High Explanatory Power Research Articles

Identifying the Formative Factors which Shape Individual Intention to Prefer Imported Used or Locally Assembled Cars: A Survey on Pakistan

The current study intended to examine the consumer intention while purchasing locally assembled and imported cars. Hence, the study proposed a model which is underpinned with social identity theory. The research model employed consumer ethnocentrism, self-congruity product characteristic, perceived relative price, brand personality and service quality. The current study identify research gap and found to the best knowledge of researchers that past study is lacking the determinants which motivate consumer intention, separately, to select local or imported cars. Moreover, aforementioned studies reported inconsistent results about consumer inclination towards automobile selection. The sample size of the study was 396. The proposed model was analyzed using structural equation model. The finding of the study revealed that consumer intention to purchase locally assembled and imported cars are shaped by both factors like rational and emotional. In addition to the results unveiled the fact that consumer purchase intention towards locally assembled cars highly influenced by ethnocentrism, brand personality as well as product characteristics. In continuation with the brand personality has highest explanatory power for making consumer intention towards imported cars. In contrary to that while purchasing imported cars the consumer influenced by self-congruity and brand personality. In addition to perceived relative price and service quality having insignificant effect on both cars. The present study confirmed that in collectivism society the purchase of automobile shaped by emotions and social influences. Although the study contributed in literature with theoretical and practical implication nevertheless suggested some future research direction.

Прогнозирование спреда доходности на российском долговом рынке

The article provides an empirical study of factors which make a significant impact on the yield spread of corporate bonds on Russia’s market. Unlike most studies based only on IPO data, the current study covers primary and secondary markets data of 2010–2019. The aim of the study is to test the method allowing to build a model capable of predicting the yield spread with maximum approximation to actual value. The author develops a regression model applying a cross-validation method, a procedure for empirical assessment of the model generalizing ability. An important prerequisite is the inclusion of a limited number of regressors with high explanatory power in the model, stability over time, and explicit economic interpretation. The paper confirms the key hypothesis on high degree of issuer's rating on the yield spread which is a new step in the study of the Russian market. The findings prove that the yield spread is determined mainly by the level of risk corresponding to the degree of the issuer's reliability. The issuer's industry affiliation, the size of the company, the MSCI stock index has also a significant impact on the spread. Among the advantages of the proposed model is its relative simplicity, explicit economic interpretation and stable response to various data which determine the practical significance of the work. The approaches to building and testing the model applied in this work can be useful in further studies aimed at developing predictive models of this class.

My video game console is so cool! A coolness theory-based model for intention to use video game consoles.

With the outbreak of COVID-19, the video game console market is thriving again. In this study, we attempted to explore users’ intention to use video game consoles by developing a causal model mainly based on coolness theory and the technology acceptance model. To better illustrate user experience for video game consoles, we added several concepts to the causal model, including hedonic motivation, system and service quality, perceived cost, and game variety. Through examining survey-based data from 360 Koreans, we discovered that the model had a high explanatory power for users’ intention to use video game consoles. The key findings were as follows: First, among the components of coolness theory, individuals’ attitude toward consoles was significantly related to subcultural appeal and originality, but not to attractiveness. Second, originality positively influenced subcultural appeal significantly. Overall, this study implied that the novel coolness theory is effective for exploring user experience regarding of specific devices and services.

Climatic and Morphometric Explanatory Variables of Glacier Changes in the Andes (8–55°S): New Insights From Machine Learning Approaches

