Sampling Units Research Articles

MODELAGEM PREDITIVA APLICADA AO MAPEAMENTO DE RISCO POTENCIAL DE EROSÃO DE SOLOS NA AMAZÔNIA OCIDENTAL

The modeling of areas susceptible to soil loss due to hydro-erosive processes consists of methods that simplify reality to predict future behavior based on the observation and interaction of a set of geoenvironmental factors. Thus, the objective of the current analysis is to predict susceptibility to soil loss and map areas with the potential risk of erosion using the principles of Binary Logistic Regression (BLR) and Artificial Neural Networks (ANN). The hydrographic sub-basin of the Sete Voltas River (330 km2), Rondônia, Brazil, was defined as the experimental area. Models were obtained using 100 sample units and 14 predictor parameters. Susceptibility was mapped based on five reference classes: very low, low, moderate, high, and very high. ANN obtained an area under the curve (AUC) of 0.808 and global precision of 79.2%, and the BLR model showed an AUC of 0.888 and global precision of 77%. Potentially susceptible areas represent 57.71% and 54.80% of the area for BLR and ANN models, respectively. The greatest potential risks are verified in places with no vegetation cover associated with agricultural practices. The technique proved to be effective, with adequate precision and the advantage of being less time-consuming and expensive than other methods. Keywords: Binary Logistic Regression; Artificial Neural Network; Erosion Susceptibility.

FACTORS AFFECTING THE USE INFORMATION AND COMMUNICATION TECHNOLOGY IN MANAGING GREENHOUSE

In recent years, information and communication technology in the field of e-commerce has reduced many of the challenges of business development. E-commerce can be used to develop the agricultural sector and to market agricultural products. This research is a survey aimed at evaluating the adoption of greenhouse owners to Affecting the use information and communication technology in managing greenhouse units in Isfahan Township. The type of research is descriptive-analytic. The statistical community is about 460 and 197 number of sample units are accidentally chosen using Cochran formula with possible precision. The research method was library and field based. After determining the indices and variables of the research, a researcher-made questionnaire was used to collect the required statistical data in the study area. The main tool of the research is questionnaire and its processing is done in the software Spss21. The reliability of questionnaire has been gained through using cronbach alpha also the validity of the research was also calculated using the KMO coefficient higher than 0.7. Results of this research showed that 10 percent greenhouse owners have started accepting the use information and communication technology in managing greenhouse units. The results of the research show that the there was a correlation between the level of education, job satisfaction and income level with the components of adopting, decision, persuasion, and knowledge of meaningful and positive. The results of regression analysis also show that variables such as age, job, experience and communication channels, psychological factors and decision describe 46 percent of the dependent variable of accepting the use of the internet.

Geospatial and environmental determinants of stunting, wasting, and underweight: Empirical evidence from rural South and Southeast Asia

ObjectiveChild malnutrition, comprising of undernutrition and obesity, is a global concern with severe implications for survival, leading to acute and chronic diseases that adversely affect the productivity of individuals and society. Asia shoulders the greatest burden, with 7 out of 10 undernourished children residing in the region. Despite the decline in global child stunting, particularly in Asia, its prevalence remains significant. In 2017, an estimated 151 million children under five experienced stunting, and an additional 38 million were overweight, with Africa and Asia accounting for 25% and 46% of the global figures, respectively. Therefore, this paper aims to analyze the geospatial and environmental determinants of undernutrition in rural South and Southeast Asia. MethodsTo explore the geospatial and environmental determinants of undernutrition (stunting, wasting, and underweight), we use Poisson regression and the data from recent rounds of the Demographic and Health Survey (DHS) from India, Bangladesh, Pakistan, Nepal, Cambodia, and Timor-Leste. ResultsThis study found a high prevalence of stunting, wasting, and underweight among children aged 0 to 59 months in rural areas of South and Southeast Asia, with considerable variation between countries and clusters/primary sampling units. Results show a positive association between child malnutrition and factors such as maternal illiteracy, unsafe drinking water, and dirty cooking fuel in South and Southeast Asia. Children from impoverished households in India, Pakistan, and Cambodia were disproportionately affected. In addition to socio-economic factors, climatic risks such as temperature increase and rainfall variations also emerged as important determinants of child malnutrition in India, Bangladesh, and Timor-Leste. ConclusionsThis paper emphasizes the role of environmental and climatic factors on child nutrition, underscoring their significance regardless of socio-economic conditions. As the impacts of climate change continue to intensify, and agrarian societies bear the brunt, these factors will play a critical role in shaping child nutritional outcomes. Thus, amid growing climate change, nutritional security should be prioritized, considering the spatial domain and targeting climate distress areas along with other socio-economic and demographic aspects.

