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Phylogenetic conservatism in the relationship between functional and demographic characteristics in Amazon tree taxa
Get PDF1. Leaf and wood functional traits of trees are related to growth, reproduction, and survival, but the degree of phylogenetic conservatism in these relationships is largely unknown. In this study, we describe the variability of strategies involving leaf, wood and demographic characteristics for tree genera distributed across the Amazon Region, and quantify phylogenetic signal for the characteristics and their relationships.
2. Leaf and wood traits are aligned with demographic variables along two main axes of variation. The first axis represents the coordination of leaf traits describing resource uptake and use, wood density, seed mass, and survival. The second axis represents the coordination between size and growth. Both axes show strong phylogenetic signal, suggesting a constrained evolution influenced by ancestral values, yet the second axis also has an additional, substantial portion of its variation that is driven by functional correlations unrelated to phylogeny, suggesting simultaneously higher evolutionary lability and coordination.
3. Synthesis. Our results suggest that life history strategies of tropical trees are generally phylogenetically conserved, but that tree lineages may have some capability of responding to environmental changes by modulating their growth and size. Overall, we provide the largest-scale synopsis of functional characteristics of Amazonian trees, showing substantial nuance in the evolutionary patterns of individual characteristics and their relationships
Revealing hidden sources of uncertainty in biodiversity trend assessments
Get PDFIdiosyncratic decisions during the biodiversity trend assessment process may limit reproducibility, whilst ‘hidden' uncertainty due to collection bias, taxonomic incompleteness, and variable taxonomic resolution may limit the reliability of reported trends. We model alternative decisions made during assessment of taxon-level abundance and distribution trends using an 18-year time series covering freshwater fish, invertebrates, and primary producers in England. Through three case studies, we test for collection bias and quantify uncertainty stemming from data preparation and model specification decisions, assess the risk of conflating trends for individual species when aggregating data to higher taxonomic ranks, and evaluate the potential uncertainty stemming from taxonomic incompleteness. Choice of optimizer algorithm and data filtering to obtain more complete time series explained 52.5% of the variation in trend estimates, obscuring the signal from taxon-specific trends. The use of penalized iteratively reweighted least squares, a simplified approach to model optimization, was the most important source of uncertainty. Application of increasingly harsh data filters exacerbated collection bias in the modelled dataset. Aggregation to higher taxonomic ranks was a significant source of uncertainty, leading to conflation of trends among protected and invasive species. We also found potential for substantial positive bias in trend estimation across six fish populations which were not consistently recorded in all operational areas. We complement analyses of observational data with in silico experiments in which monitoring and trend assessment processes were simulated to enable comparison of trend estimates with known underlying trends, confirming that collection bias, data filtering and taxonomic incompleteness have significant negative impacts on the accuracy of trend estimates. Identifying and managing uncertainty in biodiversity trend assessment is crucial for informing effective conservation policy and practice. We highlight several serious sources of uncertainty affecting biodiversity trend analyses and present tools to improve the transparency of decisions made during the trend assessment process
A Quantitative Microbial Risk Assessment (QMRA) framework for exposure from toilet flushing using experimental aerosol concentration measurements
Get PDFBackground
Flushing a toilet generates aerosols potentially containing microorganisms, serving as a transmission route for pathogens, notably gastrointestinal and respiratory infections. Despite identification of aerosols and positive microbial sampling, there is a lack of quantitative assessments linking aerosol generation to infection risk in toilet settings.
Methods
We develop a framework to evaluate the infection risk to a second susceptible individual using a shared toilet following faecal shedding and flush aerosolisation by an infected individual. Experimental measurements of particle concentrations from a toilet flush in a controlled chamber are combined with a model using Quantitative Microbial Risk Assessment (QMRA) methods. We demonstrate the approach for SARS-CoV-2 and norovirus, examining model sensitivity and how adding cubicle space and varying occupancy times affect risk.
Results
The model suggests non-negligible infection risk from the toilet plume, particularly for pathogens with higher concentrations in faeces. The model suggests norovirus could have a 2 times greater maximum infection risk than SARS-CoV-2. Mean and median risks for all scenarios decreased when the second individual entered 60 s post-flush compared to 0 s. Occupancy times had less impact on risk compared to the timing of entry post-flush.
