Evaluation of a DNA pooled-sampling strategy for estimating the RFLP diversity of maize populations

Molecular characterization by means of RFLPs of large sets of populations is presently limited by experimental costs. In order to reduce costs, we have evaluated a method based on the RFLP analysis of balanced bulks of DNA from several individuals. The precision of this approach for estimating allele frequencies within each population was investigated using (i) DNA extracted from controlled bulks of leaf tissues of maize inbred lines, (ii) data obtained from individual analyses of 10 maize populations. Both approaches showed that allele frequencies can generally be estimated with a high precision (coefficients of determination up to 0.99 for some probe-enzyme combinations assayed), relative to the variation in allele frequencies observed among maize populations. Although further efforts are needed to define a set of probe-enzyme combinations that can be routinely image processed, these results, and preliminary results from a 65 maize populations project, suggest that this approach could provide highly informative data for large sets of populations, and at relatively low costs.     

Effective/census population size ratio estimation: a compendium and appraisal

With an ecological-evolutionary perspective increasingly applied toward the conservation and management of endangered or exploited species, the genetic estimation of effective population size (N_e) has proliferated. Based on a comprehensive analysis of empirical literature from the past two decades, we asked: (i) how often do studies link N_e to the adult census population size (N)? (ii) To what extent is N_e correctly linked to N? (iii) How readily is uncertainty accounted for in both N_e and N when quantifying N_e/N ratios? and (iv) how frequently and to what degree might errors in the estimation of N_e or N affect inferences of N_e/N ratios? We found that only 20% of available N_e estimates (508 of 2617; 233 studies) explicitly attempted to link N_e and N; of these, only 31% (160 of 508) correctly linked N_e and N. Moreover, only 7% (41 of 508) of N_e/N ratios (correctly linked or not) reported confidence intervals for both N_e and N; for those cases where confidence intervals were reported for N_e only, 31% of N_e/N ratios overlapped with 1, of which more than half also reached below N_e/N = 0.01. Uncertainty in N_e/N ratios thus sometimes spanned at least two orders of magnitude. We conclude that the estimation of N_e/N ratios in natural populations could be significantly improved, discuss several options for doing so, and briefly outline some future research directions.     

Estimating aboveground herbaceous plant biomass via proxies: The confounding effects of sampling year and precipitation

Direct measurements of aboveground plant biomass are often not feasible, thus various biomass proxies are in use. To obtain biomass estimates, these proxies are calibrated against actual biomass, and the resulting proxy-biomass relationship is often used across multiple years and experimental treatments within a study. We investigated how the proxy-biomass relationship varied across years and considered interannual precipitation variability as a contributing factor.We sampled a perennial grassland for ten consecutive years (2003–2012) in central Hungary and estimated vegetation cover and Normalized Difference Vegetation Index (NDVI); two frequently used biomass proxies representing two contrasting methods. Aboveground live herbaceous plant biomass was harvested from each plot after sampling, and regression models were used to assess the relationship between biomass proxies and actual aboveground biomass.We found that cover and NDVI were equally effective at estimating biomass. However, the relationship between either biomass proxy and actual biomass varied amongst years, and this was related to the amount of precipitation. In wetter years, proxy-biomass relationships were steeper than in drier years.These results indicate that using the same proxy-biomass relationship across different years or precipitation regimes may not be valid and may introduce systematic error into biomass estimations in long-term studies or precipitation manipulation experiments.     

Edge effects on palm diversity in rain forest fragments in western Ecuador

At the edges of tropical rain forest fragments, altered abiotic and biotic conditions influence the structure and dynamics of plant communities. In Neotropical rain forests, palms (Arecaceae) are important floristic and ecological elements. Palms’ responses to edge effects appear to be idiosyncratic and to depend on the level of disturbance at edges. This paper explores how variation in forest structure at the edges of two old-growth forest fragments in a tropical rain forest in western Ecuador affects palms of different species, life-forms, and size classes. We investigate (1) how edge effects influence the relative proportion of palm adults and juveniles, (2) how distance from the forest edge affects palm density and species richness, (3) how altered forest structure along edges affects palm density. We found that at edges (1) palm communities had a lower proportion of adults relative to juvenile individuals compared to continuous forests, (2) the density of two species of palms and the overall species richness of the palm community tended to decrease toward the edges within forest fragments, and, (3) altered forest structure decreased the density of adult palms. Hence, edge effects on palms were controlled by the degree of modification of the forest structure, and by species responses to edge-related disturbance.     

