The Central Balkans region is of great importance for understanding the spread of the Neolithic in Europe but the Early Neolithic population dynamics of the region is unknown. In this study we apply the method of summed calibrated probability distributions to a set of published radiocarbon dates from the Republic of Serbia in order to reconstruct population dynamics in the Early Neolithic in this part of the Central Balkans. The results indicate that there was a significant population growth after ~6200 calBC, when the Neolithic was introduced into the region, followed by a bust at the end of the Early Neolithic phase (~5400 calBC). These results are broadly consistent with the predictions of the Neolithic Demographic Transition theory and the patterns of population booms and busts detected in other regions of Europe. These results suggest that the cultural process that underlies the patterns observed in Central and Western Europe was also in operation in the Central Balkan Neolithic and that the population increase component of this process can be considered as an important factor for the spread of the Neolithic as envisioned in the demic diffusion hypothesis.

Bellringer activities designed to support Advanced Placement Human Geography.

Anticipating critical transitions in spatially extended systems is a key topic of interest to ecologists. Gradually declining metapopulations are an important example of a spatially extended biological system that may exhibit a critical transition. Theory for spatially extended systems approaching extinction that accounts for environmental stochasticity and coupling is currently lacking. Here, we develop spatially implicit two-patch models with additive and multiplicative forms of environmental stochasticity that are slowly forced through population collapse, through changing environmental conditions. We derive patch-specific expressions for candidate indicators of extinction and test their performance via a simulation study. Coupling and spatial heterogeneities decrease the magnitude of the proposed indicators in coupled populations relative to isolated populations, and the noise regime and the degree of coupling together determine trends in summary statistics. This theory may be readily applied to other spatially extended ecological systems, such as coupled infectious disease systems on the verge of elimination.

How does the association between gender attitudes and housework share vary across countries and time? We examine the second demographic transition as it unmasks in the association between gender attitudes and housework participation. Using data of the 2002 and 2012 International Social Survey Programme (ISSP) for 24 countries, we find that the association between gender attitudes and housework share became stronger over time in most countries, signifying that the Second Demographic Transition was in place. The results also show that the association varied across the 24 countries, reaching an equilibrium in many but at different stages. Our findings suggest that equilibria in the domestic division of labour take various forms and paces in the ISSP countries.

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...

Grandmothers provide key care to their grandchildren in both contemporary and historic human populations. The length of the grandmother-grandchild relationship provides a basis for such interactions, but its variation and determinants have rarely been studied in different contexts, despite changes in age-specific mortality and fertility rates likely having affected grandmotherhood patterns across the demographic transition. Understanding how often and long grandmothers have been available for their grandchildren in different conditions may help explain the large differences between grandmaternal effects found in different societies, and is vital for developing theories concerning the evolution of menopause, post-reproductive longevity, and family living. Using an extensive genealogical dataset from Finland spanning the demographic transition, we quantify the length of grandmotherhood and its determinants from 1790–1959. We found that shared time between grandmothers and grandchildren was consistently low before the demographic transition, only increasing greatly during the 20th century. Whilst reduced childhood mortality and increasing adult longevity had a role in this change, grandmaternal age at birth remained consistent across the study period. Our findings further understanding of the temporal context of grandmother-grandchild relationships, and emphasise the need to consider the demography of grandmotherhood in a number of disciplines, including biology (e.g. evolution of the family), sociology (e.g. changing family structures), population health (e.g. changing age structures), and economics (e.g. workforce retention).

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.