Impact of Digital Finance on New Venture Performance Along with the Moderating Role of Entrepreneurial Finance and Risk Management

This research seeks to unravel the influence of digital finance on the performance of emerging ventures and delve into the moderating roles of risk management and entrepreneurial finance in shaping this dynamic relationship. This study tried to answer the question if digital finance plays a role in enhancing the performance of new ventures and whether entrepreneurial finance and risk management moderate this relation. The data used in our study is primary data, collected directly from the respondents through a structured questionnaire using convenience sampling techniques. The sampling unit were managers, owners, and employees of new ventures. The sample size was 370 individuals. A partial least square tool is used to analyze the data. Confirmatory factor analysis is conducted in which reliability and validity are examined by composite reliability, Cronbach alpha, AVE, and discriminant validity were measured using heterotrait-monotrait ratio. PLS structural model was used to investigate the relationship between variables. The study outcomes unveiled a noteworthy positive correlation between digital finance and the performance of new ventures. Additionally, a significant and positive association between entrepreneurial finance and new venture performance emerged, while an analogous positive relationship between risk management and new venture performance was also evident upon data analysis. Furthermore, risk management and entrepreneurial finance also play a moderating role between new venture performance and digital finance. This study will contribute to filling the gap in the literature and will help the researchers, teachers, students, and practitioners to better understand the direct impact of digital finance, entrepreneurial finance, and risk management and moderating effect of entrepreneurial finance and risk management on new venture performance. Practical implications of the study are that the study will help practitioners of newly initiated businesses to place importance on implementing each of the variables while running the business. The higher success rate of new ventures will motivate more people to start a new business and help to improve the economy. The cross-sectional design of the study, coupled with the utilization of a convenient sampling technique and a restricted sample size, introduces certain constraints and limitations to our research.

Effects of Eucalyptus species on soil physicochemical properties in Ruhande Arboretum, Rwanda

This study combines research on soil physical and chemical properties as affected by four Eucalyptus species in Ruhande arboretum. The soil samples for research properties were taken from 0-20 cm depth using auger and one undisturbed core from each sampling unit was taken for the analysis of soil bulk density. Soil bulk density and moisture did not differ significantly between all treatments. Sand proportions differed significantly only between E. tereticornis and E. maidenii whereas silt and clay were non-significant. The soil under Eucalyptus was sandy, with sand proportion ranging from 66.4-71%. Bulk density increased with increasing sand whereas moisture content showed a reverse trend. The soil samples for studying chemical properties were taken as described in Nsabimana et al. 2008. All chemical parameters except base saturation differed significantly between treatments. Soil pH was strongly acidic but rich in total nitrogen and organic carbon which was attributed to higher litter production, its relatively faster rate of decomposition, and greater amount of residues produced by the eucalypts. Carbon/nitrogen ratio, CEC, and BS were high under all treatments while the available phosphorus was lower which was attributed to the low pH. Future studies should test if the species similarly affect the soil or not and confirm if the species increase soil nutrients. Benchmarked study sites should be used to enable differences in the species effects on the site if any.

Assessing intra- and inter-method agreement of functional data.

