Future Population Growth Research Articles

PENERAPAN METODE RUNGE KUTTA FEHLBERG PADA PERSAMAAN LOGISTIK DALAM MEMPREDIKSI PERTUMBUHAN PENDUDUK DI SULBAR

This research discusses the application of the Runge Kutta Fehlberg method in predicting population growth in West Sulawesi through the logistic equation. Employing applied research methodology, the study seeks to forecast future population trends in the West Sulawesi province. Utilizing a step size of h = 0.01 and a growth rate of m = 0.0198, the Runge-Kutta Fehlberg method (RKF 45) was applied, starting from an initial population value of P (t0) = 1.419.229 individuals, resulting in a projected population of P (t10) = 1.506.142 individuals. These findings demonstrate the applicability of the Runge-Kutta Fehlberg (RKF 45) method in predicting population dynamics in West Sulawesi Province.

Hotspots of wetland loss to impervious surfaces in the conterminous United States

In this study, a first wall-to-wall comparison between the National Wetlands Inventory (NWI) and the National Land Cover Database (NLCD) was conducted across the entire conterminous United States (CONUS) to evaluate U.S. wetland loss conditions. Annually, around 26 km2 of wetlands are lost to impervious surfaces across the CONUS. Spatially, wetland loss is not evenly distributed, with 90 % of losses occurring in only 9 % of the land area, forming hotspots around expanding urban regions such as Houston, Jacksonville, and Naples. Over the past few decades, Florida experienced the highest wetland loss (5.73 km2/year) among all states, while Houston had the most wetland loss (2.54 km2/year) among all metropolitan regions. Stepwise multiple regression models identified population growth and its associated demand for new housing as the major drivers for wetland loss. Wetland loss per population increase is the highest (>15 m2/person) in most metropolitan regions around the East Coast and Gulf of Mexico. Unfortunately, current wetland loss hotspots will likely suffer further losses in future decades due to projected population growth, with Houston, Cape Coral, and Miami metropolitan regions having the greatest projected wetland loss of 89.15 km2, 34.35 km2, and 28.20 km2, respectively. This study has identified wetland loss hotspots and their drivers across the U.S. that were not possible in previous sample-based studies. The findings are critical in wetland management and protection across the U.S.

Multi-objective models for crop rotation planning problems

CONTEXTAgriculture is a vital component of the global economy and modern societies. It has undergone significant consolidation and transformation in response to the food supply crisis, highlighting the important relationship between humans and the environment. However, concerns remain about food security, particularly with the projected population growth of over 9.5 billion by 2050. The computerization of agri-food supply chains has emerged as a significant response to these challenges. OBJECTIVE(1) Develop a multi-objective model that explores both net return and crop diversity. (2) Solve the problem using techniques that guarantee optimality. (3) Evaluate the gain in crop diversity versus the net return of the optimized configuration. METHODSThe study presents four Multi-objective Mixed-Integer Linear Programming models with integer and binary decision variables for Crop Rotation Planning Problems. The objectives are to maximize net income and increase crop diversity and land utilization. RESULTS AND CONCLUSIONSThe study exclusively employs linear programming techniques to solve the models resulting in an optimal solution. A comparative analysis with existing models in the literature, which primarily focused on maximizing net income, yielded a noteworthy result. The proposed models demonstrate an average increase of 60% in crop diversity, with net return losses of less than 5%. SIGNIFICANCEIn conclusion, this research provides valuable information for crop rotation planning and highlights the importance of agricultural farm management and precision agriculture in addressing current challenges. The innovative nature of this research is exemplified by the use of mixed-integer linear programming techniques to solve a multi-objective problem with integer and binary variables. The obtained results demonstrate increased crop diversity and minimal economic losses, which have significant implications for several areas of agricultural science, policy, and practice.

