The effect of dairy, piggery and wool scour effluents on willow growth and the soil characteristics : a thesis presented in partial fulfillment of the requirements for the degree of Master of Applied Science in Soil Science at Massey University

Restrictions on the disposal of agricultural effluents to the waterway means that alternative land based outlets are required in New Zealand. Willow, as a short forest rotation, represents a significant land use that could produce a high dry matter and benefit from the application of effluent irrigation. However, there has been little information on the effect of effluent irrigation on the growth of willow and the removal of nutrients. In order to assess the effects of dairy, piggery and wool scour effluents on willow growth, a greenhouse experiment was established using the Manawatu sandy fine loam soil. A complete nutrient solution and nutrient - free tap water treatments were also included in addition to the effluent treatments. The design of the experiment was a 5 x 2 factorial combination of treatments with four replications in randomized blocks. Two factors (effluents and irrigation rates) each with 5 levels were examined, the levels of irrigation were 12.5 mm, 25 mm, 37.5 mm, 50 mm and 62.5 mm per fortnight. The plant growth, production and macro-nutrients accumulation, and the soil pH, electrical conductivity, and total N, P and cations were monitored Irrigation with effluents affected the growth of willow cutting. The piggery and dairy effluent irrigation increased the willow growth and nutrient accumulation followed the increase in DM yield. The piggery and dairy irrigation accounted for 32% and 18% increase in total DM yield over tap water; while the wool scour effluent resulted in 17% decrease in comparison with tap water. Irrigation with dairy, piggery and wool scour effluents onto the Manawatu fine sandy loam soil, caused a significant increase in pH and EC. The significant change in pH and EC was attributed to the soluble salts in these effluents, especially K in the wool scour effluent. The recovery of N from these effluents was very small and was less than that of P and K in soil. Chemical analysis of willow, treated with dairy, piggery and wool scour effluents up to 8 weeks, showed a relatively high concentration of N, P and K in leaf, and had a very high K and a very low Mg concentration in leaf with wool scour effluent irrigation. However, the efficiency of the N, P and K nutrient accumulated by willow was inversely related to the concentration of these effluents and the DM yield of willow cutting was positively related to the irrigation rates. It was evident that willow cutting was too young to require a large quantity of nutrients at the early growth stage and there was a risk of nutrient loss with increasing irrigation rate. The application of wool scour effluent caused a very high pH and EC, and the willow cutting growth decreased at > 37.5 mm/fortnight irrigation rates. The reasons for the detrimental effects of wool scour effluent on soil properties and willow growth need to be investigated further. The results suggested that it is possible to enhance the willow growth and adjust the soil fertility by application of dairy and piggery effluents irrigation

The Econometric Analysis of Microscopic Simulation Models

This paper studies how to compare different microscopic simulation (MS) models and how to compare a MS model with real world. The parameters of interest are classified and characterized, various econometric methods are applied for the comparison. We illustrate the methodolgy on testing of the equality of parameters, such as mean, autocorrelation coefficient, for both the case of comparing two different MS models and of comparing a MS model with real worldMS models, econometrics

Long Memory, Heterogeneity and Trend Chasing

Long-range dependence in volatility is one of the most prominent examples of applications in financial market research involving universal power laws. Its characterization has recently spurred attempts at theoretical explanation of the underlying mechanism. This paper contributes to this recent development by analyzing a simple market fraction asset pricing model with two types of traders fundamentalists who trade on the price deviation from estimated fundamental value and trend followers who follow a trend which is updated through a geometric learning process. Our analysis shows that the heterogeneity, trend chasing through learning, and the interplay of noisy processes and a stable deterministic equilibrium can be the source of power-law distributed fluctuations. Statistical analysis based on Monte Carlo simulations are conducted to characterize the long memory. Realistic estimates of the power-law decay indices and the (FI)GARCH parameters are found.asset pricing; fundamentalists and trend followers; market fraction; stability; learning; long memory

Heterogeneity, Profitability and Autocorrelations

This paper contributes to the development of recent literature on the explanation power and calibration issue of heterogeneous asset pricing models by presenting a simple stochastic market fraction asset pricing model of two types of traders (fundamentalists and trend followers) under a market maker scenario. It seeks to explain aspects of financial market behaviour (such as market dominance, under and over-reaction, profitability and survivability) and to characterize various statistical properties (including autocorrelation structure) of the stochastic model by using the the dynamics of the underlying deterministic system, traders? behaviour and market fractions. Statistical analysis based on Monte Carlo simulations shows that the long-run behaviour and convergence of the market prices, long (short)-run profitability of the fundamental (trend following) trading strategy, survivability of chartists, and various under and over-reaction autocorrelation patterns of returns can be characterized by the stability and bifurcations of the underlying deterministic system. Our analysis underpins mechanism on various market behaviour (such as under/over-reactions), market dominance and stylized facts in high frequency financial markets.asset pricing; heterogeneous beliefs; market fraction; stability; bifurcation; market behaviour; profitability; survivability; autocorrelation

Co-occurrence network analysis of biogas reactor microbiomes based on metagenomics sequencing data

Metagenome sequencing makes it possible to capture microbial communities in their diversity, to investigate population structures and evolutionary relationships, and to predict metabolic functions and interactions within the microbial community and with the environment. Metagenomics thus, significantly expands the research scope of microbiology. Compared with 16S sequencing, metagenome sequencing can get more information of species identification, and in-depth research on gene and function. Metagenome-assembled genomes (MAGs) retrieved from metagenomics data of 20 AD biogas reactors and the respective Illumina sequencing reads were used to create an abundance table and conduct co-occurrence network analysis. A feasible method was designed for making OTU table and network analysis of metagenomics data and some potential clusters were found may connected to the food chain in microbial community