Maximum likelihood estimation of a migration matrix and effective population sizes in n subpopulations by using a coalescent approach

A maximum likelihood estimator based on the coalescent for unequal migration rates and different subpopulation sizes is developed. The method uses a Markov chain Monte Carlo approach to investigate possible genealogies with branch lengths and with migration events. Properties of the new method are shown by using simulated data from a four-population n-island model and a source–sink population model. Our estimation method as coded in migrate is tested against genetree; both programs deliver a very similar likelihood surface. The algorithm converges to the estimates fairly quickly, even when the Markov chain is started from unfavorable parameters. The method was used to estimate gene flow in the Nile valley by using mtDNA data from three human populations.

Population genetic structure and demography analysis in palinurus elephas populations from atlantic and mediterranean waters

Report for the scientific sojourn at the University of Reading, United Kingdom, from January until May 2008. The main objectives have been firstly to infer population structure and parameters in demographic models using a total of 13 microsatellite loci for genotyping approximately 30 individuals per population in 10 Palinurus elephas populations both from Mediterranean and Atlantic waters. Secondly, developing statistical methods to identify discrepant loci, possibly under selection and implement those methods using the R software environment. It is important to consider that the calculation of the probability distribution of the demographic and mutational parameters for a full genetic data set is numerically difficult for complex demographic history (Stephens 2003). The Approximate Bayesian Computation (ABC), based on summary statistics to infer posterior distributions of variable parameters without explicit likelihood calculations, can surmount this difficulty. This would allow to gather information on different demographic prior values (i.e. effective population sizes, migration rate, microsatellite mutation rate, mutational processes) and assay the sensitivity of inferences to demographic priors by assuming different priors.

Population consequences of environmental sex reversal.

When sex determination in a species is predominantly genetic but environmentally reversible, exposure to (anthropogenic) changes in the environment can lead to shifts in a population's sex ratio. Such scenarios may be common in many fishes and amphibians, yet their ramifications remain largely unexplored. We used a simple model to study the (short-term) population consequences of environmental sex reversal (ESR). We examined the effects on sex ratios, sex chromosome frequencies, and population growth and persistence after exposure to environmental forces with feminizing or masculinizing tendencies. When environmental feminization was strong, X chromosomes were driven to extinction. Analogously, extinction of normally male-linked genetic factors (e.g., Y chromosomes) was caused by continuous environmental masculinization. Although moderate feminization was beneficial for population growth in the absence of large viability effects, our results suggest that the consequences of ESR are generally negative in terms of population size and the persistence of sex chromosomes. Extreme sex ratios resulting from high rates of ESR also reduced effective population sizes considerably. This may limit any evolutionary response to the deleterious effects of ESR. Our findings suggest that ESR changes population growth and sex ratios in some counter-intuitive ways and can change the predominant factor in sex determination from genetic to fully environmental, often within only a few tens of generations. Populations that lose genetic sex determination may quickly go extinct if the environmental forces that cause sex reversal cease.

Manipulating sex ratio to increase population growth: the example of the Lesser Kestrel

Small or decreasing populations call for emergency actions like, for example, captive breeding programs. Such programs aim at rapidly increasing population sizes in order to reduce the loss of genetic variability and to avoid possible Allee effects. The Lesser Kestrel Falco naumanni is one of the species that is currently supported in several captive breeding programs at various locations. Here, we model the demographic and genetic consequences of potential management strategies that are based on offspring sex ratio manipulation. Increased population growth could be achieved by manipulating female conditions and/or male attractiveness in the captive breeders and consequently shifting the offspring sex ratio towards more female offspring, which are then used for reintroduction. Fragmenting populations into wild-breeding and captive-breeding demes and manipulating population sex ratio both immediately increase the inbreeding coefficient in the next generation (i.e. decrease N-e) but may, in the long term, reduce the loss of genetic variability if population growth is restricted by the number of females. We use the Lesser Kestrel and the wealth of information that is available on this species to predict the long-term consequences of various kinds of sex-ratio manipulation. We find that, in our example and possibly in many other cases, a sex-ratio manipulation that seems realistic could have a beneficial effect on the captive breeding program. However, the possible long-term costs and benefits of such measures need to be carefully optimized.

