Agri-environment schemes are an increasingly important tool for the maintenance and restoration of farmland biodiversity in Europe but their ecological effects are poorly known. Scheme design is partly based on non-ecological considerations and poses important restrictions on evaluation studies. We describe a robust approach to evaluate agri-environment schemes and use it to evaluate the biodiversity effects of agri-environment schemes in five European countries. We compared species density of vascular plants, birds, bees, grasshoppers and crickets, and spiders on 202 paired fields, one with an agri-environment scheme, the other conventionally managed. In all countries, agri-environment schemes had marginal to moderately positive effects on biodiversity. However, uncommon species benefited in only two of five countries and species listed in Red Data Books rarely benefited from agri-environment schemes. Scheme objectives may need to differentiate between biodiversity of common species that can be enhanced with relatively simple modifications in farming practices and diversity or abundance of endangered species which require more elaborate conservation measures.

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An approach to derive relationships for defining land degradation and desertification risk and developing appropriate tools for assessing the effectiveness of the various land management practices using indicators is presented in the present paper. In order to investigate which indicators are most effective in assessing the level of desertification risk, a total of 70 candidate indicators was selected providing information for the biophysical environment, socio-economic conditions, and land management characteristics. The indicators were defined in 1,672 field sites located in 17 study areas in the Mediterranean region, Eastern Europe, Latin America, Africa, and Asia. Based on an existing geo-referenced database, classes were designated for each indicator and a sensitivity score to desertification was assigned to each class based on existing research. The obtained data were analyzed for the various processes of land degradation at farm level. The derived methodology was assessed using independent indicators, such as the measured soil erosion rate, and the organic matter content of the soil. Based on regression analyses, the collected indicator set can be reduced to a number of effective indicators ranging from 8 to 17 in the various processes of land degradation. Among the most important indicators identified as affecting land degradation and desertification risk were rain seasonality, slope gradient, plant cover, rate of land abandonment, land-use intensity, and the level of policy implementation.

Spliceosomal (pre-mRNA) introns have previously been found in eukaryotic protein-coding genes, in the small nuclear RNAs of some fungi, and in the small- and large-subunit ribosomal DNA genes of a limited number of ascomycetes. How the majority of these introns originate remains an open question because few proven cases of recent and pervasive intron origin have been documented. We report here the widespread occurrence of spliceosomal introns (69 introns at 27 different sites) in the small- and large-subunit nuclear-encoded rDNA of lichen-forming and free-living members of the Ascomycota. Our analyses suggest that these spliceosomal introns are of relatively recent origin, i.e., within the Euascomycetes, and have arisen through aberrant reverse-splicing (in trans) of free pre-mRNA introns into rRNAs. The spliceosome itself, and not an external agent (e.g., transposable elements, group II introns), may have given rise to these introns. A nonrandom sequence pattern was found at sites flanking the rRNA spliceosomal introns. This pattern (AG-intron-G) closely resembles the proto-splice site (MAG-intron-R) postulated for intron insertions in pre-mRNA genes. The clustered positions of spliceosomal introns on secondary structures suggest that particular rRNA regions are preferred sites for insertion through reverse-splicing.

Memory is among the most important and neglected forces that shapes animal movement patterns. Research on the movement-memory interface is crucial to understand how animals use spatial learning to navigate across space because memory-based navigation is directly linked to animals' space use and home range behaviour; however, because memory cannot be measured directly, it is difficult to account for. Here, we incorporated spatial memory into step selection functions (SSF) to understand how resource selection and spatial memory affect space use of feral hogs (Sus scrofa). We used Biased Random Bridge kernel estimates linked to residence time as a surrogate for memory and tested four conceptually different dynamic maps of spatial memory. We applied this memory-based SSF to a data set of hog relocations to evaluate the importance of land cover type, time of day and spatial memory on the animals' space use. Our approach has shown how the incorporation of spatial memory into animal movement models can improve estimates of habitat selection. Memory-based SSF provided a feasible way to gain insight into how animals use spatial learning to guide their movement decisions. We found that while hogs selected forested areas and water bodies and avoided grasslands during the day (primarily at noon), they had a strong tendency to select previously visited areas, mainly those held in recent memory. Beyond actively updating their memory with recent experiences, hogs were able to discriminate among spatial memories encoded at different circadian phases of their activity. Even though hogs are thought to have long memory retention, they likely relied on recent experiences because the local food resources are quickly depleted and slowly renewed, yielding an uncertain spatial distribution of resources.