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Licorice firefly leaf beetle Diorhbda tarsalis Weise harm licorice leaves one of the important pests cause significant losses of Trades licorice production. Indoor and field trials in 2003 and 2004 by the morphology of the pest, habits, life history, developmental threshold temperature and effective accumulated temperature, the Population Spatial distribution system; 9 under constant temperature conditions observed at 15 ~ 36 ℃ pest experimental population growth and development, survival and reproduction, the formation of a laboratory population life table; under different temperature conditions and the initial development of a comprehensive management measures. The results are as follows: (1) biology: insect 1 year 2 or 3 generations, began in late October last adult 2 ~ 5cm at overwintering in the litter or sand shallow, mid-April of the following year, in late unearthed activities feeding nutritional supplement, and copulation spawning. Eggs prolific in the dorsal or soil, third instar larvae, mature larvae do soil under licorice cocoon to pupate. Into larvae licorice leaves designed feeding habits, adults feign death, can fly short distances, life multiple mating, spawning multiple times. (2) effective accumulated temperature: in the temperature range of 15 ~ 36 ℃, insect developmental rate with increasing temperature and speed up, the Logistic model: developmental threshold temperature and effective accumulated temperature calculated instars. (3) The spatial distribution: fit chi-square (x 2 ) fitting adults in line with the core distribution and negative binomial distribution, the larvae in line with the negative binomial distribution; indicators Moore I, Lloyd m < sup> * / m indicators, Kuno Ca indicators, diffusion coefficient C, degree of aggregation test negative binomial distribution K index, adults, larvae are aggregated distribution; the m * -m regression analysis the law and Toylar power the aggregation rule further confirmed; establish the model of the Kuno risk decision sequential sampling and analysis of insect in Daejeon optimum theoretical sampling mathematical model fitting. (4) the influence of temperature on survival: instars survival rate in the temperature range of 23 ~ 30 ℃, 25 ℃ the highest generation survival; survival decreased when the temperature is below 23 ° C or above 30 ℃, . The cumulative survival rate from high to low temperature of the order of pre-spawning order of 25 ° C, 27 ° C, 23 ° C, 30 ° C, 21 ° C, 33 ° C, 18 ° C, 36 ° C, 15 ° C. (5) the temperature on spawning: the sooner the period of fecundity is highest at 25 ℃ ~ 27 ℃ higher than 27 ℃ or lower than 25 ℃ spawning volume became smaller; And the higher the temperature, spawning the shorter the duration, spawning, just change the amplitude gradually smaller. The 15 ℃ insect do not lay eggs. (6) The temperature adult life: 18 ~ 36 ℃ in adult life as a whole, with increasing temperature and shortening. Logistic prediction model and fitting a the adult longevity reciprocal temperature relationship: N = 0.1093 / [exp (2.2799-0.069x)] (R 2 = 0.949). (7) the formation of the experimental population life table: different constant temperature of 25 ° C under the population trend index is the highest, 33 ℃ innate capacity for increase maximum. K value and regression coefficient (b) analysis, and learned that the larvae of the impact of changes in the key insect pest experimental populations period. (8) The efficacy trials: an indoor leaf dipping method, measured adults phoxim most sensitive reaction, the minimum lethal concentration LC 50 relative toxicity index; followed TIANBA, Chlorpyrifos and omethoate, the worst of the sensitivity of imidacloprid. One thousand insects grams (BtA) and DDV for the prevention and treatment of a large area in the field using the same dilution factor, seven days after the drug, one thousand insects of g (BtA) and DDV control effect quite. One thousand insects grams (BtA) is a highly effective broad-spectrum biocide, thus the thousand insect grams (BtA) is the choice for the pest control agent. (9) by phenological forecasting the occurrence of the pest, and propose effective physical control and biological control measures.
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