Long-term Population Growth Research Articles

Variety is the spice of life: nongenetic variation in life histories influences population growth and evolvability.

Individual vital rates, such as mortality and birth rates, are key determinants of lifetime reproductive success, and variability in these rates shapes population dynamics. Previous studies have found that this vital rate heterogeneity can influence demographic properties, including population growth rates. However, the explicit effects of the variation within and the covariance between vital rates that can also vary throughout the lifespan on population growth remain unknown. Here, we explore the analytical consequences of nongenetic heterogeneity on long-term population growth rates and rates of evolution by modifying traditional age-structured population projection matrices to incorporate variation among individual vital rates. The model allows vital rates to be permanent throughout life ("fixed condition") or to change over the lifespan ("dynamic condition"). We reduce the complexity associated with adding individual heterogeneity to age-structured models through a novel application of matrix collapsing ("phenotypic collapsing"), showing how to collapse in a manner that preserves the asymptotic and transient dynamics of the original matrix. The main conclusion is that nongenetic individual heterogeneity can strongly impact the long-term growth rate and rates of evolution. The magnitude and sign of this impact depend heavily on how the heterogeneity covaries across the lifespan of an organism. Our results emphasize that nongenetic variation cannot simply be viewed as random noise, but rather that it has consistent, predictable effects on fitness and evolvability.

A model of long-term population growth with an application to Central West Argentina.

We propose an Ideal Specialization Model to help explain the diversity of population growth trajectories exhibited across archaeological regions over thousands of years. The model provides a general set of expectations useful for guiding empirical research, and we provide a concrete example by conducting a preliminary evaluation of three expectations in Central West Argentina. We use kernel density estimates of archaeological radiocarbon, estimates of paleoclimate, and human bone stable isotopes from archaeological remains to evaluate three expectations drawn from the model's dynamics. Based on our results, we suggest that innovations in the production of food and social organization drove demographic transitions and population expansion in the region. The consistency of population expansion in the region positively associates with changes in diet and, potentially, innovations in settlement and social integration.

Exploring the link between CO2 emissions, health expenditure, and economic growth in Türkiye: evidence from the ARDL model

In recent times, the literature has seen considerable growth in research at the intersection of CO2 emission, health expenditure, and economic growth. But looking at the literature, it appears that the relationship between health expenditures, CO2 emissions, and economic growth is unclear. To resolve this uncertainty, this study was conducted with different data, countries, and methods. To this end, the present study analyzed the nexus between CO2 emissions, health expenditure, and economic growth in Türkiye from 1975 to 2020 using the Autoregressive Distributed Lagged (ARDL) model developed by Pesaran et al. (J Appl Econ 16(3):289–326, 2001). The study reveals a connection between CO2 emissions, health spending, and economic development in Türkiye over the long term. It also highlights a short-term correlation among these factors. The study indicates that a 1% increase in economic growth results in a 0.553 and 0.297 rise in CO2 emissions in the short and long term, respectively. That is, it suggests that if economic growth in Türkiye doesn’t involve renewable energy, it could negatively affect CO2 emissions both in the short and long term. To address this, substantial efforts are needed to transition to low-carbon technologies like renewable energy and energy efficiency, aiming to reduce emissions and support long-term economic growth. The study further demonstrates that a 1% growth in health expenditure leads to a 0.124% decrease in CO2 emissions over the long term. This implies that Türkiye’s health sector could benefit from utilizing more renewable energy or using fossil fuels more efficiently. Additionally, the study warns that long-term population growth could negatively affect CO2 emissions in Türkiye.

Unclear relationships between mean survival rate and its environmental variance in vertebrates.

