Abstracts

Diversity of the Fauna

Siberian moth is a major forest insect pest in Siberia. Outbreaks of the moth can be considered as ecological catastrophes. It would be possible to prevent future outbreaks of Siberian moth provided that an effective regular monitoring of the moth population density is conducted. A monitoring technology has been worked out and is now used in Krasnoyarsk Center for Forest Protection under financial support of the Institute of Sustainable Communities (Montpelier, Vermont). 

The technology is based on a set of test plots. The plots are located in sites ecologically optimal for Siberian moth populations. Literature analysis preceded field work. Siberian moth outbreaks are known to start on elevated well-drained sites in mature stands dominated by Siberian fir with abundant green mosses on the ground. 

Every plot consists of a number of sample points and a route crossing habitats suitable for the moth populations. The route is normally several kilometers long. The sample points are located on the route within the distance of one kilometer from each other, 3-10 sample trees at each point. All sample trees are examined every year for the presence of Siberian moth larvae within spring or fall season. During the examination, the trees are shaken over a large cloth (normally a parachute). Fallen larvae are counted, collected, identified and sent to our laboratory in Krasnoyarsk for investigation for microbial and parasitoid infection, sex ratio and fertility of females. Recently, information on the moth population density comes to the Center from 196 test plots situated in different parts of the region. Employees of the Center collect data from 103 plots, and local forestry workers survey the remaining 93 plots.

A special Microsoft Access database has been developed in the Center to store and process data on insect pest population density. The database is connected to GIS ArcView electronic maps, on which numbers of the pests registered on the plots are automatically indicated. A gradation of colors permits recognition of observed population densities. A clear, easily perceptible picture of pest density is then generated by computer for the whole region.

The most fragile element of any monitoring system is the reliability of collected information, because professional skills of forestry workers not always allow them to do proper field work to monitor pests. The suggested method solves this problem and considerably reduces the doubts, which analysts always experience while working with data obtained from periphery. The collected data can be treated as reliable, because a good agreement exists among different data sets. The maps indicate that points where the moth larvae were found are not sparse or disordered, but instead form compact clouds corresponding to certain parts of the monitored region. In fact, the reliability of information is guaranteed by the large number of test plots that provide a consonant collective pattern of forest pest monitoring results. This regularly updated monitoring system will hopefully let us design a method of outbreak forecast and correspondingly undertake timely pest control measures.

Note. Abstracts are published in author's edition

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