# Browsing by Subject "FRAMEWORK"

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Now showing items 1-20 of 117
• (2021)
Ecological indicator approaches typically compare the prevailing state of an ecosystem component to a reference state reflecting good environmental conditions, i.e. the desirable state. However, defining the reference state is challenging due to a wide range of uncertainties related to natural variability and measurement error in data, as well as ecological understanding. This study propose a novel probabilistic approach combining historical monitoring data and ecological understanding to estimate the uncertainty associated with the boundary value of an ecological indicator between good and poor environmental states. Bayesian inference is used to estimate the epistemic uncertainty about the true state of an indicator variable during an historical reference period. This approach replaces the traditional boundary value with probability distribution, indicating the uncertainty about the boundary between environmental states providing a transparent safety margin associated with the risk of misclassification of the indicator's state. The approach is demonstrated by applying it to a time-series of an ecological status indicator, 'Abundance of coastal key fish species', included in HELCOM's Baltic Sea regional status assessment. We suggest that acknowledgement of the uncertainty behind the final classification leads to more transparent and better-informed decision-making processes.
• (2020)
Aerial organs of plants, being highly prone to local injuries, require tissue restoration to ensure their survival. However, knowledge of the underlying mechanism is sparse. In this study, we mimicked natural injuries in growing leaves and stems to study the reunion between mechanically disconnected tissues. We show that PLETHORA (PLT) and AINTEGUMENTA (ANT) genes, which encode stem cell-promoting factors, are activated and contribute to vascular regeneration in response to these injuries. PLT proteins bind to and activate the CUC2 promoter. PLT proteins and CUC2 regulate the transcription of the local auxin biosynthesis gene YUC4 in a coherent feed-forward loop, and this process is necessary to drive vascular regeneration. In the absence of this PLT-mediated regeneration response, leaf ground tissue cells can neither acquire the early vascular identity marker ATHB8, nor properly polarise auxin transporters to specify new venation paths. The PLT-CUC2 module is required for vascular regeneration, but is dispensable for midvein formation in leaves. We reveal the mechanisms of vascular regeneration in plants and distinguish between the wound-repair ability of the tissue and its formation during normal development.
• (2020)
A whole-genome alignment of 240 phylogenetically diverse species of eutherian mammal-including 131 previously uncharacterized species-from the Zoonomia Project provides data that support biological discovery, medical research and conservation. The Zoonomia Project is investigating the genomics of shared and specialized traits in eutherian mammals. Here we provide genome assemblies for 131 species, of which all but 9 are previously uncharacterized, and describe a whole-genome alignment of 240 species of considerable phylogenetic diversity, comprising representatives from more than 80% of mammalian families. We find that regions of reduced genetic diversity are more abundant in species at a high risk of extinction, discern signals of evolutionary selection at high resolution and provide insights from individual reference genomes. By prioritizing phylogenetic diversity and making data available quickly and without restriction, the Zoonomia Project aims to support biological discovery, medical research and the conservation of biodiversity.
• (2019)
In a comparative study of student teachers in Finland and South Africa, the researchers aimed to capture students' views of how and what they had learned from practice in two university-affiliated primary schools. With data from survey questionnaires, we found that students in the two customized programmes accentuated different domains of teacher knowledge. The newly established teaching practice school in Johannesburg afforded closer integration of university and school practicum experiences for students than the well-established school in Helsinki. The authors conclude that an innovative teacher education model can be re-invented in a significantly different context and also add new dimensions to the original.
• (2021)
This article provides a perspective on nature-based solutions. First, the argument is developed that nature-based solutions integrate social and ecological systems. Then, theoretical considerations relating to relational values, multifunctionality, transdisciplinarity, and polycentric governance are briefly outlined. Finally, a conceptual model of the social–ecological system of nature-based solutions is synthesised and presented. This conceptual model comprehensively defines the social and ecological external and internal systems that make up nature-based solutions, and identifies theoretical considerations that need to be addressed at different stages of their planning and implementation The model bridges the normative gaps of existing nature-based solution frameworks and could be used for consistent, comprehensive, and transferable comparisons internationally. The theoretical considerations addressed in this article inform practitioners, policymakers, and researchers about the essential components of nature-based solutions. The conceptual model can facilitate the identification of social and ecological interconnections within nature-based solutions and the range of stakeholders and disciplines involved.
