The application of an age-structured model with unbounded mortality to demography

We carry out a simulation of the female population of the USA using the non-autonomous Lotka-McKendrick model with finite maximum age and recent demographic data. The most important contributions in our study are the identification of the mortality rate (including the maximum age) and the design and analysis of a numerical method that works efficiently with unbounded mortality rates. We also consider the effect in the population projections produced by different ways to choose the vital rates and we present a sensitivity analysis with respect to the mortality. Finally, we exemplify the limitations the data impose on the quality of the projections of this model through a 10-year simulation for the USA from 1990 to 2000 and we project the female population of the USA in 2010 using this model.     

Current Demographics Suggest Future Energy Supplies Will Be Inadequate to Slow Human Population Growth

Influential demographic projections suggest that the global human population will stabilize at about 9–10 billion people by mid-century. These projections rest on two fundamental assumptions. The first is that the energy needed to fuel development and the associated decline in fertility will keep pace with energy demand far into the future. The second is that the demographic transition is irreversible such that once countries start down the path to lower fertility they cannot reverse to higher fertility. Both of these assumptions are problematic and may have an effect on population projections. Here we examine these assumptions explicitly. Specifically, given the theoretical and empirical relation between energy-use and population growth rates, we ask how the availability of energy is likely to affect population growth through 2050. Using a cross-country data set, we show that human population growth rates are negatively related to per-capita energy consumption, with zero growth occurring at ∼13 kW, suggesting that the global human population will stop growing only if individuals have access to this amount of power. Further, we find that current projected future energy supply rates are far below the supply needed to fuel a global demographic transition to zero growth, suggesting that the predicted leveling-off of the global population by mid-century is unlikely to occur, in the absence of a transition to an alternative energy source. Direct consideration of the energetic constraints underlying the demographic transition results in a qualitatively different population projection than produced when the energetic constraints are ignored. We suggest that energetic constraints be incorporated into future population projections.     

Updates to astronaut radiation limits: radiation risks for never-smokers

New epidemiology assessments of the life span study (LSS) of the atomic bomb survivors in Japan and of other exposed cohorts have been made by the U.S. National Academy of Sciences, the United Nations Committee on the Effects of Atomic Radiation, and the Radiation Research Effects Foundation in Japan. The National Aeronautics and Space Administration (NASA) uses a 3% risk of exposure-induced death (REID) as a basis for setting age- and gender-specific dose limits for astronauts. NASA's dose limits originate from the report of the National Council on Radiation Protection and Measurements (NCRP) in the year 2000 based on analysis of older epidemiology data. We compared the results of the recent analysis of the LSS to the earlier risk projections from the NCRP. Using tissue-specific, incidence-based risk transfer from the LSS data to a U.S. population to project REID values leads to higher risk and reduced dose limits for older astronauts (>40 years) compared to earlier models that were based on mortality risk transfer. Because astronauts and many other individuals should be considered as healthy workers, including never-smokers free of lifetime use of tobacco, we considered possible variations in risks and dose limits that would occur due to the reference population used for estimates. After adjusting cancer rates to remove smoking effects, radiation risks for lung and total cancer were estimated using a mixture model, with equal weights for additive and multiplicative transfer, to be 20% and 30% lower for males and females, respectively, for never-smokers compared to the average U.S. population. We recommend age- and gender-specific dose limits based on incidence-based risk transfer for never-smokers that could be used by NASA. Our analysis illustrates that gaining knowledge to improve transfer models, which entail knowledge of cancer initiation and promotion effects, could significantly reduce uncertainties in risk projections.     