Modern medical devices are increasingly producing complex data that could offer deeper insights into physiological mechanisms of underlying diseases. One type of complex data that arises frequently in medical imaging studies is functional data, whose sampling unit is a smooth continuous function. In this work, with the goal of establishing the scientific validity of experiments involving modern medical imaging devices, we focus on the problem of evaluating reliability and reproducibility of multiple functional data that are measured on the same subjects by different methods (i.e. different technologies or raters). Specifically, we develop a series of intraclass correlation coefficient and concordance correlation coefficient indices that can assess intra-method, inter-method, and total (intra + inter) agreement based on multivariate multilevel functional data consisting of replicated functional data measurements produced by each of the different methods. For efficient estimation, the proposed indices are expressed using variance components of a multivariate multilevel functional mixed effect model, which can be smoothly estimated by functional principal component analysis. Extensive simulation studies are performed to assess the finite-sample properties of the estimators. The proposed method is applied to evaluate the reliability and reproducibility of renogram curves produced by a high-tech radionuclide image scan used to non-invasively detect kidney obstruction.

Southern Ethiopian skilled birth attendant variations and maternal mortality: A multilevel study of a population-based cross-sectional household survey.

Studies examining skilled birth attendants (SBA) use and its correlation with maternal mortality at lower administrative levels are scarce. This study assessed the coverage and variations of SBA, the physical accessibility of health facilities for SBA, and the association of SBA with maternal mortality. A cross-sectional study using a population-based household survey was conducted in six Sidama National Regional State, southern Ethiopia districts, from July 2019 to May 2020. Women who had given birth in the past two years before the study were included. Stata 15 and ArcGIS 10.4.1 were used for data analysis. A multilevel logistic regression analysis was conducted to assess the effect of the sampling units and identify factors independently associated with SBA. The association between SBA and maternal mortality was examined using maternal mortality household survey data. A total of 3191 women who had given birth in the past two years and resided in 8880 households sampled for the associated maternal mortality household survey were interviewed. The coverage of SBA was 46.7%, with high variations in the districts. Thirty percent of SBA use was accounted for by the differences among the districts. One-third of the women travel more than two hours on foot to access the nearest hospital. Districts with low coverage of SBA and located far away from the regional referral centre had high maternal mortality. Education of the mother, occupation of the husband, pregnancy-related complications, use of antenatal care, parity, and distance to the nearest hospital and health centre were associated with the use of SBA. The coverage of SBA in the Sidama Region was low, with high variations in the districts. Low SBA use was associated with high maternal mortality. Due attention should be given to districts with low coverage of SBA and those located far away from the referral centre. Access to hospitals has to improve. All women should be encouraged to get antenatal care services.

A stratified modified probability proportional to size sampling technique

In Probability Proportional to Size (PPS) sampling, size variable associated with the sampling unit leads to the probability selection of units proportional to its size. In the literature, modification to PPS has been proposed by dividing the population in two groups on arranging the units in decreasing order of their frequency. We introduce Stratified Modified Probability Proportional to Size with Replacement (Stratified MPPSWR) sampling and Stratified Modified Rao-Hartley-Cochran (Stratified MRHC) design in case of without replacement sampling where the data are distributed in homogeneous strata such that it follows Zipf’s law within each stratum and the units are selected using MPPSWR and MRHC design respectively. In proposed schemes, each stratum is divided into two groups and first group is selected into the sample with probability 1 and units from second group are selected using PPSWR and RHC sampling respectively as in MPPSWR and MRHC sampling design. The relative efficiency of the proposed schemes is carried out and an illustration is given using the real data set. The proposed sampling schemes are seen to be more efficient than existing techniques.

Factors Affecting Online Purchase Intention on Social Media Users During the Pandemic in Jakarta

This study analyzes the factors influencing online purchase intention among social media users in Jakarta during the Covid-19 pandemic. In the literature, many variables can be used to explain the phenomenon of online purchases. However, this research is limited to the main variables such as social media marketing, customer trust, e-Word of mouth, brand image, and online customer reviews. The data collection method was carried out through a questionnaire with a purposive sampling technique via a google form, which was distributed using social media networks, namely WhatsApp group and Facebook, which are popular platforms in the country. The relationship of each independent variable to the dependent variable was tested using the structural equation modeling (SEM) technique using Smart PLS version 3. A total of 238 sample units spread across the DKI Jakarta area were successfully collected and processed. The results of the data analysis show that of the five hypotheses proposed, only one is significant, namely, online customer reviews have a significant relationship to online purchase intention during the Covid-19 pandemic in DKI Jakarta.