Over the last decades, glaciers across the Andes have been strongly affected by a loss of mass and surface areas. This increases risks of water scarcity for the Andean population and ecosystems. However, the factors controlling glacier changes in terms of surface area and mass loss remain poorly documented at watershed scale across the Andes. Using machine learning methods (Least Absolute Shrinkage and Selection Operator, known as LASSO), we explored climatic and morphometric variables that explain the spatial variance of glacier surface area variations in 35 watersheds (1980–2019), and of glacier mass balances in 110 watersheds (2000–2018), with data from 2,500 to 21,000 glaciers, respectively, distributed between 8 and 55°S in the Andes. Based on these results and by applying the Partitioning Around Medoids (PAM) algorithm we identified new glacier clusters. Overall, spatial variability of climatic variables presents a higher explanatory power than morphometric variables with regards to spatial variance of glacier changes. Specifically, the spatial variability of precipitation dominates spatial variance of glacier changes from the Outer Tropics to the Dry Andes (8–37°S) explaining between 49 and 93% of variances, whereas across the Wet Andes (40–55°S) the spatial variability of temperature is the most important climatic variable and explains between 29 and 73% of glacier changes spatial variance. However, morphometric variables such as glacier surface area show a high explanatory power for spatial variance of glacier mass loss in some watersheds (e.g., Achacachi with r2 = 0.6 in the Outer Tropics, Río del Carmen with r2 = 0.7 in the Dry Andes). Then, we identified a new spatial framework for hydro-glaciological analysis composed of 12 glaciological zones, derived from a clustering analysis, which includes 274 watersheds containing 32,000 glaciers. These new zones better take into account different seasonal climate and morphometric characteristics of glacier diversity. Our study shows that the exploration of variables that control glacier changes, as well as the new glaciological zones calculated based on these variables, would be very useful for analyzing hydro-glaciological modelling results across the Andes (8–55°S).

Reverse FDI and knowledge-and-physical-capital model: empirical evidence from emerging economies

PurposeThe main aim of this paper is to verify whether the modern mainstream economic theory of multinational enterprise that explains foreign direct investment (FDI) from developed countries is also able to account for investment decisions of multinational enterprises (MNEs) from emerging economies.Design/methodology/approachUsing Knowledge-And-Physical-Capital (KAPC) model as an analytical framework and Poisson-pseudo maximum likelihood estimation technique, the authors identify determinants of FDI flows from emerging economies. The data set consists of 38 home and 134 host countries during the period 2000–2012. Empirical evidence supports high explanatory power of KAPC model. Further, compared with the earlier Knowledge-Capital (KC) model, results confirm the importance of physical capital.FindingsThe estimation results confirm the hypothesis that mainstream economic theory can explain FDI flows from the emerging economies by highlighting the roles of total market size, skilled-labor abundance, investment and trade costs and geographical distance between two countries.Research limitations/implicationsThis study casts doubt on the alternative way that the KAPC model suggests to distinguish between horizontal and vertical FDI. The argument that horizontal MNE headquarters would be relatively more abundant than vertical MNE headquarters in countries that are abundant in physical capital relative to skilled labor seems reasonable but the idea of variable specification in the estimated equation should be revised.Practical implicationsFirms should be allowed to move their resources freely into and out of specific activities, both internally and internationally across border. To reach that goal, governments of potential host countries can adopt several measures, most importantly remove restrictions on payments, transfers and capital transactions and open previously closed industries to welcome foreign investment. In addition, to improve investment climate in general, governments need to pay attention to enhancing security of property rights, regulating internal taxation (i.e. corporate income tax), guaranteeing adequacy of infrastructure, efficient functioning of finance and labor markets and fighting against corruption.Social implicationsThe location choice of emerging investors set priority on similarity in economic size, geographical and cultural proximity. It is because shared borders or common official languages would reduce information costs and enhance information flows. Also, investors consider horizontal FDI (with motivation to expand market demand) as one of main modes of entry into a foreign market and a substitute for export. Likewise, distance is often understood as an important investment friction.Originality/valueThe outstanding contribution is that the research has uncovered the positive and statistically significant effect of physical capital on FDI activity, which has not been discussed in the earlier KC model. However, at the same time, the study casts doubt on the KAPC model's argument that relative abundance in physical capital to skilled labor between two countries determines FDI types and suggests that this argument and its empirical model specification should be carefully reviewed.

The Effect of Hybrid Attributes on Property Prices

Abstract This study focuses on the sales comparison and the adjustment grid methods, under the framework of the market approach to valuation. The literature mostly focuses on the structural qualities of the properties, referring to the buildings and their locational characteristics, which pertain to their positioning within the urban fabric. Here we focus on a particular set of attributes which depend on how a building is placed in a specific land plot and relate to the surrounding environment. The term «hybrid» is used to identify this class of attributes. It is shown that hybrid attributes affect property prices and should not be disregarded by practitioners and appraisers. The role played by hybrid characteristics is analyzed based on the methodological foundation of the hedonic and the adjustment grid methods. The derived linear and log-linear models are tested by means of a case study. The models prove to have high explanatory power. The weight of each hybrid attribute is estimated to vary between 1% and 10%. Overall, these attributes contribute to 17-23% of the property prices. The validation performed using the grid adjustment method shows that the estimated marginal prices are effective in adjusting the prices per unit area of the comparables.

