Climate Change Impacts on Polar Marine Ecosystems: Toward Robust Approaches for Managing Risks and Uncertainties

The Polar Regions chapter of the Intergovernmental Panel on Climate Change's Special Report on the Ocean and Cryosphere in a Changing Climate (SROCC) provides a comprehensive assessment of climate change impacts on polar marine ecosystems and associated consequences for humans. It also includes identification of confidence for major findings based on agreement across studies and weight of evidence. Sources of uncertainty, from the extent of available datasets, to resolution of projection models, to the complexity and understanding of underlying social-ecological linkages and dynamics, can influence confidence. Here we, marine ecosystem scientists all having experience as lead authors of IPCC reports, examine the evolution of confidence in observed and projected climate-linked changes in polar ecosystems since SROCC. Further synthesis of literature on polar marine ecosystems has been undertaken, especially within IPCC's Sixth Assessment Report (AR6) Working Group II; for the Southern Ocean also the Marine Ecosystem Assessment for the Southern Ocean (MEASO). These publications incorporate new scientific findings that address some of the knowledge gaps identified in SROCC. While knowledge gaps have been narrowed, we still find that polar region assessments reflect pronounced geographical skewness in knowledge regarding the responses of marine life to changing climate and associated literature. There is also an imbalance in scientific focus; especially research in Antarctica is dominated by physical oceanography and cryosphere science with highly fragmented approaches and only short-term funding to ecology. There are clear indications that the scientific community has made substantial progress in its ability to project ecosystem responses to future climate change through the development of coupled biophysical models of the region facilitated by increased computer power allowing for improved resolution in space and time. Lastly, we point forward—providing recommendations for future advances for IPCC assessments.

Syphilis in riverine communities: prevalence and associated factors

Objective: To estimate the prevalence of syphilis and associated factors in riverine communities. Method: This is a cross-sectional and analytical study carried out with 250 riverside dwellers living in five communities in the city of João Pessoa, state of Paraíba. Data were collected through interviews and rapid screening tests to investigate syphilis. Bivariate, logistic regression and weight of evidence analysis were performed to identify the association between risk factors and behavior variables and rapid test positivity. Results: he prevalence of syphilis was 11.6% (95%CI: 7.5–15.6). Riverside dwellers who have a previous history of Sexually Transmitted Infection (OR 8.00; 95%CI: 2.76–23.2), history of imprisonment (OR 7.39; 95%CI: 1.61–33.7) and who reported having more than two sexual partners in the last 12 months (OR 4.31; 95%CI: 1.55–11.9) were more likely to be positive for syphilis. Conclusion: High prevalence of syphilis among riverside dwellers and the presence of behavioral factors that increase vulnerability to acquiring the infection. The need to invest in preventive and screening strategies for syphilis in populations considered vulnerable is highlighted.

Application of Data-Driven Techniques For Landslide Susceptibility Prediction Along An Earthquake Affected Road Section in Kashmir Himalaya

The interaction of seismic events with geo-environmental conditions and anthropogenic activities may exacerbate the risk of landslide hazard in a mountainous region. As an example of this, 2005 Kashmir earthquake triggered a large number of shallow to deep slope failures, which was further intensified in following years by human activities notably along road networks, posing a long-term hazard. Hence, this study was planned to evaluate the effectiveness of landslide susceptibility prediction along earthquake affected road-section of Neelum Highway using six different data-driven models. We applied analytical hierarchy process as heuristic approach, weight of evidence and index of entropy as statistical models and multi-layer perceptron, support vector machine and binary logistic regression (BLR) as machine learning models. Initially, 224 landslides locations were marked through field surveys to prepare landslide inventory which was further randomly divided into training (70%) and testing (30%) datasets. Then, 13 landslide causative factors (LCFs) were extracted from geo-spatial database and analysed by measuring collinearity among factors and assessing their contribution in landslide occurrence using different feature selection methods for inclusion in susceptibility modelling. Thereafter, six employed models were trained to produced landslide susceptibility maps of investigated road-section. Finally, the area under receiver operating characteristics (AU-ROC) curve and various statistical measures were applied to validate and compare the performance of modeled landslide susceptibility. The results revealed that no collinearity issue exists among all 13 LCFs, and all six models exhibited satisfying performance in predicting landslide susceptibility of study area. However, BLR model have produced most promising and optimum results as compared to other models with AU-ROC (0.881), Matthew’s correlation coefficient (0.609), Kappa coefficient (0.604), accuracy (0.797) and F-score (0.787). The outcomes of this study can be used as pertinent guide for preventing and managing the landslide disaster risk along Neelum Highway and beyond.

