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  • 1
    Publication Date: 2018-03-08
    Description: This contribution proposes a cautious way of constructing the susceptibility classes obtained from favourability modeling of landslide occurrences. It is based on the ranks of the numerical values obtained by the modelling. Such ranks can be displayed in the form of histograms, cumulative curves, and prediction patterns resembling maps. A number of models have been proposed and in this contribution the following will be compared in terms of their respective rankings for equal area classes: fuzzy set function, empirical likelihood ratio, linear and logistic regression, and Bayesian prediction function. The analyses performed and contrasted exemplify a generalized methodology for comparing predictions that should allow evaluating prediction patterns from any model. Unfortunately, many applications in the scientific literature use methods of characterizing prediction quality that make comparison hard or impossible. A database from a study area in the Mountain Community of Tirano in Valtellina, Lombardy Region, northern Italy, is used to illustrate how the results of the different models and strategies of analysis show the relevance of the properties of the database over those of the models.
    Description: Published
    Description: 1135-1144
    Description: 2TR. Ricostruzione e modellazione della struttura crostale
    Keywords: Landslide susceptibility, spatial support, spatial relationships, prediction models, prediction patterns, target pattern, ranked classes, cross-validation, database signature ; 04.04. Geology
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: book chapter
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  • 2
    Publication Date: 2022-05-26
    Description: © The Author(s), 2018. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Aquatic Sciences 80 (2018): 44, doi:10.1007/s00027-018-0594-z.
    Description: Complex natural systems are affected by multiple anthropogenic stressors, and therefore indirect effects within food webs are increasingly investigated. In this context, dead organic matter (OM) or detritus provides a food source sustaining detrital food webs that recycle the retained energy through microbial decomposition and invertebrate consumption. In aquatic environments, poorly water-soluble contaminants, including nanoparticles (NPs), quickly adsorb onto OM potentially modifying OM-associated microbial communities. Since invertebrates often depend on microbial conditioning to enhance OM quality, adverse effects on OM-associated microbial communities could potentially affect invertebrate performances. Therefore, this study assessed the effect of environmentally relevant concentrations of the model emerging contaminant, silver nanoparticles (AgNPs), on OM-associated microorganisms and subsequent indirect effects on growth of the invertebrate Asellus aquaticus. At low concentrations (0.8 ug/L), AgNPs inhibited activity and altered metabolic diversity of the OM-associated microbial community. This was observed to coincide with a negative effect on the growth of A. aquaticus due to antimicrobial properties, as a decreased growth was observed when offered AgNP-contaminated OM. When A. aquaticus were offered sterile OM in the absence of AgNPs, invertebrate growth was observed to be strongly retarded, illustrating the importance of microorganisms in the diet of this aquatic invertebrate. This outcome thus hints that environmentally relevant concentrations of AgNPs can indirectly affect the growth of aquatic invertebrates by affecting OM-associated microbial communities, and hence that microorganisms are an essential link in understanding bottom-up directed effects of chemical stressors in food webs.
    Description: The Chinese Scholarship Council (CSC) is gratefully acknowledged for its financial support to Yujia Zhai [201506510003]. Martina G. Vijver is funded by NWO-VIDI [project number 864.13.010].
    Keywords: Asellus aquaticus ; Food web ; Freshwater biofilms ; Decomposition and consumption ; Silver nanoparticles ; Ecosystem functioning
    Repository Name: Woods Hole Open Access Server
    Type: Article
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