Essential oil phytocomplex activity, a review with a focus on multivariate analysis for a network pharmacology-informed phytogenomic approach

Thanks to omic disciplines and a systems biology approach, the study of essential oils and phytocomplexes has been lately rolling on a faster track. While metabolomic fingerprinting can provide an effective strategy to characterize essential oil contents, network pharmacology is revealing itself as an adequate, holistic platform to study the collective effects of herbal products and their multi-component and multi-target mediated mechanisms. Multivariate analysis can be applied to analyze the effects of essential oils, possibly overcoming the reductionist limits of bioactivity-guided fractionation and purification of single components. Thanks to the fast evolution of bioinformatics and database availability, disease-target networks relevant to a growing number of phytocomplexes are being developed. With the same potential actionability of pharmacogenomic data, phytogenomics could be performed based on relevant disease-target networks to inform and personalize phytocomplex therapeutic application

Assessing the potential distribution of insect pests: case studies on large pine weevil (Hylobius abietis L) and horse-chestnut leaf miner (Cameraria ohridella) under present and future climate conditions in European forests†

Forest insect pests represent a serious threat to European forests and their negative effects could be exacerbated by climate change. This paper illustrates how species distribution modelling integrated with host tree species distribution data can be used to assess forest vulnerability to this threat. Two case studies are used: large pine weevil (Hylobius abietis L) and horse-chestnut leaf miner (Cameraria ohridella Deschka & Dimic) both at pan-European level. The proposed approach integrates information from different sources. Occurrence data of insect pests were collected from the Global Biodiversity Information Facility (GBIF), climatic variables for present climate and future scenarios were sourced, respectively, from WorldClim and from the Research Program on Climate Change, Agriculture and Food Security (CCAFS), and distributional data of host tree species were obtained from the European Forest Data Centre (EFDAC), within the Forest Information System for Europe (FISE). The potential habitat of the target pests was calculated using the machine learning algorithm of Maxent model. On the one hand, the results highlight the potential of species distribution modelling as a valuable tool for decision makers. On the other hand, they stress how this approach can be limited by poor pest data availability, emphasizing the need to establish a harmonised open European database of geo-referenced insect pest distribution data. Evaluation de la repartition potentielle des insectes nuisibles: etudes de cas sur le grand charancon du pin (Hylobius abietis L.) et sur la mineuse du marronnier (Cameraria ohridella) dans les conditions climatiques actuelles et futures dans les forets europeennes Les insectes nuisibles des forets representent une menace serieuse pour les forets europeennes et leurs effets negatifs pourraient etre aggraves par le changement climatique. Cet article illustre l'utilisation de la modelisation de la repartition des especes, integree aux donnees de repartition des arbres-hotes, pour evaluer la vulnerabilite des forets a cette menace. Deux etudes de cas sont utilisees, toutes deux au niveau paneuropeen, pour le grand charancon du pin (Hylobius abietis L.) et la mineuse du marronnier (Cameraria ohridella Deschka & Dimic). L'approche proposee utilise des informations de differentes sources. Les donnees sur la presence des insectes nuisibles proviennent du service mondial d'information sur la biodiversite ('Global Biodiversity Information Facility', GBIF), les variables climatiques pour le climat actuel et des scenarios futurs ont ete obtenues, respectivement, a partir de WorldClim et du Programme de recherche sur le changement climatique, l'agriculture et la securite alimentaire (CCAFS), et les donnees sur la repartition des arbres-hotes ont ete obtenues aupres du Centre europeen de donnees sur les forets (EFDAC), qui fait partie du systeme d'information forestiere pour l'Europe ('Forest Information System for Europe', FISE). L'habitat potentiel des ravageurs etudies a ete calcule en utilisant l'algorithme d'apprentissage automatique du modele Maxent. D'une part, les resultats indiquent que la modelisation de la repartition des especes peut devenir un outil precieux pour les decideurs. D'autre part, ils indiquent que cette approche peut etre limitee par le manque de donnees sur les organismes nuisibles, renforcant ainsi la necessite de creer une base de donnees europeenne harmonisee et ouverte pour les donnees geo-referencees sur la repartition des insectes nuisibles. Oцeнкa пoтeнциaльнoгo pacпpocтpaнeния вpeдныx нaceкoмыx нa пpимepe бoльшoгo cocнoвoгo дoлгoнocикa (Hylobius abietis L) и лиcтoвoгo минёpa кoнcкoгo кaштaнa (Cameraria ohridella) пpи cyщecтвyющиx и бyдyщиx климaтичecкиx ycлoвияx в eвpoпeйcкиx лeca

