Analysis of climate change scenarios based on modelling of the seasonal dynamics of a Danubian copepod species

Climate change is one of the most crucial ecological problems of our age with great influence. Seasonal dynamics of aquatic communities are — among others — regulated by the climate, especially by temperature. In this case study we attempted the simulation modelling of the seasonal dynamics of a copepod species, Cyclops vicinus, which ranks among the zooplankton community, based on a quantitative database containing ten years of data from the Danube’s Göd area. We set up a simulation model predicting the abundance of Cyclops vicinus by considering only temperature as it affects the abundance of population. The model was adapted to eight years of daily temperature data observed between 1981 and 1994 and was tested successfully with the additional data of two further years. The model was run with the data series of climate change scenarios specified for the period around 2070- 2100. On the other hand we looked for the geographically analogous areas with the Göd region which are mostly similar to the future climate of the Göd area. By means of the above-mentioned points we can get a view how the climate of the region will change by the end of the 21st century, and the way the seasonal dynamics of a chosen planktonic crustacean species may follow this change. According to our results the area of Göd will be similar to the northern region of Greece. The maximum abundance of the examined species occurs a month to one and a half months earlier, moreover larger variances are expected between years in respect of the abundance. The deviations are expected in the direction of smaller or significantly larger abundance not observed earlier.

Trends in research on the possible effects of climate change concerning aquatic ecosystems with special emphasis on the modelling approach

Knowledge on the expected effects of climate change on aquatic ecosystems is defined by three ways. On the one hand, long-term observation in the field serves as a basis for the possible changes; on the other hand, the experimental approach may bring valuable pieces of information to the research field. The expected effects of climate change cannot be studied by empirical approach; rather mathematical models are useful tools for this purpose. Within this study, the main findings of field observations and their implications for future were summarized; moreover, the modelling approaches were discussed in a more detailed way. Some models try to describe the variation of physical parameters in a given aquatic habitat, thus our knowledge on their biota is confined to the findings based on our present observations. Others are destined for answering special issues related to the given water body. Complex ecosystem models are the keys of our better understanding of the possible effects of climate change. Basically, these models were not created for testing the influence of global warming, rather focused on the description of a complex system (e. g. a lake) involving environmental variables, nutrients. However, such models are capable of studying climatic changes as well by taking into consideration a large set of environmental variables. Mostly, the outputs are consistent with the assumptions based on the findings in the field. Since synthetized models are rather difficult to handle and require quite large series of data, the authors proposed a more simple modelling approach, which is capable of examining the effects of global warming. This approach includes weather dependent simulation modelling of the seasonal dynamics of aquatic organisms within a simplified framework.

Seasonal dynamics of an aquatic macroinvertebrate assembly (Hydrobiological case study of Lake Balaton No. 2)

In 2002, 2003 and 2004, we took macoinvertebrate samples on a total of 36 occasions at the Badacsony bay of Lake Balaton. Our sampling site was characterised by areas of open water (in 2003 and 2004 full of reed-grass) as well as by areas covered by common reed (Phragmites australis) and narrowleaf cattail (Typha angustifolia). Samples were taken both from water body and benthic ooze by use of a stiff hand net. We have gained our data from processing 208 individual samples. We took samples frequently from early spring until late autumn for a deeper understanding of the processes of seasonal dynamics. The main seasonal patterns and temporal changes of diversity were described. We constructed a weather-dependent simulation model of the processes of seasonal dynamics in the interest of a possible further utilization of our data in climate change research. We described the total number of individuals, biovolume and diversity of all macroinvertebrate species with a single index and used the temporal trends of this index for simulation modelling. Our discrete deterministic model includes only the impact of temperature, other interactions might only appear concealed. Running the model for different climate change scenarios it became possible to estimate conditions for the 2070-2100 period. The results, however, should be treated very prudently not only because our model is very simple but also because the scenarios are the results of different models.

How much is corporate cash-pooling worth? Modelling and simulation

The paper analyzes a special corporate banking product, the so called cash-pool, which gained remarkable popularity in the recent years as firms try to centralize and manage their liquidity more efficiently. The novelty of this paper is the formalization of a valuation model which can serve as a basis for a Monte Carlo simulation to assess the most important benefits of the firms arising from the pooling of their cash holdings. The literature emphasizes several benefits of cash-pooling such as interest rate savings, economy of scale and reduced cash-flow volatility. The presented model focuses on the interest rate savings complemented with a new aspect: the reduced counterparty risk toward the bank. The main conclusion of the analysis is that the value of a cash-pool is higher in case of firms with large, diverse and volatile cash-flows having less access to the capital markets especially if the partner bank is risky and offers a high interest spread. It is also shown that cash-pooling is not the privilege of large multinational firms any more as the initial direct costs can be easily regained within a year even in the case of SMEs.

