Tree level indicators of species composition of saproxylic beetles in old-growth mountainous spruce–beech forest through variation partitioning

Forest reserves can serve as an opportunity for studying natural processes in the wild. We studied the effect of easy-to-see tree level indicators on saproxylic beetles (Coleoptera), using window traps. Our study was conducted in old-growth mountainous spruce–beech forest Bukacka in the Orlicke Mts. (Czech Republic). Our analyses showed that the species composition of the study group and its response to tree level indicators in the relatively homogenous environment of old-growth mountainous forest area could be explained reasonably well through variance partitioning. The results indicated that the decay stage was the category hosting the highest level of explained variance with respect to saproxylics, followed by diameter and tree. Red-listed beetle species were nearly the same associated with conifers and broadleaves. Our results highlighted the desirability of using tree level indicators to assess insect diversity, using window traps on tree trunk.     

Cytotoxicity and Antioxidative Effects of Herbal and Fruit Extracts In Vitro

Many studies have been carried out on bioactivities of individual herbs/fruits using in cosmetics or as a diet products, however, no collective study on their comparative antioxidant activities against oxidative damage or on cytotoxicity effect has been reported. The aim of this work was study the cytotoxicity and antioxidative activity of eight extracts with hypothetical antioxidative influence in vitro. To further elucidate of a possible role of herbals/fruits extracts on cell protection was used on the healthy and UV-A damaged mouse fibroblast cells. The cell viability was detect using MTT assay. Kinetic production of reactive oxygen species, identification of cell death, cell cycle and gene expression C-FOS were measured. Intracellular and mitochondrial transmembrane potential was evaluate with JC-1 fluorescence probe. Comet assay was employed to detect the UV-A induced DNA damage. The results indicated that using the extracts decreased ROS production. It can lead to greatly enhance and promote the viability of cells. As the most effective antioxidant in quenching of the ROS, in cell viability and DNA presentation was determined Prunella Vulgaris. However, one of them (Wheat Germ Oil) caused increased production of ROS and low cell viability.     

Does spatial co-occurrence of carnivores in a Central European agricultural landscape follow the null model?

Spatiotemporal heterogeneity in the distribution of resources, interspecific competition and predation are important factors determining the spatial distribution and co-occurrence of many animal taxa. Here, we use data from scent station field studies and permutation-based null model analyses to test whether spatial co-occurrence of different carnivores’ species is non-random in a Central European landscape that has been strongly modified and fragmented through human activity. In general, our results suggest a higher degree of spatial co-occurrence of different carnivore species than expected by chance; though it should be noted that this difference was not detectable under the conservative form of the null model. On the other hand, our data do not provide evidence for a significant degree of spatial segregation at the interspecific level. In conclusion, our results imply that antagonistic interactions, such as interspecific competition and predation, are not the dominant factors shaping spatial distribution of carnivores. Consequently, we suggest that the high degree of spatial co-occurrence might be a consequence of spatial heterogeneity in distribution of resources that are shared at the interspecific level.     

A weighted partial likelihood approach for zero‐truncated models

Zero‐truncated data arises in various disciplines where counts are observed but the zero count category cannot be observed during sampling. Maximum likelihood estimation can be used to model these data; however, due to its nonstandard form it cannot be easily implemented using well‐known software packages, and additional programming is often required. Motivated by the Rao–Blackwell theorem, we develop a weighted partial likelihood approach to estimate model parameters for zero‐truncated binomial and Poisson data. The resulting estimating function is equivalent to a weighted score function for standard count data models, and allows for applying readily available software. We evaluate the efficiency for this new approach and show that it performs almost as well as maximum likelihood estimation. The weighted partial likelihood approach is then extended to regression modelling and variable selection. We examine the performance of the proposed methods through simulation and present two case studies using real data.     

Estimating negative binomial parameters from occurrence data with detection times

The negative binomial distribution is a common model for the analysis of count data in biology and ecology. In many applications, we may not observe the complete frequency count in a quadrat but only that a species occurred in the quadrat. If only occurrence data are available then the two parameters of the negative binomial distribution, the aggregation index and the mean, are not identifiable. This can be overcome by data augmentation or through modeling the dependence between quadrat occupancies. Here, we propose to record the (first) detection time while collecting occurrence data in a quadrat. We show that under what we call proportionate sampling, where the time to survey a region is proportional to the area of the region, that both negative binomial parameters are estimable. When the mean parameter is larger than two, our proposed approach is more efficient than the data augmentation method developed by Solow and Smith ( 2010 , Am. Nat. 176 , 96–98), and in general is cheaper to conduct. We also investigate the effect of misidentification when collecting negative binomially distributed data, and conclude that, in general, the effect can be simply adjusted for provided that the mean and variance of misidentification probabilities are known. The results are demonstrated in a simulation study and illustrated in several real examples.     

What we can and what we cannot see with extracellular multielectrodes

Extracellular recording is an accessible technique used in animals and humans to study the brain physiology and pathology. As the number of recording channels and their density grows it is natural to ask how much improvement the additional channels bring in and how we can optimally use the new capabilities for monitoring the brain. Here we show that for any given distribution of electrodes we can establish exactly what information about current sources in the brain can be recovered and what information is strictly unobservable. We demonstrate this in the general setting of previously proposed kernel Current Source Density method and illustrate it with simplified examples as well as using evoked potentials from the barrel cortex obtained with a Neuropixels probe and with compatible model data. We show that with conceptual separation of the estimation space from experimental setup one can recover sources not accessible to standard methods.