Ecological and methodological drivers of species' distribution and phenology responses to climate change

Climate change is shifting species’ distribution and phenology. Ecological traits, such as mobility or reproductive mode, explain variation in observed rates of shift for some taxa. However, estimates of relationships between traits and climate responses could be influenced by how responses are measured. We compiled a global data set of 651 published marine species’ responses to climate change, from 47 papers on distribution shifts and 32 papers on phenology change. We assessed the relative importance of two classes of predictors of the rate of change, ecological traits of the responding taxa and methodological approaches for quantifying biological responses. Methodological differences explained 22% of the variation in range shifts, more than the 7.8% of the variation explained by ecological traits. For phenology change, methodological approaches accounted for 4% of the variation in measurements, whereas 8% of the variation was explained by ecological traits. Our ability to predict responses from traits was hindered by poor representation of species from the tropics, where temperature isotherms are moving most rapidly. Thus, the mean rate of distribution change may be underestimated by this and other global syntheses. Our analyses indicate that methodological approaches should be explicitly considered when designing, analysing and comparing results among studies. To improve climate impact studies, we recommend that (1) reanalyses of existing time series state how the existing data sets may limit the inferences about possible climate responses; (2) qualitative comparisons of species’ responses across different studies be limited to studies with similar methodological approaches; (3) meta-analyses of climate responses include methodological attributes as covariates; and (4) that new time series be designed to include the detection of early warnings of change or ecologically relevant change. Greater consideration of methodological attributes will improve the accuracy of analyses that seek to quantify the role of climate change in species’ distribution and phenology changes

Strengthening confidence in climate change impact science

Aim: To assess confidence in conclusions about climate-driven biological change through time, and identify approaches for strengthening confidence scientific conclusions about ecological impacts of climate change. Location: Global. Methods: We outlined a framework for strengthening confidence in inferences drawn from biological climate impact studies through the systematic integration of prior expectations, long-term data and quantitative statistical procedures. We then developed a numerical confidence index (Cindex) and used it to evaluate current practices in 208 studies of marine climate impacts comprising 1735 biological time series. Results: Confidence scores for inferred climate impacts varied widely from 1 to 16 (very low to high confidence). Approximately 35% of analyses were not associated with clearly stated prior expectations and 65% of analyses did not test putative non-climate drivers of biological change. Among the highest-scoring studies, 91% tested prior expectations, 86% formulated expectations for alternative drivers but only 63% statistically tested them. Higher confidence scores observed in studies that did not detect a change or tracked multiple species suggest publication bias favouring impact studies that are consistent with climate change. The number of time series showing climate impacts was a poor predictor of average confidence scores for a given group, reinforcing that vote-counting methodology is not appropriate for determining overall confidence in inferences. Main conclusions: Climate impacts research is expected to attribute biological change to climate change with measurable confidence. Studies with long-term, high-resolution data, appropriate statistics and tests of alternative drivers earn higher Cindex scores, suggesting these should be given greater weight in impact assessments. Together with our proposed framework, the results of our Cindex analysis indicate how the science of detecting and attributing biological impacts to climate change can be strengthened through the use of evidence-based prior expectations and thorough statistical analyses, even when data are limited, maximizing the impact of the diverse and growing climate change ecology literature

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Tracking of fatness during childhood, adolescence and young adulthood: a 7-year follow-up study in Madeira Island, Portugal

Aims: Investigating tracking of fatness from childhood to adolescence, early adolescence to young adulthood and late adolescence to young adulthood. Subjects and methods: Participants from the Madeira Growth Study were followed during an average period of 7.2 years. Height, body mass, skin-folds and circumferences were measured, nine health- and performance-related tests were administered and the Baecke questionnaire was used to assess physical activity. Skeletal maturity was estimated using the TW3 method. Results: The prevalence of overweight plus obesity ranged from 8.2–20.0% at baseline and from 20.4–40.0% at followup, in boys. Corresponding percentages for girls were 10.6– 12.0% and 13.2–18.0%. Inter-age correlations for fatness indicators ranged from 0.43–0.77. BMI, waist circumference and sum of skin-folds at 8, 12 and 16-years old were the main predictors of these variables at 15, 19 and 23-years old, respectively. Strength, muscular endurance and aerobic fitness were negatively related to body fatness. Physical activity and maturation were independently associated with adolescent (15 years) and young adult (19 years) fatness. Conclusions: Over 7.2 years, tracking was moderate-to-high for fatness. Variance was explained by fatness indicators and to a small extent by physical fitness, physical activity and maturation

