| Forest pests and diseases being as a kind of biological disaster occurring frequently are an important constrainting factor for the production of forestry and the ecological engineering construction.China is one of the countries in the world in which forest pests and diseases are more serious,and has more than 200 kinds of forest pests and diseases which often bring damage. Heilongjiang has obvious advantage at forest resource in China.At the same time,forest pests and diseases are very serious for Heilongjiang province.In order to reduce the loss because of the damage of forest pests and diseases,the future occurrence and development trends of forest pests and diseases can be forecasted,then can be controlled persistently by researching the regulation of diseases and pests populations changing in forest ecosystem.The occurrences and prevailing of forest pests and diseases are the synthesis results of trees,harmful organisms and meteorological factors,and meteorological factors are the key factors.The system model can be built by mathematics and ecology methods,and then these models can be used in forecasting population trend accurately in pest populations for important forest diseases and pests,and then to take scientific measures for the comprehensive management according to meteorological factors' impact on the population dynamics of forest diseases and pests in forest ecosystem.The purpose of setting up mathematical models was to find out the best management measure for ecosystem by mathematical and ecological methods.In the paper,internal relations of the pests and diseases and the meteorological factors were analysed and forecasting models of relative areas were set up according to the principle of mathematical statistics,then damage degree and occurrence trend of forest pests and diseases in the future were forecasted using meteorological datum and investigation data.The scientific basis of monitoring and control to forest pests and diseases for area and county in Heilongjiang province was provided by determining key meteorological factors impacting the population dynamics of forest pests and diseases,and setting up forecasting models.The occurrence and development dynamics of major forest pests and diseases was known timely and the scientific support for the decision-making was provided timely for the prevention and control of forest pests and diseases.And to minimize the loss of forest pests and diseases,and establish a scientific and effective predicting system for forest pests and diseases with the best comprehensive benefit.The relationship of meteorological factors and three important forest pests and diseases in Heilongjiang were studied separately,which were Dendrolimus superans,Cryptorrhynchus lapathi and poplar canker.In the study,monthly average temperature,monthly average humidity,the monthly highest temperature,the monthly lowest temperature and precipitation were used as impact factors.Methods used in the paper were correlation analysis,partial correlation analysis,stepwise regression,multiple linear regression and path analysis.And the main conclusions were as follows: 1,The forecasting models of Dendrolimus superans were analyzed for the first time according to the meteorological data and the actual survey data of Dendrolimus superans which came from Hailin city of Mudanjiang area,Mishan county of Jixi area,Qing'an county of Suihua area and Longjiang county of Qiqihar region.For Hailin city,Mishan county,Qing'an county and Longjiang county,the forecasting modles were y=-35.374+0.286x2+0.517x72-0.694x78+0.163x80-0.154x90+l.011x73,y=-45.427+1.003x2+0.293x72+0.697x73+0.835x65+0.355x66+1.702x69,y=-65.303+0.925x2+0.384x65+0.316x69+0.237x72+0.047x80+0.087x59-0.008x95,and y=9.826+ 0.065x2+0.114x69+ 0.485x73-0.064x90-0.010x95+0.352x54 separately.The average forecasting accuracy of stepwise regression model was 79.73921%for Hailin city,88.855%for Mishan county, 88.193%for Qing'an county and 78.071%for Longjiang county.For Mishan county and Qing'an county,the forecasting accuracy being more than 80%was 88.3%,77.8%and 100%of the years studied respectively.Path analysis further confirmed the role of the main meteorological factors in the models affecting Dendrolimus superans.The analysises were in line with the facts.It was shown that,in Hail.in city,the average humidity of January in the last year(x2),the average humidity of March (x72),the highest temperature of April(x78),the precipitation of April(x80),the precipitation of June(x90),the highest temperature of March(x73) were the major factors affecting population density ofDendrolimus superans.And in Mishan county,they were the average humidity of January in the last year(x2),the average humidity of March(x72),the highest temperature of March(x73), the precipitation of January(x65),the average temperature of February(x66) and the lowest temperature(x69).At