scholarly journals Landscape Resistance Index Aiming At Functional Forest Connectivity

2021 ◽  
Author(s):  
Ivan Vanderley-Silva ◽  
Roberta Averna Valente
Keyword(s):  
Land Surface ◽  
Structural Equation ◽  
Resistance Index ◽  
Biosphere Reserve ◽  
Equation Modeling ◽  
Landscape Resistance ◽  
Class Interval ◽  
Forest Connectivity ◽  
Environmental Attributes ◽  
The Matrix

Abstract The terrestrial surface is the basis for defining the species dispersion paths and overcoming the matrix resistance. In this approach, connecting paths with high levels of integrity must avoid barriers and anthropized areas. In this context, the main objective of this study was to develop the Landscape Resistance Index based on environment integrity. It was developed through Structural Equation Modeling (SEM), supported by the criteria of Land Surface Temperature, Nighttime Reflectance, and Inverted NDVI, which are called observed variables. The landscape studied in the Green Belt Biosphere Reserve of São Paulo has suffered from urban sprawl. However, it has significant remnants of the Atlantic Forest, which is a biodiversity hotspot. Our results indicated criteria variability in the landscape, however, modeled through the SEM, obtaining a significant adjustment of the Landscape Resistance Index, with CFI of 1.00 and RMSEA of 0.00. The index reflects the resistance levels of the land-use/land-cover, expressed by the class interval, ranging from 0% (1.73) to 100% (493.88), with the highest values associated with the anthropized uses and forest isolation. This way, the index based on environmental attributes reflects the structure of functional forest connectivity, supporting the planning design of forest corridors across landscapes.

scholarly journals Development of a structure-validated hypersexuality scale in Chinese university students

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Yanli Jia ◽  
Xu Shao ◽  
Chanchan Shen ◽  
Wei Wang
Keyword(s):  
University Students ◽  
Structural Equation ◽  
Negative Impact ◽  
Male Students ◽  
Equation Modeling ◽  
Validated Questionnaire ◽  
Five Factors ◽  
Exploratory Factor Analyses ◽  
The Matrix ◽  
Clinical Conditions

Abstract Background Hypersexuality is associated with many psychiatric disorders and creates enormous burden for the affected individual, family and society. There are numerous inventories measuring behavioral, emotional or stressful features of hypersexuality, we still need a structure-validated questionnaire to measure hypersexuality in a comprehensive way. Methods Based on previous inventories and related clinical descriptions of hypersexuality, we designed a matrix of 72 items related to hypersexual experience, and we invited 282 heterosexual university students who experienced hypersexuality at least once life-long to answer the matrix. Results Through exploratory factor analyses and exploratory structural equation modeling, we constructed a Hypersexuality Scale, with a satisfactory model structure of five factors (or scales, 4 items for each scale) of hypersexuality, and named them as the Negative Impact, Emotional Coping, Uncontrolled Behavior, Post-sex Regret, and Increased Interest. Most inter-correlations of these factors were significant but in low or medium levels in all participants. Male students scored significantly higher on Negative Impact and Increased Interest than females did. Conclusions The five scales described in this study might help to understand hypersexuality, and the Hypersexuality Scale might be applied to the clinical conditions related to hypersexuality.

Influence of Cognitive and Emotional Advertisements on Biosphere Reserve Image and Visitation Intention for Youth

2020 ◽  
Vol 11 (6) ◽  
pp. 1391
Author(s):  
Anda ARKLINA ◽  
Kristine GRINBERGA ◽  
Nripendra SINGH ◽  
Agita LIVINA
Keyword(s):  
Structural Equation ◽  
Online Survey ◽  
Biosphere Reserve ◽  
Equation Modeling ◽  
Daily Routine ◽  
Group Discussions ◽  
Biosphere Reserves ◽  
The North ◽  
Integrated Research ◽  
Social Media Platforms

The purpose of this study is to explore the role of the North Vidzeme Biosphere Reserve’s image (functional, symbolic and experiential) in building young visitors’ intentions to visit biosphere reserves. Integrated research methods were used. An online survey was conducted for data collection (n=295), and focus group discussions and observations (three groups - two from Latvia and one from Estonia) were conducted about youth traveling behavior in the North Vidzeme Biosphere Reserve. Descriptive statistics and structural equation modeling were used to analyze data. Findings showed that the North Vidzeme Biosphere Reserve has a weak image in the perception of young people. Most respondents agreed that visiting biosphere reserves relieves stress, helps them to socialize, and allows them to escape from daily routine; additionally, they noted that they would visit protected areas more often if they would see their friends visiting them. Youth 15–19 was more excited, pleasureful, and excited about visiting biosphere reserves, but youth 20–25 was more neutral about it. Both groups agreed that there was a lack of advertisements and visibility of these areas on social media platforms. Research results showed that improving functional, symbolic, and emotional images of the North Vidzeme Biosphere Reserve will have a positive effect on youth visiting and revisiting intentions.

