Analysing multiple time series and extending significance testing in wavelet analysis

Rouyer, Tristan; Fromentin, Jean‐Marc; Stenseth, Nils Chr.; Cazelles, Bernard

doi:10.3354/meps07330

Cited by 101 publications

(111 citation statements)

References 58 publications

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“…Particularly, unlike Fourier transform, wavelet analysis performs locally in both time and frequency domains and thus can track the change of its periodicity over time (nonstationary periodicity) Rouyer et al, 2008). Cross-wavelet transform and wavelet coherence are suitable for examining relationships in time-frequency space between two time series' (Grinsted et al, 2004).…”

Section: Statisticsmentioning

confidence: 99%

Macro-Economic Cycles Related to Climate change in Dynastic China

et al. 2015

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Investigations of the relationships between climate and human history often place more emphasis on the science of climate change than on understanding human socio-economic processes, and therefore suffer from superficial results and an unbalanced perspective. This is partly due to the lack of high-resolution data concerning long-term socio-economic processes. Here, we base our study of climate and society on a series of 2130-yr-long economic proxy data from China with decadal resolution. The economy was associated significantly with temperature and precipitation at the two predominant bands of 100 and 320 yr. The phase transition of economic states was influenced positively by long-term temperature change combined with triggering effects of short-term changes in precipitation. However, climatic impact on economy should not be recognized as simple causality but some driving-response relation coupled with meditation by human agency at multiple scales. A model of 'adaptive cycles' implies, in relative to the developing phases, climate-economy relationship during the declining phases was more easily moderated by slower processes like rigidity and faster processes like unrest. From a more-macro perspective, climatic driving for the macro-economic cycles was moderated by larger and slower processes like social memory, spatial shifting of key economic areas, and social-technical advance.

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Section: Statisticsmentioning

confidence: 99%

Macro-Economic Cycles Related to Climate change in Dynastic China

et al. 2015

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“…However, no robust measure of whether this may be an artefact of the dominance of one of the signals, or not, is carried out (e.g. combining clustered wavelet spectra with maximum covariance analysis presented by Rouyer et al (2008)). The higherfrequency 'wave-contaminated' scales appear to be less coherent in all planes both near the bed and outside the boundary layer.…”

Section: Spectral Analysis Of Turbulence and Suspensionmentioning

confidence: 99%

Wave-induced coherent turbulence structures and sediment resuspension in the nearshore of a prototype-scale sandy barrier beach

Kassem

Thompson

Amos

et al. 2015

Continental Shelf Research

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Abstract:The suspension of sediments by oscillatory flows is a complex case of fluid-particle interaction. The aim of this study is to provide insight into the spatial (time) and scale (frequency) relationships between wave-generated boundary layer turbulence and eventdriven sediment transport beneath irregular shoaling and breaking waves in the nearshore of a prototype sandy barrier beach, using data collected through the Barrier Dynamics Experiment II (BARDEX II). Statistical, quadrant and spectral analyses reveal the anisotropic and intermittent nature of Reynolds' stresses (momentum exchange) in the wave boundary layer, in all three orthogonal planes of motion. The fractional contribution of coherent turbulence structures appears to be dictated by the structural form of eddies beneath plunging and spilling breakers, which in turn define the net sediment mobilisation towards or away from the barrier, and hence ensuing erosion and accretion trends. A standing transverse wave is also observed in the flume, contributing to the substantial skewness of spanwise turbulence. Observed low frequency suspensions are closely linked to the mean flow (wave) properties. Wavelet analysis reveals that the entrainment and maintenance of sediment in suspension through a cluster of bursting sequence is associated with the passage of intermittent slowly-evolving large structures, which can modulate the frequency of smaller motions. Outside the boundary layer, small scale, higher frequency turbulence drives the suspension. The extent to which these spatially varied perturbation clusters persist is associated with suspension events in the high frequency scales, decaying as the turbulent motion ceases to supply momentum, with an observed hysteresis effect. The suspension of sediment in turbulent flows is a complex case of fluid-particle interaction, governed by shear stresses (momentum exchanges) at the bed and within the benthic boundary layer (BBL). Defining the physical processes which dictate the resuspension of sediments in coastal and estuarine settings is fundamental for accurate predictions of bed morphology evolution (Van Rijn et al., 2007), and has profound implications for the biogeochemical processes that shape their local ecology (Thompson et al., 2011). It is also a prerequisite to quantifying erosion and deposition trends, and hence guiding engineering applications such as beach nourishment, defence schemes against erosion and flooding, maintenance of marine infrastructure and waterways, and aggregate dredging. There is a genuine need for better, robust models of suspended sediment transport in the coastal zone (Aagaard and Jensen, 2013). In a vision paper on future research needs in coastal dynamics, Van Rijn et al. (2013) highlighted the pressing need for research to support such models, focusing in particular on sand transport in the shoreface (non-breaking waves), surf and swash zones; employing field and controlled laboratory experiments.The mobilisation of sediments in the nearshore and shoreface is dominated b...

