Ecosystem-level responses to multiple stressors using a time-dynamic food-web model: The case of a re-oligotrophicated coastal embayment (Saronikos Gulf, E Mediterranean).

Multiple stressors may combine in unexpected ways to alter the structure of ecological systems, however, our current ability to evaluate their ecological impact is limited due to the lack of information concerning historic trophic interactions and ecosystem dynamics. Saronikos Gulf is a heavily exploited embayment in the E Mediterranean that has undergone significant ecological alterations during the last 20 years including a shift from long-standing eutrophic to oligotrophic conditions in the mid-2000's. Here we used a historical Ecopath food-web model of Saronikos Gulf (1998-2000) and fitted the time-dynamic module Ecosim to biomass and catch time series for the period 2001-2020. We then projected the model forward in time from 2021 to 2050 under 8 scenarios to simulate ecosystem responses to the individual and combined effect of sea surface temperature increase, primary productivity shifts and fishing effort release. Incorporating trophic interactions, climate warming, fishing and primary production improved model fit, depicting that both fishing and the environment have historically influenced ecosystem dynamics. Retrospective simulations of the model captured historical biomass and catch trends of commercially important stocks and reproduced successfully the marked recovery of marine resources 10 years after re-oligotrophication. In future scenarios increasing temperature had a detrimental impact on most functional groups, increasing and decreasing productivity had a positive and negative effect on all respectively, while fishing reductions principally benefited top predators. Combined stressors produced synergistic or antagonistic effects depending on the direction and magnitude of change of each stressor in isolation while their overall impact seemed to be strongly mediated via food-web interactions. Such holistic approaches advance of our mechanistic understanding of ecosystems enabling us to develop more effective management strategies in the face of a rapidly changing marine environment.

Disaggregated energy use and socioeconomic sustainability within OECD countries.

This study investigates the relationship between disaggregated energy use, human development, trade openness, economic growth, urbanization, and sustainability index in OECD countries from 2014 to 2019. Static, quantile, and dynamic panel data approaches are employed. The findings reveal that fossil fuels such as petroleum, solid fuels, natural gas, and coal decrease sustainability. On the contrary, alternative sources such as renewable and nuclear energy seem to contribute positively to sustainable socioeconomic development. It is also interesting to note that alternative energy sources strongly influence socioeconomic sustainability in the lower and upper quantiles. Also, the human development index and trade openness improve sustainability, while urbanization seems to be an obstacle in complying with sustainability goals within OECD countries. Policymakers should revisit their strategies toward sustainable development by mitigating fossil fuels and urbanization and promoting human development, trade openness, and alternative energy sources as drivers of economic progress.

Green, resilient, agile, and sustainable fresh food supply chain enablers: evidence from India.

The existing research on fresh food supply chains (FFSC) sustainability consisting of fur fundamental pillars, namely green (G), resilient (R), agile (A), and sustainability (S) (hereafter GRAS), is explored sparsely and needs thorough investigation. Further, conceptualization and mutual interactions among GRAS enablers that can help perpetuate sustainable supply chains (SSC) still need to be addressed. This study proposes a methodological framework to evaluate the SCS from the perspective of GRAS enablers with an application for the Indian FFSC. A mixed-method sequential approach was used with interviews followed by integrated fuzzy interpretive structural modelling-decision-making trial and evaluation laboratory (FISM-DEMATEL) techniques. The study recognizes twenty supply chain sustainability (SCS) enablers through an extensive literature review and discussions with the expert group. The research discloses that the firms' 'organization culture' acts as the most powerful driver in achieving sustainability in FFSC, followed by the firms' 'environmental certification program' and 'financial strength.' This investigation helps the managers/policymakers of the Indian FFSC to ascertain and comprehend the most significant SCS enablers to achieve sustainability in the supply chain (SC). The causation of SCS enablers supports the managers in systematically focusing on the most significant enablers and working towards their successful implementation. According to our knowledge, this is the first scholarly work that establishes hierarchies and interrelationships among GRAS enablers, thereby providing a holistic picture to decision-makers while adapting such practices. Supplementary Information: The online version contains supplementary material available at 10.1007/s10479-023-05176-x.