The Future of Tropical Forest Species1

Deforestation and habitat loss are widely expected to precipitate an extinction crisis among tropical forest species. Humans cause deforestation, and humans living in rural settings have the greatest impact on extant forest area in the tropics. Current human demographic trends, including slowing population growth and intense urbanization, give reason to hope that deforestation will slow, natural forest regeneration through secondary succession will accelerate, and the widely anticipated mass extinction of tropical forest species will be avoided. Here, we show that the proportion of potential forest cover remaining is closely correlated with human population density among countries, in both the tropics and the temperate zone. We use United Nations population projections and continent‐specific relationships between both total and rural population density and forest remaining today to project future tropical forest cover. Our projections suggest that deforestation rates will decrease as population growth slows, and that a much larger area will continue to be forested than previous studies suggest. Tropical forests retracted to smaller areas during repeated Pleistocene glacial events in Africa and more recently in selected areas that supported large prehistoric human populations. Despite many caveats, these projections and observations provide hope that many tropical forest species will be able to survive the current wave of deforestation and human population growth. A strategy to preserve tropical biodiversity might include policies to improve conditions in tropical urban settings to hasten urbanization and preemptive conservation efforts in countries with large areas of extant forest and large projected rates of future human population growth. We hope that this first attempt inspires others to produce better models of future tropical forest cover and associated policy recommendations.     

Gene flow and immigration: genetic diversity and population structure of lions (Panthera leo) in Hwange National Park,Zimbabwe

The genetic diversity and population structure of a population of African lions in Hwange National Park, Zimbabwe, was studied using 17 microsatellite loci. Spatial genetic analysis using Bayesian methods suggested a weak genetic structure within the population and high levels of gene flow across the study area. We were able to identify a few individuals with aberrant or admixed ancestry, which we interpreted as either immigrants or as descendants thereof. This, together with relatively high genetic diversity, suggests that immigrants from beyond the study area have influenced the genetic structure within the park. We suggest that the levels of genetic diversity and the observed weak structure are indicative of the large and viable Okavango-Hwange population of which our study population is a part. Genetic patterns can also be attributed to still existing high levels of habitat connectivity between protected areas. Given expected increases in human populations and anthropogenic impacts, efforts to identify and maintain existing movement corridors between regional lion populations will be important in retaining the high genetic diversity status of this population. Our results show that understanding existing levels of genetic diversity and genetic connectivity has implications, not only for this lion population, but also for managing large wild populations of carnivores.     

The Combined Use of Correlative and Mechanistic Species Distribution Models Benefits Low Conservation Status Species

Species can respond to climate change by tracking appropriate environmental conditions in space, resulting in a range shift. Species Distribution Models (SDMs) can help forecast such range shift responses. For few species, both correlative and mechanistic SDMs were built, but allis shad (Alosa alosa), an endangered anadromous fish species, is one of them. The main purpose of this study was to provide a framework for joint analyses of correlative and mechanistic SDMs projections in order to strengthen conservation measures for species of conservation concern. Guidelines for joint representation and subsequent interpretation of models outputs were defined and applied. The present joint analysis was based on the novel mechanistic model GR3D (Global Repositioning Dynamics of Diadromous fish Distribution) which was parameterized on allis shad and then used to predict its future distribution along the European Atlantic coast under different climate change scenarios (RCP 4.5 and RCP 8.5). We then used a correlative SDM for this species to forecast its distribution across the same geographic area and under the same climate change scenarios. First, projections from correlative and mechanistic models provided congruent trends in probability of habitat suitability and population dynamics. This agreement was preferentially interpreted as referring to the species vulnerability to climate change. Climate change could not be accordingly listed as a major threat for allis shad. The congruence in predicted range limits between SDMs projections was the next point of interest. The difference, when noticed, required to deepen our understanding of the niche modelled by each approach. In this respect, the relative position of the northern range limit between the two methods strongly suggested here that a key biological process related to intraspecific variability was potentially lacking in the mechanistic SDM. Based on our knowledge, we hypothesized that local adaptations to cold temperatures deserved more attention in terms of modelling, but further in conservation planning as well.     