A Comparison between the Production of Edible Macroalgae Worldwide and in the Mediterranean Sea

Macroalgae are beneficial for consumers and producers due to their high productivity, their chemical composition and their efficient cultivation without additional feed. Asia dominates global macroalgae production, while European production is still marginal and mainly based on wild harvesting in the North Atlantic. The European Commission has launched initiatives to promote the sustainable production, safe consumption and innovative use of macroalgae products in European regional seas, including the Mediterranean Sea. A variety of coastal and seabed types and a wide range of environmental conditions make the Mediterranean a hotspot of marine biodiversity while providing good conditions for the cultivation of macroalgae. The aim of this paper is to compare the global macroalgae production and macroalgae production in the Mediterranean Sea, focussing on the cultivation of edible macroalgae. The paper also discusses the limitations and possibilities of macroalgae production in the region. Macroalgae production is one of the most promising sectors of the blue economy in the Mediterranean. The production of edible macroalgae suitable for human consumption has great potential, considering future population growth and related food security and health issues, as well as the additional ecosystem benefits of macroalgae production.

Combining prior and post‐release data while accounting for dispersal to improve predictions for reintroduction populations

AbstractAttempts to reintroduce species to managed areas may be compromised by dispersal into the surrounding landscape. Therefore, decisions regarding the selection and ongoing management of reintroduction areas require predicting dispersal as well as the survival and reproduction rates of the species to be reintroduced. Dispersal can potentially be measured directly by tracking animals, but this is often impractical. However, dispersal can also be inferred from re‐sighting surveys done within reintroduction areas if such data are available from multiple areas with varying connectivity to the surrounding landscape, allowing apparent survival and recruitment to be modelled as a function of connectivity metrics. Here, we show how data from 10 previous reintroductions of a New Zealand passerine, the toutouwai (Petroica longipes), were used to predict population dynamics at a predator‐controlled reintroduction area with high connectivity, and predictions then updated using post‐release data. Bayesian hierarchical modelling of the previous data produced prior distributions for productivity, adult survival and apparent juvenile survival rates that accounted for random variation among areas as well as rat density and connectivity. The modelling of apparent juvenile survival as a function of connectivity allowed it to be partitioned into estimates of survival and fidelity. Bayesian updating based on post‐release data produced posterior distributions for parameters that were consistent with the priors but much more precise. The prior data also allowed the recruitment rate estimated in the new area to be partitioned into separate estimates for productivity, juvenile survival and juvenile fidelity. Consequently, it was possible to not only estimate population growth under current management, but also predict the consequences of reducing the scale or intensity of predator control, facilitating adaptive management. The updated model could then be used to predict population growth as a function of the connectivity and predator control regime at proposed reintroduction areas while accounting for random variation among areas.

Analysis of the Availability and Gaps of Educational Facilities in Teluk Bintuni Regency Papua

Education is recognized as a human right and the main key to a nation's progress. The availability of adequate educational facilities in each region is crucial to ensure equal access to education for all citizens. However, Indonesia faces significant challenges in providing equitable educational facilities, especially considering the diverse geographical and demographic conditions between regions. Teluk Bintuni Regency in West Papua Province is one of the areas that requires special attention in improving educational access and facilities, especially because of its geographical conditions, the majority of which are islands with mountains and sea waters. This research aims to analyze the availability of educational facilities in Teluk Bintuni Regency, with a focus on the type and level of schools. Data obtained from the Education Department shows that by 2023, this district will only have 263 schools, consisting of kindergartens, elementary schools, middle schools, high schools and vocational schools. This figure is still considered insufficient and equitable, especially when compared with the population of around 60,000 people spread across 23 sub-districts. The main challenge in providing equitable educational facilities in Teluk Bintuni Regency involves diverse geographic and demographic conditions. Therefore, it is hoped that this research can provide an in-depth evaluation of the current condition of educational facilities, identify existing gaps, and formulate the need for improving educational facilities in the future based on population growth projections. It is hoped that the results of this research can provide a strong basis for policy making by the Teluk Bintuni Regency Government, especially in terms of planning and budgeting for the equitable development of educational facilities. It is also hoped that the conclusions from this research can become a reference for related agencies, such as the Education Office, Bappeda, and the Teluk Bintuni Regency DPRD, in preparing strategic plans for educational development for the next five years.

