Variation In Population Density Research Articles

FloodNet: Low‐Cost Ultrasonic Sensors for Real‐Time Measurement of Hyperlocal, Street‐Level Floods in New York City

AbstractFlooding is one of the most dangerous and costly natural hazards, and has a large impact on infrastructure, mobility, public health, and safety. Despite the disruptive impacts of flooding and predictions of increased flooding due to climate change, municipalities have little quantitative data available on the occurrence, frequency, or extent of urban floods. To address this, we have been designing, building, and deploying low‐cost, ultrasonic sensors to systematically collect data on the presence, depth, and duration of street‐level floods in New York City (NYC), through a project called FloodNet. FloodNet is a partnership between academic researchers and NYC municipal agencies, working in consultation with residents and community organizations. FloodNet sensors are designed to be compact, rugged, low‐cost, and deployed in a manner that is independent of existing power and network infrastructure. These requirements were implemented to allow deployment of a hyperlocal, city‐wide sensor network, given that urban floods often occur in a distributed manner due to local variations in land development, population density, sewer design, and topology. Thus far, 87 FloodNet sensors have been installed across the five boroughs of NYC. These sensors have recorded flood events caused by high tides, stormwater runoff, storm surge, and extreme precipitation events, illustrating the feasibility of collecting data that can be used by multiple stakeholders for flood resiliency planning and emergency response.

Inconsistent effects of environmental variations on body size and density of pillbugs, Armadillidium vulgare (Latreille, 1804) (Isopoda, Oniscidea) in urban green spaces

Inconsistent effects of environmental variations on body size and density of pillbugs, Armadillidium vulgare (Latreille, 1804) (Isopoda, Oniscidea) in urban green spaces

Chaotic mixotroph dynamics arise with nutrient loading: Implications for mixotrophy as a harmful bloom forming mechanism

Mixotrophic nutrition, in which organisms combine aspects of heterotrophic and autotrophic nutrition, is a common characteristic amongst the phytoplankton, and especially amongst harmful algae bloom (HAB) species. To explore how the addition of a mixotrophic population influences a theoretical plankton system under different enrichment levels, we employ a previously published numerical plankton model that reproduces seasonal succession dynamics. Through this work we found potential for chaos to occur as the system was enriched. Focusing on occurrence of chaos in the mixotroph population, a novel finding, we conducted a bifurcation analysis which demonstrated a period doubling route to chaos. Further, we demonstrate that the occurrence of chaotic dynamics in the model system is not an artifact of the mixotroph life-history trait values used in our initial simulations, rather chaos was found to occur under a wide range of mixotroph trait value combinations. Through our trait analysis, we also found that regardless of whether or not the system was chaotic for a specific combination of values, variation in the mixotroph population peak population density could be high between consecutive years. These findings have implications that are important for the management of nutrients in aquatic systems and HABs. Results shed light on why it may be difficult to predict the occurrence of mixotrophic HABs based solely on environmental variables, when the year-to-year peak density of the mixotroph is chaotic or highly variable with enrichment. These results also demonstrate how initiation of a mixotrophic HAB might occur with enrichment, due to erratic population spikes, when broadcast allelopathic or toxic chemicals are at low concentrations, a novel bloom initiation mechanism.

Where does money matter more?

There is much still to learn about the relationship between income and well-being, and in particular how this may depend on the economic and social context. We use Russian data to estimate individual Welfare Functions of Income, and examine two potentially context-dependent concepts: self-assessed income needs and welfare sensitivity to income (how well-being changes with income). The considerable geographical diversity in Russia provides within-country variation in GDP, inequality, population density, and unemployment. We first show that income needs exceed actual income on average in Russia, and that these needs are less sensitive to changes in income than in other countries. Second, income needs vary by individual characteristics, while welfare sensitivity does not. Welfare sensitivity is however related to the regional context. Last, our estimated contextual results help us to understand why the existing literature has produced such a wide range of results.

