Cyclic dynamics of sympatric lemming populations on Bylot Island, Nunavut, Canada

2008 ◽  
Vol 86 (8) ◽  
pp. 910-917 ◽  
Author(s):  
Nicolas Gruyer ◽  
Gilles Gauthier ◽  
Dominique Berteaux
Keyword(s):  
Time Series ◽  
High Arctic ◽  
Sympatric Species ◽  
Population Fluctuations ◽  
Main Site ◽  
Bylot Island ◽  
Annual Index ◽  
Lemming Abundance ◽  
Highly Correlated ◽  
Arctic Area

We characterized the fluctuations (amplitude, periodicity) of two sympatric species, the brown lemming ( Lemmus sibiricus (Kerr, 1792)) and the northern collared lemming ( Dicrostonyx groenlandicus (Traill, 1823)), in a High Arctic area. Our objective was to determine if these populations were cyclic, and if fluctuations in numbers were synchronized between the two species temporally and spatially. An annual index of lemming abundance was obtained using snap-traps at two sites 30 km apart on Bylot Island (Nunavut, Canada) over 13 years (1993–2005) and 9 years (1997–2005), respectively. The time series were analyzed by spectral analyses and autoregressive modelling. At the site with the longest record, brown lemming showed regular population fluctuations of large amplitude (>40-fold), but collared lemming fluctuations were of much smaller amplitude (4-fold). At the other site, the collared lemming population was higher than at the main site, but brown lemmings were still most abundant in the peak year. Models with a second-order function obtained from a spectral analysis were highly correlated with the observed abundance index in both species at the site with the longest time series, and provide evidence of cyclic dynamic. The periods of the cycles were estimated at 3.69 ± 0.04 (SE) years for brown lemmings and 3.92 ± 0.24 (SE) years for collared lemmings, but the amplitude of the cycle was weak in the latter species. Fluctuations in abundance at the same site were relatively well synchronized between the two species, but the evidence for synchrony between sites was equivocal.

scholarly journals Estimating Conditional Transfer Entropy in Time Series Using Mutual Information and Nonlinear Prediction

Entropy ◽  
2020 ◽  
Vol 22 (10) ◽  
pp. 1124
Author(s):  
Payam Shahsavari Baboukani ◽  
Carina Graversen ◽  
Emina Alickovic ◽  
Jan Østergaard
Keyword(s):  
Time Series ◽  
State Of The Art ◽  
Difficult Case ◽  
Nonlinear Prediction ◽  
False Detection ◽  
Uniform Embedding ◽  
Embedding Technique ◽  
New Information ◽  
Highly Correlated ◽  
Intracranial Electroencephalography

We propose a new estimator to measure directed dependencies in time series. The dimensionality of data is first reduced using a new non-uniform embedding technique, where the variables are ranked according to a weighted sum of the amount of new information and improvement of the prediction accuracy provided by the variables. Then, using a greedy approach, the most informative subsets are selected in an iterative way. The algorithm terminates, when the highest ranked variable is not able to significantly improve the accuracy of the prediction as compared to that obtained using the existing selected subsets. In a simulation study, we compare our estimator to existing state-of-the-art methods at different data lengths and directed dependencies strengths. It is demonstrated that the proposed estimator has a significantly higher accuracy than that of existing methods, especially for the difficult case, where the data are highly correlated and coupled. Moreover, we show its false detection of directed dependencies due to instantaneous couplings effect is lower than that of existing measures. We also show applicability of the proposed estimator on real intracranial electroencephalography data.

Co-movement of precious metals and forecasting using scale by scale wavelet transform

2017 ◽  
Vol 04 (01) ◽  
pp. 1750007 ◽  
Author(s):  
Emrah Oral ◽  
Gazanfer Unal
Keyword(s):  
Time Series ◽  
Wavelet Transform ◽  
Moving Average ◽  
Precious Metals ◽  
Wavelet Coherence ◽  
Frequency Scale ◽  
Time Space ◽  
Daily Data ◽  
Gold Silver ◽  
Highly Correlated

In this paper, a new approach is proposed to improve forecasting performances. We analyze the co-movement of precious metals (daily data of gold, silver and platinum starting from July, 2011) using multiple wavelet coherence and determine the movement dependencies on frequency–time space. The data is split into frequencies using scale by scale continuous wavelet transform. All three time series retaining the same frequency scale are (i) selected, (ii) inversed and (ii) forecasted using multivariate model, Vector Auto Regressive Moving Average (VARMA). We conclude that the efficiency of VARMA forecasting is substantially increased because of same frequency highly correlated time series obtained by using scale by scale wavelet transform. Moreover, the direction of price shift (increasing/decreasing trend) is prospected to an adequately distinguishable degree.

