Phenological shifts of abiotic events, producers and consumers across a continent

Ongoing climate change can shift organism phenology in ways that vary depending on species, habitats and climate factors studied. To probe for large-scale patterns in associated phenological change, we use 70,709 observations from six decades of systematic monitoring across the former Union of Soviet Socialist Republics. Among 110 phenological events related to plants, birds, insects, amphibians and fungi, we find a mosaic of change, defying simple predictions of earlier springs, later autumns and stronger changes at higher latitudes and elevations. Site mean temperature emerged as a strong predictor of local phenology, but the magnitude and direction of change varied with trophic level and the relative timing of an event. Beyond temperature-associated variation, we uncover high variation among both sites and years, with some sites being characterized by disproportionately long seasons and others by short ones. Our findings emphasize concerns regarding ecosystem integrity and highlight the difficulty of predicting climate change outcomes. The authors use systematic monitoring across the former USSR to investigate phenological changes across taxa. The long-term mean temperature of a site emerged as a strong predictor of phenological change, with further imprints of trophic level, event timing, site, year and biotic interactions.Peer reviewe

Chronicles of nature calendar, a long-term and large-scale multitaxon database on phenology

We present an extensive, large-scale, long-term and multitaxon database on phenological and climatic variation, involving 506,186 observation dates acquired in 471 localities in Russian Federation, Ukraine, Uzbekistan, Belarus and Kyrgyzstan. The data cover the period 1890-2018, with 96% of the data being from 1960 onwards. The database is rich in plants, birds and climatic events, but also includes insects, amphibians, reptiles and fungi. The database includes multiple events per species, such as the onset days of leaf unfolding and leaf fall for plants, and the days for first spring and last autumn occurrences for birds. The data were acquired using standardized methods by permanent staff of national parks and nature reserves (87% of the data) and members of a phenological observation network (13% of the data). The database is valuable for exploring how species respond in their phenology to climate change. Large-scale analyses of spatial variation in phenological response can help to better predict the consequences of species and community responses to climate change.Peer reviewe

Eurasian Chronicle of Nature as a basis for large-scale analysis of changing ecosystems.

At present, the study of the consequences of global climate change on ecosystems has become particularly relevant. "Chronicles of Nature" is a unique monitoring program unmatched in geographical (former USSR) and temporal scale (from early 1900s and still ongoing in most locations), that accumulated mostly on paper until early 2000s with no coordinated attempt to compile it in a common format. It has become the basis for international cooperation since 2011 in the framework of ECN project led by the University of Helsinki. ECN: Eurasian Chronicle of Nature - Large Scale Analysis of Changing Ecosystems, it has more than 450 participants (researchers) representing 176 organizations from 12 countries including 114 PAs, 34 research institutes, 15 universities, and ministries and departments for environmental protection. The compilation of the data into a common database was conducted by the database coordinators. Large-scale and long-term dataset currently processed that can be used to examine community-level spatial variation in phenological dynamics and its climatic drivers. The database consist of 401,127 observation dates collected in 239 localities in Russia, Ukraine, Belarus, Latvia, Lithuania and Estonia, with the longest time series of 115 years - from 1899 to 2014. In addition to phenological data, we compile the long-term population data of mammals and birds and other types of surveys included "Сhronicle of nature". From the very beginning, the project had the task of forming an international network of cooperation and provided for the creation of a database for the mass counting of mammals (including small ones), birds, invertebrates, the dynamics of abundance and diversity of vascular plants and fungi, hunting statistics, meteorological factors, forest cover and phenology . The area of research is biomes of the Eurasian taiga - from Scandinavia to the Urals and further to the coast of the Pacific Ocean. It is assumed, that the database will reflect the environmental changes that have occurred in the ecosystem of boreal forests over the last 50-100 years (including taking into account the monitoring of anthropogenic dynamics of the forest structure occurring against the backdrop of climate change). Data processing is based on developments of the Group of Mathematical Biology of the University of Helsinki. The main work of the Group focuses on the interaction between theoretical and empirical research in spatial and evolutionary biology. The group developed a wide range of mathematical, statistical and computational methods for analyzing the movement of species inhabiting diverse landscapes, with special emphasis on the survival of populations. The existing experience of joint research allows us to speak about the special importance of monitoring works within the "Chronicles of nature" of PAs, and the significance of this work grows in proportion to the duration of observations.peerReviewe

Raman Spectroscopy Study of Structurally Uniform Hydrogenated Oligomers of α-Olefins

The expansion of the range of physico-chemical methods in the study of industrially significant α-olefin oligomers and polymers is of particular interest. In our article, we present a comparative Raman study of structurally uniform hydrogenated dimers, trimers, tetramers, and pentamers of 1-hexene and 1-octene, that are attractive as bases for freeze-resistant engine oils and lubricants. We found out that the joint monitoring of the disorder longitudinal acoustic mode (D-LAM) and symmetric C–C stretching modes allows the quantitative characterization of the number and length of alkyl chains (i.e., two structural characteristics), upon which the pour point and viscosity of the hydrocarbons depend, and to distinguish these compounds from both each other and linear alkanes. We demonstrated that the ratio of the contents of CH2 and CH3 groups in these hydrocarbons can be determined by using the intensities of the bands in the spectra, related to the asymmetric stretching vibrations of these groups. The density functional theory (DFT) calculations were applied to reveal the relations between the wavenumber and bandshape of the symmetric C–C stretching mode and a conformation arrangement of the 1-hexene and 1-octene dimers. We found that the branched double-chain conformation results in the splitting of the C–C mode into two components with the wavenumbers, which can be used as a measure of the length of branches. This conformation is preferable to the extended-chain conformation for hydrogenated 1-hexene and 1-octene dimers

