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Overgrazing affects the grass‐livestock balance and endangers grassland ecological security. Despite extensive studies conducted on identifying and quantifying grazing intensity, there is still room for improvement in the research on gridding grazing intensity, particularly in areas with limited data on the Qinghai–Tibet Plateau. Therefore, we proposed a grazing intensity spatialization method using geographically weighted random forest (GWRF) to gain further insights into the spatial heterogeneity of alpine grassland grazing intensity. This method incorporates multiple remote sensing data related to human activities and natural factors, as well as annual livestock statistics at the township level over several years, while adequately considering the spatial autocorrelation of grazing intensity. Additionally, we employed Lindeman Merenda Gold (LMG), the geographical detector model, and the structural equation model (SEM) to assess the contribution and influence path of driving factors to grazing intensity. We also utilize partial correlation analysis and dual‐phase mapping to examine the impact of natural and human activities on the spatial distribution of grazing intensity. The results demonstrate that the GWRF‐based grazing intensity spatial model accurately predicts grazing intensity by demonstrating its consistency with township‐scale livestock data (R2 = 0.92 (p < 0.01), RMSE = 1.07). This provides valuable technical support for quantifying grazing intensity in alpine pastoral areas with limited data availability. We evaluate trends in grazing intensity and observe an increase in Gar and Purang counties. Furthermore, population density, normalized difference vegetation index (NDVI), and temperature are identified as three influential factors affecting grazing intensity in alpine pastoral areas. Additionally, other factors indirectly impact grazing intensity by influencing population density and NDVI levels, while their interactions amplify their overall influence. The dual‐phase mapping technique has demonstrated a significant impact of population density on 45.92% (p < 0.01) of the study area, emphasizing the substantial influence of human activities on grazing intensity. Our study provides a novel framework for spatially analyzing grazing intensity and unraveling the intricated driving mechanisms behind spatiotemporal changes, particularly in areas with limited data availability. [ABSTRACT FROM AUTHOR]

Mini‐grid electrification constitutes an increasingly important solution to universal access to energy, notably in off‐grid rural Africa. Rural electrification has important implications for mitigating the immigration trends of the rural population toward urban regions. In this study, we adopted a mediation model to investigate the direct and indirect effects of mini‐grid electrification on the urbanization process, and multivariate regression is employed as a robustness check. More specifically, with the support of a mini‐grid project in Ghana, we conducted a survey to assess the perception of the local population about the impact of rural electrification on healthcare, education, employment, and security and further examined the impact of these development outcomes on their willingness to immigrate to cities. The study's findings suggested that the development of rural electrification helped improve education, healthcare, security, and employment, significantly affecting urbanization. Our study concluded that increased electricity access through mini‐grids tends to reduce the urbanization trends in rural Ghana. [ABSTRACT FROM AUTHOR]

We empirically evaluate the effect of China's Belt and Road Initiative (BRI) on the energy intensity of countries along the route. Furthermore, we decompose this overall effect into direct effects via connectivity and indirect effects through development. We apply a relatively new synthetic control method based on interactive fixed effects to identify the causal effects of the BRI. Our main results include: (1) the overall effect of the BRI reduces the energy intensity of countries along the route by 0.0152 toes per thousand dollars, of which the direct effect is 0.0125 (82%); (2) the indirect effect in the current status is limited, mainly through the contradictory effects of economic growth and industrial structural change; and (3) countries along the route with a lower level of development, higher levels of energy technology, more abundant energy endowments, and less stringent carbon regulations experience a greater reduction in energy intensity after the BRI. [ABSTRACT FROM AUTHOR]

The effects of mineral composition (N, P, K, Mg, Fe, Cu, and Zn) against fire blight caused by Erwinia amylovora, the most devastating disease of pome fruits, was investigated in pear. Due to the transport physiology of minerals, the leaf contained higher concentrations of every mineral analyzed, especially macro-minerals (N, P, K, and Mg) compared to the fruit. Minerals obtained from the leaves were not statistically correlated with resistance to fire blight, however all the minerals examined in the fruit, except for K, were found to be significant. Increased P and Mg concentrations were associated with disease resistance, while N, Zn, Fe, and Cu were associated with susceptibility. Nitrogen-causing susceptibility exerted 61% of this impact through itself directly and was sharply distinguished from other mineral compounds. Furthermore, the indirect effect of nitrogen on disease susceptibility through Cu (39%), Zn (33%), and Fe (30%) was even higher than the direct effect of these minerals (21%, 24%, and 29%, respectively). The direct effects of P (13%) and Mg (10%), which are associated with an increase in resistance, were lower than the indirect effects (19% and 29%, respectively) due to their negative correlation with nitrogen, showing that the main effect of these minerals was in suppressing the negative effects of nitrogen on susceptibility by maintaining mineral balance. [ABSTRACT FROM AUTHOR]

Our work was motivated by the question whether, and to what extent, well‐established risk factors mediate the racial disparity observed for colorectal cancer (CRC) incidence in the United States. Mediation analysis examines the relationships between an exposure, a mediator and an outcome. All available methods require access to a single complete data set with these three variables. However, because population‐based studies usually include few non‐White participants, these approaches have limited utility in answering our motivating question. Recently, we developed novel methods to integrate several data sets with incomplete information for mediation analysis. These methods have two limitations: (i) they only consider a single mediator and (ii) they require a data set containing individual‐level data on the mediator and exposure (and possibly confounders) obtained by independent and identically distributed sampling from the target population. Here, we propose a new method for mediation analysis with several different data sets that accommodates complex survey and registry data, and allows for multiple mediators. The proposed approach yields unbiased causal effects estimates and confidence intervals with nominal coverage in simulations. We apply our method to data from U.S. cancer registries, a U.S.‐population‐representative survey and summary level odds‐ratio estimates, to rigorously evaluate what proportion of the difference in CRC risk between non‐Hispanic Whites and Blacks is mediated by three potentially modifiable risk factors (CRC screening history, body mass index, and regular aspirin use). [ABSTRACT FROM AUTHOR]

