Water table depth, experimental warming, and reduced precipitation impact on litter decomposition in a temperate Sphagnum-peatland.

The Tea Bag Index (TBI) method was used to estimate the litter decomposition rate in peatland exposed for climate manipulation (increased temperature and reduced precipitation) at two contrasting sites differing in water table depth (WTD) dynamics. To manipulate climate on peatland, the prototyped Open Top Chambers (OTC) and automated rain-out shelters were used. OTCs increased daytime air temperatures by ~1.

Impact of warming and reduced precipitation on morphology and chlorophyll concentration in peat mosses (Sphagnum angustifolium and S. fallax).

Peatlands are one of the most important ecosystems due to their biodiversity and abundant organic compounds; therefore, it is important to observe how different plant species in peatlands react to changing environmental conditions. Sphagnum spp. are the main component of peatlands and are considered as the creator of conditions favorable for carbon storage in the form of peat.

Dynamics of sun-induced chlorophyll fluorescence and reflectance to detect stress-induced variations in canopy photosynthesis.

Passive measurement of sun-induced chlorophyll fluorescence (F) represents the most promising tool to quantify changes in photosynthetic functioning on a large scale. However, the complex relationship between this signal and other photosynthesis-related processes restricts its interpretation under stress conditions. To address this issue, we conducted a field campaign by combining daily airborne and ground-based measurements of F (normalized to photosynthetically active radiation), reflectance and surface temperature and related the observed changes to stress-induced variations in photosynthesis.

Improving remote estimation of winter crops gross ecosystem production by inclusion of leaf area index in a spectral model.

The hysteresis of the seasonal relationships between vegetation indices () and gross ecosystem production () results in differences between these relationships during vegetative and reproductive phases of plant development cycle and may limit their applicability for estimation of croplands productivity over the entire season. To mitigate this problem and to increase the accuracy of remote sensing-based models for estimation we developed a simple empirical model where greenness-related are multiplied by the leaf area index (). The product of this multiplication has the same seasonality as , and specifically for vegetative periods of winter crops, it allowed the accuracy of estimations to increase and resulted in a significant reduction of the hysteresis of vs.