Overcoming the gender bias in ecology and evolution: is the double-anonymized peer review an effective pathway over time?

Male researchers dominate scientific production in science, technology, engineering, and mathematics (STEM). However, potential mechanisms to avoid this gender imbalance remain poorly explored in STEM, including ecology and evolution areas. In the last decades, changes in the peer-review process towards double-anonymized (DA) have increased among ecology and evolution (EcoEvo) journals. Using comprehensive data on articles from 18 selected EcoEvo journals with an impact factor >1, we tested the effect of the DA peer-review process in female-leading (i.e., first and senior authors) articles. We tested whether the representation of female-leading authors differs between double and single-anonymized (SA) peer-reviewed journals. Also, we tested if the adoption of the DA by previous SA journals has increased the representativeness of female-leading authors over time. We found that publications led by female authors did not differ between DA and SA journals. Moreover, female-leading articles did not increase after changes from SA to DA peer-review. Tackling female underrepresentation in science is a complex task requiring many interventions. Still, our results highlight that adopting the DA peer-review system alone could be insufficient in fostering gender equality in EcoEvo scientific publications. Ecologists and evolutionists understand how diversity is important to ecosystems' resilience in facing environmental changes. The question remaining is: why is it so difficult to promote and keep this "diversity" in addition to equity and inclusion in the academic environment? We thus argue that all scientists, mentors, and research centers must be engaged in promoting solutions to gender bias by fostering diversity, inclusion, and affirmative measures.

Reservoir population ecology, viral evolution and the risk of emerging infectious disease.

The ecology and life history of wild animals influences their potential to harbour infectious disease. This observation has motivated studies identifying empirical relationships between traits of wild animals and historical patterns of spillover and emergence into humans. Although these studies have identified compelling broad-scale patterns, they are generally agnostic with respect to underlying mechanisms. Here, we develop mathematical models that couple reservoir population ecology with viral epidemiology and evolution to clarify existing verbal arguments and pinpoint the conditions that favour spillover and emergence. Our results support the idea that average lifespan influences the likelihood of an animal serving as a reservoir for human infectious disease. At the same time, however, our results show that the magnitude of this effect is sensitive to the rate of viral mutation. Our results also demonstrate that viral pathogens causing persistent infections or a transient immune response within the reservoir are more likely to fuel emergence. Genetically explicit stochastic simulations enrich these mathematical results by identifying relationships between the genetic basis of transmission and the risk of spillover and emergence. Together, our results clarify the scope of applicability for existing hypotheses and refine our understanding of emergence risk.

Spatio-Temporal Analysis and Influencing Factors of Rural Resilience from the Perspective of Sustainable Rural Development.

Rural resilience is not only a comprehensive reflection of "thriving businesses, pleasant living environments, social etiquette and civility, effective governance, and prosperity". It is also the unity of resilience in industry, ecology, culture, organization and livelihood. This paper uses the entropy weight-TOPSIS method to measure the rural resilience level in 31 regions in China and analyzes the configuration of influencing factors with the Fuzzy-set qualitative comparative analysis (fsQCA). The results of the study are as follows: (1) The level of rural resilience in China showed a stable increase from 2010 to 2019, but the overall level was low, with large regional disparities, showing a significant positive spatial correlation. (2) In the high-level rural resilience explanatory path, labor-driven, cultural-driven and market-labor-technology linkage-driven play a core role, while administrative force is not playing a significant role. In the explanation path of non-high level rural resilience, the market-labor absent, administrative-market absent and cultural absent hinder the improvement of rural resilience. In summary, we put forward the following suggestions. Policy renovation and support should be strengthened. Adaption to local conditions should be considered in order to achieve sustainable and differentiated development. Development should be coordinated and balanced in different regions so as to achieve an overall resilience level in rural areas.

The Impact of Tax Reduction and Fee Reduction Based on Big Data Algorithm on the High-Quality Development of the Real Economy under the Action of Coupling Effect or Substitution Effect.

