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Related Experiment Video

Updated: Jun 11, 2025

Linking Predation Risk, Herbivore Physiological Stress and Microbial Decomposition of Plant Litter

Linking Predation Risk, Herbivore Physiological Stress and Microbial Decomposition of Plant Litter

Published on: March 12, 2013

Asymmetric Biotic Interactions Cannot Be Inferred Without Accounting for Priority Effects.

Francisca Powell-Romero¹, Konstans Wells², Nicholas J Clark¹

¹School of Veterinary Science, The University of Queensland, Gatton, Queensland, Australia.

Ecology Letters

|October 2, 2024

Summary

This summary is machine-generated.

Sampling design is crucial for detecting biotic interactions. Priority effects, or the order of species colonization, can obscure asymmetric interactions in co-occurrence data, necessitating careful study design for accurate ecological insights.

Keywords:

asymmetric interactions biotic interactions community ecology priority effects species interactions

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Area of Science:

Community ecology
Species distribution modelling
Ecological interactions

Background:

Quantifying biotic interactions is key for ecological predictions.
Computational methods for biotic interactions are advancing.
Sampling design's role in detecting biotic interactions is understudied.

Purpose of the Study:

To explore how priority effects influence the detection of biotic interactions.
To demonstrate the limitations of cross-sectional co-occurrence data for inferring asymmetric interactions.
To propose improved sampling designs for studying biotic interactions.

Main Methods:

Utilized simulations to investigate the impact of priority effects.
Analyzed cross-sectional co-occurrence data.
Compared standard sampling with designs accounting for priority effects.

Main Results:

Cross-sectional co-occurrence data alone are insufficient for reliable inference of asymmetric biotic interactions.
Priority effects can mask asymmetric interactions, even when species occurrence is accurately predicted.
Sampling designs incorporating priority effects can recover lost information on asymmetric interactions.

Conclusions:

Caution is advised when inferring biotic interactions from binary co-occurrence data.
Priority effects significantly impact the detectability of ecological interactions.
Specific sampling designs are needed to accurately capture asymmetric biotic interactions.