Acoustic and Genetic Data Can Reduce Uncertainty Regarding Populations of Migratory Tree-Roosting Bats Impacted by Wind Energy

Wind turbine-related mortality may pose a population-level threat for migratory tree-roosting bats, such as the hoary bat (Lasiurus cinereus) in North America. These species are dispersed within their range, making it impractical to estimate census populations size using traditional survey methods. Nonetheless, understanding population size and trends is essential for evaluating and mitigating risk from wind turbine mortality. Using various sampling techniques, including systematic acoustic sampling and genetic analyses, we argue that building a weight of evidence regarding bat population status and trends is possible to (1) assess the sustainability of mortality associated with wind turbines; (2) determine the level of mitigation required; and (3) evaluate the effectiveness of mitigation measures to ensure population viability for these species. Long-term, systematic data collection remains the most viable option for reducing uncertainty regarding population trends for migratory tree-roosting bats. We recommend collecting acoustic data using the statistically robust North American Bat Monitoring Program (NABat) protocols and that genetic diversity is monitored at repeated time intervals to show species trends. There are no short-term actions to resolve these population-level questions; however, we discuss opportunities for relatively short-term investments that will lead to long-term success in reducing uncertainty.

The weight of criminal judicial evidence

The study is devoted to the current issue of the weight of criminal judicial evidence, which is understudied in the national doctrine. The legislator, having introduced this evaluative concept in 2012 (Paragraph 1, Part 11, Article 1 of 178 CCP), did not provide its normative definition. As a result, there is a conceptual uncertainty, which is inappropriate given the requirements of the rule of law (Article 8 of the Constitution of Ukraine, Article 8 of the CCP). Therefore, the purpose of study is to attempt to formulate a definition of the “weight of evidence”, to propose a scheme of work of a lawyer to determine the signs of this activity phenomenon in situations of making appropriate procedural decisions. The study is based on the activity methodology using a number of special methods – search and bibliographic; semantic; Aristotelian; hermeneutic; historical-legal; comparative-legal; functional analysis; generalisation. The study formulated the definition of the “weight of evidence” as an activity characteristic. The latter is the result of a pragmatic logical and legal evaluation of ad hoc evidence within its totality. Thus, certain evidence is prioritised due to the greater suitability attributed to it by the lawyer to serve as a convincing evidence base of the procedural decision. Therefore, the conclusion is substantiated that the “weight of available evidence” as its activity characteristic is “the fifth element” of the structure of “criminal judicial evidence” along with such characteristics as “credibility”, “admissibility”, “reliability”, and “sufficiency”. The study includes conclusion that the introduction by the legislator in 2012 of the “weight of available evidence” meets the requirements of the evidentiary practice of the modern national adversarial process and the ECHR

Capturing a Comprehensive Picture of Biological Events From Adverse Outcome Pathways in the Drug Exposome

Background: The chemical part of the exposome, including drugs, may explain the increase of health effects with outcomes such as infertility, allergies, metabolic disorders, which cannot be only explained by the genetic changes. To better understand how drug exposure can impact human health, the concepts of adverse outcome pathways (AOPs) and AOP networks (AONs), which are representations of causally linked events at different biological levels leading to adverse health, could be used for drug safety assessment.Methods: To explore the action of drugs across multiple scales of the biological organization, we investigated the use of a network-based approach in the known AOP space. Considering the drugs and their associations to biological events, such as molecular initiating event and key event, a bipartite network was developed. This bipartite network was projected into a monopartite network capturing the event–event linkages. Nevertheless, such transformation of a bipartite network to a monopartite network had a huge risk of information loss. A way to solve this problem is to quantify the network reduction. We calculated two scoring systems, one measuring the uncertainty and a second one describing the loss of coverage on the developed event–event network to better investigate events from AOPs linked to drugs.Results: This AON analysis allowed us to identify biological events that are highly connected to drugs, such as events involving nuclear receptors (ER, AR, and PXR/SXR). Furthermore, we observed that the number of events involved in a linkage pattern with drugs is a key factor that influences information loss during monopartite network projection. Such scores have the potential to quantify the uncertainty of an event involved in an AON, and could be valuable for the weight of evidence assessment of AOPs. A case study related to infertility, more specifically to “decrease, male agenital distance” is presented.Conclusion: This study highlights that computational approaches based on network science may help to understand the complexity of drug health effects, with the aim to support drug safety assessment.