Eruca Vesicaria (Arugula) Extract: Possible Acaricidal Effect Against Red Palm Mite

Purpose: Therefore, this study aimed to use the crude extract of Eruca vesicaria (arugula) leaves in the management of Raoiella indica. Theoretical reference: The red palm mite is an invasive species and is considered a pest of great importance for coconut and banana trees and other plants in the Arecaceae family. Therefore, this study aimed to use the crude extract of Eruca vesicaria (arugula) leaves in the management of Raoiella indica. Method: For this, fine powder from arugula leaves was used diluted in water and Tween® adhesive spreader, in concentrations of 1.0; 1.58; 2.51; 3.98; 6.31, and 10.0 %. These extracts were sprayed on 10 adult females of R. indica per sample unit, with 10 replicates for each concentration. The acaricidal effect was evaluated at different time intervals after spraying: 12, 24, 36, 48, 60, and 72 hours. Results and conclusion: The results demonstrate that mortality of the R. indica mite increases as the concentration of arugula vegetable extract increases, with lethal concentrations above 3.98 % being indicated for control. Research implications: The aqueous arugula extract, in its different concentrations, demonstrated acaricidal efficacy against the red palm mite under laboratory conditions. Originality/value: This text adds value to fields of study such as alternative insect control in crops and sustainability, proposing a change in the ecologically responsible behavior of farmers.

Deriving a zero-truncated modelling methodology to analyse capture–recapture data from self-reported social networks

Capture–recapture (CRC) is widely used to estimate the size (N) of hidden human populations (e.g., the homeless) from the overlap of sample units between two or more repeated samples or lists (a.k.a., capture occasions). There is growing interest in deriving CRC data from social-network data. The current paper hence explored if self-reported social networks (lists of social ties) submitted by participants from the target population could function as distinct capture occasions. We particularly considered the application of zero-truncated count distribution modelling to this type of data. A case study and follow-up simulation study focused on two methodological issues: (1) that a participant cannot be named in their own self-reported social network and hence cannot be named as many times as non-participants; and (2) positive dependence between being a participant and being named by (a social tie of) other participants. Regarding the latter, a further motivation of the simulation study was to consider the impact of using respondent-driven sampling to select participants, because all non-seed RDS participants are recruited as a social tie of another participant. Exponential random graph modelling was used to generate the simulation study’s target populations. Early comparison was also made to estimates of N from Successive Sampling.

Differences in SARS-COV-2 seroprevalence in the population of Cusco, Peru

BackgroundThe spread of the coronavirus disease 2019 (COVID-19) in Peru has been reported at the regional level, few studies have evaluated its spread at the provincial level, in which the mechanisms could be different. MethodsWe conducted an analytical, cross-sectional, multistage observational population study to assess the seroprevalence of SARS-COV-2 at the provincial and urban/rural levels in a high-altitude setting. The sampling unit was the household, including a randomly selected family member. Sampling was performed using a data collection sheet on clinical and epidemiological variables. Chemiluminescence tests were used to detect total anti-SARS-COV-2 antibodies (IgG and IgM simultaneously). The percentages were adjusted to the sampling design. ResultsThe overall prevalence in the region of Cusco was 25.9%, with considerably different prevalence between the 13 provinces (from 15.9% in Acomayo to 40.1% in Canchis) and between rural (21.1%) and urban (31.7%) areas. In multivariable model, living in a rural area was a protective factor (adjusted prevalence ratio [aPR], 0.68; 95% confidence interval [CI], 0.61–0.76). ConclusionsGeographic diversity and population density determine different prevalence rates, typically lower in rural areas, possibly due to natural social distancing or limited interaction with people at risk.