Nonidentifiability of population size from capture-recapture data with heterogeneous detection probabilities

Heterogeneity in detection probabilities has long been recognized as problematic in mark-recapture studies, and numerous models developed to accommodate its effects. Individual heterogeneity is especially problematic, in that reasonable alternative models may predict essentially identical observations from populations of substantially different sizes. Thus even with very large samples, the analyst will not be able to distinguish among reasonable models of heterogeneity, even though these yield quite distinct inferences about population size. The problem is illustrated with models for closed and open populations.     

Statistical inference for serial dilution assay data

Serial dilution assays are widely employed for estimating substance concentrations and minimum inhibitory concentrations. The Poisson-Bernoulli model for such assays is appropriate for count data but not for continuous measurements that are encountered in applications involving substance concentrations. This paper presents practical inference methods based on a log-normal model and illustrates these methods using a case application involving bacterial toxins.     

Preservation and computer-aided microscopic analysis of planktonic Protozoa and algae

Samples of microplankton and larger nanoplankton (5 to 200 m) are preserved with a combination of Lugol's solution and DaFano's fixative. Organisms are then settled on a gelatin-coated slide, dried and embedded in 40 percent glycerin. Counting and sizing is performed under a microscope using a drawing tube, which facilitates measuring the organisms with a microcomputer-interfaced caliper. An interactive computer program, written in BASIC, allows for estimating the volumes of cells in up to 40 shape/species categories. The program then saves data on a disk, retrieves them, and calculates the results either for individual species (abundance, biomass, and mean cell volume) or as a pooled size spectrum of all organisms measured.     

Statistical shape and appearance models for fast and automated estimation of proximal femur fracture load using 2D finite element models

Estimating the risk of osteoporotic fractures is an important diagnostic step that needs to be taken before medicinal treatment. Densitometry-based criteria are normally used in clinical practice for this purpose. However, densitometry-based techniques could not explain all low-energy fractures. As patient-specific finite element (FE) models allow for consideration of other parameters (e.g. load conditions) that are known to be associated with fracture, they are considered promising candidates for more accurate fracture risk estimation. Nevertheless, they are often time consuming, expensive, and complex to build and may need the type of expertise that is not normally available in clinical settings. In this study, we report the development of an automated platform for estimating proximal femur fracture loads using patient-specific 2D FE models generated using dual-energy x-ray absorptiometry (DXA) scans. First, a statistical shape and appearance model (SSAM) is built using DXA scans of patients screened for osteoporosis following a low energy fracture. SSAM is then used together with Active Appearance Models (AAM) for automated segmentation of the proximal femur from new unseen DXA scans. The mean point-to-curve error of the automated procedure, i.e. 1.2–1.4 mm, is shown to be only slightly larger than the intra-observer variability of manual segmentation, i.e. 1.0 mm. Moreover, the developed platform automatically meshes the segmented shape, assigns density-based mechanical properties, assigns loads and boundary conditions, submits the 2D FE model for solution, and performs post-processing of the 2D FE simulation data to determine fracture loads. The fracture loads predicted using the manually generated and automatically generated 2D FE models are shown to be very close with a mean difference of around 8.8%. Repeated measures ANOVA showed no significant differences between the fracture loads calculated using FE models manually generated by three independent observers and those calculated using the automatically generated FE models (p>0.05).     

INBREEDING DEPRESSION IN TWO MIMULUS TAXA MEASURED BY MULTIGENERATIONAL CHANGES IN THE INBREEDING COEFFICIENT

In mixed-mating plant populations, one can estimate the relative fitness of selfed progeny w by measuring the inbreeding coefficient F and selfing rate s of adults of one generation, together with F of adults in the following generation (after selection). In the first application of this multigenerational method, we estimated F and s for adults over three consecutive generations in adjacent populations of two annual Mimulus taxa: the outbreeding M. guttatus and the inbreeding M. platycalyx. This gave estimates of w for the last two generations. Although average multilocus selfing rates were high in both taxa (0.63 in M. guttatus; 0.84 in M. platycalyx), the relative fitness of selfed progeny averaged only 0.19 in M. guttatus and 0.32 in M. platycalyx. An alternative estimator for w that incorporates biparental inbreeding gave even lower estimates of w. These values are significantly below the 0.5 threshold thought to favor selfing, and show that partially selfing populations can harbor substantial genetic load. In accordance with the purging hypothesis, the more highly selfing M. platycalyx showed marginally lower inbreeding depression than M. guttatus in both years (P = 0.08). Inbreeding depression and selfing rates also varied among years in concert among taxa. Several sources of bias are discussed, but computer simulations indicate it is unlikely that w is biased downwards by linkage of marker loci to load loci.