Method for forecasting forest pest occurrence degree

Abstract

The invention provides a method for forecasting forest pest occurrence degree which uses occurrence index number to measure occurrence of forest pest, combines the occurrence degree with an occurrence area, and can accurately reflect occurrence conditions of the forest pest. Occurrence degree classification is conducted according to the occurrence index number and based on data within a large region; meteorological data is not directly used in forecasting, and change of meteorological factors is used as independent variable. Therefore, occurrence of the forest pest in different geographical scales is unified, and a forecasting model can be used for forecasting not only in small regions (city or county) but also in large regions (province or whole nation).

Description

technical field [0001] The invention belongs to the field of forecasting the occurrence of forestry harmful organisms, and in particular relates to a method for predicting the occurrence degree of forestry harmful organisms. Background technique [0002] The occurrence of forestry pests is closely related to environmental factors. These factors include natural enemies, weather and site factors. There are too many reports on the use of environmental factors to predict the occurrence of forestry pests. But there have been several problems with these studies for a long time. One is that the previous studies only used the meteorological data and pine caterpillar occurrence data of a region (usually a county or city, or a forestry bureau). Due to the prediction of small areas, the measurement of the occurrence degree of forestry pests is different. Therefore, it is impossible to predict large areas; the second is that in previous studies, either the population density (disease...

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Problems solved by technology

One is that the previous studies only used the meteorological data and pine caterpillar occurrence data of a region (usually a county or city, or a forestry bureau). Due to the prediction of small areas, the measurement of the occurrence degree of forestry pests is different. Therefore, it is impossible to predict large areas; the second is that in previous studies, either the population density (disease index) was used to measure the occurrence degree of pests, or the occurrence area was used to measure, and the two were not combined, which could not fully reflect its occurrence. The third is that from the perspective of a larger region or the whole country, the occurrence of a certain forestry pest (such as larch caterpillar) is always low in some areas, or has never occurred

In the context of climate warming, a large-scale event may occur in this area, but the historical data of this area cannot provide corresponding meteorological data and occurrence conditions

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