A simulation study of sampling in difficult settings: Statistical superiority of a little-used method

Taking a representative sample to determine prevalence of variables such as disease or vaccination in a population presents challenges, especially when little is known about the population. Several methods have been proposed for second stage cluster sampling. They include random sampling in small areas (the approach used in several international surveys), random walks within a specified geographic area, and using a grid superimposed on a map. We constructed 50 virtual populations with varying characteristics, such as overall prevalence of disease and variability of population density across towns. Each population comprised about a million people spread over 300 towns. We applied ten sampling methods to each. In 1,000 simulations, with different sample sizes per cluster, we estimated the prevalence of disease and the relative risk of disease given an exposure and calculated the Root Mean Squared Error (RMSE) of these estimates. We compared the sampling methods using the RMSEs. In our simulations a grid method was the best statistically in the great majority of circumstances. It showed less susceptibility to clustering effects, likely because it sampled over a much wider area than the other methods. We discuss the findings in relation to practical sampling issues.

Transmission ecology of Trypanosoma cruzi by Rhodnius prolixus (Reduviidae: Triatominae) infesting palm-tree species in the Colombian Orinoco, indicates risks to human populations.

Chagas disease, affecting approximately eight million individuals in tropical regions, is primarily transmitted by vectors. Rhodnius prolixus, a triatomine vector, commonly inhabits in ecotopes with diverse palm tree species, creating optimal conditions for vector proliferation. This study aims to explore the transmission ecology of Trypanosoma cruzi, the causative parasite of Chagas disease, by investigating the feeding patterns and natural infection rates of R. prolixus specimens collected from various wild palm species in the Colombian Orinoco region. To achieve this objective, we sampled 35 individuals from three palm species (Attalea butyracea, Acrocomia aculeata, and Mauritia flexuosa) in a riparian forest in the Casanare department of eastern Colombia, totaling 105 sampled palm trees. DNA was extracted and analyzed from 115 R. prolixus specimens at different developmental stages using quantitative PCR (qPCR) for T. cruzi detection and identification of discrete typing units. Feeding preferences were determined by sequencing the 12S rRNA gene amplicon through next-generation sequencing. A total of 676 R. prolixus specimens were collected from the sampled palms. The study revealed variation in population densities and developmental stages of R. prolixus among palm tree species, with higher densities observed in A. butyracea and lower densities in M. flexuosa. TcI was the exclusive T. cruzi discrete typing unit (DTU) found, with infection frequency positively correlated with R. prolixus abundance. Insects captured in A. butyracea exhibited higher abundance and infection rates than those from other palm species. The feeding sources comprised 13 mammal species, showing no significant differences between palm species in terms of blood sources. However, Didelphis marsupialis and Homo sapiens were present in all examined R. prolixus, and Dasypus novemcinctus was found in 89.47% of the insects. This study highlights the significance of wild palms, particularly A. butyracea, as a substantial risk factor for T. cruzi transmission to humans in these environments. High population densities and infection rates of R. prolixus were observed in each examined palm tree species.

The Impact of China’s New Infrastructure Development on Urban Innovation Quality—A Quasi-Natural Experiment of Smart City Pilots

Currently, human society is in the era of the digital economy, driven by a new wave of digital technology revolution. Against this backdrop, China actively draws on global development concepts, accelerating the advancement of new infrastructure construction. This initiative aims to stabilize current economic demands while laying a material foundation for long-term development. Therefore, the efficient implementation of this new infrastructure has become a pressing issue for China, as unlocking its empowering role in the national economy is of paramount importance. This study, based on balanced panel data from China’s initial smart city pilot projects from 2008 to 2018, employs both two-way fixed effects and mediation effect models to empirically examine the impact of new infrastructure construction on urban innovation quality, considering endogeneity issues. The research findings reveal that new infrastructure construction enhances urban innovation quality by expediting industrial structural upgrades and enhancing total factor productivity. Furthermore, due to variations in geographical location and population density, there is heterogeneity in the impact of new infrastructure on urban innovation quality, with investments in new infrastructure exerting a more pronounced positive effect in cities with high population density.

