Evolutionary Genomics of High Fecundity.

Natural highly fecund populations abound. These range from viruses to gadids. Many highly fecund populations are economically important. Highly fecund populations provide an important contrast to the low-fecundity organisms that have traditionally been applied in evolutionary studies. A key question regarding high fecundity is whether large numbers of offspring are produced on a regular basis, by few individuals each time, in a sweepstakes mode of reproduction. Such reproduction characteristics are not incorporated into the classical Wright-Fisher model, the standard reference model of population genetics, or similar types of models, in which each individual can produce only small numbers of offspring relative to the population size. The expected genomic footprints of population genetic models of sweepstakes reproduction are very different from those of the Wright-Fisher model. A key, immediate issue involves identifying the footprints of sweepstakes reproduction in genomic data. Whole-genome sequencing data can be used to distinguish the patterns made by sweepstakes reproduction from the patterns made by population growth in a population evolving according to the Wright-Fisher model (or similar models). If the hypothesis of sweepstakes reproduction cannot be rejected, then models of sweepstakes reproduction and associated multiple-merger coalescents will become at least as relevant as the Wright-Fisher model (or similar models) and the Kingman coalescent, the cornerstones of mathematical population genetics, in further discussions of evolutionary genomics of highly fecund populations.

Fear of predators in free-living wildlife reduces population growth over generations.

Correctly assessing the total impact of predators on prey population growth rates (lambda, λ) is critical to comprehending the importance of predators in species conservation and wildlife management. Experiments over the past decade have demonstrated that the fear (antipredator responses) predators inspire can affect prey fecundity and early offspring survival in free-living wildlife, but recent reviews have highlighted the absence of evidence experimentally linking such effects to significant impacts on prey population growth. We experimentally manipulated fear in free-living wild songbird populations over three annual breeding seasons by intermittently broadcasting playbacks of either predator or nonpredator vocalizations and comprehensively quantified the effects on all the components of population growth, together with evidence of a transgenerational impact on offspring survival as adults. Fear itself significantly reduced the population growth rate (predator playback mean λ = 0.91, 95% CI = 0.80 to 1.04; nonpredator mean λ = 1.06, 95% CI = 0.96 to 1.16) by causing cumulative, compounding adverse effects on fecundity and every component of offspring survival, resulting in predator playback parents producing 53% fewer recruits to the adult breeding population. Fear itself was consequently projected to halve the population size in just 5 years, or just 4 years when the evidence of a transgenerational impact was additionally considered (λ = 0.85). Our results not only demonstrate that fear itself can significantly impact prey population growth rates in free-living wildlife, comparing them with those from hundreds of predator manipulation experiments indicates that fear may constitute a very considerable part of the total impact of predators.

Temperature dependence of competitive ability is cold-shifted compared to that of growth rate in marine phytoplankton.

The effect of climate warming on community composition is expected to be contingent on competitive outcomes, yet approaches to projecting ecological outcomes often rely on measures of density-independent performance across temperatures. Recent theory suggests that the temperature response of competitive ability differs in shape from that of population growth rate. Here, we test this hypothesis empirically and find thermal performance curves of competitive ability in aquatic microorganisms to be systematically left-shifted and flatter compared to those of exponential growth rate. The minimum resource requirement for growth, R*-an inverse indicator of competitive ability-changes with temperature following a U-shaped pattern in all four species tested, contrasting from their left-skewed density-independent growth rate thermal performance curves. Our results provide new evidence that exploitative competitive success is highest at temperatures that are sub-optimal for growth, suggesting performance estimates of density-independent variables might underpredict performance in cooler competitive environments.

A framework for understanding climate change impacts through non-compensatory intra- and interspecific climate change responses.