Toward Open Science at the European Scale: Geospatial Semantic Array Programming for Integrated Environmental Modelling

[Excerpt] Interfacing science and policy raises challenging issues when large spatial-scale (regional, continental, global) environmental problems need transdisciplinary integration within a context of modelling complexity and multiple sources of uncertainty. This is characteristic of science-based support for environmental policy at European scale, and key aspects have also long been investigated by European Commission transnational research. Approaches (either of computational science or of policy-making) suitable at a given domain-specific scale may not be appropriate for wide-scale transdisciplinary modelling for environment (WSTMe) and corresponding policy-making. In WSTMe, the characteristic heterogeneity of available spatial information and complexity of the required data-transformation modelling (D-TM) appeal for a paradigm shift in how computational science supports such peculiarly extensive integration processes. In particular, emerging wide-scale integration requirements of typical currently available domain-specific modelling strategies may include increased robustness and scalability along with enhanced transparency and reproducibility. This challenging shift toward open data and reproducible research (open science) is also strongly suggested by the potential - sometimes neglected - huge impact of cascading effects of errors within the impressively growing interconnection among domain-specific computational models and frameworks. Concise array-based mathematical formulation and implementation (with array programming tools) have proved helpful in supporting and mitigating the complexity of WSTMe when complemented with generalized modularization and terse array-oriented semantic constraints. This defines the paradigm of Semantic Array Programming (SemAP) where semantic transparency also implies free software use (although black-boxes - e.g. legacy code - might easily be semantically interfaced). A new approach for WSTMe has emerged by formalizing unorganized best practices and experience-driven informal patterns. The approach introduces a lightweight (non-intrusive) integration of SemAP and geospatial tools - called Geospatial Semantic Array Programming (GeoSemAP). GeoSemAP exploits the joint semantics provided by SemAP and geospatial tools to split a complex D-TM into logical blocks which are easier to check by means of mathematical array-based and geospatial constraints. Those constraints take the form of precondition, invariant and postcondition semantic checks. This way, even complex WSTMe may be described as the composition of simpler GeoSemAP blocks. GeoSemAP allows intermediate data and information layers to be more easily and formally semantically described so as to increase fault-tolerance, transparency and reproducibility of WSTMe. This might also help to better communicate part of the policy-relevant knowledge, often diffcult to transfer from technical WSTMe to the science-policy interface. [...

Assessing the role of EO in biodiversity monitoring: options for integrating in-situ observations with EO within the context of the EBONE concept

The European Biodiversity Observation Network (EBONE) is a European contribution on terrestrial monitoring to GEO BON, the Group on Earth Observations Biodiversity Observation Network. EBONE’s aims are to develop a system of biodiversity observation at regional, national and European levels by assessing existing approaches in terms of their validity and applicability starting in Europe, then expanding to regions in Africa. The objective of EBONE is to deliver: 1. A sound scientific basis for the production of statistical estimates of stock and change of key indicators; 2. The development of a system for estimating past changes and forecasting and testing policy options and management strategies for threatened ecosystems and species; 3. A proposal for a cost-effective biodiversity monitoring system. There is a consensus that Earth Observation (EO) has a role to play in monitoring biodiversity. With its capacity to observe detailed spatial patterns and variability across large areas at regular intervals, our instinct suggests that EO could deliver the type of spatial and temporal coverage that is beyond reach with in-situ efforts. Furthermore, when considering the emerging networks of in-situ observations, the prospect of enhancing the quality of the information whilst reducing cost through integration is compelling. This report gives a realistic assessment of the role of EO in biodiversity monitoring and the options for integrating in-situ observations with EO within the context of the EBONE concept (cfr. EBONE-ID1.4). The assessment is mainly based on a set of targeted pilot studies. Building on this assessment, the report then presents a series of recommendations on the best options for using EO in an effective, consistent and sustainable biodiversity monitoring scheme. The issues that we faced were many: 1. Integration can be interpreted in different ways. One possible interpretation is: the combined use of independent data sets to deliver a different but improved data set; another is: the use of one data set to complement another dataset. 2. The targeted improvement will vary with stakeholder group: some will seek for more efficiency, others for more reliable estimates (accuracy and/or precision); others for more detail in space and/or time or more of everything. 3. Integration requires a link between the datasets (EO and in-situ). The strength of the link between reflected electromagnetic radiation and the habitats and their biodiversity observed in-situ is function of many variables, for example: the spatial scale of the observations; timing of the observations; the adopted nomenclature for classification; the complexity of the landscape in terms of composition, spatial structure and the physical environment; the habitat and land cover types under consideration. 4. The type of the EO data available varies (function of e.g. budget, size and location of region, cloudiness, national and/or international investment in airborne campaigns or space technology) which determines its capability to deliver the required output. EO and in-situ could be combined in different ways, depending on the type of integration we wanted to achieve and the targeted improvement. We aimed for an improvement in accuracy (i.e. the reduction in error of our indicator estimate calculated for an environmental zone). Furthermore, EO would also provide the spatial patterns for correlated in-situ data. EBONE in its initial development, focused on three main indicators covering: (i) the extent and change of habitats of European interest in the context of a general habitat assessment; (ii) abundance and distribution of selected species (birds, butterflies and plants); and (iii) fragmentation of natural and semi-natural areas. For habitat extent, we decided that it did not matter how in-situ was integrated with EO as long as we could demonstrate that acceptable accuracies could be achieved and the precision could consistently be improved. The nomenclature used to map habitats in-situ was the General Habitat Classification. We considered the following options where the EO and in-situ play different roles: using in-situ samples to re-calibrate a habitat map independently derived from EO; improving the accuracy of in-situ sampled habitat statistics, by post-stratification with correlated EO data; and using in-situ samples to train the classification of EO data into habitat types where the EO data delivers full coverage or a larger number of samples. For some of the above cases we also considered the impact that the sampling strategy employed to deliver the samples would have on the accuracy and precision achieved. Restricted access to European wide species data prevented work on the indicator ‘abundance and distribution of species’. With respect to the indicator ‘fragmentation’, we investigated ways of delivering EO derived measures of habitat patterns that are meaningful to sampled in-situ observations