The basic idea of the mass of medical growth is to adhere to local market price thinking with a Chinese touch and follow the development policy of "quality first, efficiency first." It insists on properly handling a series of important relationships betwixt socialism and market economy, the first to drive the rich later, the government and the market, equality and efficiency, short-term growth and long-term development, China and the international economy, ecology and growth of the region. Under the guidance of the qualitative thinking theory, it combines the strategic goals of China's economic qualitative development and actively draws on the research results of other countries. It uses big data algorithms to focus on the impact of qualitative development on tax and income reduction in the real economy. It conducts research experiments on the impact of tax reduction and fee reduction based on big data algorithms on the top-notch growth of the real economy. Its experimental data show that: in 2018, the share of primary, tertiary, and primary sector in China's dimensional economy top-notch growth coordination index was 7.2%, 40.7%, and 52.2%, respectively. Its contribution rate to economic growth was 4.2%, 36.1%, and 59.7%, respectively. From these data, it can be concluded that the top-notch growth of the real economy is getting better and better under the influence of tax reduction and fee reduction by big data algorithms.

Association between obesity and diabetes prevalence and COVID-19 mortality in Mexico: an ecological study.

INTRODUCTION: Mortality rates associated with COVID-19 vary widely between countries and, within countries, between regions. These differences might be explained by population susceptibility, environmental factors, transmission dynamics, containment strategies, and diagnostic approaches. We aimed to analyze if obesity and diabetes prevalence are associated with higher COVID-19 mortality rates in Mexico. METHODOLOGY: We analyzed the mortality rate for each of the 2,457 municipalities in Mexico, one of the countries with highest COVID-19 mortality rate, during the first seven months of the pandemic to identify factors associated with higher mortality, including demographic, health-related characteristics (prevalence of obesity, diabetes, and hypertension in adults older than 20 years old), and altitude. RESULTS: During the first seven months of the COVID-19 pandemic there were 85,666 deaths reported in Mexico, with a cumulative mortality rate of 67 per 100,000 population. The mean mortality rate for the 2,457 municipalities in Mexico was 33.9 per 100,000 population. At a municipal level, the prevalence of diabetes and obesity, as well as high human development index, and location at < 500 or > 2000 above sea level were associated with higher mortality rate. CONCLUSIONS: Elevated obesity and diabetes prevalence explain, in part, high COVID-19 mortality rates registered in certain municipalities in Mexico. These results suggest that a regionalized approach should be considered to successfully limit the impact of SARS-CoV-2.

Microbial Ecology and Evolution Are Essential for Understanding Pandemics.

Ecology and evolution, especially of microbes, have never been more relevant than in our global fight against SARS-CoV-2, the virus that causes COVID-19. Understanding how populations of SARS-CoV-2 grow, disperse, and evolve is of critical importance to managing the COVID-19 pandemic, and these questions are fundamentally ecological and evolutionary in nature. We compiled data from bioRxiv and medRxiv preprint abstracts and US National Institutes of Health Research Project grant abstracts to visualize the impact that the pivot to COVID-19 research has had on the study of microbes across biological disciplines. Finding that the pivot appears weaker in ecology and evolutionary biology than in other areas of biology, we discuss why the ecology and evolution of microbes, both pathogenic and otherwise, need renewed attention and investment going forward.

The future of zoonotic risk prediction.

In the light of the urgency raised by the COVID-19 pandemic, global investment in wildlife virology is likely to increase, and new surveillance programmes will identify hundreds of novel viruses that might someday pose a threat to humans. To support the extensive task of laboratory characterization, scientists may increasingly rely on data-driven rubrics or machine learning models that learn from known zoonoses to identify which animal pathogens could someday pose a threat to global health. We synthesize the findings of an interdisciplinary workshop on zoonotic risk technologies to answer the following questions. What are the prerequisites, in terms of open data, equity and interdisciplinary collaboration, to the development and application of those tools? What effect could the technology have on global health? Who would control that technology, who would have access to it and who would benefit from it? Would it improve pandemic prevention? Could it create new challenges? This article is part of the theme issue 'Infectious disease macroecology: parasite diversity and dynamics across the globe'.

Analysing the Relationship between University Students' Ecological Footprint and Their Connection with Nature and Pro-Environmental Attitude.

