Variations in radial growth of declining old-growth stands of Abiesamabilis after tephra deposition from Mount St. Helens

1995 ◽  
Vol 25 (9) ◽  
pp. 1484-1492 ◽  
Author(s):  
Gerardo Segura ◽  
Thomas M. Hinckley ◽  
Linda B. Brubaker
Keyword(s):  
Time Series ◽  
Radial Growth ◽  
Time Series Models ◽  
Silver Fir ◽  
Growth Trend ◽  
Old Growth ◽  
Compensatory Response ◽  
Growth Changes ◽  
Original Time ◽  
Mount St Helens

Radial growth trends of old-growth mixed conifer forests were evaluated in areas impacted by tephra deposition from the 1980 eruption of Mount St. Helens, Washington. These areas were characterized by a crown decline in Abiesamabilis (Dougl.)Forbes (Pacific silver fir), associated with the long-term tephra retention by foliage. Post-1980 growth changes of A. amabilis were quantified using standard dendrochronological techniques in stands covering a range of crown decline conditions, amount of tephra deposited, elevation, and species composition. Time-series models revealed autocorrelations in the growth trend of all species at all sites. Intervention analysis quantified posteruption radial growth changes and significantly improved the description of the original time series models. Growth reductions of A. amabilis were generally consistent with the mean crown decline conditions of individual sites. However, the magnitude of growth reductions did not correspond closely to the decline condition of the stand. Abiesamabilis experienced significant post-1980 growth reductions in sites with high crown decline, but no growth changes were detected in sites with low decline. Tsugaheterophylla (Raf.)Sarg.(western hemlock) and Pseudotsugamenziesii (Mirb.) Franco (Douglas-fir), which consistently occurred with A. amabilis in the study area, did either not experience growth reductions or had significant positive growth after 1981. This positive post-disturbance growth could be explained as a compensatory response to the appreciable growth decline of A. amabilis.

scholarly journals Evidence of elevation-specific growth changes of spruce, fir, and beech in European mixed mountain forests during the last three centuries

2020 ◽  
Vol 50 (7) ◽  
pp. 689-703 ◽  
Author(s):  
Hans Pretzsch ◽  
Torben Hilmers ◽  
Peter Biber ◽  
Admir Avdagić ◽  
Franz Binder ◽  
...  
Keyword(s):  
Abies Alba ◽  
European Beech ◽  
Spatiotemporal Pattern ◽  
Silver Fir ◽  
Mountain Forests ◽  
Growth Trend ◽  
Dependent Change ◽  
Fagus Sylvatica L ◽  
Growth Changes

In Europe, mixed mountain forests, primarily comprised of Norway spruce (Picea abies (L.) Karst.), silver fir (Abies alba Mill.), and European beech (Fagus sylvatica L.), cover about 10 × 106 ha at elevations between ∼600 and 1600 m a.s.l. These forests provide invaluable ecosystem services. However, the growth of these forests and the competition among their main species are expected to be strongly affected by climate warming. In this study, we analyzed the growth development of spruce, fir, and beech in moist mixed mountain forests in Europe over the last 300 years. Based on tree-ring analyses on long-term observational plots, we found for all three species (i) a nondecelerating, linear diameter growth trend spanning more than 300 years; (ii) increased growth levels and trends, the latter being particularly pronounced for fir and beech; and (iii) an elevation-dependent change of fir and beech growth. Whereas in the past, the growth was highest at lower elevations, today’s growth is superior at higher elevations. This spatiotemporal pattern indicates significant changes in the growth and interspecific competition at the expense of spruce in mixed mountain forests. We discuss possible causes, consequences, and silvicultural implications of these distinct growth changes in mixed mountain forests.

Stem growth responses of declining mature Abiesamabilis trees after tephra deposition from Mount St. Helens

1995 ◽  
Vol 25 (9) ◽  
pp. 1493-1502 ◽  
Author(s):  
Gerardo Segura ◽  
Thomas M. Hinckley ◽  
Chadwick D. Oliver
Keyword(s):  
Radial Growth ◽  
Stem Growth ◽  
Silver Fir ◽  
Growth Responses ◽  
Stem Analysis ◽  
Cross Sectional ◽  
Breast Height ◽  
Per Se ◽  
Mount St Helens

Stem analysis of mature Abiesamabilis (Dougl.) Forbes (Pacific silver fir) trees was used to analyze patterns of radial growth in areas of southwestern Washington where this species is experiencing a severe crown decline associated with heavy tephra deposition from the 1980 eruption of Mount St. Helens. Reductions in stem growth after 1980 appeared to be related to the severity of crown damage. The largest reductions in cross-sectional area increment exceeded 50% and extended along most of the stem. An increase in stem growth in the upper crown was common among declining trees. This zone coincided with a portion of the crown that has experienced vigorous and rapid growth since 1980. The role of this recovery zone on subsequent tree recovery is discussed. Decline or recovery of trees appeared independent of crown class per se. Reductions in radial growth of declining trees tended to be more pronounced at breast height, suggesting that estimations of whole-stem growth based on breast height measurements would overestimate growth losses.