Logistics performance: critical factors in the implementation of end-of-life management practices in the pharmaceutical care process.

The management of healthcare waste and end-of-life medication coming from different sources are primary challenges faced by public health leaders. Several factors may be considered critical and inhibitive to reverse logistics within the context of waste management processes. If those factors are not addressed, they may become obstacles to reverse logistics implementation. The purpose of this study is to evaluate the effect that critical factors play in the adoption of end-of-life management practices for medication and its influence on logistics performance. Literature provided some critical factors: management factor, collaboration factor, information technology factor, infrastructure factor, politics factor, financial and economic factor, end-of-life management practices, and logistics performance factor. A sample of 67 professionals from the public pharmaceutical care process answered a structured questionnaire. The collected data was analyzed using partial least square-structural equation modeling. The theoretical structural test confirmed eleven out of the fifteen hypotheses considered. The results have indicated that end-of-life management practices exert a direct influence on logistics performance. The analysis confirmed a direct effect of the information technology factor on end-of-life management practices, but not a moderation effect. Findings have contributed to the literature by providing deeper insights into the relationship between end-of-life management practices for medicines and logistics performance. Moreover, it supports health managers' decision-making in the pharmaceutical care process improvement and engagement with solid waste management policies.

Policies for supporting the regional circular economy and sustainability.

The Circular Economy and Sustainability are among the greatest challenges faced by policymakers, producers, and consumers. Circular Economy processes demand less from the environment since they can minimize waste generation and, hence, can be powerful tools to combat the negative effects of climate change. Additionally, following subsidiarity principles, public policies supporting the Circular Economy should be designed at the lowest levels of public administrations-this provides huge opportunities for regional governments to design, implement and monitor these policies. This editorial of the special issue explores and discusses implications for those policies before introducing the five papers published in the special issue dedicated to policies for regional economy and sustainability. While some of the papers attempt to conceptualize sustainable development through a microeconomic perspective, others have a clear macroeconomic empirical focus. In consequence, this special issue provides a rich body of work for further Circularity and Sustainability nexus studies.

Food web interactions in a human dominated Mediterranean coastal ecosystem.

Mediterranean coastal ecosystems provide various valuable ecosystem goods and services; however, they are vulnerable to ecological degradation due to a dramatic increase in resource use and environmental stress. Disentangling the effects of multiple human interventions on coastal ecosystems requires whole description of food web interactions using quantitative tools. A mass balance Ecopath model has been developed here for Saronikos Gulf, a naturally oligotrophic Mediterranean coastal ecosystem with a long history of human interventions. Our main focus was to describe the structure and functioning of the ecosystem, investigate the trophic interplay among the various compartments of the food web under the impact of mixed multi-gear fisheries, and to quantify resilience related emergent ecosystem properties. To this end, we reviewed a large amount of local and regional biological information which was integrated in 40 functional groups covering all trophic levels, while fishing activities were described with 7 fleets. The model shared characteristics of both productive (e.g., high amount of flows) and oligotrophic systems (e.g., low biomass accumulation) and presented typical features of Mediterranean ecosystem functioning, such as the importance of detritus as an energy source, strong benthic-pelagic coupling and the dominance of the pelagic compartment in terms of total production and consumption. Trophic forcing in the ecosystem of Saronikos Gulf was complex with both top-down and bottom-up drivers being important. Zooplankton was the central nexus between basal resources and higher trophic levels, while top predators such as hake, squids and anglerfish were identified as keystone species presenting a significant overall effect on the food web via direct and indirect trophic interactions. Ecological indicators depicted a moderately complex food-web of a large and immature ecosystem with its strengths in reserve being affected by environmental degradation. Additionally, exploitation indices classified fishing activities in Saronikos Gulf as unsustainable, affecting several target groups, including high trophic level species. However, the morphological and bathymetric complexity of Saronikos Gulf seems to function as a natural ecological reserve for the ecosystem by providing nursery grounds to various species (e.g., hake, small pelagic fishes) and supporting important fish stocks for local fisheries.

