Do the rich get richer? Varying effects of tree species identity and diversity on the richness of understory taxa.

Understory herbs and soil invertebrates play key roles in soil formation and nutrient cycling in forests. Studies suggest that diversity in the canopy and in the understory are positively associated, but these studies often confound the effects of tree species diversity with those of tree species identity and abiotic conditions. We combined extensive field sampling with structural equation modeling to evaluate the simultaneous effects of tree diversity on the species diversity of understory herbs, beetles, and earthworms. The diversity of earthworms and saproxylic beetles was directly and positively associated with tree diversity, presumably because species of both these taxa specialize on certain species of trees. Tree identity also strongly affected diversity in the understory, especially for herbs, likely as a result of interspecific differences in canopy light transmittance or litter decomposition rates. Our results suggest that changes in forest management will disproportionately affect certain understory taxa. For instance, changes in canopy diversity will affect the diversity of earthworms and saproxylic beetles more than changes in tree species composition, whereas the converse would be expected for understory herbs and detritivorous beetles. We conclude that the effects of tree diversity on understory taxa can vary from positive to negative and may affect biogeochemical cycling in temperate forests. Thus, maintaining high diversity in temperate forests can promote the diversity of multiple taxa in the understory.

PIZZARO: Forensic analysis and restoration of image and video data.

This paper introduces a set of methods for image and video forensic analysis. They were designed to help to assess image and video credibility and origin and to restore and increase image quality by diminishing unwanted blur, noise, and other possible artifacts. The motivation came from the best practices used in the criminal investigation utilizing images and/or videos. The determination of the image source, the verification of the image content, and image restoration were identified as the most important issues of which automation can facilitate criminalists work. Novel theoretical results complemented with existing approaches (LCD re-capture detection and denoising) were implemented in the PIZZARO software tool, which consists of the image processing functionality as well as of reporting and archiving functions to ensure the repeatability of image analysis procedures and thus fulfills formal aspects of the image/video analysis work. Comparison of new proposed methods with the state of the art approaches is shown. Real use cases are presented, which illustrate the functionality of the developed methods and demonstrate their applicability in different situations. The use cases as well as the method design were solved in tight cooperation of scientists from the Institute of Criminalistics, National Drug Headquarters of the Criminal Police and Investigation Service of the Police of the Czech Republic, and image processing experts from the Czech Academy of Sciences.