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.

Tények, adatok és mutatószámok felhasználásának anomáliái (The anomalies of the usage of facts, data, and indexes)

Tudomány nem létezik a tények felmérése, adatok gyűjtése és felhasználása nélkül. A tényeket azonban el lehet hallgatni vagy ferdíteni, az adatokat sokféleképpen lehet összeválogatni, az azokból készült mutatószámokat pedig a bonyolult és változó valóság leegyszerűsítő, sőt meghamisító ábrázolására, illetve magyarázatára is fel lehet használni. _____ Economics cannot do without measuring. However, the required data are not always available or they are not reliable, as some cases of population census exemplify it. The indicators we use, particularly composite indexes, are often misleading because they oversimplify complex phenomena or processes, and neglect important non-measurable ones, as the examples of the per capita GDP indicator measuring the development level of countries, and the composite indexes measuring the “human development” of countries (HDI), or their “national competitiveness” (GCI) may show. To avoid the enchantment of numbers, the quantitative approach must always be combined and corrected by a critical, holistic and qualitative approach.