Fishing through (and up) Alaskan food webs

2009 ◽  
Vol 66 (2) ◽  
pp. 201-211 ◽  
Author(s):  
Michael A. Litzow ◽  
Daniel Urban
Keyword(s):  
Time Series ◽  
Trophic Level ◽  
High Trophic Level ◽  
Climate Index ◽  
Climate Regime ◽  
Fisheries Sustainability ◽  
Competing Hypotheses ◽  
Mean Trophic Level ◽  
Highly Correlated ◽  
Historical Periods

We used a 112-year time series of Alaskan fishery catches to test competing hypotheses concerning trends in mean catch trophic level, a widely used indicator of fisheries sustainability. We found that mean trophic level has generally remained steady or increased in recent decades on Alaska-wide and regional scales, indicating stable catches of high trophic level taxa. During historical periods of declining mean trophic level, catches of upper trophic level taxa either increased or remained steady, contrary to the predictions of the “fishing down the food web” hypothesis. Further, a climate index was highly correlated (r = 0.69–0.97) with mean trophic level and (or) the related fisheries in balance (FIB) index across climate regime shifts in the 1940s and 1970s, indicating that climate effects, particularly on high trophic level taxa, can act as the major driver of variability in these parameters. These results provide a contrast to the view of ubiquitous declines in mean trophic level of fishery catches, driven by overexploitation and serial stock replacement.

scholarly journals Variability and trends in dynamical forcing of tropical lower stratospheric temperatures

2014 ◽  
Vol 14 (24) ◽  
pp. 13439-13453 ◽  
Author(s):  
S. Fueglistaler ◽  
M. Abalos ◽  
T. J. Flannaghan ◽  
P. Lin ◽  
W. J. Randel
Keyword(s):  
Heat Flux ◽  
Time Series ◽  
Reanalysis Data ◽  
Heat Fluxes ◽  
Momentum Balance ◽  
Latitude Belt ◽  
Eddy Heat Flux ◽  
Temperature Trends ◽  
Highly Correlated ◽  
Additional Support

Abstract. The contribution of dynamical forcing to variations and trends in tropical lower stratospheric 70 hPa temperature for the period 1980–2011 is estimated based on ERA-Interim and Modern-Era Retrospective Analysis for Research and Applications (MERRA) reanalysis data. The dynamical forcing is estimated from the tropical mean residual upwelling calculated with the momentum balance equation, and with a simple proxy based on eddy heat fluxes averaged between 25° and 75° in both hemispheres. The thermodynamic energy equation with Newtonian cooling is used to relate the dynamical forcing to temperature. The deseasonalised, monthly mean time series of all four calculations are highly correlated (~ 0.85) with temperature for the period 1995–2011 when variations in radiatively active tracers are small. All four calculations provide additional support to previously noted prominent aspects of the temperature evolution 1980–2011: an anomalously strong dynamical cooling (~ −1 to −2 K) following the Pinatubo eruption that partially offsets the warming from enhanced aerosol, and a few years of enhanced dynamical cooling (~ −0.4 K) after October 2000 that contributes to the prominent drop in water entering the stratosphere at that time. The time series of dynamically forced temperature calculated with the same method are more highly correlated and have more similar trends than those from the same reanalysis but with different methods. For 1980–2011 (without volcanic periods), the eddy heat flux calculations give a dynamical cooling of ~ −0.1 to ~ −0.25 K decade−1 (magnitude sensitive to latitude belt considered and reanalysis), largely due to increasing high latitude eddy heat flux trends in September and December–January. The eddy heat flux trends also explain the seasonality of temperature trends very well, with maximum cooling in January–February. Trends derived from momentum balance calculations show near-zero annual mean dynamical cooling, with weaker seasonal trends especially in December–January. These contradictory results arising from uncertainties in data and methods are discussed and put in context to previous analyses.