Quantifying the importance of geographic replication and representativeness when estimating demographic rates,using a coastal species as a case study

Demographic rates are rarely estimated over an entire species range, limiting empirical tests of ecological patterns and theories, and raising questions about the representativeness of studies that use data from a small part of a range. The uncertainty that results from using demographic rates from just a few sites is especially pervasive in population projections, which are critical for a wide range of questions in ecology and conservation. We developed a simple simulation to quantify how this lack of geographic representativeness can affect inferences about the global mean and variance of growth rates, which has implications for the robust design of a wide range of population studies. Using a coastal songbird, saltmarsh sparrow Ammodramus caudacutus, as a case study, we first estimated survival, fecundity, and population growth rates at 21 sites distributed across much of their breeding range. We then subsampled this large, representative dataset according to five sampling scenarios in order to simulate a variety of geographic biases in study design. We found spatial variation in demographic rates, but no large systematic patterns. Estimating the global mean and variance of growth rates using subsets of the data suggested that at least 10–15 sites were required for reasonably unbiased estimates, highlighting how relying on demographic data from just a few sites can lead to biased results when extrapolating across a species range. Sampling at the full 21 sites, however, offered diminishing returns, raising the possibility that for some species accepting some geographical bias in sampling can still allow for robust range‐wide inferences. The subsampling approach presented here, while conceptually simple, could be used with both new and existing data to encourage efficiency in the design of long‐term or large‐scale ecological studies.     

Genetic diversity and evolutionary patterns of Taraxacum kok‐saghyz Rodin

Taraxacum kok‐saghyz Rodin (TKS) is an important potential alternative source of natural inulin and rubber production, which has great significance for the production of industrial products. In this study, we sequenced 58 wild TKS individuals collected from four different geography regions worldwide to elucidate the population structure, genetic diversity, and the patterns of evolution. Also, the first flowering time, crown diameter, morphological characteristics of leaf, and scape of all TKS individuals were measured and evaluated statistically. Phylogenetic analysis based on SNPs and cluster analysis based on agronomic traits showed that all 58 TKS individuals could be roughly divided into three distinct groups: (a) Zhaosu County in Xinjiang (population AB, including a few individuals from population C and D); (b) Tekes County in Xinjiang (population C); and (c) Tuzkol lake in Kazakhstan (population D). Population D exhibited a closer genetic relationship with population C compared with population AB. Genetic diversity analysis further revealed that population expansion from C and D to AB occurred, as well as gene flow between them. Additionally, some natural selection regions were identified in AB population. Function annotation of candidate genes identified in these regions revealed that they mainly participated in biological regulation processes, such as transporter activity, structural molecule activity, and molecular function regulator. We speculated that the genes identified in selective sweep regions may contribute to TKS adaptation to the Yili River Valley of Xinjiang. In general, this study provides new insights in clarifying population structure and genetic diversity analysis of TKS using SNP molecular markers and agronomic traits.     

Population regulation and demography in a harvested freshwater crayfish from Madagascar

Despite advances in statistical techniques for investigating population dynamics based on mark–recapture data, the majority of our understanding about demography and regulation comes from relatively few taxa. Most proposed generalisations about the association between demography and variation in population size are based on data from vertebrates, there are few sufficiently detailed invertebrate studies to examine whether these generalisations are widely supported. The population biology of freshwater invertebrates is especially poorly known. We present a large-scale mark–recapture study of an endemic freshwater crayfish from Madagascar ( Astacoides granulimanus ). Variation in density, caused by difference in fishing pressure due to local taboos, allowed us to investigate density-dependent regulation. We found evidence of density dependence in fecundity operating through the proportion of reproductive females by size but no significant evidence of density dependence in growth. Using a prospective analysis based on the elasticities from a size-structured matrix model, we found that both recruitment rates and survival rates of large individuals were strongly associated with deterministic population growth – a result that differs from generalisations drawn from vertebrate studies. A central assumption in mark–recapture studies is that handling does not affect mortality. By treating the number of times an individual was captured as an individual covariate, easily done using the freeware program MARK, we were able to test for, and take account of, handling-induced mortality. Our results show interesting similarities, and important differences, to generalisations based on vertebrate studies and emphasise the importance of population studies on poorly known taxa.     

