Plant interaction networks reveal the limits of our understanding of diversity maintenance

Abstract

Species interactions are key drivers of biodiversity and ecosystem stability. Current theoretical frameworks for understanding the role of interactions make many assumptions which unfortunately, do not always hold in natural, diverse communities. This mismatch extends to annual plants, a common model system for studying coexistence, where interactions are typically averaged across environmental conditions and transitive competitive hierarchies are assumed to dominate. We quantify interaction networks for a community of annual wildflowers in Western Australia across a natural shade gradient at local scales. Whilst competition dominated, intraspecific and interspecific facilitation were widespread in all shade categories. Interaction strengths and directions varied substantially despite close spatial proximity and similar levels of local species richness, with most species interacting in different ways under different environmental conditions. Contrary to expectations, all networks were predominantly intransitive. These findings encourage us to rethink how we conceive of and categorize the mechanisms driving biodiversity in plant systems.

A Qualitative Study on the Consumer Behaviour Related to Food Waste: Romanian Perspectives through Word Cloud and Sentiment Analysis

“…Term co-occurrence measurement and natural language processing (NLP) were performed using the Tidytext and Quanteda packages in R [41,42]. Codes in the text were categorised into relevant themes or topics, and the relationships between them were analysed and visualised using the IGRAPH library in R [43]. These steps led to insights and interpretation of textual data, facilitating informed decision-making, and identifying trends and patterns in the analysed data.…”