Understanding and predicting population responses to climate change is a crucial challenge. A key component of population responses to climate change are cases in which focal biological rates (e.g., population growth rates) change in response to climate change due to non-compensatory effects of changes in the underlying components (e.g., birth and death rates) determining the focal rates. We refer to these responses as non-compensatory climate change effects. As differential responses of biological rates to climate change have been documented in a variety of systems and arise at multiple levels of organization within and across species, non-compensatory effects may be nearly ubiquitous. Yet, how non-compensatory climate change responses combine and scale to influence the demographics of populations is often unclear and requires mapping them to the birth and death rates underlying population change. We provide a flexible framework for incorporating non-compensatory changes in upstream rates within and among species and mapping their consequences for additional downstream rates across scales to their eventual effects on population growth rates. Throughout, we provide specific examples and potential applications of the framework. We hope this framework helps to enhance our understanding of and unify research on population responses to climate change.

Acclimation to warmer temperatures can protect host populations from both further heat stress and the potential invasion of pathogens.

Thermal acclimation can provide an essential buffer against heat stress for host populations, while acting simultaneously on various life-history traits that determine population growth. In turn, the ability of a pathogen to invade a host population is intimately linked to these changes via the supply of new susceptible hosts, as well as the impact of warming on its immediate infection dynamics. Acclimation therefore has consequences for hosts and pathogens that extend beyond simply coping with heat stress-governing both population growth trajectories and, as a result, an inherent propensity for a disease outbreak to occur. The impact of thermal acclimation on heat tolerances, however, is rarely considered simultaneously with metrics of both host and pathogen population growth, and ultimately fitness. Using the host Daphnia magna and its bacterial pathogen, we investigated how thermal acclimation impacts host and pathogen performance at both the individual and population scales. We first tested the effect of maternal and direct thermal acclimation on the life-history traits of infected and uninfected individuals, such as heat tolerance, fecundity, and lifespan, as well as pathogen infection success and spore production. We then predicted the effects of each acclimation treatment on rates of host and pathogen population increase by deriving a host's intrinsic growth rate (rm) and a pathogen's basic reproductive number (R0). We found that direct acclimation to warming enhanced a host's heat tolerance and rate of population growth, despite a decline in life-history traits such as lifetime fecundity and lifespan. In contrast, pathogen performance was consistently worse under warming, with within-host pathogen success, and ultimately the potential for disease spread, severely hampered at higher temperatures. Our results suggest that hosts could benefit more from warming than their pathogens, but only by linking multiple individual traits to population processes can the full impact of higher temperatures on host and pathogen population dynamics be realised.

Exact confidence intervals for population growth rate, longevity and generation time.

By quantifying key life history parameters in populations, such as growth rate, longevity, and generation time, researchers and administrators can obtain valuable insights into its dynamics. Although point estimates of demographic parameters have been available since the inception of demography as a scientific discipline, the construction of confidence intervals has typically relied on approximations through series expansions or computationally intensive techniques. This study introduces the first mathematical expression for calculating confidence intervals for the aforementioned life history traits when individuals are unidentifiable and data are presented as a life table. The key finding is the accurate estimation of the confidence interval for r, the instantaneous growth rate, which is tested using Monte Carlo simulations with four arbitrary discrete distributions. In comparison to the bootstrap method, the proposed interval construction method proves more efficient, particularly for experiments with a total offspring size below 400. We discuss handling cases where data are organized in extended life tables or as a matrix of vital rates. We have developed and provided accompanying code to facilitate these computations.

The impact of boldness on demographic rates and life-history outcomes in the wandering albatross.

Differences among individuals within a population are ubiquitous. Those differences are known to affect the entire life cycle with important consequences for all demographic rates and outcomes. One source of among-individual phenotypic variation that has received little attention from a demographic perspective is animal personality, which is defined as consistent and heritable behavioural differences between individuals. While many studies have shown that individual variation in individual personality can generate individual differences in survival and reproductive rates, the impact of personality on all demographic rates and outcomes remains to be assessed empirically. Here, we used a unique, long-term, dataset coupling demography and personality of wandering albatross (Diomedea exulans) in the Crozet Archipelago and a comprehensive analysis based on a suite of approaches (capture-mark-recapture statistical models, Markov chains models and structured matrix population models). We assessed the effect of boldness on annual demographic rates (survival, breeding probability, breeding success), life-history outcomes (life expectancy, lifetime reproductive outcome, occupancy times), and an integrative demographic outcome (population growth rate). We found that boldness had little impact on female demographic rates, but was very likely associated with lower breeding probabilities in males. By integrating the effects of boldness over the entire life cycle, we found that bolder males had slightly lower lifetime reproductive success compared to shyer males. Indeed, bolder males spent a greater proportion of their lifetime as non-breeders, which suggests longer inter-breeding intervals due to higher reproductive allocation. Our results reveal that the link between boldness and demography is more complex than anticipated by the pace-of-life literature and highlight the importance of considering the entire life cycle with a comprehensive approach when assessing the role of personality on individual performance and demography.