Analysis of operational risk of banks – catastrophe modelling

Nowadays financial institutions due to regulation and internal motivations care more intensively on their risks. Besides previously dominating market and credit risk new trend is to handle operational risk systematically. Operational risk is the risk of loss resulting from inadequate or failed internal processes, people and systems or from external events. First we show the basic features of operational risk and its modelling and regulatory approaches, and after we will analyse operational risk in an own developed simulation model framework. Our approach is based on the analysis of latent risk process instead of manifest risk process, which widely popular in risk literature. In our model the latent risk process is a stochastic risk process, so called Ornstein- Uhlenbeck process, which is a mean reversion process. In the model framework we define catastrophe as breach of a critical barrier by the process. We analyse the distributions of catastrophe frequency, severity and first time to hit, not only for single process, but for dual process as well. Based on our first results we could not falsify the Poisson feature of frequency, and long tail feature of severity. Distribution of “first time to hit” requires more sophisticated analysis. At the end of paper we examine advantages of simulation based forecasting, and finally we concluding with the possible, further research directions to be done in the future.

A villamos erőművek szén-dioxid-kibocsátásának modellezése reálopciók segítségével = Modelling of the carbon dioxide emissions of a power plant, using real options

A szerző egy, a szennyezőanyag-kibocsátás európai kereskedelmi rendszerében megfelelésre kötelezett gázturbinás erőmű szén-dioxid-kibocsátását modellezi négy termékre (völgy- és csúcsidőszaki áramár, gázár, kibocsátási kvóta) vonatkozó reálopciós modell segítségével. A profitmaximalizáló erőmű csak abban az esetben termel és szennyez, ha a megtermelt áramon realizálható fedezete pozitív. A jövőbeli időszak összesített szén-dioxid-kibocsátása megfeleltethető európai típusú bináris különbözetopciók összegének. A modell keretein belül a szén-dioxid-kibocsátás várható értékét és sűrűségfüggvényét becsülhetjük, az utóbbi segítségével a szén-dioxid-kibocsátási pozíció kockáztatott értékét határozhatjuk meg, amely az erőmű számára előírt megfelelési kötelezettség teljesítésének adott konfidenciaszint melletti költségét jelenti. A sztochasztikus modellben az alaptermékek geometriai Ornstein-Uhlenbeck-folyamatot követnek. Ezt illesztette a szerző a német energiatőzsdéről származó publikus piaci adatokra. A szimulációs modellre támaszkodva megvizsgálta, hogy a különböző technológiai és piaci tényezők ceteris paribus megváltozása milyen hatással van a megfelelés költségére, a kockáztatott értékére. ______ The carbon-dioxide emissions of an EU Emissions Trading System participant, gas-fuelled power generator are modelled by using real options for four underlying instruments (peak and off-peak electricity, gas, emission quota). This profit-maximizing power plant operates and emits pollution only if its profit (spread) on energy produced is positive. The future emissions can be estimated by a sum of European binary-spread options. Based on the real-option model, the expected value of emissions and its probability-density function can be deducted. Also calculable is the Value at Risk of emission quota position, which gives the cost of compliance at a given confidence level. To model the prices of the four underlying instruments, the geometric Ornstein-Uhlenbeck process is supposed and matched to public available price data from EEX. Based on the simulation model, the effects of various technological and market factors are analysed for the emissions level and the cost of compliance.

Evaluation of climate change scenarios based on aquatic food web modelling

In the years 2004 and 2005 we collected samples of phytoplankton, zooplankton and macroinvertebrates in an artificial small pond in Budapest. We set up a simulation model predicting the abundance of the cyclopoids, Eudiaptomus zachariasi and Ischnura pumilio by considering only temperature as it affects the abundance of population of the previous day. Phytoplankton abundance was simulated by considering not only temperature, but the abundance of the three mentioned groups. This discrete-deterministic model could generate similar patterns like the observed one and testing it on historical data was successful. However, because the model was overpredicting the abundances of Ischnura pumilio and Cyclopoida at the end of the year, these results were not considered. Running the model with the data series of climate change scenarios, we had an opportunity to predict the individual numbers for the period around 2050. If the model is run with the data series of the two scenarios UKHI and UKLO, which predict drastic global warming, then we can observe a decrease in abundance and shift in the date of the maximum abundance occurring (excluding Ischnura pumilio, where the maximum abundance increases and it occurs later), whereas under unchanged climatic conditions (BASE scenario) the change in abundance is negligible. According to the scenarios GFDL 2535, GFDL 5564 and UKTR, a transition could be noticed.