Sociodemographic Factors and Policy Implications for Improved Food Security

Ensuring food security is a pressing challenge facing East Kalimantan, and practical solutions are necessary. With the impending relocation of Indonesia's capital to this region, it's crucial to evaluate the area's food security in light of projected population growth and economic shifts. Prior to the new capital city project, it's essential to understand East Kalimantan's socio-economic factors to develop policies that strengthen food security for the future. This research uses logistic regression to analyze data from the Food Insecurity Experience Scale (FIES) module of the 2021 National Socio-Economic Survey (Susenas-BPS). The results show that 14.75% of households experience food insecurity, while 85.25% maintain food security. Factors such as education, family size, land ownership, marital status, employment, residence, and retirement security influence food security status significantly. However, age, gender, and home ownership have little impact. Notably, agricultural workers are more likely to experience food insecurity, while education and land ownership correlate with higher food security. Additionally, larger families are more vulnerable to food insecurity.

Comparative Analysis Of Water Network Demand And Development With The Availability Of Clean Water In The Regional Drinking Water Company (RDWC) Lematang Enim

This study aims to analyze the projected demand for clean water and assess the existing condition of the clean water network in relation to the projected population growth in the next 10 years; Analyze the availability of water discharge from the Lematang Enim RDWC water source in meeting those needs; Analyze the development of clean water distribution networks. This research was conducted from August to December 2023. The research location is in Gelumbang Subdistrict, Muara Enim Regency. Data were collected through interviews using questionnaires related to performance, availability, and distribution of water. The results of the study show that the water demand from projection results increases every year from 2022 to 2041; the availability of water from the Lematang River is still sufficient for drinking water needs; The water needs of Gelumbang sub-district in 2032 from the calculation results obtained domestic needs of 165,403.6 m3/day, Non-domestic needs of 419.68 m3/day, and water loss of 33,164.656 m3/day; The total demand for discharge over the next 10 years (2022-2032) to meet 413,731 SL is 198,987.936 m3/day. Thus, there is an increase in the number of customers from 2022-2032 by 113,348 so that the additional distribution network needed by the Lematang Enim RDWC to meet the discharge is 45,339.2 m3/day from 2023 to 2032, totaling 113,348 so that the additional distribution network needed by the Lematang Enim RDWC to meet the discharge is 45,339.2 m3 from 2023 to 2032.

Forecasting the ecological footprint of G20 countries in the next 30 years

The Ecological Footprint evaluates the difference between the availability of renewable resources and the extent of human consumption of these resources. Over the past few decades, historical records have shown an accelerated decline in the availability of resources. Based on national footprint and biocapacity accounts, this analysis aims to advance the forecasting of the G20 countries' ecological footprints over a 30-year time frame. We employed a time series forecasting approach implemented in Python, which included-modular regression (Prophet) and Autoregressive Integrated Moving Average (ARIMA & Auto-ARIMA) methods. We evaluated and combined the performance of these three methods. The results indicated that among the largest economies of the G20, only four countries are projected to have a positive ecological footprint balance by 2050. These countries share the common denominator of large land areas and a moderate population growth projection. However, the overall trend of the indicator suggests that it will continue to decline.

Comparison Of 6 Machine Learning Models in Estimating Population Growth

With the rapidly increasing population globally, it is essential for policymakers to be able to accurately predict or gain an idea of the forecast of population growth to be able to make effective regulations that can benefit the general public. Therefore, the development of a machine learning model to estimate future population growth is crucial. In this article, various machine learning models such as linear regression, logistic regression, decision trees, random forest, neural networks, and support vector machines are discussed and the benefits and downsides of each are considered. Factors impacting population growth are also discussed to conclude the qualities needed for a model to most suitably perform the task of population prediction. In the end, it is shown that random forest is the best model for this job as it can give a generalized pattern for its results as well as handle complex data types. This paper provides predictions and insights based on machine learning to predict future demographic trends, which can provide useful information for policymakers, researchers, and society in various fields.

