Literature DB >> 24777443

How to measure ecosystem stability? An evaluation of the reliability of stability metrics based on remote sensing time series across the major global ecosystems.

Wanda De Keersmaecker1, Stef Lhermitte, Olivier Honnay, Jamshid Farifteh, Ben Somers, Pol Coppin.   

Abstract

Increasing frequency of extreme climate events is likely to impose increased stress on ecosystems and to jeopardize the services that ecosystems provide. Therefore, it is of major importance to assess the effects of extreme climate events on the temporal stability (i.e., the resistance, the resilience, and the variance) of ecosystem properties. Most time series of ecosystem properties are, however, affected by varying data characteristics, uncertainties, and noise, which complicate the comparison of ecosystem stability metrics (ESMs) between locations. Therefore, there is a strong need for a more comprehensive understanding regarding the reliability of stability metrics and how they can be used to compare ecosystem stability globally. The objective of this study was to evaluate the performance of temporal ESMs based on time series of the Moderate Resolution Imaging Spectroradiometer derived Normalized Difference Vegetation Index of 15 global land-cover types. We provide a framework (i) to assess the reliability of ESMs in function of data characteristics, uncertainties and noise and (ii) to integrate reliability estimates in future global ecosystem stability studies against climate disturbances. The performance of our framework was tested through (i) a global ecosystem comparison and (ii) an comparison of ecosystem stability in response to the 2003 drought. The results show the influence of data quality on the accuracy of ecosystem stability. White noise, biased noise, and trends have a stronger effect on the accuracy of stability metrics than the length of the time series, temporal resolution, or amount of missing values. Moreover, we demonstrate the importance of integrating reliability estimates to interpret stability metrics within confidence limits. Based on these confidence limits, other studies dealing with specific ecosystem types or locations can be put into context, and a more reliable assessment of ecosystem stability against environmental disturbances can be obtained.
© 2013 John Wiley & Sons Ltd.

Keywords:  Normalized Difference Vegetation Index; climate disturbances; ecosystem stability; reliability; remote sensing; resilience; resistance; variance

Mesh:

Year:  2014        PMID: 24777443     DOI: 10.1111/gcb.12495

Source DB:  PubMed          Journal:  Glob Chang Biol        ISSN: 1354-1013            Impact factor:   10.863


  11 in total

1.  Ecology: Vegetation's responses to climate variability.

Authors:  Alfredo Huete
Journal:  Nature       Date:  2016-02-17       Impact factor: 49.962

2.  Diversity, Productivity, and Stability of an Industrial Microbial Ecosystem.

Authors:  Doruk Beyter; Pei-Zhong Tang; Scott Becker; Tony Hoang; Damla Bilgin; Yan Wei Lim; Todd C Peterson; Stephen Mayfield; Farzad Haerizadeh; Jonathan B Shurin; Vineet Bafna; Robert McBride
Journal:  Appl Environ Microbiol       Date:  2016-04-04       Impact factor: 4.792

3.  A resilience sensing system for the biosphere.

Authors:  Timothy M Lenton; Joshua E Buxton; David I Armstrong McKay; Jesse F Abrams; Chris A Boulton; Kirsten Lees; Thomas W R Powell; Niklas Boers; Andrew M Cunliffe; Vasilis Dakos
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2022-06-27       Impact factor: 6.671

4.  Identifying species from the air: UAVs and the very high resolution challenge for plant conservation.

Authors:  Susana Baena; Justin Moat; Oliver Whaley; Doreen S Boyd
Journal:  PLoS One       Date:  2017-11-27       Impact factor: 3.240

5.  Terrestrial land-cover type richness is positively linked to landscape-level functioning.

Authors:  Jacqueline Oehri; Bernhard Schmid; Gabriela Schaepman-Strub; Pascal A Niklaus
Journal:  Nat Commun       Date:  2020-01-09       Impact factor: 14.919

6.  Spatial Heterogeneity Analysis: Introducing a New Form of Spatial Entropy.

Authors:  Chaojun Wang; Hongrui Zhao
Journal:  Entropy (Basel)       Date:  2018-05-23       Impact factor: 2.524

7.  Simulating forest resilience: A review.

Authors:  Katharina Albrich; Werner Rammer; Monica G Turner; Zak Ratajczak; Kristin H Braziunas; Winslow D Hansen; Rupert Seidl
Journal:  Glob Ecol Biogeogr       Date:  2020-10-08       Impact factor: 6.909

8.  Temporal Stability of Vegetation Cover across the Loess Plateau Based on GIMMS during 1982-2013.

Authors:  Chunyan Zhang; Shan Guo; Yanning Guan; Danlu Cai; Xiaolin Bian
Journal:  Sensors (Basel)       Date:  2021-01-05       Impact factor: 3.576

9.  N-dimensional hypervolumes to study stability of complex ecosystems.

Authors:  Ceres Barros; Wilfried Thuiller; Damien Georges; Isabelle Boulangeat; Tamara Münkemüller
Journal:  Ecol Lett       Date:  2016-07       Impact factor: 9.492

10.  Effect of diversity on growth, mortality, and loss of resilience to extreme climate events in a tropical planted forest experiment.

Authors:  Chantal Hutchison; Dominique Gravel; Frédéric Guichard; Catherine Potvin
Journal:  Sci Rep       Date:  2018-10-18       Impact factor: 4.379

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