Belowground top-down and aboveground bottom-up effects structure multitrophic community relationships in a biodiverse forest
Research output: Journal contributions › Journal articles › Research › peer-review
Authors
Ecosystem functioning and human well-being critically depend on numerous species interactions above- and belowground. However, unraveling the structure of multitrophic interaction webs at the ecosystem level is challenging for biodiverse ecosystems. Attempts to identify major relationships between trophic levels usually rely on simplified proxies, such as species diversity. Here, we propose to consider the full information on species composition across trophic levels, using Procrustes correlation and structural equation models. We show that species composition data of a highly diverse subtropical forest - with 5,716 taxa across 25 trophic groups - reveal strong interrelationships among plants, arthropods, and microorganisms, indicating complex multitrophic interactions. We found substantial support for top-down effects of microorganisms belowground, indicating important feedbacks of microbial symbionts, pathogens, and decomposers on plant communities. In contrast, aboveground pathways were characterized by bottom-up control of plants on arthropods, including many non-trophic links. Additional analyses based on diversity patterns revealed much weaker interrelationships. Our study suggests that multitrophic communities in our forest system are structured via top-down effects of belowground biota on plants, which in turn affect aboveground arthropod communities across trophic levels. Moreover, the study shows that the consequences of species loss will be more complex than indicated by studies based solely on diversity.
Original language | English |
---|---|
Article number | 4222 |
Journal | Scientific Reports |
Volume | 7 |
Issue number | 1 |
Number of pages | 9 |
ISSN | 2045-2322 |
DOIs | |
Publication status | Published - 01.12.2017 |
- Ecosystems Research - Biodiversity, Community ecology, Ecological networks, Forest ecology, Microbial ecology