The present study investigated the mediating effects of emotional intelligence and self-esteem between youth sports participation and life satisfaction, as well as the comparative effects of different types of sports involvement (team, individual, and non-participation) on these selected variables. A sample of 1053 Portuguese adolescents (612 girls and 441 boys), aged between 12 and 18 years (M = 14.40; SD = 1.55), completed the following self-report measures: the Wong and Law Emotional Intelligence Scale, the Rosenberg Self-Esteem Scale, and the Satisfaction with Life Scale. The structural equation modeling results indicated a complete mediating role of two emotional intelligence dimensions (use of emotion and self-emotional appraisal) and self-esteem in the relationship between sports participation and adolescents' life satisfaction. Team sport participants reported higher emotional intelligence and self-esteem scores than their non-sport participant counterparts who revealed lower levels of emotion use than their individual sport participant peers. These findings provide novel insights into the potential emotional and psychological mechanisms underlying the association between youth sports participation and life satisfaction. [ABSTRACT FROM AUTHOR]

The study aimed at understanding the direct and indirect effects of epistemological beliefs as an independent variable in academic procrastination as a dependent variable, through self-regulated learning as a mediating variable among Al-Azhar University students. The researcher proposed a model in which he assumed that there were direct and indirect effects of epistemological beliefs in academic procrastination. The basic research sample consisted of (503) students at the third year from Faculty of Education in Tafhana AlAshraf, Al-Azhar University. The researcher developed the academic procrastination scale, the self-regulated learning scale, and the epistemological beliefs scale, which were all used as research tools. The following findings were revealed after statistical analysis of the data using the path analysis method: There is a good match between the proposed path analysis model and the data of the research sample with regard to the various relationships between the research variables, there are also statistically significant direct effects of epistemological beliefs in academic procrastination. Findings also revealed statistically significant direct effects of epistemological beliefs in self-regulated learning, and statistically significant direct effects of self-regulated learning in academic procrastination. Finally, there are statistically significant indirect effects of epistemological beliefs in academic procrastination through self-regulated learning. [ABSTRACT FROM AUTHOR]

The aim of this investigation was to evaluate the direct and indirect effects of yield components on bean yield (kg/ha) in a completely randomized block design during two semesters (2019–2020), the performance of 21 bean genotypes (six parents and fifteen hybrids) was evaluated. This experiment was conducted at the CEUNP experimental center of the Universidad Nacional de Colombia-Palmira. Statistical analysis was based on genetic correlations determined through the "agricolae, aariability, hmisc and tidyverse" libraries in R. Results showed that average pod weight and number of pods per plant contribute positively to yield expression. However, the number of seeds per pod and pod length are components that have a negative contribution on pod yield per area. These results suggested that characters such as average pod weight and number of pods per plant can be considered as selection criteria for the genetic improvement of pod yield in bean. The data were subjected to analysis of variance and Scott-Knott tests (p ≤ 0.05). The analysis was based on genetic correlations determined through the libraries "agricolae, variability, Hmisc and tidyverse" in R. The results showed that average pod weight and number of pods per plant contribute positively to yield expression. However, the number of seeds per pod and pod length are components that have a negative contribution on pod yield per area. These results suggested that characters such as average pod weight and number of pods per plant can be considered as selection criteria for the genetic improvement of pod yield in bean. [ABSTRACT FROM AUTHOR]

In this paper, we explore the relations among institutional quality, households' level of trust, and stock market participation. We find that institutional quality has a significant impact on both trust and participation. The individual level of trust significantly affects participation, but trust plays a small role in the effect of institutional quality on participation. Further, we demonstrate that immigrants are affected by the institutional quality of both their country of residence and their home country, and that education emerges as an important learning factor in immigrants' adaptation to new institutional environments. [ABSTRACT FROM AUTHOR]

Since the geopolitical conflict between Russia and Ukraine, Western countries led by the United States and the European Union have launched several energy sanctions against Russia. How will sanctions and countersanctions on energy trade affect the EU-Russia and the world’s energy trade pattern? This paper sets six energy trade scenarios based on the degree of energy sanctions and counter-sanction measures imposed by the EU and Russia. We use the global multi-region comparative static CGE model to simulate the changes in macroeconomic indicators in major countries worldwide. The diversion effect of energy trade and the impact on the national economy caused by geographical risks quantitatively analyzes. The results show: (1) Energy sanctions will cause economic damage to both sides, in the worst-case scenario, the EU economic loss reaches 1.488%, the Russian loss reaches 4.8%, and worldwide inflation will rise; (2) Russia’s counter-sanctions will have a direct economic impact on the EU, but will not improve its economic situation; (3) Energy sanctions will bring about a direct energy trade transfer effect, the EU’s energy imports will be diverted to non-Russian markets, and Russian energy exports will also shift to Asian markets, and energy trade between the two economies will be significantly reduced; (4) Energy supply will have a profound impact on the world’s economy and society, leading to social instability and a decline in total output of 2.895%. Energy games will have a negative impact on the world’s carbon emission reduction and energy consumption structure transformation. Through quantitative analysis of the impact of energy sanctions on the world economy and society, the energy game caused by the geopolitical crisis will harm both parties involved in the game and the world economy. The world pattern will return from the development pattern of cooperative division of labor to a situation of conflict and confrontation, which is not conducive to the transformation of energy trade and consumption structure under market rules.

To investigate causal mechanisms, causal mediation analysis decomposes the total treatment effect into the natural direct and indirect effects. This article examines the estimation of the direct and indirect effects in a general treatment effect model, where the treatment can be binary, multi-valued, continuous, or a mixture. We propose generalized weighting estimators with weights estimated by solving an expanding set of equations. Under some sufficient conditions, we show that the proposed estimators are consistent and asymptotically normal. Specifically, when the treatment is discrete, the proposed estimators attain semiparametric efficiency bounds. Meanwhile, when the treatment is continuous, the convergence rates of the proposed estimators are slower than N − 1 / 2 ; however, they are still more efficient than those constructed from the true weighting function. A simulation study reveals that our estimators exhibit satisfactory finite-sample performance, while an application shows their practical value. [ABSTRACT FROM AUTHOR]

This article contrasts whether the sectors with a GDP close to the average contribute more to the economic system through their employment multipliers and/or dispersion effects than those with a higher GDP. To achieve this, an 11-year horizon (2008-2018) and the 11 main centers of Chile's macro territories [Norte Chico (6) and Patagonia (5)] are used as a reference. The input-output matrices are used as source of information from which the variables GDP, employment multiplier and dispersion coefficients are obtained, the latter understood as those that allow quantifying the scope of the repercussions of an economic activity, by means of its direct and/or indirect effects. The results allow us to conclude that economic activities with a GDP close to the average, such as that of the education sector, show diffused effects that support the idea of facilitating development through changes in their production versus others that, with high GDPs, show concentrated effects that therefore limit their contribution in terms of interaction. These results will contribute to the establishment of economic development policies according to the particularities of each territory. [ABSTRACT FROM AUTHOR]

