Stage-Specific Demographic Effects of Hydrologic Variation in a Stream Salamander.

AbstractWe lack a strong understanding of how organisms with complex life histories respond to climate variation. Many stream-associated species have multistage life histories that are likely to influence the demographic consequences of floods and droughts. However, tracking stage-specific demographic responses requires high-resolution, long-term data that are rare. We used 8 years of capture-recapture data for the headwater stream salamander Gyrinophilus porphyriticus to quantify the effects of flooding and drying magnitude on stage-specific vital rates and population growth. Drying reduced larval recruitment but increased the probability of metamorphosis (i.e., adult recruitment). Flooding reduced adult recruitment but had no effect on larval recruitment. Larval and adult survival declined with flooding but were unaffected by drying. Annual population growth rates (λ) declined with flooding and drying. Lambda also declined over the study period (2012-2021), although mean λ was 1.0 over this period. Our results indicate that G. porphyriticus populations are resilient to hydrologic variation because of compensatory effects on recruitment of larvae versus adults (i.e., reproduction vs. metamorphosis). Complex life cycles may enable this resilience to climate variation by creating opportunities for compensatory demographic responses across stages. However, more frequent and intense hydrologic variation in the latter half of this study contributed to a decline in λ over time, suggesting that increasing environmental variability poses a threat even when demographic compensation occurs.

Long-term population projections: Scenarios of low or rebounding fertility.

The size of the human population is projected to peak in the 21st century. But quantitative projections past 2100 are rare, and none quantify the possibility of a rebound from low fertility to replacement-level fertility. Moreover, the most recent long-term deterministic projections were published a decade ago; since then there has been further global fertility decline. Here we provide updated long-term cohort-component population projections and extend the set of scenarios in the literature to include scenarios in which future fertility (a) stays below replacement or (b) recovers and increases. We also characterize old-age dependency ratios. We show that any stable, long-run size of the world population would persistently depend on when an increase towards replacement fertility begins. Without such an increase, the 400-year span when more than 2 billion people were alive would be a brief spike in history. Indeed, four-fifths of all births-past, present, and future-would have already happened.

Chronic Effects of an Insect Growth Regulator (teflubenzuron) on the Life Cycle and Population Growth Rate of Folsomia candida.

Current standard toxicity tests on nontarget soil invertebrates mainly focus on the endpoints survival and reproduction. Such results are likely insufficient to predict effects at higher organizational levels, for example, the population level. We assessed the effects of exposure to the pesticide teflubenzuron on the collembolan Folsomia candida, by performing a full life-cycle experiment exposing single individuals via contaminated food (uncontaminated control and 0.2, 0.32, 0.48, 0.72, 1.08, and 1.6 mg/kg dry yeast). Several life-history traits were considered by following the growth and development of newly hatched individuals over a period of 65 days. We assessed survival, body length, time to first oviposition, cumulative egg production, and hatchability of eggs. A two-stage model was applied to calculate the population growth rate (λ) combined with elasticity analysis to reveal the relative sensitivity of λ to the effects of teflubenzuron on each life-history parameter. Body length was the least sensitive life-history parameter (median effective concentration = 1.10 mg teflubenzuron/kg dry yeast) followed by time to first oviposition (0.96 mg/kg), survival (median lethal concentration = 0.87 mg/kg), cumulative egg production (0.32 mg/kg), and egg hatchability (0.27 mg/kg). Population growth decreased with increasing concentrations of teflubenzuron (λ = 1.162/day in control to 1.005/day in 0.72 mg/kg dry yeast, with populations going extinct at 1.08 and 1.6 mg/kg dry yeast). Elasticity analysis showed that changes in juvenile survival had a greater impact on the population growth rate compared with the other life-history traits. Our study provides a comprehensive overview of individual-level effects of long-term exposure to teflubenzuron and integrates these effects to assess the potential risk to collembolan populations. Environ Toxicol Chem 2024;43:1173-1183. © 2024 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

The long-term expansion and recession of human populations.