Inequality and migration in Kenya: Investigating the subnational associations using census data

Background: Since the early 2000s, there has been an extensive debate on whether migration and inequality are interlinked, with varying conclusions arising from methodological as well as theoretical dispositions. The aim of this study is to contribute to this debate by exploring the nexus between several dimensions of inequalities and migration in Kenya. Methods: This study used the subnational(county) data on inequalities and migration in Kenya obtained from several reports. Four explanatory variables including access to water, electricity, composite index of County Human Development Index (County HDI) and County Gini were used. Our dependent variable was migration intensity, measured by the Revised Weighted Net Migration Rate. Correlation and spatial regression analysis were performed to model the relationship between migration and inequality. Results: Findings revealed that migration had a non-linear relationship with income inequality, such that a change in one unit of migration intensity results in a 567 negative change in County Gini. The County Gini had the highest explanatory power in our model, although counties with high HDI tend to have higher migration intensities. Migration intensities in the country were not randomly distributed as we found evidence of spatial clustering with two key emergent hotspots, a high-high in the lake region and a low-low in the coastal region. Regions with low migration intensities correspond with higher poverty, implying that structural factors may explain the migration intensities in the country. Conclusions: The study highlights that the subnational income inequality reduces as migration intensifies. We conclude that migration has an equalizing effect on inequality as observed in some studies. Regions with high poverty tend to have lower migration intensity, implying that structural factors are important in influencing migration. Use of migration intensity and application of spatial analysis have improved our understanding of migration and inequality, and should be applied in future research.

Investigating working adults' intentions to participate in microlearning using the decomposed theory of planned behaviour

AbstractThe current work validated the decomposed theory of planned behaviour (DTPB) with working adults to assess its ability to predict intentions to participate in microlearning and also identify the significant factors that drive microlearning usage decisions. We found that positive attitudes towards microlearning (Attitude), stronger beliefs in others' opinions regarding microlearning use (SN), and stronger perceptions about one's capability to engage in microlearning (PBC), are associated with stronger intentions to participate in microlearning. All decomposed constructs were found to be significant predictors of the respective factors, except superior influence (SI) and resource facilitating conditions. We discuss potential targeted interventions focused on what works best to encourage microlearning adoption. For instance, while reporting superiors have no significant influence over one's microlearning use decisions, the opinions of peers and colleagues positively influence microlearning use. Hence, focusing on embedding community‐related aspects into a microlearning design may effectively encourage the use of microlearning. Practitioner notesWhat is already known about this topic The decomposed theory of planned behaviour (DTPB) is reported to be suited for studying e‐Learning adoption due to its robustness and high explanatory power. The DTPB allows for a deeper and more detailed explanation of behavioural intentions compared to other models. However, the DTPB has not been explored for learning innovation such as microlearning. What this paper adds The DTPB was found to be theoretically sufficient for predicting intentions to participate in microlearning. Attitudes towards microlearning was found as the strongest determinant of intentions, followed by one's beliefs in others' opinions regarding microlearning use, and lastly, perceptions about one's capability to engage in microlearning. Contrary to expectations, only the influence of peers in one's social circle was significantly predictive of subjective norm, while the influence of those in positions of authority in the workplace (e.g., one's reporting manager or superior) was not. Additionally, while self‐efficacy and technology‐related facilitating conditions (e.g., technical compatibility, technical support) were significant predictors of perceived behavioural control, the availability of resources required to perform microlearning was not. Implications for practice and/or policy Factors identified as strongly influential for behavioural intentions may aid in facilitating and accelerating microlearning adoption in the workforce.