Single-crystal sapphire microstructure for high-resolution synchrotron X-ray monochromators

We report on the growth and characterization of sapphire single crystals for X-ray optics applications. Structural defects were studied by means of laboratory double-crystal X-ray diffractometry and white-beam synchrotron-radiation topography. The investigations confirmed that the main defect types are dislocations. The best quality crystal was grown using the Kyropoulos technique. Therein the dislocation density was 102–103 cm−2 and a small area with approximately 2*2 mm2 did not show dislocation contrast in many reflections. This crystal has suitable quality for application as a backscattering monochromator. A clear correlation between growth rate and dislocation density is observed, though growth rate is not the only parameter impacting the quality

Differences in spatial versus temporal reaction norms for spring and autumn phenological events

For species to stay temporally tuned to their environment, they use cues such as the accumulation of degree-days. The relationships between the timing of a phenological event in a population and its environmental cue can be described by a population-level reaction norm. Variation in reaction norms along environmental gradients may either intensify the environmental effects on timing (cogradient variation) or attenuate the effects (countergradient variation). To resolve spatial and seasonal variation in species' response, we use a unique dataset of 91 taxa and 178 phenological events observed across a network of 472 monitoring sites, spread across the nations of the former Soviet Union. We show that compared to local rates of advancement of phenological events with the advancement of temperature-related cues (i.e., variation within site over years), spatial variation in reaction norms tend to accentuate responses in spring (cogradient variation) and attenuate them in autumn (countergradient variation). As a result, among-population variation in the timing of events is greater in spring and less in autumn than if all populations followed the same reaction norm regardless of location. Despite such signs of local adaptation, overall phenotypic plasticity was not sufficient for phenological events to keep exact pace with their cues-the earlier the year, the more did the timing of the phenological event lag behind the timing of the cue. Overall, these patterns suggest that differences in the spatial versus temporal reaction norms will affect species' response to climate change in opposite ways in spring and autumn

Enhancement of COPD biological networks using a web-based collaboration interface

The construction and application of biological network models is an approach that offers a holistic way to understand biological processes involved in disease. Chronic obstructive pulmonary disease (COPD) is a progressive inflammatory disease of the airways for which therapeutic options currently are limited after diagnosis, even in its earliest stage. COPD network models are important tools to better understand the biological components and processes underlying initial disease development. With the increasing amounts of literature that are now available, crowdsourcing approaches offer new forms of collaboration for researchers to review biological findings, which can be applied to the construction and verification of complex biological networks. We report the construction of 50 biological network models relevant to lung biology and early COPD using an integrative systems biology and collaborative crowd-verification approach. By combining traditional literature curation with a data-driven approach that predicts molecular activities from transcriptomics data, we constructed an initial COPD network model set based on a previously published non-diseased lung-relevant model set. The crowd was given the opportunity to enhance and refine the networks on a website (https://bionet.sbvimprover.com/) and to add mechanistic detail, as well as critically review existing evidence and evidence added by other users, so as to enhance the accuracy of the biological representation of the processes captured in the networks. Finally, scientists and experts in the field discussed and refined the networks during an in-person jamboree meeting. Here, we describe examples of the changes made to three of these networks: Neutrophil Signaling, Macrophage Signaling, and Th1-Th2 Signaling. We describe an innovative approach to biological network construction that combines literature and data mining and a crowdsourcing approach to generate a comprehensive set of COPD-relevant models that can be used to help understand the mechanisms related to lung pathobiology. Registered users of the website can freely browse and download the networks

Original networks, NVC networks and COPD data sets used in: Enhancement of COPD biological networks using a web-based collaboration interface

<p>Original networks, NVC networks and their descriptions.<br>The file contains the names of the original networks (as they were published), agglomerated NVC networks (as presented on the Bionet website), and network descriptions. The 15 networks that were discussed during jamboree are indicated by “X” in the column Discussed in Jamboree.</p> <p>COPD data sets, their descriptions, and the comparisons used to build the COPD models during Phase 1.<br>Reverse causal reasoning was performed using COPD and emphysema data sets from lung, small airway, and alveolar macrophages of early COPD patients and healthy smokers. Data Sets, the Gene Expression Omnibus (GEO) used to build the COPD networks. SCs, state changes defined using differentially expressed genes that meet the following criteria: FDR adjusted p<0.05, fold change ≥1.3, and minimum expression of 100 (for Affy platforms). HYPs, mechanisms or hypotheses predicted from the SCs and the Selventa Knowledgebase [1] with the following cutoffs: richness p<0.1, concordance p<0.1.</p> <p>Early COPD was defined as Global Initiative for Chronic Obstructive Lung Disease (GOLD) stages 1 and 2.<br>The three small airway data sets were merged using ComBat [2] because of the small sample size of early COPD patients within each data set.<br>Lone emphysema is defined in the GSE10006 data set as patients who have normal spirometry but decreased transfer factor and evidence of emphysema on chest computed tomography scans. The lone emphysema data were selected because they might be useful in understanding COPD onset.</p> <p>References<br>1. Catlett NL, Bargnesi AJ, Ungerer S, Seagaran T, Ladd W, Elliston KO, Pratt D: Reverse causal reasoning: applying qualitative causal knowledge to the interpretation of high-throughput data. BMC bioinformatics 2013, 14:340.<br>2. Chen C, Grennan K, Badner J, Zhang D, Gershon E, Jin L, Liu C: Removing batch effects in analysis of expression microarray data: an evaluation of six batch adjustment methods. PloS one 2011, 6:e17238.</p> <p> </p