Seasonal ionic fluctuations and annual growth rates in stands of Pinus silvestris L. and Picea abies Karst. (L.)

1974 ◽  
Vol 41 (2) ◽  
pp. 343-350 ◽  
Author(s):  
Lars Christersson
Keyword(s):  
Picea Abies ◽  
Growth Rates ◽  
Annual Growth ◽  
Pinus Silvestris

Spurious Persistence and Unit Roots due to Seasonal Differencing: The Case of Inflation Rates / Künstliche Persistenz und Einheitswurzeln infolge saisonaler Differenzen: Das Beispiel Inflationsraten

2005 ◽  
Vol 225 (4) ◽  
Author(s):  
Uwe Hassler ◽  
Matei Demetrescu
Keyword(s):  
Growth Rates ◽  
Unit Root ◽  
Unit Roots ◽  
Annual Growth ◽  
Seasonal Growth ◽  
Seasonal Differences ◽  
Inflation Rates ◽  
European Economies ◽  
Seasonal Data

SummaryStudying annual growth rates (seasonal differences) in case of seasonal data produces much more persistence, autocorrelation and stronger evidence in favour of a unit root than analyzing seasonal growth rates (ordinary differences). First, this statement is quantified theoretically. Second, it is supported experimentally with simulations, and, finally, it is empirically illustrated with quarterly GDP deflators from 7 European economies.

Automatic Detection of Annual Growth Units on Picea abies Logs Using Optical and X-Ray Techniques

2005 ◽  
Vol 24 (1) ◽  
pp. 29-43 ◽  
Author(s):  
Fleur Longuetaud ◽  
Laurent Saint-André ◽  
Jean-Michel Leban
Keyword(s):  
Picea Abies ◽  
Automatic Detection ◽  
Annual Growth ◽  
X Ray

Early Life History of Fishes in the San Francisco Estuary and Watershed

2004 ◽  
Keyword(s):  
Growth Rate ◽  
San Francisco ◽  
Striped Bass ◽  
Growth Rates ◽  
Early Life History ◽  
San Francisco Estuary ◽  
Annual Growth ◽  
Factors Affecting ◽  
Juvenile Abundance ◽  
History Of

<em>Abstract.</em>—We investigated factors affecting growth of larval striped bass <em>Morone saxatilis </em>in the San Francisco Estuary from 1984 to 1993. We estimated ages and growth rates of larval striped bass from daily otolith increments. Mean annual growth rates of 6–14 mm standard length striped bass varied from 0.13 to 0.27mm/d, the lowest rate occurring in 1989 and the highest in 1992. The 1989 growth rate was significantly lower than all other years, and growth rates for 1992 and 1993 were significantly higher than all other years, but did not differ from one another. Differences in annual growth rates apparently were due mainly to differences in mean annual prey densities because growth rate increased as prey density increased. Compared to both laboratory measured growth rates and growth rates of field-caught Chesapeake Bay larvae, growth rates from the San Francisco Estuary appeared to be high for the food available, indicating that larvae can grow at relatively high rates even at low prey densities. Correlation analyses did not support density-dependent control of growth rates. Growth rate was not significantly related to mean annual conductivity, water temperature, mortality rates, or the juvenile abundance index, but was significantly and positively correlated with densities of 1-mm length-groups of 9–14-mm striped bass.

scholarly journals Can We Measure a COVID-19-Related Slowdown in Atmospheric CO2 Growth? Sensitivity of Total Carbon Column Observations

2020 ◽  
Vol 12 (15) ◽  
pp. 2387 ◽  
Author(s):  
Ralf Sussmann ◽  
Markus Rettinger
Keyword(s):  
Growth Rate ◽  
Growth Rates ◽  
Measurement Precision ◽  
Annual Growth ◽  
Total Carbon ◽  
Mathematical Framework ◽  
Single Measurement ◽  
Synoptic Variability ◽  
Concentration Changes ◽  
The Impact

