Metadata Made Easy: Develop and Use Domain‐Specific Metadata Schemes by following the dmdScheme approach

Metadata plays an essential role in the long-term preservation, reuse, and interoperability of data. Nevertheless, creating useful metadata can be sufficiently difficult and weakly enough incentivized that many datasets may be accompanied by little or no metadata. One key challenge is, therefore, how to make metadata creation easier and more valuable. We present a solution that involves creating domain-specific metadata schemes that are as complex as necessary and as simple as possible. These goals are achieved by co-development between a metadata expert and the researchers (i.e., the data creators). The final product is a bespoke metadata scheme into which researchers can enter information (and validate it) via the simplest of interfaces: a web browser application and a spreadsheet.We provide the R package dmdScheme (dmdScheme: An R package for working with domain specific MetaData schemes (Version v0.9.22), 2019) for creating a template domain-specific scheme. We describe how to create a domain-specific scheme from this template, including the iterative co-development process, and the simple methods for using the scheme, and simple methods for quality assessment, improvement, and validation.The process of developing a metadata scheme following the outlined approach was successful, resulting in a metadata scheme which is used for the data generated in our research group. The validation quickly identifies forgotten metadata, as well as inconsistent metadata, therefore improving the quality of the metadata. Multiple output formats are available, including XML.Making the provision of metadata easier while also ensuring high quality must be a priority for data curation initiatives. We show how both objectives are achieved by close collaboration between metadata experts and researchers to create domain-specific schemes. A near-future priority is to provide methods to interface domain-specific schemes with general metadata schemes, such as the Ecological Metadata Language, to increase interoperability

Transition to adult services for children and young people with palliative care needs: a systematic review.

Objective: To evaluate the evidence on the transition process from child to adult services for young people with palliative care needs. Design: Systematic review Setting: Child and adult services and interface between healthcare providers. Patients: Young people aged 13 to 24 years with palliative care conditions in the process of transition. Main outcome measures: Young people and their families’ experiences of transition, the process of transition between services and its impact on continuity of care, and models of good practice. Results: 92 studies included. Papers on transition services were of variable quality when applied to palliative care contexts. Most focused on common life threatening and life limiting conditions. No standardised transition programme identified and most guidelines used to develop transition services were not evidence based. Most studies on transition programmes were predominantly condition-specific (e.g. cystic fibrosis, cancer) services. Cystic fibrosis services offered high quality transition with the most robust empirical evaluation. There were differing condition-dependent viewpoints on when transition should occur but agreement on major principles guiding transition planning and probable barriers. There was evidence of poor continuity between child and adult providers with most originating from within child settings. Conclusions: Palliative care was not, in itself, a useful concept for locating transition-related evidence. It is not possible to evaluate the merits of the various transition models for palliative care contexts, or their effects on continuity of care, as there are no long-term outcome data to measure their effectiveness. Use of validated outcome measures would facilitate research and service development

Past major tsunamis and the level of tsunami risk on the Aitape coast of Papua New Guinea

This paper reports the results of an investigation into past major tsunamis on the Aitape coast of Papua New Guinea. The investigation was mounted to gather information to help assess the level of ongoing tsunami risk, in the aftermath of a catastrophic tsunami that struck this coast in 1998. We found that local residents have a strong oral tradition of a great tsunami at some time in the past, date unknown. A possible geological record of past major tsunamis was found in a submerged rock face that comprised clay-rich mudstone with three centimetric interbeds of peat, two of which contained coarse detrital sediment of marine origin. The topmost peat contained much marine detrital sediment, some of it very coarse (pebbles to 4 cm), and was dated at around AD 1440–1600. The second peat contained a much smaller proportion of detrital sediment, finer sediment than was in the topmost, and was dated at around AD 1150–1240. The lowermost peat was dated at around AD 980–1050. The two occurrences of coarse detrital sediments are presumed to be a record of past marine incursions into coastal swamps, probably as tsunamis or possibly as storm waves. The more recent, and more energetic, incursion, at around AD 1440–1600, was very likely the great tsunami of legend. In the thousand years recorded in the submerged rock face, there have been, at most, three major tsunamis, at approximate intervals of 300–500 years.We thank the Australian aid program for a grant which covered the cost of drilling

Vital evidence: Change in the marine ¹⁴C reservoir around New Zealand (Aotearoa) and implications for the timing of Polynesian settlement.

