DOI: 10.1111/gcb.12495
论文题名: How to measure ecosystem stability? An evaluation of the reliability of stability metrics based on remote sensing time series across the major global ecosystems
作者: De Keersmaecker W. ; Lhermitte S. ; Honnay O. ; Farifteh J. ; Somers B. ; Coppin P.
刊名: Global Change Biology
ISSN: 13541013
出版年: 2014
卷: 20, 期: 7 起始页码: 2149
结束页码: 2161
语种: 英语
英文关键词: Climate disturbances
; Ecosystem stability
; Normalized Difference Vegetation Index
; Reliability
; Remote sensing
; Resilience
; Resistance
; Variance
Scopus关键词: climate effect
; drought
; ecosystem service
; environmental disturbance
; land cover
; MODIS
; NDVI
; reliability analysis
; remote sensing
; climate change
; ecosystem
; environmental monitoring
; Europe
; evaluation study
; procedures
; remote sensing
; reproducibility
; theoretical model
; Climate Change
; Ecosystem
; Environmental Monitoring
; Europe
; Models, Theoretical
; Remote Sensing Technology
; Reproducibility of Results
英文摘要: 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. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/62054
Appears in Collections: 影响、适应和脆弱性
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作者单位: M3-BIORES, KU Leuven, Willem de Croylaan 34, Heverlee, B-3001, Belgium; Royal Netherlands Meteorological Institute (KNMI), Wilhelminalaan 10, De Bilt, NL-3732, Netherlands; Department of Earth and Environmental Sciences, KU Leuven, Celestijnenlaan 200E, Heverlee, B-3001, Belgium; Ecologie, Evolutie en Biodiversiteitsbehoud, KU Leuven, Kasteelpark Arenberg 31, Heverlee, B-3001, Belgium; Division of Forest, Nature and Landscape, KU Leuven, Celestijnenlaan 200E, Heverlee, B-3001, Belgium
Recommended Citation:
De Keersmaecker W.,Lhermitte S.,Honnay O.,et al. How to measure ecosystem stability? An evaluation of the reliability of stability metrics based on remote sensing time series across the major global ecosystems[J]. Global Change Biology,2014-01-01,20(7)