Financial Literacy for Personal Financial Matters: A Study of Indian Army Officers

The basic as well as desirable needs of a person for decent survival in today’s materialistic and globalised world demand corresponding financial resources in hand. Irrespective of the profession and societal strata, individuals have their own financial aspirations and challenges. Financial literacy enables a person with understanding of financial terms and concepts besides imbibing skills, consciousness, talent and attitude to take important financial decisions. Military service having peculiar service conditions and limited exposure to financial field further makes it imperative to study the subject for inclusivity as very few studies have looked into financial issues pertaining to military personnel. The main aim of this research paper is to ascertain financial literacy of Commissioned Officers of Indian Army. For the study, 133 serving Commissioned Officers of Indian Army of varying age and length of service constituted the sample. Non-Probability technique of selecting sample has been used for the study wherein Purposive sampling is used to draw responses from the sample units. A structured questionnaire was developed to collect Primary data from serving Commissioned Officers of Indian Army. Detailed analysis has been carried out for the collected data using various tools and techniques in Microsoft Excel and SPSS. The study has brought out that financial literacy levels of serving commissioned officers of Indian Army are high. Though the demographic variables and financial literacy levels of Indian Army officers are not statistically associated, however overall high levels of financial literacy indicate their maturity of thought and quest for learning. Overall, the study outcomes indicate a healthy state for the organization and the Nation in terms of financial literacy of serving Commissioned Officers of Indian Army with respect to personal financial planning.

Diversity Of Insect Pests And Natural Enemies In Green Bean (Vigna Radiata) Plantations In Lakekun Village, Kobalima District, East Malaka

This research was conducted in Lakekun Village, Kobalima District, Malaka Regency from May to July 2023, aiming to determine the types of insect pests and natural enemies in mung beans. Data collection was carried out using direct observation techniques on mung bean plants and sampling using several traps. The types of traps used were pitfall trap, swepnet, yellow sticky trap, swing net and light trap. Sampling was done diagonally to determine the sample unit. The number of observation plots in the field is 3 observation plots. in 1 plot there are 5 sample units and a total of 3 observation plots there are 15 aub plots observed. Insect pests found on mung bean in the research location have three roles, namely as pests, predators and parasitoids. Species that act as pests consist of Artherigona exigua, Nezara viridula L, Aphis craccivora, Halyomopha halys, Riptortus linearis, Adoretus sp. and Gralliclava horrens. Insects that act as predators consist of Menochilus sexmaculatus, Coccinella transversalis, Orthhetrum sabina, Iscunara senegalensis. While insects that act as parasitoids are Tiphia femorata. The highest population found at the research site was Aphis craccivora which amounted to 315 individuals and the lowest population was Graliclava horrens with a total of 7 individuals. The value of the diversity index in mung bean plants is classified as moderate, namely 1.89.
 Keywords: diversity, insects, mung bean, identification.

Role of applying PCMs on thermal behavior of innovative unit roof enclosure

As a technical approach, using Phase Change Materials (PCM) can be an effective method to prevent energy losses through building enclosures. In the present paper, different roof structures containing PCM have been examined to analyze their thermal behavior. The governing equations were developed and solved for a sample unit extracted from a typical roof. The control volume based finite element method has been applied for solving coupled equations governing heat transfer through the roof and flow of melted PCM. The effect of key parameters including thermal diffusivity of the PCM and the wall, Prandtl number (Pr), Rayleigh number (Ra) and solid wall thickness to total thickness has been examined. The main results indicate an enhancement of heat transfer through the increase of the thermal diffusivity of the PCM with respect to the building material. Increasing the thermal diffusivity ratio from 1 to 25 doubles the heat transfer rate and decreases the full melting time by 80% for high Rayleigh. Pr affects the mode of heat transfer but has little impact on PCM melting rate. Raising Ra improves heat transfer under the condition of high thermal diffusivity in the PCM. Increasing Rayleigh number from 104 to 106 doubles the heat transfer rate and reduces the melting by 67% for high thermal diffusivity ratio. Finally, increasing the size of the wall thickness does not affect the fraction of melted PCM but reduces the heat transfer rate. The heat transfer rate can be increased by up to 75% when the non-dimensional thickness of the solid layer is reduced from 0.5 to 0.005.