Over the last 12,000 y, human populations have expanded and transformed critical earth systems. Yet, a key unresolved question in the environmental and social sciences remains: Why did human populations grow and, sometimes, decline in the first place? Our research builds on 20 y of archaeological research studying the deep time dynamics of human populations to propose an explanation for the long-term growth and stability of human populations. Innovations in the productive capacity of populations fuels exponential-like growth over thousands of years; however, innovations saturate over time and, often, may leave populations vulnerable to large recessions in their well-being and population density. Empirically, we find a trade-off between changes in land use that increase the production and consumption of carbohydrates, driving repeated waves of population growth over thousands of years, and the susceptibility of populations to large recessions due to a lag in the impact of humans on resources. These results shed light on the long-term drivers of human population growth and decline.

The Formal Demography of Peak Population.

When will the human population peak? In this article, we build on classical results by Ansley Coale, who showed that when fertility declines steadily, births reach their maximum before fertility reaches replacement level, and the decline in total population size does not occur until several decades after fertility has reached that level. We extend Coale's results by modeling longevity increases, net immigration, and a slowdown in fertility decline that resembles current projections. With these extensions, our models predict a typical lag between replacement-level fertility and population decline of about 35 to 40 years, consistent with projections by the United Nations and about 15 years longer than the lag predicted by Coale. Our analysis helps reveal underlying factors in the timing of peak population.

Xrn1 Exoribonuclease-An Intrinsic Marker of Yeast Population Growth.

BACKGROUND: Xrn1 exoribonuclease is the major mRNA degradation enzyme in Saccharomyces cerevisiae. In exponentially growing cells, Xrn1 is localised in the yeast cells and directs the degradation of mRNA molecules. Xrn1 is gradually deposited and presumably inactivated in the processing bodies (P-bodies) as the yeast population ages. Xrn1 can also localise to the membrane compartment of the arginine permease Can1/eisosome compartment at the yeast plasma membrane. This localisation correlates with the metabolic (diauxic) shift from glucose fermentation to respiration, although the relevance of this Xrn1 localisation remains unknown. METHODS: We monitored the growth rates and morphology of Xrn1-green fluorescent protein (GFP) cells compared to wild-type and Δxrn1 cells and observed the Xrn1-GFP localisation pattern in different media types for up to 72 hours using fluorescence microscopy. RESULTS: We present the dynamic changes in the localisation of Xrn1 as a versatile tool for monitoring the growth of yeast populations at the single-cell level using fluorescence microscopy. CONCLUSIONS: The dynamic changes in the localisation of Xrn1 can be a versatile tool for monitoring the growth of yeast populations at the single-cell level. Simultaneously, Xrn1 localisation outside of P-bodies in post-diauxic cells supports its storage and cytoprotective function, yet the role of P-bodies in cell metabolism has still not yet been entirely elucidated.

Nonlinear life table response experiment analysis: Decomposing nonlinear and nonadditive population growth responses to changes in environmental drivers.

Life table response experiments (LTREs) decompose differences in population growth rate between environments into separate contributions from each underlying demographic rate. However, most LTRE analyses make the unrealistic assumption that the relationships between demographic rates and environmental drivers are linear and independent, which may result in diminished accuracy when these assumptions are violated. We extend regression LTREs to incorporate nonlinear (second-order) terms and compare the accuracy of both approaches for three previously published demographic datasets. We show that the second-order approach equals or outperforms the linear approach for all three case studies, even when all of the underlying vital rate functions are linear. Nonlinear vital rate responses to driver changes contributed most to population growth rate responses, but life history changes also made substantial contributions. Our results suggest that moving from linear to second-order LTRE analyses could improve our understanding of population responses to changing environments.

Mapping of population growth influence on land use transformation from 1994 to 2015 in Madaba Governorate, Jordan.

