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Mycorrhizal fungi greatly enhanced the ability of plants to take up phosphorus and other nutrients those are relatively immobile and exist in low concentration in the soil solution. Fungi can be important in the uptake of other nutrients by the host plant. Mycorrhizae establish symbiotic relationships with plants and play an essential role in plant growth, disease protection, and overall soil quality. Of the seven types of mycorrhizae described in current scientific literature (arbuscular, ecto, ectendo, arbutoid, monotropoid, ericoid and orchidaceous mycorrhizae), the arbuscular and ectomycorrhizae are the most abundant and widespread. This chapter presents an overview of current knowledge of mycorrhizal interactions, processes, and potential benefits to society. The molecular basis of nutrient exchange between arbuscular mycorrhizal (AM) fungi and host plants is presented; the role of AM fungi in disease protection, alleviation of heavy metal stress and increasing grain production. Most land plants form associations with mycorrhizal fungi. Mycorrhizas are mutualistic associations between fungi and plant roots. They are described as symbiotic because the fungus receives photo synthetically derived carbon compounds and the plant has increased access to mineral nutrients and sometimes water.
This paper describes the application of artificial neural networks (ANNs) for the time series modeling of total phosphorous concentrations in the Odra River. Data from the monitoring site Police in the lower part of the Odra were used for training, validating and testing the models. Two models are proposed to prove the satisfactory forecast of phosphorus concentrations: a simpler one with a single input variable and a more complex one with 14 input variables. Both ANN models show a high ability to predict from the new data set. On the basis of sensitivity analysis the relationships between phosphorus concentrations and other water quality variables were established.
Diffused solar radiation increases ecosystem productivity. One of the explanations for this phenomenon is the fact that this type of radiation penetrates the vegetation layer more efficiently, thus changing radiation conditions under the plant canopy. The study of reed transparency under different radiation diffusion conditions makes it possible to estimate the amount of radiation energy that reaches plants living under the reed canopy. The presented radiation parameters were obtained using the SS1 probe (Delta-T Devices Ltd. UK.). The measurements were carried out in September 2014 in a reed canopy in the Rzecin peatland (52°45′N, 16°18′E, 54 m a.s.l.). Analyses showed that the transparency of the reed canopy (Tr) is directly proportional to the degree of diffusion (D*) of the radiation which reaches the plant surface and the reed Tr value is always greater at cloudy conditions than during periods of low radiation diffusion. At the same time, Tr is inversely proportional to the leaf area index (LAI). Under high diffusion of radiation the plants growing under the reed canopy gain approximately 38% radiation energy in comparison with periods characterised by low values of D*.
Partitioning sources of ecosystem and soil respiration (Reco and Rs) is important for understanding how climate change affects carbon cycling. Plant and microbial biomass analyses and daytime measurements of Reco and Rs were performed for 25 plots in an alpine meadow at elevation 4313 m on the Tibetan Plateau. Plant and microbial biomass were determined by harvesting method and the chloroform fumigation-extraction method, respectively. Respiration fluxes were measured by an automated CO2 flux system (LI-8100, LI-COR Biosciences, Lincoln, NE, USA). Soil respiration can be estimated by a linear or exponential relationship between Reco and aboveground plant biomass (AGB). Microbial respiration (Rm) can be estimated by a linear or exponential relationship between Rs and belowground plant biomass (BGB) or by a multiple relationship between Reco and AGB and BGB. Soil respiration (or Rm) is respiration flux when AGB (or BGB) is extrapolated to zero for the linear and exponential regression methods. Similarly, Rm is respiration flux when both AGB and BGB are zero for the multiple regression method. Our findings suggest that the exponential regression method to partition sources of Reco and Rs may be more appropriate compared to other methods for this alpine meadow of Tibet.
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