National Population Growth Rate, Its Components, and Subnational Contributions: A Research Note.

A population's current growth rate is determined jointly by changes in fertility, mortality, and migration. This overall growth rate is also the average of age-specific growth rates, which can be decomposed into the result of historical changes in fertility, mortality, and migration. However, doing so requires more than 100 years of historical data, meaning that such analyses are possible only in a select few populations. In this research note, we propose an adapted version of the variable-r model to measure contributions to the population growth rate for countries with shorter demographic series. In addition, we extend this model to explore the contribution of subnational changes to the national population growth rate. Our results demonstrate that the age-specific growth rates obtained from short historical series, say 25 years, closely match those of the longer series. These abbreviated age-specific growth rates closely resemble the growth rate at birth of their respective cohorts, which is the major determinant of population growth, except at older ages where mortality becomes the main explanatory element. Exploring subnational populations, we find considerable heterogeneity in the age profile of the components of growth and find that the most populous regions tend to have an outsized impact on national-level growth.

The 8 billion milestone: Risk perceptions of global population growth among UK and US residents.

In November 2022, the global human population reached 8 billion and is projected to reach 10 billion by 2060. Theories, models, and evidence indicate that global population growth (GPG) increases the likelihood of many adverse outcomes, such as biodiversity loss, climate change, mass migrations, wars, and resource shortages. A small body of research indicates that many individuals are concerned about the effects of GPG, and these concerns are strongly related to the willingness to engage in mitigative and preventative actions. However, scientific understanding of the factors that influence GPG risk perceptions remains limited. To help address this research gap, we conducted a study of the perceived risk of GPG among UK and US residents (N = 1029) shortly after the "8 billion milestone." Our results confirmed that GPG is perceived as a moderate-to-high risk and these perceptions have a strong positive relationship with the willingness to engage in and support risk management actions. Our participants believed that the worst effects of GPG were yet to come but would largely be geographically and socially remote. Despite their willingness to engage in risk management actions, our participants reported low self-efficacy and that governments (cf. individuals and communities) have the greatest capacity to influence GPG. Risk perceptions were strongly predicted by worldviews and were higher among our UK (cf. US) participants. We also found that the perceived benefits of GPG were low and found no evidence to suggest that risk perceptions were affected by exposure to media coverage of the 8 billion milestone.

Faster-growing parasites threaten host populations via patch-level population dynamics and higher virulence; a case study in Varroa mites (Mesostigmata: Varroidae) and honey bees (Hymenoptera: Apidae).

Honey bee parasites remain a critical challenge to management and conservation. Because managed honey bees are maintained in colonies kept in apiaries across landscapes, the study of honey bee parasites allows the investigation of spatial principles in parasite ecology and evolution. We used a controlled field experiment to study the relationship between population growth rate and virulence (colony survival) of the parasite Varroa destructor (Anderson and Trueman). We used a nested design of 10 patches (apiaries) of 14 colonies to examine the spatial scale at which Varroa population growth matters for colony survival. We tracked Varroa population size and colony survival across a full year and found that Varroa populations that grow faster in their host colonies during the spring and summer led to larger Varroa populations across the whole apiary (patch) and higher rates of neighboring colony loss. Crucially, this increased colony loss risk manifested at the patch scale, with mortality risk being related to spatial adjacency to colonies with fast-growing Varroa strains rather than with Varroa growth rate in the colony itself. Thus, within-colony population growth predicts whole-apiary virulence, demonstrating the need to consider multiple scales when investigating parasite growth-virulence relationships.

