Correspondence Analysis Research Articles

Functional traits mediate the elevational patterns of functional diversity and community structure of mosses in a tropical mountain area

Functional diversity refers to the value, range, and distribution of functional traits within a community, such as the morphological, physiological and behavioral characteristics of species that determine the role a species plays in an ecosystem. Assessing the drivers of elevational pattern of functional diversity is crucial to predict the effects of global change on functional diversity and community structure. In our research, we collected mosses species data from 65 sampling sites and measured 11 functional traits that are related to their ecological functions. We applied double canonical correspondence analysis (DCCA) to analyze species responses to environmental conditions based on their traits. We applied generalized additive models with a Gaussian function of variance to determine the elevational patterns of functional trait composition, diversity and community structure. We applied and compared boosted regression trees (BRT) without considering functional traits and piecewise structural equation modelling (SEM) mediated with functional traits to relate environmental variables with functional diversity and functional community structure, respectively. We found the first DCCA axis accounted for the largest dissimilarities between the two groups of species and correlated mainly with the water-utilization traits. Although both functional diversity and community structure displayed negatively skewed pattern along the elevational gradient, habitat complexity and climatic variables contributed differently to their respective patterns. The SEM approach consistently outperformed the BRT approach in explaining the variations in both functional diversity and community structure. Our findings highlight the important role of functional traits in mediating the relationship between the environment and functional diversity metrics. Both biotic and abiotic processes play a significant role in shaping the community assemblages, with environmental variables having distinct impacts. Traits related to structure maintenance, water absorption, cell hydration, and nutrient acquisition were found to be key drivers of functional diversity, while water-utilization traits were mainly responsible for regulating functional community structure.

Do gestures have meaning? An empirical analysis on the gestures performed by Fidel Castro at the United Nations

In everyday conversations, there are said to be unconscious meanings that we convey through our body. For example, if a story is being told, our hands move according to the message, following a rhythm and forming shapes that we are unaware of. According to McNeill (1992), gestures are a form of language different from speech, but even though they have been regarded as individual entities, they are, in fact, parallel and work in synch with each other. This is the scope of the analysis of gestures. In the following paper, the objective was to test whether there is an association between gestures and meaning. Consequently, the gestures of former Cuban president, Fidel Castro, were extracted and analyzed from his intervention at the United Nations in 1979. The process of annotation was carried out on the program ELAN, based on a series of categories: the type of gesture and topic, the position and movement of both arms and hands as well as the orientation. Additionally, a series of quantitative and qualitative analysis were performed through the statistical program R. A Chi-squared test showed a significant relationship between the type of gestures and the topics which was further corroborated through a conditional inference tree and a multiple correspondence analysis, reaffirming the idea that these are form-meaning pairs. Moreover, there was a strong connection between the type of gesture and arm movement, suggesting that this is due to the intention of the message while the orientation of the hand was a clear indicator of arm movement.

Mcadet: A feature selection method for fine-resolution single-cell RNA-seq data based on multiple correspondence analysis and community detection.

Single-cell RNA sequencing (scRNA-seq) data analysis faces numerous challenges, including high sparsity, a high-dimensional feature space, and biological noise. These challenges hinder downstream analysis, necessitating the use of feature selection methods to identify informative genes, and reduce data dimensionality. However, existing methods for selecting highly variable genes (HVGs) exhibit limited overlap and inconsistent clustering performance across benchmark datasets. Moreover, these methods often struggle to accurately select HVGs from fine-resolution scRNA-seq datasets and minority cell types, which are more difficult to distinguish, raising concerns about the reliability of their results. To overcome these limitations, we propose a novel feature selection framework for scRNA-seq data called Mcadet. Mcadet integrates Multiple Correspondence Analysis (MCA), graph-based community detection, and a novel statistical testing approach. To assess the effectiveness of Mcadet, we conducted extensive evaluations using both simulated and real-world data, employing unbiased metrics for comparison. Our results demonstrate the superior performance of Mcadet in the selection of HVGs in scenarios involving fine-resolution scRNA-seq datasets and datasets containing minority cell populations. Overall, we demonstrate that Mcadet enhances the reliability of selected HVGs, although the impact of HVG selection on various downstream analyses varies and needs to be further investigated.

