Some neo-Malthusians regard fertility as being kept in check by scarcities and constraints and, conversely, as being raised by economic prosperity. Since out-migration to developed countries and the receipt of food aid from developed countries relax the constraints imposed by a country’s carrying capacity, both will have a positive effect on fertility rates in developing countries. Moreover, better economic prospects will also raise fertility, all other things equal. This article provides an empirical test of these hypotheses derived from a neo-Malthusian theory of fertility change. The results fail to confirm the theory and often contradict it.

Speed of life and reproductive strategy form the two major axes that organize variation in life history strategies across plant and animal species. The position of a species along these axes can inform on their sensitivity to environmental change. This provides a tantalizing link between sets of traits and population responses to change, contained in a highly generalizable theoretical framework. The underlying mechanisms are assumed to be governed by life history tradeoffs at the individual level. Examples include the tradeoff between current and future reproductive success, and investing energy into growth versus reproduction. But the importance of such tradeoffs in structuring population-level responses to environmental change remains understudied. We aim to increase our understanding of the link between individual-level life history tradeoffs and the structuring of life history strategies across species, and if they link to population responses to environmental change. We find that the classical association between life history strategies and population responses to environmental change breaks down when accounting for individual-level tradeoffs and reproductive decisions. Projecting population responses to environmental change can therefore not always be inferred based on a limited set of species traits alone. We summarize our perspective and a way forward in a conceptual framework.

Supplementary Materials for the paper "Why did foraging, horticulture and pastoralism persist after the Neolithic demographic transition? The Oasis Theory of agricultural intensification"

Populations declining toward extinction can persist via genetic adaptation in a process called evolutionary rescue. Predicting evolutionary rescue has applications ranging from conservation biology to medicine, but requires understanding and integrating the multiple effects of a stressful environmental change on population processes. Here we derive a simple expression for how generation time, a key determinant of the rate of evolution, varies with population size during evolutionary rescue. Change in generation time is quantitatively predicted by comparing how intraspecific competition and the source of maladaptation each affect the rates of births and deaths in the population. Depending on the difference between two parameters quantifying these effects, the model predicts that populations may experience substantial changes in their rate of adaptation in both positive and negative directions, or adapt consistently despite severe stress. These predictions were then tested by comparison to the results of individual-based simulations of evolutionary rescue, which validated that the tolerable rate of environmental change varied considerably as described by analytical results. We discuss how these results inform efforts to understand wildlife disease and adaptation to climate change, evolution in managed populations, and treatment resistance in pathogens.

As thermal regimes change worldwide, projections of future population and species persistence often require estimates of how population growth rates depend on temperature. These projections rarely account for how temporal variation in temperature can systematically modify growth rates relative to projections based on constant temperatures. Here,we tested the hypothesis that time-averaged population growth rates in fluctuating thermal environments differ from growth rates in constant conditions as a consequence of Jensen's inequality, and that the thermal performance curves (TPCs) describing population growth in fluctuating environments can be predicted quantitatively based on TPCs generated in constant lab conditions. With experimental populations of the green alga Tetraselmis tetrahele, we show that nonlinear averaging techniques accurately predicted increased as well as decreased population growth rates influctuating thermal regimes relative to constant thermal regimes. We extrapolate from these results to project critical temperatures for population growth and persistence of 89 phytoplankton species in naturally variable thermal environments. These results advance our ability to predict population dynamics in the context of global change.

Population growth in the next half-century is on pace to raise global carbon emissions by half. Carbon emissions are associated with fertility as a by-product of somatic and parental investment, which is predicted to involve time orientation/preference as a mediating psychological mechanism. Here, we draw upon life-history theory (LHT) to investigate associations between future orientation and fertility, and their impacts on carbon emissions. We argue ‘K-strategy’ life history (LH) in high-income countries has resulted in parental investment behaviours involving future orientation that, paradoxically, promote unsustainable carbon emissions, thereby lowering the Earth's K or carrying capacity. Increasing the rate of approach towards this capacity are ‘r-strategy’ LHs in low-income countries that promote population growth. We explore interactions between future orientation and development that might slow the rate of approach towards global K. Examination of 67 000 individuals across 75 countries suggests that future orientation interacts with the relationship between environmental risk and fertility and with development related parental investment, particularly investment in higher education, to slow population growth and mitigate per capita carbon emissions. Results emphasize that LHT will be an important tool in understanding the demographic and consumption patterns that drive anthropogenic climate change.

