The impact of temporal patterns of temperature and precipitation on silver Prussian carp (Carassius gibelio) spawning events

Keywords: spawning; temperature; precipitation; principal component analysis; phenology


It was revealed that Gibel carp, Carassius gibelio (Bloch, 1782) spawning phenology is determined by regular patterns of variability in temperature and precipitation over the period of time after spawning in the previous year. The sensitivity to temperature of water as a stimulus to spawning was shown as being dependent on the characteristics of the environment and fish development trajectories over the previous year. Information about fish spawning was collected in the Dnipro-Orylskiy Nature Reserve in the following locations: Nikolayev system of water bodies, River Protoch system and the Obukhov floodplain, the channel of the River Dnipro, water bodies of the Taromske ledge. The materials that formed the basis of this research were collected from the waters of the reserve in the years 1997–2018. There are dependencies between the air and water temperatures that have their own characteristics depending on the type of water body. These dependencies are described by a logistic equation. The temperature regime in water bodies of the Taromske ledge is very similar to the temperature regime of Nikolayev system of water bodies. The difference is that the spring period of the temperature increase in water bodies of the Taromske ledge comes earlier – in late February – early March. The air temperature dynamics over the year is described by the fourth degree polynomial. The residuals of the polynomial regression for each year were subjected to principal component analysis. The principal component analysis allowed us to identify 8 principal components of the temperature regimes, which together describe 59.2% of the variation of the residual of the polynomial trend. Deviations from the linear trend of the precipitation are systematic throughout the year, reflecting the uneven nature of rainfall during the year. The residuals of linear trend regression models of cumulative precipitation can be used as indicators of the dynamics characteristic of precipitation during the year. The residuals were used for principal component analysis, which revealed that the dynamics of the precipitation can be divided into five orthogonal principal components. The first five principal components explain 82.6% of the feature space variation. The timing of the onset of C. gibelio spawning in 95% of cases occurs on the 113–139th days of the year (on average, it takes place on the 125th day). Regression analysis revealed that the climate principal components and types of the lake systems can explain 79% of the variation in the timing of the onset of C. gibelio spawning. The water temperature at the time of C. gibelio spawning was exposed to natural dynamics in year aspect. The local minimum of the onset of spawning temperatures occured in the mid 2000s. Total of 69% of the water temperature variation at which spawning begins can be described by climatic predictors and water biotope types. The variation explained by some temperature principal components may be increased considerably after including as covariates such variables as the precipitation principal component and the biotope type. This principal component which represents the high frequency variation of the air temperature regime with a characteristic period 20 and 45 days has the highest explanation ability of all the components and is a constant explanatory predictor for all considered spawning characteristics.


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