The present study investigated the mediating effects of emotional intelligence and self-esteem between youth sports participation and life satisfaction, as well as the comparative effects of different types of sports involvement (team, individual, and non-participation) on these selected variables. A sample of 1053 Portuguese adolescents (612 girls and 441 boys), aged between 12 and 18 years (M = 14.40; SD = 1.55), completed the following self-report measures: the Wong and Law Emotional Intelligence Scale, the Rosenberg Self-Esteem Scale, and the Satisfaction with Life Scale. The structural equation modeling results indicated a complete mediating role of two emotional intelligence dimensions (use of emotion and self-emotional appraisal) and self-esteem in the relationship between sports participation and adolescents’ life satisfaction. Team sport participants reported higher emotional intelligence and self-esteem scores than their non-sport participant counterparts who revealed lower levels of emotion use than their individual sport participant peers. These findings provide novel insights into the potential emotional and psychological mechanisms underlying the association between youth sports participation and life satisfaction.

The article presents the results of studying the influence of quantitative traits on the barley plant performance. Thirty typical plants were selected for each of the 28 genotypes spring two-row barley cultivars and their height, productive tillering capacity, spike length, number and weight of kernels from the main spike, 1000-kernel weight, and performance were measured. As a result, we found significant positive correlations between the performance and productive tillering capacity and weight of kernels from the main spike. Path analysis showed that the weight of kernels from the main spike had the greatest direct effect on the plant performance (0.61). We have established that the paths “spike length – weight of kernels from the main spike – performance” and “kernel number per spike – weight of kernels from the main spike – performance” are of the greatest importance in select for the barley plant performance.

The way in which terrestrial organisms use the acoustic realm is fundamentally important and shapes behavior, populations, and communities, but how background acoustics, or noise, influence the patterns and processes in ecology is still relatively understudied. In this review, we summarize how background acoustics have traditionally been studied from the signaling perspective, discuss what is known from a receiver's perspective, and explore what is known about population- and community-level responses to noise. We suggest that there are major gaps linking animal physiology and behavior in noise to fitness; that there is a limited understanding of variation in hearing within and across species, especially in the context of real-world acoustic conditions; and that many puzzling responses to noise could be clarified with a community-level lens that considers indirect effects. Failing to consider variation in acoustic conditions, and the many ways organisms use and interact via this environmental dimension, risks a limited understanding of natural systems. [ABSTRACT FROM AUTHOR]

Stand structure, which links function and management, plays a crucial role in regulating forest ecosystems and influencing biodiversity. Nevertheless, knowledge of the effect of climate change on stand structure and plant diversity is still poorly understood on a large scale. To explore the effects of various climate conditions on stand structure–plant diversity, we conducted a comprehensive analysis of data from 1272 plots across China's temperate and subtropical forests. Leveraging the structural equation model (SEM), we explored the direct and indirect effects of climate, topography, and tree diversity on understory woody and herbaceous plants with respect to stand structure. Furthermore, we evaluated the effect size of stand structure on understory vegetation diversity under different climatic zones. Our results showed that tree size variation (CV DBH) and stem density (SD) were the key drivers for understory woody plants, while the stand structure complexity index (SSCI) was more important for understory herbaceous diversity. Furthermore, the positive effects of stand structure differed across various climate zones and were enhanced with an increase in the climatic gradient. For instance, the impact of SD on understory woody plants, as well as the influence of the SSCI on the diversity of understory herbaceous vegetation, were both strengthened. These findings raise our awareness of the pressing need to manage stand structure heterogeneity differently across different climate zones, and different management also needs to be implemented among different understory plant types. It becomes evident that distinct forest management measures must be applied under future climate change and forest management practices in order to preserve biodiversity. [ABSTRACT FROM AUTHOR]

This paper investigates the intersection of income and race in structuring access to higher education among students that participate in a national high-stakes exam in Brazil. Our objectives are (i) to estimate the probability of students coming from different income strata, racial groups, and performance levels to access higher education and (ii) to decompose income and racial effects into direct (net of educational performance) and indirect effects (through educational performance). Our data comes from a panel of high school graduates tracked between 2012 and 2017 and allow us to describe the following findings. Firstly, the probability of entering higher education is always higher among candidates from higher income strata. Second, there is a convergence in admission probabilities across the performance scale. Third, the admission curve across a performance scale is much steeper among applicants from low-income strata compared to richer students. In all of these results, students self-identified as black, brown, or indigenous (BBI) are less likely to transition to higher education than whites, even though they are in the same income and performance strata. We suggest that students from privileged socioeconomic backgrounds benefit from alternative entry strategies, such as paying tuition at less competitive private colleges. For students from low-income strata, the main alternative for entering higher education is through high academic performance. By decomposing racial effects, we show the cumulative effect of racial stratification; the gap between white and BBI students is both related to higher propensity of transitioning to higher education and higher educational performance. [ABSTRACT FROM AUTHOR]

Abstract Background New genomic techniques (NGTs) allow new genotypes and traits to be developed in different ways and with different outcomes compared to previous genetic engineering methods or conventional breeding (including non-targeted mutagenesis). EU GMO regulation requires an assessment of their direct and indirect effects that may be immediate, delayed or cumulative. Such effects may also result from the interactions of NGT organisms simultaneously present in a shared receiving environment or emerge from a combination of their traits. This review elaborates such potential interactions based on a literature review and reasoned scenarios to identify possible pathways to harm. Main findings NGT organisms might be introduced into the environment and food chains on a large-scale, involving many traits, across a broad range of species and within short periods of time. Unavoidably, this would increase the likelihood that direct or indirect effects will occur through interactions between NGT organisms that are, for example simultaneously present within a shared environment. It has to be assumed that the cumulative effects of these NGT organisms may exceed the sum of risks identified in the distinct ‘events’. Consequently, risk assessors and risk managers not only need to consider the risks associated with individual NGT organisms (‘events’), but should also take account of risks resulting from their potential interactions and combinatorial effects. In addition, a prospective technology assessment could help the risk manager in defining criteria to minimize potential unintended interactions between NGT organisms through limiting the scale of releases. Conclusions If genetically engineered (GE) organisms derived from NGTs are released into the environment, their potentially negative impacts need to be minimized. As with all GE organisms, it is, therefore, crucial to not only assess the risks of the individual events, but also their potential interactions which can trigger direct and indirect effects with adverse impacts. It is necessary to develop hypotheses and specific scenarios to explore interactions between NGT organisms and possible pathways to harm from the perspective of the precautionary principle. In addition, the introduction prospective technology assessment could provide an instrument for the risk manager to control the scale of releases of NGT organisms.