Hotspots of uncertainty in land‐use and land‐cover change projections: a global‐scale model comparison

Model‐based global projections of future land‐use and land‐cover (LULC) change are frequently used in environmental assessments to study the impact of LULC change on environmental services and to provide decision support for policy. These projections are characterized by a high uncertainty in terms of quantity and allocation of projected changes, which can severely impact the results of environmental assessments. In this study, we identify hotspots of uncertainty, based on 43 simulations from 11 global‐scale LULC change models representing a wide range of assumptions of future biophysical and socioeconomic conditions. We attribute components of uncertainty to input data, model structure, scenario storyline and a residual term, based on a regression analysis and analysis of variance. From this diverse set of models and scenarios, we find that the uncertainty varies, depending on the region and the LULC type under consideration. Hotspots of uncertainty appear mainly at the edges of globally important biomes (e.g., boreal and tropical forests). Our results indicate that an important source of uncertainty in forest and pasture areas originates from different input data applied in the models. Cropland, in contrast, is more consistent among the starting conditions, while variation in the projections gradually increases over time due to diverse scenario assumptions and different modeling approaches. Comparisons at the grid cell level indicate that disagreement is mainly related to LULC type definitions and the individual model allocation schemes. We conclude that improving the quality and consistency of observational data utilized in the modeling process and improving the allocation mechanisms of LULC change models remain important challenges. Current LULC representation in environmental assessments might miss the uncertainty arising from the diversity of LULC change modeling approaches, and many studies ignore the uncertainty in LULC projections in assessments of LULC change impacts on climate, water resources or biodiversity.     

Ancient,but not recent,population declines have had a genetic impact on alpine yellow-bellied toad populations,suggesting potential for complete recovery

Reduction in population size and local extinctions have been reported for the yellow-bellied toad, Bombina variegata, but the genetic impact of this is not yet known. In this study, we genotyped 200 individuals, using mtDNA cytochrome b and 11 nuclear microsatellites. We investigated fine-scale population structure and tested for genetic signatures of historical and recent population decline, using several statistical approaches, including likelihood methods and approximate Bayesian computation. Five major genetically divergent groups were found, largely corresponding to geography but with a clear exception of high genetic isolation in a highly touristic area. The effective sizes in the last few generations, as estimated from the random association among markers, never exceeded a few dozen of individuals. Our most important result is that several analyses converge in suggesting that genetic variation was shaped in all groups by a 7- to 45-fold demographic decline, which occurred between a few hundred and a few 1000 years ago. Remarkably, only weak evidence supports recent genetic impact related to human activities. We believe that the alpine B. variegata populations should be monitored and protected to stop their recent decline and to prevent local extinctions, with highest priority given to genetically isolated populations. Nonetheless, current genetic variation pattern, being mostly shaped in earlier times, suggests that complete recovery can be achieved. In general, our study is an example of how the potential for recovery should be inferred even under the co-occurrence of population decline, low genetic variation, and genetic bottleneck signals.     

A Re-Interpretation of the ‘Two-child Norm’ in Post-Transitional Demographic Systems: Fertility Intentions in Taiwan

Taiwan currently has one of the lowest fertility rates in the world, leading to projections of rapid population ageing and decline. In common with other territories in Pacific Asia, policies designed to support childbearing have recently been introduced. Some optimism for the future success of these policies has been drawn from the fact that the ‘ideal’ number of children stated in Taiwanese surveys is over two. In this way, Taiwan appears to fit the ‘two-child norm’ model identified for Europe and North America. Furthermore, this feature has led commentators to state that Taiwan is not in a ‘low fertility trap’–where positive feedback mechanisms emanating from the normalisation of small families, slow economic growth and ageing/declining population mean attempts to increase fertility become ever less likely to succeed. Using a recent national representative survey, and arguing that ‘intentions’ are a more reliable guide to understanding the circumstances of family formation, this paper explores fertility intentions in Taiwan with a special focus on women at parity one and parity two. This will form the first full-length examination of fertility intentions in Taiwan published in English and one of the few studies of Pacific Asia that reports a micro-level analysis. We argue that using intentions should provide a better ‘barometer’ of attitudes towards childbearing in Taiwan, and that through micro-level analysis, we can better identify the predictors of intentions that could, in turn, provide useful clues both for projections as well as shaping policy responses. While we found some evidence for a ‘two-child norm’ among childless women, this could be an unrealistic ideal. This is supported by the fact that a majority of women with one child do not intend to have another.     

