Testing for Validity and Reliability in Cross-Cultural Research

A set of procedures is offered for assessing interraler reliability and certain aspects of validity of codes in cross-cultural studies. The method assumes that at least two independent raters have coded more than one trait. Each trait coded by one rater is correlated with each trait coded by a second, and all the codings by a single rater are intercorrelated with each other. The results are presented in a multitrait-multi-rater matrix. From this matrix it is possible to determine the interrater reliability and discriminant validity of trails in addition to a higher order concept based on pairs of traits.     

A novel approach for assessing factors affecting biodiversity based on networks analysis

We propose in this work a novel approach aiming at assessing cause and effect relationships between variables that can affect target biodiversity issues. These cause–effect relations are used to build a network whose nodes represent variables linked by directed arcs. The arcs have associated a value that represents trends of cause–effect relations. An important novelty of this approach is the use of product and addition operations between trends of cause–effect relations for assessing factors that can affect target variables. For the analysis of the network we use the concept of paths. Paths are defined as sequences of cause–effect relations from source variables to target variables. For example, the path from population increment that causes effects on the increment of transport routes, which in turn causes effects on the loss of vegetation cover. This approach was applied to the assessment of vegetation cover in the Morelos State, México during the period 2000–2010. The results show a promising practical alternative to assess the potential effects on biodiversity issues based on the analysis of the paths represented in the network.     

Forest floor photosynthesis and respiration in a drained peatland forest in southern Finland

Background: Although forest floor forms a large biomass pool in forested peatlands, little is known about its role in ecosystem carbon (C) dynamics.

Aim: We aimed to quantify forest floor photosynthesis (P _FF) and respiration (R _FF) as a part of overall C dynamics in a drained peatland forest in southern Finland.

Methods: We measured net forest floor CO₂ exchange with closed chambers and reconstructed seasonal CO₂ exchange in the prevailing plant communities.

Results: The vegetation was a mosaic of plant communities that differed in CO₂ exchange dynamics. The reconstructed growing season P _FF was highest in the Sphagnum community and lowest in the feather moss communities. On the contrary, R _FF was highest in the feather moss communities and lowest in the Sphagnum community. CO₂ assimilated by the forest floor was 20–30% of the total CO₂ assimilated by the forest. The forest floor was a net CO₂ source to the atmosphere, because respiration from ground vegetation, tree roots and decomposition of soil organic matter exceeded the photosynthesis of ground vegetation.

Conclusions: Tree stand dominates C fluxes in drained peatland forests. However, forest floor vegetation can have a noticeable role in the C cycle of peatlands drained for forestry. Similarly to natural mires, Sphagnum moss-dominated communities were the most efficient assimilators of C.     

Adaptive Neural Network-Based ECG Data Compression According to the Morphology

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Flight loss linked to faster molecular evolution in insects

The loss of flight ability has occurred thousands of times independently during insect evolution. Flight loss may be linked to higher molecular evolutionary rates because of reductions in effective population sizes (N_e) and relaxed selective constraints. Reduced dispersal ability increases population subdivision, may decrease geographical range size and increases (sub)population extinction risk, thus leading to an expected reduction in N_e. Additionally, flight loss in birds has been linked to higher molecular rates of energy-related genes, probably owing to relaxed selective constraints on energy metabolism. We tested for an association between insect flight loss and molecular rates through comparative analysis in 49 phylogenetically independent transitions spanning multiple taxa, including moths, flies, beetles, mayflies, stick insects, stoneflies, scorpionflies and caddisflies, using available nuclear and mitochondrial protein-coding DNA sequences. We estimated the rate of molecular evolution of flightless (FL) and related flight-capable lineages by ratios of non-synonymous-to-synonymous substitutions (dN/dS) and overall substitution rates (OSRs). Across multiple instances of flight loss, we show a significant pattern of higher dN/dS ratios and OSRs in FL lineages in mitochondrial but not nuclear genes. These patterns may be explained by relaxed selective constraints in FL ectotherms relating to energy metabolism, possibly in combination with reduced N_e.     

Constructing more informative plant–pollinator networks: visitation and pollen deposition networks in a heathland plant community

Interaction networks are widely used as tools to understand plant–pollinator communities, and to examine potential threats to plant diversity and food security if the ecosystem service provided by pollinating animals declines. However, most networks to date are based on recording visits to flowers, rather than recording clearly defined effective pollination events. Here we provide the first networks that explicitly incorporate measures of pollinator effectiveness (PE) from pollen deposition on stigmas per visit, and pollinator importance (PI) as the product of PE and visit frequency. These more informative networks, here produced for a low diversity heathland habitat, reveal that plant–pollinator interactions are more specialized than shown in most previous studies. At the studied site, the specialization index was lower for the visitation network than the PE network, which was in turn lower than for the PI network. Our study shows that collecting PE data is feasible for community-level studies in low diversity communities and that including information about PE can change the structure of interaction networks. This could have important consequences for our understanding of threats to pollination systems.     

A random fatigue of mechanize titanium abutment studied with Markoff chain and stochastic finite element formulation

To measure fatigue in dental implants and in its components, it is necessary to use a probabilistic analysis since the randomness in the output depends on a number of parameters (such as fatigue properties of titanium and applied loads, unknown beforehand as they depend on mastication habits). The purpose is to apply a probabilistic approximation in order to predict fatigue life, taking into account the randomness of variables. More accuracy on the results has been obtained by taking into account different load blocks with different amplitudes, as happens with bite forces during the day and allowing us to know how effects have different type of bruxism on the piece analysed.     

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.