Most scholars support the increase in carbon dioxide (CO2) emissions as one of the major causes of the increase in global climate change. Therefore, reducing CO2 emissions from the main emitter countries, including Iran as the sixth emitter, is important to deal with the harmful effects of global climate change. Accordingly, the main aim of this paper was to analyze the social, economic, and technical factors affecting CO2 emissions in Iran. Previous studies on diverse variables affecting emissions are not very accurate and reliable as they do not consider indirect effects. This study applied a structural equation model (SEM) to estimate the direct and indirect impacts of factors on the emissions by panel data for 28 provinces of Iran from 2003 to 2019. According to geographical location, three distinct regions, the north, center, and south of Iran were considered. The findings suggest that a 1% increase in social factor directly increased CO2 emissions by 2.23% (in the north) and 1.58% (in the center), but indirectly reduced emissions by 0.41% (in the north) and 0.92% (in the center). Hence, the total effects of the social factor on CO2 emissions were estimated at 1.82%, and 0.66% in the northern, and central regions, respectively. In addition, the total effects of the economic factor on CO2 emissions were estimated at 1.52%, and 0.73% in those regions. The results of this study showed that the direct effects of a technical factor on CO2 emissions were negative in the north and center. However, they were positive in the south of Iran. Based on the empirical results of this study, three policy implications are discussed in order to control CO2 emissions in regional distinctions of Iran as follows: First, policymakers should pay attention to the social factor, i.e., the growth of human capital in the southern region with the aim of increasing sustainable development. Second, Iranian policymakers must prevent unilaterally increasing gross domestic product (GDP) and financial development in the north and center. Third, policymakers should pay attention to the technical factor, i.e., improving energy efficiency, as well as upgrading information and communications technology (ICT) in the northern and central regions, and limiting the technical factor in the southern region. [ABSTRACT FROM AUTHOR]

The article describes the modelling of strategic infrastructure project effects and results using methods of analysing direct and indirect effects and helping to determine the feasibility of railway infrastructure project implementation. Neglecting this fact significantly reduces the overall efficiency of infrastructure projects, and in some cases leads to the wrong decisions that reject project implementation.Investigations made by authors allow to identify, classify and quantitatively estimate the direct and indirect effects from the implementation of infrastructure projects, including integrated assessment of budgetary efficiency and an assessment of economic effects for the development of territories.Among indirect effects the special attention was paid to the multimodal effects resulting from the redistribution of passenger and cargo flows and more rational capacity of the transportation system. The attention was paid to the multiplier effects caused in related sectors of the economy, agglomeration effects leading to increased connectivity of urban and suburban areas and the corresponding growth in employment, investment and productivity, the effects of optimising subsidies, etc.Scenario forecasting procedures were used within the presented investigations. Macroeconomic effects, bottlenecks in the railway system impact on the level of undertransportation of goods as well as price arbitrage were determined for various scenarios.

Abstract Background Mediation analysis aims at estimating to what extent the effect of an exposure on an outcome is explained by a set of mediators on the causal pathway between the exposure and the outcome. The total effect of the exposure on the outcome can be decomposed into an indirect effect, i.e. the effect explained by the mediators jointly, and a direct effect, i.e. the effect unexplained by the mediators. However finer decompositions are possible in presence of independent or sequential mediators. Methods We review four statistical methods to analyse multiple sequential mediators, the inverse odds ratio weighting approach, the inverse probability weighting approach, the imputation approach and the extended imputation approach. These approaches are compared and implemented using a case-study with the aim to investigate the mediating role of adverse reproductive outcomes and infant respiratory infections in the effect of maternal pregnancy mental health on infant wheezing in the Ninfea birth cohort. Results Using the inverse odds ratio weighting approach, the direct effect of maternal depression or anxiety in pregnancy is equal to a 59% (95% CI: 27%,94%) increased prevalence of infant wheezing and the mediated effect through adverse reproductive outcomes is equal to a 3% (95% CI: -6%,12%) increased prevalence of infant wheezing. When including infant lower respiratory infections in the mediation pathway, the direct effect decreases to 57% (95% CI: 25%,92%) and the indirect effect increases to 5% (95% CI: -5%,15%). The estimates of the effects obtained using the weighting and the imputation approaches are similar. The extended imputation approach suggests that the small joint indirect effect through adverse reproductive outcomes and lower respiratory infections is due entirely to the contribution of infant lower respiratory infections, and not to an increased prevalence of adverse reproductive outcomes. Conclusions The four methods revealed similar results of small mediating role of adverse reproductive outcomes and early respiratory tract infections in the effect of maternal pregnancy mental health on infant wheezing. The choice of the method depends on what is the effect of main interest, the type of the variables involved in the analysis (binary, categorical, count or continuous) and the confidence in specifying the models for the exposure, the mediators and the outcome.

Background: New genomic techniques (NGTs) allow new genotypes and traits to be developed in different ways and with different outcomes compared to previous genetic engineering methods or conventional breeding (including non-targeted mutagenesis). EU GMO regulation requires an assessment of their direct and indirect effects that may be immediate, delayed or cumulative. Such effects may also result from the interactions of NGT organisms simultaneously present in a shared receiving environment or emerge from a combination of their traits. This review elaborates such potential interactions based on a literature review and reasoned scenarios to identify possible pathways to harm. Main findings: NGT organisms might be introduced into the environment and food chains on a large-scale, involving many traits, across a broad range of species and within short periods of time. Unavoidably, this would increase the likelihood that direct or indirect effects will occur through interactions between NGT organisms that are, for example simultaneously present within a shared environment. It has to be assumed that the cumulative effects of these NGT organisms may exceed the sum of risks identified in the distinct 'events'. Consequently, risk assessors and risk managers not only need to consider the risks associated with individual NGT organisms ('events'), but should also take account of risks resulting from their potential interactions and combinatorial effects. In addition, a prospective technology assessment could help the risk manager in defining criteria to minimize potential unintended interactions between NGT organisms through limiting the scale of releases. Conclusions: If genetically engineered (GE) organisms derived from NGTs are released into the environment, their potentially negative impacts need to be minimized. As with all GE organisms, it is, therefore, crucial to not only assess the risks of the individual events, but also their potential interactions which can trigger direct and indirect effects with adverse impacts. It is necessary to develop hypotheses and specific scenarios to explore interactions between NGT organisms and possible pathways to harm from the perspective of the precautionary principle. In addition, the introduction prospective technology assessment could provide an instrument for the risk manager to control the scale of releases of NGT organisms. [ABSTRACT FROM AUTHOR]