Bioengineering nitrogen acquisition in rice: can novel initiatives in rice genomics and physiology contribute to global food security?

Rice is the most important crop species on earth, providing staple food for 70% of the world's human population. Over the past four decades, successes in classical breeding, fertilization, pest control, irrigation and expansion of arable land have massively increased global rice production, enabling crop scientists and farmers to stave off anticipated famines. If current projections for human population growth are correct, however, present rice yields will be insufficient within a few years. Rice yields will have to increase by an estimated 60% in the next 30 years, or global food security will be in danger. The classical methods of previous green revolutions alone will probably not be able to meet this challenge, without being coupled to recombinant DNA technology. Here, we focus on the promise of these modern technologies in the area of nitrogen acquisition in rice, recognizing that nitrogen deficiency compromises the realization of rice yield potential in the field more than any other single factor. We summarize rice-specific advances in four key areas of research: (1). nitrogen fixation, (2). primary nitrogen acquisition, (3). manipulations of internal nitrogen metabolism, and (4). interactions between nitrogen and photosynthesis. We develop a model for future plant breeding possibilities, pointing out the importance of coming to terms with the complex interactions among the physiological components under manipulation, in the context of ensuring proper targeting of intellectual and financial resources in this crucial area of research.     

Overestimates of maternity and population growth rates in multi-annual breeders

There has been limited attention to estimating maternity rate because it appears to be relatively simple. However, when used for multi-annual breeder species, such as the largest carnivores, the most common estimators introduce an upward bias by excluding unproductive females. Using a simulated dataset based on published data, we compare the accuracy of maternity estimates derived from standard methods against estimates derived from an alternative method. We show that standard methods overestimate maternity rates in the presence of unsuccessful pregnancies. Importantly, population growth rates derived from a matrix model parameterized with the biased estimates may indicate increasing populations although the populations are stable or even declining. We recommend the abandonment of the biased standard methods and to instead use the unbiased alternative method for population projections and assessments of population viability.     

The effects of prorating risk in the development of life‐tables

This study used computer models to investigate two different strategies for assessing risk in the development of age‐based life‐tables from studbook data sets. One methodology is similar to that currently employed in American Zoo and Aquarium Association population management, which prorates animals at risk within age‐classes. The other follows the method used in human life‐tables that assumes animals are at risk for the entire age‐class. This study concludes that prorating risk may invalidate population growth projections by significantly and unequally over‐estimating fecundity and mortality rates. This effect is most pronounced in species that have distinct breeding seasons (birth pulse populations), seasonal mortality, and small data sets. Recommendations include using a non‐prorated methodology, tabulating life‐tables using only completely known age‐class data, and combining population parameters for emigrations, releases, and deaths for population growth projections. Zoo Biol 20:279–291, 2001. © 2001 Wiley‐Liss, Inc.     

Analysis of Population Structure: A Unifying Framework and Novel Methods Based on Sparse Factor Analysis

We consider the statistical analysis of population structure using genetic data. We show how the two most widely used approaches to modeling population structure, admixture-based models and principal components analysis (PCA), can be viewed within a single unifying framework of matrix factorization. Specifically, they can both be interpreted as approximating an observed genotype matrix by a product of two lower-rank matrices, but with different constraints or prior distributions on these lower-rank matrices. This opens the door to a large range of possible approaches to analyzing population structure, by considering other constraints or priors. In this paper, we introduce one such novel approach, based on sparse factor analysis (SFA). We investigate the effects of the different types of constraint in several real and simulated data sets. We find that SFA produces similar results to admixture-based models when the samples are descended from a few well-differentiated ancestral populations and can recapitulate the results of PCA when the population structure is more “continuous,” as in isolation-by-distance models.     

