Average Population Density Research Articles

Using data from collective hunts to estimate the wild boar (Sus scrofa) population density in north-eastern Poland

The spread of the African swine fever through wild boar population has caused major losses in the pig industry. Therefore, to decrease the population density of wild boar in Poland, the culling of these animals has been dramatically increased. However, the effect of depopulation is unknown because there are no methods that could be used throughout the country to estimate the number of wild boar. Thus, during two hunting seasons an attempt was made to estimate the number of wild boar using data from collective hunts. The forested area of 21 hunting districts (351.5 km2) was divided into five sampling inventory blocks (SIBs), which were used for the statistical analysis of the population density, the harvest rate and results of collective hunts. The average population density obtained by a driving census amounted to 8.19 ± 1.12 and 10.09 ± 1.06 (x̅ ± SE), animals/km2, which indicates that 2879 and 3547 wild boar were living in the study area in 2012/2013 and 2013/2014 seasons respectively. The number of wild boars bagged per one hunting plot was adopted as the harvest success index (HBI). In SIBs the HBI value fluctuated in the range of 0.55 to 1.87 individuals/hunting plot and the population density ranged from 6.46 to 12.18 wild boars/km2. The non-linear regression showed a positive relationship between the HBI index and the population density. The discussion covers the possibility of using collective hunts to estimate the number of wild boar in Poland and in the European Union.

Oscillations and Pattern Formation in a Slow-Fast Prey-Predator System.

We consider the properties of a slow-fast prey-predator system in time and space. We first argue that the simplicity of the prey-predator system is apparent rather than real and there are still many of its hidden properties that have been poorly studied or overlooked altogether. We further focus on the case where, in the slow-fast system, the prey growth is affected by a weak Allee effect. We first consider this system in the non-spatial case and make its comprehensive study using a variety of mathematical techniques. In particular, we show that the interplay between the Allee effect and the existence of multiple timescales may lead to a regime shift where small-amplitude oscillations in the population abundances abruptly change to large-amplitude oscillations. We then consider the spatially explicit slow-fast prey-predator system and reveal the effect of different timescales on the pattern formation. We show that a decrease in the timescale ratio may lead to another regime shift where the spatiotemporal pattern becomes spatially correlated, leading to large-amplitude oscillations in spatially average population densities and potential species extinction.

Evaluating urban-rural access to pathology and laboratory medicine services in Tanzania.

Placement of pathology and laboratory medicine (PALM) services requires balancing efficiency (maximizing test volume) with equitable urban-rural access. We compared the association between population density (proxy for efficiency) and travel time to the closest facility (proxy for equitable access) across levels of Tanzania's public sector health system. We linked geospatial data for Tanzania from multiple sources. Data on facility locations and other geographic measures were collected from government and non-governmental databases. We classified facilities assuming increasing PALM availability by tier: (1) dispensaries, (2) health centres, (3) district hospitals and (4) regional/referral hospitals. We used the AccessMod 5 algorithm to estimate travel time to the closest facility for each tier across Tanzania with 500-m resolution. District-level average population density and travel time to the closest facility were calculated and presented using medians and interquartile ranges. Spatial correlations between these variables were estimated using the global Moran's I and bivariate Local Indicator of Spatial Autocorrelation, specifying a queen's neighbourhood matrix. Spatial analysis was restricted to 171 contiguous districts. The study included 5406 dispensaries, 675 health centres, 186 district hospitals and 37 regional/referral hospitals. District-level travel times were shortest for Tier 1 (median: [IQR]: 45.4 min [30.0-74.7]) and longest for Tier 4 facilities (160.2 min [107.3-260.0]). There was a weak spatial autocorrelation across tiers (Tier 1: -0.289, Tier 2: -0.292, Tier 3: -0.271 and Tier 4: -0.258) and few districts were classified as significant spatial outliers. Across tiers, geographic patterns of populated districts surrounded by neighbours with short travel time and sparsely populated districts surrounded by neighbours with long travel time were observed. Similar spatial correlation measures across health system levels suggest that Tanzania's health system reflects equitable urban-rural access to different PALM services. Longer travel times to hospital-based care could be ameliorated by shifting specialized diagnostics to more accessible lower tiers.