Theoretical and empirical research has shown that increased variability in demographic rates often results in a decline in the population growth rate. In order to reduce the adverse effects of increased variability, life-history theory predicts that demographic rates that contribute disproportionately to population growth should be buffered against environmental variation. To date, evidence of demographic buffering is still equivocal and limited to analyses on a reduced number of age-classes (e.g. juveniles and adults), and on single sex models. Here we used Bayesian inference models for age-specific survival and fecundity on a long-term dataset of wild mountain gorillas. We used these estimates to parameterize two-sex, age-specific stochastic population projection models that accounted for the yearly covariation between demographic rates. We estimated the sensitivity of the long-run stochastic population growth rate to reductions in survival and fecundity on ages belonging to nine sex-age-classes for survival and three age-classes for female fecundity. We found a statistically significant negative linear relationship between the sensitivities and variances of demographic rates, with strong demographic buffering on young adult female survival and low buffering on older female and silverback survival and female fecundity. We found moderate buffering on all immature stages and on prime-age females. Previous research on long-lived slow species has found high buffering of prime-age female survival and low buffering on immature survival and fecundity. Our results suggest that the moderate buffering of the immature stages can be partially due to the mountain gorilla social system and the relative stability of their environment. Our results provide clear support for the demographic buffering hypothesis and its predicted effects on species at the slow end of the slow-fast life history continuum, but with the surprising outcome of moderate social buffering on the survival of immature stages. We also demonstrate how increasing the number of sex-age-classes can greatly improve the detection of demographic buffering in wild populations.

Methods The study was carried out in Volcanoes National Park in Rwanda, on the groups of habituated mountain gorillas monitored by the Dian Fossey Gorilla Fund’s Karisoke Research Center, often referred to as the Karisoke subpopulation. Since 1967, groups in this subpopulation have been monitored and protected on a near daily basis. Through the mid 2000s, the Karisoke groups generally numbered three but over the last decade, group fissions and new group formations resulted in an average of 10 groups in the region (see Caillaud et al, 2014). During daily observations, detailed demographic data were recorded, such as dates of birth and death, dates and types of individuals’ entry (immigrants) and departure (emigrants) from the study population, group composition, and maternal relatedness (for further details see Strier et al. 2010 and Granjon et al. (2020). In particular, groups were frequently monitored (daily between 2010-2016), and the arrival of a new individual to a monitored group was recorded as immigration. When individuals were lost to follow, depending on age, sex, health and group movement individuals could be classified as emigrated. However, when in doubt, the fate was recorded as unknown (Granjon et al. 2020).

Understanding the influence of environmental variability on population dynamics is a fundamental goal of ecology. Theory suggests that, for populations in variable environments, temporal correlations between demographic vital rates (e.g., growth, survival, reproduction) can increase (if positive) or decrease (if negative) the variability of year-to-year population growth. Because this variability generally decreases long-term population viability, vital rate correlations may importantly affect population dynamics in stochastic environments. Despite long-standing theoretical interest, it is unclear whether vital rate correlations are common in nature, whether their directions are predominantly negative or positive, and whether they are of sufficient magnitude to warrant broad consideration in studies of stochastic population dynamics. We used long-term demographic data for three perennial plant species, hierarchical Bayesian parameterization of population projection models, and stochastic simulations to address the following questions: (1) What are the sign, magnitude, and uncertainty of temporal correlations between vital rates? (2) How do specific pairwise correlations affect the year-to-year variability of population growth? (3) Does the net effect of all vital rate correlations increase or decrease year-to-year variability? (4) What is the net effect of vital rate correlations on the long-term stochastic population growth rate (λS)? We found only four moderate to strong correlations, both positive and negative in sign, across all species and vital rate pairs; otherwise, correlations were generally weak in magnitude and variable in sign. The net effect of vital rate correlations ranged from a slight decrease to an increase in the year-to-year variability of population growth, with average changes in variance ranging from -1% to +22%. However, vital rate correlations caused virtually no change in the estimates of λS (mean effects ranging from -0.01% to +0.17%). Therefore, the proportional changes in the variance of population growth caused by demographic correlations were too small on an absolute scale to importantly affect population growth and viability. We conclude that in our three focal populations and perhaps more generally, vital rate correlations have little effect on stochastic population dynamics. This may be good news for population ecologists, because estimating vital rate correlations and incorporating them into population models can be data-intensive and technically challenging.

