1. Time-series analysis of oxygen as an important environmental parameter for monitoring diversity hotspot ecosystems : an example of a river sinking into the karst undergroundSaptashwa Bhattacharyya, Janez Mulec, Andreea Oarga-Mulec, 2023, original scientific article Abstract: Predicting variations in dissolved oxygen concentration (DO) is important for management and environmental monitoring of aquatic ecosystems. Regression analyses and univariate and multivariate time-series analyses based on autoregressive methods were performed to investigate oxygen conditions in the Pivka River, Slovenia. The monitoring site was established upstream where the river sinks into the karst cave Postojnska jama, which hosts one of the richest subterranean faunas yet studied worldwide. It was found that abnormal variations of DO started to be noticeable at values of DO < 3 mg/L and became more pronounced until the ecosystem reached fully anoxic conditions. The abnormal fluctuations during the critical summer period were due to environmental conditions, organic load and resident biota. Predictions for future detection of anomalies in DO values were made from stable residuals of the measured data, and it was demonstrated that the model could be used to obtain a reliable estimate for a short period, such as one day. The example presented an analysis pipeline based on specific and established threshold DO values, and it is particularly important for ecosystems with diversity hotspots where prolonged low DO values can pose a threat to their biota.
Keywords: karst (geology), aquatic ecosystems, dissolved oxygen, modelling, prediction
Published in RUNG: 05.09.2023; Views: 731; Downloads: 5
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7. How size of target avalanches influences prediction efficiencyAlexander Shapoval, M. Shnirman, 2004, original scientific article Abstract: Bak, Tang, and Wiesenfeld [Phys. Rev. Lett.59, 381 (1987)] introduced their sand-pile (BTW sand-pile) as the cellular automata coming to their critical state without tuning any inner model parameters. The main model features deal with grains falling slowly onto the two-dimensional lattice and a quick deterministic transport of the superfluous grains to the boundary. The simplest modifications of the BTW sand-pile develop a random transport mechanism instead of a deterministic one. The model transportation of the grains generates avalanches. We find that before the big avalanches the height of the pile increases and the singular grains organize themselves in special clusters. These observations lead to the formal algorithm that predicts the big avalanches in advance with a certain efficiency. However the efficiency for the BTW sand-pile is worse than that for its stochastic modifications.
Keywords: sandpile, prediction, avalanches
Published in RUNG: 19.04.2021; Views: 1612; Downloads: 0
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8. Strong events in the sand-pile modelAlexander Shapoval, M. Shnirman, 2004, original scientific article Abstract: Here is a sand-pile introduced by Bak et al. The system accumulates particles one by one. From time to time it topples. Every toppling initiates an event. The distribution of the events' size follows a power law for all the events except the strongest ones. The fraction of the strongest events does not depend on the system length. The number of particles and their clustering increase before the strongest events.
Keywords: sandpile, prediction, power-law
Published in RUNG: 19.04.2021; Views: 1691; Downloads: 0
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9. Impact of bacterial ice nucleating particles on weather predicted by a numerical weather prediction modelMaher Sahyoun, Ulrik S. Korsholm, Jens H. Sørensen, Tina Šantl Temkiv, Kai Finster, Ulrich Gosewinkel, Niels Woetmann Nielsen, 2017, original scientific article Keywords: Heterogeneous ice nucleation, Bacterial INP, Cloud ice, Precipitation, Global solar radiation, Numerical weather prediction model
Published in RUNG: 04.01.2021; Views: 2963; Downloads: 0
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