» Articles » PMID: 33133633

Quantifying Large-scale Ecosystem Stability with Remote Sensing Data

Overview
Date 2020 Nov 2
PMID 33133633
Citations 5
Authors
Affiliations
Soon will be listed here.
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.

Citing Articles

Monitoring Terrestrial Ecosystem Resilience Using Earth Observation Data: Identifying Consensus and Limitations Across Metrics.

Runge K, Tucker M, Crowther T, Fournier de Lauriere C, Guirado E, Bialic-Murphy L Glob Chang Biol. 2025; 31(3):e70115.

PMID: 40066618 PMC: 11894503. DOI: 10.1111/gcb.70115.


Remotely sensing potential climate change tipping points across scales.

Lenton T, Abrams J, Bartsch A, Bathiany S, Boulton C, Buxton J Nat Commun. 2024; 15(1):343.

PMID: 38184618 PMC: 10771461. DOI: 10.1038/s41467-023-44609-w.


Differential developmental rates and demographics in Red Kangaroo () populations separated by the dingo barrier fence.

Mitchell D, Cairns S, Kortner G, Bradshaw C, Saltre F, Weisbecker V J Mammal. 2023; 104(5):929-940.

PMID: 37800099 PMC: 10550248. DOI: 10.1093/jmammal/gyad053.


Research Progress of Grassland Ecosystem Structure and Stability and Inspiration for Improving Its Service Capacity in the Karst Desertification Control.

He S, Xiong K, Song S, Chi Y, Fang J, He C Plants (Basel). 2023; 12(4).

PMID: 36840118 PMC: 9959505. DOI: 10.3390/plants12040770.


Increasing connections among temporal invariability, resistance and resilience of alpine grasslands on the Tibetan Plateau.

Yang Y, Sun Y, Niu B, Feng Y, Han F, Li M Front Plant Sci. 2022; 13:1026731.

PMID: 36438152 PMC: 9682138. DOI: 10.3389/fpls.2022.1026731.


References
1.
Hillebrand H, Langenheder S, Lebret K, Lindstrom E, Ostman O, Striebel M . Decomposing multiple dimensions of stability in global change experiments. Ecol Lett. 2017; 21(1):21-30. DOI: 10.1111/ele.12867. View

2.
Donohue I, Petchey O, Montoya J, Jackson A, McNally L, Viana M . On the dimensionality of ecological stability. Ecol Lett. 2013; 16(4):421-9. DOI: 10.1111/ele.12086. View

3.
Pettorelli N, Vik J, Mysterud A, Gaillard J, Tucker C, Stenseth N . Using the satellite-derived NDVI to assess ecological responses to environmental change. Trends Ecol Evol. 2006; 20(9):503-10. DOI: 10.1016/j.tree.2005.05.011. View

4.
de Keersmaecker W, Lhermitte S, Honnay O, Farifteh J, Somers B, Coppin P . How to measure ecosystem stability? An evaluation of the reliability of stability metrics based on remote sensing time series across the major global ecosystems. Glob Chang Biol. 2014; 20(7):2149-61. DOI: 10.1111/gcb.12495. View

5.
MORAN P . Notes on continuous stochastic phenomena. Biometrika. 1950; 37(1-2):17-23. View