Spatial distribution and community analysis of plant-parasitic nematodes associated with rice (Oryza sativa L.) in Benue State, Nigeria

Plant-parasitic nematodes (PPNs), also known as phyto-parasitic or plant-destructive nematodes are microscopic, translucent, bilaterally symmetrical, pseudocoelomic, multicellular worm-like organisms which feed on plant root mostly, and seldom on other vegetative parts. Although these PPNs have been reported to constitute threat to rice production, documentation of their spatial distribution and densities in major rice-producing areas of Benue state, Nigeria is absent. Using multi-stage sampling procedure, surveillance for PPNs, their densities and community analyses were conducted in six major rice-producing local government areas (LGAs) of Benue. The LGAs included Agatu, Apa, Gwer West, Guma, Kwande and Makurdi LGAs and a total of 108 samples were collected comprising 54 soil and 54 root samples. Nine plant-parasitic nematode genera which included Criconemoides, Tylenchorhynchus, Trichodorus, Hirschmanniella, Xiphinema, Helicotylenchus, Scutellonema, Pratylenchus and Meloidogyne were recovered. In order of ranking, Meloidogyne sp., P. zeae and H. oryzeae had the highest population densities across all LGAs included in the study. The highest density of PPN was recorded in Kwande (ca. 133 PPNs/10mL of nematode suspension) while lowest population density was recorded in Makurdi (ca. 77 PPNs/10mL of suspension). Although Meloidogyne sp. recorded the highest average population density in all LGA except in Gwer West LGA where H. oryzae recorded the highest average population density of approximately 13 PPNs/10mL of suspension. Community analysis also revealed that Meloidogyne sp. was the most spatially distributed PPN closely followed by P. zeae and H. oryzae with prominence values of 37.78, 21.84 and 20.91, respectively. However, in the soil, the highest prominence value was recorded in H. oryzae making it the most spatially distributed PPN in the soil.

Population density, genetic diversity and hot spots of Commiphora wightii (Arnott) Bhandari in Rajasthan State

Commiphora wightii (Arnott) Bhandari also known as ‘Guggal’, is a critically endangered medicinal plant species. Natural population of this species is declining due to poor regeneration, over-exploitation and destructive harvesting methods. In present study extensive surveys were conducted in all the guggal occurring forest areas of Rajasthan state with the objectives to study the population density, genetic diversity and its relationship with geographical patterns, distances and agroclimatic zones. Average population density of guggal was 21.9 plants ha−1 in guggal occurrence areas of forests in Rajasthan. The highest density (105.9 plants ha−1) was recorded in Sawai Madhopur and lowest (1.6 plants ha−1) in Jhalawar district. Variation in guggal population density was also observed due to altitude differences. The maximum density (40 plants ha−1) was recorded in altitude range from 301−350 m AMSL mainly in Aravalli range and it reduces at higher (>350 m AMSL) and lower (<301 m AMSL) altitudes.Genetic diversity was studied with 96 genotypes collected from all over Rajasthan using selected six RAPD primers. The genetic distances among these genotypes ranged from 0.000 to 0.732. Statistical analysis indicated low genetic diversity (H = 0.195; I = 0.299), low genetic differentiation (GST = 0.169) and moderate gene flow (Nm = 2.455) between four agroclimatic zone populations. These results indicate that these populations are in process of genetic drift and genetic differentiation. The Mantel test showed statistically significant correlation (R = 0.306; p = 0.000) between pairwise geographical distance and genetic distance.

