2019
DOI: 10.1016/j.dendro.2019.02.007
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Different climate response of three tree ring proxies of Pinus sylvestris from the Eastern Carpathians, Romania

Abstract: The aim of this study was to compare the climatic responses of three tree rings proxies: tree ring width (TRW), maximum latewood density (MXD), and blue intensity (BI). For this study, 20 cores of Pinus sylvestris covering the period 1886-2015 were extracted from living non-damaged trees from the Eastern Carpathian Mountains (Romania). Each chronology was compared to monthly and daily climate data. All tree ring proxies had a stronger correlation with the daily climate data compared to monthly data. The highes… Show more

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Cited by 30 publications
(22 citation statements)
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“…Kaczka et al 2017 [44] indicates that the highest temperature relevance for tree growth occurs between Jun 9th and Jul 19th while Pritzkow et al 2014 [76] determines it between Jul 7th and Jul 29th, which in both cases highlights the relevance of summer temperatures on tree growth, where in Northern Poland we define the early spring period as thermally relevant. Seo et al 2008 [77], Kaczka et al 2017 [44], Nagavciuc et al 2019 [78] reported that the use of daily climatic data was more reliable as there was a higher correlation with ring-widths. Moreover, they found that the flexible time interval based upon days rather than months adapted to the vegetation period of plants better.…”
Section: Discussionmentioning
confidence: 99%
“…Kaczka et al 2017 [44] indicates that the highest temperature relevance for tree growth occurs between Jun 9th and Jul 19th while Pritzkow et al 2014 [76] determines it between Jul 7th and Jul 29th, which in both cases highlights the relevance of summer temperatures on tree growth, where in Northern Poland we define the early spring period as thermally relevant. Seo et al 2008 [77], Kaczka et al 2017 [44], Nagavciuc et al 2019 [78] reported that the use of daily climatic data was more reliable as there was a higher correlation with ring-widths. Moreover, they found that the flexible time interval based upon days rather than months adapted to the vegetation period of plants better.…”
Section: Discussionmentioning
confidence: 99%
“…In the previous section, we used CCA to identify the large-scale drivers of April PP, but CCA does not consider if the relationship between two variables is stationary in time or not. To overcome the problem of non-stationarity and to test if the identified coupled mode of variability between April PP and April Z500 is stable over time, we employed a methodology used for the monthly to seasonal prediction of the mean runoff of the Elbe River 55,56 and in dendroclimatological studies 57,58 . A detailed description of the methodology is given in Ionita (2017) 59 .…”
Section: Stability Mapsmentioning
confidence: 99%
“…The 80% and 85% levels are used as "buffer zones" and only grid cells where the correlation is above 90% significance level, are retained for further analysis. The methodology has been already tested for the prediction of the spring streamflow condition for the Elbe river 16 , as well as for the prediction of the September Arctic Sea ice 19 and in dendroclimatological studies 20,21 . In this respect, this study describes the performance of a statistical model in predicting low flow situations for the major watersheds in Germany: Rhine and Elbe (Fig.…”
mentioning
confidence: 99%