Precise and accurate radiocarbon chronologies are essential to achieve tight chronological control for the ~ 750-years since Polynesian settlement of New Zealand. This goal has, however, been elusive. While radiocarbon datasets in the region are typically dominated by marine and estuarine shell dates, such chronological information has been ignored by those interpreting the timing of key events because a detailed regional calibration methodology for marine shell, comparable to the highly precise Southern Hemisphere calibration curve, is lacking. In this paper, we present the first temporal ¹⁴C marine offset (ΔR) model for New Zealand based on paired estuarine/marine and terrestrial radiocarbon dates from 52 archaeological contexts. Our dataset displays significant offsets between the measured New Zealand data and the modelled global marine radiocarbon curve. These shifts are associated with oceanographic fluctuation at the onset of the Little Ice Age ~ AD 1350-1450 (650-500 BP). The application of a regional and temporal correction to archaeological shell dates provides complimentary information to terrestrial radiocarbon production and has the potential to add structure to the blurred chronology that has plagued archaeological theories about the colonization of New Zealand, and other Pacific islands, for decades

Dynamic species classification of microorganisms across time, abiotic and biotic environments-A sliding window approach.

The development of video-based monitoring methods allows for rapid, dynamic and accurate monitoring of individuals or communities, compared to slower traditional methods, with far reaching ecological and evolutionary applications. Large amounts of data are generated using video-based methods, which can be effectively processed using machine learning (ML) algorithms into meaningful ecological information. ML uses user defined classes (e.g. species), derived from a subset (i.e. training data) of video-observed quantitative features (e.g. phenotypic variation), to infer classes in subsequent observations. However, phenotypic variation often changes due to environmental conditions, which may lead to poor classification, if environmentally induced variation in phenotypes is not accounted for. Here we describe a framework for classifying species under changing environmental conditions based on the random forest classification. A sliding window approach was developed that restricts temporal and environmentally conditions to improve the classification. We tested our approach by applying the classification framework to experimental data. The experiment used a set of six ciliate species to monitor changes in community structure and behavior over hundreds of generations, in dozens of species combinations and across a temperature gradient. Differences in biotic and abiotic conditions caused simplistic classification approaches to be unsuccessful. In contrast, the sliding window approach allowed classification to be highly successful, as phenotypic differences driven by environmental change, could be captured by the classifier. Importantly, classification using the random forest algorithm showed comparable success when validated against traditional, slower, manual identification. Our framework allows for reliable classification in dynamic environments, and may help to improve strategies for long-term monitoring of species in changing environments. Our classification pipeline can be applied in fields assessing species community dynamics, such as eco-toxicology, ecology and evolutionary ecology

Inferring community assembly processes from macroscopic patterns using dynamic eco-evolutionary models and Approximate Bayesian Computation (ABC)

Statistical techniques exist for inferring community assembly processes from community patterns. Habitat filtering, competition, and biogeographical effects have, for example, been inferred from signals in phenotypic and phylogenetic data. The usefulness of current inference techniques is, however, debated as a mechanistic and causal link between process and pattern is often lacking, and evolutionary processes and trophic interactions are ignored. Here, we revisit the current knowledge on community assembly across scales and, in line with several reviews that have outlined challenges associated with current inference techniques, we identify a discrepancy between the current paradigm of eco-evolutionary community assembly and current inference techniques that focus mainly on competition and habitat filtering. We argue that trait-based dynamic eco-evolutionary models in combination with recently developed model fitting and model evaluation techniques can provide avenues for more accurate, reliable, and inclusive inference. To exemplify, we implement a trait-based, spatially explicit eco-evolutionary model and discuss steps of model modification, fitting, and evaluation as an iterative approach enabling inference from diverse data sources. Through a case study on inference of prey and predator niche width in an eco-evolutionary context, we demonstrate how inclusive and mechanistic approaches—eco-evolutionary modelling and Approximate Bayesian Computation (ABC)—can enable inference of assembly processes that have been largely neglected by traditional techniques despite the ubiquity of such processes. Much literature points to the limitations of current inference techniques, but concrete solutions to such limitations are few. Many of the challenges associated with novel inference techniques are, however, already to some extent resolved in other fields and thus ready to be put into action in a more formal way for inferring processes of community assembly from signals in various data sources

Effect of vitamin D supplementation on blood pressure:a systematic review and meta-analysis incorporating individual patient data