Current environmental changes may increase temporal variability of life history traits of species thus affecting their long-term population growth rate and extinction risk. If there is a general relationship between environmental variances (EVs) and mean annual survival rates of species, that relationship could be used as a guideline for analyses of population growth and extinction risk for populations, where data on EVs are missing. For this purpose, we present a comprehensive compilation of 252 EV estimates from 89 species belonging to five vertebrate taxa (birds, mammals, reptiles, amphibians and fish) covering mean annual survival rates from 0.01 to 0.98. Since variances of survival rates are constrained by their means, particularly for low and high mean survival rates, we assessed whether any observed relationship persisted after applying two types of commonly used variance stabilizing transformations: relativized EVs (observed/mathematical maximum) and logit-scaled EVs. With raw EVs at the arithmetic scale, mean-variance relationships of annual survival rates were hump-shaped with small EVs at low and high mean survival rates and higher (and widely variable) EVs at intermediate mean survival rates. When mean annual survival rates were related to relativized EVs the hump-shaped pattern was less distinct than for raw EVs. When transforming EVs to logit scale the relationship between mean annual survival rates and EVs largely disappeared. The within-species juvenile-adult slopes were mainly positive at low (<0.5) and negative at high (>0.5) mean survival rates for raw and relativized variances while these patterns disappeared when EVs were logit transformed. Uncertainties in how to interpret the results of relativized and logit-scaled EVs, and the observed high variation in EV's for similar mean annual survival rates illustrates that extrapolations of observed EVs and tests of life history drivers of survival-EV relationships need to also acknowledge the large variation in these parameters.

Modified Verhulst–Solow model for long-term population and economic growth

AbstractIn this study, we analyze the relationship between human population growth and economic dynamics. To do so, we present a modified version of the Verhulst model and the Solow model, which together simulate population dynamics and the role of economic variables. The model incorporates support and foraging functions, which participate in the dynamic relationship between population growth and the creation and destruction of carrying capacity. The validity of the model is demonstrated using empirical data.

Revisiting international house price convergence using house price level data

The literature on house price convergence largely relies on house price indices, based in an arbitrary year, rather than on actual price levels. This is essentially due to the scarcity of comparable house price level data. However, this severely constrains the analysis. In particular, it often forces to discard a large part of the data sample, which leads to a great loss of information and hampers analysis on sub-periods. In this paper, we combine the price level estimates produced by Bricongne et al. (2019) with long OECD house price series to analyse long-run house price convergence across 18 OECD countries. Applying the Phillips and Sul (2007) procedure, we find convergence in OECD nominal house prices, but two separate convergence clubs in real house prices. We find some convergence in euro area real house prices, but no evidence of strengthening after the introduction of the euro. β-convergence regressions (linking changes in house prices to their initial levels) point to conditional convergence, related to the evolution of gaps in real GDP per capita, long-term interest rates and population growth across countries.

Global burden of non-optimal temperature attributable stroke: The long-term trends, population growth and aging effects

Since the 20th century, the world has undergone climate change, population growth and population aging, which may result in alterations in the epidemiology of non-optimal temperature-associated strokes. We employed multiple methodologies and data from the global burden of disease 2019 to unveil the long-term curvilinear trends in strokes attributed to non-optimal temperature and the impact of aging and population growth on its changing epidemiology. From 1990 to 2019, the age-standardized DALYs rate (ASDR) of strokes attributable to low temperature had been decreasing, but from 2016, the continued downward trend in ASDR disappeared and began to remain stable. On the contrary, the ASDR of strokes attributable to high temperature continued to increase. The high socio-demographic index (SDI) region experienced the fastest decreased trend. The disease burden of stroke attributable to low temperature is increased by aging in 178 countries (87.25%), compared with 130 (63.73%) for high temperature. After excluding aging and population growth, the DALY rate for strokes attributed to high temperature was increasing in 87 countries and territories (42.64%). The disease burden of strokes attributed to low temperature is far greater than that of high temperature in absolute figures. However, globally, there is a significant trend toward an increase in strokes attributed to high temperature. Social development has largely offset the burden of strokes attributed to low temperature, but most regions of the world are equally affected by strokes attributed to high temperature. Simultaneously, in the framework of climate change, aging is also largely hindering stroke prevention efforts.