The JCMT Gould Belt Survey: A first look at Southern Orion A with SCUBA-2

This is the author accepted manuscript. The final version is available from OUP via the DOI in this record.We present the JCMT Gould Belt Survey's first look results of the southern extent of the Orion A Molecular Cloud ( δ ≤ -5:31:27.5). Employing a two-step structure identification process, we construct individual catalogues for large-scale regions of significant emission labelled as islands and smaller-scale subregions called fragments using the 850 μm continuum maps obtained using SCUBA-2. We calculate object masses, sizes, column densities, and concentrations. We discuss fragmentation in terms of a Jeans instability analysis and highlight interesting structures as candidates for follow-up studies. Furthermore, we associate the detected emission with young stellar objects (YSOs) identified by Spitzer and Herschel. We find that although the population of active star-forming regions contains a wide variety of sizes and morphologies, there is a strong positive correlation between the concentration of an emission region and its calculated Jeans instability. There are, however, a number of highly unstable subregions in dense areas of the map that show no evidence of star formation. We find that only ~72 per cent of the YSOs defined as Class 0+I and flat-spectrum protostars coincide with dense 850 μm emission structures (column densities > 3.7 × 1021 cm-2). The remaining 28 per cent of these objects, which are expected to be embedded in dust and gas, may be misclassified. Finally, we suggest that there is an evolution in the velocity dispersion of YSOs such that sources which are more evolved are associated with higher velocities.Steve Mairs was partially supported by the Natural Sciences and Engineering Research Council (NSERC) of Canada graduate scholarship programme. Doug Johnstone is supported by the National Research Council of Canada and by an NSERC Discovery Grant

Timeless standards for species delimitation

published_or_final_versio

Performance of CMS muon reconstruction in pp collision events at sqrt(s) = 7 TeV

The performance of muon reconstruction, identification, and triggering in CMS has been studied using 40 inverse picobarns of data collected in pp collisions at sqrt(s) = 7 TeV at the LHC in 2010. A few benchmark sets of selection criteria covering a wide range of physics analysis needs have been examined. For all considered selections, the efficiency to reconstruct and identify a muon with a transverse momentum pT larger than a few GeV is above 95% over the whole region of pseudorapidity covered by the CMS muon system, abs(eta) < 2.4, while the probability to misidentify a hadron as a muon is well below 1%. The efficiency to trigger on single muons with pT above a few GeV is higher than 90% over the full eta range, and typically substantially better. The overall momentum scale is measured to a precision of 0.2% with muons from Z decays. The transverse momentum resolution varies from 1% to 6% depending on pseudorapidity for muons with pT below 100 GeV and, using cosmic rays, it is shown to be better than 10% in the central region up to pT = 1 TeV. Observed distributions of all quantities are well reproduced by the Monte Carlo simulation.Comment: Replaced with published version. Added journal reference and DO

Performance of CMS muon reconstruction in pp collision events at sqrt(s) = 7 TeV

The performance of muon reconstruction, identification, and triggering in CMS has been studied using 40 inverse picobarns of data collected in pp collisions at sqrt(s) = 7 TeV at the LHC in 2010. A few benchmark sets of selection criteria covering a wide range of physics analysis needs have been examined. For all considered selections, the efficiency to reconstruct and identify a muon with a transverse momentum pT larger than a few GeV is above 95% over the whole region of pseudorapidity covered by the CMS muon system, abs(eta) < 2.4, while the probability to misidentify a hadron as a muon is well below 1%. The efficiency to trigger on single muons with pT above a few GeV is higher than 90% over the full eta range, and typically substantially better. The overall momentum scale is measured to a precision of 0.2% with muons from Z decays. The transverse momentum resolution varies from 1% to 6% depending on pseudorapidity for muons with pT below 100 GeV and, using cosmic rays, it is shown to be better than 10% in the central region up to pT = 1 TeV. Observed distributions of all quantities are well reproduced by the Monte Carlo simulation.Comment: Replaced with published version. Added journal reference and DO

Circulating microparticles: square the circle

Background: The present review summarizes current knowledge about microparticles (MPs) and provides a systematic overview of last 20 years of research on circulating MPs, with particular focus on their clinical relevance. Results: MPs are a heterogeneous population of cell-derived vesicles, with sizes ranging between 50 and 1000 nm. MPs are capable of transferring peptides, proteins, lipid components, microRNA, mRNA, and DNA from one cell to another without direct cell-to-cell contact. Growing evidence suggests that MPs present in peripheral blood and body fluids contribute to the development and progression of cancer, and are of pathophysiological relevance for autoimmune, inflammatory, infectious, cardiovascular, hematological, and other diseases. MPs have large diagnostic potential as biomarkers; however, due to current technological limitations in purification of MPs and an absence of standardized methods of MP detection, challenges remain in validating the potential of MPs as a non-invasive and early diagnostic platform. Conclusions: Improvements in the effective deciphering of MP molecular signatures will be critical not only for diagnostics, but also for the evaluation of treatment regimens and predicting disease outcomes

Study of hadronic event-shape variables in multijet final states in pp collisions at √s=7 TeV

Peer reviewe