Understanding digital contact tracing app continuance: Insights from India

ObjectivesDigital contact tracing (DCT) was touted as an effective alternative to lockdown and other restrictive measures in controlling the spread of the COVID-19 pandemic. Despite considerable investments in research and development, the usage of DCT apps was found to be phenomenally low across the world. In this context, the current study investigates the factors influencing citizens’ continuance intentions to use the DCT app. MethodsA theoretical framework was developed by extending the Expectation-confirmation model (ECM) of Information system continuance with Technology trust theory and a contextual factor perceived security and privacy to predict citizens’ continuance intentions to use the DCT app. The model was empirically tested using data from a field survey of 206 actual users of a DCT app implemented in India. ResultsThe findings reveal that user satisfaction, trust in government, and trust in technology are significant predictors of citizens’ continuance intention. The model demonstrates high explanatory power by explaining 57.8% of the variance of continuance intention. It also validates the role of perceived security and privacy and trust in technology in determining user satisfaction. ConclusionThe study makes a theoretical contribution by extending the ECM framework to predict DCT app continuance behavior. The insights from the study could be helpful for developers and policymakers in crafting strategies to improve the usage of DCT apps during future disease outbreaks.

The prognostic significance of the alterations of pulmonary hemodynamics in patients with pulmonary arterial hypertension: a meta-regression analysis of randomized controlled trials

BackgroundHemodynamic assessment in patients with pulmonary arterial hypertension (PAH) is essential for risk stratification and pharmacological management. However, the prognostic value of the hemodynamic changes after treatment is less well established.ObjectivesWe investigated the prognostic impacts of the changes in hemodynamic indices, including mean pulmonary artery pressure (mPAP), pulmonary vascular resistance (PVR), right atrial pressure (RAP), and cardiac output index (CI). We conducted this systematic review with meta-regression analysis on existing clinical trials.MethodsWe searched and identified all relevant randomized controlled trials from multiple databases. An analogous R2 index was used to quantify the proportion of variance explained by each predictor in the association with PAH patients’ prognosis. A total of 21 trials and 3306 individuals were enrolled.ResultsThe changes in mPAP, PVR, RAP, and CI were all significantly associated with the change in 6MWD (∆6MWD). The change in mPAP was with the highest explanatory power for ∆6MWD (R2 analog = 0.740). Additionally, the changes in mPAP, PVR, and CI were independently predictive of adverse clinical events. The change in mPAP had the highest explanatory power for the clinical events (R2 analog = 0.911). Furthermore, the change in PVR was with the highest explanatory power for total mortality of PAH patients (R2 analog = 0.612).ConclusionHemodynamic changes after treatment, including mPAP, PVR, CI, and RAP, were significantly associated with adverse clinical events or mortality in treated PAH patients. It is recommended that further studies be conducted to evaluate the changes in hemodynamic indices to guide drug titration.Systematic review registrationPROSPERO CRD42019125157

Roads and land tenure mediate the effects of precipitation on forest cover change in the Argentine Dry Chaco

Dry forests are among the most threatened ecosystems globally, due to agricultural expansion driven by the increasing demand for food, fibers, and energy in developed and emerging countries. Among these, the forests of the South American Gran Chaco are one of the global deforestation hotspots. The Argentine Dry Chaco has been the focus of several studies that assess the factors that drive forest conversion. However, these studies do not describe the causal relationships among these drivers and seldom use existing theory to select drivers. Here we employ a theory-driven approach to test the relative merits of alternative and complementary hypotheses to explain the drivers and mechanisms explaining the unequal spatial distribution of forest loss and maintenance in the Argentine Dry Chaco from 2000 to 2010. Using structural equation modeling, we quantified the direct and indirect effects of multiple drivers and compared the explanatory power and parsimony of these alternative hypotheses, i.e. the biophysical, infrastructure, socio-demographic, institutional, and the integration of them. For both forest loss and maintenance, the model containing infrastructural drivers had the best balance between parsimony and explanatory power. Integrated models, comprising a combination of drivers, had the highest explanatory power (R2 = 0.81 for forest maintenance, and R2 = 0.58 for forest loss). We show that biophysical constraints operate directly and indirectly: soil suitability had direct effects on forest cover maintenance, while precipitation affected it both directly and indirectly through influencing the institutional (land tenure) and infrastructure (road density). Indigenous communities positively affected forest maintenance both directly and indirectly mediated by non-private land tenure. Our results suggest that disentangling the structure of the relationships among drivers could increase our capacity for understanding and steering land-use change. Furthermore, policies for halting deforestation might increase their effectiveness by accounting for the mechanisms that underlie forest loss and maintenance.