Conclusion
To mitigate infection risk from shared toilets, ventilating the room before entering is crucial. Allowing time between toilet usages may be more effective compared to reducing occupancy times. Models provide valuable insights into relative impacts of measures and comparison between pathogens, but improved quantitative data is needed, particularly in higher risk scenarios (e.g. hospitals, public events), to quantify absolute risks
Floodplain forests drive fruit-eating fish diversity at the Amazon Basin-scale
Get PDFUnlike most rivers globally, nearly all lowland Amazonian rivers have unregulated flow, supporting seasonally flooded floodplain forests. Floodplain forests harbor a unique tree species assemblage adapted to flooding and specialized fauna, including fruit-eating fish that migrate seasonally into floodplains, favoring expansive floodplain areas. Frugivorous fish are forest-dependent fauna critical to forest regeneration via seed dispersal and support commercial and artisanal fisheries. We implemented linear mixed effects models to investigate drivers of species richness among specialized frugivorous fishes across the ~6,000,000 km² Amazon Basin, analyzing 29 species from 9 families (10,058 occurrences). Floodplain predictors per subbasin included floodplain forest extent, tree species richness (309,540 occurrences for 2,506 species), water biogeochemistry, flood duration, and elevation, with river order controlling for longitudinal positioning along the river network. We observed heterogeneous patterns of frugivorous fish species richness, which were positively correlated with floodplain forest extent, tree species richness, and flood duration. The natural hydrological regime facilitates fish access to flooded forests and controls fruit production. Thus, the ability of Amazonian floodplain ecosystems to support frugivorous fish assemblages hinges on extensive and diverse seasonally flooded forests. Given the low functional redundancy in fish seed dispersal networks, diverse frugivorous fish assemblages disperse and maintain diverse forests; vice versa, diverse forests maintain more fish species, underscoring the critically important taxonomic interdependencies that embody Amazonian ecosystems. Effective management strategies must acknowledge that access to diverse and hydrologically functional floodplain forests is essential to ensure the long-term survival of frugivorous fish and, in turn, the long-term sustainability of floodplain forests
Extensive culture:Expressions of endlessness in the metaverse and the limits of data accumulation
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Specification, Validation and Verification of Social, Legal, Ethical, Empathetic and Cultural Requirements for Autonomous Agents
Get PDFAutonomous agents are increasingly being proposed for use in healthcare, assistive care, education, and other applications governed by complex human-centric norms. To ensure compliance with these norms, the rules they induce need to be unambiguously defined, checked for consistency, and used to verify the agent. In this paper, we introduce a framework for formal specification, validation and verification of social, legal, ethical, empathetic and cultural (SLEEC) rules for autonomous agents. Our framework comprises: (i) a language for specifying SLEEC rules and rule defeaters (that is, circumstances in which a rule does not apply or an alternative form of the rule is required); (ii) a formal semantics (defined in the process algebra tock-CSP) for the language; and (iii) methods for detecting conflicts and redundancy within a set of rules, and for verifying the compliance of an autonomous agent with such rules. We show the applicability of our framework for two autonomous agents from different domains: a firefighter UAV, and an assistive-dressing robot
Monitoring of Argon plasma in a coating manufacturing process by utilising IR imaging techniques
Get PDFAtmospheric plasma spray is a complex multivariable manufacturing process used in a wide range of industries. Deviations in the process parameters have been shown to affect the coating quality. Currently, the quality analysis is performed at the end of the process rather than checking for defects during the process. However, monitoring for these deviations during a coating process is difficult due to environmental hazards such as UV radiation, dusty environment, and excessive noise generation. A commercially available thermal imaging camera was integrated into this space to directly monitor the atmospheric plasma heat distribution and its influence on the in-flight particle trajectories during spraying. A novel metric called asymmetric angle is proposed to monitor the asymmetry of the plasma heat distribution. This is an important metric as a symmetric heat distribution is required to heat all the particles adequately to form a good quality coating. Further metrics of Gaussian Aspect Ratio (GAR) and contour area were found to have a relationship with the plasma gas flow rate and are discussed. The spray angle of the material is also tracked by fitting a 1D line to the regional Shannon entropy of the thermal image. The limitations of these metrics are discussed with possible avenues of further investigation
Kinetic Steering of Amyloid Formation and Polymorphism by Canagliflozin, a Type-2 Diabetes Drug
Get PDFAmyloid formation is involved in widespread health conditions such as Alzheimer’s disease, Parkinson’s disease, and type-2 diabetes. Amyloid fibrils have a similar cross-β architecture, but fibrils formed by a single protein sequence can have diverse structures, varying with time, self-assembly conditions, and sequence modifications. Fibril structure has been proposed to be diagnostic of disease, but why different structures result under different conditions, especially in vitro, remains elusive. We previously identified a small molecule, YX-I-1, which inhibits in vitro amyloid formation by islet amyloid polypeptide (IAPP), a peptide hormone whose amyloid formation is involved in type-2 diabetes. Here, using YX-I-1 as a lead, we identified regulator-approved drugs with similar structures by chemical similarity analysis and substructure searches and monitored the effect of 24 of these potential ligands on IAPP amyloid assembly in vitro. We show that one such compound, canagliflozin (Invokana), a type-2 diabetes drug already in clinical use, can strongly delay the kinetics of IAPP amyloid formation, an activity independent of its intended mode of action [sodium-glucose linked transporter 2 (SGLT2) inhibitor] that may have important therapeutic implications. Combining analysis of amyloid self-assembly kinetics, biophysical characterization of monomer and fibril binding, and cryo-EM of the assembly products, we show that YX-I-1 and canagliflozin target IAPP early in aggregation, remodeling the energy landscape of primary nucleation and profoundly altering the resulting fibril structures. Early binding events thus imprint long-lasting effects on the amyloid structures that form
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