Perinatal care in SARS-CoV-2 infected women: the lesson learnt from a national prospective cohort study during the pandemic in Italy

Background: Despite the growing importance given to ensuring high-quality childbirth, perinatal good practices have been rapidly disrupted by SARS-CoV-2 pandemic. This study aimed at describing the childbirth care provided to infected women during two years of COVID-19 emergency in Italy. Methods: A prospective cohort study enrolling all women who gave birth with a confirmed SARS-CoV-2 infection within 7 days from hospital admission in the 218 maternity units active in Italy during the periods February 25, 2020-June 30, 2021, and January 1-May 31, 2022. Perinatal care was assessed by evaluating the prevalence of the following indicators during the pandemic: presence of a labour companion; skin-to-skin; no mother-child separation at birth; rooming-in; breastfeeding. Logistic regression models including women' socio-demographic, obstetric and medical characteristics, were used to assess the association between the adherence to perinatal practices and different pandemic phases. Results: During the study period, 5,360 SARS-CoV-2 positive women were enrolled. Overall, among those who had a vaginal delivery (n = 3,574; 66.8%), 37.5% had a labour companion, 70.5% of newborns were not separated from their mothers at birth, 88.1% were roomed-in, and 88.0% breastfed. These four indicators showed similar variations in the study period with a negative peak between September 2020 and January 2021 and a gradual increase during the Alpha and Omicron waves. Skin-to-skin (mean value 66.2%) had its lowest level at the beginning of the pandemic and gradually increased throughout the study period. Among women who had a caesarean section (n = 1,777; 33.2%), all the indicators showed notably worse outcomes with similar variations in the study period. Multiple logistic regression analyses confirm the observed variations during the pandemic and show a lower adherence to good practices in southern regions and in maternity units with a higher annual number of births. Conclusions: Despite the rising trend in the studied indicators, we observed concerning substandard childbirth care during the SARS-CoV-2 pandemic. Continued efforts are necessary to underscore the significance of the experience of care as a vital component in enhancing the quality of family-centred care policies

Impacts of soil conditions and light availability on natural regeneration of Norway spruce Picea abies (L.) H. Karst. in low-elevation mountain forests

& Key message Natural regeneration of P. abies (L.) H. Karst. may reach high densities in lower mountain elevations. The highest densities were found in sites with moderate light availability, with low pH, and not near the riverbank. However, age-height classes differed in the predicted magnitude of response, but were consistent in response directions. Mosses and understory species typical of coniferous forests were positively correlated with regeneration density. & Context Norway spruce Picea abies (L.) H. Karst. in Central Europe is at risk under climate change scenarios, particularly in mountain regions. Little is known about the impact of environmental factors on the natural regeneration of P. abies in lowelevation mountain forests. & Aims We aimed to assess impacts of distance from the riverbank, soil pH, and light availability on natural P. abies regeneration. We hypothesized that (1) natural P. abiesregeneration would depend on light availability and soil pH and (2) there are understory plant species which may indicate the microsites suitable for natural regeneration of P. abies. & Methods The study was conducted in the Stołowe Mountains National Park (SW Poland, 600–800 m a.s.l.). We established 160 study plots (25 m2 ) for natural regeneration, light availability, soil pH, and understory vegetation assessment