Eco-Innovation: Analysis of EU Member States Performance in the EU Eco-Innovation Index 2013–2022

Sustainability is about intergenerational solidarity in finding solutions to ensure the continued growth that allows organizations and companies to be proactive. In the context of contemporary technology, the fourth industrial revolution, i.e., the widely accepted notion of Industry 4.0, and swift corporate growth; the effects of industry, transportation, and urbanization on climate change; and the preservation of the environment in its entirety are becoming more and more significant. The primary objective of this study is to evaluate the eco-innovation performance of European nations, comparing their evolution from 2013 to 2022, in order to identify patterns, leaders, and opportunities for improvement in the implementation of eco-innovation strategies. This study includes the analysis of the Eco-Innovation Index as well as other studies carried out at the European Union level in the field of sustainability and sustainable innovation through the graphic maps, cluster analysis, and correspondence analysis in the statistical program SPSS. Different approaches to development are taken by the EU’s member states. Even though some countries have achieved significantly lower results than the average of the Eco-Innovation Index or significantly higher results than the average, overall, all countries (except Romania) have improved their point evaluations when compared to the year 2013 when the Eco-Innovation Index started to be reported. The nations in the Northern European region produce consistent, long-term outcomes, and these countries have emerged as leaders in innovation in recent years. The countries of Luxembourg, Austria, Finland, Sweden, and Denmark have the best long-term outcomes. On the contrary, Bulgaria has ranked last for a long time, with the least-rated eco-innovation activities.

Distribution Patterns of Urban Spontaneous Vegetation Diversity and Their Response to Habitat Heterogeneity: A Case Study of Five Cities in Heilongjiang Province, China

Spontaneous vegetation is an important component of urban biodiversity and an excellent agent for exploring the mutual feedback mechanism between urbanization and urban ecosystems. Rapid urbanization has had a significant impact on the composition, structure, and distribution patterns of urban spontaneous vegetation diversity. Studying the diversity distribution patterns and causes of urban plant communities is beneficial for understanding the formation and maintenance mechanisms of plant diversity in specific urban habitats. This study selected five cities in different climate subregions of Heilongjiang Province as research targets and conducted field research using uniform sampling and typical sampling methods. The composition, distribution pattern, and driving factors of spontaneous vegetation were analyzed. The results showed the following: (1) A total of 633 examples of spontaneous vegetation were recorded, belonging to 93 families and 341 genera, mainly consisting of herbaceous plants and native plants. (2) The diversity index and similarity index of spontaneous vegetation in gravel-type abandoned land habitats are higher than those in other habitat types, while the diversity index of spontaneous vegetation in trees and shrubs is lower, and there is no significant difference in regards to different habitats. (3) Urban population density is a key factor affecting the diversity of native plants, while woody plant coverage, patch area, and landscape trait index are key factors affecting non-native plants. (4) The results of canonical correspondence analysis (CCA) showed that the total explanatory power of environmental characteristic factors in regards to the distribution pattern of spontaneous vegetation was 7.5%. The closest distance between adjacent patches, the coverage of woody plants in patches, the distance from the city edge, the patch area, and the surface impermeability of the buffer zones were key factors affecting the distribution of dominant species in spontaneous vegetation communities. The research results will provide an important reference for the conservation of urban biodiversity and the construction of low-maintenance urban green space plant landscapes in Heilongjiang Province.

Consumer Support for Climate Policies Driven by Political Ideologies

Consumer support for climate policies is essential for new sustainable consumption patterns, which may face challenges considering the left-right political spectrum. This study aims to understand how different types of climate policies receive different levels of support from Liberals (Left), Moderates (Center), and Conservatives (Right). We analyzed data from an online panel with 1000 Brazilians through linear (ANOVA, MANOVA, and Correspondence Analysis) and non-linear predictive (Artificial Neural Networks) methods. Although Liberals are more concerned about overall global warming and climate change than Conservatives, both groups are more prone to support than to oppose climate change public policies. Moreover, while Moderates and Conservatives are getting more concerned about climate change, Liberals are becoming more pessimistic about mitigation strategies. Policies based on opportunity-facilitating or constraining using regulatory or economic instruments are associated differently with Liberals, Moderates, and Conservatives, indicating specific preferences for each political ideology.