Estimation in SEM: A Concrete Example

2007 ◽  
Vol 32 (1) ◽  
pp. 110-120 ◽  
Author(s):  
John M. Ferron ◽  
Melinda R. Hess
Keyword(s):  
Structural Equation ◽  
Likelihood Estimation ◽  
Equation Model ◽  
Equation Modeling ◽  
Unknown Parameters ◽  
Technical Literature ◽  
Partial Derivatives ◽  
First Order ◽  
The Matrix ◽  
Definition Of

A concrete example is used to illustrate maximum likelihood estimation of a structural equation model with two unknown parameters. The fitting function is found for the example, as are the vector of first-order partial derivatives, the matrix of second-order partial derivatives, and the estimates obtained from each iteration of the Newton-Raphson algorithm. The goal is to provide a concrete illustration to help those learning structural equation modeling bridge the gap between the verbal descriptions of estimation procedures and the mathematical definition of these procedures provided in the technical literature.

scholarly journals Rock the MIC: The Matrix of Implied Causation, a Tool for Experimental Design and Model Checking

2020 ◽  
Vol 3 (3) ◽  
pp. 286-299
Author(s):  
Timothy R. Brick ◽  
Drew H. Bailey
Keyword(s):  
Structural Equation Modeling ◽  
Experimental Design ◽  
Model Checking ◽  
Structural Equation ◽  
Equation Modeling ◽  
Causal Process ◽  
Path Modeling ◽  
Modeling Framework ◽  
Additional Tool ◽  
The Matrix

Path modeling and the extended structural equation modeling framework are in increasingly common use for statistical analysis in modern behavioral science. Path modeling, including structural equation modeling, provides a flexible means of defining complex models in a way that allows them to be easily visualized, specified, and fitted to data. Although causality cannot be determined simply by fitting a path model, researchers often use such models as representations of underlying causal-process models. Indeed, causal implications are a vital characteristic of a model’s explanatory value, but these implications are rarely examined directly. When models are hypothesized to be causal, they can be differentiated from one another by examining their causal implications as defined by a combination of the model assumptions, data, and estimation procedure. However, the implied causal relationships may not be immediately obvious to researchers, especially for intricate or long-chain causal structures (as in longitudinal panel designs). We introduce the matrix of implied causation (MIC) as a tool for easily understanding and reporting a model’s implications for the causal influence of one variable on another. With examples from the literature, we illustrate the use of MICs in model checking and experimental design. We argue that MICs should become a routine element of interpretation when models with complex causal implications are examined, and that they may provide an additional tool for differentiating among models with otherwise similar fit.

scholarly journals Farmers’ Intention to Climate Change Adaptation in Agriculture in the Red River Delta Biosphere Reserve (Vietnam): A Combination of Structural Equation Modeling (SEM) and Protection Motivation Theory (PMT)

2019 ◽  
Vol 11 (10) ◽  
pp. 2993 ◽  
Author(s):  
The Anh Luu ◽  
An Thinh Nguyen ◽  
Quoc Anh Trinh ◽  
Van Tuan Pham ◽  
Ba Bien Le ◽  
...  
Keyword(s):  
Climate Change ◽  
Structural Equation Modeling ◽  
Climate Change Adaptation ◽  
Structural Equation ◽  
Biosphere Reserve ◽  
Protection Motivation Theory ◽  
Red River ◽  
Equation Modeling ◽  
Red River Delta ◽  
Climate Risks