The role of strategic intelligence for leadership in developing proactive work behaviours amongst universities' employees

PurposeThis paper aims to bring these areas closer by exploring the relationship between the dimensions of strategic intelligence (SI) for leadership and the proactive work behaviours (PWBs) of Upper Egypt universities' employees. Therefore, the research question revolves around: is there a relationship between SI and PWB?Design/methodology/approachThe study relied on a descriptive analytical approach and a stratified random sample. The paper opts for a descriptive study using the survey lists that depends on three scales: strategic leadership intelligence. The sampling unit is represented by the individuals working in Upper Egypt Universities, distributed on a sample of 364 Upper Egypt universities' employees.FindingsThe results indicate a significant relationship between dimensions of SI for leadership and the PWBs.Originality/valueBecause of the chosen research approach, the research results may lack generalisability. Therefore, researchers are encouraged to test the proposed propositions further. This paper is the first to examine, to the authors' knowledge the relationship between intelligence for leadership and the PWBs.

The burden of dengue and force of infection among children in Kerala, India; seroprevalence estimates from Government of Kerala-WHO Dengue study

Dengue shows high geographic heterogeneity within and across endemic countries. In the context of increasing burden and predicted outbreaks due to climate change, understanding the heterogeneity will enable us to develop region specific targeted interventions, including vaccination. World Health Organisation (WHO) suggests standard methodologies to study the burden and heterogeneity at national and subnational levels. Regional studies with robust and standard methodology to capture heterogeneity are scarce. We estimated the seroprevalence of dengue in children aged 9-12 years and the force of infection in Kerala, India, from where Zika cases also have been reported recently. We conducted a school-based cross-sectional survey in 38 clusters; selected by stratified random sampling, representing rural, urban, high burden and low-burden administrative units. Validation of Indirect IgG ELISA was done by Plaque Reduction Neutralization Test (PRNT90) using the local isolates of all four serotypes. Force of infection (FOI) was estimated using the WHO-FOI calculator. We conducted a follow-up survey among a subsample of seronegative children, to estimate the rate of sero-conversion. Among 5236 children tested, 1521 were positive for anti-dengue IgG antibody. The overall seroprevalence in the state was 29% (95% CI 24.1-33.9). The validity corrected seroprevalence was 30.9% in the overall sample, 46.9% in Thiruvananthapuram, 26.9% in Kozhikkode and 24.9% in Kollam. Age-specific seroprevalence increased with age; 25.7% at 9 years, 29.5% at 10 years, 30.9% at 11 years and 33.9% at 12 years. Seroprevalence varied widely across clusters (16.1%-71.4%). The estimated force of infection was 3.3/100 person-years and the seroconversion rate was 4.8/100 person-years. 90% of children who tested positive were not aware of dengue infection. All the four serotypes were identified in PRNT and 40% of positive samples had antibodies against multiple serotypes. The study validates the WHO methodology for dengue serosurveys and confirms its feasibility in a community setting. The overall seroprevalence in the 9-12 year age group is low to moderate in Kerala; there are regional variations; high burden and low burden clusters co-exist in the same districts. The actual burden of dengue exceeds the reported numbers. Heterogeneity in prevalence, the high proportion of inapparent dengue and the hyperendemic situation suggest the need for region-specific and targeted interventions, including vaccination. World Health Organization.