Characterization of dairy goat production systems in coastal valleys of the Lima region

Goat farming in Peru is a husbandry activity that, although it is considered secondary in the country, has a great economic and social impact on the rural population, that is why government efforts to develop is so important. The objective of this study was to characterize dairy goat rearing systems in the coastal valleys of the Lima region to identify gaps and opportunities for improvement. This cross-sectional research was conducted in four provinces located in the Lima region, Peru. A total of 62 goat farmers participated in the trial. For data collection, a standard survey was prepared with open and closed questions distributed across two components (socioeconomic and productive). The surveys were processed for qualitative variables using a multiple correspondence analysis (MCA) followed by a hierarchical cluster analysis (HCA) to differentiate the types of farming systems prevalent based on the survey population. The hierarchical cluster analysis resulted in the formation of three separate groups of goat farmers, which can be classified as extensive systems differentiated by management practices and their production and marketing objectives. The test showed a significant difference; therefore, it can be affirmed that they are associated with the groups or clusters formed. These results will allow actors related to goat farming, such as state and regional entities, to focus efforts on addressing specific demands of the different types of goat farmers found in this study.

Two worlds, one nation? Comparing the political spaces of Flanders and Francophone Belgium

Abstract The transformation of the Belgian party system has unfolded asymmetrically: while conservative and far-right parties have thrived in Flanders, the populist right vote has not (yet) been mobilized in Francophone Belgium. Focusing on the demand side of electoral politics, this article explores whether these disparities on the supply side mirror distinct political dimensions and cleavages in both regions. By using an innovative methodology of (class-specific) multiple correspondence analysis, we find that the Flemish and the Francophone political space are largely alike – both in terms of the composition of their political dimensions as in their cleavage structure. However, we also find that Francophones adhere to a distinctive welfare consensus, which prevents working-class embourgeoisement and likely moderates the electoral fortunes of the far right. Overall, our results challenge the common stereotypes of a ‘conservative Flanders’ and a ‘progressive Wallonia’.

Perceptions and responses to diseases among patients with inflammatory bowel disease: text-mining analysis of posts on a Japanese patient community website

Introduction: Patients with inflammatory bowel disease (IBD) are increasingly using online platforms to communicate with other patients and healthcare professionals seeking disease-related information and support. Free-text posts on these platforms could provide insights into patients’ everyday lives, which could help to improve patient care. In this proof-of-concept study, we applied text-mining to extract patient needs from free-text posts on a community forum in Japan, and holistically visualized the patients’ perceptions and their connections, and explored the patient characteristic-dependent trends in the use of words. Methods: Free-text posts written between May 11, 2020 and May 31, 2022 on the community forum were retrieved and subjected to text-mining analysis. Trends in the use of words were extracted from the posts for correspondence and co-occurrence network analyses using KH Coder open-source text-mining software. Results: Seventy-four posts were analyzed. Using text mining methods, we successfully extracted and visualized a variety of patient concerns and their connections. The correspondence and co-occurrence analyses revealed patient segment-dependent trends in the use of words. For example, patients with a disease duration of ≤5 yrs were more likely to use words related to emotions or their desire to change or quit their job, such as ‘anxiety’ and ‘resignation.’ Patients with a disease duration of >10 yrs were more likely to use words showing that they are finding ways to live with or accept their disease, and are getting used to the lifestyle but some patients continued to experience worsening disease. Conclusions: We found that free texts posted on an IBD community forum can be a useful source of information to capture the wide variety of thoughts of patients. Text mining procedures can help to visualize the relative importance of the topics identified from free text posts. Our findings of this proof-of-concept study will be useful for generating new hypotheses to better understand and address the needs of patients with IBD.