Phylogenetic niche conservatism and variations in species diversity–climate relationships

Although contemporary climate has been identified as one of the major determinants of large‐scale species diversity patterns, its effect on species diversity greatly varies among clades. Understanding the drivers of the variation in species diversity–climate relationships (DCRs) across clades, which is critical for developing general mechanisms underlying the effects of climate on species diversity patterns, remains a current challenge. Using newly compiled distribution data of 914 Rosaceae species in China and a dated genus‐level phylogeny, we first assessed the DCRs for the entire family, the two major growth forms (woody versus herbaceous), and each genus separately, and then explored the drivers underlying the variation in DCRs across different clades. We found that the DCRs significantly differed between woody and herbaceous plants and among different genera in this family. Closely related genera had more similar species diversity patterns and DCRs than expected. Both the ancestral climate niches of different genera and the discrepancy between contemporary and ancestral climate niches explained the variations in DCR slopes across genera with high explanatory power, indicating the effect of niche conservatism on DCRs. Our study suggests that niche conservatism is a major driver of DCR variations between clades, which enhances our understanding of the mechanisms underlying large‐scale species diversity patterns.

Development of an Estimation Formula to Evaluate Mission Motion Suitability of Military Jackets

We developed an estimation formula for mission motion suitability evaluation based on the general motion protocol to evaluate the motion suitability of a tracked vehicle crew jacket. Motion suitability evaluation was conducted for the 9 general motions and 12 mission motions among 27 tracked vehicle crew members who wore a tracked vehicle crew jacket. We conducted correlation and factor analyses on motions to extract the main mission motions, and a multiple regression analysis was performed on major mission motions using general motions as independent variables. As a result, two mission behavior factors related to ammunition stowing and boarding/entry were extracted. We selected ammunition stowing I and the boarding motion, which has the highest factor load in each factor and the highest explanatory power (R2) of the estimation formula. Regression equations for ammunition stowing consisting of five general motions (p < 0.001) and for boarding motion (p < 0.01) consisting of one general motion could be obtained. In conclusion, the estimation formula for mission motion suitability using general motion is beneficial for enhancing the effectiveness of the evaluation of military jackets for tracked vehicle crews.

Explaining the Geographic Pattern of Plant Invasion in 67 Nature Reserves in China

Biological invasion is a serious threat to biodiversity and ecosystem function in nature reserves. However, the knowledge of the spatial patterns and underlying mechanisms of plant invasions in nature reserves is still limited. Based on a recent dataset on both invasive and native plants in 67 nature reserves of China, we used correlation, regression, and variation partitioning methods to statistically assess the relative roles of the “human activity,” “biotic acceptance,” and “environmental heterogeneity” hypotheses in explaining the geographic pattern of plant invasion. A total of 235 invasive plant species were compiled from 67 nature reserves. The high explanatory power of the human activity variables supported the human activity hypothesis. The biotic acceptance hypothesis was weakly supported since no significant correlations between climatic variables and invasion levels were found when the effects of the other factors were controlled. The environmental heterogeneity hypothesis was partially supported, since the number of native plants, representing environmental heterogeneity at fine-scale explained remarkable proportion of spatial variance of invasive plants but not that of the proportion of invasive plants. We predict that nature reserves with high plant diversity affected by rapid economic development and increasing temperature will face a serious threat of exotic plant invasion. In conclusion, our results provide crucial clues for understanding geographic variance of plant invasion in China’s nature reserves and spatial risk assessment.

Tadpoles Inhabiting Natural and Anthropogenic Temporary Water Bodies: Which Are the Environmental Factors that Affect the Diversity of the Assemblages?