One main motivation of attracting inward foreign direct investment (FDI) for emerging economies is to obtain knowledge spillovers from developed countries and promote domestic innovation. The effects of FDI on innovation include both the direct effects from FDI on targeted domestic firms and indirect effects from foreign ownership on other foreign and domestic firms' innovation. Applying a design with a two-stage randomization procedure that allows for both direct and indirect effects of FDI on innovation and allows these two effects to vary with the share of foreign firms in a well-specified cluster, we empirically investigate the effects of inward FDI on Chinese firms' innovation using patent filings as a proxy for innovation. Our findings indicate that the potential innovation of firm varies with the share of foreign firms in the cluster. The approach used in this paper can help researchers and policymakers to better understand the benefits of inward FDI promotion programs, agglomeration and regional policy. [ABSTRACT FROM AUTHOR]

The article presents the results of studying the influence of quantitative traits on the barley plant performance. Thirty typical plants were selected for each of the 28 genotypes spring two-row barley cultivars and their height, productive tillering capacity, spike length, number and weight of kernels from the main spike, 1000-kernel weight, and performance were measured. As a result, we found significant positive correlations between the performance and productive tillering capacity and weight of kernels from the main spike. Path analysis showed that the weight of kernels from the main spike had the greatest direct effect on the plant performance (0.61). We have established that the paths "spike length - weight of kernels from the main spike - performance" and "kernel number per spike - weight of kernels from the main spike - performance" are of the greatest importance in select for the barley plant performance. [ABSTRACT FROM AUTHOR]

Climate change alters surface water availability (WA; precipitation minus evapotranspiration, P − ET) and consequently impacts agricultural production and societal water needs, leading to increasing concerns on the sustainability of water use. Although the direct effects of climate change on WA have long been recognized and assessed, indirect climate effects occurring through adjustments in terrestrial vegetation are more subtle and not yet fully quantified. To address this knowledge gap, here we investigate the interplay between climate‐induced changes in leaf area index (LAI) and ET and quantify its ultimate effect on WA during the period 1982–2016 at the global scale, using an ensemble of data‐driven products and land surface models. We show that ~44% of the global vegetated land has experienced a significant increase in growing season‐averaged LAI and climate change explains 33.5% of this greening signal. Such climate‐induced greening has enhanced ET of 0.051 ± 0.067 mm year−2 (mean ± SD), further amplifying the ongoing increase in ET directly driven by variations in climatic factors over 36.8% of the globe, and thus exacerbating the decline in WA prominently in drylands. These findings highlight the indirect impact of positive feedbacks in the land–climate system on the decline of WA, and call for an in‐depth evaluation of these phenomena in the design of local mitigation and adaptation plans. [ABSTRACT FROM AUTHOR]

Canadian federal policy mandates a floor price on greenhouse gas emissions in all provinces and territories or an equivalent quantity instrument. Provinces that implement a system consistent with the federal benchmark maintain control of revenues. Provinces that do not implement a carbon price are subject to a federally administered pricing system, with revenue recycling via lump-sum household rebates. Using rich synthetic household microdata, we quantify the direct and indirect tax burden on households and carbon pricing revenues in each province. We also calculate carbon pricing revenue available to each province. Using these data, we measure the net cost to households and the overall progressivity of carbon pricing under four revenue recycling scenarios: (a) a means-tested sales tax credit increase, (b) a lump-sum dividend, (c) a sales tax rate reduction, and (d) a personal income tax basic exemption increase. We find that the carbon tax is generally progressive even without revenue recycling, the sales tax credit and lump-sum rebate are progressive, the sales tax rate reduction is mostly regressive, and the income tax change is regressive. We also show that Canada's output-based pricing system for large emitters helps to mitigate indirect carbon pricing costs with a notable effect in reducing household costs. [ABSTRACT FROM AUTHOR]

Path coefficient analyses were applied to detect the direct and indirect effects upon grain yield/plant in three groups as a: each of seed index, biological yield/plant and weight of spikes/plant; b: each of thrashing index, biological yield/plant and weight of spikes/plant; and c: all studied grain yield attributes. The three groups of path analyses were applied through F4 and F5 population of The direct effects of biological yield and .early and late pedigree line selection weight of spikes spikes/plant were decreased from the starting generations to final selections in the three groups, except final early selections possessed increased values in group two (g2) and group three (g3) for weight of spikes/plant. Otherwise, the direct effect of harvest index on grain yield was increased from started base to final selections. These results exhibited that the direct effects of those three traits on grain yield were responded differently according to the rearrangement of their genetic make-up across the different generations of selections and the type of path analysis. [ABSTRACT FROM AUTHOR]

F1 materials of half-diallel crosses for nine characters in lentils were studied for correlation, path-coefficient, and selection index. The phenotypic component of variation (σ2p) was higher than the genotypic component of variation (σ2g). The highest σ2g and σ2pwere obtained for CAMF. Investigation showed that genotypic correlations (rg) were higher than the respective phenotypic correlations (rp) for most of the characters. SWPP showed a highly significant and positive correlation coefficient with other characters except for the NPBFF at the genotypic level and except NPBFF and DF at the phenotypic level. The highest significant and positive genotypic correlation coefficient was recorded for NSBFF with PdWPP at the genotypic level and PdWPP with SWPP at the phenotypic level. PdWPP had the highest positive direct effect on SWPP at both genotypic and phenotypic levels. The maximum expected genetic gain of 4603.196% was found when NPBFF and RW were included in the index. These two characters a had high correlation coefficient with most of the characters studied as well as a direct effect at the genotypic level may be considered as primary yield components. [ABSTRACT FROM AUTHOR]

