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Ecological Disturbance

Ecological Disturbance

An ecological disturbance is a temporary disruption in the environment resulting from abiotic, biotic, or anthropogenic factors, causing a pronounced change in an ecosystem. The impact of an ecological disturbance, which can depend on its intensity, frequency, and spatial distribution, plays a significant role in shaping the species diversity within the ecosystem.

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Early Detection of Cyanobacterial Blooms and Associated Cyanotoxins using Fast Detection Strategy

Early Detection of Cyanobacterial Blooms and Associated Cyanotoxins using Fast Detection Strategy

Published on: February 25, 2021

Towards ecosystem-based techniques for tipping point detection.

Deevesh Ashley Hemraj¹, Jacob Carstensen¹

¹Department of Ecoscience, Aarhus University, Frederiksborgvej 399, Roskilde, DK-4000, Denmark.

Biological Reviews of the Cambridge Philosophical Society

|November 20, 2024

Summary

Detecting ecosystem state shifts is challenging due to complex interactions. Current methods often fail to capture the full ecosystem, limiting our understanding and management strategies for environmental change.

Keywords:

alternative stable state bifurcation dimensionality ecosystem resilience ecosystem state non‐linear regime shift threshold

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Last Updated: Jun 7, 2025

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Area of Science:

Ecology
Environmental Science
Complex Systems

Background:

Ecosystems can shift to alternative stable states when critical thresholds of pressure are exceeded.
Detecting these shifts is difficult due to complex interlinkages, feedback loops, and resilience mechanisms within ecosystems.
Current detection methods may not provide a comprehensive ecosystem-wide perspective, potentially limiting management applications.

Purpose of the Study:

To review and evaluate techniques for retrospective detection of ecosystem state shifts from empirical data.
To identify limitations of current methods in capturing broad ecological perspectives and high-dimensional data.
To explore methods suitable for a holistic, ecosystem-based approach to state shift detection.

Main Methods:

Systematic review of existing techniques for retrospective ecosystem state shift detection.
Analysis of methods based on their ability to integrate intervariable non-linear relationships and high-dimensional data.
Evaluation of the suitability of techniques for a broad ecosystem perspective.

Main Results:

Approximately 85% of current techniques focus on single subsystems, neglecting intervariable interactions and high-dimensional data.
Most methods are not designed for a broad ecosystem perspective, potentially leading to a limited perception of state shifts.
Current approaches often rely on smaller datasets that may not be representative of entire ecosystems.

Conclusions:

There is a need for improved methods that incorporate intervariable interactions and high-dimensionality data for accurate ecosystem state shift detection.
Developing techniques that adopt a broad ecosystem-based approach is crucial for effective ecosystem management and understanding resilience.
Future research should focus on methods that can integrate diverse data sources and complex ecological relationships to better detect critical thresholds.