Major insights into the relationship between life-history features and fitness have come from Lotka's proof that population growth rate is determined by the level (expected amount) of reproduction and the average timing of reproduction of an individual. But this classical result is limited to age-structured populations. Here we generalize this result to populations structured by stage and age by providing a new, unique measure of reproductive timing (Tc) that, along with net reproductive rate (R0), has a direct mathematical relationship to and approximates growth rate (r). We use simple examples to show how reproductive timing Tc and level R0 are shaped by stage dynamics (individual trait changes), selection on the trait, and parent-offspring phenotypic correlation. We also show how population structure can affect dispersion in reproduction among ages and stages. These macroscopic features of the life history determine population growth rate r and reveal a complex interplay of trait dynamics, timing, and level of reproduction. Our results contribute to a new framework of population and evolutionary dynamics in stage-and-age-structured populations.

Theory suggests that the drivers of demographic variation and local adaptation are shared and may feedback on one other. Despite some evidence for these links in controlled settings, the relationship between local adaptation and demography remains largely unexplored in natural conditions. Using 10 years of demographic data and two reciprocal transplant experiments, we tested predictions about the relationship between the magnitude of local adaptation and demographic variation (population growth rates and their elasticities to vital rates) across 10 populations of a well-studied annual plant. In both years, we found a strong unimodal relationship between mean home-away local adaptation and stochastic population growth rates. Other predicted links were either weakly or not supported by our data. Our results suggest that declining and rapidly growing populations exhibit reduced local adaptation, potentially due to maladaptation and relaxed selection, respectively. Methods This dataset includes long-term data collected using observations and environmetnal sensors, data on population dynamics derived from field census data, and data from 2 years of reciprocal transplants in field conditions. Data describing population dynamics have been processed from raw census data using matrix population models. All other data processing is performed using code that is archived along with the data.

In 2024, the total population of Spain was around 48.38 million people. By 2029, it was forecast to grow up to 50.76 million inhabitants.

Population of Spain While Spain’s fertility rate has been relatively decreasing over the past decade, its year-over-year population growth has been increasing continuously since 2016. The collapse of the job and real estate markets may have led the Spanish to postpone having (more) kids or to migrate to other countries in search of a more stable economy, while inflow of migrates has increased . This theory is supported by data on the average age of Spain’s inhabitants; a look at the median age of Spain’s population from 1950 up until today shows that the Spanish get older on average – perhaps due to the aforementioned factors.

Economic recovery Speaking of Spain’s economy, economic key factors suggest that the country is still recovering from the crisis. Its gross domestic product (GDP) was in admirable shape prior to the collapse, but it still has not returned to its former glory. Only recently has Spain reported actual GDP growth since 2008. Nevertheless, during 2020 and the COVID-19 pandemic, Spain's GDP had a decrease of more than 11 percent. This in turn, led to an increase of the country’s unemployment rate after years of slowly but surely decreasing following an alarming peak of 26 percent in 2013. Future perspectives are, however, somewhat brighter, as GDP is forecast to maintain a positive growth rate at least until 2029, even exceeding two percentage points in 2025.

pA is the frequency of strategy A among the total population. The frequency of p fluctuates as it approaches 1 because strategy B does not converge a unique age distribution and growth rate.

Mean transition probabilities (and standard deviation of the estimate) for a 13-month period for population 2.

Species' geographic ranges and climatic niches are likely to be increasingly mismatched due to rapid climate change. If a species' range and niche are out of equilibrium, then population performance should decrease from high-latitude "leading" range edges, where populations are expanding into recently ameliorated habitats, to low-latitude "trailing" range edges, where populations are contracting from newly unsuitable areas. Demographic compensation is a phenomenon whereby declines in some vital rates are offset by increases in others across time or space. In theory, demographic compensation could increase the range of environments over which populations can succeed and forestall range contraction at trailing edges. An outstanding question is whether range limits and range contractions reflect inadequate demographic compensation across environmental gradients, causing population declines at range edges. We collected demographic data from 32 populations of the scarlet monkeyflower (Erythranthe cardinalis) spanning 11˚ latitude in western North America and used integral projection models to evaluate population dynamics and assess demographic compensation across the species' range. During the 5-year study period, which included multiple years of severe drought and warming, population growth rates decreased from north to south, consistent with leading-trailing dynamics. Southern populations at the trailing range edge declined due to reduced survival, growth, and recruitment, despite compensatory increases in reproduction and faster life history characteristics. These results suggest that demographic compensation may only delay population collapse without the return of more favorable conditions or the contribution of other buffering mechanisms such as evolutionary rescue.

