Change in the general aboveground phytomass as a basis for modeling dynamics of recovery of vegetative cover

Abstract

Our study was focused on changes in the general aboveground phytomass during restoration of the vegetative cover. The objective was to analyze changes in the aboveground phytomass as an indicator of autogenic ecosystem dynamics. Therefore, we set the following goals: to detect changes that occurred in the amount of aboveground phytomass while the natural vegetation reco­vered; develop a mathematical model that would describe the process of dynamics of aboveground phytomass during progressive autogenic successions; develop a parameter of natural ecosystem dynamics based on changes in the aboveground phytomass during recovery of natural vegetation. To achieve our goals, we conducted a series of eight stationary experiments that lasted from 2005 to 2014 in the territory of central Polissia. Also, we carried out geobotanical studies, measuring phytomass outside the stationary plots. As vegetation in the disturbed areas recovered, the amount of aboveground phytomass naturally increased. Function of the natural logarithm is a mathematical model of change in the aboveground phytomass. In this model, regression coefficient “a” represents the initial conditions of when recovery started. For secondary ecological successions, regression coefficient “a” was higher than for the initial one. Regression coefficient “b” indicated the rates of production of aboveground phytomass. With time, a predicted trend of change in the aboveground phytomass becomes more likely to deviate.. Increase in the aboveground phytomass in most cases accompanies autogenic succession, and its decline, except in rare cases, accompanies/ homogenic succession. Accumulation of maximum possible phytomass and its storage for a maximum time interval corresponds to the state of energy (climatic) climax, while stopping its production at lower values – to catastrophic climax. The mathematical model of change in the general aboveground phytomass is the basis for further development of an integral theory of ecosystem dynamics. Prediction algorithms that have been developed based on the proposed mathematical model can be useful during environmental audit or decision making in nature protection when assessing whether an area requires a strict protection regime.