Transit-oriented development (TOD) in a scattered city: applied study in Brasília, Federal District

This research aims to analyze the territorial urban strategy entitled transit-oriented development (TOD), a methodology originated in the United States, which for at least 30 years has been little discussed and applied in Brazil. Faced with the challenges imposed in the 21st century in terms of sustainability and the projection of upward population growth of Brazilian cities, DOT planning is a viable concrete alternative for the transformation of today's dispersed, distant, and disconnected (3D) cities into future compact, connected and coordinated urban complexes (3C). Thus, based on the characterization of the DOT, it has led to the conclusion that this methodology is suitable for application in Brasília, Federal District, so that mass transport planning in the city would integrate with urban planning, in a fairer and more equitable way.

Spatial and temporal changes in population distribution and population projection at county level in China

Counties in China play a pivotal role in economic and social development, acting as essential leadership hubs for large and medium-sized cities, contributing to rural revitalization, and facilitating urban-rural integration. Using ArcGIS spatial analysis, this study examines the population distribution spatial and dispersion patterns in Chinese counties based on 40 years of data from the first to the seventh national population census. Results reveal noticeable growth trends and regional disparities in county populations, with an increase in large-population counties and a decrease in small-population ones. Recent population growth concentrates in urban agglomerations, metropolitan areas, and southeastern coastal regions, while reductions occur in the northeastern and Inner Mongolia border areas. Furthermore, the study identifies “high-high” agglomerations around provincial capitals and “low-low” agglomerations in economically underdeveloped western and northeastern border regions. China’s population distribution spatial agglomeration has been increasing, with acceleration toward specific areas. The first through seventh census show rapid growth at low density, followed by growth at medium density, stable growth, and eventually negative growth. This suggests a likely slowdown and potential reversal in China’s future population growth. Additionally, an Auto Regression Integrated Moving Average (ARIMA) model is employed to forecast China’s total population, projecting a decline to 1343.68 million by 2035. The emergence of “population loss counties” in contemporary China underscores the need for a rational understanding of their development status and trends to optimize population development strategies and promote economic and social progress.

Demography and threats to population growth of Cirsium pitcheri, a threatened dune plant, in Wisconsin.

Multi-year and multi-site demographic data for rare plants allow researchers to observe threats and project population growth rates and thus long-term persistence of the species, generating knowledge, which allows for effective conservation planning. Demographic studies across more than a decade are extremely rare but allow for the effects of threats to be observed and assessed within the context of interannual environmental variation. We collected demographic data on the Threatened plant Cirsium pitcheri in two sites from 2011-2022. These sites were chosen because one exhibited the presence of non-native seed predators while the other did not, and we hypothesized that we would see declines and potentially extinction of the population threatened by predation. Over the course of our study, we observed additional threats, such as human trampling and high lake levels, which led to significant erosion, sand burial, and storm damage to plants. We find high interannual variation in vital rates and population growth rates for both populations, which mask the overall effects of predation. We observed dramatic declines in plant survivorship and population growth rates in both sites in the years with high lake levels. We conclude that high lake levels, which are expected to become more frequent with climate change, pose a significant threat to all near-shore populations of C. pitcheri.

Markov equilibrium of social security: An analytic solution under CRRA utility and the future of social security

The politico-economic sustainability of pay-as-you-go social security has been studied with the help of two-period overlapping generation models under Markovian equilibrium concepts. The literature has mostly used logarithmic utility for tractability, whereas versions under the more general isoelastic CRRA utility have only been analyzed computationally. This paper demonstrates that a prototypical social security model under CRRA utility has a closed-form solution; it revisits previously obtained computational conclusions and presents new findings and extensions. Quantitatively, the model can explain the observed path of payroll tax rates in the USA and predicts increased tax rates as the equilibrium response to lower future population growth rates. The model predicts a gradual increase in tax rates, from the current 12.4% to about 15% or so in 2060, and then staying at that level. Benefits are expected to decrease slowly, by about 2% (or less) per decade, starting in 2030.

