The project was completed in 2009 and the final report was delivered in October 2009. The aim of the project was to find a method to predict the potential growth and winter hardiness of three turfgrass species as a function of different light and temperature conditions. Good knowledge of the potential growth is the basis for planning a sound and sustainable maintenance programme, both regarding turf grass quality and economic and environmental concerns.
A simulation model for grass growth and winter mortality was used to estimate growth curves and winter survival for three different turfgrass species (Agrostis stolonifera, Festuca rubra and Poa annua) for different climatic conditions. Four locations in the Nordic countries (Umeå, Västerås and Lund in Sweden and Særheim in Norway) were modelled. The three different sites in Sweden represented different light and temperature conditions due to different latitudes. Særheim in Norway was selected to represent a more maritime climate. The effect of different climate change scenarios was also tested. Field data from Fullerö gk, Västerås, were collected during 2007 and 2008 to be used for calibration of the model.
The model developed was able to reproduce the growth pattern of turfgrass (Agrostis stolonifera) within the range of measurements over several years when compared against independent data on grass clippings. However, there are still many uncertainties in parameterisation of the model, especially the winter mortality part, because of lack of physiological knowledge of the grass species studied and lack of observations against which to test the model.
The results on winter mortality showed very interesting results and identified the complexity of the two opposite processes of hardening and dehardening and the interaction with the climatic conditions during winter in determining the effects on plant mortality. The model showed that although a milder climate reduced the risk of the temperature falling below the minimum temperature for grass tolerance at maximum hardening, a mild autumn could lead to less effective hardening so that maximum hardening was never reached. This weaker hardening made the grass more sensitive to low temperatures. A milder climate also decreased the number of days during winter with snow cover. The number of days with snow cover and the depth of snow are very im-portant parameters for the soil surface temperature and thus for the survival of the turf.
Conclusions:
– The model was able to reproduce the growth pattern of turfgrass (Agrostis stolonifera) within the range of measurements over several years when compared against independent data on grass clippings.
– Winter mortality was the most important factor for the differences in the biomass pool when comparing the sites at Umeå (Poa), Västerås and Lund (Agrostis). However, when the same species were simulated for all sites, the differences in winter mortality between the sites decreased. Actually, severe winter mortality was more frequent at Västerås and Lund compared with the more northerly Umeå for Agrostis, and almost as severe in Västerås as in Umeå for Poa.
– The model showed that a milder climate could lead to less effective hardening during autumn so that maximum hardening was never reached, thus increasing the risk of winter kill during cold spells.
– A milder climate also reduced the period with snow cover during winter, which caused more rapid dehardening to occur.
– As expected, the growth period lasted longer due to higher temperatures in the autumn for the coastal climate of Særheim compared with Västerås. However, in spring the climatic conditions were more similar. The simulated growth at Særheim was greatly influenced by low radiation conditions during rainy periods in summer.
– Winter hardening/dehardening was greatly influenced by the climate change scenario, with a warmer climate leading to much weaker hardening and more rapid dehardening, especially for the Agrostis turf at Västerås and Lund.
