Quantifying large‐scale ecosystem stability with remote sensing data. Issue 3 (1st April 2020)

• Record Type: Journal Article
• Authors: White, Hannah J.; Gaul, Willson; Sadykova, Dinara; León‐Sánchez, Lupe; Caplat, Paul; Emmerson, Mark C.; Yearsley, Jon M.
• Editors: Pettorelli, Nathalie; Zlinszky, András
• Is Part Of: Remote sensing in ecology and conservation. Volume 6:Issue 3(2020)
• Page Start: 354
• Page End: 365
• Publication Date: 2020-04-01
• Subjects: Ecosystem functioning -- resilience -- satellite -- stability -- vegetation index; Remote sensing -- Periodicals; Ecology -- Research -- Periodicals; Ecology -- Methodology -- Periodicals; Ecology -- Remote sensing -- Periodicals; Nature conservation -- Methodology -- Periodicals; 577.0723
• DOI: 10.1002/rse2.148
• Languages: English
• ISSNs: 2056-3485

Abstract

Abstract: To fully understand ecosystem functioning under global change, we need to be able to measure the stability of ecosystem functioning at multiple spatial scales. Although a number of stability components have been established at small spatial scales, there has been little progress in scaling these measures up to the landscape. Remote sensing data holds huge potential for studying processes at landscape scales but requires quantitative measures that are comparable from experimental field data to satellite remote sensing. Here we present a methodology to extract four components of ecosystem functioning stability from satellite‐derived time series of Enhanced Vegetation Index (EVI) data. The four stability components are as follows: variability, resistance, recovery time and recovery rate in ecosystem functioning. We apply our method to the island of Ireland to demonstrate the use of remotely sensed data to identify large disturbance events in productivity. Our method uses stability measures that have been established at the field‐plot scale to quantify the stability of ecosystem functioning. This makes our method consistent with previous small‐scale stability research, whilst dealing with the unique challenges of using remotely sensed data including noise. We encourage the use of remotely‐sensed data in assessing the stability of ecosystems at a scale that is relevant to conservation and management practices. Abstract : This paper presents a new methodological approach to measure multiple stability components of ecosystem functioning at large spatial scales using remotely sensed data. The measures of resistance, recovery time, recovery rate and temporal variability are comparable to those previously established at small scales whilst accounting for inherent noise within the data.