Computational models are useful to estimate agricultural greenhouse gas emissions at regional scales. However, empirically based parameter values are required for the models to accurately represent carbon (C) and nitrogen (N) mineralization rates of different organic amendments in more and less humid regions or during wet and dry periods of the growing season. A controlled environment study was conducted to assess the rates of C and N mineralization in differently processed sewage sludge (biosolids) in wet and dry soil. Parameter values were estimated for use in modelling the degradation of three types of biosolids. A loam soil with either 49% water-filled pore space (WFPS) or 29% WFPS was amended with mesophilic anaerobically digested (digested), alkaline-stabilized, or composted biosolids. Headspace samples were collected and analysed for carbon dioxide (CO2) and nitrous oxide (N2O), and soil samples for nitrate () and ammonium (). Four different first-order models were fitted to the cumulative CO2–C and N2O–N data (R2 > 0.98), and soil (R2 > 0.65) and (R2 > 0.93) concentrations. CO2–C data indicated that C mineralization was higher in soil with 49% WFPS than in soils with 29% WFPS. Seventy-nine percent of the C compounds in digested biosolids degraded in soil with 49% WFPS, compared with 52% for alkaline-stabilized biosolids and 8% for composted biosolids. The fitted coefficient values were similar for all of the four first-order models used in this study and provide useful information for parameterizing more sophisticated mechanistic models of the degradation of biosolids in soil. 相似文献
Uses of game resources are under constant debate. One such debate focuses on hunting tourism and its contributions to rural economics. To prioritize future investment and inform policy decisions, it is necessary to identify the full economic consequences of the operation of hunting tourism companies in rural areas. However, the true economic significance of these typically small-scale companies is not apparent when examined on an industrial scale. These companies may nevertheless serve as a sustainable solution to local-scale rural challenges. In this article, the regional economic significance of hunting tourism is estimated for the East Lapland sub-region of northern Finland through the use of Computable General Equilibrium simulation models. Although these models are known to effectively evaluate short- and long-term regional economic effects of industries such as tourism, they have not previously been applied to evaluate hunting tourism. 相似文献
In the years 2002–2005, special trials concerning the level of infection of pea varieties by downy mildew were performed in Poland. In these trials, the large number of varieties were tested in many locations (environments), separately on reach and light soils. Obtained trial data are unique because of the large scale of the performed investigations and also for the fact that all the observations were made by the same observer. In a paper, two methods of statistical analysis of such (ordered) data are compared.
Several models have been proposed for the statistical interpretation of ordinal data. One of the most popular is the cumulative-type fixed logistic model. In the present work, using two field pea data sets, we considered whether adding random effects to the simple logistic model can improve inference. It was investigated whether there is any difference between the decisions concerning varieties resulting from the simple logistic model and the proposed mixed logistic model. The two models were also compared in terms of goodness of fit. According to two applied goodness-of-fit statistics, the mixed model performed better in all the cases. Statistical analysis (what is important for practical agriculture) enabled identification of the most resistant and the most susceptible variety from the analyzed set of cultivars. 相似文献
Simulating the influence of intensive management and annual weather fluctuations on tree growth requires a shorter time step than currently employed by most regional growth models. High-quality data sets are available for several plantation species in the Pacific Northwest region of the United States, but the growth periods ranged from 2 to 12 years in length. Measurement periods of varying length complicate efforts to fit growth models because observed growth rates must be interpolated to a common length growth period or those growth periods longer or shorter than the desired model time step must be discarded. A variation of the iterative technique suggested by Cao [Cao, Q.V., 2000. Prediction of annual diameter growth and survival for individual trees from periodic measurements. Forest Sci. 46, 127–131] was applied to estimate annualized diameter and height growth equations for pure plantations of Douglas-fir, western hemlock, and red alder. Using this technique, fits were significantly improved for all three species by embedding a multi-level nonlinear mixed-effects framework (likelihood ratio test: p < 0.0001). The final models were consistent with expected biological behavior of diameter and height growth over tree, stand, and site variables. The random effects showed some correlation with key physiographic variables such as slope and aspect for Douglas-fir and red alder, but these relationships were not observed for western hemlock. Further, the random effects were more correlated with physiographic variables than actual climate or soils information. Long-term simulations (12–16 years) on an independent dataset using these annualized equations showed that the multi-level mixed effects models were more accurate and precise than those fitted without random effects as mean square error (MSE) was reduced by 13 and 21% for diameter and height growth prediction, respectively. The level of prediction error was also smaller than an existing similar growth model with a longer time step (ORGANON v8) as the annualized equations reduced MSE by 17 and 38% for diameter and height growth prediction, respectively. These models will prove to be quite useful for understanding the interaction of weather and silviculture in the Pacific Northwest and refining the precision of future growth model projections. 相似文献