Analysis of historic jack pine budworm outbreaks in the Prairie provinces of Canada

1988 ◽  
Vol 18 (9) ◽  
pp. 1152-1158 ◽  
Author(s):  
W. Jan A. Volney
Keyword(s):  
Time Series ◽  
Severity Index ◽  
Jack Pine ◽  
Stationary Time Series ◽  
Sufficient Information ◽  
Outbreak Area ◽  
Jack Pine Budworm ◽  
Annual Time Series ◽  
Time Series Analyses ◽  
Highly Correlated

The annual Forest Insect and Disease Survey reports of the Canadian Forestry Service were used to develop a jack pine budworm (Choristoneurapinus Freeman) defoliation severity index for a 50-year span. The region covered was the western half of the host's (Pinusbanksiana Lamb.) range. An interpretation of this record permitted the construction of an annual time series of the total area moderately to severely or severely defoliated. The area of outbreaks has increased over the period. This trend was removed from the data to obtain a stationary time series. Analyses of the time series showed that there was a statistically significant periodicity to the size of outbreaks. An examination of the sample autocorrelation function revealed that only the past year's outbreak area was significantly correlated with that of the current year's outbreak. The model identified by applying the Box–Jenkins methodology to these results was inadequate, indicating that the series itself does not contain sufficient information for predictions. Outbreak area and the total area burned in Manitoba and Saskatchewan 4–7 years previously were highly correlated. Despite the crudity of the data, these relations could be exploited to develop predictors of outbreak size and occurrence. The significance of these results for forest management in the region is discussed.

Dynamic correlation of Eastern and Western markets and forecasting: Scale-by-scale wavelet-based approach

2017 ◽  
Vol 04 (04) ◽  
pp. 1750040 ◽  
Author(s):  
Emrah Oral ◽  
Gazanfer Unal
Keyword(s):  
Time Series ◽  
Wavelet Transform ◽  
Moving Average ◽  
Wavelet Coherence ◽  
Vector Autoregressive ◽  
Frequency Space ◽  
Time Frequency ◽  
Dynamic Correlation ◽  
Frequency Scale ◽  
Highly Correlated

In this paper, dynamic four-dimensional (4D) correlation of eastern and western markets is analyzed. A wavelet-based scale-by-scale analysis method has been introduced to model and forecast stock market data for strongly correlated time intervals. The daily data of stock markets of SP500, FTSE and DAX (western markets) and NIKKEI, TAIEX and KOSPI (eastern markets) are obtained from 2009 to the end of 2016 and their co-movement dependencies on time–frequency space using 4D multiple wavelet coherence (MWC) are determined. Once the data is detached into levels of different frequencies using scale-by-scale continuous wavelet transform, all of the time series possessing the same frequency scale are selected, inversed and forecasted using multivariate model, vector autoregressive moving average (VARMA). It is concluded that the efficiency of forecasting is increased substantially using the same-frequency highly correlated time series obtained by scale-by-scale wavelet transform. Moreover, the increasing or decreasing trend of prospected price shift is foreseen fairly well.

The stratospheric quasi-biennial oscillation observed in the semidiurnal ground pressure data

1995 ◽  
Vol 13 (7) ◽  
pp. 740-744 ◽  
Author(s):  
H. Teitelbaum ◽  
F. Vial ◽  
P. Bauer
Keyword(s):  
Time Series ◽  
Pressure Measurements ◽  
Pressure Data ◽  
Quasi Biennial Oscillation ◽  
Ground Pressure ◽  
Trace Back ◽  
Stratospheric Balloon ◽  
Highly Correlated ◽  
Biennial Oscillation ◽  
Balloon Measurements

Abstract. Ground pressure observations made at Macao (22°N, 113°E) from 1953 to 1991 are analyzed and compared with the stratospheric quasi-biennial oscillation (QBO) data obtained during the same interval. The periods of the two phenomena and their time evolution are found to be close to each other. Furthermore, the time series of the stratospheric winds and the S2(p) QBO signature are highly correlated, thus confirming earlier analysis. On this basis, pressure measurements obtained at Batavia (now Djakarta: 6°S, 107°E) from 1870 to 1944 are used to trace back the QBO phenomenon before the advent of systematic stratospheric balloon measurements. The inferred period, which varies between 25 and 32 months, suggests that the QBO has been present in the atmosphere at least since 1870.

scholarly journals A Synergistic Analysis of Cloud Cover and Vertical Distribution from A-Train and Ground-Based Sensors over the High Arctic Station Eureka from 2006 to 2010