The study of tadpole assemblages allows inferring habitat availability and using their occupation as a means of proxy for the effective reproduction of the species, contributing to complementary information for the study of their adult forms. Environmental variables, represented by abiotic variables, vegetation structure, matrix management, and landscape elements, affect species having reproductive modes associated with oviposition and development in bodies of water. In the Orinoco region, most amphibians have complex life cycles and deposit their eggs in highly dynamic lentic bodies of water. Therefore, it is important to know how larval assemblages change over short periods of water accumulation and their relationship with environmental variables. Fieldwork was conducted during 9 weeks of larval sampling, from the beginning of the rainy season. We evaluate changes in anuran assemblages associated with water accumulation in five temporary water bodies of anthropogenic (road or pasture) and natural (savanna or gallery forest) origin. Twenty environmental variables were evaluated and measured in the center of each water body. Of these, nine landscape variables were measured only once during the study. The other eleven variables, representing management practices, physicochemical and structural characteristics of the water bodies, were measured weekly during the 3 months of sampling. We explored differences in the structure and diversity of larval-stage anuran assemblages using statistical tests suitable for small sample sizes (i.e., permutational multivariate analysis of variance PERMANOVA and the distance-based linear modeling DistLM). Of the 14 species found, two species had remarkedly high abundances from whichRhinella humboldti(19% of the total tadpole abundance) was a generalist inhabiting the natural and anthropogenic water bodies, whileLeptodactylus insularum(18% of the total tadpole abundance) was a specialist at a natural pond in the savanna. The natural water bodies contained the highest number of species (between 10 and 12) and a total abundance of larvae (between 847 and 485 individuals). In contrast, the anthropogenic water body tracks generated by tractors were only occupied by two species with 50 individuals in total, while the water body generated by the trampling of cattle in pastures had three species with 474 individuals. These three species that inhabited the anthropogenic puddles were also found in the natural ponds and none of the eight species of hylids inhabited the puddles. In each field trip, all the tadpoles were collected from the sampled bodies of water. However, a week later, we found that each of the water bodies had been recolonized by four species (Leptodactylus fuscus, Leptodactylus fragilis, Elachistocleis ovalis,andR. humbolti). The variables with the highest explanatory power on the variation of anuran assemblage structure throughout all the water bodies were height of plants, number of cattle, distance to the nearest native forest edge, distance to an anthropic lentic body of water, distance to a natural lentic body of water, and pH. The bodies of water immersed in the natural cover were more diverse and had a greater degree of spatial and temporal species turnover. Our study calls for the importance of understanding the turnover of larval stage anurans over short periods, associated with water accumulation, in highly dynamic systems such as natural ponds and anthropogenic puddles. The importance of species traits and local processes is also highlighted, from environmental variables to human management activities, in the conservation of amphibian assemblages.

Relationship between pain intensity, pain catastrophizing, and self-efficacy in patients with frozen shoulder: a cross-sectional study

BackgroundPain catastrophizing and self-efficacy are useful for predicting pain; these are associated with pain intensity and facilitate evaluation of psychological factors. However, it remains unclear whether the effects are direct or indirect in patients with frozen shoulder; the impact on each variable has also not been clarified. Thus, this study aimed to examine the structural relationship between pain catastrophizing, self-efficacy, and pain intensity in patients with frozen shoulder.MethodsParticipants who were diagnosed with frozen shoulder between January 2016 and March 2017 were recruited from a single orthopedic clinic. Patients aged 18 years or older, who had been symptomatic for < 1 year and reported localized pain in one shoulder, experienced night pain, and had restricted active and passive shoulder motions were included. Pain intensity (Numerical Rating Scale (NRS)), pain catastrophizing (Pain Catastrophizing Scale (PCS)), and self-efficacy (Pain Self-Efficacy Questionnaire (PSEQ)) were measured at the first examination, and the relationship was examined using the Bayesian estimation method. The model was modified repeatedly based on the posterior prediction p value, deviance information criterion (DIC), and Bayesian information criterion (BIC); the model with the highest explanatory power was adopted as the final model.ResultsNinety-three patients diagnosed with frozen shoulder were included in this study. On path analysis, the model in which pain intensity affected psychological factors had the most explanation. The convergence index potential scale reduction was below 1.1, and the convergence of the estimate was confirmed. The posterior prediction p value was 0.25, DIC = 1328.705, and BIC = 1356.872; the validity of the fit of the model was confirmed. The path coefficients from the NRS to the PSEQ, from the NRS to the PCS, and from the PSEQ to the PCS scores were − 0.232 (95% confidence interval (CI), − 0.406 to − 0.033), 0.259 (95% CI, 0.083–0.419), and − 0.504 (95% CI, − 0.646 to − 0.334), respectively; these values were statistically significant (p < 0.05).ConclusionOur results show that pain intensity increases the risk of chronic pain including pain catastrophizing and self-efficacy and that pain catastrophizing increases by decreasing self-efficacy in patients with frozen shoulder.

