Research on Multilevel Models of Risks Analysis for Striped Stem Borer, Chilo Suppressalis
|Course||Agricultural Entomology and Pest Control|
|Keywords||rice pest insects Multilevel Model Hierarchical Linear Model forecasting Chilo suppressalis Regression analysis database analysis of variance|
This research is subsidized by National Natural Science Fund, "Research on Multilevel Models of Risks Analysis for Rice Insect Pests" (No.30370914) . This research analyzed and distinguished the key factors that influence the occurrence of striped stem borer, Chilo suppressalis. Applying the Hierarchical Linear Modeling (HLM) statistical technology, a two-level HLM model of the outbreaking of the striped stem borer over a large area was established. The mode was used to explain the key factors which influence the occurrence of Chilo suppressalis and probe into the influence of each ecosystem level upon the occurrence of Chilo suppressalis from the point of view of the Agricultural Ecosystem. The main results of this research are as follow:1. Establishment of information management system for rice insect pests and meteorological factors(1) Establishment of database for rice insect pests. The data of rice insect pests are come from 34 countries of Zhejiang province during the 20 years from 1981 to 2000 in this research. We sort out the data and put data into the computer. Microsoft Access was used to develop database management system for rice insect pests.(2) Establishment of database for meteorological, geographic, ecological factors. The data of meteorological factors are come from weather bureau of Zhejiang Province during the 20 years from 1981 to 2000 in this research. We tidy the data and put them into the computer. The database included the temperature-rainfall coefficient, the hygrothermal coefficient, maximum temperature, minimum temperature, average temperature, rain day, humidity, sunlight time, rainfall and other ecological factors.(3) We build the information management system for management and inquire of pest and meteorological data. The system can help us to get data from database convenient for the modeling.2. Study on the two-level hierarchical linear modeling for Chilo suppressalisConsidering the hierarchical structure of agricultural ecological system and applying the HLM statistical technology, a two-level HLM model for Chilo suppressalis was built. In the first level, 4 climatic factors and one pest factor was introduced into the model. They are minimum temperature in the late April, humidity in late April, rainfall in the early May, temperature-rainfall coefficient in the middle May and the occurrence degree of last-season rice. The level-1 regression model included 5 key factors which have significantly influence on the occurrence of Chilo suppressalis, such as minimum temperature in the late April (P=0.043 ) , humidity in late April (P=0.026) , rainfall in the late May (P=0.011) , temperature-rainfall coefficient in the middleMay (.P=0.007) , the occurrence degree of last-season rice (jP=0.008) .In the second level, three factors, the level of chemical fertilizer, percentage of hills cover, and percentage of forest land was introduced into the model. Combining the influence of the level-1 key factors, the level-2 key factors have significantly influence (/K0.01) on the occurrence of Chilo suppressalis of early-season rice in the final two-level linear model.Based on the hierarchical linear model, author carried out the analysis of the relationship between the occurrence of Chilo suppressalis and ecological, meteorological and geographic factors, and made clear several points as below:First, the results indicate that the most important factors that influence the occurrence of striped stem borer are still from the individual meteorological factors, which take about 56% of the total variance. But the inter-regional level factors can not be ignored, which take about 44% of the total variance.Second, between the intra-regional key factors (the level-1 key factors), the number of pest sources is the most significant, and the temperature-rainfall coefficient in middle May is the most significant in meteorological factors.Finally, between the inter-regional key factors (the level-2 key factors ) , the area percentage of hills land is likely most significant (the frequency is 3/6) , and the other factor is the percentage of forest land (the frequency is 2/6) , and the level of chemical fertilizer (the frequency is 2/6) . The result indicated that the regional difference is mainly come from geographic factors.