Extreme population differentiation in vulnerable slavemaking ant with fragmented distribution

Understanding levels of population differentiation and inbreeding are important issues in conservation biology, especially for social Hymenoptera with fragmented and small population sizes. Isolated populations are more vulnerable to genetic loss and extinction than those with extended continuous distributions. However, small populations are not always a consequence of a recent reduction of their habitat. Thus, determining the history of population isolation and current patterns of genetic variation of a species is crucial for its conservation. Rossomyrmex minuchae is a slave-making ant with patchy distribution in South Eastern Spain and is classified as vulnerable by the IUCN. In contrast, the other three known species of the genus are presumed to show more uniform distributions. Here we investigate the genetic diversity and population structure of R. minuchae and compare it with that found in two other species of the genus: R. anatolicus and R. quandratinodum. We conclude that although genetic diversity of R. minuchae is low, there is no evidence of a recent bottleneck, suggesting a gradual and natural fragmentation process. We also show extreme population differentiation at nuclear and mitochondrial markers, and isolation by distance at a local scale. Despite some evidence for inbreeding and low genetic variation within populations, we found almost no diploid males, a finding which contrasts with that expected in inbred Hymenoptera with single locus complementary sex determination. This could mean that sex is determined by another mechanism. We argue that continued low population size means that detrimental effects of inbreeding and low genetic variation are likely in the future. We suggest that a policy of artificial gene flow aimed at increasing within population variation is considered as a management option.

Stable isotopes provide insight into population structure and segregation in eastern North Atlantic sperm whales

In pelagic species inhabiting large oceans, genetic differentiation tends to be mild and populations devoid of structure. However, large cetaceans have provided many examples of structuring. Here we investigate whether the sperm whale, a pelagic species with large population sizes and reputedly highly mobile, shows indication of structuring in the eastern North Atlantic, an ocean basin in which a single population is believed to occur. To do so, we examined stable isotope values in sequential growth layer groups of teeth from individuals sampled in Denmark and NW Spain. In each layer we measured oxygen- isotope ratios (δ18O) in the inorganic component (hydroxyapatite), and nitrogen and carbon isotope ratios (δ15N: δ13C) in the organic component (primarily collagenous). We found significant differences between Denmark and NW Spain in δ15N and δ18O values in the layer deposited at age 3, considered to be the one best representing the baseline of the breeding ground, in δ15N, δ13C and δ18O values in the period up to age 20, and in the ontogenetic variation of δ15N and δ18O values. These differences evidence that diet composition, use of habitat and/or migratory destinations are dissimilar between whales from the two regions and suggest that the North Atlantic population of sperm whales is more structured than traditionally accepted.

The effects of spatial and temporal heterogeneity on the population dynamics of four animal species in a Danish landscape

Background: Variation in carrying capacity and population return rates is generally ignored in traditional studies of population dynamics. Variation is hard to study in the field because of difficulties controlling the environment in order to obtain statistical replicates, and because of the scale and expense of experimenting on populations. There may also be ethical issues. To circumvent these problems we used detailed simulations of the simultaneous behaviours of interacting animals in an accurate facsimile of a real Danish landscape. The models incorporate as much as possible of the behaviour and ecology of skylarks Alauda arvensis, voles Microtus agrestis, a ground beetle Bembidion lampros and a linyphiid spider Erigone atra. This allows us to quantify and evaluate the importance of spatial and temporal heterogeneity on the population dynamics of the four species. Results: Both spatial and temporal heterogeneity affected the relationship between population growth rate and population density in all four species. Spatial heterogeneity accounted for 23–30% of the variance in population growth rate after accounting for the effects of density, reflecting big differences in local carrying capacity associated with the landscape features important to individual species. Temporal heterogeneity accounted for 3–13% of the variance in vole, skylark and spider, but 43% in beetles. The associated temporal variation in carrying capacity would be problematic in traditional analyses of density dependence. Return rates were less than one in all species and essentially invariant in skylarks, spiders and beetles. Return rates varied over the landscape in voles, being slower where there were larger fluctuations in local population sizes. Conclusion: Our analyses estimated the traditional parameters of carrying capacities and return rates, but these are now seen as varying continuously over the landscape depending on habitat quality and the mechanisms of density dependence. The importance of our results lies in our demonstration that the effects of spatial and temporal heterogeneity must be accounted for if we are to have accurate predictive models for use in management and conservation. This is an area which until now has lacked an adequate theoretical framework and methodology.