The Ethics of Population Policy for the Two Worlds of Population Conditions.

Population policy has taken two divergent trajectories. In the developing part of the world, controlling population growth has been a major tune of the debate more than a half-century ago. In the more developed part of the world, an inverse pattern results in the discussion over the facilitation of population growth. The ethical debates on population policy have primarily focused on the former and ignored the latter. This paper proposes a more comprehensive account that justifies states' population policy interventions. We first consider the reasons that support pro-natalist policies to enhance fertility rates and argue that these policies are ethically problematic. We then establish an ethics of population policy grounded on account of self-sustaining the body politic, which consists of four criteria: survival, replacement, accountability, and solidarity. We discuss the implications of this account regarding birth-control and pro-natalist policies, as well as non-procreative policies such as immigration, adoption, and unintended baby-saving strategies.

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.

Compensatory responses of vital rates attenuate impacts of competition on population growth and promote coexistence.

Competition is among the most important factors regulating plant population and community dynamics, but we know little about how different vital rates respond to competition and jointly determine population growth and species coexistence. We conducted a field experiment and parameterised integral projection models to model the population growth of 14 herbaceous plant species in the absence and presence of neighbours across an elevation gradient (284 interspecific pairs). We found that suppressed individual growth and seedling establishment contributed the most to competition-induced declines in population growth, although vital rate contributions varied greatly between species and with elevation. In contrast, size-specific survival and flowering probability and seed production were frequently enhanced under competition. These compensatory vital rate responses were nearly ubiquitous (occurred in 92% of species pairs) and significantly reduced niche overlap and stabilised coexistence. Our study highlights the importance of demographic processes for regulating population and community dynamics, which has often been neglected by classic coexistence theories.

Amplified Cyclicality in Mast Seeding Dynamics Positively Influences the Dynamics of a Seed Consumer Species.

AbstractTemporal autocorrelation in environmental conditions influences population dynamics through its effects on vital rates. However, a comprehensive understanding of how and to what extent temporal autocorrelation shapes population dynamics is still lacking because most empirical studies have unrealistically assumed that environmental conditions are temporally independent. Mast seeding is a biological event characterized by highly fluctuating and synchronized seed production at the tree population scale as well as a marked negative temporal autocorrelation. In the current context of global change, mast seeding events are expected to become more frequent, leading to strengthened negative temporal autocorrelations and thereby amplified cyclicality in mast seeding dynamics. Theory predicts that population growth rates are maximized when the environmental cyclicality of consumer resources and their generation times are closely matched. To test this prediction, we took advantage of the long-term monitoring of a wild boar population, a widespread seed consumer species characterized by a short generation time (∼2 years). As expected, simulations indicated that its stochastic population growth rate increased as mast seeding dynamics became more negatively autocorrelated. Our findings demonstrate that accounting for temporal autocorrelations in environmental conditions relative to the generation time of the focal population is required, especially under conditions of global warming, where the cyclicality in resource dynamics is likely to change.

Internal cues for optimizing reproduction in a varying environment.

In varying environments, it is beneficial for organisms to utilize available cues to infer the conditions they may encounter and express potentially favourable traits. However, external cues can be unreliable or too costly to use. We consider an alternative strategy where organisms exploit internal sources of information. Even without sensing environmental cues, their internal states may become correlated with the environment as a result of selection, which then form a memory that helps predict future conditions. To demonstrate the adaptive value of such internal cues in varying environments, we revisit the classic example of seed dormancy in annual plants. Previous studies have considered the germination fraction of seeds and its dependence on environmental cues. In contrast, we consider a model of germination fraction that depends on the seed age, which is an internal state that can serve as a memory. We show that, if the environmental variation has temporal structure, then age-dependent germination fractions will allow the population to have an increased long-term growth rate. The more the organisms can remember through their internal states, the higher the growth rate a population can potentially achieve. Our results suggest experimental ways to infer internal memory and its benefit for adaptation in varying environments.

Taylor's law for exponentially growing local populations linked by migration.

