Direct and indirect effects of landscape and field management intensity on carabids through trophic resources and weeds.

Author(s):  
Benjamin Carbonne ◽  
David A. Bohan ◽  
Hana Foffová ◽  
Eirini Daouti ◽  
Britta Frei ◽  
...  
2021 ◽  
Vol 9 (2) ◽  
pp. 463
Author(s):  
Steffen Boch ◽  
Hugo Saiz ◽  
Eric Allan ◽  
Peter Schall ◽  
Daniel Prati ◽  
...  

Using 642 forest plots from three regions in Germany, we analyzed the direct and indirect effects of forest management intensity and of environmental variables on lichen functional diversity (FDis). Environmental stand variables were affected by management intensity and acted as an environmental filter: summing direct and indirect effects resulted in a negative total effect of conifer cover on FDis, and a positive total effect of deadwood cover and standing tree biomass. Management intensity had a direct positive effect on FDis, which was compensated by an indirect negative effect via reduced standing tree biomass and lichen species richness, resulting in a negative total effect on FDis and the FDis of adaptation-related traits (FDisAd). This indicates environmental filtering of management and stronger niche partitioning at a lower intensity. In contrast, management intensity had a positive total effect on the FDis of reproduction-, dispersal- and establishment-related traits (FDisRe), mainly because of the direct negative effect of species richness, indicating functional over-redundancy, i.e., most species cluster into a few over-represented functional entities. Our findings have important implications for forest management: high lichen functional diversity can be conserved by promoting old, site-typical deciduous forests with a high richness of woody species and large deadwood quantity.


2005 ◽  
Author(s):  
Dana M. Binder ◽  
Martin J. Bourgeois ◽  
Christine M. Shea Adams

2020 ◽  
Vol 35 (1) ◽  
Author(s):  
Willem Gravett

The development of artificial intelligence has the potential to transform lives and work practices, raise efficiency, savings and safety levels, and provide enhanced levels of services. However, the current trend towards developing smart and autonomous machines with the capacity to be trained and make decisions independently holds not only economic advantages, but also a variety of concerns regarding their direct and indirect effects on society as a whole. This article examines some of these concerns, specifically in the areas of privacy and autonomy, state surveillance, and bias and algorithmic transparency. It concludes with an analysis of the challenges that the legal system faces in regulating the burgeoning field of artificial intelligence.


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