Land cover changes and management effectiveness of protected areas in tropical coastal area of sub-Saharan Africa

Nature-based solutions to ecological challenges have continued to draw significant attention, and are connected to the increased establishment of protected areas as a means for climate and ecological crisis mitigation. This study presents an innovative approach that combines spatial and statistical analysis of land cover change and drivers to evaluate land use management and effectiveness of 22 designated protected areas (PAs) across the tropical coastal regions of sub-Saharan Africa. While the results provided insight into land use management and conservation priorities, it highlighted (1) the use of these protected areas for food production is prevalent, irrespective of its designation. Nevertheless, there is evidence of a decline in cropland in some of the protected areas, suggesting a shift in policy towards conservation land use. (2) The occurrence of forest loss suggests that conservation is weak in most of the protected areas, while wetland conservation efforts are stronger due to their land cover expansion. (3) Population density (human factor) is the most significant driver of land cover change in these protected areas, followed by elevation (natural environment), precipitation (climate), nighttime light (socio-economic), and slope (natural environment). (4) In terms of Ecosystem value, only 15 of the 22 protected areas exhibited an increase in their total ecosystem service value according to land cover change, indicating sustainable land use and measures effectiveness in these protected areas. However, based on an individual land cover assessment, most protected areas showed signs of loss, especially in forests. Given the projected population growth in Africa, a regular assessment of protected areas should be initiated to enable effective and timely management decisions. Additionally, policies to improve the management effectiveness of African protected areas through funding should be a top priority, while taking into consideration the livelihoods of the indigenous people in the area in order to find a sustainable balance.

Alien Species of Vascular Plants in the Flora of Prioksko-Terrasny Biosphere Reserve

The paper presents data on alien species of vascular plants in the Prioksko-Terrasny Biosphere Reserve. In total 96 species are classified as alien, which is 10,6% of the total floristic diversity. This proportion is small and reflects a low disturbance and relative stability of indigenous phytocenoses. The appearance of a new 43 alien species for the flora of the reserve was noted. The characteristics of the current state of populations of alien species, location and prospects for further development, are given. Almost all alien species registered by us (with the exception of Oxalis stricta, Torilis japonica, Conyza canadensis) to one degree or another are the result of introduction activities. Depending on the degree of naturalization and potential danger to the ecosystem, alien species are divided into 5 categories: Status 0 – cultivated (unnaturalized) (32 species); Status 1 – alien non-naturalizing plants (11 species); Status 2 – casual alien plants (2 species); Status 3 – naturalized plants (45 species); Status 4 – invasive species-transformers (6 species). Areas occupied by Cornus alba and Caragana arborescens have been measured to further estimate population growth by comparing with a similar measurement after several years. Extermination of small pioneer Heracleum sosnowskyi population is recommended.

Studi Kelayakan Sungai Cidanau Kabupaten Serang Banten untuk Kebutuhan Sumber Air Baku Kecamatan Padarincang

Cidanau River water is one of the important facilities for the people of Padarincang District. People use the river flow for their daily needs. Along its course there are non-densely populated settlements, where residents dump domestic waste into rivers. The purpose of this study is to analyze river water quality, the amount of raw water needs and the feasibility of the Cidanau River. The study used quantitative methods in the form of water sampling, population growth projections and river water feasibility by analyzing the water quality of the Cidanau River with the Pollution Index (IP) method. The results of the pollution index can be concluded that the Cidanau River meets quality standards based on class II criteria with the lightly polluted category because the IP results show a value of 2.84 which means 1 ≤ IP ≤ 5. Based on the results of data processing of projected population of Padarincang District in the next 10 years amounting to 103,440 people, the total clean water needs of Padarincang District are 149,618,181 m³ / day. It can be concluded that based on the water needs of the Padarincang District Population of 149,618,181 m³ / day with a discharge of 1.2269 m³ / day is said to be unfeasible because the river water discharge < water needs.

