Carbon Profile of the Managed Forest Sector in Canada in the 20th Century: Sink or Source?

2014 ◽  
Vol 48 (16) ◽  
pp. 9859-9866 ◽  
Author(s):  
Jiaxin Chen ◽  
Stephen J. Colombo ◽  
Michael T. Ter-Mikaelian ◽  
Linda S. Heath

2017 ◽  
Vol 47 (8) ◽  
pp. 1082-1094 ◽  
Author(s):  
J.M. Metsaranta ◽  
C.H. Shaw ◽  
W.A. Kurz ◽  
C. Boisvenue ◽  
S. Morken

Canada’s National Forest Carbon Monitoring Accounting and Reporting System (NFCMARS) quantifies the carbon (C) dynamics and greenhouse gas (GHG) emissions and removals of Canada’s managed forest to fulfill reporting obligations under international climate conventions. Countries are also requested to assess the uncertainty associated with these estimates, which we report here. We used Monte Carlo simulation to quantify uncertainty of carbon stock and flux estimates from the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3), the core ecosystem model of the NFCMARS. We evaluated the impacts of model algorithms, parameters, and the input data used to describe forest characteristics and disturbance rates. Under our assumptions, 95% confidence interval widths averaged 16.2 Pg C (+8.3 and –7.9 Pg C, or ±15%) for total ecosystem C stock and 32.2 Tg C·year−1 (+16.6 and –15.6 Tg C·year−1) for net biome production relative to an overall simulation median of –0.8 Tg C·year−1 from 1990 to 2014. The largest sources of uncertainty were related to factors determining biomass increment and the parameters used to model soil and dead organic matter C dynamics. Opportunities to reduce uncertainty and associated research challenges were identified.







2016 ◽  
Vol 224 (4) ◽  
pp. 240-246 ◽  
Author(s):  
Mélanie Bédard ◽  
Line Laplante ◽  
Julien Mercier

Abstract. Dyslexia is a phenomenon for which the brain correlates have been studied since the beginning of the 20th century. Simultaneously, the field of education has also been studying dyslexia and its remediation, mainly through behavioral data. The last two decades have seen a growing interest in integrating neuroscience and education. This article provides a quick overview of pertinent scientific literature involving neurophysiological data on functional brain differences in dyslexia and discusses their very limited influence on the development of reading remediation for dyslexic individuals. Nevertheless, it appears that if certain conditions are met – related to the key elements of educational neuroscience and to the nature of the research questions – conceivable benefits can be expected from the integration of neurophysiological data with educational research. When neurophysiological data can be employed to overcome the limits of using behavioral data alone, researchers can both unravel phenomenon otherwise impossible to document and raise new questions.





1994 ◽  
Vol 39 (7) ◽  
pp. 764-765
Author(s):  
William E. Deuser ◽  
Craig A. Anderson
Keyword(s):  


1994 ◽  
Vol 39 (1) ◽  
pp. 9-11 ◽  
Author(s):  
Harry C. Triandis


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