The Madaba Governorate, as the second-largest wheat producer in Jordan, holds a crucial position in safeguarding regional food security. Its evolving landscape, marked by changes in land use, presents environmental and socio-economic challenges that necessitate sustainable urban planning and land management practices. This study delves into the intricate relationship between the conversion of agricultural lands into urban areas and the concurrent rise in population within the Madaba Governorate. Utilizing a Markov model, this research employs land use and land cover (LULC) data from 1994, 2004, and 2015 to project future changes in 2025 and 2035 with an impressive 80% accuracy (kappa coefficient). The findings reveal a projected 6% increase in urban areas over the next decade and a notable 11.81% decline in rural lands, signifying a substantial urbanization trend. In response to these population-driven LULC dynamics, there is an urgent need for the implementation of sustainable land use planning and management solutions. Given the constraints of limited water resources in the region, this study also places emphasis on water resource management. Recommendations include measures such as restricting urban sprawl, preserving agricultural lands, managing population growth, and implementing water conservation strategies. These insights provide invaluable information for stakeholders in the Madaba Governorate, including policymakers and land use planners, fostering a comprehensive understanding of the complex interplay between regional water resources, population expansion, and land use changes.

Detrimental effects of hull cleaning wastewater on oxidative status, life cycle parameters, and population growth of the monogonont rotifer Brachionus manjavacas.

While wastewater discharged from in-water cleaning process of ship hulls on rotifer consistently released into aquatic ecosystem, its detrimental effects on non-target animals are largely unclear. In this study, we provide evidence on detrimental effects of hull cleaning wastewater in the monogonont rotifer Brachionus manjavacas by analyzing biochemical and physiological parameters in its oxidative status, survival, lifespan, growth, fecundity, and population. The wastewater contained high concentrations of metals (Zn and Cu) and metal-based antifoulants (CuPT and ZnPT). Significant oxidative stress was observed in response to two wastewater samples [1) raw wastewater (RW) and 2) mechanical filtrated in the cleaning system (MF)]. Higher detrimental effects in survival, lifespan, fecundity, and population growth for 10 days were measured in the RW-exposed rotifers than those results analyzed in the MF-exposed rotifers. Two growth parameters, lorica length and width were also significantly modulated by both wastewater samples. These results indicate that even filtered hull cleaning wastewater would have deleterious effects on the maintenance of the rotifer population when they exposed constantly.

Oystershell scale (Hemiptera: Diaspididae) population growth, spread, and phenology on aspen in Arizona, USA.

Oystershell scale (OSS; Lepidosaphes ulmi L.) is an invasive insect that threatens sustainability of aspen (Populus tremuloides Michx.) in the southwestern United States. OSS invasions have created challenges for land managers tasked with maintaining healthy aspen ecosystems for the ecological, economic, and aesthetic benefits they provide. Active management is required to suppress OSS populations and mitigate damage to aspen ecosystems, but before management strategies can be implemented, critical knowledge gaps about OSS biology and ecology must be filled. This study sought to fill these gaps by addressing 3 questions: (i) What is the short-term rate of aspen mortality in OSS-infested stands in northern Arizona, USA? (ii) What are the short-term rates of OSS population growth on trees and OSS spread among trees in aspen stands? (iii) What is the phenology of OSS on aspen and does climate influence phenology? We observed high levels of aspen mortality (annual mortality rate = 10.4%) and found that OSS spread rapidly within stands (annual spread rate = 10-12.3%). We found first, second, and young third instars throughout the year and observed 2 waves of first instars (i.e., crawlers), one throughout the summer and a second in mid-winter. The first wave appeared to be driven by warming seasonal temperatures, but the cause of the second wave is unknown and might represent a second generation. We provide recommendations for future OSS research, including suggestions for more precise quantification of OSS phenology, and discuss how our results can inform management of OSS and invaded aspen ecosystems.

Factors influencing baby boomers' intention to choose a dish featuring plant-based meat alternatives (PBMA) at a restaurant: Findings from an online panel study.