Integrative Assessment of Sediments Affected by CO2 Enrichment: A Case Study in the Bay of Santos—SP, Brazil

CO2 enrichment in the marine environment caused by leakages from carbon capture and storage technologies may occur over operational procedures. An integrated approach using weight-of-evidence was applied to assess the environmental risk associated with the acidification caused by CO2 enrichment in coastal sediments from Santos (Brazil). Chemical analyses (metal(loid)s and organic contaminant (e.g., hydrocarbons), toxicity tests (amphipods mortality, sea-urchin embryo-larval development) and macro-benthic community structure alteration assessment were performed with different acidified scenarios (pH 8.0–6.0) for two stations with different contamination degrees. These lines of evidence were statistically analyzed and integrated (multivariate analysis and ANOVA). Results of toxicity showed significant chronic effects starting at pH 7.0 while acute effects were observed starting at pH 6.5. The macro-benthic community integrity showed significant differences for all treatments at the Piaçaguera channel station, considered to be moderately contaminated. Results from the multivariate analysis correlated toxic effects and increase in the mobility of some elements with acidification. Also, the biological indexes were correlated with concentrations of dissolved Zn in seawater. The pH of 6.0 was extremely toxic for marine life due to its high acidification and metal bioavailability. The approach herein identified and discriminated the origin of the degradation caused by the acidification related to the enrichment of CO2.

Vague multi-attribute group decision-making method based on evidence theory with a new aspect to solve weights

In order to solve the problems of weight solving and information aggregation in the Vague multi-attribute group decision-making, this paper first solves the weight of Vague evaluation value, and then fuses the information of Vague sets through evidence theory, and obtains an information aggregation algorithm for Vague multi-attribute group decision-making. Firstly, The algorithm draws on the idea of solving the weight of evidence in the improved evidence theory algorithm, and calculates the weight of Vague evaluation value, and revises the original evaluation information after obtaining the weight of each Vague evaluation value. Secondly, this algorithm analyzes the mathematical relationship between the Vague sets and the evidence theory, and uses the evidence theory to fuse the evaluation information to obtain the final Vague evaluation value of each alternative. Finally, this algorithm uses a score function to calculate the score of each alternative to determine the best alternative. The algorithm given in the paper enables decision-makers to make rational decisions in uncertain environments, and then select the best alternative.

Resilience in Relation to Multimorbidity in Older Adults: A Scoping Review

Multimorbidity is widespread, costly, and associated with a range of deleterious symptoms, affecting 70-80 % of older adults. Resilience in late life has been the focus of considerable research to understand differences in vulnerabilities and recovery from stressors relevant to multimorbidity. Despite this, previous reviews have not focused on resilience in relation to multimorbidity in older adults; therefore, this study synthesized relevant literature. The study design was a scoping review following JBI methodology. Searched electronic databases included PubMed, Embase, CINAHL, and PsycINFO. Data were extracted by two independent reviewers and charted using Garrard’s review matrix method. Gough’s weight of evidence criteria were used to appraise quality. Of 468 retrieved studies, 14 met inclusion criteria, primarily from the US, UK, and Canada. Most resilience in multimorbidity frameworks operationalize resilience as dependent on the socio-environmental context of older adults. Resilience was commonly considered a dynamic process, but only one study was longitudinal. Measures were primarily psychological or psycho-social in nature and did not include biological or physical measures of resilience. Quality of life and quality of care were common outcomes; resilience significantly related to these outcomes. Findings indicate both the important relationships of resilience with outcomes of multimorbidity, as well as multiple gaps in our current understanding of resilience in relation to multimorbidity. Results highlight the need for studies with diverse populations across diverse cultures, studies that incorporate multidimensional measures, with attention to physiological or physical properties of resilience, and longitudinal studies that capture the dynamic process of resilience in multimorbidity.