Not many studies have documented climate and air quality changes of settlements at early stages of development. This is because high quality climate and air quality records are deficient for the periods of the early 18th century to mid 20th century when many U.S. cities were formed and grew. Dramatic landscape change induces substantial local climate change during the incipient stage of development. Rapid growth along the urban fringe in Phoenix, coupled with a fine-grained climate monitoring system, provide a unique opportunity to study the climate impacts of urban development as it unfolds. Generally, heat islands form, particularly at night, in proportion to city population size and morphological characteristics. Drier air is produced by replacement of the countryside's moist landscapes with dry, hot urbanized surfaces. Wind is increased due to turbulence induced by the built-up urban fabric and its morphology; although, depending on spatial densities of buildings on the land, wind may also decrease. Air quality conditions are worsened due to increased city emissions and surface disturbances. Depending on the diversity of microclimates in pre-existing rural landscapes and the land-use mosaic in cities, the introduction of settlements over time and space can increase or decrease the variety of microclimates within and near urban regions. These differences in microclimatic conditions can influence variations in health, ecological, architectural, economic, energy and water resources, and quality-of-life conditions in the city. Therefore, studying microclimatic conditions which change in the urban fringe over time and space is at the core of urban ecological goals as part of LTER aims. In analyzing Phoenix and Baltimore long-term rural/urban weather and climate stations, Brazel et al. (In progress) have discovered that long-term (i.e., 100 years) temperature changes do not correlate with populations changes in a linear manner, but rather in a third-order nonlinear response fashion. This nonlinear temporal change is consistent with the theories in boundary layer climatology that describe and explain the leading edge transition and energy balance theory. This pattern of urban vs. rural temperature response has been demonstrated in relation to spatial range of city sizes (using population data) for 305 rural vs. urban climate stations in the U.S. Our recent work on the two urban LTER sites has shown that a similar climate response pattern also occurs over time for climate stations that were initially located in rural locations have been overrun bu the urban fringe and subsequent urbanization (e.g., stations in Baltimore, Mesa, Phoenix, and Tempe). Lack of substantial numbers of weather and climate stations in cities has previously precluded small-scale analyses of geographic variations of urban climate, and the links to land-use change processes. With the advent of automated weather and climate station networks, remote-sensing technology, land-use history, and the focus on urban ecology, researchers can now analyze local climate responses as a function of the details of land-use change. Therefore, the basic research question of this study is: How does urban climate change over time and space at the place of maximum disturbance on the urban fringe? Hypotheses 1. Based on the leading edge theory of boundary layer climate change, largest changes should occur during the period of peak development of the land when land is being rapidly transformed from open desert and agriculture to residential, commercial, and industrial uses. 2. One would expect to observe, on average and on a temporal basis (several years), nonlinear temperature and humidity alterations across the station network at varying levels of urban development. 3. Based on past research on urban climate, one would expect to see in areas of the urban fringe, rapid changes in temperature (increases at night particularly), humidity (decreases in areas from agriculture to urban; increases from desert to urban), and wind speed (increases due to urban heating). 4. Changes of the surface climate on the urban fringe are expected to be altered as a function of various energy, moisture, and momentum control parameters, such as albedo, surface moisture, aerodynamic surface roughness, and thermal admittance. These parameters relate directly to population and land-use change (Lougeay et al. 1996).

The data collection contains population projections for UK ethnic groups and all local area by age (single year of age up to 100+) and sex. Included in the data set are also input data to the cohort component model that was used to project populations into the future-fertility rates, mortality rates, international migration flows and internal migration probabilities. Also included in data set are output data: Number of deaths, births and internal migrants. All data included are for the years 2011 to 2061. We have produced two ethnic population projections for UK local authorities, based on information on 2011 Census ethnic populations and 2010-2011-2012 ethnic components. Both projections align fertility and mortality assumptions to ONS assumptions. Where they differ is in the migration assumptions. In LEEDS L1 we employ internal migration rates for 2001 to 2011, including periods of boom and bust. We use a new assumption about international migration anticipating that the UK may leave the EU (BREXIT). In LEEDS L2 we use average internal migration rates for the 5 year period 2006-11 and the official international migration flow assumptions with a long term balance of +185 thousand per annum.

This project aims to understand and to forecast the ethnic transition in the United Kingdom's population at national and sub-national levels. The ethnic transition is the change in population composition from one dominated by the White British to much greater diversity. In the decade 2001-2011 the UK population grew strongly as a result of high immigration, increased fertility and reduced mortality. Both the Office for National Statistics (ONS) and Leeds University estimated the growth or decline in the sixteen ethnic groups making up the UK's population in 2001. The 2011 Census results revealed that both teams had over-estimated the growth of the White British population and under-estimated the growth of the ethnic minority populations. The wide variation between our local authority projected populations in 2011 and the Census suggested inaccurate forecasting of internal migration. We propose to develop, working closely with ONS as our first external partner, fresh estimates of mid-year ethnic populations and their components of change using new data on the later years of the decade and new methods to ensure the estimates agree in 2011 with the Census. This will involve using population accounting theory and an adjustment technique known as iterative proportional fitting to generate a fully consistent set of ethnic population estimates between 2001 and 2011.