Exploring the complex origins of energy poverty in The Netherlands with machine learning

Energy poverty is receiving increased attention in developed countries like the Netherlands. Although it only affects a relatively small share of the population, it constitutes a stern challenge that is hard to quantify and monitor, hence difficult to effectively tackle through adequate policy measures. In this paper we introduce a framework to categorize energy poverty risk based on income and energy expenditure. We propose the use of a machine learning classifier to predict energy poverty risk from a broad set of socio-economic parameters: house value, ownership and age, household size, and average population density. While income remains the single most important predictor, we find that the inclusion of these additional socio-economic features is indispensable in order to achieve high prediction reliability. This result forms an indication of the complex nature of the mechanisms underlying energy poverty. Our findings are valid at different geographical scales, i.e. both for single households and for entire neighborhoods. Extensive sensitivity analysis shows that our results are independent of the precise position of risk category boundaries. The outcomes of our study indicate that machine learning could be used as an effective means to monitor energy poverty, and assist the design and implementation of appropriate policy measures.

Socio-economic predictors of public understanding of the COVID-19 pandemic

The COVID-19 (Coronavirus 2019) pandemic has proven to be the biggest global shock since World War II. That war resulted in 5.5 million deaths. The number of COVID-19-infected persons exceeded 13 million in the first 6 months of the pandemic and many more asymptomatic cases are undocumented. The global economy has been affected severely. The tension, the fear, the drastic measures to try to control the spread of the disease disrupted everyone's life from child to senior. The condition is worse in the global south, such as in Bangladesh, where the average population density is 7.5 times higher than that of China, where COVID-19 began and spread uncontrollably at the end of 2019. Lockdowns and social distancing were tried to stop the transmission of the disease but were often not observed faithfully or were less effective than thought to be. People need to trade and interact to earn money to survive but these activities could endanger others' lives if they do not maintain safety measures. Individual awareness is not only curtailing the spread of COVID-19 but also saves others' lives. This cross-sectional study used Ordinal and Binary logit models to predict the level of awareness through potential regressors of the citizen toward COVID-19 in Bangladesh. Findings of the study are that the level of awareness is dependent on the level of trauma; also, that household income is a statistically-significant predictor of awareness. Behavioral activities such as use of masks, outdoor activities, and stockpiling tendencies are found to be statistically significant predictors of awareness as well.

Increasing Urban Heat Island area in Jakarta and it’s relation to land use changes

Urban Heat Island (UHI) is a phenomenon that occurs in almost all metropolitan cities in the world. The UHI phenomenon also occurs in Jakarta, the capital city of Indonesia, a metropolitan city with an area of 662 km2, 12 million inhabitants, and an average population density of 16,000 per km2. Previous research shows the area of UHI, areas with temperatures> 300, in Jakarta in 1989 reached 84.53 km2 or 0.1 % of the total area. Based on these facts, the aim of this study is to identify changes in the area of UHI areas from 2008 to 2018 and their relation to land use changes. Temperature data used in this study are from Landsat satellite images in 2008, 2013 and 2018, while the land use data used are from National Geospatial Information Agency. Similar to the previous research, the operational definition of UHI used in this study is that UHI is the area with surface temperature > 300. The method used is spatial analysis and comparison method. The results showed that the area of UHI in Jakarta had increased. The areas of UHI Jakarta were 36.5%, 84.7%, and 85.2% of the total areas respectively in 2008, 2013 and 2018. The increases of UHI’s area were in line with the increases of the built areas that respectively 79.2%, 82.9% and 85.2%. Land use for housing, commercial and services, industry and warehousing and transportation facilities seem to be more significantly affecting the increases of UHI area rather other land uses.