Coastal communities living in the low delta areas of Vietnam are increasingly vulnerable to tropical storms and related natural hazards of global climate change. Particularly in the Red River Delta Biosphere Reserve (RRDBR), farmers change the crop structure and diversify agricultural systems to adapt to the changing climate. The paper deals with a quantitative approach combined with behavior theories and surveyed data to analyze farmers’ intention to climate change adaptation in agriculture. Based on the Protection Motivation Theory (PMT), seven constructs are developed to a questionnaire surveying 526 local farmers: risk perception, belief, habit, maladaptation, subjective norm, adaptation assessment, and adaptation intention. Structural Equation Modeling (SEM) is implemented to extract eight factors and to quantify the relationship between protective behavior factors with the adaptation intention of the surveyed farmers. Two bootstrap samples of sizes 800 and 1200 are generated to estimate the coefficients and standard errors. The SEM result suggests a regional and three local structural models for climate change adaptation intention of farmers living in the RRDBR. Farmers show a higher adaptation intention when they perceive higher climate risks threatening their physical health, finances, production, social relationships, and psychology. In contrast, farmers are less likely to intend to adapt when they are subject to wishful thinking, deny the climate risks, or believe in fatalism.

Ambient Encounters in Retail “Discounters”

2020 ◽  
pp. 1-22
Author(s):  
Cristina Calvo-Porral
Keyword(s):  
Customer Satisfaction ◽  
Structural Equation ◽  
Equation Modeling ◽  
Factors Affecting ◽  
Discount Store ◽  
Product Assortment ◽  
Environmental Attributes ◽  
Store Location ◽  
Discount Stores ◽  
Product Layout

Cheap prices are the central positioning criterion of discount stores and the key variable explaining the intention to shop in discounters. Accordingly, discounters design their stores to maximize their efficiency. However, price may explain only a part of customer satisfaction. The purpose of this study is to delve into the environmental factors affecting discount retail store satisfaction. A conceptual model is empirically tested on the influence of discount store environmental attributes of customer satisfaction. Data are analyzed through partial least squares-structural equation modeling (PLS-SEM) on a sample of 381 customers. Findings show that factors, different from low prices, influence satisfaction with discount stores. Despite customers seek for low prices, the store personnel positively influences customer satisfaction, followed by a convenient product assortment and an attractive product layout and a convenient store location. Discount store managers may use the store personnel as a way to differentiate from other retail competitors in a cost-service tradeoff.

scholarly journals Financial Inclusion, Community Capacity Building and Pro-Wildlife Conservation Behavior around the Northern Periphery of Dja Biosphere Reserve, Cameroon

2020 ◽  
Vol 3 (1) ◽  
pp. 47
Author(s):  
Nashipu Thalut ◽  
Dobdinga Cletus Fonchamnyo ◽  
Molem Christopher Sama
Keyword(s):  
Factor Analysis ◽  
Capacity Building ◽  
Structural Equation ◽  
Wildlife Conservation ◽  
Biosphere Reserve ◽  
Financial Inclusion ◽  
Community Capacity ◽  
Equation Modeling ◽  
Conservation Behavior ◽  
Community Capacity Building

The study examines the contribution of financial inclusion and community capacity building on pro-wildlife conservation behavior among rural households at the Northern Periphery of Dja Biosphere Reserve, the east region of Cameroon. The data were elicited through the survey questionnaire administered on a sample of 279 households involved in the program of conservation in the areas. The study used a cluster sampling approach in grouping proximity villages into four zones and a purposive sampling technique was used in selecting the households. The objective was achieved empirically using three-stage maximum likelihood estimation techniques; factor analysis, confirmatory factor analysis and structural equation modeling. The result shows that financial inclusion and community capacity building had a significant positive effect on pro-wildlife conservation behavior. The magnitude of the effect of financial inclusion on pro-wildlife conservation behavior was even larger than the magnitude of the effect of community capacity building. The findings suggest that financial inclusion and community capacity building had the tendency to reduce the decline in wildlife stocks as it promoted friendly behavior towards wildlife and its habitats. The study, therefore, recommends policies that support financial inclusion and community capacity building that are essential for sustainable conservation since it promotes pro-wildlife conservation behavior.JEL Classification: G20, O15, Q57

Development of a Structure-Validated Hypersexuality Scale in Chinese University Students

2020 ◽  
Author(s):  
Yanli Jia ◽  
Xu Shao ◽  
Chanchan Shen ◽  
Wei Wang
Keyword(s):  
University Students ◽  
Structural Equation ◽  
Negative Impact ◽  
Male Students ◽  
Equation Modeling ◽  
Validated Questionnaire ◽  
Five Factors ◽  
Exploratory Factor Analyses ◽  
The Matrix ◽  
Clinical Conditions