Globally, pharmaceuticals and personal care products (PPCPs) are detected in surface waters receiving wastewater, yet their presence in biota, remain largely understudied. To address this, we conducted a study that measured 46 PPCPs in spot water samples and fish caught up- and downstream from wastewater treatment plants (WWTPs) in Victoria, Australia. We sampled 15 sites located along four waterways following a 3-site design: WWTP-discharge('hotspot'), 'upstream'(∼2 km) and 'downstream'(∼2 km). Spot water and fish were also sampled at reference sites >100 km from WWTP discharge (n = 3). Additionally, spot water samples were taken from WWTP effluent outflows (n = 3). From each locality, we analysed 3–12 fish (n = 131 total). In waterways, passive samplers (POCIS; ∼28d, n = 19 PPCPs) were also deployed. Individual fish (axial muscle) and water were analysed with LC-MS-MS. We found that PPCP concentrations in environmental surface water ranged from<0.02–0.97 μg/L. In WWTP effluent, the range was <0.02–1.4 μg/L. Of the 46 PPCPs analysed, 12 were detected in spot water samples and five in fish. In water, the highest concentration detected was for antidepressant venlafaxine (3 μg/L). The most frequently detected PPCPs: venlafaxine (54.9%), metoprolol (41.2%), propranolol (29.4%), carbamazepine (29.4%), caffeine (17.6%) and sulfamethoxazole (17.6%). Out of 131 fish analysed, 35 fish had detectable levels of PPCPs in the muscle tissue. The highest muscle concentrations were: venlafaxine (150 μg/kg, redfin perch), and sertraline (100 μg/kg, eel). Bioaccumulation factors ranged from 104 to 341L/kg for venlafaxine in redfins, 21-1,260L/kg for carbamazepine in redfins and eels, and 367-3,333L/kg for sertraline in eels. Based on our human health risk calculations for venlafaxine, carbamazepine, sertraline, triclosan, and caffeine, consumption of fish does not pose a significant risk to human health. Despite this, most of the detected PPCPs in surface waters exceeded 10 ng/L trigger value, which has led to further investigations by EPA. Our study highlights the need for using multiple lines of evidence for estimating risks of PPCPs. [Display omitted] • 15 sites were sampled for 46 x PPCPs in freshwater and fish. • At the discharge or downstream sites, fish had distinct exposure signatures. • Carbamazepine, venlafaxine, sertraline, triclosan, and caffeine detected in fish. • Antidepressant venlafaxine detected up to 150 μg/kg in redfin perch axial muscle. [ABSTRACT FROM AUTHOR]

• We provide a fine-scale daily quantification of the time-accumulation and -lag effects of precipitation on carbon fluxes. • Time-accumulation and -lag effects significantly amplify the combined effects of precipitation on carbon fluxes. • The synthesis of decadal site observations with broad regional scale analyses reveals a time-delayed response of carbon fluxes to precipitation. Precipitation (PRE) plays a vital role in hydrological processes, ecological vegetation, and land-atmosphere interactions in semi-arid regions. Previous research has mainly focused on the impact of PRE on large-scale regional climate change and ecological evolution. However, there have been few studies on the long-term effects of PRE on carbon fluxes in these regions, especially the time-accumulation and -lag effects. Here, we employed observational data from the Semi-Arid Climate and Environment Observatory of Lanzhou University (SACOL) and integrated multiple data sources, including remote sensing and carbon flux simulation data, to quantitatively assess the lagged response of carbon fluxes to PRE and elucidate the underlying mechanisms from multiple perspectives. Characterization of PRE, soil water content (SWC) and carbon fluxes at SACOL qualitatively reveals the existence of a time-delayed response of carbon fluxes to PRE, both on monthly and finer daily temporal scales. The average lagged response of net ecosystem exchange (NEE) and gross primary productivity (GPP) to accumulated PRE (APRE) is approximately 42 days. When considering time-accumulation and -lag effects, the combined direct and indirect effects of APRE on NEE and GPP increase by 0.37 and 0.58, respectively. Notably, preceding APRE primarily exerts a direct effect on current carbon fluxes, whereas the impact of SWC at a depth of 0.1 m is primarily mediated through the memory effect of preceding APRE, resulting in an indirect effect on carbon fluxes. These findings emphasize the importance of preceding APRE. Significantly, our subsequent study indicates that the delay in NEE and GPP responses to APRE also extends to approximately 40 to 50 days at the regional scale. Our findings emphasize the significant time effects of APRE on carbon fluxes, and considering these effects will contribute to a better understanding of the interplay between PRE and vegetation over semi-arid regions in China. [ABSTRACT FROM AUTHOR]

Stand structure, which links function and management, plays a crucial role in regulating forest ecosystems and influencing biodiversity. Nevertheless, knowledge of the effect of climate change on stand structure and plant diversity is still poorly understood on a large scale. To explore the effects of various climate conditions on stand structure–plant diversity, we conducted a comprehensive analysis of data from 1272 plots across China’s temperate and subtropical forests. Leveraging the structural equation model (SEM), we explored the direct and indirect effects of climate, topography, and tree diversity on understory woody and herbaceous plants with respect to stand structure. Furthermore, we evaluated the effect size of stand structure on understory vegetation diversity under different climatic zones. Our results showed that tree size variation (CV DBH) and stem density (SD) were the key drivers for understory woody plants, while the stand structure complexity index (SSCI) was more important for understory herbaceous diversity. Furthermore, the positive effects of stand structure differed across various climate zones and were enhanced with an increase in the climatic gradient. For instance, the impact of SD on understory woody plants, as well as the influence of the SSCI on the diversity of understory herbaceous vegetation, were both strengthened. These findings raise our awareness of the pressing need to manage stand structure heterogeneity differently across different climate zones, and different management also needs to be implemented among different understory plant types. It becomes evident that distinct forest management measures must be applied under future climate change and forest management practices in order to preserve biodiversity.

Background: Mediation analysis aims at estimating to what extent the effect of an exposure on an outcome is explained by a set of mediators on the causal pathway between the exposure and the outcome. The total effect of the exposure on the outcome can be decomposed into an indirect effect, i.e. the effect explained by the mediators jointly, and a direct effect, i.e. the effect unexplained by the mediators. However finer decompositions are possible in presence of independent or sequential mediators.Methods: We review four statistical methods to analyse multiple sequential mediators, the inverse odds ratio weighting approach, the inverse probability weighting approach, the imputation approach and the extended imputation approach. These approaches are compared and implemented using a case-study with the aim to investigate the mediating role of adverse reproductive outcomes and infant respiratory infections in the effect of maternal pregnancy mental health on infant wheezing in the Ninfea birth cohort.Results: Using the inverse odds ratio weighting approach, the direct effect of maternal depression or anxiety in pregnancy is equal to a 59% (95% CI: 27%,94%) increased prevalence of infant wheezing and the mediated effect through adverse reproductive outcomes is equal to a 3% (95% CI: -6%,12%) increased prevalence of infant wheezing. When including infant lower respiratory infections in the mediation pathway, the direct effect decreases to 57% (95% CI: 25%,92%) and the indirect effect increases to 5% (95% CI: -5%,15%). The estimates of the effects obtained using the weighting and the imputation approaches are similar. The extended imputation approach suggests that the small joint indirect effect through adverse reproductive outcomes and lower respiratory infections is due entirely to the contribution of infant lower respiratory infections, and not to an increased prevalence of adverse reproductive outcomes.Conclusions: The four methods revealed similar results of small mediating role of adverse reproductive outcomes and early respiratory tract infections in the effect of maternal pregnancy mental health on infant wheezing. The choice of the method depends on what is the effect of main interest, the type of the variables involved in the analysis (binary, categorical, count or continuous) and the confidence in specifying the models for the exposure, the mediators and the outcome. [ABSTRACT FROM AUTHOR]

