DOI: 10.1016/j.quascirev.2019.01.009
Scopus记录号: 2-s2.0-85060885609
论文题名: Inferring critical transitions in paleoecological time series with irregular sampling and variable time-averaging
作者: Stegner M.A. ; Ratajczak Z. ; Carpenter S.R. ; Williams J.W.
刊名: Quaternary Science Reviews
ISSN: 2773791
出版年: 2019
卷: 207 起始页码: 49
结束页码: 63
语种: 英语
英文关键词: Abrupt change
; Critical transitions
; Data analysis
; Data treatment
; Global
; Paleolimnology
; Quaternary
; Regime shifts
; Resilience indicators
; Vegetation dynamics
Scopus关键词: Autocorrelation
; Data reduction
; Deforestation
; Paleolimnology
; Sedimentology
; Time series
; Abrupt change
; Data treatment
; Global
; Quaternary
; Regime shift
; Vegetation dynamics
; Sedimentation
; aridification
; data acquisition
; deforestation
; Holocene
; paleoecology
; paleolimnology
; proxy climate record
; sampling
; sedimentation
; sedimentation rate
; time series
; vegetation dynamics
; woodland
; Minnesota
; Steel Lake
; United States
英文摘要: Many ecosystems have abruptly changed in the past and may again in the future, yet prediction and inference of mechanisms causing abrupt changes remains challenging. Critical transitions are one such mechanism, occurring when systems with alternative states cross a threshold. Such transitions are associated with a loss of resilience, often signaled by increasing variability or autocorrelation over time. However, critical transitions are difficult to distinguish from other causal mechanisms, and detection of resilience loss in sedimentary archives can be confounded by time-averaging and discontinuous sampling. Here, we simulate woodland-grassland regime shifts resulting from critical transitions and other mechanisms. We then test the diagnostic ability of two widely-used resilience indicators, standard deviation and autocorrelation time, after alterations common in sedimentary records: time averaging, discontinuous sampling, and varying sedimentation rates. Standard deviation—but not autocorrelation time—still distinguishes gradually forced critical transitions from other regime shifts when sedimentation rates are constant, and can be robust to abrupt changes in sedimentation rate. Unfortunately, shifts in standard deviation alone are rarely definitive evidence of critical transitions. Under exponential sedimentation regimes, which are common in younger upper-column sediments, neither resilience indicator is effective. Discontinuous sampling weakened the strength of resilience indicators. A demonstrative analysis of abrupt early Holocene deforestation recorded at Steel Lake, Minnesota showed signals consistent with resilience loss during early Holocene aridification. Hence, signals of resilience loss can be recovered from sedimentary archives, but efficacy varies among indicators and sedimentation regime. High-resolution and multi-proxy records remain essential to inferring causes, while process-based time series modeling such as this can be calibrated to systems of interest to explicitly test hypotheses about abrupt change causes. © 2019 Elsevier Ltd Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/117376
Appears in Collections: 气候变化与战略
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Recommended Citation:
Stegner M.A.,Ratajczak Z.,Carpenter S.R.,et al. Inferring critical transitions in paleoecological time series with irregular sampling and variable time-averaging[J]. Quaternary Science Reviews,2019-01-01,207