The purpose of this study is to examine the psychosocial determinants of baby boomers'-born between 1946 and 1964- intention to choose a menu item featuring plant-based meat alternatives (PBMA) when dining out. The specific objectives are as follows: 1) to identify the baby boomer generation's health-related perceptions about PBMA, and 2) to examine the factors that influence baby boomers' intention to choose a dish featuring PBMA at a restaurant. A total of 174 responses obtained using the Qualtrics panel were analyzed with content analysis and partial least squares structural equation modeling (PLS-SEM). The findings identified various underlying perceptions of baby boomers toward PBMA, such as perceived health outcomes, perceived availability, and willingness to purchase. Furthermore, subjective norm, cues to action, and self-identity were found to be significant predictors of the intention to choose a menu item featuring PBMA when dining out. Theoretical and practical implications are discussed.

An integrated deep-learning model for smart waste classification.

Efficient waste management is essential for human well-being and environmental health, as neglecting proper disposal practices can lead to financial losses and the depletion of natural resources. Given the rapid urbanization and population growth, developing an automated, innovative waste classification model becomes imperative. To address this need, our paper introduces a novel and robust solution - a smart waste classification model that leverages a hybrid deep learning model (Optimized DenseNet-121 + SVM) to categorize waste items using the TrashNet datasets. Our proposed approach uses the advanced deep learning model DenseNet-121, optimized for superior performance, to extract meaningful features from an expanded TrashNet dataset. These features are subsequently fed into a support vector machine (SVM) for precise classification. Employing data augmentation techniques further enhances classification accuracy while mitigating the risk of overfitting, especially when working with limited TrashNet data. The results of our experimental evaluation of this hybrid deep learning model are highly promising, with an impressive accuracy rate of 99.84%. This accuracy surpasses similar existing models, affirming the efficacy and potential of our approach to revolutionizing waste classification for a sustainable and cleaner future.

Succession and climatic stochasticity induce long-term decline of a forest browser.

Removal of predators and creation of early seral habitat have, in many systems, caused substantial population growth of herbivores. Hyperabundant herbivores, in turn, induce cascading ecosystem effects, but few studies have investigated long-term browser density trends in relation to succession and stochastic climate events. Here, we use annual, empirical population estimates of a forest browser to relate forest succession to long-term decline of an herbivore that prefers early seral habitat. From 2007-2021, concurrent with reduced timber harvest, we used line-transect distance sampling to document annual changes in Columbian black-tailed deer (Odocoileus hemionus columbianus) density on a mid-sized (17.3km2) predator-free island. We documented successional changes associated with forest aggradation and decreased forage quality for deer: early successional shrub/scrub habitat declined 3.8%/year; timber volume increased 4.5%/year; and canopy coverage increased 2.5%. In 2007-2008, deer densities were the greatest observed (~44/km2), but then an historic snowstorm reduced deer density by 39%. From 2010-2021, as forests continued to mature, deer density decreased 4.0%/year, declining to 20 deer/km2. Using a multivariate approach to combine habitat variables (i.e., early seral coverage, timber volume, and canopy closure) into a measure of forest maturation, we found a significant negative relationship between deer density and forest aggradation. Thus, consistent with predictions for bottom-up limited browsers, we observed significant annual declines in a deer population throughout an extended period of forest regrowth. Despite declines, deer density on the island exceeds mainland densities, and overbrowsing likely continues to disrupt ecosystem processes.

Tumor growth and population modeling in a toxicant-stressed random environment.