Mapping epistemic pluralism: A network analysis of discursive practices in communities promoting refused knowledge about healthcare and wellbeing

This article presents an analysis of discourses performed in communities that share and disseminate knowledge refused by institutional science. The study focuses on an online community concerned with alkaline water, food, and lifestyle, aiming at understanding how promoters of refused knowledge in this community enrol other forms of knowledge, including science. Theoretically, this work is framed in Science & Technology Studies, and in the tradition of actor-network theory, situating itself in a recent turn that takes epistemic instability and pluralism into due consideration, thus overcoming opaque views of the opposition between science and non-science. Empirically, this fine-grained analytic purpose is addressed by a mixed-method strategy in which discursive practices are observed through a web-ethnography conducted between January 2020 and December 2021 on the relevant online spaces and then analysed qualitatively and quantitively by means of formal techniques. Relying on the tools of social network analysis, the discursive space of the community under study is formalised as a two-mode network of knowledge claims and heterogeneous actors enrolled in discourse to sustain those claims. Then, community detection is performed to map the different assemblages of claims and actors and the relevant repertoires characterising those assemblages. Finally, multiple correspondence analysis applied to two-mode networks is used to highlight the dimensions of concern and meaning expressed in the knowledge organisation of this community.

Assessing the spread of sulfachloropyridazine in poultry environment and its impact on Escherichia coli resistance

Sulfachloropyridazine (SCP) is an antimicrobial (AM) commonly used in the poultry industry. This drug is excreted as the original compound, which may accumulate in litter. This work was done to assess whether SCP residues from droppings of broiler chickens that were treated with therapeutic doses of this drug spread into the production environment and to determine if these events were associated with the selection of resistant bacteria. To this end, broiler chickens were raised under controlled conditions, and their droppings and litter were processed to detect and identify SCP residues using an HPLC-MS/MS technique. This study selected Escherichia coli as an indicator bacterium for AM resistance. Its phenotypic resistance was determined using the Kirby-Bauer disk diffusion method, and its genotypic resistance was determined by performing a conventional PCR test. Our results showed that SCP residues did spread from the treated group to untreated sentinel groups because SCP residues in the litter reached levels up to 43.05 µg·kg−1 in a group placed immediately adjoining to the treated group, while another group placed 30 cm away showed a concentration of 29.79 µg·kg−1. Meanwhile, only trace concentrations were detected in droppings collected from sentinel groups. Of 239 strains of E. coli isolated from droppings, 12.13 % were resistant to sulfonamides, whereas 23.91 % of 92 E. coli isolated from broiler litter were resistant. The most prevalent resistance gene was the sul2 gene, both in droppings and litter, followed by the sul1 gene. The SCP concentrations were associated with the probability of E. coli being resistant to sulfonamides (p-value = 0.01). A Multiple Correspondence Analysis (MCA) also showed that phenotypic and genotypic resistances were associated and that both genes sul1 and sul2 would determine phenotypic resistance to sulfonamides in E. coli. The results presented in this study show that inedible by-products of the poultry industry are potentially a source of drug resistance that can spread from the animal production line to the environment, so awareness of the correct use of antimicrobials is essential to combat antimicrobial resistance.

Correlations Between Spatiotemporal Variations in Phytoplankton Community Structure and Physicochemical Parameters in the Seungchon and Juksan Weirs