2014 ◽  
Vol 53 (11) ◽  
pp. 2553-2570 ◽  
Author(s):  
Yann Blanchard ◽  
Jacques Pelon ◽  
Edwin W. Eloranta ◽  
Kenneth P. Moran ◽  
Julien Delanoë ◽  
...  
Keyword(s):  
Vertical Distribution ◽  
Lower Troposphere ◽  
High Arctic ◽  
Satellite Observations ◽  
The Arctic ◽  
Cloud Detection ◽  
Hit Rate ◽  
Sensitivity Loss ◽  
Independent Observations ◽  
Arctic Area

AbstractActive remote sensing instruments such as lidar and radar allow one to accurately detect the presence of clouds and give information on their vertical structure and phase. To better address cloud radiative impact over the Arctic area, a combined analysis based on lidar and radar ground-based and A-Train satellite measurements was carried out to evaluate the efficiency of cloud detection, as well as cloud type and vertical distribution, over the Eureka station (80°N, 86°W) between June 2006 and May 2010. Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) and CloudSat data were first compared with independent ground-based cloud measurements. Seasonal and monthly trends from independent observations were found to be similar among all datasets except when compared with the weather station observations because of the large reported fraction of ice crystals suspended in the lower troposphere in winter. Further investigations focused on satellite observations that are collocated in space and time with ground-based data. Cloud fraction occurrences from ground-based instruments correlated well with both CALIPSO operational products and combined CALIPSO–CloudSat retrievals, with a hit rate of 85%. The hit rate was only 77% for CloudSat products. The misdetections were mainly attributed to 1) undetected low-level clouds as a result of sensitivity loss and 2) missed clouds because of the distance between the satellite track and the station. The spaceborne lidar–radar synergy was found to be essential to have a complete picture of the cloud vertical profile down to 2 km. Errors are quantified and discussed.

scholarly journals A net decrease in the Earth's cloud plus aerosol reflectivity during the past 33 yr (1979–2011) and increased solar heating at the surface

2012 ◽  
Vol 12 (12) ◽  
pp. 31991-32038 ◽  
Author(s):  
J. R. Herman ◽  
M. T. DeLand ◽  
L.-K. Huang ◽  
G. Labow ◽  
D. Larko ◽  
...  
Keyword(s):  
Time Series ◽  
Southern Oscillation ◽  
Weighted Average ◽  
Equatorial Region ◽  
The Us ◽  
Surface Reflectivity ◽  
Zonal Average ◽  
Decadal Climate ◽  
Highly Correlated

Abstract. Measured upwelling radiances from Nimbus-7 SBUV, seven NOAA SBUV/2 and the AURA-OMI instruments have been used to calculate the 340 nm Lambertian Equivalent Reflectivity (LER) of the Earth from 1979 to 2011 after applying a new common calibration. The 340 nm LER is highly correlated with cloud and aerosol cover because of the low surface reflectivity of the land and oceans (typically 2 to 6 RU, where 1 RU = 0.01 = 1.0%) relative to the much higher reflectivity of clouds plus aerosols (typically 10 to 90 RU). Because of the nearly constant seasonal and long-term 340 nm surface reflectivity, the 340 nm LER can be used to estimate changes in cloud plus aerosol amount associated with seasonal and interannual variability and decadal climate change. The annual motion of the Intertropical Convergence Zone, episodic El Nino Southern Oscillation ENSO, and latitude dependent seasonal cycles are apparent in the LER time series. LER trend estimates from 5° zonal average and from 2° × 5° latitude × longitude time series show that there has been a global net decrease in cloud plus aerosol reflectivity. The decrease in global cos2 (latitude) weighted average LER from 60° S to 60° N is 0.79 ± 0.03 RU over 33 yr, corresponding to a 3.6 ± 0.2% change in LER. Based on energy balance partitioning (Trenberth et al., 2009) this corresponds to an increase of 2.7 W m−2 of solar energy reaching the Earth's surface (an increase of 1.4% or 2.3 W m−2) absorbed by the surface, which is partially offset by an increase in longwave cooling to space. Most of the decreases in cloud reflectivity occur over land, with the largest decreases occurring over the US (−0.97 RU decade−1), Brazil (−0.9 RU decade−1), and Central Europe (−1.35 RU decade−1). There are reflectivity increases near the west coast of Peru and Chile (0.8 ± 0.1 RU decade−1) over parts of India, China, and Indochina, and almost no change over Australia. The largest Pacific Ocean change is −2 ± 0.1 RU decade−1 over the central equatorial region associated with ENSO. An area in Central Greenland shows a decrease in reflectivity of −0.3 ± 0.03 RU decade−1 caused by cloud and possible surface changes.

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