Abstract BackgroundHypersexuality is associated with many psychiatric disorders and creates enormous burden for the affected individual, family and society. However, there is no structure-validated questionnaire available to measure hypersexuality in a comprehensive way, especially in aspects of emotion and stress. MethodsWe designed a matrix of 72 items related to hypersexual experience, and we invited 282 heterosexual university students who experienced hypersexuality at least once life-long to answer the matrix. ResultsThrough exploratory factor analyses and exploratory structural equation modeling, we constructed a Hypersexuality Scale, with a satisfactory model structure of five factors (or scales, 4 items for each scale) of hypersexuality, and named them as the Negative Impact, Emotional Coping, Uncontrolled Behavior, Post-sex Regret, and Increased Interest. Most inter-correlations of these factors were significant but in low or medium levels in all participants. Male students scored significantly higher on Negative Impact and Increased Interest than females did. ConclusionsThe five scales described in this study might help to understand hypersexuality, and the Hypersexuality Scale might be applied to the clinical conditions related to hypersexuality.

scholarly journals Diagnosis of Atmospheric Drivers of High-Latitude Evapotranspiration Using Structural Equation Modeling

Atmosphere ◽  
2021 ◽  
Vol 12 (10) ◽  
pp. 1359
Author(s):  
Sarah M. Thunberg ◽  
Eugénie S. Euskirchen ◽  
John E. Walsh ◽  
Kyle M. Redilla
Keyword(s):  
Structural Equation Modeling ◽  
Wind Speed ◽  
Solar Radiation ◽  
Path Analysis ◽  
High Latitude ◽  
Land Surface ◽  
Structural Equation ◽  
Heat Fluxes ◽  
Equation Modeling ◽  
Independent Contribution

Evapotranspiration (ET) is a relevant component of the surface moisture budget and is associated with different drivers. The interrelated drivers cause variations at daily to interannual timescales. This study uses structural equation modeling to diagnose the drivers over an ensemble of 45 high-latitude sites, each of which provides at least several years of in situ measurements, including latent heat fluxes derived from eddy covariance flux towers. The sites are grouped by vegetation type (tundra, forest) and the presence or absence of permafrost to determine how the relative importance of different drivers depends on land surface characteristics. Factor analysis is used to quantify the common variance among the variables, while a path analysis procedure is used to assess the independent contributions of different variables. The variability of ET at forest sites generally shows a stronger dependence on relative humidity, while ET at tundra sites is more temperature-limited than moisture-limited. The path analysis shows that ET has a stronger direct correlation with solar radiation than with any other measured variable. Wind speed has the largest independent contribution to ET variability. The independent contribution of solar radiation is smaller because solar radiation also affects ET through various other drivers. The independent contribution of wind speed is especially apparent at forest wetland sites. For both tundra and forest vegetation, temperature loads higher on the first factor when permafrost is present, implying that ET will become less sensitive to temperature as permafrost thaws.

A Psychometric Study of the Quality Perception Questionnaire

2012 ◽  
Vol 71 (2) ◽  
pp. 101-106 ◽  
Author(s):  
Raffaele Cioffi† ◽  
Anna Coluccia ◽  
Fabio Ferretti ◽  
Francesca Lorini ◽  
Aristide Saggino ◽  
...  
Keyword(s):  
Structural Equation ◽  
Factor Model ◽  
Equation Modeling ◽  
Fit Indices ◽  
Quality Perception ◽  
Italian Survey ◽  
Confirmatory Factor ◽  
Instrument Measuring ◽  
Hospital Structures

The present paper reexamines the psychometric properties of the Quality Perception Questionnaire (QPQ), an Italian survey instrument measuring patients’ perceptions of the quality of a recent hospital admission experience, in a sample of 4400 patients (Mage = 56.42 years; SD = 19.71 years, 48.8% females). The 14-item survey measures four factors: satisfaction with medical doctors, nursing staff, auxiliary staff, and hospital structures. First, we tested two models using a confirmatory factor analysis (structural equation modeling): a four orthogonal factor and a four oblique factor model. The SEM fit indices and the χ² difference suggested the acceptance of the second model. We then did a simulation using a bootstrap with 1000 replications. Results confirmed the four oblique factor solution. Third, we tested whether there were significant differences with respect to age or sex. The multivariate general linear model showed no significant differences in the factors with respect to sex or age.

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