• (2019)
We investigate the problem of computing the number of linear extensions of a given n-element poset whose cover graph has treewidth t. We present an algorithm that runs in time $${\tilde{O}}(n^{t+3})$$O~(nt+3)for any constant t; the notation $${\tilde{O}}$$O~hides polylogarithmic factors. Our algorithm applies dynamic programming along a tree decomposition of the cover graph; the join nodes of the tree decomposition are handled by fast multiplication of multivariate polynomials. We also investigate the algorithm from a practical point of view. We observe that the running time is not well characterized by the parameters n and t alone: fixing these parameters leaves large variance in running times due to uncontrolled features of the selected optimal-width tree decomposition. We compare two approaches to select an efficient tree decomposition: one is to include additional features of the tree decomposition to build a more accurate, heuristic cost function; the other approach is to fit a statistical regression model to collected running time data. Both approaches are shown to yield a tree decomposition that typically is significantly more efficient than a random optimal-width tree decomposition.
• (2019)
Aims/hypothesisIdentifying rare coding variants associated with albuminuria may open new avenues for preventing chronic kidney disease and end-stage renal disease, which are highly prevalent in individuals with diabetes. Efforts to identify genetic susceptibility variants for albuminuria have so far been limited, with the majority of studies focusing on common variants.MethodsWe performed an exome-wide association study to identify coding variants in a two-stage (discovery and replication) approach. Data from 33,985 individuals of European ancestry (15,872 with and 18,113 without diabetes) and 2605 Greenlanders were included.ResultsWe identified a rare (minor allele frequency [MAF]: 0.8%) missense (A1690V) variant in CUBN (rs141640975, =0.27, p=1.3x10(-11)) associated with albuminuria as a continuous measure in the combined European meta-analysis. The presence of each rare allele of the variant was associated with a 6.4% increase in albuminuria. The rare CUBN variant had an effect that was three times stronger in individuals with type 2 diabetes compared with those without (p(interaction)=7.0x10(-4), with diabetes=0.69, without diabetes=0.20) in the discovery meta-analysis. Gene-aggregate tests based on rare and common variants identified three additional genes associated with albuminuria (HES1, CDC73 and GRM5) after multiple testing correction (p(Bonferroni)
• (2019)
Predicting metabolizer phenotype (MP) is typically performed using data from a single gene. Cytochrome p450 family 2 subfamily D polypeptide 6 (CYP2D6) is considered the primary gene for predicting MP in reference to approximately 30% of marketed drugs and endogenous toxins. CYP2D6 predictions have proven clinically effective but also have well-documented inaccuracies due to relatively high genotype-phenotype discordance in certain populations. Herein, a pathway-driven predictive model employs genetic data from uridine diphosphate glucuronosyltransferase, family 1, polypeptide B7 (UGT2B7), adenosine triphosphate (ATP)-binding cassette, subfamily B, number 1 (ABCB1), opioid receptor mu 1 (OPRM1), and catechol-O-methyltransferase (COMT) to predict the tramadol to primary metabolite ratio (T:M1) and the resulting toxicologically inferred MP (t-MP). These data were then combined with CYP2D6 data to evaluate performance of a fully combinatorial model relative to CYP2D6 alone. These data identify UGT2B7 as a potentially significant explanatory marker for T:M1 variability in a population of tramadol-exposed individuals of Finnish ancestry. Supervised machine learning and feature selection were used to demonstrate that a set of 16 loci from 5 genes can predict t-MP with over 90% accuracy, depending on t-MP category and algorithm, which was significantly greater than predictions made by CYP2D6 alone.
• (2020)
Species distribution models (SDM) are a key tool in ecology, conservation and management of natural resources. Two key components of the state-of-the-art SDMs are the description for species distribution response along environmental covariates and the spatial random effect that captures deviations from the distribution patterns explained by environmental covariates. Joint species distribution models (JSDMs) additionally include interspecific correlations which have been shown to improve their descriptive and predictive performance compared to single species models. However, current JSDMs are restricted to hierarchical generalized linear modeling framework. Their limitation is that parametric models have trouble in explaining changes in abundance due, for example, highly non-linear physical tolerance limits which is particularly important when predicting species distribution in new areas or under scenarios of environmental change. On the other hand, semi-parametric response functions have been shown to improve the predictive performance of SDMs in these tasks in single species models. Here, we propose JSDMs where the responses to environmental covariates are modeled with additive multivariate Gaussian processes coded as linear models of coregionalization. These allow inference for wide range of functional forms and interspecific correlations between the responses. We propose also an efficient approach for inference with Laplace approximation and parameterization of the interspecific covariance matrices on the euclidean space. We demonstrate the benefits of our model with two small scale examples and one real world case study. We use cross-validation to compare the proposed model to analogous semi-parametric single species models and parametric single and joint species models in interpolation and extrapolation tasks. The proposed model outperforms the alternative models in all cases. We also show that the proposed model can be seen as an extension of the current state-of-the-art JSDMs to semi-parametric models.