Movement patterns of the rodent Trinomys dimidiatus in Atlantic Forest

AbstractAnimal movements of wild species are in theory related to individual and species' traits such as sex and reproductive condition, and temporal variation in resource availability or population density. Understanding how individuals move within an area throughout life, how frequent exploratory and dispersive movement are in the population and which individual traits and environmental conditions influence movement are of great importance for understanding how animals respond to environmental changes. Using capture‐mark‐recapture data of Trinomys dimidiatus gathered for 8 years in a montane Atlantic Forest area, we describe movement patterns by comparing two distance metrics (ORL—Observed Range Length and SDT—Mean Successive Distance/Time); we also evaluate the influences of sex on these distance metrics and residence time and number of captures on ORL. Additionally, model selection was used to evaluate the role of individual traits and environmental factors on T. dimidiatus' movements. We recorded 44 individuals (60.27%) with restricted movement pattern and 29 individuals (39.73%) with broad movement pattern within our grid. Broad movement pattern was observed in individuals with both long and short residence time. Males presented larger distance metrics and movements than females. Individuals with greater residence time presented larger ORL, mainly males. Heavier individuals of both sexes presented larger movements than lighter ones, especially males. Males presented shorter movements in periods of increased rainfall, but females' movements did not respond to rainfall variations. Overall, body mass was more important than rainfall in determining movements. The results here show that T. dimidiatus may present different movement patterns, including exploratory or dispersive movements to a new core area. Also, we highlight the importance of individual traits and environmental factors and reinforce sexual differences in individuals' movements and lifetime use of space.

Spatial Variation of Population Density and Age Structure of White-Tailed Deer (Odocoileus virginianus) in a Colombian Moor

Wildlife population density is affected by resource availability, predators and competitors, and anthropogenic stressors. Its analysis and the factors affecting it are important for conservation, use, or population control. Based on estimates of density and population parameters, together with niche modeling, previous studies considered that the white-tailed deer population at the Chingaza National Natural Park (NNP) is undergoing exponential growth due to the marginal influence of factors regulating its abundance, such as predators. The aim of this study was to evaluate the population density and age structure of the white-tailed deer in the Chingaza NNP, Colombia. To evaluate the population density and age structure of white-tailed deer in the Monterredondo and La Paila sectors of the Chingaza NNP, 10 transects were installed with circular plots in each. These were visited twice; in each visit, we collected all deer pellet groups, measuring each pellet to estimate its volume. Population density was calculated using the Eberhardt and Van Etten method and the semi-automated PELLET procedure using FSC and FAR techniques; the age structure was estimated by k-means and fuzzy clustering analyses. With the FAR technique, the estimated deer density was 2.09 ind/km2 in Monterredondo and 0.94 ind/km2 in La Paila. With PELLET, these values were 0.37 ± 0.4 ind/km2 for Monterredondo and 0.16 ± 0.2 ind/km2 for La Paila. The proportion of age classes (adult, juvenile, and fawn) was 1:0.29:0 for Monterredondo and 1:0.57:0.04 for La Paila. The population density of white-tailed deer in two sectors of the Chingaza NNP is not homogeneous, but shows temporal and spatial variations. Population density has decreased versus reports from previous studies in this same area, with the highest deer abundance recorded in 2004, mostly in the Monterredondo sector. The proportion of age classes suggests that the population is stable, as the largest proportion of individuals corresponds to the adult stage

Economic valuation of artisanal small-scale gold mining impacts: A framework for value transfer application

Illegal artisanal and small-scale gold mining (ASGM) activities have serious environmental and health consequences. In this study, we developed a framework for calculating the economic costs associated with the negative environmental and social impacts of ASGM in the Brazilian Amazon. Based on a literature review on impact valuations of deforestation, land degradation, and mercury contamination, we used multiple parameters to develop a generalizable value transfer formula. The formula relates input variables, such as mining site area, pit depth, gold extraction productivity, and other context variables (population density, per capita income, average daily fish consumption, and transportation cost for restoration) to calculate the average monetary values associated with the impact. Additionally, we propose an enhancement to the model used by Bakker et al. (2021) for estimating mercury impacts on human health. Our findings show that values associated with social and environmental damage range from US$ 187,200 to US$ 389,200 per kilogram of gold, which is mostly attributable to health outcomes related to mercury contamination, which represents more than twice the market value of gold. Furthermore, we conducted a case study for the Tapajós Basin, which revealed that the socioeconomic costs generated by 4,547 ha of alluvial ASGM in the basin surpasses US$ 1 billion for the year 2020.