D-PRESSURE Collaboration: et al.[Importance]: Low levels of vitamin D are associated with elevated blood pressure (BP) and future cardiovascular events. Whether vitamin D supplementation reduces BP and which patient characteristics predict a response remain unclear.[Objective]: To systematically review whether supplementation with vitamin D or its analogues reduce BP.[Data Sources]: We searched MEDLINE, CINAHL, EMBASE, Cochrane Central Register of Controlled Trials, and http://www.ClinicalTrials.com augmented by a hand search of references from the included articles and previous reviews. Google was searched for gray literature (ie, material not published in recognized scientific journals). No language restrictions were applied. The search period spanned January 1, 1966, through March 31, 2014.[Study Selection]: We included randomized placebo-controlled clinical trials that used vitamin D supplementation for a minimum of 4 weeks for any indication and reported BP data. Studies were included if they used active or inactive forms of vitamin D or vitamin D analogues. Cointerventions were permitted if identical in all treatment arms.[Data Extraction and Synthesis]: We extracted data on baseline demographics, 25-hydroxyvitamin D levels, systolic and diastolic BP (SBP and DBP), and change in BP from baseline to the final follow-up. Individual patient data on age, sex, medication use, diabetes mellitus, baseline and follow-up BP, and 25-hydroxyvitamin D levels were requested from the authors of the included studies. For trial-level data, between-group differences in BP change were combined in a random-effects model. For individual patient data, between-group differences in BP at the final follow up, adjusted for baseline BP, were calculated before combining in a random-effects model.[Main Outcomes and Measures]: Difference in SBP and DBP measured in an office setting.[Results]: We included 46 trials (4541 participants) in the trial-level meta-analysis. Individual patient data were obtained for 27 trials (3092 participants). At the trial level, no effect of vitamin D supplementation was seen on SBP (effect size, 0.0 [95% CI, −0.8 to 0.8] mm Hg; P = .97; I2 = 21%) or DBP (effect size, −0.1 [95% CI, −0.6 to 0.5] mm Hg; P = .84; I2 = 20%). Similar results were found analyzing individual patient data for SBP (effect size, −0.5 [95% CI, −1.3 to 0.4] mm Hg; P = .27; I2 = 0%) and DBP (effect size, 0.2 [95% CI, −0.3 to 0.7] mm Hg; P = .38; I2 = 0%). Subgroup analysis did not reveal any baseline factor predictive of a better response to therapy.[Conclusions and Relevance]: Vitamin D supplementation is ineffective as an agent for lowering BP and thus should not be used as an antihypertensive agent.Peer reviewe

Functional redundancy and sensitivity of fish assemblages in European rivers, lakes and estuarine ecosystems

The impact of species loss on ecosystems functioning depends on the amount of trait similarity between species, i.e. functional redundancy, but it is also influenced by the order in which species are lost. Here we investigated redundancy and sensitivity patterns across fish assemblages in lakes, rivers and estuaries. Several scenarios of species extinction were simulated to determine whether the loss of vulnerable species (with high propensity of extinction when facing threats) causes a greater functional alteration than random extinction. Our results indicate that the functional redundancy tended to increase with species richness in lakes and rivers, but not in estuaries. We demonstrated that i) in the three systems, some combinations of functional traits are supported by non-redundant species, ii) rare species in rivers and estuaries support singular functions not shared by dominant species, iii) the loss of vulnerable species can induce greater functional alteration in rivers than in lakes and estuaries. Overall, the functional structure of fish assemblages in rivers is weakly buffered against species extinction because vulnerable species support singular functions. More specifically, a hotspot of functional sensitivity was highlighted in the Iberian Peninsula, which emphasizes the usefulness of quantitative criteria to determine conservation prioritiesinfo:eu-repo/semantics/publishedVersio

Functional diversity can facilitate the collapse of an undesirable ecosystem state

Biodiversity may increase ecosystem resilience. However, we have limited understanding if this holds true for ecosystems that respond to gradual environmental change with abrupt shifts to an alternative state. We used a mathematical model of anoxic–oxic regime shifts and explored how trait diversity in three groups of bacteria influences resilience. We found that trait diversity did not always increase resilience: greater diversity in two of the groups increased but in one group decreased resilience of their preferred ecosystem state. We also found that simultaneous trait diversity in multiple groups often led to reduced or erased diversity effects. Overall, our results suggest that higher diversity can increase resilience but can also promote collapse when diversity occurs in a functional group that negatively influences the state it occurs in. We propose this mechanism as a potential management approach to facilitate the recovery of a desired ecosystem state