1. Growth-limiting factors and climate response variability in Norway spruce (Picea abies L.) along an elevation and precipitation gradients in SloveniaJernej Jevšenak, Ivan Tychkov, Jožica Gričar, Tom Levanič, Jan Tumajer, Peter Prislan, Domen Arnič, Margarita Popkova, Vladimir V. Shishov, 2020, original scientific article Abstract: Norway spruce (Picea abies L.) is among the most sensitive coniferous species to ongoing climate change. However, previous studies on its growth response to increasing temperatures have yielded contrasting results (from stimulation to suppression), suggesting highly site-specific responses. Here, we present the first study that applies two independent approaches, i.e. the nonlinear, process-based Vaganov-Shashkin (VS) model and linear daily response functions. Data were collected at twelve sites in Slovenia differing in climate regimes and ranging elevation between 170 and 1300 m a.s.l. VS model results revealed that drier Norway spruce sites at lower elevations are mostly moisture limited, while moist high-elevation sites are generally more temperature limited. Daily response functions match well the pattern of growth-limiting factors from the VS model and further explain the effect of climate on radial growth: prevailing growth-limiting factors correspond to the climate variable with higher correlations. Radial growth correlates negatively with rising summer temperature and positively with higher spring precipitation. The opposite response was observed for the wettest site at the highest elevation, which positively reacts to increased summer temperature and will most likely benefit from a warming climate. For all other sites, the future radial growth of Norway spruce largely depends on the balance between spring precipitation and summer temperature. Keywords: Vaganov-Shashkin model, climate-growth correlations, tree rings, process-based modelling, dendroTools, dendroclimatology Published in DiRROS: 21.10.2020; Views: 1380; Downloads: 1122
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2. New features in the dendroTools R package : bootstrapped and partial correlation coefficients for monthly and daily climate dataJernej Jevšenak, 2020, original scientific article Abstract: Climate-growth relationships are usually analysed using monthly climate data. The dendroTools R package also provides methodological approaches that enable climate-growth analysis for daily climate data. Such analysis reveals more complete climate signal patterns. In this article, new functions of the dendroTools R package are presented. Partial correlation coefficients are now implemented and can be used to calculate the strength of a linear relationship between two variables, while controlling for a third variable. Bootstrapped correlations can then be used to provide insights into the confidence intervals of statistical estimates. The calculation of partial and bootstrapped correlations is available for daily and monthly data. Finally, data transformation, S3 generic plotting and summary functions are also presented here. Keywords: dendroTools, daily climate data, partial correlations, bootstrap, dendroclimatology Published in DiRROS: 24.09.2020; Views: 1411; Downloads: 672
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