In the last decade, universities worldwide have adopted various measures intended to promote sustainability in higher education and include it in the curriculum. However, although this paradigm shift appears to be contributing to students' acquisition of the knowledge, skills and values necessary to fight for a more sustainable world, serious global crises such as the present SARS-CoV-2 pandemic oblige us to rethink our behaviour and spur us to accelerate the move towards a deep-seated commitment to the environment and people. Therefore, the aims of this study were (a) to explore consumption habits in students at four Spanish universities by analysing their individual ecological footprint (EF); (b) to develop indices of connection with nature and a pro-environmental attitude and to determine relationships between these indices and students' consumption. Among other factors, our results showed that private university students have a higher EF than public university students; that food consumption has the greatest impact on individuals' EF; and that those who consume more sustainably do not show a more pro-environmental attitude or feel a greater connection with nature. Therefore, we conclude that there was no apparent direct relationship between study participants' convictions and their daily behaviour. There is a pressing need in education to demonstrate the connection between our actions and their environmental impact.

Positioning zoonotic disease research in forced migration: A systematic literature review of theoretical frameworks and approaches.

BACKGROUND: The emergence and transmission of zoonotic diseases are driven by complex interactions between health, environmental, and socio-political systems. Human movement is considered a significant and increasing factor in these processes, yet forced migration remains an understudied area of zoonotic research-due in part to the complexity of conducting interdisciplinary research in these settings. OBJECTIVES: We conducted a systematic review to identify and analyze theoretical frameworks and approaches used to study linkages between forced migration and zoonotic diseases. METHODS: We searched within eight electronic databases: ProQuest, SCOPUS, Web of Science, PubMed, PLoSOne, Science Direct, JSTOR, and Google Scholar, to identify a) research articles focusing on zoonoses considering forced migrants in their study populations, and b) forced migration literature which engaged with zoonotic disease. Both authors conducted a full-text review, evaluating the quality of literature reviews and primary data using the Critical Appraisal Skills Programme (CASP) model, while theoretical papers were evaluated for quality using a theory synthesis adapted from Bonell et al. (2013). Qualitative data were synthesized thematically according to the method suggested by Noblit and Hare (1988). RESULTS: Analyses of the 23 included articles showed the increasing use of interdisciplinary frameworks and approaches over time, the majority of which stemmed from political ecology. Approaches such as EcoHealth and One Health were increasingly popular, but were more often linked to program implementation and development than broader contextual research. The majority of research failed to acknowledge the heterogeneity of migrant populations, lacked contextual depth, and insufficient acknowledgments of migrant agency in responding to zoonotic threats. CONCLUSIONS: Addressing the emergence and spread of zoonoses in forced migration contexts requires more careful consideration and use of interdisciplinary research to integrate the contributions of social and natural science approaches. Robust interdisciplinary theoretical frameworks are an important step for better understanding the complex health, environment, and socio-political drivers of zoonotic diseases in forced migration. Lessons can be learned from the application of these approaches in other hard-to-reach or seldom-heard populations.

Assessing the Impact of Green Hiring on Sustainable Performance: Mediating Role of Green Performance Management and Compensation.

The global need to preserve ecology has propelled the green movement across the globe. An emerging managerial challenge for all organizations is to protect natural resources by reducing their negative impact on the environment and increase sustainable performance. Greening is the need of the age to conserve natural resources. This study investigates the impact of green human resource management practice-i.e., green hiring-on the sustainable performance of public and private healthcare organizations. A quantitative research approach was used for data collection. Scale survey of 160 responses was gathered from public and private healthcare organizations. Partial least square-structural equation modeling was used for data analysis. The study results suggest that green recruitment has a positive and significant impact on environmental performance, economic performance, and social performance. Path coefficients test also revealed that green performance management and compensation significantly mediate the relationship between green hiring and sustainable performance of public and private healthcare organizations. This study is helpful for organizations in adapting GHRM practices that will benefit the organizations in all ways. This study also provides a better understanding to policymakers on how to promote GHRM practices and increase sustainability in organizations.

Ecology and Evolution of Betacoronaviruses.

The crown-like outline of the virions of coronaviruses will long endure as the iconic image of 2020 - the year of the COVID-19 pandemic. This major human health emergency has been caused by a betacoronavirus, as have others in the past. In this chapter, we outline the taxonomy of betacoronaviruses and their properties, both genetic and biological. We discuss their recombinational and mutational histories separately to show that the sequence of the RaTG13 bat virus isolate is the closest currently known full-length genetic homolog of that of the severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2). However, the RaTG13 bat virus and SARS-CoV-2 have probably diverged over 20 years. We discuss the ecology of their pangolin and bat hosts and conclude that, like other recent viral pandemics, the underlying cause of the SARS-CoV-2 emergence is probably the relentless growth of the world's human population and the overexploitation and disturbance of the environment.