Filtration Regimes Calculation of Hydraulic Structures of Alma Reservoir

In the article the Crimean Peninsula is exposed as one of the most problematic areas for providing water resources in the Russian Federation. By 2013, the filling of drinking-water reservoirs due to river runoff and precipitation was at the level of 20-25% of the total design volume and it was the lowest indicator for the last 25 years. In 2014, after the reunification of Crimea with Russia, new hydraulic structures began functioning to supply water to Crimean residents, which allowed filling the North Crimean Canal with water from the Belogorsky and Taigan reservoirs along the Biyuk-Karasu riverbed and eastern Crimea residents began to receive water. The average population density of Crimea is 85 people / km2. The average long-term value of water resources for this territory is 1.0 km3 / year, and one resident - 432 m3 / year, which is the lowest of all the constituent entities of the Russian Federation. Much attention is paid to the safety of operating reservoirs, including the oldest one in Crimea - Alminsky reservoir. The calculations are given and filtration strength of the dam body soils of reservoir is estimated: specific filtration flow rates, filtration flow outlet velocity and effective pressure gradients. Calculation of the filtration regimes of the dam construction was carried out for two loading cases: main and special load combination. The obtained data indicates that actual parameters of the dam construction provide filtration strength and structure reliability under the accepted loading cases.

Expansion of a native species and its impacts on alpine ecosystems, Indian Himalaya

In recent years, a number of studies have reported invasion by alien species, however, global studies on invasion or expansion of native species are still limited, and such studies are completely lacking from the Himalayan region. The study aims to find the direction of correlation between the expansion of a native species (Polygonum polystachyum Wall. ex Meisn.) and plant species richness in the alpine ecosystem of Indian Himalaya. We have carried out vegetation sampling in selected invaded and un-invaded areas along an elevation gradient (3000–4100 m a. s. l.) over a period of four years. Three different sites i.e., Valley of Flower National Park (VoFNP), Lata-Khark and Hemkund Sahib Trek in Nanda Devi Biosphere Reserve (NDBR) were selected for the study. The range of plant diversity was analysed to be 1.2–2.1 in invaded plots, and 2.4–3.7 in un-invaded plots/sites. Average population density of P. polystachyum varied significantly (p < 0.001) between invaded and un-invaded sites, and ranges from 11.1–67.1 individual / meter2 in invaded sites and 0.0–3.8 ind / m2 in un-invaded sites. The result of mixed effects model revealed significant decrease (p < 0.01) in species richness and increase in density and abundance (p < 0.01) of P. polystachyum in the invaded sites during 2015–2018, which imparts negative impacts on plant diversity, particularly on high value threatened medicinal plants.

Responses of Local Wheat Varieties to Greenbug Schizaphus graminum and Bird-Cherry Oat Aphid Rhopalosiphum padi Infestation

Field and laboratory studies were conducted to assess the sensitivity of 12 varieties of local wheat varieties (IPA-95, IPA-99, Abu-Ghreib, Babel-113, Bhooth-10, Bhooth-22, and Bhooth-158, Baraka, Tammuz, Fatih, Latifia and Rasheed) against infestation by Greenbug Shizaphis graminum and Bird-Cherry Oat Aphid Rhopalosihum padi in the province of Basrah. The field trial was carried out in Al-Nashwa district, county of Shatt Al-Arab, during the growing season 2019/2020. The first infestation of R. padi appeared on 9/1/2020, and reached the peak of population density on 30/1/2020, while the first appearance of S. graminum was on 17/1/2020; it reached its peak on 13/2/2020. The results of responses of local wheat varieties to the infestation of Greenbug showed that the highest average population density of greenbug was on Bhooth-158, Abu-Ghraib, Bhooth-22, and Babel-113 reaching 51.59, 17.84, 16.41, and 16.63 aphids/plant, respectively. Whereas the lowest population densities were at Fatih, Tammuz, Bhooth-10, Rasheed, and IPA-99, with averages of 8.28, 8.09, 8.87, 7.19, and 7.62 aphids.plant-1, respectively. The highest density rate of R. padi was recorded on the cultivars IPA-95 and Abu-Ghraib, with an average of 139.83 and 169.31 aphids.plant-1 respectively, while the verities Bhooth-22, Bhooth-158, and IPA-99 recorded the lowest population density rate (89.03, 99.41, and 100.25 aphids.plant-1) compared to the other varieties. The results of the chemical analysis determined the proportions of some metabolites of the local wheat varieties and their relationship to the infestation of Greenbug and showed that phenols have an effective role by reducing the population density of aphids. The verities Rasheed and IPA-99 which recorded low population rates of the aphids have the highest rates of phenols at a rate of 7 and 6.78 mg.100g-1 dry weight Also, varieties Abu-Ghraib, IPA-99, and Rasheed cultivars recorded the highest productivity rates (weight of thousand grains), with an average of 33.47, 43, and 67.42 g, respectively.