Chorological data for the main European woody species

The data are organized as a set of ESRI shapefiles (*.shp, *.shx, *.dbf, *.prj files) mapping the distribution ranges of the main European tree and shrub species. For each species and in some cases subspecies, one or more shapefiles have been created containing: a) polygon features (name suffix “plg”), which define continuous areas of occupancy of the species range and b) point features (name suffix “pnt”), which identify more fragmented and isolated populations. For species with reported synanthropic occurrences outside the natural range, an additional point and/or polygon shapefile has also been created (suffix “syn”). Polygon borders delimiting species ranges are generalized across the mainland and sea boundaries. This offers the possibility to mask sea areas or to clip and extract the terrestrial range parts using GIS data layers of the users' choice. An additional version of polygon ranges are clipped with a coastline (name suffix “clip”), which have been derived from Natural Earth dataset "Admin 0 - Countries" 1:50M version 4.1.0 (https://www.naturalearthdata.com). Finally, an accompanying text document is included with the data, which provides more details on methodology and a list of all mapped species with related file names, taxonomical delimitation of the mapped species and references used to compile the respective chorological dataset

Chorological data for the main European woody species

The data are organized as a set of ESRI shapefiles (*.shp, *.shx, *.dbf, *.prj files) mapping the distribution ranges of the main European tree and shrub species. For each species and in some cases subspecies, one or more shapefiles have been created containing: a) polygon features (name suffix “plg”), which define continuous areas of occupancy of the species range and b) point features (name suffix “pnt”), which identify more fragmented and isolated populations. For species with reported synanthropic occurrences outside the natural range, an additional point and/or polygon shapefile has also been created (suffix “syn”). Polygon borders delimiting species ranges are generalized across the mainland and sea boundaries. This offers the possibility to mask sea areas or to clip and extract the terrestrial range parts using GIS data layers of the users' choice. An additional version of polygon ranges are clipped with a coastline (name suffix “clip”), which have been derived from Natural Earth dataset "Admin 0 - Countries" 1:50M version 4.1.0 (https://www.naturalearthdata.com). Finally, an accompanying text document is included with the data, which provides more details on methodology and a list of all mapped species with related file names, taxonomical delimitation of the mapped species and references used to compile the respective chorological dataset

Chorological data for the main European woody species

The data are organized as a set of ESRI shapefiles (*.shp, *.shx, *.dbf, *.prj files) mapping the distribution ranges of the main European tree and shrub species. For each species and in some cases subspecies, one or more shapefiles have been created containing: a) polygon features (name suffix “plg”), which define continuous areas of occupancy of the species range and b) point features (name suffix “pnt”), which identify more fragmented and isolated populations. For species with reported synanthropic occurrences outside the natural range, an additional point and/or polygon shapefile has also been created (suffix “syn”). Polygon borders delimiting species ranges are generalized across the mainland and sea boundaries. This offers the possibility to mask sea areas or to clip and extract the terrestrial range parts using GIS data layers of the users' choice. An additional version of polygon ranges are clipped with a coastline (name suffix “clip”), which have been derived from Natural Earth dataset "Admin 0 - Countries" 1:50M version 4.1.0 (https://www.naturalearthdata.com). Finally, an accompanying text document is included with the data, which provides more details on methodology and a list of all mapped species with related file names, taxonomical delimitation of the mapped species and references used to compile the respective chorological dataset

Chorological data for the main European woody species

The data are organized as a set of ESRI shapefiles (*.shp, *.shx, *.dbf, *.prj files) mapping the distribution ranges of the main European tree and shrub species. For each species and in some cases subspecies, one or more shapefiles have been created containing: a) polygon features (name suffix “plg”), which define continuous areas of occupancy of the species range and b) point features (name suffix “pnt”), which identify more fragmented and isolated populations. For species with reported synanthropic occurrences outside the natural range, an additional point and/or polygon shapefile has also been created (suffix “syn”). Polygon borders delimiting species ranges are generalized across the mainland and sea boundaries. This offers the possibility to mask sea areas or to clip and extract the terrestrial range parts using GIS data layers of the users' choice. An additional version of polygon ranges are clipped with a coastline (name suffix “clip”), which have been derived from Natural Earth dataset "Admin 0 - Countries" 1:50M version 4.1.0 (https://www.naturalearthdata.com). Finally, an accompanying text document is included with the data, which provides more details on methodology and a list of all mapped species with related file names, taxonomical delimitation of the mapped species and references used to compile the respective chorological dataset