Comparisons of Walleye Fecundity Before, During, and After Rehabilitation of the Red Lakes Fishery

Abstract The Red Lakes, Minnesota supported a substantial Walleye Sander vitreus fishery from the early to mid-20th century but experienced a major crash in the late 1990s. The population has since rebounded after a successful interagency recovery program and now supports valuable commercial and recreational fisheries. The variation in population densities associated with the collapse and subsequent recovery in the Red Lakes Walleye population provides a rare opportunity to study potential changes in relative fecundity (eggs/kg of body mass) under varying rates of exploitation: overexploited (1989 data), recovering (2004 data), and recovered (2017 data). We collected female Walleye in spring of 1989 (n = 30) from the Blackduck and Tamarac rivers and in spring of 2004 (n = 30) and 2017 (n = 30) from the Tamarac River. Results indicate that relative fecundity was significantly lower in 2017 (50,768, SD = 10,266) than in 1989 (58,216, SD = 6,211) and 2004 (61,964, SD = 7,472). We hypothesize that differences in relative fecundity among fishery states were due to differences in Walleye population abundances caused by varying exploitation rates in the years leading up to fecundity estimates.

Pengaruh Pendidikan, Pendapatan dan Kepadatan Penduduk Serta Distribusi Pendapatan Terhadap Permintaan Air PDAM di Kabupaten/Kota Provinsi Sumatera Barat

This study aims to examine the effect of Education, Income and PopulationDensity as well as Income Distribution on Water Demand in theRegencies/Cities of West Sumatra Province with the selected model being theRandom Effect Model (REM). The data used is panel data with a cross sectionof 18 regencies/cities and a 5 year time series from 2017 – 2021. The results ofthis study indicate that education has a significant positive effect on PDAMwater demand. The income and population density variables have nosignificant positive effect, while the income distribution variable has nosignificant negative effect on PDAM water demand.

Population Exposure to Compound Precipitation–Temperature Extremes in the Past and Future Climate across India

Abstract This study explores the population exposure to an increasing number of hydroclimatic extreme events owing to the warming climate. It is well agreed that the extreme events are increasing in terms of frequency as well as intensity due to climate change and that the exposure to compound extreme events (concurrent occurrence of two or more extreme phenomena) affects population, ecosystems, and a variety of socioeconomic aspects more adversely. Specifically, the compound precipitation–temperature extremes (hot-dry and hot-wet) are considered, and the entire Indian mainland is regarded as the study region that spans over a wide variety of climatic regimes and wide variation of population density. The developed copula-based statistical method evaluates the change in population exposure to the compound extremes across the past (1981–2020) and future (near future: 2021–60 and far future: 2061–2100) due to climate change. The results indicate an increase of more than 10 million person-year exposure from the compound extremes across many regions of the country, considering both near and far future periods. Densely populated regions have experienced more significant changes in hot-wet extremes as compared with the hot-dry extremes in the past, and the same is projected to continue in the future. The increase is as much as sixfold in many parts of the country, including the Indo-Gangetic Plain and southernmost coastal regions, identified as the future hotspots with the maximum increase in exposure under all the projected warming and population scenarios. The study helps to identify the regions that may need greater attention based on the risks of population exposure to compound extremes in a warmer future. Significance Statement How is the growing population being affected now, and in the future, how will it be affected due to climate change induced compound extreme events? This study explores this societal consequence in terms of population exposure for the most populous country, India. An increase of more than 10 million person-year exposure from the precipitation–temperature compound extremes across many regions is indicated. Densely populated regions are expected to experience enhanced population exposure to hot-wet extremes as compared with the hot-dry extremes. Furthermore, the maximum increase in population exposure to compound extremes is expected across the Indo-Gangetic Plain and southern coastal regions of India. The outcome of the study will be helpful for adopting socioeconomic decisions toward the welfare of society.

