The risks of climate change to children have been widely discussed, but the risks of overpopulation have not been similarly scrutinised. Projections of the health and mortality rates of infants and children have largely ignored overpopulation; for example, the United Nation's projections of infant mortality to 2100 disregard the influences of rapidly increasing populations in low-and middle-income countries and a deteriorating climate. In this paper, we first summarise the evidence that a large and growing human population will increase child mortality, and compromise health and wellbeing this century. Population growth increases the pace and magnitude of climate change because the degree of climate disruption is a product of per-capita consumption and total population size. Population growth also increases overcrowding, which in turn increases local and global air pollution, disease transmission, and resource scarcity, all of which have disproportionate effects on children compared to adults. To gain insight into the potential risks that children will face this century, we analysed the United Nation's Medium and High population projections for this century to show that between 9.91 billion and 14.49 billion children will be born from 2022 to 2100, and that most (> 60%) will be born in sub-Saharan Africa and Central/South Asia (6.19 billion and 9.10 billion, 62.5% and 61.4% of all births, Medium and High projections, respectively), where malnutrition is already high and capacity lowest to increase crop yields accordingly. We then identify areas where future child mortality can be expected to be higher than current predictions. We show that the lowest-income nations with the highest population growth have the fewest resources to protect increasing numbers of children from the deteriorating climate and the risks of overcrowding. We emphasise the urgent need for appropriate, quality, free, non-coercive, familyplanning services to be universally available to allow men and women the opportunity to choose the size of their family. In summary, we provide the first evaluation of the evidence that overpopulation is already adversely affecting children and the evidence that there will be increasingly serious consequences for children if population growth continues at its current pace.

The koala (Phascolarctos cinereus) is Australia’s largest arboreal folivore that inhabits eastern and south-eastern Australia. While its populations are in decline in areas of New South Wales and Queensland, high and increasing densities in the Mount Lofty Ranges of South Australia raise concerns of overbrowsing. This challenge highlights the need for optimized fertility-control strategies to balance sustainable population management with ecological, ethical, and logistic complexities. Demographic models are valuable tools for predicting population dynamics, but their accuracy hinges on reliable estimates of population density, often influenced by biases in expert-elicited and citizen-science data. We developed and combined a point-process model, an ensemble species distribution model, and a demographic model to project koala populations in the Mount Lofty Ranges over the next 25 years to assess the efficiency and cost-effectiveness of fertility-control interventions. We tested two hypotheses: (1) koala distribution is driven by rainfall, temperature, and native vegetation, with summer rainfall boosting habitat suitability, and (2) spatially targeted fertility intervention is more cost-effective than generalized strategies due to subpopulation connectivity. Accounting for sampling biases and local densities, our models estimate that highly suitable areas in the Mount Lofty Ranges are determined by rainfall, temperature, and vegetation. Without intervention, this population could increase by ~10% in 25 years. Fertility control focusing on adult females was the most cost-effective (~AU$28 million) strategy, although this scenario was slower at reducing population size compared to an intervention also sterilizing female back young. While the choice of sterilization scenario has minimal impact on overall costs, ethical considerations and long-term conservation goals such as population density thresholds will have more influence on managing expenses effectively.

Analysis of long-term trends in abundance provide insights into population dynamics. Population growth rates are the emergent interplay of fertility, survival, and dispersal, but the density feedbacks on some vital rates (component) can be decoupled from density feedback on population growth rates (ensemble). However, the mechanisms responsible for this decoupling are poorly understood. We simulated component density feedbacks on survival in age-structured populations of long-living vertebrates and quantified how imposed nonstationarity (density-independent mortality and variation in carrying-capacity) modified the ensemble feedback signal estimated from logistic-growth models to the simulated abundance time series. The statistical detection of ensemble density feedback was largely unaffected by density-independent processes, but catastrophic and proportional mortality eroded the effect of density-dependent survival on ensemble-feedback strength more strongly than variation in carrying capacity. Thus, phenomenological models offer a robust approach to capture density feedbacks from nonstationary census data when density-independent mortality is low.

AbstractThe pursuit of simple, yet fair, unbiased, and objective measures of researcher performance has occupied bibliometricians and the research community as a whole for decades. However, despite the diversity of available metrics, most are either complex to calculate or not readily applied in the most common assessment exercises (e.g., grant assessment, job applications). The ubiquity of metrics like the h-index (h papers with at least h citations) and its time-corrected variant, the m-quotient (h-index ÷ number of years publishing) therefore reflect the ease of use rather than their capacity to differentiate researchers fairly among disciplines, career stage, or gender. We address this problem here by defining an easily calculated index based on publicly available citation data (Google Scholar) that corrects for most biases and allows assessors to compare researchers at any stage of their career and from any discipline on the same scale. Our ε′-index violates fewer statistical assumptions relative to other metrics when comparing groups of researchers, and can be easily modified to remove inherent gender biases in citation data. We demonstrate the utility of the ε′-index using a sample of 480 researchers with Google Scholar profiles, stratified evenly into eight disciplines (archaeology, chemistry, ecology, evolution and development, geology, microbiology, ophthalmology, palaeontology), three career stages (early, mid-, late-career), and two genders. We advocate the use of theε′-index whenever assessors must compare research performance among researchers of different backgrounds, but emphasise that no single index should be used exclusively to rank researcher capability.