Effects of previous fertilization with N (in total, 600 kg urea-N·ha1 applied in 1976, 1980, and 1985) were studied after final felling in 1992 of a Norway spruce (Picea abies (L.) Karst.) stand in southern Sweden. The logging residues were removed from the site. In the clearcut, soil water at 50 cm depth was sampled 16 times with ceramic suction samplers (P80) in experimental plots during 19921995. The biomass and N content of the field layer was measured on seven occasions. The N storage of the field layer was significantly (p < 0.05) higher in the urea treatment than in the control. Significant interactions between treatment and time were found in soil water for nitrate-N and total N but not for ammonium-N, organic N, and pH. During the first year after final felling, nitrate-N tended to increase faster in the urea treatment than in the control. After a period with similar concentrations in both treatments, nitrate-N in the urea treatment declined while at the same time, a peak was observed in the control showing four to seven times higher concentrations than in the urea treatment. At the end of the study, the concentrations still appeared to be highest in the control. Thus, the study demonstrated the importance of using a sufficiently long study period when investigating environmental effects. Total leaching of nitrate-N from the urea treatment was roughly 40% ([Formula: see text]20 kg·ha1) less than that from the control. The difference in leaching may be partly explained by the greater accumulation of N in the field-layer vegetation in the urea treatment.
Clay minerals and K feldspars were evaluated as sources of K in a Norway spruce stand (Picea abies (L.) Karst.) from the Skogaby experimental forest in southwest Sweden. The soil, developed in a Quaternary glacial till, has only 3-5% clay, and more than 95% of its K resides in feldspars. Ratios of K/Rb were assessed in interlayers of 2:1 clay minerals (extracted with hot (100°C) 2 M HCl), biomass and the forest floor. These compartments had similarly low K/Rb ratios, whereas K feldspars were significantly poorer in Rb. A fractionation model indicated preferential retention of Rb in the biomass and forest floor, due to stronger adsorption of Rb than K in the humus, as well as preferential uptake of K from the exchange complex in the mineral soil. Preferential uptake of K may result from weaker adsorption of K by the cation exchanger, or preference for dissolved K over Rb by the roots. A quantitative mineralogical analysis revealed that loss from micas may account for half of the Holocene loss of K from the soil, which was approximately 22 Mg ha -1 . Exceptionally low K/Rb ratios in HCl extracts of the upper 60 cm of the profile indicated extensive loss of K from mica in the parent material and re-fixation of K and Rb at lower ratios. The results indicate that fixation in and release from clay minerals may be prominent in the cycling of K, even in a soil that is poor in clay minerals.
Liming can counteract acidification in forest soils, but the effects on soil C and N pools and fluxes over long periods are less well understood. Replicated plots in an acidic and N-rich 40-year-old Norway spruce (Picea abies) forest in SW Sweden (Hasslöv) were treated with 0, 3.45 and 8.75 Mg ha−1 of dolomitic lime (D0, D2 and D3) in 1984. Between 1984 and 2016, soil organic C to 30 cm depth increased by 28 Mg ha−1 (30% increase) in D0 and decreased by 9 Mg ha−1 (9.4% decrease) in D3. The change in D2 was not significant (+ 2 Mg ha−1). Soil N pools changed proportionally to those in soil C pools. The C and N changes occurred almost exclusively in the top organic layer. Non-burrowing earthworms responded positively to liming and stimulated heterotrophic respiration in this layer in both D2 and D3. Burrowing earthworms in D3 further accelerated C and N turnover and loss of soil. The high soil C and N loss at our relatively N-rich site differs from studies of N-poor sites showing no C and N loss. Earthworms need both high pH and N-rich food to reach high abundance and biomass. This can explain why liming of N-rich soils often results in decreasing C and N pools, whereas liming of N-poor soils with few earthworms will not show any change in soil C and N. Extractable nitrate N was always higher in D3 than in D2 and D0. After 6 years (1990), potential nitrification was much higher in D3 (197 kg N ha−1) than in D0 (36 kg N ha−1), but this difference decreased during the following years, when also the unlimed organic layers showed high nitrification potential. Our experiment finds that high-dose liming of acidic N-rich forest soils produces an initial pulse of soil heterotrophic respiration and increases in earthworm biomass, which together cause long-term declines in soil C and N pools.
The process of interception was studied in 25-year-old dense stands of Norway spruce in South Sweden. The throughfall was measured intensively during one month and extensively during four growing seasons using water captured by large roofs and with randomly distributed funnel gauges. It was found that about 45% of the precipitation was lost as interception loss from this dense forest canopy. However, many sources of potential error, particularly in measurement of precipitation and throughfall, may be involved in quantifying the interception loss. The data set was used to test the interception part of a hydrological model, SOIL. The model uses a simple threshold formulation to calculate the accumulation of intercepted water in a single storage variable. The model was able to estimate fairly well the long-term cumulative interception loss from the forest canopy However, similarly to many other models, SOIL showed a pattern of overestimation of the interception loss during events with small precipitation and underestimation during events with large precipitation. It was concluded that the storage capacity was of major importance in modelling of long-term interception loss. Tree canopy water storage capacity on a leaf area basis was estimated to 0.7 mm which was three times larger than that obtained from a precipitation/throughfall graph.
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