Spatiotemporal evolution and impact mechanism of ecological vulnerability in the Guangdong–Hong Kong–Macao Greater Bay Area

The constant conflict between the rapidly developing socioeconomic and ecological environment within the Guangdong–Hong Kong–Macao Greater Bay Area necessitates the exploration of ecosystem vulnerability patterns and driving mechanisms. A comprehensive social–economic–ecological framework is proposed to assess the ecosystem vulnerability pattern of the Greater Bay Area, specifically spanning from 1990 to 2020. Employing geographic detectors and weighting methods, the study quantifies spatiotemporal variation and the underlying mechanisms driving vulnerability in the study area. The results demonstrate an obvious trend in ecosystem vulnerability index (ESVI) across the Greater Bay Area, with an initial decline followed by gradual increase during the1990–2020. A substantial majority of the region (approximately 63.85% of the total area) experienced a decline in ESVI from 1990 to 2010. Moreover, the spatial distribution of this decline exhibited a prevailing east-to-west pattern, indicating an overall southward shift over time. Furthermore, a decline was primarily concentrated in the central region and the rapidly expanding urban areas situated on both sides of the Pearl River estuary. Encouragingly, a notable amplification in ESVI was observed between 2010 and 2020, which is attributed to the development, utilization, and protection of land, forests, water bodies, and other pertinent factors associated with urban expansion. The impact of climate change on ESVI changes exhibits a growing magnitude over time, while human activities persist as the predominant driver of ESVI changes. The natural factors exerted a substantial impact on ESVI changes primarily in the upper reaches of the Pearl River, which included topographic relief, precipitation, water network density, biological abundance, and related aspects. Conversely, the pronounced influence of human activities on ESVI changes predominantly manifests within the urban agglomeration of the Pearl River Delta. Key contributors to such a manifestation encompass land change types, intensity of human activities, population density, and related variables. Changes in land use have the potential to induce heightened ecological vulnerability changes. The amelioration of ecological protection and land use practices can be mitigated and reduced by employing ESVI. Moreover, the framework introduced in this study holds the potential to extend vulnerability assessments to other regions with similar ecosystem types. It is expected that the findings derived from this framework could contribute to the formulation of policy recommendations pertaining to ecosystem protection and management.

Public support for decarbonization policies in the UK: exploring regional variations and policy instruments

ABSTRACT Decarbonization policies require public support to be implemented and to remain in legislation. Examinations of public support for climate policies tend to focus on a small number of policy instruments and/or use hypothetical instead of real policy proposals. Here, we address these criticisms by examining public support across four distinct policy instruments – command-and-control, market-based, information-based, and voluntary – using sixteen policy proposals by UK political parties and government institutions. In addition to assessing UK national policy support, we also explore regional differences. Using a representative sample of the UK population (N = 1,911), we find that, at a national level, individuals preferred instruments shown to be less effective in reaching net-zero: information-based and voluntary policies. Our results indicate that the extent to which individuals believe in the free market, their environmental worldviews and political party support as well as their age are all correlated with policy support. We find stark regional differences where, compared to individuals living in Greater London, those living in the remainder of the country were 32% and 30% less likely to support command-and-control and market-based policies, respectively (among other regional differences). Regional variations in free-market beliefs and population density partly explain differences in policy support. We propose policymakers focus on place-based initiatives to increase support for decarbonization policies that are more effective in reaching net-zero and on improving the perception of market-based and command-and-control policies through positive framing and policy bundles.

Seasonal variation in giraffe population density and abundance in the Tsavo landscape, Kenya

AbstractThe giraffe population is thought to vary seasonally in the Tsavo landscape of Kenya, but little data exists to establish if there indeed exists any variability. This study examined the impact of seasonal variation on the giraffe population in the Tsavo landscape. We conducted road transect counts and found 2683 and 3295 giraffes during the wet and dry seasons, with mean KAI and density of 0.19 ± 0.01 and 1.20 ± 0.435/km2, respectively. The giraffe population did not vary significantly between seasons, age and sex. The parks had more giraffes during the wet season compared to the dry season, while the reverse was true for Rombo and Taita ranches. No giraffes were sighted in South Kitui National Reserve.

Mapping urban living standards and economic activity in developing countries with energy data.

