Spawning phenology of the white bream (Blicca bjoerkna) in the "Dnieper-Orylskiy" Nature Reserve in relation to seasonal temperature dynamic

Keywords: spawning, phenology, environmental factors, climate, regression analysis


This paper examines the relationship between climatic conditions and the phenology of spawning of the white bream Blicca bjoerkna (Linnaeus, 1758) in natural habitats of the "Dnipro-Orylskiy" Nature Reserve. The characteristic of spawning distribution is symmetric, as the asymmetry coefficients do not significantly differ from zero. The distribution of the timing of spawning and its duration are also characterized by excesses, which do not significantly differ from zero alternatives. Analysis of meteorological data for the period of study allowed us to determine the trends in temperature variation, which correlate with the temperature of the water. Spawning events in any given year take place entirely within an upward temperature progression that can be accurately described by a linear equation in the form: Y = b + a · x, where Y – ten-day average temperature; x – the order of decades for I–VI months of the year, a and b – the parameters of the equation. The same equation can be used to describe downward movements in the temperature for decades during the VII–XII months of the year. Regression parameters and coefficients of determination have the following environmental sense. For the ascending temperature branch the regression coefficient b will decrease in proportion to the increase in the contrast between winter and summer temperatures. Due to the fact that linear approximation is a certain generalization of the sinusoid natural course of temperature, it should be borne in mind that the highest summer temperatures are close to the change in direction in the course of temperature from increase to decrease. Therefore, the coefficient b will largely depend on the minimum winter temperatures and should be interpreted as a marker of the coldness of the winter. This interpretation is all the more justified because we are concerned here with assessment of the impact on fish spawning, and the processes that precede spawning events clearly have importance for their explanation. Changes in the direction of the course of temperature which occur after spawning have no value in explaining spawning. If we consider coefficient b beyond the environmental context, then certainly this figure depends on the coldness of the winter and equally on the warmness of the summer. Similar considerations lead us to interpret the coefficient b of a descending branch as a marker of the warmness of the summer. Comparison of the ascending temperature branch of the current year and the descending branch of the previous year gives the coefficient of correlation between these parameters of linear regression r = –0.10, P = 0.39. This result confirms our assumption that the coefficient b of a descending branch is a marker of the warmness of summer, because if it were a marker of the coldness of a winter, then the coefficient of correlation parameters for the temperature course that are common for this winter would be statistically significant. In addition, the absence of connections indicates that these coefficients provide independent and additional information about the weather conditions. Coefficient a for the ascending branch characterizes the rate of warming during the spring, ie the rate of onset of summer, and for the descending branch – the rate of cooling in the fall, that is the speed of the onset of winter. The linear model reflects the general trend of warming in spring and cooling in autumn. In reality, the course of temperature change is by its nature a complex oscillatory process. Therefore the coefficient of determination of linear regression indicates the extent of correspondence of the real process to the linear model. Significant deviations from the general trend lead to a reduction in the coefficient of determination. These variations are the result of processes of sharp warming, alternating with periods of abrupt cooling. The more such events occur, the smaller the coefficient of determination. Thus, to describe the timing of spawning events we can examine the impact on them of such factors as regression model parameters for the current year for the ascending branch of temperature changes and parameters for the model of the previous year for the descending branch of temperature changes. As a result of our studies, we found that during the period 1997–2015 the typical course of temperature during the year is characterized by two branches: ascending and descending. The data obtained support the hypothesis that the onset of the various phases of spawning (the beginning of spawning, the end of spawning, spawning duration) is explained by temperature variation of the current year up to the spawning event and by temperature variation in the preceding year. The timing of the spawning of B. bjoerkna can be described at a statistically significant level by multidimensional factors reflecting the peculiarities of weather conditions and habitat type. The colder the previous summer and the winter of the current year and the fewer variables there are in the course of temperature, the later spawning occurs. The warmer the previous summer and the colder the winter of the current year, the later the spawning ends. Temperature variability in the course of temperature contributes to an earlier completion of spawning. There is a strong correlation between the beginning and the end of the spawning season so the impact of environmental factors at the beginning of spawning is also reflected in the timing of the end of spawning. The influence of conditions in the current year on the end of spawning is conditioned by the timing of the onset of spawning and the impact of weather conditions of the previous year on the end of spawning has independent significance. 


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