The Yeongsan River is one of the four major rivers in South Korea. Since the construction of two weirs as part of the Four Major Rivers Project to secure water resources in 2011, issues with algal blooms have frequently arisen, prompting the Ministry of Environment of Korea to conduct continuous monitoring of water quality and algal outbreaks. This study, conducted between 2019 and 2023, examined the relationship between the phytoplankton community structure and physicochemical factors at the Seungchon and Juksan weirs. Phytoplankton were categorized into four groups (Bacillariophyceae, Chlorophyceae, Cyanophyceae, and other phytoplankton), and 20 dominant genera were selected for analysis. As microalgal species vary depending on environmental conditions, understanding the specific relationships among the microalgae observed in the study area can help explain their occurrence mechanisms and contribute to the development of effective management strategies. Therefore, we used principal component analysis (PCA) to analyze the seasonal variation patterns of the four microalgal groups and visualize key data features through dimensionality reduction. Additionally, PCA was employed to identify and visualize environmental factors related to seasonal variations in phytoplankton communities. PCA helped elucidate how different environmental factors influence phytoplankton fluctuations across seasons. We used canonical correspondence analysis (CCA) to investigate the relationships among the 20 dominant genera in each group and environmental factors. Additionally, CCA was used to analyze the relationship between the distribution of the top five dominant phytoplankton taxa in each group and various environmental factors. CCA allowed for a detailed examination of how these dominant taxa interact with environmental conditions. PCA revealed significant correlations between other phytoplankton and Chl-a in spring and Cyanophyceae and water temperature in summer. Bacillariophyceae was positively correlated with nitrogen-based nutrients but negatively with phosphate phosphorus (PO4-P). CCA revealed significant correlations between dominant genera and environmental factors. Stephanodiscus sp. was associated with nitrogen-based nutrients, whereas Microcystis sp. and Dolichospermum sp. were associated with water temperature and PO4-P. Stephanodiscus sp. affected water treatment through filtration and sedimentation issues, whereas Microcystis sp. and Dolichospermum sp. produced the toxin microcystin. These findings offer valuable insights for water quality management.

Health Management of Remote Workers Using Tele-Exercise During The COVID-19 Pandemic in Japan

Health management is increasingly recognized as a vital business resource aimed at enhancing employee well-being. The COVID-19 pandemic has significantly influenced lifestyle habits, underscoring the need for effective health management strategies tailored to thechanging work environment. This study aims to explore the impact of tele-exercise interventions on remote workers group (G1). Itcompares the effects of tele-exercise with those of traditional face-to-face exercise group (G2). Over three months, G1 engaged in a 30-minute weekly exercise program tailored for remote execution, while G2 participated in traditional, in-person sessions. The analysis includedANOVA to assess the differences over time between G1 and G2, Correlation Analysis to examine the relationships among the measuredvariables within each group, and Correspondence Analysis to explore the association patterns between the groups' responses and thevariables of interest. The ANOVA revealed a significant difference in Daily Stress (DS) levels between G1 and G2, with G1 showing higherDS levels. Correlation analysis indicated a strong negative relationship between Body Mass Index (BMI) and Sleep Quality (SQ) in G1, and astrong positive relationship between DS and Satisfaction of Life (SL). Correspondence Analysis showed that that G1 was encompassed in ajob and life satisfaction area, and G2 was encompassed in a sleep and stress for weight control area. This study concluded that both groupsinitially experienced weight gains and increased sleep duration due to remote work. Daily Stress was found to be significantly higher in G1than in G2, possibly due to the isolation of tele-exercise. Correlation analyses highlighted the influence of time on relationship between BMIand SQ, and DS and SL. The study emphasizes stress management and good sleep quality in remote work, with exercise interventionspromoting well-being and productivity.

Implications of Farm Production and Farmers' Characteristics on Poverty Reduction in Benue Division, Cameroon

The main objective of this study was to determine the effect of farm production and Farmers' Characteristics on Poverty Reduction in the Benue division in the Northern region of Cameroon. Data were collected from 399 respondents using a self-administered questionnaire through a stratified sampling technique of 12 sub-divisions in the Benue division. We adopted a survey research design. To estimate our results, we used Multiple correspondent analysis (MCA) and the OLS technique. The results reveal that there is a positive relationship between farm production and poverty reduction in Benue state. An increase in farm production will lead to a 2.19% reduction in farmers' poverty in Benue and this result is significant at a 5% level of significance. Similarly, the farmer's characteristics reveal that gender, farmers' experience, and educational level also significantly affect poverty reduction. In this light, there is a need for the government to train and deploy more extension workers in the various sub-divisions and communities in Benue division, to increase farmers' access to these services. This can be done by imparting specific skills to produce dominant food crops and livestock in the Benue division through workshops and seminars.