We will study, at national and local scales, the development of demographic rates for ethnic group populations (fertility, mortality, internal migration and international migration). The ten year time series of component summary indicators and age-specific rates will provide a basis for modelling future assumptions for projections. We will, in our main projection, align the assumptions to the ONS 2012-based principal projection. The national assumptions will need conversion to ethnic groups and to local scale. The ten years of revised ethnic-specific component rates will enable us to study the relationships between national and local demographic trends. In addition, we will analyse a consistent time series of local authority internal migration. We cannot be sure, at this stage, how the national-local relationships for each ethnic group will be modelled but we will be able to test our models using the time series.

Of course, all future projections of the population are uncertain. We will therefore work to measure the uncertainty of component rates. The error distributions can be used to construct probability distributions of future populations via stochastic projections so that we can define confidence intervals around our projections. Users of projections are always interested in the impact of the component assumptions on future populations. We will run a set of reference projections to estimate the magnitude and direction of impact of international migrations assumptions (net effect of immigration less emigration), of internal migration assumptions (the net effect of in-migration less out-migration), of fertility assumptions compared with replacement level, of mortality assumptions compared with no change and finally the effect of the initial age distribution (i.e. demographic potential).

The outputs from the project will be a set of technical reports on each aspect of the research, journal papers submitted for peer review and a database of projection inputs and outputs available to users via the web. The demographic inputs will be subject to quality assurance by Edge Analytics, our second external partner. They will also help in disseminating these inputs to local government users who want to use them in their own ethnic projections. In sum, the project will show how a wide range of secondary data sources can be used in theoretically refined demographic...

The current extinction and climate change crises pressure us to predict population dynamics with ever-greater accuracy. Although predictions rest on the well-advanced theory of age-structured populations, two key issues remain poorly-explored. Specifically, how the age-dependency in demographic rates and the year-to-year interactions between survival and fecundity affect stochastic population growth rates. We use inference, simulations, and mathematical derivations to explore how environmental perturbations determine population growth rates for populations with different age-specific demographic rates and when ages are reduced to stages. We find that stage- vs. age-based models can produce markedly divergent stochastic population growth rates. The differences are most pronounced when there are survival-fecundity-trade-offs, which reduce the variance in the population growth rate. Finally, the expected value and variance of the stochastic growth rates of populations with different age-specific demographic rates can diverge to the extent that, while some populations may thrive, others will inevitably go extinct.

These codes were produced by Amy Hurford (ahurford@mun.ca) and Christina Cobbold.Below is a list of all the figures in the manuscript paired with the code that produces them. These codes run on MATLAB. Import sections of code are repeated across files with small changes.Figure 1 - Figure1_Defins.m (dependency on subtightplot.m)Figure 2 - Figure2_Niches.mFigure 3 - Figure3_DensitySkewness.m (dependency on subtightplot.m)Figure 4 - Figure4_MainResults.m (dependency on EffectOf.m)Figures S1 and S2 - FigureS1_S2.mFigures S3-S5 - FiguresS3S4S5.mFigure S6 - FigureS6_ExtinctionDebt.mFigure S7 - FigureS7_Dispersal.m (dependency on EffectOfD.m)Figure S8 - FigureS8_AssymetricDispersal.m (dependency on EffectOf3.m)Figure S9, S10 and S12 - Figure4_MainResults.m (dependency on EffectOf.m)Figure S11 - FigureS11_CCEliminatesCycles.mFigures S13 and S14 - FiguresS13S14_Stochastic.m (depency on EffectOfS.m)——————————EffectOf.m - performs the calculations for Figure4_MainResults.mEffectOfD.m - performs the calculations for FigureS7_Dispersal.mEffectOf3.m - performs the calculations for FigureS8_AssymetricDispersal.m EffectOfS.m - performs the calculations for FiguresS13S14_Stochastic.msubtightplot.m - controls the spacing of subpanels in plots.

