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Future increase in atmospheric CO concentrations will potentially enhance grassland biomass production and shift the functional group composition with consequences for ecosystem functioning. In the "GiFACE" experiment (Giessen Free Air Carbon dioxide Enrichment), fertilized grassland plots were fumigated with elevated CO (eCO ) year-round during daylight hours since 1998, at a level of +20% relative to ambient concentrations (in 1998, aCO was 364 ppm and eCO 399 ppm; in 2014, aCO was 397 ppm and eCO 518 ppm). Harvests were conducted twice annually through 23 years including 17 years with eCO (1998 to 2014). Biomass consisted of C3 grasses and forbs, with a small proportion of legumes. The total aboveground biomass (TAB) was significantly increased under eCO (p = .045 and .025, at first and second harvest). The dominant plant functional group grasses responded positively at the start, but for forbs, the effect of eCO started out as a negative response. The increase in TAB in response to eCO was approximately 15% during the period from 2006 to 2014, suggesting that there was no attenuation of eCO effects over time, tentatively a consequence of the fertilization management. Biomass and soil moisture responses were closely linked. The soil moisture surplus (c. 3%) in eCO manifested in the latter years was associated with a positive biomass response of both functional groups. The direction of the biomass response of the functional group forbs changed over the experimental duration, intensified by extreme weather conditions, pointing to the need of long-term field studies for obtaining reliable responses of perennial ecosystems to eCO and as a basis for model development.

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Feedbacks of plant phenology to the regional climate system affect fluxes of energy, water, CO2, biogenic volatile organic compounds as well as canopy conductance, surface roughness length, and are influencing the seasonality of albedo. We performed simulations with the regional climate model COSMO-CLM (CCLM) at three locations in Germany covering the period 1999 to 2015 in order to study the sensitivity of grass phenology to different environmental conditions by implementing a new phenology module. We provide new evidence that the annually-recurring standard phenology of CCLM is improved by the new calculation of leaf area index (LAI) dependent upon surface temperature, day length, and water availability. Results with the new phenology implemented in the model show a significantly higher correlation with observations than simulations with the standard phenology. The interannual variability of LAI improves the representation of vegetation in years with extremely warm winter/spring (e.g., 2007) or extremely dry summer (e.g., 2003) and shows a more realistic growth period. The effect of the newly implemented phenology on atmospheric variables is small but tends to be positive. It should be used in future applications with an extension on more plant functional types.