Climatic warming affects plant growth and physiology, yet how warming alters chemistry in invasive plants and indirectly affects herbivorous insects remains largely unknown. Here, we explored warming-induced changes in leaf chemistry of the invasive plant Alternanthera philoxeroides and its native congener Alternanthera sessilis , and further examined how these changes affected the performance of the herbivores, Cassida piperata and Spodoptera litura. We conducted a simulated warming experiment to address its effects on 13 leaf chemical traits of A. philoxeroides and A. sessilis. We measured growth and development time of two herbivores reared on plants from warming or ambient controls. Warming significantly affected leaf chemistry composition for both the invasive and native Alternanthera. Warming decreased nitrogen concentration in A. philoxeroides and increased total flavonoid and total phenol concentration in A. sessilis. The effects of warming on nutrients (i.e. fructose, sucrose, total soluble sugar and starch) varied with individual chemicals and plant species. Weight of C. piperata pupal and S. litura larval reared on warming-treated A. sessilis significantly decreased compared with non-warmed control, and a similar pattern was observed for weight of S. litura larval feeding on warming-treated A. philoxeroides. In addition, warming-treated A. sessilis significantly prolonged larval development time of S. litura. These results indicate that warming can directly affect the leaf chemistry in both invasive plant and its native congener, but these effects vary by species. Such differences in warming-induced changes in plant chemistry could indirectly affect herbivorous insects associated with the invasive and native plants. [ABSTRACT FROM AUTHOR]

Attribution of groundwater recharge (GR) change is important for understanding subsurface hydrological processes and managing regional groundwater resources. Despite vegetation change directly influencing GR, its indirect effects are mostly incorporated into other effects because of multicollinearity in environmental factors. Taking the 59 hydrological stations from 13 basins in the Loess Plateau of China as an example, GR was estimated with daily streamflow data and recession-curve-displacement method for 1961–2019. Geographical detector was employed to qualitatively attribute the spatial variability of GR, while structural equation modeling and elasticity coefficient method were utilized for qualitative and quantitative analysis of the direct and indirect impacts of environmental factors on the temporal variation of GR. The annual mean GR in 13 basins ranged from 11 to 53 mm/year, and the spatial heterogeneity of GR can be well explained by loess thickness. GR significantly decreased in 68% of hydrological stations by 38% ± 15%. Averaged over the 13 basins, the direct and indirect effects of NDVI change respectively accounted for 10% and 48% of GR reduction, which greatly exceeded other factors. The indirect effects of vegetation change dominated GR change, but they were getting smaller with increasing latitude. This study highlights the importance in considering indirect effects of vegetation change in hydrological variability, and the results can improve the understanding of hydrological variability. [ABSTRACT FROM AUTHOR]

Fungicides are one possible way to manage fungal and oomycete plant pathogens in order to safeguard yield and quality of crops and to improve shelf‐life of produce in agriculture and horticulture. However, global warming and the resulting temperature increase may affect the effectiveness of some important fungicides, including efficacy and duration of plant disease control. Nevertheless, according to our literature survey, there is little specific information available on whether and how temperature influences the effectiveness of fungicides. The very few publications that show specific data are summarized herein. Specific data are mainly gained under controlled conditions, both based on in vitro and in planta experiments. Field data are more or less missing. Most researchers assume that indirect effects of temperature on fungicide efficacy are particularly important. For example, temperature effects on pathogen spore germination and hyphal growth (optimal versus sub‐ and supra‐optimal), whereby optimal temperature conditions can improve pathogen fitness, thereby increasing the tolerance of pathogens to fungicides. Presumably, these indirect effects are often more important than the direct effects of temperature on fungicide performance. However, the data needed to prove this assumption are lacking. Therefore, it would be beneficial to conduct more in‐depth laboratory, greenhouse and field experiments in order to investigate the potential direct and indirect influence of temperature on the effectiveness of important fungicides. This would enable the establishment of appropriate recommendations for fungicide use in an increasingly warmer world and would assist the development of future fungicide solutions, based on improved knowledge. The effects of temperature on the effectiveness of important fungicides should be investigated in order to guide fungicide use in an increasingly warmer world, based on improved knowledge. [ABSTRACT FROM AUTHOR]

Although the fruit yield has a core importance in Tahiti acid lime breeding programs, other traits stand out among the quality fruit and vegetative traits as ones that still need to be improved in selection of superior genotypes. Appling efficient tools aiming selection, such as the Bayesian inference, becomes an alternative in perennial crops. This study applied Bayesian inference in the genetic evaluation of Tahiti acid lime genotypes and estimated the interrelation between vegetative, productive and fruit quality traits. Twenty-four acid lime genotypes were evaluated for number of fruits, fruit yield, canopy volume, stem diameter, soluble solids content, shell thickness, and juice yield traits. The genotypic values were estimated through Bayesian inference and models with different residual structure were tested via deviance information criterion. Pearson's correlation and the path analysis were estimated, removing the multicollinearity effect. The Bayesian inference estimates genotypic values with high selective accuracy. The correlations obtained between traits from different groups can be useful in selection strategies for improvement of Tahiti acid lime. The Bayesian inference demonstrated to be an important tool and should be considered in perennial breeding programs. [ABSTRACT FROM AUTHOR]