Modulation of synchrony without changes in firing rates

It was often reported and suggested that the synchronization of spikes can occur without changes in the firing rate. However, few theoretical studies have tested its mechanistic validity. In the present study, we investigate whether changes in synaptic weights can induce an independent modulation of synchrony while the firing rate remains constant. We study this question at the level of both single neurons and neuronal populations using network simulations of conductance based integrate-and-fire neurons. The network consists of a single layer that includes local excitatory and inhibitory recurrent connections, as well as long-range excitatory projections targeting both classes of neurons. Each neuron in the network receives external input consisting of uncorrelated Poisson spike trains. We find that increasing this external input leads to a linear increase of activity in the network, as well␣as an increase in the peak frequency of oscillation. In␣contrast, balanced changes of the synaptic weight of␣excitatory long-range projections for both classes of postsynaptic neurons modulate the degree of synchronization without altering the firing rate. These results demonstrate that, in a simple network, synchronization and firing rate can be modulated independently, and thus, may be used as independent coding dimensions. Electronic supplementary material  The online version of this article (doi: ) contains supplementary material, which is available to authorized users.     

Evolution and population dynamics in stochastic environments

Inter-generational temporal variability of the environment is important in the evolution and adaptation of phenotypic traits. We discuss a population-dynamic approach which plays a central role in the analysis of evolutionary processes. The basic principle is that the phenotypes with the greatest long-term average growth rate will dominate the entire population. The calculation of longterm average growth rates for populations under temporal stochasticity can be highly cumbersome. However, for a discrete non-overlapping population, it is identical to the geometric mean of the growth rates (geometric mean fitness), which is usually different from the simple arithmetic mean of growth rates. Evolutionary outcomes based on geometric mean fitness are often very different from the predictions based on the usual arithmetic mean fitness. In this paper we illustrate the concept of geometric mean fitness in a few simple models. We discuss its implications for the adaptive evolution of phenotypes, e.g. foraging under predation risks and clutch size. Next, we present an application: the risk-spreading egg-laying behaviour of the cabbage white butterfly, and develop a two-patch population dynamic model to show how the optimal solution diverges from the ssual arithmetic mean approach. The dynamics of these stochastic models cannot be predicted from the dynamics of simple deterministic models. Thus the inclusion of stochastic factors in the analyses of populations is essential to the understanding of not only population dynamics, but also their evolutionary dynamics.     

New Routes to Phylogeography: A Bayesian Structured Coalescent Approximation

Phylogeographic methods aim to infer migration trends and the history of sampled lineages from genetic data. Applications of phylogeography are broad, and in the context of pathogens include the reconstruction of transmission histories and the origin and emergence of outbreaks. Phylogeographic inference based on bottom-up population genetics models is computationally expensive, and as a result faster alternatives based on the evolution of discrete traits have become popular. In this paper, we show that inference of migration rates and root locations based on discrete trait models is extremely unreliable and sensitive to biased sampling. To address this problem, we introduce BASTA (BAyesian STructured coalescent Approximation), a new approach implemented in BEAST2 that combines the accuracy of methods based on the structured coalescent with the computational efficiency required to handle more than just few populations. We illustrate the potentially severe implications of poor model choice for phylogeographic analyses by investigating the zoonotic transmission of Ebola virus. Whereas the structured coalescent analysis correctly infers that successive human Ebola outbreaks have been seeded by a large unsampled non-human reservoir population, the discrete trait analysis implausibly concludes that undetected human-to-human transmission has allowed the virus to persist over the past four decades. As genomics takes on an increasingly prominent role informing the control and prevention of infectious diseases, it will be vital that phylogeographic inference provides robust insights into transmission history.