Abstract Machine learning (ML) and deep learning (DL) possess excellent advantages in
data analysis (eg, feature extraction, clustering, classification, regression, image recognition …

Species richness and evenness have been widely used to investigate the spatiotemporal
variation of α-diversity. However, some studies have indicated that a negative relationship …

The ecological role of microorganisms is of utmost importance due to their multiple
interactions with the environment. However, assessing the contribution of individual …

The use of Earth Observation (EO) for water quality monitoring has substantially raised in the
recent decade; however, harmonisation of EO-based indicators across the seas to support …

The rapid and continuous loss of biodiversity highlights the urgent need for research on
functional diversity. Although the study of functional diversity has exploded in the past two …

Trait-based ecology has recently gained increasing importance in phytoplankton research.
In particular, the taxonomic and morphological traits, such as size and shape of …

Long-term monitoring data is central for the analysis of biodiversity change and its drivers.
Time series allow a more accurate evaluation of diversity indices, trait identification and …

Fungi, serving as real-time bioindicators to environmental changes and stressors, are crucial
for effective forest conservation and management practices under ongoing global change …

The movement of pedestrian crowds is studied both for real-world applications and to gain
fundamental scientific insights into systems of self-driven particles. Trajectory data describes …

Compositional measurements from species assemblages define a high dimensional
dataspace in which the data can form complex structures, termed manifolds. Comparing …