When examining some factors that contribute to the growth or decline of a population or tumor, it is essential to consider a random hypothesis. By analyzing the effects of stress on a population (or volume of tumor growth) in a random environment, we develop stochastic models describing the dynamics of the population (or tumor growth) based on random adjustments to the population's intrinsic growth rate, carrying capacity, and harvesting efforts (or tumor treatments). Apart from the models' ability to capture fluctuations, the availability of a shape parameter in the models gives it the flexibility to describe a variety of population/tumor data with different shapes. The distribution of the stressed population size with or without harvesting (or treatments) is derived and used to calculate the maximum expected amount of harvests that can be taken from the population without depleting resources in the long run (or the minimum amount of chemotherapy needed to cause shrinkage or eradication of a tumor). The work done is applied to analyze tumor growth using published data comprising of the volume of breast tumor obtained by orthotopically implanting LM2-[Formula: see text] cells into the right inguinal mammary fat pads of 6- to 8-week-old female Severe Combined Immuno-Deficient mice.

When can a population spreading across sink habitats persist?

We consider populations with time-varying growth rates living in sinks. Each population, when isolated, would become extinct. Dispersal-induced growth (DIG) occurs when the populations are able to persist and grow exponentially when dispersal among the populations is present. We provide a mathematical analysis of this surprising phenomenon, in the context of a deterministic model with periodic variation of growth rates and non-symmetric migration which are assumed to be piecewise continuous. We also consider a stochastic model with random variation of growth rates and migration. This work extends existing results of the literature on the DIG effects obtained for periodic continuous growth rates and time independent symmetric migration.

Adequate nutrient intake mitigate the toxic effects of bromate on the rotifer Brachionus calyciflorus.

Bromate is receiving increased attention as a typical disinfection by-product in aquatic environments, but bromate toxicity tests on invertebrate such as Brachionus calyciflorus rotifer are inadequate. In the present study, the long-term toxicity tests on B. calyciflorus were performed during 21 days under the exposure of different bromate concentrations and two algal density conditions. Furthermore, we evaluated the feeding behaviors of the rotifers under the impact of bromate. The maximum population density of rotifers was significantly reduced at 100 and 200 mg/L bromate exposure at the two algal density conditions. However, we observed that the maximum population density and population growth rate of rotifers were higher at 3.0 × 106 cells/mL algal density than those at 1.0 × 106 cells/mL under the same conditions of bromate exposure. These results suggest that higher food density may have alleviated the negative effects of bromate on rotifers. Meanwhile, the ingestion rate at an algal density of 3.0 × 106 cells/mL was higher than that at 1.0 × 106 cells/mL. The present study provides a basic reference to comprehensively evaluate the toxic effects of bromate on aquatic organisms.

In quest of China sports lottery development path to common prosperity in 2035.

OBJECTIVES: The China sports lottery contributes to sports and welfare causes. This study aims to construct a macro forecasting model supporting its sustained growth aligned with Vision 2035. METHODS: The modeling employed a distributional regression. Sales data of the China sports lottery from 2011 to 2022 were chosen as the response variable, alongside various macro- and event-level explanatory factors. RESULTS: A gamma distribution best fit the data. In the stable model spanning 2011-2019, urbanization, population dynamics, and FIFA emerged as significant contributors (Chi-square p < 0.05) to the location shift parameter. These three factors retained their significance in the 2011-2022 shock model, where shock itself notably impacted sales (p < 0.001). Utilizing the shock model, we simulated the trajectory of the China sports lottery up to 2035. China's demographics changes are poised to create structural headwinds starting in 2026, leading to an anticipated decline in sales driven by population shifts from 2032 onward. However, the FIFA effect is projected to continue fortifying this sector. CONCLUSIONS: Beyond offering original insights into the sales trajectory until 2035, specifically concerning new urbanization, negative population growth, and the FIFA effect, this macro forecasting framework can assist in addressing the policy priority of balancing growth with risk mitigation. We recommend policymakers connect market development with mass sports, potentially garnering a dual boost from the growing population of older consumers and the inherent benefits of a "FIFA (mass sports)" effect. A people-centered approach to the China sports lottery could significantly contribute to the long-range objectives of achieving common prosperity outlined in Vision 2035.

Regional population and social welfare from the perspective of sustainability: Evaluation indicator, level measurement, and interaction mechanism.

