TY - GEN A1 - Pekár, Stano A1 - Wolff, Jonas O. A1 - Černecká, Ľudmila A1 - Birkhofer, Klaus A1 - Mammola, Stefano A1 - Lowe, Elizabeth C. A1 - Fukushima, Caroline S. A1 - Herberstein, Marie E. A1 - Kučera, Adam A1 - Buzatto, Bruno A. T1 - The World Spider Trait database: a centralized global open repository for curated data on spider traits T2 - Database N2 - Spiders are a highly diversified group of arthropods and play an important role in terrestrial ecosystems as ubiquitous predators, which makes them a suitable group to test a variety of eco-evolutionary hypotheses. For this purpose, knowledge of a diverse range of species traits is required. Until now, data on spider traits have been scattered across thousands of publications produced for over two centuries and written in diverse languages. To facilitate access to such data, we developed an online database for archiving and accessing spider traits at a global scale. The database has been designed to accommodate a great variety of traits (e.g. ecological, behavioural and morphological) measured at individual, species or higher taxonomic levels. Records are accompanied by extensive metadata (e.g. location and method). The database is curated by an expert team, regularly updated and open to any user. A future goal of the growing database is to include all published and unpublished data on spider traits provided by experts worldwide and to facilitate broad cross-taxon assays in functional ecology and comparative biology. Y1 - 2021 UR - https://spidertraits.sci.muni.cz/ U6 - https://doi.org/10.1093/database/baab064 SN - 1758-0463 IS - 2021 ER - TY - GEN A1 - Riva, Federico A1 - Graco-Roza, Caio A1 - Daskalova, Gergana N. A1 - Hudgins, Emma J. A1 - Lewthwaite, Jayme M. M. A1 - Newman, Erica A. A1 - Ryo, Masahiro A1 - Mammola, Stefano T1 - Toward a cohesive understanding of ecological complexity T2 - Science Advances N2 - Ecological systems are quintessentially complex systems. Understanding and being able to predict phenomena typical of complex systems is, therefore, critical to progress in ecology and conservation amidst escalating global environmental change. However, myriad definitions of complexity and excessive reliance on conventional scientific approaches hamper conceptual advances and synthesis. Ecological complexity may be better understood by following the solid theoretical basis of complex system science (CSS). We review features of ecological systems described within CSS and conduct bibliometric and text mining analyses to characterize articles that refer to ecological complexity. Our analyses demonstrate that the study of complexity in ecology is a highly heterogeneous, global endeavor that is only weakly related to CSS. Current research trends are typically organized around basic theory, scaling, and macroecology. We leverage our review and the generalities identified in our analyses to suggest a more coherent and cohesive way forward in the study of complexity in ecology. Y1 - 2023 U6 - https://doi.org/10.1126/sciadv.abq4207 SN - 2375-2548 VL - 9 IS - 25 PB - American Association for the Advancement of Science (AAAS) ER -