A genomic predictor for age at sexual maturity for mammalian species.

Age at sexual maturity is a key life history trait that can be used to predict population growth rates and develop life history models. In many wild animal species, the age at sexual maturity is not accurately quantified. This results in a reduced ability to accurately model demography of wild populations. Recent studies have indicated the potential for CpG density within gene promoters to be predictive of other life history traits, specifically maximum lifespan. Here, we have developed a machine learning model using gene promoter CpG density to predict the mean age at sexual maturity in mammalian species. In total, 91 genomes were used to identify 101 unique gene promoters predictive of age at sexual maturity across males and females. We found these gene promoters to be most predictive of age at sexual maturity in females (R 2 = 0.881) compared to males (R 2 = 0.758). The median absolute error rate was also found to be lower in females (0.427 years) compared to males (0.785 years). This model provides a novel method for species-level age at sexual maturity prediction without the need for long-term monitoring. This study also highlights a potential epigenetic mechanism for the onset of sexual maturity, indicating the possibility of using epigenetic biomarkers for this important life history trait.

Effects of two types of Coccomyxa sp. KJ on in vitro ruminal fermentation, methane production, and the rumen microbiota.

Coccomyxa sp. KJ is a unicellular green microalga that accumulates abundant lipids when cultured under nitrogen-deficient conditions (KJ1) and high nitrogen levels when cultured under nitrogen-sufficient conditions (KJ2). Considering the different characteristics between KJ1 and KJ2, they are expected to have different effects on rumen fermentation. This study aimed to determine the effects of KJ1 and KJ2 on in vitro ruminal fermentation, digestibility, CH4 production, and the ruminal microbiome as corn silage substrate condition. Five treatments were evaluated: substrate only (CON) and CON + 0.5% dry matter (DM) KJ1 (KJ1_L), 1.0% DM KJ1 (KJ1_H), 0.5% DM KJ2 (KJ2_L), and 1.0% DM KJ2 (KJ2_H). DM degradability-adjusted CH4 production was inhibited by 48.4 and 40.8% in KJ2_L and KJ2_H, respectively, compared with CON. The proportion of propionate was higher in the KJ1 treatments than the CON treatment and showed further increases in the KJ2 treatments. The abundances of Megasphaera, Succiniclasticum, Selenomonas, and Ruminobacter, which are related to propionate production, were higher in KJ2_H than in CON. The results suggested that the rumen microbiome was modified by the addition of 0.5-1.0% DM KJ1 and KJ2, resulting in increased propionate and reduced CH4 production. In particular, the KJ2 treatments inhibited ruminal CH4 production more than the KJ1 treatments. These findings provide important information for inhibiting ruminal CH4 emissions, which is essential for increasing animal productivity and sustaining livestock production under future population growth.

Rapid neighbourhood-scale modelling of urban heat risks for early-stage quantification of potential passive design mitigation strategy effectiveness: Copenhagen test case

This study employed the urban weather generator (UWG) to model the formation of the urban heat island (UHI) across the twelve (12) districts (bydele) of the City of Copenhagen (Københavns Kommune). In the face of projected future population growth, increased urban development, and rising global temperatures, it is necessary to quantify the ability of sustainable urban development objectives to mitigate the formation of UHIs. Assessment of baseline UHI formation in Copenhagen allowed for testing passive UHI mitigation strategies as defined in Copenhagen’s Kommuneplan 19 (KP19). The results of this study identified city districts experiencing higher baseline levels of urban heat and the effectiveness of the passive UHI mitigation strategies proposed in KP19. Additionally, results from this study suggest that UHI mitigation strategies are more effective combined.