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Science of the Total Environment 2012-Dec

Seasonal variation of the ¹³⁷Cs level and its relationship with potassium and carbon levels in conifer needles.

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Aino Rantavaara
Virve Vetikko
Hannu Raitio
Lasse Aro

Kľúčové slová

Abstrakt

Seasonal variations in foliar ¹³⁷Cs levels were examined in Norway spruce (Picea abies (L.) Karst.), and Scots pine (Pinus sylvestris L.) in western Finland. Our aim was to test the occurrence of seasonal variation in contents and concentrations of ¹³⁷Cs, potassium and carbon in needles. The study focused on analysing levels of total ¹³⁷Cs in the three youngest needle age classes and comparing them to the levels of potassium and carbon. Spruce and pine needles were collected from 50- and 65-year-old stands on 18 sampling occasions between April 1996 and February 1997. Phases of intensive growth, needle elongation and dormancy were apparent in the time series for the needle contents and activity concentration of ¹³⁷Cs, both of which varied according to needle age class and tree species. The sequence of phases with a temporal fluctuation of needle contents, activity concentrations of ¹³⁷Cs and concentrations of K and carbon varied occasionally, and the efficiency of their translocation revealed some differences in the dynamics of ¹³⁷Cs, K and carbon in spruce and pine. The data clearly showed that the needles' K contents responded strongly to changes in K demand from other parts of the tree due to seasonal changes and that these responses were stronger than the associated retranslocations of ¹³⁷Cs, particularly in Scots pine. During intensive growth, K was less mobile than ¹³⁷Cs in the needles. The uptake of ¹³⁷Cs by current-year needles is simultaneously affected by uptake from the soil via the roots and retranslocation from other internal sources, and both of these processes affect the observed transfer rates during the growth period. Our results provided information on the transfer rates and revealed differentiation of root uptake and retranslocation of ¹³⁷Cs in needles. The study can support dynamic modelling of atmospheric ¹³⁷Cs contamination in forests.

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