Evaluating social vulnerability of people inhabiting a tropical coast in Kerala, south west coast of India

Coastal Social Vulnerability Index (CSoVI) studies have drawn considerable attention in recent years due to its significance in identifying the spatial variation of socially vulnerable people inhabiting the coast. CSoVI provides a comparative spatial assessment of human capacity to respond to coastal hazards. The present study is an attempt to compute CSoVI for the coast of Thiruvananthapuram, which is densely populated and beset with several problems. This coast stretches for 75 km covering nine panchayats and two urban centers with an average population density of 3119 persons/km2. CSoVI has been defined in this study in terms of eleven quantifiable variables, comprising four demographic, three economic, and four infrastructural variables. Social Vulnerability Index (CSoVI) of each coastal panchayats has been computed after adding the factor scores of extracted four PCs placed in an additive model after adjusting their cardinality on social vulnerability. The study reveals that about 25% (19 km) of the coastline in Thiruvananthapuram is high socially vulnerable. Medium Social Vulnerability is found in three local bodies of the coast and covered 55% (41 km) of the coastline. Low Social Vulnerability is observed for about 20% (15 km) of the coastline. It is expected the findings of this study will be useful for the concerned departments, Trivandrum Corporation, and coastal panchayats of Thiruvananthapuram district in framing out various strategies for disaster risk reduction and resilience increase in the coast.

Geographical variations of socioeconomic status and prostate cancer mortality in Taiwan

A population-wide study was conducted to determine the association between area-level socioeconomic status and prostate cancer mortality in Taiwan. Age-period-cohort analysis was performed to adjust the time-trend variation. The area-level socioeconomic factors included proportion with a higher education, average income tax, population density, and clinical workload. After adjustment for time-trend variations in age, period, and cohort, prostate cancer mortality was significantly lower in the groups with the highest higher education proportion (rate ratio 0.88; 95% Confidence Intervals 0.83-0.93), average income tax (RR 0.90; 95% CIs 0.86-0.94), and population density (RR 0.88; 95% CI 0.83-0.93). When all variables were incorporated into one model, the rate ratio of prostate cancer mortality was 0.92 (95% CIs 0.88-0.97) in the region with the highest average income tax level compared with that with the lowest level, but differences in the other socioeconomic factors were not significant. This study revealed a significantly lower prostate cancer mortality rate in areas with a high higher education proportion, average income tax level, and population density compared with areas of low socioeconomic status in Taiwan.

Assessment of the ecological stability of the landscapes of the Pavlodar region

There are presented main results of the assessment of the ecological stability of the landscapes of the Pavlodar region, performed by GIS. The assessment of the ecological stability of the study region was carried out using a series of indicators: the area of water resources, the area of specially protected natural territories, the average NDVI value, the area of buildings, the average population density, the length of transport routes, the area of arable land, as well as the area of man-made territories that have an impact on the natural environment, both positive and negative. There has been compiled map of the ecological stability of the landscapes of the study region.

Weather Variability, Socioeconomic Factors, and Pneumonia in Children Under Five-Years Old - Bangladesh, 2012-2016.

What is already known on this topic?Different socioecological factors were associated with childhood pneumonia in Bangladesh. However, previous studies did not assess spatial patterns, and socioecological factors and spatial variation have the potential to improve the accuracy and predictive ability of existing models.What is added by this report?The spatial random effects were present at the district level and were heterogeneous. Average temperature, temperature variation, and population density may influence the spatial pattern of childhood pneumonia in Bangladesh.What are the implications for public health practice?The study results will help policymakers and health managers to identify the vulnerable districts, plan further investigations, help to improve proper resource allocation, and improve health interventions.