Repeated long-term population growth overshoots and recessions among hunter-gatherers

We propose a model that may explain long-term population growth and decline events among human populations: The intensification of production generates a tradeoff between the adaptive capacity of individuals to generate a surplus of energy to maximize their fitness in the short-run and the long-term capacity of a population as a whole to experience a smooth transition into a demographic equilibrium. The model reconciles the conflicting insights of dynamic systems models of human population change, and we conduct a preliminary test of this model’s implications in Central Texas by developing time-series that estimate changes in human population density, modeled ecosystem productivity, human diet, and labor over the last 12,500 years. Our analysis indicates that Texas hunter-gatherers experienced three long-term population growth overshoots and recessions into quasi equilibria. Evidence indicates that each of these overshoots and recessions associate with changes in diet and labor devoted to processing high density, lower quality resources to unlock calories and nutrients. Over the long-term, population recessions may be necessary for populations to experiment with social and physical infrastructure changes that raise the carrying capacity of their environment.

Coevolution of Patch Selection in Stochastic Environments.

AbstractSpecies interact in landscapes where environmental conditions vary in time and space. This variability impacts how species select habitat patches. Under equilibrium conditions, evolution of this patch selection can result in ideal free distributions where per capita growth rates are zero in occupied patches and negative in unoccupied patches. These ideal free distributions, however, do not explain why species occupy sink patches, why competitors have overlapping spatial ranges, or why predators avoid highly productive patches. To understand these patterns, we solve for coevolutionarily stable strategies (coESSs) of patch selection for multispecies stochastic Lotka-Volterra models accounting for spatial and temporal heterogeneity. In occupied patches at the coESS, we show that the differences between the local contributions to the mean and the variance of the long-term population growth rate are equalized. Applying this characterization to models of antagonistic interactions reveals that environmental stochasticity can partially exorcize the ghost of competition past, select for new forms of enemy-free and victimless space, and generate hydra effects over evolutionary timescales. Viewing our results through the economic lens of modern portfolio theory highlights why the coESS for patch selection is often a bet-hedging strategy coupling stochastic sink populations. Our results highlight how environmental stochasticity can reverse or amplify evolutionary outcomes as a result of species interactions or spatial heterogeneity.

A demographic approach for predicting population responses to multifactorial stressors.

Populations face a suite of anthropogenic stressors acting simultaneously, which can combine additively or interact to have complex effects on population persistence. Yet we still know relatively little about the mechanisms underlying population-level responses to multifactorial combinations of stressors because multiple stressor impacts across organisms' life cycles have not been systematically considered in population models. Specifically, different anthropogenic stressors can have variable effects across an organism's life cycle, resulting in non-intuitive results for long-term population persistence. For example, synergistic or antagonistic interactions might exacerbate or alleviate the effects of stressors on population dynamics, and different life-history stages or vital rates might contribute unequally to long-term population growth rates. Demographic modelling provides a framework to incorporate individual vital rate responses to multiple stressors into estimates of population growth, which will allow us to make more informed predictions about population-level responses to novel combinations of anthropogenic change. Without integrating stressors' interactive effects across the entire life cycle on population persistence, we may over- or underestimate threats to biodiversity and risk missing conservation management actions that could reduce species' vulnerability to stress.

Evolutionary game theory to predict the population growth in Few districts of Tamil Nadu and Kerala

The conventional models in Game Theory focuses entirely on the relative fitness of the population agents leaving the dynamic behaviour of the size of population left uncovered. Therefore, a robust model is required to combine both the growth dynamics and internal evolution of agents. Evolutionary Game Theory to Predict the Population Growth in Few Districts of Tamil Nadu and Kerala. In this paper, we develop an Evolutionary Game Theory (EGT) model which is integrated with the Residual deterministic learning (RDL) model to increase the rate of prediction of the population growth. Various deterministic models including Arithmetic Increase, Geometric Increase, Incremental Increase and Simple graphical models are used to improve the prediction ability of EGT. The EGT combined with RDL forms REGT model that is found scalable to predict the long-term population growth in near proximal districts of Tamil Nadu and Kerala. Various inputs affecting the population growth are considered as the inputs to the REGT model to the Matlab simulator. The experimentation shows that the proposed REGT model is better in predicting the population growth than the existing game theory models.

Optimal energy allocation trade-off driven by size-dependent physiological and demographic responses to warming.

