Molecular techniques reveal cryptic life history and demographic processes of a critically endangered marine turtle

The concept of ‘effective population size’ (Ne), which quantifies how quickly a population will lose genetic variability, is one of the most important contributions of theoretical evolutionary biology to practical conservation management. Ne is often much lower than actual population size: how much so depends on key life history and demographic parameters, such as mating systems and population connectivity, that often remain unknown for species of conservation concern. Molecular techniques allow the indirect study of these parameters, as well as the estimation of current and historical Ne. Here, we use genotyping to assess the genetic health of an important population of the critically endangered hawksbill turtle (Eretmochelys imbricata), a slow-to-mature, difficult-to-observe species with a long history of severe overhunting. Our results were surprisingly positive: we found that the study population, located in the Republic of Seychelles, Indian Ocean, has a relatively large Ne, estimated to exceed 1000, and showed no evidence of a recent reduction in Ne (i.e. no genetic bottleneck). Furthermore, molecular inferences suggest the species' mating system is conducive to maintaining a large Ne, with a relatively large and widely distributed male population promoting considerable gene flow amongst nesting sites across the Seychelles area. This may also be reinforced by the movement of females between nesting sites. Our study underlines how molecular techniques can help to inform conservation biology. In this case our results suggest that this important hawksbill population is starting from a relatively strong position as it faces new challenges, such as global climate change

Serological Evidence of Discrete Spatial Clusters of Plasmodium falciparum Parasites

BACKGROUND: Malaria transmission may be considered to be homogenous with well-mixed parasite populations (as in the classic Ross/Macdonald models). Marked fine-scale heterogeneity of transmission has been observed in the field (i.e., over a few kilometres), but there are relatively few data on the degree of mixing. Since the Plasmodium falciparum Erythrocyte Membrane Protein 1 (PfEMP1) is highly polymorphic, the host's serological responses may be used to infer exposure to parasite sub-populations. METHODS AND FINDINGS: We measured the antibody responses to 46 individual PfEMP1 domains at four time points among 450 children in Kenya, and identified distinct spatial clusters of antibody responses to individual domains. 35 domains showed strongly significant sero-clusters at p = 0.001. Individuals within the high transmission hotspot showed the greatest diversity of anti-PfEMP1 responses. Individuals outside the hotspot had a less diverse range of responses, even if as individuals they were at relatively intense exposure. CONCLUSIONS: We infer that antigenically distinct sub-populations of parasites exist on a fine spatial scale in a study area of rural Kenya. Further studies should examine antigenic variation over longer periods of time and in different study areas

Data from: Evidence of opposing fitness effects of parental heterozygosity and relatedness in a critically endangered marine turtle?

How individual genetic variability relates to fitness is important in understanding evolution and the processes affecting populations of conservation concern. Heterozygosity-fitness correlations (HFCs) have been widely used to study this link in wild populations, where key parameters that affect both variability and fitness, such as inbreeding, can be difficult to measure. We used estimates of parental heterozygosity and genetic similarity (‘relatedness’) derived from 32 microsatellite markers to explore the relationship between genetic variability and fitness in a population of the critically endangered hawksbill turtle, Eretmochelys imbricata. We found no effect of maternal MLH (multilocus heterozygosity) on clutch size or egg success rate, and no single-locus effects. However, we found effects of paternal MLH and parental relatedness on egg success rate that interacted in a way that may result in both positive and negative effects of genetic variability. Multicollinearity in these tests was within safe limits, and null simulations suggested the effect was not an artefact of using paternal genotypes reconstructed from large samples of offspring. Our results could imply a tension between inbreeding and outbreeding depression in this system, which is biologically feasible in turtles: female-biased natal philopatry may elevate inbreeding risk and local adaptation, and both processes may be disrupted by male-biased dispersal. Although this conclusion should be treated with caution due to a lack of significant identity disequilibrium, our study shows the importance of considering both positive and negative effects when assessing how variation in genetic variability affects fitness in wild systems

Data from: Reconstructing paternal genotypes to infer patterns of sperm storage and sexual selection in the hawksbill turtle

Postcopulatory sperm storage can serve a range of functions, including ensuring fertility, allowing delayed fertilization and facilitating sexual selection. Sperm storage is likely to be particularly important in wide-ranging animals with low population densities, but its prevalence and importance in such taxa, and its role in promoting sexual selection, are poorly known. Here, we use a powerful microsatellite array and paternal genotype reconstruction to assess the prevalence of sperm storage and test sexual selection hypotheses of genetic biases to paternity in one such species, the critically endangered hawksbill turtle, Eretmochelys imbricata. In the majority of females (90.7%, N = 43), all offspring were sired by a single male. In the few cases of multiple paternity (9.3%), two males fertilized each female. Importantly, the identity and proportional fertilization success of males were consistent across all sequential nests laid by individual females over the breeding season (up to five nests over 75 days). No males were identified as having fertilized more than one female, suggesting that a large number of males are available to females. No evidence for biases to paternity based on heterozygosity or relatedness was found. These results indicate that female hawksbill turtles are predominantly monogamous within a season, store sperm for the duration of the nesting season and do not re-mate between nests. Furthermore, females do not appear to be using sperm storage to facilitate sexual selection. Consequently, the primary value of storing sperm in marine turtles may be to uncouple mating and fertilization in time and avoid costly re-mating

Intelligent methods for solving inverse problems of backscattering spectra with noise : a comparison between neural networks and simulated annealing

This paper investigates two different intelligent techniques - the neural network (NN) method and the simulated annealing (SA) algorithm for solving the inverse problem of Rutherford Backscattering (RBS) with noisy data. The RBS inverse problem is to determine the sample structure information from measured spectra, which can be defined as either a function approximation or a non-linear optimization problem. Early studies emphasized on numerical methods and empirical fitting. In this work, we have applied intelligent techniques and compared their performance and effectiveness for spectral data analysis by solving the inverse problem. Since each RBS spectrum may contain up to 512 data points, principal component analysis is used to make the feature extraction so as to ease the complexity of constructing the network. The innovative aspects of our work include introducing dimensionality reduction and noise modeling. Experiments on RBS spectra from SiGe thin films on a silicon substrate show that the SA is more accurate but the NN is faster, though both methods produce satisfactory results. Both methods are resilient to 10% Poisson noise in the input. These new findings indicate that in RBS data analysis the NN approach should be preferred when fast processing is required; whereas the SA method becomes the first choice should the analysis accuracy be targeted