Social Representations of the War in Italy during the Russia/Ukraine Conflict

Social representations of the war, anchored in historical experience and cultural values, play a motivational role in justifying collective behavior. Following Russia’s 2022 invasion of Ukraine, the research delves into the meanings associated with war through a social representation approach. Employing Doise’s sociodynamic approach, researchers identify the semantic field linked with war and analyze its organizing principles, revealing the variability of representations. In total, 313 Italian participants (female = 241, 75.4%; age range = 18–74) completed a questionnaire featuring a free association task with the word “war”, providing demographic and political and religious orientation data. Lexical correspondence analysis, utilizing Spad-t software, highlights three polarized themes: the emotional dimension aroused by war, media-conveyed imagery, and the underlying causes of conflict. The social anchoring analysis projects variables such as gender and political orientation onto a factorial plane. Finally, cluster analysis dissects psychological anchoring, identifying four distinct groups characterized by their descriptions of war: effects, reasons, emotions, and images. Theoretical and practical implications are discussed.

Dynamics of phytoplankton community in relation to environmental variables in tropical mangrove estuary, Sundarbans, India

Aim: To explore the spatio-temporal variation of phytoplankton diversity and community structure, in response to associated environmental variables in Matla estuary, Sundarbans, India. Methodology: Monthly sampling was carried out from August 2022 to July 2023 at three locations within the estuary. Plankton was identified and its dynamics were studied in relation to the environment variables. Results: A total of 38 genera of phytoplankton, belonging to 8 classes, were identified. Spatial diversity was high in the upper reaches of the estuary, while temporal diversity peaked during the monsoon season. The majority of the abundance (96%) was contributed by four classes: Coscinodiscophyceae (35%), Mediophyceae (27%), Bacillariophyceae (25%) and Dinophyceae (9%). Bacillariophyceae exhibited higher species richness, while Coscinodiscophyceae dominated in terms of density. Cluster analysis and non-metric multidimensional scaling revealed four separate groups with varying spatio-temporal attributes. Analysis of variance (ANOVA) post-hoc tests highlighted significant variations in environmental parameters across seasons. Various phytoplankton groups were positively correlated with the physio-chemical parameters such as temperature, alkalinity, free CO2, NO3, NO2, silicate, temperature, orthophosphate and chlorophyll-a. Biota-environment stepwise analysis (BIO-ENV) underscored the importance of air temperature and free CO2 (ρ= 0.4929) as key factors shaping phytoplankton distribution and community structure. Canonical Correspondence Analysis (CCA) further showed the significant influence of parameters such as temperature, silicate, nitrite and orthophosphate on the phytoplankton community. Interpretation: Finding of this study enriches our comprehension of estuarine ecosystem dynamics, and this information may serve as a baseline study and thereby aid in framing management measures for long-term conservation and management of both biotic and abiotic components within estuaries. Key words: Environmental variables, Estuary, Mangrove, Phytoplankton, Sundarbans

Requirements for Standard and I/O Cell Library Domestic Characterization System Development

The article is devoted to define requirements and discover specific featuresfor domestic standard cell and I/O libraries characterization EDA tool. A general structure of the library characterization system is presented. The basic requirements indicted for the system are considered and analyzed in the article. A comparative analysis of correspondence to these requirements for domestic and foreign characterization tools is done. The specific features the domestic library characterization system should satisfy are formulated. Among the main features the following are outlined in the article: compatibility and support of domestic OS, support of well-known foreign and domestic Spice-simulators, Russian language support for documentation, scalability, ensuring confidence of the output data. A brief review of typical tasks, intrinsic for characterization tool development and corresponding algorithms, required for its resolving is given. The following issues along with appropriate proposals for its solution are mentioned: automated definition of optimal input waveforms for sequential cells initialization, searching for maximum capacitance load for the cell, setup and hold parameters calculation for sequential cells, method of optimal output current PWL approximation for CCS parameters calculation. As a conclusion of the investigation the current status of domestic characterization systems development is analyzed. In the outcome a problem of domestic library characterization tool that aligned with all the requirements and support the specific features defined above has been raised.