Survivorship data for the 58 mammal species considered in survivorship analysis.

AdultFatThis file and all that follow represent the dependent variables collected on all seven of the density manipulation experiments included in this paper.growthmean growth of each mm size class in all seven experimentsNumberofOffspringfecundity of all preserved adult females from all seven experimentsOffspringSizemean size of offspring dissected from all females preserved at the end of the experimentsReproductiveAllocationreproductive allocation of all pregnant females preserved at the end of all experimentsSurvivalmean survival, by mm size class, in all seven experiments

Determining population growth across large scales is difficult because it is often impractical to collect data at large scales and over long timespans. Instead, the growth of a population is often only measured at a small, plot-level scale and then extrapolated to derive a mean field estimate. However, this approach is prone to error since it simplifies spatial processes such as the neighbourhood effects of density and dispersal. We present a novel approach that estimates how spatial processes derived from the effects of density and dispersal affect population growth between plot scales and landscape scales. The method is based on a scale transition theory and calculates a transition term to measure the spatial scaling of population growth, which we extend to unstable, expanding populations in order to assess whether landscape-scale population dynamics are different from those estimated at smaller spatial scales. We illustrate this approach using aerial imagery of eight locations in New...

1. Mechanisms for maintaining biodiversity are still unclear despite considerable research. The classic theory predicts that stable co‐occurrence of competitive species requires niche differentiation. In fact, the co‐occurring species are often differentiated from each other. However, the neutral theory assuming equivalence of the reproductive rate of all individuals regardless of the species in a biological community has successfully recreated the observed patterns of species abundance distribution. This success is based on the unrealistic assumption suggesting that some mechanisms eliminate interspecific differences in the reproductive rates.
2. Here, I present sexual selection as a candidate of the mechanisms by constructing analytical and simulation models. Sexual selection affects the traits that increase mating success even at the expense of fecundity when the species is abundant. By contrast, when the species is at a relatively low density, this negative effect on fecundity is mitigated because less competition for mating occurs in the rare species.
3. The analytical model of this effect on fecundity predicted that sexual organisms stop population growth before exhausting resources due to the effect. This prediction was confirmed by simulation models. The simulations also showed that hundreds of competitive species with interspecific differences in reproductive potential can coexist over 10,000 generations. Moreover, species abundance distributions obtained from the simulations were similar to the patterns observed in field data. Given the generality of sexual reproduction in nature, sexual selection is likely to play a significant role in sustaining biodiversity over a broad range of environments.
4. Synthesis. Evolution does not always maximize population growth rate. This study shows that evolution of sexual selection controls the population growth rate according to density and stabilizes the population size. This stabilizing effect has a potential to rescue endangered species from extinction, prevent overgrowth of common species, promote coexistence of competitive species, and successfully recreate the observed patterns of species abundance distribution.

Individual metabolism generally scales with body mass with an exponent around 3/4. From dimensional arguments it follows that maximum population growth rate (rmax) scales with a -1/4 exponent. However, the dimensional argument implicitly assumes that offspring size is proportional to adult size. Here we calculate rmax from metabolic scaling at the level of individuals within size-structured populations while explicitly accounting for offspring size. We identify four general patterns of how rmax scales with adult mass based on four empirical life-history patterns employed by groups of species. These life-history patterns are determined by how traits of somatic growth rate and/or offspring mass relate to adult mass. One life-history pattern -- constant adult:offspring mass ratio and somatic growth rate independent of adult mass -- leads to the classic -1/4 scaling of rmax. The other three life-history patterns lead either to non-metabolic population growth scaling with adult mass or do no...