin in Europe

Wine Protected Designation of Origin (PDO) products are strictly regulated and therefore highly susceptible to changes in climatic, environmental and socioeconomic conditions. Analysing the impacts of such changes has so far been challenging, because the legal specifications of wine PDOs in Europe have never been summarised in a harmonised dataset. Here, we present how we created the first inventory of regulatory information for the 1177 wine PDO in Europe, based on the geographical indication register of the European Union

A geospatial inventory of regulatory information for wine protected designations of origin in Europe

The Wine Protected Designation of Origin (PDO) label is a European quality scheme that protects high quality wines by linking them to legally defined geographic areas and a set of specific production practices. Because of the tight relation between PDO wines and the specifications defined in the official regulatory documents, these products are highly susceptible to changes in climatic, environmental, or socioeconomic conditions. However, the content of these regulatory documents has never been systematically analysed and summarized in a single dataset. Here, we present the first geospatial inventory that organizes regulatory information about the 1177 wine PDO in Europe based on the documents from the official EU geographical indication register. It includes essential legal information that defines the wine PDO such as the geographic boundaries, authorized cultivars and maximum yields. This inventory opens new possibilities for researchers to accurately assess, compare and map the regulatory information in each wine region at an unprecedented level of detail, supporting decision makers in developing adaptation strategies for the preservation of PDO wine regions

Vintage Port prediction and climate change scenarios

The Douro region is renowned for its quality wines, particularly for the famous Port Wine. Vintage years, declared approximately 2–3 times per decade, signify exceptional quality linked to optimum climatic conditions driving grape quality attributes. Climate change poses challenges, as rising temperatures and extreme weather events impact viticulture. This study uses machine learning algorithms to assess the climatic influence on vintage years and climate change impacts for the next decades. Historical vintage data were collected from 1850 to 2014. Monthly climatic data for the same period were obtained, including temperature, precipitation, humidity, solar radiation, and wind components. Various machine-learning algorithms were selected for classification, and a statistical analysis helped identify relevant climate variables for differentiation. Cross-validation was used for model training and evaluation, with the hits and misses (confusion matrix) as the performance metric. The best-performing model underwent hyperparameter tuning. Subsequently, future climate projections were acquired for four regional climate models from 2030 until 2099 under different socio-economic scenarios (IPCC SSP2, SSP3, and SSP5). Quantile mapping bias adjustment was applied to correct future climate data and reduce model biases. Past data revealed that vintages occurred 23.6 % of the years, with an average of two vintage years per decade, with a slightly positive trend. Climate variables such as precipitation in March, air temperatures in April and May, humidity in March and April, solar radiation in March, and meridional wind in June were identified as important factors influencing vintage year occurrence. Machine-learning models were employed to predict vintage years based on the climate variables, with the XGBClassifier achieving the highest performance with 76 %/88 % hits for the vintage/non-vintage classes, respectively, and an ROC score of 0.86, demonstrating strong predictive capabilities. Future climate change scenarios under different socio-economic pathways were assessed, and the results indicated a decrease in the occurrence vintage years until 2099 (10.3 % for SSP2, 9.1 % for SSP3, and 5.8 % for SSP5). The study provides valuable insights into the relationship between climate variables and wine vintage years, enabling winemakers to make informed decisions about vineyard management and grape cultivation. The predictions suggest that climate change may challenge the wine industry, emphasising the need for adaptation strategies

Influence of phospholipid composition on cationic emulsions/DNA complexes: physicochemical properties, cytotoxicity, and transfection on Hep G2 cells

Michelle Fraga1,2, Fernanda Bruxel1, Valeska Lizzi Lagranha2,3, Helder Ferreira Teixeira1, Ursula Matte2,31Post Graduation Program in Pharmaceutical Sciences, Universidade Federal do Rio Grande do Sul, 2Gene Therapy Center, Experimental Research Center, Hospital de Clínicas de Porto Alegre, 3Post Graduation Program in Genetics and Molecular Biology, Universidade Federal do Rio Grande do Sul, Porto Alegre, BrazilBackground: Cationic nanoemulsions have been recently considered as potential delivery systems for nucleic acids. This study reports the influence of phospholipids on the properties of cationic nanoemulsions/DNA plasmid complexes.Methods: Nanoemulsions composed of medium-chain triglycerides, stearylamine, egg lecithin or isolated phospholipids, ie, DSPC, DOPC, DSPE, or DOPE, glycerol, and water were prepared by spontaneous emulsification. Gene transfer to Hep G2 cells was analyzed using real-time polymerase chain reaction.Results: The procedure resulted in monodispersed nanoemulsions with a droplet size and zeta potential of approximately 250 nm and +50 mV, respectively. The complexation of cationic nanoemulsions with DNA plasmid, analyzed by agarose gel retardation assay, was complete when the complex was obtained at a charge ratio of ≥1.0. In these conditions, the complexes were protected from enzymatic degradation by DNase I. The cytotoxicity of the complexes in Hep G2 cells, evaluated by MTT assay, showed that an increasing number of complexes led to progressive toxicity. Higher amounts of reporter DNA were detected for the formulation obtained with the DSPC phospholipid. Complexes containing DSPC and DSPE phospholipids, which have high phase transition temperatures, were less toxic in comparison with the formulations obtained with lecithin, DOPC, and DOPE.Conclusion: The results show the effect of the DNA/nanoemulsion complexes composition on the toxicity and transfection results.Keywords: plasmids, cationic nanoemulsions, phospholipids, physicochemical characterization, gene transfer, stearylamin

Performance of seasonal forecasts for the flowering and veraison of two major Portuguese grapevine varieties

Seasonal phenology forecasts are becoming increasingly demanded by winegrowers and viticulturists. Forecast performance needs to be investigated over space and time before practical applications. We assess seasonal forecast performance (skill, probability and accuracy) in predicting flowering and veraison stages of two representative varieties in Portugal over 1993–2017. The state-of-the-art forecast system ECMWF-SEAS5 provides 7-month seasonal forecasts and is coupled with a locally adapted phenology model. Overall, findings illustrate the dependence of forecast performance on initialization timings, regions and predicting subjects (stages and varieties). Forecast performance improves by delaying the initialization timing and only forecasts initialized on April 1st show better skills than climatology on predicting phenology terciles (early/normal/late). The considerable bias of daily values of seasonal climate predictions can represent the main barrier to accurate forecasts. Better prediction performance is consistently found in Central-Southern regions compared to Northern regions, attributing to an earlier phenology occurrence with a shorter forecast length. Comparable predictive skills between flowering and veraison for both varieties imply better predictability in summer. Consequently, promising seasonal phenology predictions are foreseen in Central-Southern wine regions using forecasts initialized on April 1st with approximately 1–2/3–4 months lead time for flowering/veraison: potential prediction errors are ∼2 weeks, along with an overall moderate forecast skill on categorical events. However, considerable inter-annual variability of forecast performance over the same classified phenology years reflects the substantial influence of climate variability. This may represent the main challenge for reliable forecasts in Mediterranean regions. Recommendations are suggested for methodological innovations and practical applications towards reliable regional phenology forecasts