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Under the current global biodiversity crisis, there is a need for automated and noninvasive monitoring techniques that can gather large amounts of data cost‐effectively at various ecological scales, from local to large spatial scales. These data can then be analyzed to inform stakeholders and decision‐makers. One such technique is passive acoustic monitoring, which is commonly coupled with automatic identification of animal sp...
LandFrag : A Dataset to Investigate the Effects of Forest Loss and Fragmentation on BiodiversityNARA Subscribed
Motivation The accelerated and widespread conversion of once continuous ecosystems into fragmented landscapes has driven ecological research to understand the response of biodiversity to local (fragment size) and landscape (forest cover and fragmentation) changes. This information has important theoretical and applied implications, but is still far from complete. We compiled the most comprehensive and updated database to inves...
Aim Understanding how climate conditions influence plant–pollinator interactions at the global scale is crucial to understand how pollinator communities and ecosystem function respond to environmental change. Here, we investigate whether climate drives differences in network roles of the main insect pollinator orders: Diptera, Coleoptera, Lepidoptera and Hymenoptera. Location Global. Time period 1968–2020. Major taxa studied D...
In every liter of seawater there are between 10 and 100 billion life forms, mostly invisible, called marine plankton or marine microbiome, which form the largest and most dynamic ecosystem on our planet, at the heart of global ecological and economic processes. While physical and chemical parameters of planktonic ecosystems are fairly well measured and modeled at the planetary scale, biological data are still scarce due to the...
Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severityNARA Subscribed
The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the pr...
Plants are sessile organisms and, consequently, are exposed to a plethora of stresses in their local habitat. As a result, different populations of a species are subject to different selection pressures leading to adaptation to local conditions and intraspecific divergence. The annual brassicaceous plant Arabidopsis thaliana is an attractive model for ecologists and evolutionary biologists due to the availability of a large co...
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