Predictability analysis of the Pound's Brexit exchange rates based on Google Trends data.

During the last decade, the use of online search traffic data is becoming popular in examining, analyzing, and predicting human behavior, with Google Trends being a popular tool in monitoring and analyzing the users' online search patterns in several research areas, like health, medicine, politics, economics, and finance. Towards the direction of exploring the Sterling Pound's predictability, we employ Google Trends data from the last 5 years (March 1st, 2015 to February 29th, 2020) and perform predictability analysis on the Pound's exchange rates to Euro and Dollar. The period selected includes the 2016 UK referendum as well as the actual Brexit day (January 31st, 2020), with the analysis aiming at analyzing the Pound's relationships with Google query data on Pound-related keywords and topics. A quantile dependence method is employed, i.e., cross-quantilograms, to test for directional predictability from Google Trends data to the Pound's exchange rates for lags from zero to 30 (in weeks). The results indicate that statistically significant quantile dependencies exist between Google query data and the Pound's exchange rates, which point to the direction of one of the main implications in this field, that is to examine whether the movements in one economic variable can cause reactions in other economic variables.

Assessing the Methods, Tools, and Statistical Approaches in Google Trends Research: Systematic Review.

BACKGROUND: In the era of information overload, are big data analytics the answer to access and better manage available knowledge? Over the last decade, the use of Web-based data in public health issues, that is, infodemiology, has been proven useful in assessing various aspects of human behavior. Google Trends is the most popular tool to gather such information, and it has been used in several topics up to this point, with health and medicine being the most focused subject. Web-based behavior is monitored and analyzed in order to examine actual human behavior so as to predict, better assess, and even prevent health-related issues that constantly arise in everyday life. OBJECTIVE: This systematic review aimed at reporting and further presenting and analyzing the methods, tools, and statistical approaches for Google Trends (infodemiology) studies in health-related topics from 2006 to 2016 to provide an overview of the usefulness of said tool and be a point of reference for future research on the subject. METHODS: Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines for selecting studies, we searched for the term "Google Trends" in the Scopus and PubMed databases from 2006 to 2016, applying specific criteria for types of publications and topics. A total of 109 published papers were extracted, excluding duplicates and those that did not fall inside the topics of health and medicine or the selected article types. We then further categorized the published papers according to their methodological approach, namely, visualization, seasonality, correlations, forecasting, and modeling. RESULTS: All the examined papers comprised, by definition, time series analysis, and all but two included data visualization. A total of 23.1% (24/104) studies used Google Trends data for examining seasonality, while 39.4% (41/104) and 32.7% (34/104) of the studies used correlations and modeling, respectively. Only 8.7% (9/104) of the studies used Google Trends data for predictions and forecasting in health-related topics; therefore, it is evident that a gap exists in forecasting using Google Trends data. CONCLUSIONS: The monitoring of online queries can provide insight into human behavior, as this field is significantly and continuously growing and will be proven more than valuable in the future for assessing behavioral changes and providing ground for research using data that could not have been accessed otherwise.

Integrating Smart Health in the US Health Care System: Infodemiology Study of Asthma Monitoring in the Google Era.