• (2015)
Aerosol climate effects are intimately tied to interactions with water. Here we combine hygroscopicity measurements with direct observations about the phase of secondary organic aerosol (SOA) particles to show that water uptake by slightly oxygenated SOA is an adsorption-dominated process under subsaturated conditions, where low solubility inhibits water uptake until the humidity is high enough for dissolution to occur. This reconciles reported discrepancies in previous hygroscopicity closure studies. We demonstrate that the difference in SOA hygroscopic behavior in subsaturated and supersaturated conditions can lead to an effect up to about 30% in the direct aerosol forcinghighlighting the need to implement correct descriptions of these processes in atmospheric models. Obtaining closure across the water saturation point is therefore a critical issue for accurate climate modeling.
• (2017)
The aim of this study was to analyse electronic health record-related patient safety incidents in the patient safety incident reporting database in fully digital hospitals in Finland. We compare Finnish data to similar international data and discuss their content with regard to the literature. We analysed the types of electronic health record-related patient safety incidents that occurred at 23 hospitals during a 2-year period. A procedure of taxonomy mapping served to allow comparisons. This study represents a rare examination of patient safety risks in a fully digital environment. The proportion of electronic health record-related incidents was markedly higher in our study than in previous studies with similar data. Human-computer interaction problems were the most frequently reported. The results show the possibility of error arising from the complex interaction between clinicians and computers.
• (2021)
International organizations, governments, researchers, and activists have proposed the need for deeper integration of sustainability considerations in national food-based dietary guidelines (FBDGs). Yet, as recent scholarship advances the conversation, questions remain around how to effectively frame and address the interconnectedness of multiple sustainability domains. Little systematic analysis has evaluated how current FBDGs have integrated complex messages about socially, environmentally, and economically sustainable consumption practices with nutrition and health messages. This study had two nested objectives: (i) to examine the validity of an existing sustainable diets framework by assessing how sustainability concepts have been framed and included in national FBDGs available from 2011 to 2019 and (ii) to describe a novel analysis approach that augments an existing framework which integrates sustainability domains and can be adapted for use by future FBDGs. A qualitative content analysis was used to examine sustainability concepts found in 12 FBDGs and supporting documents available in English that were developed for use in 16 countries across Europe, North and South America, and Asia as of 2019-from a global review of those published prior to 2016 and gray literature review of publications between 2016 and 2019. Health domains were the primary frame found across the FBDGs examined, but documents also commonly incorporated agricultural, sociocultural, and economic sustainability principles. Analyzed documents were used to adapt an existing policy analysis framework into a "Sustainability in FBDGs Framework." This proposed framework contributes a novel analysis approach and has five core domains that are interconnected: health and nutrition, food security and agriculture, markets and value chains, sociocultural and political, and environment and ecosystems. This study adds to the growing body of literature related to sustainable food systems and dietary guidelines by presenting how sustainability framing in FBDGs can be used to further develop a comprehensive framework for integrating sustainability domains. While this project helps to validate previous work, further analyses of FBDGs which have emerged since this study and those not available in English are needed to improve the guidance approach described here and for assessing the incorporation of sustainability domains in future FBDGs. This work is useful in informing processes for policy developers to integrate sustainability considerations into their national FBDGs.
• (2016)
Natural and business ecosystems are complex and dynamic service systems that interact through the utilization of ecosystem service offerings for human well-being. Currently, natural and business sciences have not developed a shared and common set of service-based terms or concepts for discussing ecosystem service offerings in the process of value co-creation. In this study, the ecosystem service approach was compared with marketing science's service-dominant logic. The terminology and concepts were harmonized, and the two approaches were then integrated into a service-dominant value creation (SVC) framework. The incorporation of natural ecosystems includes accounting for the flow of positive and negative impacts through associated value networks. Therefore, the term value-in-impact was proposed to describe these value flows. A case study of the global forest-based sector was then presented, demonstrating how to discuss current research challenges using the proposed framework. In conclusion, a shared service-dominant approach provides an opportunity for deeper inter-disciplinary discussion between natural and business sciences. This study represents a contribution towards the development of a holistic service science that includes consideration for natural ecosystems. The SVC framework also addresses many of the multidimensional challenges noted by previous sustainability frameworks. (C) 2016 Elsevier Ltd. All rights reserved.
