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Temperate forest ecosystems have recently been identified as an important net sink in the global carbon budget. The factors responsible for the strength of the sinks and their permanence, however, are less evident. In this paper, we quantify the present carbon sequestration in Thuringian managed coniferous forests. We quantify the effects of indirect human-induced environmental changes (increasing temperature, increasing atmospheric CO2 concentration and nitrogen fertilization), during the last century using BIOME-BGC, as well as the legacy effect of the current age-class distribution (forest inventories and BIOME-BGC). We focused on coniferous forests because these forests represent a large area of central European forests and detailed forest inventories were available. The model indicates that environmental changes induced an increase in biomass C accumulation for all age classes during the last 20 years (1982–2001). Young and old stands had the highest changes in the biomass C accumulation during this period. During the last century mature stands (older than 80 years) turned from being almost carbon neutral to carbon sinks. In high elevations nitrogen deposition explained most of the increase of net ecosystem production (NEP) of forests. CO2 fertilization was the main factor increasing NEP of forests in the middle and low elevations. According to the model, at present, total biomass C accumulation in coniferous forests of Thuringia was estimated at 1.51 t C ha−1 yr−1 with an averaged annual NEP of 1.42 t C ha−1 yr−1 and total net biome production of 1.03 t C ha−1 yr−1 (accounting for harvest). The annual averaged biomass carbon balance (BCB: biomass accumulation rate-harvest) was 1.12 t C ha−1 yr−1 (not including soil respiration), and was close to BCB from forest inventories (1.15 t C ha−1 yr−1). Indirect human impact resulted in 33% increase in modeled biomass carbon accumulation in coniferous forests in Thuringia during the last century. From the forest inventory data we estimated the legacy effect of the age-class distribution to account for 17% of the inventory-based sink. Isolating the environmental change effects showed that these effects can be large in a long-term, managed conifer forest. [ABSTRACT FROM AUTHOR]

When planning sampling in an experiment where soil organic carbon (SOC) content is expected to change, it is necessary to know how many samples will need to be taken to demonstrate a change in Soc and after how long this change will be detectable. Much has been published on the number of samples required to demonstrate the minimum detectable difference in SOC. but less on how long it takes for this change to be detectable. In this paper, a model of SOC dynamics is used to estimate the minimum time taken for a change in total SOC content to become measurable under different carbon inputs, land uses and soil types. For free air carbon dioxide enrichment (FACE), and other experiments in which SOC is expected to increase, relationships between the percentage change in C inputs and the time taken to measure a change in SOC are presented, for two levels of sampling intensity corresponding to the maximum that is practically possible in most experiments (∼100 samples) and that used regularly in field experiments (10-20 samples). In FACE experiments, where C inputs increase by a maximum of about 20-25%, SOC change could be detected with 90% confidence after about 6-10 years if a sampling regime allowing 3% change in background SOC level (probably requiring a very large number of samples) were used, but could not be detected at all if a sampling regime were used that allowed only a 15% change in background SOC to be detected. If increases in C inputs are much below 15%, it might not be possible to detect a change in soil C without an enormous number of samples. Relationships between the change in C inputs and the time taken to measure a change in SOC are robust over a range of soil types and land uses. The results demonstrate how models of SOC dynamics can be used to complement statistical power analyses for planning when, and how intensively, to sample soils during experiments. An advantage of the modelling approach demonstrated here is that estimates of the minimum time taken for a change in soil carbon to become detectable can be made, even before any detailed soil samples are taken, simply from estimates of the likely increase in carbon inputs to the soil (via expected changes in net primary production). [ABSTRACT FROM AUTHOR]