Globally, forest soils contain twice as much carbon as forest vegetation. Consequently, natural and anthropogenic disturbances affecting carbon accumulation in forest soils can alter regional to global carbon balance. In this study, we evaluate the effects of historic litter raking on soil carbon stocks, a former forest use which used to be widespread throughout Europe for centuries. We estimate, for Switzerland, the carbon sink potential in current forest soils due to recovery from past litter raking ('legacy effect'). The year 1650 was chosen as starting year for litter raking, with three different end years (1875/ 1925/1960) implemented for this forest use in the biogeochemical model LPJ-GUESS. The model was run for different agricultural and climatic zones separately. Number of cattle, grain production and the area of wet meadow have an impact on the specific demand for forest litter. The demand was consequently calculated based on historical statistical data on these factors. The results show soil carbon pools to be reduced by an average of 17 % after 310 years of litter raking and legacy effects were still visible 130 years after abandonment of this forest use (2 % average reduction). We estimate the remaining carbon sink potential in Swiss forest due to legacy effects from past litter raking to amount to 158,000 tC. Integrating historical data into biogeochemical models provides insight into the relevance of past land-use practices. Our study underlines the importance of considering potentially long-lasting effects of such land use practices for carbon accounting.

Neurons of the same column in L4 of the cat visual cortex are likely to share the same sensory input from the same region of the visual field. Using visually-guided patch clamp recordings we investigated the biophysical properties of the synapses of neighboring layer 4 neurons. We recorded synaptic connections between all types of excitatory and inhibitory neurons in L4. The E–E, E–I, and I–E connections had moderate CVs and failure rates. However, E–I connections had larger amplitudes, faster rise-times, and shorter latencies. Identification of the sites of putative synaptic contacts together with compartmental simulations on 3D reconstructed cells, suggested that E–I synapses tended to be located on proximal dendritic branches, which would explain their larger EPSP amplitudes and faster kinetics. Excitatory and inhibitory synapses were located at the same distance on distal dendrites of excitatory neurons. We hypothesize that this co-localization and the fast recruitment of local inhibition provides an efficient means of modulating excitation in a precisely timed way.

Abstract. Models of carbon cycling in terrestrial ecosystems contain formulations for the dependence of respiration on temperature, but the sensitivity of predicted carbon pools and fluxes to these formulations and their parameterization is not well understood. Thus, we performed an uncertainty analysis of soil organic matter decomposition with respect to its temperature dependency using the ecosystem model LPJ-GUESS.We used five temperature response functions (Exponential, Arrhenius, Lloyd-Taylor, Gaussian, Van't Hoff). We determined the parameter confidence ranges of the formulations by nonlinear regression analysis based on eight experimental datasets from Northern Hemisphere ecosystems. We sampled over the confidence ranges of the parameters and ran simulations for each pair of temperature response function and calibration site. We analyzed both the long-term and the short-term heterotrophic soil carbon dynamics over a virtual elevation gradient in southern Switzerland.The temperature relationship of Lloyd-Taylor fitted the overall data set best as the other functions either resulted in poor fits (Exponential, Arrhenius) or were not applicable for all datasets (Gaussian, Van't Hoff). There were two main sources of uncertainty for model simulations: (1) the lack of confidence in the parameter estimates of the temperature response, which increased with increasing temperature, and (2) the size of the simulated soil carbon pools, which increased with elevation, as slower turn-over times lead to higher carbon stocks and higher associated uncertainties. Our results therefore indicate that such projections are Correspondence to: A. Wolf (annett.wolf@env.ethz.ch) more uncertain for higher elevations and hence also higher latitudes, which are of key importance for the global terrestrial carbon budget.

Abstract. Models of carbon cycling in terrestrial ecosystems contain formulations for the dependence of respiration on temperature, but the sensitivity of predicted carbon pools and fluxes to these formulations and their parameterization is not understood. Thus, we made an uncertainty analysis of soil organic matter decomposition with respect to its temperature dependency using the ecosystem model LPJ-GUESS. We used five temperature response functions (Exponential, Arrhenius, Lloyd-Taylor, Gaussian, Van't Hoff). We determined the parameter uncertainty ranges of the functions by nonlinear regression analysis based on eight experimental datasets from northern hemisphere ecosystems. We sampled over the uncertainty bounds of the parameters and run simulations for each pair of temperature response function and calibration site. The uncertainty in both long-term and short-term soil carbon dynamics was analyzed over an elevation gradient in southern Switzerland. The function of Lloyd-Taylor turned out to be adequate for modelling the temperature dependency of soil organic matter decomposition, whereas the other functions either resulted in poor fits (Exponential, Arrhenius) or were not applicable for all datasets (Gaussian, Van't Hoff). There were two main sources of uncertainty for model simulations: (1) the uncertainty in the parameter estimates of the response functions, which increased with increasing temperature and (2) the uncertainty in the simulated size of carbon pools, which increased with elevation, as slower turn-over times lead to higher carbon stocks and higher associated uncertainties. The higher uncertainty in carbon pools with slow turn-over rates has important implications for the uncertainty in the projection of the change of soil carbon stocks driven by climate change, which turned out to be more uncertain for higher elevations and hence higher latitudes, which are of key importance for the global terrestrial carbon budget.