Metapopulation theory posits that suitable habitat may frequently be unoccupied because it is isolated and has never been colonized or has been colonized followed by local extinction and has not yet been recolonized. This research addresses the question of how to identify suitable, unoccupied habitat and distinguish it from unsuitable habitat. We are studying a group of six species of forest understory herbs chosen to represent a broad range of habitat distribution and dispersal characteristics. Our aim is to quantify the fundamental niche of these species (sensu Hutchinson 1957), in terms of variables such as soil moisture and temperature, by developing a set of habitat specific demographic stage transition models (i.e. conditional on such environmental variables) for these species. These models, in combination with data from field surveys of the local distribution of the species, will be used to develop testable predictive maps of the distribution of suitable habitat which can be compared to the observed distribution of the plants. We hypothesize that both dispersal ability and the distribution of suitable habitat are important determinants of the actual distribution of species. The goal of this research is both to further our conceptual understanding of the relationships between habitat requirements and species distributions, and to provide a practical approach to operationalizing the concept of "suitable habitat."

Body size often strongly covaries with demography across species. Metabolism has long been invoked as the driver of these patterns but tests of causal links between size, metabolism and demography within a species are exceedingly rare. We used 400 generations of artificial selection to evolve a 2427% size difference in the microalga Dunaliella tertiolecta. We repeatedly measured size, energy fluxes and demography across the evolved lineages. Then, we used standard metabolic theory to generate predictions of how size and demography should covary based on the scaling of energy fluxes that we measured. The size-dependency of energy remained relatively consistent in time, but metabolic theory failed to predict demographic rates, which varied unpredictably in strength and even sign across generations. Classic theory holds that size affects demography via metabolism – our results suggest that both metabolism and size act separately to drive demography and that among-species patterns may not predict within-species processes.

Estimating the population size of Marbled Murrelets with distance sampling.

Sexual selection and the evolution of costly mating strategies can negatively impact population demography and adaptive potential. While laboratory studies have documented outcomes stemming from these processes, theory suggests that the demographic impact of sexual selection is contingent on the environment and therefore may have been overestimated in simple laboratory settings. Here we find support for this claim. We exposed copies of beetle lines, previously evolved with or without sexual selection, to a 10-generation heatwave while maintaining half of them in a simple environment and the other half in a complex environment. Populations with an evolutionary history of sexual selection maintained larger sizes and more stable growth rates in complex (relative to simple) environments, an effect not seen in populations that evolved without sexual selection. These results have implications for evolutionary forecasting and suggest that the demographic impact of sexual selection in natural p...

The project, based at the University of Greenwich, UK and Stellenbosch University, South Africa, aimed to examine epidemiologic transitions by identifying and quantifying the drivers of change in CVD risk in the middle-income country of South Africa compared to the high-income nation of England. The project produced a harmonised dataset of national surveys measuring CVD risk factors in South Africa and England for others to use in future work. The harmonised dataset includes microdata from nationally-representative surveys in South Africa derived from the Demographic and Health Surveys, National Income Dynamics Study, South Africa National Health and Nutrition Examination Survey and Study on Global Ageing and Adult Health, covering 11 cross-sections and approximately 156,000 individuals aged 15+ years, representing South Africa’s adult population from 1998 to 2017.

Data for England come from 17 Health Surveys for England (HSE) over the same time period, covering over 168,000 individuals aged 16+ years, representing England’s adult population.

This study uses existing data to identify drivers of recent health transitions in South Africa compared to England. The global burden of non-communicable diseases (NCDs) on health is increasing. Cardiovascular diseases (CVD) in particular are the leading causes of death globally and often share characteristics with many major NCDs. Namely, they tend to increase with age and are influenced by behavioural factors such as diet, exercise and smoking. Risk factors for CVD are routinely measured in population surveys and thus provide an opportunity to study health transitions. Understanding the drivers of health transitions in countries that have not followed expected paths (eg, South Africa) compared to those that exemplified models of 'epidemiologic transition' (eg, England) can generate knowledge on where resources may best be directed to reduce the burden of disease. In the middle-income country of South Africa, CVD is the second leading cause of death after HIV/AIDS and tuberculosis (TB). Moreover, many of the known risk factors for NCDs like CVD are highly prevalent. Rates of hypertension are high, with recent estimates suggesting that over 40% of adults have high blood pressure. Around 60% of women and 30% of men over 15 are overweight in South Africa. In addition, excessive alcohol consumption, a risk factor for many chronic diseases, is high, with over 30% of men aged 15 and older having engaged in heavy episodic drinking within a 30-day period. Nevertheless, infectious diseases such as HIV/AIDS remain the leading cause of death, though many with HIV/AIDS and TB also have NCDs. In high-income countries like England, by contrast, NCDs such as CVD have been the leading causes of death since the mid-1900s. However, CVD and risk factors such as hypertension have been declining in recent decades due to increased prevention and treatment. The major drivers of change in disease burden have been attributed to factors including ageing, improved living standards, urbanisation, lifestyle change, and reduced infectious disease. Together, these changes are often referred to as the epidemiologic transition. However, recent research has questioned whether epidemiologic transition theory accurately describes the experience of many low- and middle-income countries or, in fact, of high-income nations such as England. Furthermore, few studies have empirically tested the relative contributions of demographic, behavioural, health and economic factors to trends in disease burden and risk, particularly on the African continent. In addition, many social and environmental factors are overlooked in this research. To address these gaps, our study will use population measurements of CVD risk derived from surveys in South Africa over nearly 20 years in order to examine whether and to what extent demographic, behavioural, environmental, medical, social and other factors contribute to recent health trends and transitions. We will compare these trends to those occurring in England over the same time period. Thus, this analysis seeks to illuminate the drivers of health transitions in a country which is assumed to still be 'transitioning' to a chronic disease profile but which continues to have a high infectious disease burden (South Africa) as compared to a country which is assumed to have already transitioned following epidemiological transition theory (England). The analysis will employ modelling techniques on pooled cross-sectional data to examine how various factors explain the variation in CVD risk over time in representative population samples from South Africa and England. The results of this analysis may help to identify some of the main contributors to recent changes in CVD risk in South Africa and England. Such information can be used to pinpoint potential areas for intervention, such as social policy and services, thereby helping to set priorities for governmental and...