A Global Meta-Analysis for Estimating Local Ecosystem Service Value Functions

The Meta-analysis has increasingly been used to synthesize the ecosystem services literature, with some testing of the use of such analyses to transfer benefits. These are typically based on local primary studies. However, meta-analyses associated with ecosystem services are a potentially powerful tool for transferring benefits, especially for environmental assets for which no primary studies are available. In this study we use the Ecosystem Service Valuation Database (ESVD), which brings together 1350 value estimates from more than 320 studies around the world, to estimate meta-regression functions for Provisioning, Regulating and maintenance, and Cultural ecosystem services across 12 biomes. We tested the reliability of these meta-regression functions and found that even using variables with high explanatory power, transfer errors could still be large. We show that meta-analytic transfer performs better than simple value transfer and, in addition, that local meta-analytical transfer (i.e., based on local explanatory variable values) provides more reliable estimates than global meta-analytical transfer (i.e., based on mean global explanatory variable values). Thus, we conclude that when taking into account the characteristics of the study area under analysis, including explanatory variables such as income, population density, and protection status, we can determine the value of ecosystem services with greater accuracy.

P–256 Time Lapse Imaging (TLI) acquired morphokinetic variables, nucleation errors and cleavage abnormalities are associated with live birth and may aid in de-selection of transfer embryos

Abstract Study question May the observation by TLI of morphokinetics, nucleation errors and cleavage abnormalities assist in de-selecting embryos before embryo transfer? Summary answer The combine predictive power of the association between the three biomarkers and live birth may aid in embryo de-selection What is known already Morphokinetic parameters and cleavage biomarkers are associated with treatment outcomes following in vitro fertilization (IVF). Nucleation errors observed by TLI have also been associated with IVF outcomes. It is also shown that nucleation error self-repair in pre-implantation embryos occurs, resulting in euploid blastocysts and live births. Biomarkers identified by TLI have been incorporated in developing algorithms to be used in selecting “the embryo” with the best potential for a live birth. However, the few randomized control studies (RCT) have not shown convincingly that TLI significantly improves live birth rate. Study design, size, duration Analyses of TLI data from transferred embryos, cultured in the EmbryoScope TM between June 2012 and August 2018, in a single IVF clinical setting were included. 2082 treatment cycles with Known Implantation Data (KID) for implantation and live birth were included in the analyses. Nucleation errors such as micronucleation, binucleation, and multinucleation were systematically annotated. Cleavage abnormalities such as direct cleavages, rapid and reverse cleavages were annotated for a minimum of 44 hours post insemination. Participants/materials, setting, methods Annotations for cleavage abnormalities, morphokinetic variables and nucleation errors, during a minimum of 44 hours, for 2959 transferred embryos were obtained from the EmbryoScope. The potential negative association between day 2 KID embryo biomarkers and implantation as well as live birth was assessed. The analyses controlled for potential confounding by adjusting for maternal age, infertility diagnosis, BMI, hormonal stimulation regime and insemination method. Main results and the role of chance Preliminary results were obtained regarding biomarkers in the form of nucleation errors, cleavage abnormalities and early embryo morphological attributes. Several of these biomarkers were significantly associated with implantation and live birth. Nucleation errors were associated with substantial decrease in implantation and live birth, but contrary to findings from other studies, none of the recorded nucleation error types precluded live birth. Many morphokinetically defined cleavage abnormalities were also shown to be significantly associated with implantation and live birth, with timings to 2-cells (t2) and second cell cycle (cc2) displaying the most prominent predictions for live birth probability. Within each of the three biomarker groups, logistic regression models with implantation and live birth probability predictions displayed reasonable explanatory power regarding implantation and live birth. Combining all types of biomarkers lead to logistic regression models with substantially higher explanatory power than when the regression models only comprised a single biomarker group. With a study of this size and P values for the basic findings predominantly being highly significant, the role of chance is likely to be limited. The statistical uncertainty may therefore be subordinated to the confounding caused by embryo transfer selection and further by exclusive use of embryos with known implantation Limitations, reasons for caution Only transferred embryos with KID data were analysed and hence the outcome of other embryos is unknown. Our study used mostly day 2 embryos, therefore generalisation up to blastocyst stage is not possible. Our findings apply to our study cohort and may differ from findings in another clinical setting. Wider implications of the findings: Our study provides knowledge about the role of TLI biomarkers and their potential for deselecting embryos for transfer. This will avoid transfer of lower quality embryos with lower chances of live birth. Incorporating such non-invasive de-selection strategies, alongside morphology may contribute to improving IVF outcome. Trial registration number NA

