Quantifying large-scale ecosystem stability with remote sensing data

Area of Science:

• Ecology
• Remote Sensing
• Environmental Science

Background:

• Understanding ecosystem functioning stability is vital for predicting responses to global change.
• Existing stability measures are primarily limited to small spatial scales, hindering landscape-level assessments.
• Remote sensing offers potential for large-scale ecological studies but requires methods linking field and satellite data.

Purpose of the Study:

• To develop and present a methodology for extracting ecosystem functioning stability components from satellite-derived time series data.
• To quantify four key stability components: variability, resistance, recovery time, and recovery rate.
• To demonstrate the application of this methodology for identifying large-scale disturbance events.

Main Methods:

• Utilized time series of satellite-derived Enhanced Vegetation Index (EVI) data.
• Extracted four components of ecosystem functioning stability: variability, resistance, recovery time, and recovery rate.
• Applied the methodology to the island of Ireland to identify major productivity disturbances.

Main Results:

• Successfully extracted four components of ecosystem functioning stability from satellite EVI data.
• Demonstrated the capability to identify large-scale disturbance events impacting ecosystem productivity.
• Validated the consistency of the method with established small-scale stability research while addressing remote sensing data challenges.

Conclusions:

• The developed methodology enables consistent, landscape-scale assessment of ecosystem functioning stability using remote sensing.
• This approach bridges the gap between field-scale ecological research and large-scale remote sensing observations.
• Encourages the use of remote sensing for ecosystem stability assessments relevant to conservation and management.