Evolution and plasticity can drive population-level phenotypic change (e.g., changes in the mean phenotype) on time scales comparable to changes in population densities. However, it is unclear if phenotypic change has the potential to be just as fast as changes in densities, or if comparable rates of change only occur when densities are changing slow enough for phenotypes to keep pace. Moreover, it is unclear if this depends on the mode of adaptation. Using scaling theory and fast-slow dynamical systems theory, we develop a method for comparing maximum rates of density and phenotypic change estimated from population-level time series data. We apply our method to 30 published empirical studies where changes in morphological traits are caused by evolution, plasticity, or an unknown combination. For every study, the maximum rate of phenotypic change was 0.5 to 2.5 times faster than the maximum rate of change in density. Moreover, there were no systematic differences between systems with different modes of adaptation. Our results show that plasticity and evolution can drive phenotypic change just as fast as changes in densities. We discuss the implications of our results in terms of the strengths of feedbacks between population densities and traits.

The global movement of pathogens is altering populations and communities through a variety of direct and indirect ecological pathways. The direct effect of a pathogen on a host is reduced survival, which can lead to decreased population densities. However, theory also suggests that increased mortality can lead to no change or even increases in the density of the host. This paradoxical result can occur in a regulated population when the pathogen's negative effect on survival is countered by increased reproduction at the lower density. Here we analyze data from a long-term capture-mark-recapture experiment of Trinidadian guppies (Poecilia reticulata) that was recently infected with a nematode parasite (Camallanus cotti). By comparing the newly infected population with a control population that was not infected we show that decreases in the density of the infected guppy population were transient. The guppy population compensated for the decreased survival by a density-dependent increase in recruitment of new individuals into the population, without any change in the underlying recruitment function. Increased recruitment was related to an increase in the somatic growth of uninfected fish. Twenty months into the new invasion, the population had fully recovered to pre-invasion densities even though the prevalence of infection of fish in the population remained high (72%). These results show that density-mediated indirect effects of novel parasites can be positive, not negative, which makes it difficult to extrapolate to how pathogens will affect species interactions in communities. We discuss possible hypotheses for the rapid recovery.

Understanding how the natural world will be impacted by environmental change over the coming decades is one of the most pressing challenges facing humanity. Addressing this challenge is difficult because environmental change can generate both population level plastic and evolutionary responses, with plastic responses being either adaptive or non-adaptive. We develop an approach that links quantitative genetic theory with data-driven structured models to allow prediction of population responses to environmental change via plasticity and adaptive evolution. After introducing general new theory, we construct a number of example models to demonstrate that evolutionary responses to environmental change over the short-term will be considerably slower than plastic responses, and that the rate of adaptive evolution to a new environment depends upon whether plastic responses are adaptive or non-adaptive. Parameterization of the models we develop requires information on genetic and phenotypic variation and demography that will not always be available, meaning that simpler models will often be required to predict responses to environmental change. We consequently develop a method to examine whether the full machinery of the evolutionarily explicit models we develop will be needed to predict responses to environmental change, or whether simpler non-evolutionary models that are now widely constructed may be sufficient.

Host_Resistance_PhenotypesHost Resistance PhenotypesVirus_Densitiesas particles per mlAlgal_Densitiesas cells per ml

Mean transition probabilities (and standard deviation of the estimate) for a 13-month period for population 5.