Features of the population settlement system in the regions of the China – Mongolia – Russia economic corridor

The article presents an analysis of the existing objective conditions and patterns of population distribution on the territory of the China – Mongolia – Russia economic corridor. The study area covers the Inner Mongolia Autonomous Region of China (Inner Mongolia), the central aimags of Mongolia and the Baikal region (Russia). The settlement system of adjacent regions is highly differentiated in terms of natural and geographical conditions, the level of production development, socioeconomic development, and the state of infrastructure. The average population density of the study area is 10.1 people per km2: there are relatively low indicators in the Baikal region, 2.8 people per km2; 4.2 people per km2 are in the central regions of Mongolia, and 21.2 people per km2 are in Inner Mongolia. The highest population density is observed in areas where highways and railways pass. During the period under review (from 2000 to 2018), the indices of population change in adjacent regions amounted to 93.7% in Russia, 129.0% in Mongolia and 106.7% in China. In the study regions, the population lives mainly in cities and large settlements. In the Baikal region, the level of urbanization is 68.6%, in Mongolia – 67.8% and in Inner Mongolia – 62.7%. The growth of cities is mainly due to internal migration, especially in the Russian and Mongolian territories; the process of depopulation of the countryside is taking place.

Enhancing the Documentation Process of Traffic Accidents Registry in Gaza City Using GIS

aza City is the largest city in the Gaza Strip and the Palestinian territories. The city has a population about 700,000 inhabitants with an average population density of 12600 person/km2. Documentation procedure of traffic accidents in the city is traditional and inefficient. It is not only based on paper formatting but also is not performed in the correct way since it misses the determination of exact position of occurrence of these accidents. Furthermore, documentation data do not involve appropriate level of details and need to be re-organized. This study aims to enhance the documentation process of the traffic accidents in Gaza City using GIS as well as developing appropriate recommendations that can raise the level of traffic safety in it. To enhance the documentation, a new mobile and desktop applications based on GIS Cloud are developed in order to automatically store spatial and descriptive data about traffic accidents in a computerized geodatabase. Many analysis using GIS of the accidents statistics of 2019 are performed. Results indicate that the hot neighborhood in the city is Northern Remal, the hot road is Salah Al-Din Str., the hot period is 12 – 14 O'clock, most accidents are caused by cars, and medium injuries are the dominant of these accidents. The study recommends to build a digital geodatabase that involves all necessary data associated with traffic accidents because it is the basis for planning, analyzing and making decisions. It is also recommended to establish a GIS department in Ministry of Transportation. There is a strong need to legislate binding laws to prevent the increase in the number of traffic accidents in addition to make field actions such as the necessity to set up traffic lights as much as possible near health centers, schools and other public places.

The role of brain size on mammalian population densities.

The local abundance or population density of different organisms often varies widely. Understanding what determines this variation is an important, but not yet fully resolved question in ecology. Differences in population density are partly driven by variation in body size and diet among organisms. Here we propose that the size of an organism' brain could be an additional, overlooked, driver of mammalian population densities. We explore two possible contrasting mechanisms by which brain size, measured by its mass, could affect population density. First, because of the energetic demands of larger brains and their influence on life history, we predict mammals with larger relative brain masses would occur at lower population densities. Alternatively, larger brains are generally associated with a greater ability to exploit new resources, which would provide a competitive advantage leading to higher population densities among large-brained mammals. We tested these predictions using phylogenetic path analysis, modelling hypothesized direct and indirect relationships between diet, body mass, brain mass and population density for 656 non-volant terrestrial mammalian species. We analysed all data together and separately for marsupials and the four taxonomic orders with most species in the dataset (Carnivora, Cetartiodactyla, Primates, Rodentia). For all species combined, a single model was supported showing lower population density associated with larger brains, larger bodies and more specialized diets. The negative effect of brain mass was also supported for separate analyses in Primates and Carnivora. In other groups (Rodentia, Cetartiodactyla and marsupials) the relationship was less clear: supported models included a direct link from brain mass to population density but 95% confidence intervals of the path coefficients overlapped zero. Results support our hypothesis that brain mass can explain variation in species' average population density, with large-brained species having greater area requirements, although the relationship may vary across taxonomic groups. Future research is needed to clarify whether the role of brain mass on population density varies as a function of environmental (e.g. environmental stability) and biotic conditions (e.g. level of competition).

