An integrated method for assessing the state of biodiversity of disturbed ecosystems

The description and test results of a quite simple and yet universal integrated method for quantifying the state of ecosystems and the degree of negative impact on them by industrial facilities based on biodiversity parameters are presented.The approach is based on the normalisation of diversity parameters of indicator groups of animals and plants relative to the background (reference territory) with subsequent averaging of the obtained values to calculate the multimetric index.The resulting Integrated Indicator of the State of the Ecosystem (IISE) refl ects the extent of biodiversity change in the study area.Preliminary testing of the proposed method was carried out on the basis of materials collected during the Great Scientifi c Expedition (2022 and 2023) in the north of the Krasnoyarskii Krai in the Norilsk Industrial District and adjacent territories.Invertebrates (soil microarthropods, carabid beetles, spiders), vascular plants and lichens were used as indicator groups.The results of the preliminary testing confi rmed the eff ectiveness of the proposed approach for the assessment of the state of ecosystems and the degree of their disturbance.The integrated method of quantitative assessment of the state of ecosystems, based on the IISE calculation, made it possible to defi ne quite clearly the boundary of the belt of intensive impact on biodiversity, as well as to show a smooth gradient of reduction of negative impact towards the background area.This indicates great promise and wide potential possibilities for using this method, including for assessing the situation around large industrial facilities.However, to substantiate the possibility of wider application of the proposed method in monitoring studies, it is necessary to thoroughly test its performance and effi ciency on the basis of longer time series data, as well as on materials collected under other natural conditions and under diff erent types of anthropogenic impacts.. . - . () . , (2022 2023 .) . ( , -, ), . . , , , . , .