Biology subjects

Broadbent, H.

Publications and source records attributed to Broadbent, H..

2 recordsLinked to original sources

bioRxiv2025

Food-web coupling by mobile consumers has individual to ecosystem level effects

Mobile consumers serve as a ubiquitous link, coupling the dynamics and functions of different ecosystems, ranging from diel-vertical migration of zooplankton to seasonal movements of large ungulates. Despite mounting theoretical interest, experimental tests of the effects of consumer mobility in meta-ecosystems are virtually non-existent. Here, we used an experimental microcosm system to investigate how mobile consumers (Daphnia magna) mediate ecosystem biomass, community structure, and their own fitness by coupling spatially distinct aquatic ecosystems composed of two different protist communities. We found that consumer mobility significantly influenced the effect of consumption on ecosystem biomass and the growth and reproduction of the consumers, themselves. However, the direction and magnitude of these effects depended on community composition in the connected ecosystem. Further, we found consumer mobility consistently promoted the coexistence of a competing local species, regardless of community composition in the connected ecosystem. Our findings underscore the profound role of consumer mobility in shaping individual to ecosystem-level dynamics while emphasizing a strong mediating effect of community composition across the landscape.

ecology↗

bioRxiv2025

Extracting massive ecological data on state and interactions of species using large language models

The contemporary ecological crisis calls for integration and synthesis of ecological data describing the state, change and processes of ecological communities. However, such synthesis depends on the integration of vast amounts of mostly scattered and often hard-to-extract information that is published and dispersed across hundreds of thousands of scientific papers, for example describing species-specific interactions and trophic relationships. Recent advancements in natural language processing (NLP) and in particular the emergence of large language models (LLMs) offer a novel, and potentially revolutionary solution to this persistent challenge, for the first time creating the opportunity to access and extract virtually all data ever published. Here, we demonstrate the transformative potential of LLMs by extracting all types of biological interactions among species directly from a corpus of 83,910 scientific articles. Our approach successfully extracted a network of 144,402 interactions between 36,471 taxa. Performance analysis shows that the model exhibits a high sensitivity (70.0%) and excellent precision (89.5%). Our approach proves that LLMs are capable of carrying out complex extraction tasks on key ecological data on a very large scale, paving the way for a multitude of potential applications in ecology and beyond.

ecology↗