• (2019)
VALUE is an open European collaboration to intercompare downscaling approaches for climate change research, focusing on different validation aspects (marginal, temporal, extremes, spatial, process‐based, etc.). Here we describe the participating methods and first results from the first experiment, using “perfect” reanalysis (and reanalysis‐driven regional climate model (RCM)) predictors to assess the intrinsic performance of the methods for downscaling precipitation and temperatures over a set of 86 stations representative of the main climatic regions in Europe. This study constitutes the largest and most comprehensive to date intercomparison of statistical downscaling methods, covering the three common downscaling approaches (perfect prognosis, model output statistics—including bias correction—and weather generators) with a total of over 50 downscaling methods representative of the most common techniques. Overall, most of the downscaling methods greatly improve (reanalysis or RCM) raw model biases and no approach or technique seems to be superior in general, because there is a large method‐to‐method variability. The main factors most influencing the results are the seasonal calibration of the methods (e.g., using a moving window) and their stochastic nature. The particular predictors used also play an important role in cases where the comparison was possible, both for the validation results and for the strength of the predictor–predictand link, indicating the local variability explained. However, the present study cannot give a conclusive assessment of the skill of the methods to simulate regional future climates, and further experiments will be soon performed in the framework of the EURO‐CORDEX initiative (where VALUE activities have merged and follow on). Finally, research transparency and reproducibility has been a major concern and substantive steps have been taken. In particular, the necessary data to run the experiments are provided at http://www.value‐cost.eu/data and data and validation results are available from the VALUE validation portal for further investigation: http://www.value‐cost.eu/validationportal.
• (2016)
Large-scale reference data sets of human genetic variation are critical for the medical and functional interpretation of DNA sequence changes. Here we describe the aggregation and analysis of high-quality exome (protein-coding region) DNA sequence data for 60,706 individuals of diverse ancestries generated as part of the Exome Aggregation Consortium (ExAC). This catalogue of human genetic diversity contains an average of one variant every eight bases of the exome, and provides direct evidence for the presence of widespread mutational recurrence. We have used this catalogue to calculate objective metrics of pathogenicity for sequence variants, and to identify genes subject to strong selection against various classes of mutation; identifying 3,230 genes with near-complete depletion of predicted protein-truncating variants, with 72% of these genes having no currently established human disease phenotype. Finally, we demonstrate that these data can be used for the efficient filtering of candidate disease-causing variants, and for the discovery of human 'knockout' variants in protein-coding genes.
• (2020)
Adaptive management strategies are required to manage multi-actor and multifunctional river landscapes. Such strategies need to be inclusive of perspectives of different stakeholders. We present a case study of a pilot engineering project in the Dutch river Waal, which drastically changed the appearance of the river landscape. We study perceptions of four stakeholder groups (residents, recreational anglers, recreational boaters and shipping professionals) regarding the impacts of this intervention on landscape values, including aesthetics, naturalness, biodiversity, flood safety and accessibility. Results show that stakeholders differ in which functions of the river landscape they found important and how they perceive the longitudinal dams to influence the landscape. They also differ in levels of place attachment and trust in the responsible authority. Shipping professionals stood out for their more negative evaluations of the dams compared to the other stakeholders, while especially residents demonstrated high levels of place identity and connection with nature. Residents also feel that the dams are improving flood risk safety in the area, and they positively evaluate knowledge and skills of Dutch water managers. These results provide water managers with much needed insights into landscape functions valued by different stakeholder groups and those perceived as most endangered by landscape interventions.
• (2021)
We describe an integrative approach to improve contiguity and haploidy of a reference genome assembly and demonstrate its impact with practical examples. With two novel features of Lep-Anchor software and a combination of dense linkage maps, overlap detection and bridging long reads, we generated an improved assembly of the nine-spined stickleback (Pungitius pungitius) reference genome. We were able to remove a significant number of haplotypic contigs, detect more genetic variation and improve the contiguity of the genome, especially that of X chromosome. However, improved scaffolding cannot correct for mosaicism of erroneously assembled contigs, demonstrated by a de novo assembly of a 1.6-Mbp inversion. Qualitatively similar gains were obtained with the genome of three-spined stickleback (Gasterosteus aculeatus). Since the utility of genome-wide sequencing data in biological research depends heavily on the quality of the reference genome, the improved and fully automated approach described here should be helpful in refining reference genome assemblies.