Socio-Economic Status of Individuals in Tehran University of Medical Sciences Employees` Cohort Study Using PCA, MCA and FAMD Methods

Introduction: Determining socio-economic status (SES) can greatly help decision makers in the field of social health. Because SES can play an important role in accessing medical services or welfare amenities. We aimed to determine the SES using principal component analysis (PCA), multiple correspondence analysis (MCA), and factor analysis of mixed data (FAMD) methods. Methods: In this cross-sectional study (2023), 4448 employees aged 19 to 75 years were included to the study from Tehran University of Medical Sciences employees` cohort (TEC). Demographic variables and socioeconomic factors were considered. Considering the weaknesses of PCA and MCA methods, we calculated the SES score using PCA, MCA and FAMD methods, and the percentile of people was determined. These weaknesses include normality assumption and considering only linear relationship for PCA, inability to interpret the relationships between variables and considering each level of classification variables as a new variable for MCA. Results: We studied 4448 people (39.3% men) with mean age of 42.3 and a standard deviation of 8.7.The correlation between the percentiles obtained through PCA, MCA and FAMD methods was very high, and the highest correlation was related to the percentiles obtained through PCA and FAMD methods with a value of 0.994. The intraclass correlation coefficient value was 0.996. Also, this value was 0.996 and 0.994 in the random samples of 250 and 100 individuals from the original data, respectively. Conclusion: All of the three methods worked similarly on determining the SES and calculating the percentile of people. PCA and FAMD methods had better agreement than others. Therefore, in studies that have both quantitative and qualitative variables, the choice of analysis method depends on the opinion of the researcher.

Diversity Patterns of Plant Communities along an Elevational Gradient in Arid and Semi-Arid Mountain Ecosystems in China

Quantitative classification and ordination are instrumental in improving our understanding of plant community patterns and facilitating effective conservation efforts in national mountain ecosystems worldwide. However, there has been a lack of relevant research focused on arid and semi-arid mountain ecosystems. This study aims to address this gap by investigating the Ningxia Helan Mountain National Nature Reserve (located in Northwest China). We conducted a comprehensive study on the patterns of plant communities and their association with environmental factors across a broad elevation range from 1200 m a.s.l. to 2600 m a.s.l. Our findings revealed the presence of 121 angiosperm species across 41 families, with vegetation classified into six distinct groups through two-way indicator species analysis (TWINSPAN) along the elevational gradient. Notably, the communities of Ulmus, Prunus, and Stipa in the middle elevation range exhibited the highest Shannon–Wiener (SW) and Simpson (SN) diversity indices, and these indices followed a single-peak pattern with increasing elevation. Canonical correspondence analysis (CCA) further revealed six distinct yet interrelated plant communities, revealing elevation (ELE) and the biological aridity index (BK) as the most influential environmental factors influencing plant communities’ distribution. This understanding is critically important for biodiversity conservation and the management of ecosystems in arid and semi-arid mountain ecosystems.

Study on the concentration, distribution, and persistence of health spending for the contributory scheme in Colombia

Colombia is among the countries with the most robust financial protection against personal health spending in the world, with out-of-pocket spending ranking lowest across OECD countries. We investigate the evolution, distribution, and persistence of health spending by age group, sex, health care setting, health condition and geographic region for over 19 million users of Colombia’s health system between 2013 and 2021 (contributory scheme). We use average patient-level expenditure data from the Health-Promoting Entities of the Ministry of Health and Social Protection. We applied multivariate statistical techniques such as multiple correspondence analysis, factor maps and correlations. For both sexes, average health expenditure increases gradually with age until 60 years, accelerating thereafter abruptly. Health conditions with the highest percentage of expenditure were those related to neoplasms, blood diseases, circulatory system, pregnancy, puerperium and perinatal period. We found that home-based care in Amazonía-Orinoquía is almost non-existent, and that outpatient care represents a high proportion in all age groups (over 65%) compared to the other regions. There is a strong persistence of expenditure from one year to the next (i.e. they can provide relevant information for prediction), especially in areas with a larger supply of health services such as Bogotá-Cundinamarca. To the authors’ knowledge, this is the most comprehensive and detailed micro-analysis of health spending that has been developed for a Latin American country to date.