Direct input of monitoring data into a mechanistic ecological model as a way to identify the phytoplankton growth-rate response to temperature variations.

We present an approach (knowledge-and-data-driven, KDD, modeling) that allows us to get closer to understanding the processes that affect the dynamics of plankton communities. This approach, based on the use of time series obtained as a result of ecosystem monitoring, combines the key features of both the knowledge-driven modeling (mechanistic models) and data-driven (DD) modeling. Using a KDD model, we reveal the phytoplankton growth-rate fluctuations in the ecosystem of the Naroch Lakes and determine the degree of phase synchronization between fluctuations in the phytoplankton growth rate and temperature variations. More specifically, we estimate a numerical value of the phase locking index (PLI), which allows us to assess how temperature fluctuations affect the dynamics of phytoplankton growth rates. Since, within the framework of KDD modeling, we directly include the time series obtained as a result of field measurements in the model equations, the dynamics of the phytoplankton growth rate obtained from the KDD model reflect the behavior of the lake ecosystem as a whole, and PLI can be considered as a holistic parameter.

Phase synchronization of chlorophyll and total phosphorus oscillations as an indicator of the transformation of a lake ecosystem.

The ecosystem of the Naroch Lakes (Belarus) includes three water bodies, Lake Batorino, Lake Myastro and Lake Naroch. These lakes have a common catchment area. At the end of the 80 s, the ecosystem of the Naroch Lakes underwent a transformation, during which the nutrient load on the catchment area decreased, and the concentration of phosphorus as a limiting factor in these water bodies decreased significantly. At the same time, the Naroch Lakes were exposed to zebra mussel (Dreissena polymorpha Pallas) invasion. In the mid-90 s, the biological and hydrochemical characteristics of the ecosystem of the Naroch Lakes stabilized. We show here that complex processes associated with the transformation of the lake ecosystem and affecting both trophic interactions in the Naroch Lakes and the influence of environmental factors on them can be represented using a single parameter, the phase-locking index, PLI. In this case, a statistically significant numerical value of PLI characterizes the phase synchronization of two processes, oscillations of the concentration of total phosphorus, TP, and oscillations of the concentration of chlorophyll, Chl. We show that the phase synchronization of these processes occurs only after the stabilization of the ecosystem of the Naroch Lakes. In the period preceding the transformation of the lake ecosystem, there was no synchronization. Numerical evaluation of PLI as a holistic parameter allows us to characterize the transformation of the lake ecosystem as a whole without resorting to study of complex interactions of various factors involved in this transformation.

Assessment of the COVID-19 pandemic situation: Data from two countries with different security measures taken by authorities (Belarus and Russia).

The article presents the data on the evaluation of COVID-19 situation by adult respondents (age from 18 to 76) coming from countries with the common past, language and similar mentality but differing in governmental security measures during pandemic spring outbreak (no precautionary measures in Belarus (N = 267); lockdown and financial support in Russia (N = 397)). The data was collected via online survey platform (Google forms) from 2020.04.11 to 2020.06.04 (during the period of lock-down in Russia). The data contains socio-demographical information (sex, age, country of citizenship), survey answers and the results of standardized psychological tests (to measure dangerous and threatening social world view and hardiness). The survey consists of four blocks: specific impact of the COVID-19 situation on various aspects of respondents' life; estimation of different fears; estimation of various aspects of COVID-19 situation, and estimation of personal resources. All the items require participants to rate them on a 11-point Likert scale from 0 (totally disagree, absolutely no fear or no impact) to 10 (totally agree, the strongest fear or impact). Descriptive statistics as well as the comparison results are given. The data may be used to investigate the influence of lockdown, social distancing, and isolation on psychological well-being as well as the impact of personal resources in psychological well-being in stressful situations.