4 resultados para nutrients and biomass

em BORIS: Bern Open Repository and Information System - Berna - Suiça


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Growth, morphogenesis and function of roots are influenced by the concentration and form of nutrients present in soils, including low molecular mass inorganicN(IN, ammonium, nitrate) and organicN(ON, e. g. amino acids). Proteins, ON of high molecular mass, are prevalent in soils but their possible effects on roots have received little attention. Here, we investigated how externally supplied protein of a size typical of soluble soil proteins influences root development of axenically grown Arabidopsis. Addition of low to intermediate concentrations of protein (bovine serum albumen, BSA) to IN-replete growth medium increased root dry weight, root length and thickness, and root hair length. Supply of higher BSA concentrations inhibited root development. These effects were independent of total N concentrations in the growth medium. The possible involvement of phytohormones was investigated using Arabidopsis with defective auxin (tir1-1 and axr2-1) and ethylene (ein2-1) responses. That no phenotype was observed suggests a signalling pathway is operating independent of auxin and ethylene responses. This study expands the knowledge on N form-explicit responses to demonstrate that ON of high molecular mass elicits specific responses.

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Plant species richness of permanent grasslands has often been found to be significantly associated with productivity. Concentrations of nutrients in biomass can give further insight into these productivity- plant species richness relationships, e.g. by reflecting land use or soil characteristics. However, the consistency of such relationships across different regions has rarely been taken into account, which might significantly compromise our potential for generalization. We recorded plant species richness and measured above-ground biomass and concentrations of nutrients in biomass in 295 grasslands in three regions in Germany that differ in soil and climatic conditions. Structural equation modelling revealed that nutrient concentrations were mostly indirectly associated with plant species richness via biomass production. However, negative associations between the concentrations of different nutrients and biomass and plant species richness differed considerably among regions. While in two regions, more than 40% of the variation in plant species richness could be attributed to variation in biomass, K, P, and to some degree also N concentrations, in the third region only 15% of the variation could be explained in this way. Generally, highest plant species richness was recorded in grasslands where N and P were co-limiting plant growth, in contrast to N or K (co-) limitation. But again, this pattern was not recorded in the third region. While for two regions land-use intensity and especially the application of fertilizers are suggested to be the main drivers causing the observed negative associations with productivity, in the third region the little variance accounted for, low species richness and weak relationships implied that former intensive grassland management, ongoing mineralization of peat and fluctuating water levels in fen grasslands have overruled effects of current land-use intensity and productivity. Finally, we conclude that regional replication is of major importance for studies seeking general insights into productivity-diversity relationships.

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Due to highly erodible volcanic soils and a harsh climate, livestock grazing in Iceland has led to serious soil erosion on about 40% of the country's surface. Over the last 100 years, various revegetation and restoration measures were taken on large areas distributed all over Iceland in an attempt to counteract this problem. The present research aimed to develop models for estimating percent vegetation cover (VC) and aboveground biomass (AGB) based on satellite data, as this would make it possible to assess and monitor the effectiveness of restoration measures over large areas at a fairly low cost. Models were developed based on 203 vegetation cover samples and 114 aboveground biomass samples distributed over five SPOT satellite datasets. All satellite datasets were atmospherically corrected, and digital numbers were converted into ground reflectance. Then a selection of vegetation indices (VIs) was calculated, followed by simple and multiple linear regression analysis of the relations between the field data and the calculated VIs. Best results were achieved using multiple linear regression models for both %VC and AGB. The model calibration and validation results showed that R2 and RMSE values for most VIs do not vary very much. For percent VC, R2 values range between 0.789 and 0.822, leading to RMSEs ranging between 15.89% and 16.72%. For AGB, R2 values for low-biomass areas (AGB < 800 g/m2) range between 0.607 and 0.650, leading to RMSEs ranging between 126.08 g/m2 and 136.38 g/m2. The AGB model developed for all areas, including those with high biomass coverage (AGB > 800 g/m2), achieved R2 values between 0.487 and 0.510, resulting in RMSEs ranging from 234 g/m2 to 259.20 g/m2. The models predicting percent VC generally overestimate observed low percent VC and slightly underestimate observed high percent VC. The estimation models for AGB behave in a similar way, but over- and underestimation are much more pronounced. These results show that it is possible to estimate percent VC with high accuracy based on various VIs derived from SPOT satellite data. AGB of restoration areas with low-biomass values of up to 800 g/m2 can likewise be estimated with high accuracy based on various VIs derived from SPOT satellite data, whereas in the case of high biomass coverage, estimation accuracy decreases with increasing biomass values. Accordingly, percent VC can be estimated with high accuracy anywhere in Iceland, whereas AGB is much more difficult to estimate, particularly for areas with high-AGB variability.

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In the strongly seasonal, but annually very wet, parts of the tropics, low-water availability in the short dry season leads to a semi-deciduous forest, one which is also highly susceptible to nutrient loss from leaching in the long wet season. Patterns in litterfall were compared between forest with low (LEM) and high (HEM) abundances of ectomycorrhizal trees in Korup National Park, Cameroon, over 26 months in 1990–92. Leaf litter was sorted into 26 abundant species which included six ectomycorrhizal species, and of these three were the large grove-forming trees Microberlinia bisulcata, Tetraberlinia bifoliolata and Tetraberlinia moreliana. Larger-tree species shed their leaves with pronounced peaks in the dry season, whereas other species had either weaker dependence, showed several peaks per year, or were wet-season shedders. Although total annual litterfall differed little between forest types, in the HEM forest (dominated by M. bisulcata) the dry-season peak was more pronounced and earlier than that in the LEMforest. Species differed greatly in their mean leaf litterfall nutrient concentrations, with an approx. twofold range for nitrogen and phosphorus, and 2.5–3.5-fold for potassium, magnesium and calcium. In the dry season, LEM and HEM litter showed similar declines in P and N concentration, and increases in K and Mg; some species, especially M. bisculcata, showed strong dry-wet season differences. The concentration of P (but not N) was higher in the leaf litter of ectomycorrhizal than nonectomycorrhizal species. Retranslocation of N and P was lower among the ectomycorrhizal than nonectomycorrhizal species by approx. twofold. It is suggested that, within ectomycorrhizal groves on this soil low in P, a fast decomposition rate with minimal loss of mineralized P is possible due to the relatively high litter P not limiting the cycle at this stage, combined with an efficient recapture of released P by the surface organic layer of ectomycorrhizas and fine roots. This points to a feedback between two essential controlling steps (retranslocation and mineralization) in a tropical rain forest ecosystem dominated by ectomycorrhizal trees.