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Biodiversity

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Abundance and Species Diversity of Fungi in Rivers with Various Contaminations.

Current microbiology
The main objective of this work was to determine the abundance and species diversity of fungi in the waters of selected rivers of Central Europe, NE Poland (Augustów Lakeland), differing in size, physical and chemical properties, and streamflow rate....

Species composition of and fumonisin production by the Fusarium fujikuroi species complex isolated from Korean cereals.

International journal of food microbiology
To assess the risk of fumonisin contamination in Korean cereals, we isolated colonies of the Fusarium fujikuroi species complex (FFSC) from barley, maize, rice and soybean samples from 2011 to 2015. A total of 878 FFSC strains were isolated mostly fr...

Modeling of Beta Diversity in Tunisian Waters: Predictions Using Generalized Dissimilarity Modeling and Bioregionalisation Using Fuzzy Clustering.

PloS one
Spatial patterns of beta diversity are a major focus of ecology. They can be especially valuable in conservation planning. In this study, we used a generalized dissimilarity modeling approach to analyze and predict the spatial patterns of beta divers...

Inferring landscape-scale land-use impacts on rivers using data from mesocosm experiments and artificial neural networks.

PloS one
Identifying land-use drivers of changes in river condition is complicated by spatial scale, geomorphological context, land management, and correlations among responding variables such as nutrients and sediments. Furthermore, variations in standard me...

ENVIRONMENTS and EOL: identification of Environment Ontology terms in text and the annotation of the Encyclopedia of Life.

Bioinformatics (Oxford, England)
UNLABELLED: The association of organisms to their environments is a key issue in exploring biodiversity patterns. This knowledge has traditionally been scattered, but textual descriptions of taxa and their habitats are now being consolidated in centr...

BioEncoder: A metric learning toolkit for comparative organismal biology.

Ecology letters
In the realm of biological image analysis, deep learning (DL) has become a core toolkit, for example for segmentation and classification. However, conventional DL methods are challenged by large biodiversity datasets characterized by unbalanced class...

Spatio-temporal changes of small protist and free-living bacterial communities in a temperate dimictic lake: insights from metabarcoding and machine learning.

FEMS microbiology ecology
Microbial communities, which include prokaryotes and protists, play an important role in aquatic ecosystems and influence ecological processes. To understand these communities, metabarcoding provides a powerful tool to assess their taxonomic composit...

How widespread use of generative AI for images and video can affect the environment and the science of ecology.

Ecology letters
Generative artificial intelligence (AI) models will have broad impacts on society including the scientific enterprise; ecology and environmental science will be no exception. Here, we discuss the potential opportunities and risks of advanced generati...

Deep learning to extract the meteorological by-catch of wildlife cameras.

Global change biology
Microclimate-proximal climatic variation at scales of metres and minutes-can exacerbate or mitigate the impacts of climate change on biodiversity. However, most microclimate studies are temperature centric, and do not consider meteorological factors ...