Body size-dependent physiological effects of temperature influence individual growth, reproduction, and survival, which govern animal population responses to global warming. Considerable knowledge has been established on how such effects can affect population growth and size structure, but less is known of their potential role in temperature-driven adaptation in life-history traits. In this study, we ask how warming affects the optimal allocation of energy between growth and reproduction and disentangle the underlying fitness trade-offs. To this end, we develop a novel dynamic energy budget integral projection model (DEB-IPM), linking individuals' size- and temperature-dependent consumption and maintenance via somatic growth, reproduction, and size-dependent energy allocation to emergent population responses. At the population level, we calculate the long-term population growth rate (fitness) and stable size structure emerging from demographic processes. Applying the model to an example of pike (Esox lucius), we find that optimal energy allocation to growth decreases with warming. Furthermore, we demonstrate how growth, fecundity, and survival contribute to this change in optimal allocation. Higher energy allocation to somatic growth at low temperatures increases fitness through survival of small individuals and through the reproduction of larger individuals. In contrast, at high temperatures, increased allocation to reproduction is favored because warming induces faster somatic growth of small individuals and increased fecundity but reduced growth and higher mortality of larger individuals. Reduced optimum allocation to growth leads to further reductions in body size and an increasingly truncated population size structure with warming. Our study demonstrates how, by incorporating general physiological mechanisms driving the temperature dependence of life-history traits, the DEB-IPM framework is useful for investigating the adaptation of size-structured organisms to warming.

Research Note: Intergenerational Transmission Is Not Sufficient for Positive Long-Term Population Growth.

All leading long-term global population projections agree on continuing fertility decline, resulting in a rate of population size growth that will continue to decline toward zero and would eventually turn negative. However, scholarly and popular arguments have suggested that because fertility transmits intergenerationally (i.e., higher fertility parents tend to have higher fertility children) and is heterogeneous within a population, long-term population growth must eventually be positive, as high-fertility groups come to dominate the population. In this research note, we show that intergenerational transmission of fertility is not sufficient for positive long-term population growth, for empirical and theoretical reasons. First, because transmission is imperfect, the combination of transmission rates and fertility rates may be quantitatively insufficient for long-term population growth: higher fertility parents may nevertheless produce too few children who retain higher fertility preferences. Second, today even higher fertility subpopulations show declining fertility rates, which may eventually fall below replacement (and in some populations already are). Therefore, although different models of fertility transmission across generations reach different conclusions, depopulation is likely under any model if, in the future, even higher fertility subpopulations prefer and achieve below-replacement fertility. These results highlight the plausibility of long-term global depopulation and the importance of understanding the possible consequences of depopulation.

Spatial consistency in drivers of population dynamics of a declining migratory bird.

Many migratory species are in decline across their geographical ranges. Single-population studies can provide important insights into drivers at a local scale, but effective conservation requires multi-population perspectives. This is challenging because relevant data are often hard to consolidate, and state-of-the-art analytical tools are typically tailored to specific datasets. We capitalized on a recent data harmonization initiative (SPI-Birds) and linked it to a generalized modelling framework to identify the demographic and environmental drivers of large-scale population decline in migratory pied flycatchers (Ficedula hypoleuca) breeding across Britain. We implemented a generalized integrated population model (IPM) to estimate age-specific vital rates, including their dependency on environmental conditions, and total and breeding population size of pied flycatchers using long-term (34-64 years) monitoring data from seven locations representative of the British breeding range. We then quantified the relative contributions of different vital rates and population structure to changes in short- and long-term population growth rate using transient life table response experiments (LTREs). Substantial covariation in population sizes across breeding locations suggested that change was the result of large-scale drivers. This was supported by LTRE analyses, which attributed past changes in short-term population growth rates and long-term population trends primarily to variation in annual survival and dispersal dynamics, which largely act during migration and/or nonbreeding season. Contributions of variation in local reproductive parameters were small in comparison, despite sensitivity to local temperature and rainfall within the breeding period. We show that both short- and long-term population changes of British breeding pied flycatchers are likely linked to factors acting during migration and in nonbreeding areas, where future research should be prioritized. We illustrate the potential of multi-population analyses for informing management at (inter)national scales and highlight the importance of data standardization, generalized and accessible analytical tools, and reproducible workflows to achieve them.

