Sampling Schemes for Studying Growth of Children

Efficiency of linked cross-sectional scheme has been compared with pure longitudinal schemes for generalised estimation of norm relaxing the condition of constancy of variances. The relevant theory of estimation has been developed and the expression for the optimum estimators alongwith their variances have been derived. The percentage gain in efficiency has been calculated. It has been observed that for higher values of Q, percentage gain in efficiency of proposed scheme over cross-sectional is very high.     

Can dominance genetic variance be ignored in evolutionary quantitative genetic analyses of wild populations?

Accurately estimating genetic variance components is important for studying evolution in the wild. Empirical work on domesticated and wild outbred populations suggests that dominance genetic variance represents a substantial part of genetic variance, and theoretical work predicts that ignoring dominance can inflate estimates of additive genetic variance. Whether this issue is pervasive in natural systems is unknown, because we lack estimates of dominance variance in wild populations obtained in situ. Here, we estimate dominance and additive genetic variance, maternal variance, and other sources of nongenetic variance in eight traits measured in over 9000 wild nestlings linked through a genetically resolved pedigree. We find that dominance variance, when estimable, does not statistically differ from zero and represents a modest amount (2-36%) of genetic variance. Simulations show that (1) inferences of all variance components for an average trait are unbiased; (2) the power to detect dominance variance is low; (3) ignoring dominance can mildly inflate additive genetic variance and heritability estimates but such inflation becomes substantial when maternal effects are also ignored. These findings hence suggest that dominance is a small source of phenotypic variance in the wild and highlight the importance of proper model construction for accurately estimating evolutionary potential.     

A multiscale analysis of ecosystem services supply in the NW Iberian Peninsula from a functional perspective

In recent years, the assessment of ecosystem services (ES) supply has been based on the use of Land Use/Land Cover (LULC) data as proxies for spatial representation of ecosystems. Nevertheless, some shortcomings of this method, such as uncertainties derived from generalization of the ecosystem types and assumptions of invariance across spatial scales, indicate the need for new approaches. Such approaches could be aimed at improving knowledge of the relationships between ecosystem services and landscape structure and the spatial characteristics of ES patterns. In this study, we propose an integrative approach that involves the generation and analysis of continuous maps representing the supply of five ES potentially related to the amount of biomass. Five remote sensing images of the Northwestern Iberian Peninsula, obtained with Landsat-5 TM, were used to generate a proxy for net primary production by combining the normalized difference vegetation index (NDVI) of each image to calculate a ΣNDVI index that could act as a potential indicator of some ecosystem services. This information was combined with three variables – terrain slope, population density and occurrence of protected areas – to produce spatial models for the five ES and eventually a series of five supply maps. Food, materials and energy provision services showed a clustered pattern, with high supply values in flat zones and areas with high population densities. In contrast, mass flow and climate regulation services were more widely distributed throughout the study area. The five ecosystem service patterns were analyzed at different scales by two methods: lacunarity and four term local quadrat variance (4TLQV) analysis. These methods revealed differences in the spatial pattern: lacunarity analysis was useful for detection of scale thresholds at the local level, whereas 4TLQV was more sensitive to scale thresholds at larger spatial levels. Thus, the variance analysis yielded higher values for larger windows sizes, particularly for provisioning services. The results demonstrated the suitability of the proposed approach for the spatially explicit modeling of ecosystem services, avoiding the uncertainty of other assessments such as those based on LULC data, and for the exploratory analysis of ES supply from a spatial point of view.     

A Generalization of the GMANOVA-Model

It is shown that in some experimental designs the MANOVA- and the GMANOVA-model are too restrictive either to yield all hypothesis tests of interest or to reflect all known features of the design. An extension of these models is derived by relating the response vectors with the unknown model parameters by linear equations which may be completely different for each of the p components of the response vector and for each of the n independent vectors. For situations, in which a Wishart-distributed estimator for the underlying common covariance matrix is attainable, a test for any s-dimensional linear hypothesis on the model parameters is derived.     

The small-scale pattern of Cynodon dactylon in Mediterranean pastures

The abundance of Cynodon dactylon was recorded in 50 plots presenting different geomorphological conditions and along a transect of 16 500 2×2 cm contiguous quadrats within a small basin 330 m in length, in the granite pediment of the Sierra de Guadarrama (Central Spain). Soil analyses were undertaken on samples from the 50 plots and the soil information matrix obtained was analysed using Principal Components Analysis and Discriminant Analysis. Results showed that in the Mediterranean pastures Cynodon dactylon was restricted to deep, well developed soils with relatively high values of cations, conductivity and organic matter, and could be used as an indicator of such soil conditions in these grasslands. The spatial pattern of the species was analysed using New Local Variances which revealed the existence of a small-scale pattern, ranging from 8 to 18 cm, present at all levels of the analysis. The size of small-scale patterns was positively correlated with species abundance and was interpreted as a relation between plant vigour and favourable soil conditions.I would like to thank Professor González Bernáldez for his interest and encouragement.     