BACKGROUND: With the internet's penetration and use constantly expanding, this vast amount of information can be employed in order to better assess issues in the US health care system. Google Trends, a popular tool in big data analytics, has been widely used in the past to examine interest in various medical and health-related topics and has shown great potential in forecastings, predictions, and nowcastings. As empirical relationships between online queries and human behavior have been shown to exist, a new opportunity to explore the behavior toward asthma-a common respiratory disease-is present. OBJECTIVE: This study aimed at forecasting the online behavior toward asthma and examined the correlations between queries and reported cases in order to explore the possibility of nowcasting asthma prevalence in the United States using online search traffic data. METHODS: Applying Holt-Winters exponential smoothing to Google Trends time series from 2004 to 2015 for the term "asthma," forecasts for online queries at state and national levels are estimated from 2016 to 2020 and validated against available Google query data from January 2016 to June 2017. Correlations among yearly Google queries and between Google queries and reported asthma cases are examined. RESULTS: Our analysis shows that search queries exhibit seasonality within each year and the relationships between each 2 years' queries are statistically significant (P<.05). Estimated forecasting models for a 5-year period (2016 through 2020) for Google queries are robust and validated against available data from January 2016 to June 2017. Significant correlations were found between (1) online queries and National Health Interview Survey lifetime asthma (r=-.82, P=.001) and current asthma (r=-.77, P=.004) rates from 2004 to 2015 and (2) between online queries and Behavioral Risk Factor Surveillance System lifetime (r=-.78, P=.003) and current asthma (r=-.79, P=.002) rates from 2004 to 2014. The correlations are negative, but lag analysis to identify the period of response cannot be employed until short-interval data on asthma prevalence are made available. CONCLUSIONS: Online behavior toward asthma can be accurately predicted, and significant correlations between online queries and reported cases exist. This method of forecasting Google queries can be used by health care officials to nowcast asthma prevalence by city, state, or nationally, subject to future availability of daily, weekly, or monthly data on reported cases. This method could therefore be used for improved monitoring and assessment of the needs surrounding the current population of patients with asthma.

Quantifying the Effect of Macroeconomic and Social Factors on Illegal E-Waste Trade.

As illegal e-waste trade has been significantly growing over the course of the last few years, the consequences on human health and the environment demand immediate action on the part of the global community. Though it is argued that e-waste flows from developed to developing countries, this subject seems to be more complex than that, with a variety of studies suggesting that income per capita is not the only factor affecting the choice of regions that e-waste is illegally shipped to. How is a country's economic and social development associated with illegal e-waste trade? Is legislation an important factor? This paper aims at quantifying macroeconomic (per capita income and openness of economy) and social (human development and social progress) aspects, based on qualitative data on illegal e-waste trade routes, by examining the percentage differences in scorings in selected indicators for all known and suspected routes. The results show that illegal e-waste trade occurs from economically and socially developed regions to countries with significantly lower levels of overall development, with few exceptions, which could be attributed to the fact that several countries have loose regulations on e-waste trade, thus deeming them attractive for potential illegal activities.

Application of the Multi-Attribute Value Theory for engaging stakeholders in groundwater protection in the Vosvozis catchment in Greece.

Multi-Attribute Value Theory (MAVT) was used to investigate stakeholders' preferences and beliefs in ameliorating a deteriorating ecosystem, i.e. Vosvozis River and Ismarida Lake in Northeastern Greece. Various monetary and environmental criteria were evaluated with scores and weights by different stakeholder groups and key individuals such as farmers, fishermen, entrepreneurs, residents and ecologists to elicit their preferences concerning alternative protection scenarios. The ultimate objective was to propose policy recommendations for a sustainable water resources management for the case study area. The analysis revealed an overwhelming agreement among stakeholders regarding the dire need for immediate actions in order to preserve and enhance Vosvozis ecosystem. With a two stage evaluation process, the MAVT analysis led to a high consensus among the stakeholders on the alternative that favors water recycling from the wastewater treatment plant combined with small dams for rainwater harvesting.

Identification of recycled water with an empirically derived symbol increases its probability of use.

The experiment described in this paper compared the effects of two systems for labeling recycled water on potential consumers' intention to use this resource; the current identifying symbol used worldwide (purple color for pipes, containers, and tanks) and a new, empirically derived and validated set of symbols that provide specific information on water quality and positive comparative information. In total, 807 face-to-face surveys were carried out. Subjects were asked to rate their intentions for using different qualities of recycled water for commercial agriculture as well as for using products and facilities irrigated with recycled water, either in the presence of the established symbol or the new, empirically derived symbols. Potential consumers' self-reported intentions to use recycled water were reliably higher in the presence of empirically derived symbols with positive comparative information than in the presence of the conventional identification symbol. This program of research provides a model for the application of principles of behavioral psychology to enhance the consumer acceptance of technological advances that preserve natural resources and protect ecosystems.