Application of modern coexistence theory to rare plant restoration provides early indication of restoration trajectories.

Restoration ecology commonly seeks to re-establish species of interest in degraded habitats. Despite a rich understanding of how succession influences re-establishment, there are several outstanding questions that remain unaddressed: are short-term abundances sufficient to determine long-term re-establishment success, and what factors contribute to unpredictable restorations outcomes? In other words, when restoration fails, is it because the restored habitat is substandard, because of strong competition with invasive species, or alternatively due to changing environmental conditions that would equally impact established populations? Here, we re-purpose tools developed from modern coexistence theory to address these questions, and apply them to an effort to restore the endangered Contra Costa goldfields (Lasthenia conjugens) in constructed ("restored") California vernal pools. Using 16 years of data, we construct a population model of L. conjugens, a species of conservation concern due primarily to habitat loss and invasion of exotic grasses. We show that initial, short-term appearances of restoration success from population abundances is misleading, as year-to-year fluctuations cause long-term population growth rates to fall below zero. The failure of constructed pools is driven by lower maximum growth rates compared with reference ("natural") pools, coupled with a stronger negative sensitivity to annual fluctuations in abiotic conditions that yield decreased maximum growth rates. Nonetheless, our modeling shows that fluctuations in competition (mainly with exotic grasses) benefit L. conjugens through periods of competitive release, especially in constructed pools of intermediate pool depth. We therefore show how reductions in invasives and seed addition in pools of particular depths could change the outcome of restoration for L. conjugens. By applying a largely theoretical framework to the urgent goal of ecological restoration, our study provides a blueprint for predicting restoration success, and identifies future actions to reverse species loss.

Hybridization may aid evolutionary rescue of an endangered East African passerine.

Introgressive hybridization is a process that enables gene flow across species barriers through the backcrossing of hybrids into a parent population. This may make genetic material, potentially including relevant environmental adaptations, rapidly available in a gene pool. Consequently, it has been postulated to be an important mechanism for enabling evolutionary rescue, that is the recovery of threatened populations through rapid evolutionary adaptation to novel environments. However, predicting the likelihood of such evolutionary rescue for individual species remains challenging. Here, we use the example of Zosterops silvanus, an endangered East African highland bird species suffering from severe habitat loss and fragmentation, to investigate whether hybridization with its congener Zosterops flavilateralis might enable evolutionary rescue of its Taita Hills population. To do so, we employ an empirically parameterized individual‐based model to simulate the species' behaviour, physiology and genetics. We test the population's response to different assumptions of mating behaviour and multiple scenarios of habitat change. We show that as long as hybridization does take place, evolutionary rescue of Z. silvanus is likely. Intermediate hybridization rates enable the greatest long‐term population growth, due to trade‐offs between adaptive and maladaptive introgressed alleles. Habitat change did not have a strong effect on population growth rates, as Z. silvanus is a strong disperser and landscape configuration is therefore not the limiting factor for hybridization. Our results show that targeted gene flow may be a promising avenue to help accelerate the adaptation of endangered species to novel environments, and demonstrate how to combine empirical research and mechanistic modelling to deliver species‐specific predictions for conservation planning.

Assessing the Accuracy of National Population Projections

Few producers of official population projections provide regular evaluations of past projection inaccuracies. This paper assesses deviations between the projected and registered total population for Norway (1996–2018), as well as deviations in the age structure, total fertility rate and number of births, period life expectancy at birth and number of deaths, and net international migration. Projected life expectancy was consistently lower than the real development. Few systematic deviations were observed for fertility up to 2009, but thereafter fertility has been consistently overprojected. However, the deviations between projected and realised trends in births and deaths have been relatively small as compared to those for net international migration. The projections produced between 1996–2005 underestimated long-term population growth due primarily to the unforeseen increase in immigration following EU expansion in 2004. More recent projections contain no consistent under- or overprojection of net migration and the deviations for the total population have been moderate.