The COVID-19 pandemic is causing projected annual CO2 emission reductions up to −8% for 2020. This approximately matches the reductions required year on year to fulfill the Paris agreement. We pursue the question whether related atmospheric concentration changes may be detected by the Total Carbon Column Observing Network (TCCON), and brought into agreement with bottom-up emission-reduction estimates. We present a mathematical framework to derive annual growth rates from observed column-averaged carbon dioxide (XCO2) including uncertainties. The min–max range of TCCON growth rates for 2012–2019 was [2.00, 3.27] ppm/yr with a largest one-year increase of 1.07 ppm/yr for 2015/16 caused by El Niño. Uncertainties are 0.38 [0.28, 0.44] ppm/yr limited by synoptic variability, including a 0.05 ppm/yr contribution from single-measurement precision. TCCON growth rates are linked to a UK Met Office forecast of a COVID-19-related reduction of −0.32 ppm yr−2 in 2020 for Mauna Loa. The separation of TCCON-measured growth rates vs. the reference forecast (without COVID-19) is discussed in terms of detection delay. A 0.6 [0.4, 0.7]-yr delay is caused by the impact of synoptic variability on XCO2, including a ≈1-month contribution from single-measurement precision. A hindrance for the detection of the COVID-19-related growth rate reduction in 2020 is the ±0.57 ppm/yr uncertainty for the forecasted reference case (without COVID-19). Only assuming the ongoing growth rate reductions increasing year-on-year by −0.32 ppm yr−2 would allow a discrimination of TCCON measurements vs. the unperturbed forecast and its uncertainty—with a 2.4 [2.2, 2.5]-yr delay. Using no forecast but the max–min range of the TCCON-observed growth rates for discrimination only leads to a factor ≈2 longer delay. Therefore, the forecast uncertainties for annual growth rates must be reduced. This requires improved terrestrial ecosystem models and ocean observations to better quantify the land and ocean sinks dominating interannual variability.

Annual growth rates in newly established populations of the butterfly Pararge aegeria

1996 ◽  
Vol 21 (4) ◽  
pp. 947-952 ◽  
Author(s):  
E. POLLARD ◽  
P. ROTHERY ◽  
T.J. YATES
Keyword(s):  
Growth Rates ◽  
Annual Growth ◽  
Pararge Aegeria

The trade-off between vegetation restoration and soil & water conservation in Loess Plateau, China

2020 ◽  
Author(s):  
Haiqiang Gao ◽  
Shuguang Liu
Keyword(s):  
Soil Water ◽  
Loess Plateau ◽  
Growth Rates ◽  
Water Conservation ◽  
Growing Season ◽  
Vegetation Restoration ◽  
Annual Growth ◽  
Area Index ◽  
Water Condition ◽  
Soil And Water

&lt;p&gt;China has implemented an ambitious ecological project Grain for Green Project (GGP) on the Loess Plateau (LP) at the end of last century. The GGP was to increase vegetation coverage, reduce soil and water erosion and store Carbon by converting croplands on steep slopes barren hills and wasteland to forests. Assessing the ecological effects of GGP correctly could improve vegetation restoration activities worldwide. In this study, two major ecological indicators (vegetation restoration and soil &amp; water conservation) were used to evaluate the ecological benefits of GGP from 1982 to 2017. Our results show that the vegetation growth for most pixels of LP region have significantly increased at 21 century, annual growth rates of fraction of absorbed photosynthetically active Radiation (FPAR) in spring, summer, autumn and active growing season are 1.39, 4.49, 2.14 and 1.47, respectively. For leaf area index (LAI), these growth rates are 6.01, 20.06, 8.11 and 6.90, respectively. And for normalized difference vegetation index (NDVI), growth rates are 6.30, 25.46, 7.99 and 20.43, respectively. While the soil and water condition has differently changed, annual growth rates of soil moisture (SM) are 4.46, 2.79 and 2.30 for summer, active growing season and whole year, respectively. The coordinated responses of vegetation and soil &amp; water condition suggest that the interaction between organisms (vegetation, animal and human) and environment (soil, water and so on) in the process of vegetation restoration should be further recognized to evaluate the benefits of ecological engineering more comprehensively.&lt;/p&gt;

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