• (2016)
The ubiquitin fold modifier 1 (UFM1) cascade is a recently identified evolutionarily conserved ubiquitin-like modification system whose function and link to human disease have remained largely uncharacterized. By using exome sequencing in Finnish individuals with severe epileptic syndromes, we identified pathogenic compound heterozygous variants in UBAS, encoding an activating enzyme for UFM1, in two unrelated families. Two additional individuals with biallelic UBAS variants were identified from the UK-based Deciphering Developmental Disorders study and one from the Northern Finland Intellectual Disability cohort. The affected individuals (n = 9) presented in early infancy with severe irritability, followed by dystonia and stagnation of development. Furthermore, the majority of individuals display postnatal microcephaly and epilepsy and develop spasticity. The affected individuals were compound heterozygous for a missense substitution, c.1111G>A (p.A1a371Thr; allele frequency of 0.28% in Europeans), and a nonsense variant or c.164G>A that encodes an amino acid substitution p.Arg5SHis, but also affects splicing by facilitating exon 2 skipping, thus also being in effect a loss-of-function allele. Using an in vitro thioester formation assay and cellular analyses, we show that the p.A1a371Thr variant is hypomorphic with attenuated ability to transfer the activated UFM1 to UFC1. Finally, we show that the CNS-specific knockout of Ufml in mice causes neonatal death accompanied by microcephaly and apoptosis in specific neurons, further suggesting that the UFM1 system is essential for CNS development and function. Taken together, our data imply that the combination of a hypomorphic p.A1a371Thr variant in trans with a loss-of-function allele in UBAS underlies a severe infantile-onset encephalopathy.
• (2020)
Bioregions are important tools for understanding and managing natural resources. Bioregions should describe locations of relatively homogenous assemblages of species occur, enabling managers to better regulate activities that might affect these assemblages. Many existing bioregionalization approaches, which rely on expert-derived, Delphic comparisons or environmental surrogates, do not explicitly include observed biological data in such analyses. We highlight that, for bioregionalizations to be useful and reliable for systems scientists and managers, the bioregionalizations need to be based on biological data; to include an easily understood assessment of uncertainty, preferably in a spatial format matching the bioregions; and to be scientifically transparent and reproducible. Statistical models provide a scientifically robust, transparent, and interpretable approach for ensuring that bioregions are formed on the basis of observed biological and physical data. Using statistically derived bioregions provides a repeatable framework for the spatial representation of biodiversity at multiple spatial scales. This results in better-informed management decisions and biodiversity conservation outcomes.
• (2016)
Background: Making forecasts about biodiversity and giving support to policy relies increasingly on large collections of data held electronically, and on substantial computational capability and capacity to analyse, model, simulate and predict using such data. However, the physically distributed nature of data resources and of expertise in advanced analytical tools creates many challenges for the modern scientist. Across the wider biological sciences, presenting such capabilities on the Internet (as "Web services") and using scientific workflow systems to compose them for particular tasks is a practical way to carry out robust "in silico" science. However, use of this approach in biodiversity science and ecology has thus far been quite limited. Results: BioVeL is a virtual laboratory for data analysis and modelling in biodiversity science and ecology, freely accessible via the Internet. BioVeL includes functions for accessing and analysing data through curated Web services; for performing complex in silico analysis through exposure of R programs, workflows, and batch processing functions; for on- line collaboration through sharing of workflows and workflow runs; for experiment documentation through reproducibility and repeatability; and for computational support via seamless connections to supporting computing infrastructures. We developed and improved more than 60 Web services with significant potential in many different kinds of data analysis and modelling tasks. We composed reusable workflows using these Web services, also incorporating R programs. Deploying these tools into an easy-to-use and accessible 'virtual laboratory', free via the Internet, we applied the workflows in several diverse case studies. We opened the virtual laboratory for public use and through a programme of external engagement we actively encouraged scientists and third party application and tool developers to try out the services and contribute to the activity. Conclusions: Our work shows we can deliver an operational, scalable and flexible Internet-based virtual laboratory to meet new demands for data processing and analysis in biodiversity science and ecology. In particular, we have successfully integrated existing and popular tools and practices from different scientific disciplines to be used in biodiversity and ecological research.