MV-mimicking micelles loaded with PEG-serine-ACP nanoparticles to achieve biomimetic intra/extra fibrillar mineralization of collagen in vitro

Since their discovery, matrix vesicles (MVs) containing minerals have received considerable attention for their role in the mineralization of bone, dentin and calcified cartilage. Additionally, MVs' association with collagen fibrils, which serve as the scaffold for calcification in the organic matrix, has been repeatedly highlighted. The primary purpose of the present study was to establish a MVs–mimicking model (PEG-S-ACP/micelle) in vitro for studying the exact mechanism of MVs-mediated extra/intra fibrillar mineralization of collagen in vivo. In this study, high-concentration serine was used to stabilize the amorphous calcium phosphate (S-ACP), which was subsequently mixed with polyethylene glycol (PEG) to form PEG-S-ACP nanoparticles. The nanoparticles were loaded in the polysorbate 80 micelle through a micelle self-assembly process in an aqueous environment. This MVs–mimicking model is referred to as the PEG-S-ACP/micelle model. By adjusting the pH and surface tension of the PEG-S-ACP/micelle, two forms of minerals (crystalline mineral nodules and ACP nanoparticles) were released to achieve the extrafibrillar and intrafibrillar mineralization, respectively. This in vitro mineralization process reproduced the mineral nodules mediating in vivo extrafibrillar mineralization and provided key insights into a possible mechanism of biomineralization by which in vivo intrafibrillar mineralization could be induced by ACP nanoparticles released from MVs. Also, the PEG-S-ACP/micelle model provides a promising methodology to prepare mineralized collagen scaffolds for repairing bone defects in bone tissue engineering.     

Taylor's law and body size in exploited marine ecosystems

Taylor's law (TL), which states that variance in population density is related to mean density via a power law, and density‐mass allometry, which states that mean density is related to body mass via a power law, are two of the most widely observed patterns in ecology. Combining these two laws predicts that the variance in density is related to body mass via a power law (variance‐mass allometry). Marine size spectra are known to exhibit density‐mass allometry, but variance‐mass allometry has not been investigated. We show that variance and body mass in unexploited size spectrum models are related by a power law, and that this leads to TL with an exponent slightly <2. These simulated relationships are disrupted less by balanced harvesting, in which fishing effort is spread across a wide range of body sizes, than by size‐at‐entry fishing, in which only fish above a certain size may legally be caught.     

Can We Accurately Characterize Wildlife Resource Use When Telemetry Data Are Imprecise?

ABSTRACT Telemetry data have been widely used to quantify wildlife habitat relationships despite the fact that these data are inherently imprecise. All telemetry data have positional error, and failure to account for that error can lead to incorrect predictions of wildlife resource use. Several techniques have been used to account for positional error in wildlife studies. These techniques have been described in the literature, but their ability to accurately characterize wildlife resource use has never been tested. We evaluated the performance of techniques commonly used for incorporating telemetry error into studies of wildlife resource use. Our evaluation was based on imprecise telemetry data (mean telemetry error = 174 m, SD = 130 m) typical of field-based studies. We tested 5 techniques in 10 virtual environments and in one real-world environment for categorical (i.e., habitat types) and continuous (i.e., distances or elevations) rasters. Technique accuracy varied by patch size for the categorical rasters, with higher accuracy as patch size increased. At the smallest patch size (1 ha), the technique that ignores error performed best on categorical data (0.31 and 0.30 accuracy for virtual and real data, respectively); however, as patch size increased the bivariate-weighted technique performed better (0.56 accuracy at patch sizes >31 ha) and achieved complete accuracy (i.e., 1.00 accuracy) at smaller patch sizes (472 ha and 1,522 ha for virtual and real data, respectively) than any other technique. We quantified the accuracy of the continuous covariates using the mean absolute difference (MAD) in covariate value between true and estimated locations. We found that average MAD varied between 104 m (ignore telemetry error) and 140 m (rescale the covariate data) for our continuous covariate surfaces across virtual and real data sets. Techniques that rescale continuous covariate data or use a zonal mean on values within a telemetry error polygon were significantly less accurate than other techniques. Although the technique that ignored telemetry error performed best on categorical rasters with smaller average patch sizes (i.e., ≤31 ha) and on continuous rasters in our study, accuracy was so low that the utility of using point-based approaches for quantifying resource use is questionable when telemetry data are imprecise, particularly for small-patch habitat relationships.