The use of image analysis to estimate population growth rate in Daphnia magna

1. Population growth rate (PGR) is central to the theory of population ecology and is crucial for projecting population trends in conservation biology, pest management and wildlife harvesting. Furthermore, PGR is increasingly used to assess the effects of stressors. Image analysis that can automatically count and measure photographed individuals offers a potential methodology for estimating PGR. 2. This study evaluated two ways in which the PGR of Daphnia magna, exposed to different stressors, can be estimated using an image analysis system. The first method estimated PGR as the ratio of counts of individuals obtained at two different times, while the second method estimated PGR as the ratio of population sizes at two different times, where size is measured by the sum of the individuals' surface areas, i.e. total population surface area. This method is attractive if surface area is correlated with reproductive value (RV), as it is for D. magna, because of the theoretical result that PGR is the rate at which the population RV increases. 3. The image analysis system proved reliable and reproducible in counting populations of up to 440 individuals in 5 L of water. Image counts correlated well with manual counts but with a systematic underestimate of about 30%. This does not affect accuracy when estimating PGR as the ratio of two counts. Area estimates of PGR correlated well with count estimates, but were systematically higher, possibly reflecting their greater accuracy in the study situation. 4. Analysis of relevant scenarios suggested the correlation between RV and body size will generally be good for organisms in which fecundity correlates with body size. In these circumstances, area estimation of PGR is theoretically better than count estimation. 5. Synthesis and applications. There are both theoretical and practical advantages to area estimation of population growth rate when individuals' reproductive values are consistently well correlated with their surface areas. Because stressors may affect both the number and quality of individuals, area estimation of population growth rate should improve the accuracy of predicting stress impacts at the population level.

Linking the coevolutionary and population dynamics of host-parasitoid interactions

The interplay between coevolutionary and population or community dynamics is currently the focus of much empirical and theoretical consideration. Here, we develop a simulation model to study the coevolutionary and population dynamics of a hypothetical host-parasitoid interaction. In the model, host resistance and parasitoid virulence are allowed to coevolve. We investigate how trade-offs associated with these traits modify the system's coevolutionary and population dynamics. The most important influence on these dynamics comes from the incorporation of density-dependent costs of resistance ability. We find three main outcomes. First, if the costs of resistance are high, then one or both of the players go extinct. Second, when the costs of resistance are intermediate to low, cycling population and coevolutionary dynamics are found, with slower evolutionary changes observed when the costs of virulence are also low. Third, when the costs associated with resistance and virulence are both high, the hosts trade-off resistance against fecundity and invest little in resistance. However, the parasitoids continue to invest in virulence, leading to stable host and parasitoid population sizes. These results support the hypothesis that costs associated with resistance and virulence will maintain the heritable variation in these traits found in natural populations and that the nature of these trade-offs will greatly influence the population dynamics of the interacting species.