Time Series Models of Monthly Rainfall and Temperature to Detect Climate Change for Jorhat (Assam), India

2016 ◽  
Vol 18 (3) ◽  
pp. 494-507 ◽  
Keyword(s):  
Time Series ◽  
Minimum Temperature ◽  
Northeast India ◽  
Monthly Rainfall ◽  
Periodic Component ◽  
Maximum Temperature ◽  
Time Series Models ◽  
Normal Distribution Function ◽  
Dependent Component ◽  
Original Time

<div> <p>In the present study, monthly rainfall, maximum temperature and minimum time series models were developed for Jorhat (Assam) situated in northeast India using monthly rainfall, maximum temperature and minimum temperature data from the year 1965 to 2000. A trend free time series of rainfall and temperature was obtained by eliminating the trend component in the original time series, and then was used in identifying the periodic component. Fourier series analysis was used to identify periodic component. First five harmonics explained total variance of 79.4, 72.6 and 73.7% for monthly rainfall, maximum temperature and minimum temperature respectively. In the stochastic dependent component modelling, Autoregressive (AR) models of order 12 were found suitable on the basis of minimum value of AICC and BIC statistics. Portmanteau test formulated by McLeod and Li was carried out for checking the independence of stochastic dependent component which indicated that series consist of independent and identically distributed variables. Independent stochastic components were further modelled using normal distribution function.&nbsp; Nash-Sutcliffe coefficient also indicated high degree of models fitness to the observed data. Developed time series models were validated using eight years (2001-2008) data. Using the developed time series models, monthly rainfall, maximum temperature and minimum temperature were forecasted up to the year 2050. Assessment of changes in monthly rainfall, maximum temperature and minimum temperature in generated series (2009 to 2050) were predicted using linear regression which indicated no significant trend, i.e., the climate at Jorhat (Assam) in next four decades will remain more or less stable.&nbsp;</p> </div> <p>&nbsp;</p>

Time-Series Models in Marketing: Some Recent Developments

Marketing ZFP ◽  
2010 ◽  
Vol 32 (JRM 1) ◽  
pp. 24-29
Author(s):  
Marnik G. Dekimpe ◽  
Dominique M. Hanssens
Keyword(s):  
Time Series ◽  
Time Series Models ◽  
Recent Developments

A COMPARATIVE STUDY BETWEEN UNIVARIATE AND BIVARIATE TIME SERIES MODELS FOR CRUDE PALM OIL INDUSTRY IN PENINSULAR MALAYSIA

2020 ◽  
Vol 5 (1) ◽  
pp. 374
Author(s):  
Pauline Jin Wee Mah ◽  
Nur Nadhirah Nanyan
Keyword(s):  
Time Series ◽  
Palm Oil ◽  
Moving Average ◽  
Forecast Accuracy ◽  
Peninsular Malaysia ◽  
Time Series Models ◽  
Crude Palm Oil ◽  
Univariate Time Series ◽  
Import And Export ◽  
Bivariate Time Series

The main purpose of this study is to compare the performances of univariate and bivariate models on four time series variables of the crude palm oil industry in Peninsular Malaysia. The monthly data for the four variables, which are the crude palm oil production, price, import and export, were obtained from Malaysian Palm Oil Board (MPOB) and Malaysian Palm Oil Council (MPOC). In the first part of this study, univariate time series models, namely, the autoregressive integrated moving average (ARIMA), fractionally integrated autoregressive moving average (ARFIMA) and autoregressive autoregressive (ARAR) algorithm were used for modelling and forecasting purposes. Subsequently, the dependence between any two of the four variables were checked using the residuals’ sample cross correlation functions before modelling the bivariate time series. In order to model the bivariate time series and make prediction, the transfer function models were used. The forecast accuracy criteria used to evaluate the performances of the models were the mean absolute error (MAE), root mean square error (RMSE) and mean absolute percentage error (MAPE). The results of the univariate time series showed that the best model for predicting the production was ARIMA  while the ARAR algorithm were the best forecast models for predicting both the import and export of crude palm oil. However, ARIMA  appeared to be the best forecast model for price based on the MAE and MAPE values while ARFIMA  emerged the best model based on the RMSE value.  When considering bivariate time series models, the production was dependent on import while the export was dependent on either price or import. The results showed that the bivariate models had better performance compared to the univariate models for production and export of crude palm oil based on the forecast accuracy criteria used.

Modeling and Forecasting Africas GDP with Time Series Models

2018 ◽  
Vol 8 (4) ◽  
Author(s):  
Annie Uwimana ◽  
B. I. Xiuchun ◽  
ZHANG Shuguang
Keyword(s):  
Time Series ◽  
Time Series Models ◽  
Modeling And Forecasting

A Graphical Similarity Measure for Time Series Models.

1985 ◽  
Author(s):  
B. Kedem
Keyword(s):  
Time Series ◽  
Similarity Measure ◽  
Time Series Models

Time Series Models for Taiwan's CPI

2015 ◽  
Author(s):  
Lawrence Hsiao
Keyword(s):  
Time Series ◽  
Time Series Models

Comparative Analysis of Time Series Models for the Prediction of Conjunctivitis Disease

2020 ◽  
Author(s):  
Shobhit Verma ◽  
Nonita Sharma ◽  
Krishna Pal Sharma
Keyword(s):  
Time Series ◽  
Comparative Analysis ◽  
Time Series Models ◽  
Analysis Of Time Series
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