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New Zealand's environmental policies and political situation may have had an impact on all energy and non-energy factors that affect economic growth and CO2 emissions. Therefore, it is important to understand the impacts of these factors on NZ's CO2 emissions and economic growth, as the interconnectedness of these factors provides policymakers with valuable insights. This study assesses the various influences of energy, financial, government, and other non-energy factors on both economic growth and carbon emissions in New Zealand. To estimate the impact variables, this study uses the autoregressive distributed lag method using annual data from 1990 to 2020. The results suggest that renewable and non-renewable energy consumption, foreign direct investment, and good governance stimulate economic growth. Natural resource rents, on the other hand, have a negative impact on economic growth due to their high cost to the economy. Furthermore, the use of renewable energy, financial development, and good governance significantly reduce CO2 emissions. The exchange rate also contributes to reducing carbon emissions due to its negative impact on economic growth and trade. Finally, fossil fuel consumption is the major contributor to higher CO2 emissions. Promoting clean foreign direct investment can boost economic growth and preserve environmental quality when supported by good governance and stable exchange rates.

ABSTRACT: Objectives: Persistent colonization with Staphylococcus aureus is associated with a higher risk of invasive infections. With increasing rates of colonization, especially with antibiotic-resistant strains, it may be useful to identify specific characteristics of colonization that confer a greater infection risk. Therefore, whole-genome sequencing (WGS) of an S. aureus strain isolated from a medical student identified as a persistent carrier in Cartagena, Colombia, was performed to better characterize the strain and to identify genetic components associated with virulence and antimicrobial resistance. Methods: Antimicrobial susceptibility testing was performed for several antibiotics. Total genomic DNA was extracted and WGS was performed on a PacBio RS II sequencing platform. Whole-genome assembly was generated using PacBio SMRT Analysis v.2.3.0 and HGAP v.1.2. In silico analysis of the chromosomal and plasmid components of this strain was performed using tools available online. Results: Strain COL52-A5 was identified as a Panton–Valentine leukocidin (PVL)-positive methicillin-resistant S. aureus (MRSA) carrying staphylococcal cassette chromosome mec (SCCmec) type IVa and was resistant to cefoxitin, erythromycin, clindamycin and tetracycline. The completely closed genome of strain COL52-A5 was 2 820 086 bp with a GC content of 32.84% and it harboured one large plasmid, two active prophages, five antimicrobial resistance determinants and several virulence factors. The allelic profile was consistent with sequence type ST923 (CC8). Conclusion: Genome analysis of strain COL52-A5 found numerous virulence and resistance factors. Further comparison of genomic sequences from persistent and intermittent strains is required to gain insights into the genomic features that favour persistent carriage in healthy individuals.

Background: The anterior nares are the main ecological niche for Staphylococcus aureus, an important commensal and opportunistic pathogen. Medical students are frequently colonized by a variety of pathogens. Microbial interactions in the human nose can prevent or favor colonization by pathogens, and individuals colonized by pathogens have increased risk of infection and are the source of transmission to other community members or susceptible individuals. According to recent studies, the microbiome from several anatomic areas of healthy individuals varies across different ethnicities. Although previous studies analyzed the nasal microbiome in association with S. aureus carriage, those studies did not provide information regarding ethnicity of participants. Our aim was to assess S. aureus nasal carriage patterns and prevalence among medical students from Colombia, a country of Hispanic origin, and to investigate possible associations of colonization and nasal microbiome composition (bacterial and fungal) in a subgroup of students with known S. aureus carriage patterns. Methods: Nasal swabs from second-year medical students were used to determine prevalence and patterns of S. aureus nasal carriage. Based on microbiological results, we assigned participants into one of three patterns of S. aureus colonization: persistent, intermittent, and non-carrier. Then, we evaluated the composition of nasal microbial communities (bacterial and fungal) in 5 individuals from each carriage category using 16S rRNA and Internal-Transcribed-Spacer sequencing. Results: Prevalence of S. aureus nasal carriage among medical students was 28%. Carriage of methicillin-resistant strains was 8.4% and of methicillin-sensitive strains was 19.6%. We identified 19.6% persistent carriers, 17.5% intermittent carriers, and 62.9% non-carriers. Conclusions: Analysis of nasal microbiome found that bacterial and fungal diversity was higher in individuals colonized by S. aureus than in non-carriers; however, the difference among the three groups was non-significant. We confirmed that fungi were present within the healthy anterior nares at substantial biomass and richness.

Models can provide a structured way to think about adoption and provide a method to investigate the impacts of different factors in the adoption process. With at least 70 years of research in the adoption of agricultural innovations, there has been a proliferation of adoption models, both conceptual and numerical. This diversity has resulted in a lack of convergence in the way adoption is defined, explained, and measured, causing agricultural extension and policy to rely on a body of literature that is often not able to offer clear recommendations on the variables or mechanisms that can be used to design interventions. We conducted a review of conceptual models to clarify the concepts and approaches used in the practice of modeling adoption in agriculture. We described general adoption conceptual models originating from sociology, psychology, economics, and marketing and reviewed examples of models specifically defined for the study of adoption in agriculture. We also broadly assessed the ability of conceptual models to support building numerical models. Our review covered a range of modeling approaches for diffusion and individual adoption, illustrating different perspectives used in the literature. We found that key elements that should be used in adoption models for agriculture include: a way to assess the performance of the proposed new technology (e.g., relative advantage, both economic and non-economic) in relation to the existing technology or practice in place, the process of learning about this advantage, the interaction between individual decision-making and external influences, and characteristics of potential adopters affecting their attitudes towards the technology. We also detected inconsistencies in how different elements are treated in different conceptual models, particularly behavioral elements such as attitudes, motivations, intentions, and external influences. In terms of modeling, the main implication of these inconsistencies is the difficulty to generate quantitative evidence to support these models since multiple interpretations make it difficult to achieve consistency in the definition of observable, measurable variables that can be used to quantify cause-effect relationships. Suggestions for further research in the field include: questioning whether the adoption of all technologies and practices can be represented by the same adoption or learning process, exploring the dynamics in the relationship between adopters and technology before and after adoption, and questioning the basic assumptions behind the process of individual decision-making models and the role of collective decision-making. Findings from this review can be considered by adoption researchers and modelers in their work to assist policy and extension efforts to improve the uptake of future beneficial agricultural innovations.

This paper uses a historical analysis of agricultural development to explore functional integrity of the New Zealand rural landscape arising from a national agenda to pursue greater agricultural outputs. The concept of functional integrity is extended by Maori farming as it introduces a further set of functions related to the aspirations of indigenous landholders. A land-use integrated decision-mak­ing framework (IDMF) was developed and applied to four Maori farm case studies that wanted to use land performance to meet their aspirational goals. The IDMF has linked indigenous knowledge with Western science and industry knowledge to form a holistic framework for framing questions, and evaluating and designing land-use options that have the potential to balance multiple out­comes and confer functional integrity. The IDMF provides a framework that will organise multiple activities and coordinate different quantitative and qualitative data sets in a visual format that allows for discussion within a collective deci­sion-making environment. The framework was found to be useful for exploring and making transparent the trade-off between differing functions. This under­standing guides the exploration of strategies that will enable the attainment of several functions simultaneously.