We are a group of researchers who use an integrative approach to answer ecological questions. Our method spans from taxonomy and biodiversity recognition to understanding the functional and behavioural responses of organisms to their environment. In our studies, we utilize invertebrates as model organisms, addressing various issues through laboratory experiments and field observations. Our research frequently incorporates physiological and molecular techniques to improve our understanding of the intricate relationship between organisms and their surroundings.
Group photo in the making...
Research
Our current projects involve the study of addictive and self-medicative behaviour in the honeybee, patterns of tardigrade diversity and distribution as well as the structure and dynamics of their metacommunities, altruistic and cooperative behaviour in ants, and cognitive behaviour in trap-building insects such as antlions and wormlions.
Latest works
Integrative taxonomy supports two new species of Macrobiotus (Tardigrada: Eutardigrada: Macrobiotidae) allowing further discussion on the genus phylogeny
Small workers are more persistent when providing and requiring help in a monomorphic ant.
Scientific Reports
Injury shortens life expectancy in ants and affects some risk-related decisions of workers.
Behavioral differences between pit-building antlions and wormlions suggest limits to convergent evolution.
The tardigrade Mesobiotus aradasi (Binda, Pilato & Lisi, 2005) is widely distributed along the Antarctic Peninsula
Ecology explains anhydrobiotic performance across tardigrades, but the shared evolutionary history matters more.
Negative impact of freeze–thaw cycles on the survival of tardigrades.
Along the river: Longitudinal patterns of functional and taxonomic diversity of plants in riparian forests
Journal of Vegetation Science
Morphology, phylogenetic position, and mating behaviour of a new Mesobiotus (Tardigrada) species from a rock pool in the Socorro Box Canyon (New Mexico, USA).
Spatial patterns of flower color variation in native and introduced ranges of Convolvulus arvensis (Convolvulaceae) revealed by citizen science data and machine learning.