Key to regional sustainable development are the development and interplay of population dynamics and social welfare, each playing a significant role. As a representative region with demographic characteristics such as negative population growth and large labor outflow, the development and interaction between population and social welfare in Nanchong deserve in-depth exploration. This article takes the development of population and social welfare in Nanchong as the research object, and constructs an evaluation indicator system of population and social welfare through research backtracking, and uses entropy method and coupling coordination model to measure the development level and interactive effect of population and social welfare in Nanchong from 2010 to 2021. The research results show that: Firstly, the comprehensive evaluation results of population in Nanchong shows a linear upward trend, which indicates the stable positive effect of population structure and distribution, the gradual improvement effect of population quality effectively compensate for the weakening effect of population quantity, thus achieving the positive development of population. Secondly, the comprehensive evaluation results of social welfare in Nanchong shows an exponential upward trend, which indicates the social welfare has maintained a rapid growth momentum in various dimensions and the long-term positive effects have completely absorbed the negative effects, thus achieving the positive development of social welfare. Thirdly, during the sample period, the population and social welfare in Nanchong consistently maintained a high level of interaction strength, with factors diffusing and integrating. On this basis, the diffusion theory is used as an empirical reference to construct three interactive mechanisms between the population and social welfare in Nanchong and the implications are inferred from the empirical results.

Colony level fitness analysis identifies a trade-off between population growth rate and dauer yield in Caenorhabditis elegans.

BACKGROUND: In the evolution from unicellular to multicellular life forms, natural selection favored reduced cell proliferation and even programmed cell death if this increased organismal fitness. Could reduced individual fertility or even programmed organismal death similarly increase the fitness of colonies of closely-related metazoan organisms? This possibility is at least consistent with evolutionary theory, and has been supported by computer modelling. Caenorhabditis elegans has a boom and bust life history, where populations of nematodes that are sometimes near clonal subsist on and consume food patches, and then generate dauer larva dispersal propagules. A recent study of an in silico model of C. elegans predicted that one determinant of colony fitness (measured as dauer yield) is minimization of futile food consumption (i.e. that which does not contribute to dauer yield). One way to achieve this is to optimize colony population structure by adjustment of individual fertility. RESULTS: Here we describe development of a C. elegans colony fitness assay, and its use to investigate the effect of altering population structure on colony fitness after population bust. Fitness metrics measured were speed of dauer production, and dauer yield, an indirect measure of efficiency of resource utilization (i.e. conversion of food into dauers). We find that with increasing founder number, speed of dauer production increases (due to earlier bust) but dauer yield rises and falls. In addition, some dauer recovery was detected soon after the post-colony bust peak of dauer yield, suggesting possible bet hedging among dauers. CONCLUSIONS: These results suggest the presence of a fitness trade-off at colony level between speed and efficiency of resource utilization in C. elegans. They also provide indirect evidence that population structure is a determinant of colony level fitness, potentially by affecting level of futile food consumption.

Socioeconomic, Demographic, and Environmental Factors May Inform Malaria Intervention Prioritization in Urban Nigeria.

Urban population growth in Nigeria may exceed the availability of affordable housing and basic services, resulting in living conditions conducive to vector breeding and heterogeneous malaria transmission. Understanding the link between community-level factors and urban malaria transmission informs targeted interventions. We analyzed Demographic and Health Survey Program cluster-level data, alongside geospatial covariates, to describe variations in malaria prevalence in children under 5 years of age. Univariate and multivariable models explored the relationship between malaria test positivity rates at the cluster level and community-level factors. Generally, malaria test positivity rates in urban areas are low and declining. The factors that best predicted malaria test positivity rates within a multivariable model were post-primary education, wealth quintiles, population density, access to improved housing, child fever treatment-seeking, precipitation, and enhanced vegetation index. Malaria transmission in urban areas will likely be reduced by addressing socioeconomic and environmental factors that promote exposure to disease vectors. Enhanced regional surveillance systems in Nigeria can provide detailed data to further refine our understanding of these factors in relation to malaria transmission.