Urban data deficits in developing countries impede evidence-based planning and policy. Could energy data be used to overcome this challenge by serving as a local proxy for living standards or economic activity in large urban areas? To answer this question, we examine the potential of georeferenced residential electricity meter data and night-time lights (NTL) data in the megacity of Karachi, Pakistan. First, we use nationally representative survey data to establish a strong association between electricity consumption and household living standards. Second, we compare gridded radiance values from NTL data with a unique dataset containing georeferenced median monthly electricity consumption values for over 2 million individual households in the city. Finally, we develop a model to explain intra-urban variation in radiance values using proxy measures of economic activity from Open Street Map. Overall, we find that NTL data are a poor proxy for living standards but do capture spatial variation in population density and economic activity. By contrast, electricity data are an excellent proxy for living standards and could be used more widely to inform policy and support poverty research in cities in low- and middle-income countries.

Random Laser Emission from Fiber coated ZnO

Random lasing from a solid-state gain medium prepared on photonic crystal fibre (PCF) is observed for the first time. Vertically aligned ZnO microrods were prepared on PCF using a simple technique of chemical bath deposition (CBD). A low lasing threshold of 12.2 mJ/cm2 was observed in sample with longer zinc oxide (ZnO) rod length. The variation in morphology and population density did not affect the lasing threshold significantly. Further investigation of the effect of fiber length revealed that a shorter fiber had a lower threshold and showed quenching of the spontaneous emission revealing better lasing output. Simulations based on the morphology of the gain medium revealed light confinement in the structure, validating the origin of the lasing emission. Overall, this study shows the potential of utilising optical fiber as random lasers with a sustainable solid state gain medium.

Public capital and institutions' quality in the Italian regions

AbstractThis paper investigates the role played by public capital on the production level of Italian regions by specifically accounting for the quality of institutions. Our analysis, carried out over the period 2000–2019, benefits from a rich data set on public expenditures. This allows us to build the regional public capital stock by distinguishing among public institutions in charge of the investments and sectors of intervention. While controlling for several contextual variables (human capital, technological capital, and population density), the main results show that public capital has a positive and significant effect on production. Most interestingly, looking at Mezzogiorno's regions, public capital carried out by local institutions turns out to have a lower impact than in the rest of the Italian regions. On the other hand, central bodies in the South exhibit an impact higher than the average. Moreover, institutions' quality exhibits a positive and significant effect on regional economic performance. These results cast serious doubts about the local Southern administrations' capacity to effectively manage the National Recovery and Resilience Plan's enormous resources and the new European Union cohesion framework 2021–2027. Our results are also relevant for other European regions that, featuring structural traits similar to Southern Italian regions, are expected to face the same difficulties in managing public funding.

Partitioning variance in population growth for models with environmental and demographic stochasticity.

How demographic factors lead to variation or change in growth rates can be investigated using life table response experiments (LTRE) based on structured population models. Traditionally, LTREs focused on decomposing the asymptotic growth rate, but more recently decompositions of annual 'realized' growth rates using 'transient' LTREs have gained in popularity. Transient LTREs have been used particularly to understand how variation in vital rates translate into variation in growth for populations under long-term study. For these, complete population models may be constructed to investigate how temporal variation in environmental drivers affect vital rates. Such investigations have usually come down to estimating covariate coefficients for the effects of environmental variables on vital rates, but formal ways of assessing how they lead to variation in growth rates have been lacking. We extend transient LTREs to further partition the contributions from vital rates into contributions from temporally varying factors that affect them. The decomposition allows one to compare the resultant effect on the growth rate of different environmental factors, as well as density dependence, which may each act via multiple vital rates. We also show how realized growth rates can be decomposed into separate components from environmental and demographic stochasticity. The latter is typically omitted in LTRE analyses. We illustrate these extensions with an integrated population model (IPM) for data from a 26 years study on northern wheatears (Oenanthe oenanthe), a migratory passerine bird breeding in an agricultural landscape. For this population, consisting of around 50-120 breeding pairs per year, we partition variation in realized growth rates into environmental contributions from temperature, rainfall, population density and unexplained random variation via multiple vital rates, and from demographic stochasticity. The case study suggests that variation in first year survival via the unexplained random component, and adult survival via temperature are two main factors behind environmental variation in growth rates. More than half of the variation in growth rates is suggested to come from demographic stochasticity, demonstrating the importance of this factor for populations of moderate size.