Understanding Human–Canid Conflict and Coexistence: Socioeconomic Correlates Underlying Local Attitude and Support Toward the Endangered Dhole (Cuon alpinus) in Bhutan

Understanding human–canid conflict and coexistence must focus on documenting human–canid interactions and identifying the underlying drivers of reciprocal human attitude which enables appropriate strategies to minimize conflict and forge coexistence. The dhole (Cuon alpinus), Asia's most widely distributed wild canid, is highly threatened by human persecution and anthropogenic activities. Despite its “endangered” status, its ecological role as an apex predator, negative interactions with humans, and dhole-specific attitude studies are limited, thus hindering the development of a comprehensive dhole-conservation strategy. Here, we investigate the influence of socioeconomic factors of age, gender, income, residency inside/outside a protected area (PA), and other variables (cultural beliefs, livestock loss, and quantity of livestock loss) on the attitudes of local people and support for dhole conservation in the Himalayan Kingdom of Bhutan. We conducted a semi-structured questionnaire survey of 1,444 households located within the PA and non-PA from four representative regions in the country. Using R programming, we ran Pearson's chi-square test of independence to test the overall difference in the attitude and support for dhole conservation, followed by recursive partitioning through a conditional inference regression tree to identify its significant covariates with the highest explanatory power. Majority (79.1%) of respondents (χ2 = 488.6; df = 1; p &amp;lt; 0.001) disliked the dhole over those who liked it. More than half (57.7%) (χ2 = 412.7; df = 2; p &amp;lt; 0.001) opposed dhole conservation over those who either supported or remained neutral. Experience of livestock loss to dholes was the primary ( p &amp;lt; 0.001) factor influencing the negative attitude and opposition to dhole conservation, despite an acknowledgment of the ecological role of the dhole in controlling agricultural crop predators. Our study, which is the first-ever survey in Bhutan, solely focused on investigating human attitudes and perceptions toward the dhole, indicating that livestock loss to dholes transcends all positive attitudes to the species and drives a predominant dislike and opposition to its conservation. To improve the attitude and support toward the dhole and to foster dhole–human coexistence, livestock predation by dholes needs alleviation by improving the existing animal husbandry, in conjunction with promoting conservation awareness on this species.

Covid-19: Regional policies and local infection risk: Evidence from Italy with a modelling study.

Background: Policy-makers have attempted to mitigate the spread of covid-19 with national and local non-pharmaceutical interventions. Moreover, evidence suggests that some areas are more exposed than others to contagion risk due to heterogeneous local characteristics. We study whether Italy’s regional policies, introduced on 4th November 2020, have effectively tackled the local infection risk arising from such heterogeneity.Methods: Italy consists of 19 regions (and 2 autonomous provinces), further divided into 107 provinces. We collect 35 province-specific pre-covid variables related to demographics, geography, economic activity, and mobility. First, we test whether their within-region variation explains the covid-19 incidence during the Italian second wave. Using a LASSO algorithm, we isolate variables with high explanatory power. Then, we test if their explanatory power disappears after the introduction of the regional-level policies.Findings: The within-region variation of seven pre-covid characteristics is statistically significant (F-test p-value ) and explains 19% of the province-level variation of covid-19 incidence, on top of region-specific factors, before regional policies were introduced. Its explanatory power declines to 7% after the introduction of regional policies, but is still significant (p-value ), even in regions placed under stricter policies (p-value ).Interpretation: Even within the same region, Italy’s provinces differ in exposure to covid-19 infection risk due to local characteristics. Regional policies did not eliminate these differences, but may have dampened them. Our evidence can be relevant for policy-makers who need to design non-pharmaceutical interventions. It also provides a methodological suggestion for researchers who attempt to estimate their causal effects.Funding: None.