Covid-19 Thrives in Larger Cities, Not Denser Ones

The findings introduced in this longitudinal study of cumulative Covid-19 cases and deaths are based on reported data for 384 US Metropolitan Statistical Areas (MSAs) for 20 weeks, starting on March 6, 2020 and ending on July 23, 2020. We look at the variation in the 7-day averages of the cumulative numbers of reported cases and deaths in each city at the end of every week as a function of its total population, its ‘urbanized area,’ and its average population density (the ratio of its population and its urbanized area). We find that during the last 10 weeks, the numbers have tended to converge: (1) a city with double the population of a smaller one can be expected to have 17 percent more cases per capita and 28 percent more deaths per capita than the smaller city; (2) a city with double the urbanized area of a smaller one can be expected to have 19 percent more cases per capita and 38 percent more deaths per capita than the smaller city; and, finally, (3) a city with double the population density of a smaller one can be expected to have 4.1 percent fewer cases per capita and 7.4 percent fewer deaths per capita than the smaller city. Larger cities have more than their share of cases and deaths in part because the larger the city, the larger the number of possible interactions among its inhabitants. And it is this larger number, rather than the overall average proximity of people to each other — expressed by the average density in the city — that accounts for that larger share. In fact, when it pertains to Covid-19 cases and deaths, denser metropolitan areas appear to be better able to contain their numbers than more spread out ones.

B’laan Population Structure and School Indicators: Basis for School Planning

Aims: The aim of this study was to determine the B’laan population structure and school indicators of Matanao II District as basis for school planning.&#x0D; Study Design: Descriptive survey design.&#x0D; Place and Duration of Study: Matanao, Davao del Sur during the School Year 2017-2018.&#x0D; Methodology: The respondents of the study were the fifty (50) Grade Six B’laan pupils, twenty-one and (21) school administrators of Matanao II District. Universal sampling method using the complete enumeration technique was utilized where respondents of the survey were school administrators and barangay personnel. However, cluster sampling was used in selecting the Grade Six pupils among elementary schools in Matanao District.Three sets of survey instruments were used to gather the relevant information. Data gathered were treated using the frequency and relative frequency.&#x0D; Results: Majority of the Grade Six B’laan pupils were in the age of 12 years old and above, female, and believers of Christ to the Orient. Most of them did not have siblings studying in college. Their parents were in the elementary level, earning a monthly income of ₱1,001.00 to ₱3,000.00, and had 1 to 6 children. The common household appliances they had were television set, cellular phone, radio, electric fan, DVD player and motorcycle. The mode of transportation from home to school was mostly through walking. Majority of them did not spend any amount for their transportation, food and daily allowance. As to the profile and structure of the elementary schools, most schools in Matanao II District had a total land area of 2.0 to 2.9 hectares occupied by 4 to 6 buildings having 5 to 8 classrooms. Schools offered complete elementary education with 5 to 8 teachers handling the classes of 100 to 200 B’laan pupils. The number of B’laan pupils graduated from the schools per year was within the range of 10 to 60 pupils. Moreover, the National Achievement Test results showed that schools had an average MPS of 81-85. From the map generated, the researcher found that the average population density of B’laan were 2.07 with barangay Manga, Lagaan and Bangkal as that the top 3 barangays having the largest density of B’laan population.