Qing'an county,the average humidity of January in the last year(x2),the average humidity of March(x72),the highest temperature of March(x73),the precipitation(x65) of January,the average temperature of February(x66) and the lowest temperature(x69) were the main factors affecting the occurrence and development of Dendrolimus superans,while they were the average humidity of January in the last year(x2),the lowest temperature of January(x69),the highest temperature of March(x73),the precipitation of June(x90),the precipitation of July(x95) and lowest temperature of November in the last year(x54) at Longjiang county.In conclusion,for four counties or city selected,the average humidity of January in the last year(x2),the average humidity of March(x72),the highest temperature of March(x73) and the lowest temperature of January(x69) were more important.2,When analyzing Cryptorrhynchus lapathi,Baiquan county,Yian county,Gannan county and Zhaoyuan county were used as the scopes studied,the meteorological factors from the last October to this September corresponding to the pest population density of this year and investigation data of Cryptorrhynchus lapathi was chosen.Models were established by multiple linear regression. It was shown that in Baiquan county,the main meteorological factors impacting the population density of Cryptorrhynchus lapathi were as follows:the lowest temperature of April(x34),the precipitation of August(x55),the precipitation of April(x35),the precipitation of March(x30) and the lowest temperature of the last November(x9),while the average temperature of January(x16), the average temperature of March(x26),the precipitation of January(x20),the highest temperature of February(x23) and the lowest temperature of April(x34) for Gannan.In Zhaoyuan,the main meteorological factors impacting the population density were the highest temperature of February (x23),the lowest temperature of April(x34),the average temperature of June(x41),the precipitation of June(x45),the average temperature of July(x46),the lowest temperature of July(x49) and the average humidity of August(x52),while they were the average humidity of December in the last year(x12),the average temperature of January(x16),the average temperature of March(x26),the highest temperature of April(x33),the precipitation of June(x45),the lowest temperature of July (x49) in Yian.The average forecasting accuracy of multiple linear regression model for Baiquan county,Gannan county,Zhaoyuan county and Yian county was as follows:95.778%,83.7%,82.9% and 97.2%.And the forecasting accuracy more than 80%was 90%,70%,62.5%and 100%of the years studied respectively.All these shew that the basic requirements of model prediction has been reached.In conclusion,the main meteorological factors impacting on the occurrence and development of Cryptorrhynchus lapathi were as follows:the average temperature of January(x16),the highest temperature February(x23),the average temperature of March(x26),the lowest temperature of April(x34),the precipitation of June(x45) and the lowest temperature of July(x49).For them,the correlation coefficient were plus in addition to the precipitation of June.Analysises of these factors were consistent with the occurrence rule of Cryptorrhynchus lapathi.The forecasting accuracv of models set up was much higher,and the basic requirement was satisfied for models to forecast.3,The relationships of poplar canker and meteorological factors were analyzed for Beilin district and Zhaodong county of Suihua,and Zhaoyuan county of Daqing.The forecasting models were set up by stepwise regression using prediction factors selected.It was shown that model set up by stepwise regression displayed much higher accuracy for three counties or cities studied,and for Beilin district the forecasting accuracy being more than 90%was 87.5%,100%for Zhaodong county and Zhaoyuan county of the years studied.The occurrence of poplar canker at Beilin district had relation with the precipitation of February (x5),the lowest temperature of May(x10),the average humidity of June(x13) and the precipitation of August(x23),while the precipitation of February(x5),the lowest temperature of May(x10),the average humidity of June(x13),the precipitation of August(x23),the lowest temperature of July (x19) and the average temperature of June(x12) at Zhaodong.At Zhaoyuan the meteorological factors impacting poplar canker occurrence and development were the lowest temperature of Mav (x10),the average humidity of June(x13) and the precipitation of August(x23).In conclusion,the lowest temperature of May(x10),the average humidity of June(x13) and the precipitation of August(x23) were relatively more important for poplar canker.For other regions of Heilongjiang province,poplar canker forecasting can be mainly focused on these meteorological factors' functions.
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