While large herbivores are critically important components of terrestrial ecosystems and can have pronounced top‐down effects on plants, our understanding of the underlying mechanisms driving these effects remains incomplete. Large herbivores can alter plant growth, reproduction, and abundance through direct effects (predominantly consumption) and through indirect effects via altered interactions with abiotic factors and other species. We know considerably less about these indirect effects than the direct effects. Here, we integrate medium‐ and small‐scale field experiments to investigate how a large vertebrate herbivore, cattle (Bos taurus), affects the aboveground biomass of a dominant forb species, Artemisia scoparia, via diverse direct and indirect pathways in a temperate grassland in northeast China. Although cattle consumed this forb, its biomass increased significantly in response to grazing, due to multiple indirect positive effects that outweighed the direct negative effects of consumption. Cattle preferentially consumed the competing grass Leymus chinensis, and altered Artemisia microhabitats by reducing total plant cover and litter biomass and by increasing the abundance of co‐occurring ant species (e.g., Formica spp. and Lasius spp.). This led to additional indirect positive effects on A. scoparia likely due to (1) increased light availability in understory layers and other limiting resources (e.g., soil nutrients and moisture) caused by removal of competitors and plant litter at the soil surface and (2) the changes in resource availability (e.g., soil nutrients and moisture) associated with ant colonies. Our results show that large herbivores can affect plant growth not only via direct consumption, but also via multiple indirect effects. Focusing on the causes and consequences of herbivore‐induced indirect effects will not only help us to better understand the influence of these animals in ecological systems, but will also lead to more effective land management and conservation practices in the regions they inhabit. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to determine the spatial spillover effects of renewable energy on carbon emissions in China's less-developed areas. However, few studies have considered this issue from the perspective of less-developed areas. Based on panel data of 21 provinces in China from 2000 to 2017, this paper analyzes the spatial spillover effects of renewable energy on carbon emissions using Moran's I and Spatial Durbin Model (SDM). The results suggest that, first, Moran's I ranges from 0.378 to 0.519, Moran scatter plot presents that provinces are located in the high–high (HH) and low-low (LL) quadrants, indicating provincial carbon emissions in the study area have a significant spatial correlation and agglomeration. Second, under the three matrices, the direct effect coefficients of renewable energy are -0.2522, -0.2639 and -0.2601, this shows that renewable energy is beneficial to local carbon emissions reduction. In contrast, the indirect effect coefficients of renewable energy are 0.0605, 0.1012 and 0.1125, which means higher renewable energy consumption in a single area is conducive to the improvement of carbon emissions to neighbouring areas. Third, urbanization, industrialization, physical capital and other variables have different impacts on local and nearby carbon emissions. This study provides empirical evidence to achieve carbon emission reduction targets by government policymakers. [ABSTRACT FROM AUTHOR]

Summary: Difficulties quantifying pathogen load and mutualist abundance limit our ability to connect disease dynamics to host community ecology. For example, specific predictions about how differential pathogen load is hypothesised to drive host competitive outcomes are rarely tested. Additionally, although infection is known to affect mutualists, we rarely measure the magnitude of pathogen effects on mutualist abundance across host competitive contexts. We tested for both mechanisms in a plant–rhizobia–nematode system.We paired the legume Medicago lupulina with intraspecific and interspecific plant competitors, with and without a generalist nematode parasite Meloidogyne sp. Relative change in plant biomass was used to determine how nematode inoculation affected plant competitive outcomes. We counted nematode galls to test for direct effects of parasitism on plant competition and rhizobia nodules to test for indirect effects of nematode presence on rhizobium abundance.Parasites were destabilising despite similar nematode load across competition treatments. During interspecific compared with intraspecific competition, nematode inoculation decreased nodulation on M. lupulina, increased nodulation on Trifolium repens and had no effect on nodulation on Chamaecrista fasciculata.We found no support for hypothesised direct effects of nematode load on competitive outcomes and strong but idiosyncratic indirect effects of nematode inoculation on rhizobium abundance. [ABSTRACT FROM AUTHOR]

With multiple possible mediators on the causal pathway from a treatment to an outcome, we consider the problem of decomposing the effects along multiple possible causal path(s) through each distinct mediator. Under a path‐specific effects framework, such fine‐grained decompositions necessitate stringent assumptions, such as correctly specifying the causal structure among the mediators, and no unobserved confounding among the mediators. In contrast, interventional direct and indirect effects for multiple mediators can be identified under much weaker conditions, while providing scientifically relevant causal interpretations. Nonetheless, current estimation approaches require (correctly) specifying a model for the joint mediator distribution, which can be difficult when there is a high‐dimensional set of possibly continuous and noncontinuous mediators. In this article, we avoid the need to model this distribution, by developing a definition of interventional effects previously suggested for longitudinal mediation. We propose a novel estimation strategy that uses nonparametric estimates of the (counterfactual) mediator distributions. Noncontinuous outcomes can be accommodated using nonlinear outcome models. Estimation proceeds via Monte Carlo integration. The procedure is illustrated using publicly available genomic data to assess the causal effect of a microRNA expression on the 3‐month mortality of brain cancer patients that is potentially mediated by expression values of multiple genes. [ABSTRACT FROM AUTHOR]

In time-to-event settings, the presence of competing events complicates the definition of causal effects. Here we propose the new separable effects to study the causal effect of a treatment on an event of interest. The separable direct effect is the treatment effect on the event of interest not mediated by its effect on the competing event. The separable indirect effect is the treatment effect on the event of interest only through its effect on the competing event. Similar to Robins and Richardson's extended graphical approach for mediation analysis, the separable effects can only be identified under the assumption that the treatment can be decomposed into two distinct components that exert their effects through distinct causal pathways. Unlike existing definitions of causal effects in the presence of competing events, our estimands do not require cross-world contrasts or hypothetical interventions to prevent death. As an illustration, we apply our approach to a randomized clinical trial on estrogen therapy in individuals with prostate cancer. for this article are available online. [ABSTRACT FROM AUTHOR]

With reference to causal mediation analysis, a parametric expression for natural direct and indirect effects is derived for the setting of a binary outcome with a binary mediator, both modelled via a logistic regression. The proposed effect decomposition operates on the odds ratio scale and does not require the outcome to be rare. It generalizes the existing ones, allowing for interactions between both the exposure and the mediator and the confounding covariates. The derived parametric formulae are flexible, in that they readily adapt to the two different natural effect decompositions defined in the mediation literature. In parallel with results derived under the rare outcome assumption, they also outline the relationship between the causal effects and the correspondent pathway-specific logistic regression parameters, isolating the controlled direct effect in the natural direct effect expressions. Formulae for standard errors, obtained via the delta method, are also given. An empirical application to data coming from a microfinance experiment performed in Bosnia and Herzegovina is illustrated. [ABSTRACT FROM AUTHOR]