We consider the dynamics of a collection of n>1 populations in which each population has its own rate of growth or decay, fixed in continuous time, and migrants may flow from one population to another over a fixed network, at a rate, fixed over time, times the size of the sending population. This model is represented by an ordinary linear differential equation of dimension n with constant coefficients arrayed in an essentially nonnegative matrix. This paper identifies conditions on the parameters of the model (specifically, conditions on the eigenvalues and eigenvectors) under which the variance of the n population sizes at a given time is asymptotically (as time increases) proportional to a power of the mean of the population sizes at that given time. A power-law variance function is known in ecology as Taylor's Law and in physics as fluctuation scaling. Among other results, we show that Taylor's Law holds asymptotically, with variance asymptotically proportional to the mean squared, on an open dense subset of the class of models considered here.

Supply of obstetrician-gynecologists and gynecologic oncologists to the US Medicare population: a state-by-state analysis.

BACKGROUND: The supply of obstetrician-gynecologists and gynecologic oncologists across the United States has been described. However, these studies focused on reproductive-age patients and did not assess the growing demand for services to the advanced-age female population. OBJECTIVE: This study aimed to evaluate the supply of obstetrician-gynecologists and gynecologic oncologists who serve the US Medicare population per 100,000 female Medicare beneficiaries, over time and by state and region. STUDY DESIGN: The supply of obstetrician-gynecologists and gynecologic oncologists was extracted from the Physician and Other Supplier Public Use File database of Medicare Part B claims submitted to the US Centers for Medicare & Medicaid Services. Data were only available from 2012 to 2019. The supply of providers was divided by the number of original female Medicare beneficiaries obtained from the Kaiser Family Foundation; all values reported are providers per 100,000 female beneficiaries by state. Trends over time were assessed as the difference in provider-to-beneficiary ratio and the percentage change from 2012 to 2019. All data were collected in 2021. All analyses were performed with SAS, version 9.4. This study was exempt from institutional review board approval. RESULTS: In 2019, the average number of obstetrician-gynecologists per 100,000 female beneficiaries across all states was 121.32 (standard deviation±33.03). The 3 states with the highest obstetrician-gynecologist-to-beneficiary ratio were the District of Columbia (268.85), Connecticut (204.62), and Minnesota (171.60), and the 3 states with the lowest were Montana (78.37), West Virginia (82.28), and Iowa (83.92). The average number of gynecologic oncologists was 4.48 (standard deviation±2.08). The 3 states with the highest gynecologic oncologist-to-beneficiary ratio were the District of Columbia (11.30), Rhode Island (10.58), and Connecticut (9.24), and the 3 states with the lowest were Kansas (0.82), Vermont (1.41), and Mississippi (1.47). The number of obstetrician-gynecologists per 100,000 female beneficiaries decreased nationally by 8.4% from 2012 to 2019; the difference in provider-to-beneficiary ratio from 2012 to 2019 ranged from +29.97 (CT) to -82.62 (AK). Regionally, the Northeast had the smallest decrease in the number of obstetrician-gynecologists per 100,000 female beneficiaries (-3.8%) and the West had the largest (-18.2%). The number of gynecologic oncologists per 100,000 female beneficiaries increased by 7.0% nationally during the study period; this difference ranged from +8.96 (DC) to -3.39 (SD). Overall, the West had the smallest increase (4.7%) and the Midwest had the largest (15.4%). CONCLUSION: There is wide geographic variation in the supply and growth rate of obstetrician-gynecologists and gynecologic oncologists for the female Medicare population. This analysis provides insight into areas of the country where the supply of obstetrician-gynecologists and gynecologic oncologists may not meet current and future demand. The national decrease in the number of obstetrician-gynecologists is alarming, especially because population projections estimate that the proportion of elderly female patients will grow. Future work is needed to determine why fewer providers are available to see Medicare patients and what minimum provider-to-enrollee ratios are needed for gynecologic and cancer care. Once such ratios are established, our results can help determine whether specific states and regions are meeting demand. Additional research is needed to assess the effect of the COVID-19 pandemic on the supply of women's health providers.

Definitions of parasitism, considering its potentially opposing effects at different levels of hierarchical organization.