The population dynamics of disease on short and long time-scales

Observational evidence is scarce concerning the distribution of plant pathogen population sizes or densities as a function of time-scale or spatial scale. For wild pathosystems we can only get indirect evidence from evolutionary patterns and the consequences of biological invasions.We have little or no evidence bearing on extermination of hosts by pathogens, or successful escape of a host from a pathogen. Evidence over the last couple of centuries from crops suggest that the abundance of particular pathogens in the spectrum affecting a given host can vary hugely on decadal timescales. However, this may be an artefact of domestication and intensive cultivation. Host-pathogen dynamics can be formulated mathematically fairly easily–for example as SIR-type differential equation or difference equation models, and this has been the (successful) focus of recent work in crops. “Long-term” is then discussed in terms of the time taken to relax from a perturbation to the asymptotic state. However, both host and pathogen dynamics are driven by environmental factors as well as their mutual interactions, and both host and pathogen co-evolve, and evolve in response to external factors. We have virtually no information about the importance and natural role of higher trophic levels (hyperpathogens) and competitors, but they could also induce long-scale fluctuations in the abundance of pathogens on particular hosts. In wild pathosystems the host distribution cannot be modelled as either a uniform density or even a uniform distribution of fields (which could then be treated as individuals). Patterns of short term density-dependence and the detail of host distribution are therefore critical to long-term dynamics. Host density distributions are not usually scale-free, but are rarely uniform or clearly structured on a single scale. In a (multiply structured) metapopulation with coevolution and external disturbances it could well be the case that the time required to attain equilibrium (if it exists) based on conditions stable over a specified time-scale is longer than that time-scale. Alternatively, local equilibria may be reached fairly rapidly following perturbations but the meta-population equilibrium be attained very slowly. In either case, meta-stability on various time-scales is a more relevant than equilibrium concepts in explaining observed patterns.

City sizes and industry concentration

In a general equilibrium model of trade under transportation costs between two cities we show how the relative population sizes are simultaneously detemined with the degree of geographic concentration of industries characterized by different elasticities of scale of production. The effect on city size of the presence of nontraded goods is also analyzed.

City sizes and industry concentration

In a general equilibrium model of trade under transportation costs between two cities we show how the relative population sizes are simultaneously determined with the degree of geographic concentration of industries characterized by different elasticities of scale of production. The effect on city size of the presence of nontraded goods is also analyzed .

Estimates of Foraging Population and Territory of Heterotermes tenuis Colonies using Mark-Release-Recapture (Isoptera: Rhinotermitidae)

Heterotermes tenuis is an important economic pest in São Paulo state. Foraging populations of three field colonies of H. tenuis located on a University campus (UNESP, Rio Claro, SP, Brazil) were characterized. Foraging populations of H. tenuis colonies were calculated using four cycles of a mark-release-recapture program with a weighted mean method. The foraging population sizes of three colonies: A, B and C were 389,313±14,907; 265,589 ±12,635; and 641,600∓12,127; respectively. Foraging biomasses were 0.77 kg in the colony A, 0.51 kg in the colony B and 1.17 kg in colony C. Mean worker biomass was approximately 1.9 mg. Foraging territories occupied an area ranging from 70 m2 to 131 m2 per colony. The maximum linear foraging distance traveled by H. tenuis was 28m.

Solving the Levins' paradox in the logistic model to the population growth

We introduce a new method to improve Markov maps by means of a Bayesian approach. The method starts from an initial map model, wherefrom a likelihood function is defined which is regulated by a temperature-like parameter. Then, the new constraints are added by the use of Bayes rule in the prior distribution. We applied the method to the logistic map of population growth of a single species. We show that the population size is limited for all ranges of parameters, allowing thus to overcome difficulties in interpretation of the concept of carrying capacity known as the Levins paradox. © Published under licence by IOP Publishing Ltd.

Global optimization using a genetic algorithm with hierarchically structured population

This paper applies a genetic algorithm with hierarchically structured population to solve unconstrained optimization problems. The population has individuals distributed in several overlapping clusters, each one with a leader and a variable number of support individuals. The hierarchy establishes that leaders must be fitter than its supporters with the topological organization of the clusters following a tree. Computational tests evaluate different population structures, population sizes and crossover operators for better algorithm performance. A set of known benchmark test problems is solved and the results found are compared with those obtained from other methods described in the literature, namely, two genetic algorithms, a simulated annealing, a differential evolution and a particle swarm optimization. The results indicate that the method employed is capable of achieving better performance than the previous approaches in regard as the two criteria usually employed for comparisons: the number of function evaluations and rate of success. The method also has a superior performance if the number of problems solved is taken into account. (C) 2013 Elsevier B.V. All rights reserved.