The rampant loss of biodiversity is starting to be recognized as a global crisis rivaling the climate emergency. To address this crisis, scientists need robust methods to measure the diversity in a system. Importantly, these methods should not only count species but capture the variety of different functions that the species in a system can perform. In this paper, we propose a machine learning method by which existing data from ecosystem monitoring can be reanalyzed to reveal changes of functional biodiversity over time.
Migratory orientation of many animals is inheritable, enabling inexperienced (naïve) individuals to migrate independently using a geomagnetic or celestial compass. It remains unresolved how naïve migrants reliably reach remote destinations, sometimes …
Bacteria, in contrast to eukaryotic cells contain two types of genes: chromosomal genes that are fixed to the cell, and plasmids that are mobile genes, easily shared to other cells. The sharing of plasmid genes between individual bacteria and between …
Mechanisms terminating phytoplankton blooms are often not well understood. Potentially involved processes such as consumption by grazers, flocculation, and viral lysis each have different post-bloom consequences on the processing of the organic …
Clinicians prescribing antibiotics in a hospital context follow one of several possible 'treatment protocols' - heuristic rules designed to balance the immediate needs of patients against the long term threat posed by the evolution of antibiotic …
A distinguishing feature of many ecological networks in the microbial realm is the diversity of substrates that could potentially serve as energy sources for microbial consumers. The microorganisms are themselves the agents of compound …
The dynamics of trait-based metacommunities have attracted much attention, but not much is known about how dispersal and spatial environmental variability mutually interact with each other to drive coexistence patterns and diversity. Here, we present …