Effects of habitat disturbance and rainfall on a dominant medicinal dry forest tree

The interactive effects of anthropogenic disturbance and climatic variables can shape the demography of plant populations, but they remain poorly understood especially for long-lived species like tropical trees. Understanding these interactions is critical for designing forest management strategies in the face of both growing anthropogenic pressures and climate change. We explored the effects of habitat disturbance and interannual variation in rainfall on the population dynamics of Amphipterygium adstringens (Anacardiaceae), an ecologically dominant tree species endemic to the tropical deciduous forests of Mexico, that is heavily harvested for its medicinal bark. Specifically, we compared A. adstringens vital rates and long-term population growth rates of unharvested populations in a disturbed versus a protected tropical deciduous forest site; and explored the effects of inter-annual variation in annual rainfall on A. adstringens by comparing vital rates and population growth rates across three years with differing levels of rainfall. We established four plots in each of the two sites and monitored survival, growth and reproduction of 251 individuals over three years. We found that anthropogenic disturbance and rainfall differentially affected the vital rates of A. adstringens. Survival did not differ across sites or years. Growth tended to be lower and fecundity higher, in the protected site, but these effects varied across years and as a function of plant size. No seedlings were found in the disturbed site over the three years study period. Integral projection models showed that projected population growth rates (λ values) in the protected site were higher and much less variable over time than those of the disturbed site. Lambda values in the disturbed site were <1, indicating long-term population decline. In both sites, the rainiest year showed the highest population growth rate but the increase in λ was much higher in the disturbed site than in the protected site. These findings suggest that the population dynamics of A. adstringens are heavily affected by habitat disturbance forest management regime and that the impacts of interannual variability in rainfall or other environmental conditions may be exacerbated in disturbed conditions. The persistence of A. adstringens populations over time will require the exclusion of livestock as well as the implementation of silvicultural practices that will lead to seedling establishment and survival. This study provides key data for the management and conservation of A. adstringens, a highly valued medicinal species.

The Disconnect Between Short- and Long-Term Population Projections for Plant Reintroductions

The reintroduction of rare species in natural preserves is a commonly used restoration strategy to prevent species extinction. An essential first step in planning successful reintroductions is identifying which life stages (e.g., seeds or large adults) should be used to establish these new populations. Following this initial establishment phase, it is necessary to determine the level of survival, growth, and recruitment needed to maintain population persistence over time and identify management actions that will achieve these goals. In this 5-year study, we projected the short- and long-term population growth rates of a critically endangered long-lived shrub, Delissea waianaeensis. Using this model system, we show that reintroductions established with mature individuals have the lowest probability of quasi-population extinction (10 individuals) and the highest increase in population abundance. However, our results also demonstrate that short-term increases in population abundances are overly optimistic of long-term outcomes. Using long-term stochastic model simulations, we identified the level of natural seedling regeneration needed to maintain a positive population growth rate over time. These findings are relevant for planning future reintroduction efforts for long-lived species and illustrate the need to forecast short- and long-term population responses when evaluating restoration success.

Identifying spatial drivers of long-term population growth in three large gull species: the importance of mink farms and urban areas

Population growth generally shows extensive spatial variation within species, but the proximate and ultimate drivers of this variation are often poorly understood. For highly mobile colonial breeders, population growth is expected to be linked to resource availability within a considerable radius of the colony. We analyzed the relationship between population growth over the period 2000–2020 and resource availability for three large gull species in several hundred colonies in Denmark. Colony growth rates showed strong spatial autocorrelation for Herring Gull <em>Larus argentatus</em>, whereas no such relationship was apparent for the other two species (Great Black-backed Gull <em>L. marinus</em> and Lesser Black-backed Gull <em>L. fuscus</em>). Colony growth rates of Herring Gulls were correlated with relevant proxies of food availability within species-specific foraging ranges, including the extent of urban and subtidal foraging habitats, and the number of mink farms. No such correlations were found for the other two species. The positive relationships of Herring Gull colony growth with the number of mink farms and the extent of built-up area were particularly interesting, as they highlighted the strong dependency of this species on human-associated food sources. Furthermore, Denmark closed all mink farms in late 2020 because of concerns about the spread of SARS-CoV-2 virus between farms and between minks and humans, culling approximately 17 million minks. This dramatic change in food availability is expected to have a negative impact on the Danish Herring Gull population, which in recent years has fared better than in the neighboring countries.