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Population density, bottom-up and top-down control as an interactive triplet to trigger dispersal
Bianca Kreuzinger-Janik1, Birgit Gansfort1, Christoph Ptatscheck2
1Animal Ecology, Bielefeld University, Konsequenz 45, 33615, Bielefeld, Germany.
Scientific Reports
|April 3, 2022
Summary
Animal dispersal is influenced by environmental cues. This study shows that for the nematode Caenorhabditis elegans, reduced food and higher population density increase emigration, demonstrating context-dependent dispersal behavior.
Area of Science:
- Behavioral Ecology
- Animal Movement
- Population Dynamics
Background:
- Dispersal is a crucial life-history strategy influenced by habitat costs and fitness benefits.
- Field studies on dispersal triggers are limited by controllability, necessitating laboratory investigations.
- Understanding dispersal mechanisms is vital for modeling animal behavior in dynamic landscapes.
Purpose of the Study:
- To investigate the influence of population density, bottom-up (food availability), and top-down (predation) control on nematode dispersal.
- To determine if environmental factors trigger non-random dispersal in Caenorhabditis elegans.
- To explore the interactive effects of these factors on emigration.
Main Methods:
- Experiments utilized two-chamber arenas to manipulate population density and food availability.
- The predatory flatworm Polycelis tenuis was introduced to simulate top-down control.
- Nematode movement and emigration rates were quantified under varied conditions.
Main Results:
- Decreasing food availability significantly increased nematode dispersal.
- Increasing population density also positively influenced nematode emigration.
- Predation by P. tenuis had inconsistent effects but amplified density-dependent dispersal under specific food conditions.
Conclusions:
- Nematode dispersal is a non-random, context-dependent decision influenced by environmental information.
- Population density and food availability are key drivers of small-scale dispersal in C. elegans.
- This research enhances the understanding of dispersal triggers and traits for improved ecological modeling.
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