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“…The main requirement of many statistical tools for time series analysis (e.g., Fourier analysis) is stationarity (Priestley, 1981). However, environmental time series do not always satisfy this requirement, and growing evidence supports the need to consider the importance of transient dynamics in environmental process (Stenseth et al, 1998;Hsieh et al, 2005;Cazelles et al, 2008;Rouyer et al, 2008).…”

Section: Introductionmentioning

confidence: 99%

“…A simple approach to study environmental processes is to consider them as linear and stationary, although, non-linear, nonstationary, and multi-scale processes are the rule rather than the exception (Hsieh et al, 2005;Rouyer et al, 2008). The main requirement of many statistical tools for time series analysis (e.g., Fourier analysis) is stationarity (Priestley, 1981).…”

Section: Introductionmentioning

confidence: 99%

“…Recent evidence using wavelet analysis and other statistical tools indicates that climatic oscillations, such as the North Atlantic Oscillation (NAO), the Indian Oscillation (IOI), or the El Niño-Southern Oscillation (ENSO) have important effects on marine fish populations (Mantua et al, 1997;Mènard et al, 2007;Rouyer et al, 2008;Hsieh et al, 2009) far-reaching societal impacts (Jacobson et al, 2001;Hsieh et al, 2009). However, there are relatively few studies using cephalopod species, such as octopus, especially at the geographical locations around the Saharan bank (close to the Canary Islands and Northwestern African shelf) (Pierce et al, 2008).…”

Section: Introductionmentioning

confidence: 99%

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Wavelet analysis of correlation among Canary Islands octopus captures per unit effort, sea-surface temperatures and the North Atlantic Oscillation

et al. 2011

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a b s t r a c tShort-term fluctuations in the octopus catches off the Canary Islands have been attributed to changes in the sea surface temperature (SST) and the North Atlantic Oscillation (NAO) pattern. These results have been found using stationarity assumptions. However, the behavior of environmental systems is not always linear, and environmental time series do not always satisfy the statistical property of stationarity. Wavelet spectral analysis is a methodology which can deal with non-linear, non-stationary and noisy time series. Cross wavelet analysis (wavelet coherence) is applied to investigate the environmental effects (SST, NAO) on octopus abundance fluctuations measured as capture per unit of effort (CPUE) from 1989 to 2007 in the waters of the Canary Islands. A slightly positive correlation exists between NAO and CPUE at lags and leads of a few months. Additionally, a good relationship between SST and CPUE exists on the same seasonal scale, but there is a relatively weak relationship between SST anomalies and the NAO. When the analysis is extended to the interannual scale, the wavelet coherence identifies a statistically significant relationship between CPUE and NAO, but this does not happen when the wavelet coherence between CPUE and SST is computed. These results suggest that fluctuations in octopus catches could be the result of SST fluctuations but in synergy with other unknown environmental variables which are also affected by the NAO pattern.

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Analysing multiple time series and extending significance testing in wavelet analysis

Cited by 101 publications

References 58 publications

Macro-Economic Cycles Related to Climate change in Dynastic China

Macro-Economic Cycles Related to Climate change in Dynastic China

Wave-induced coherent turbulence structures and sediment resuspension in the nearshore of a prototype-scale sandy barrier beach

Wavelet analysis of correlation among Canary Islands octopus captures per unit effort, sea-surface temperatures and the North Atlantic Oscillation

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