Applying regional climatic indicators to study plant diversity patterns in Inner Mongolia

Climate factors have a major influence on biodiversity patterns have often used their mean values to reflect the distribution of different organisms, reducing the faceted information of the study unit to point information, a situation that may affect the accuracy of the study results. However, there has been a lack of systematic and comprehensive discussion on regional climatic indicators and their selection. To address this, we evaluated plant distribution and meteorological data from 88 banners and counties in Inner Mongolia considering five regional climatic indicators that reflect the state of climate factors, heterogeneity, and total resources in each sampling unit. Additionally, we compared and analyzed the advantages of the regional climatic indicators over mean climate indicators to determine the dominant climate factors driving the diversity patterns of plant families, genera, and species. Our results showed that the regional climatic indicators were better than the mean values at reflecting the diversity patterns of plant families and genera. In Inner Mongolia, plant species diversity patterns were mainly influenced by total precipitation and temperature heterogeneity indicators; and concurrently, the correlation between plant family and genus diversity patterns and regional climatic indicators was also higher than the mean values. The extent to which climate explains the diversity patterns of plants increases with decreasing plant taxonomic rank. The results of this study expand the available selection and use of climate indicators in biodiversity research and deepen the understanding of the effects of climate on plant family diversity patterns in arid and semi-arid regions. Therefore, this study provides new perspectives for the rational selection and accurate use of climate or environmental indicators in biodiversity conservation and restoration research.

Spatial and temporal representation of marine fish occurrences available online

Despite the 243,000 marine species described by 2022, our knowledge about the oceanic biodiversity is still incomplete. This knowledge gap carries potentially adverse and far-reaching consequences for the preservation of marine ecosystems, particularly in the context of the ongoing human-induced alterations to our biosphere and the rapid progression of climate change and global environmental shifts.Recently, however, a large number of online repositories have emerged, which catalogue, store and distribute biodiversity information, including taxonomic and species occurrence data. FishBase, the Global Biodiversity Information Facility (GBIF) and the Ocean Biodiversity Information System (OBIS) are part of these publicly available repositories representing a variety of sources that have exploded in number. However, despite the incredible accumulation of biodiversity records, not all the information is actually useful, nor does it represent any new knowledge regarding global species richness patterns.In this study, we assessed the spatial and temporal representativeness of marine fish records (order Actinopterygii) found in the GBIF and OBIS global repositories. The methodological framework that we developed relies on a series of non-parametric estimators for computing species richness from incidence data. This methodology employs hexagonal grids as sampling units that overlay marine bioregions across the globe.Using standard ecological and spatial analysis tools, we identify regions that are adequately represented in terms of available records and therefore have more reliable data, as well as regions with few records that do not represent current species richness. We overlap these results with the location of marine protected areas and fishing exploitation zones to understand the anthropogenic effect on marine ichthyofauna. We additionally evaluate hypotheses regarding the taxonomic, geographic, and temporal distribution of information biases to deepen our current understanding of public records of species occurrences worldwide.Considering that more than 40 years of information was analyzed, the results showed that, on a global scale, the primary data on marine fish available on GBIF and OBIS platforms are still far from being representative and complete. Only 1.14% of the records were useful for our analyses. In addition, we found that the information seems to be biased towards coastal areas, regions close to developed countries, and areas where there is a large fishing activity. Finally, the best represented species and families are those with a small body size, which use shallow habitats and are usually recognized as having commercial or cultural value.

Methods for combining probability and nonprobability samples under unknown overlaps

Nonprobability (convenience) samples are increasingly sought to reduce the estimation variance for one or more population variables of interest that are estimated using a randomized survey (reference) sample by increasing the effective sample size. Estimation of a population quantity derived from a convenience sample will typically result in bias since the distribution of variables of interest in the convenience sample is different from the population distribution. A recent set of approaches estimates inclusion probabilities for convenience sample units by specifying reference sample-weighted pseudo likelihoods. This paper introduces a novel approach that derives the propensity score for the observed sample as a function of inclusion probabilities for the reference and convenience samples as our main result. Our approach allows specification of a likelihood directly for the observed sample as opposed to the approximate or pseudo likelihood. We construct a Bayesian hierarchical formulation that simultaneously estimates sample propensity scores and the convenience sample inclusion probabilities. We use a Monte Carlo simulation study to compare our likelihood based results with the pseudo likelihood based approaches considered in the literature.