An annotated synthesis of textbook definitions of parasitism is presented. Most definitions declare parasitism is a long-lasting relationship between individuals of different species harming the hosts. The infection-induced costs are interpreted as diseases in the medical-veterinary literature. Alternatively, evolutionary ecologists interpret it as a reduction of host's fitness (longevity, fertility or both). Authors often assume that such effects decrease host population growth and select for antiparasitic defences, which is not necessarily true because infections may simultaneously express opposite effects at different levels of biological organization. (i) At the cellular level, infection-induced cell growth, longevity and multiplication may yield tumours maladaptive at higher levels. (ii) At the individual level, reduced host longevity, fertility or both are interpreted as disease symptoms or reduced fitness. (iii) Contrary to common sense, the growth rate of infected host lineages may increase in parallel with the individuals' reduced survival and fertility. This is because selection favours not only the production of more offspring but also their faster production. (iv) Finally, infections that reduce host individuals' or lineages' fitness may still increase infected host populations' growth rate in the context of ecological competition. Therefore, differences between parasitism and mutualism may depend on which level of organization one focuses on.

Formation and Growth of Co-Culture Tumour Spheroids: New Compartment-Based Mathematical Models and Experiments.

Co-culture tumour spheroid experiments are routinely performed to investigate cancer progression and test anti-cancer therapies. Therefore, methods to quantitatively characterise and interpret co-culture spheroid growth are of great interest. However, co-culture spheroid growth is complex. Multiple biological processes occur on overlapping timescales and different cell types within the spheroid may have different characteristics, such as differing proliferation rates or responses to nutrient availability. At present there is no standard, widely-accepted mathematical model of such complex spatio-temporal growth processes. Typical approaches to analyse these experiments focus on the late-time temporal evolution of spheroid size and overlook early-time spheroid formation, spheroid structure and geometry. Here, using a range of ordinary differential equation-based mathematical models and parameter estimation, we interpret new co-culture experimental data. We provide new biological insights about spheroid formation, growth, and structure. As part of this analysis we connect Greenspan's seminal mathematical model to co-culture data for the first time. Furthermore, we generalise a class of compartment-based spheroid mathematical models that have previously been restricted to one population so they can be applied to multiple populations. As special cases of the general model, we explore multiple natural two population extensions to Greenspan's seminal model and reveal biological mechanisms that can describe the internal dynamics of growing co-culture spheroids and those that cannot. This mathematical and statistical modelling-based framework is well-suited to analyse spheroids grown with multiple different cell types and the new class of mathematical models provide opportunities for further mathematical and biological insights.

Biotic and anthropogenic forces rival climatic/abiotic factors in determining global plant population growth and fitness.

Multiple, simultaneous environmental changes, in climatic/abiotic factors, interacting species, and direct human influences, are impacting natural populations and thus biodiversity, ecosystem services, and evolutionary trajectories. Determining whether the magnitudes of the population impacts of abiotic, biotic, and anthropogenic drivers differ, accounting for their direct effects and effects mediated through other drivers, would allow us to better predict population fates and design mitigation strategies. We compiled 644 paired values of the population growth rate (λ) from high and low levels of an identified driver from demographic studies of terrestrial plants. Among abiotic drivers, natural disturbance (not climate), and among biotic drivers, interactions with neighboring plants had the strongest effects on λ However, when drivers were combined into the 3 main types, their average effects on λ did not differ. For the subset of studies that measured both the average and variability of the driver, λ was marginally more sensitive to 1 SD of change in abiotic drivers relative to biotic drivers, but sensitivity to biotic drivers was still substantial. Similar impact magnitudes for abiotic/biotic/anthropogenic drivers hold for plants of different growth forms, for different latitudinal zones, and for biomes characterized by harsher or milder abiotic conditions, suggesting that all 3 drivers have equivalent impacts across a variety of contexts. Thus, the best available information about the integrated effects of drivers on all demographic rates provides no justification for ignoring drivers of any of these 3 types when projecting ecological and evolutionary responses of populations and of biodiversity to environmental changes.