Bernhard Ahrens

Linking variability in soil solution dissolved organic carbon to climate, soil type, and vegetation type

Lateral transport of carbon plays an important role in linking the carbon cycles of terrestrial and aquatic ecosystems. There is, however, a lack of information on the factors controlling one of the main C sources of this lateral flux, i.e., the concentration of dissolved organic carbon (DOC) in soil solution across large spatial scales and under different soil, vegetation, and climate conditions. We compiled a database on DOC in soil solution down to 80 cm and analyzed it with the aim, first, to quantify the differences in DOC concentrations among terrestrial ecosystems, climate zones, soil, and vegetation types at global scale and second, to identify potential determinants of the site-to-site variability of DOC concentration in soil solution across European broadleaved and coniferous forests. We found that DOC concentrations were 75% lower in mineral than in organic soil, and temperate sites showed higher DOC concentrations than boreal and tropical sites. The majority of the variation (R2 = 0.67–0.99) in DOC concentrations in mineral European forest soils correlates with NH4+, C/N, Al, and Fe as the most important predictors. Overall, our results show that the magnitude (23% lower in broadleaved than in coniferous forests) and the controlling factors of DOC in soil solution differ between forest types, with site productivity being more important in broadleaved forests and water balance in coniferous stands.

The use of radiocarbon to constrain current and future soil organic matter turnover and transport in a temperate forest

We investigated the merits of radiocarbon measurements for estimating soil organic matter (SOM) turnover and vertical transport for a temperate deciduous forest in Germany. Eleven parameters, defining decomposition and transport in the soil carbon model SOMPROF, were estimated using a Bayesian approach based on organic carbon measurements and radiocarbon concentration of SOM and heterotrophic respiration. The addition of radiocarbon data had strong effects on the parameters, most importantly a reduction of the decomposition and production rate of the slowest SOM pool by an order of magnitude, and a similar reduction in advective SOM transport. The modified parameters further led to changes in the partitioning of SOM over the different model pools. The calibration results were subsequently used to perform transient soil carbon projections for the period 1901-2100. These simulations were run with parameter sets from calibrations both with and without radiocarbon. The results show an increase over time of topsoil carbon and a decrease in the subsoil, adding to a net gain overall. Near the end of the 21st century, total carbon stocks stabilize and -- for the radiocarbon-constrained model -- start to decrease. However, the changes are small compared to the total stocks. The model results for the calibrations with and without radiocarbon are in general quite similar, but the latter shows notably higher heterotrophic respiration fluxes. Constraining the model with radiocarbon yielded only a small reduction of uncertainty for the total carbon stocks, while for the individual depth compartments, the uncertainty was increased.

Reconcilable differences: a joint calibration of fine-root turnover times with radiocarbon and minirhizotrons

We used bomb-radiocarbon and raw minirhizotron lifetimes of fine roots (< 0.5 mm in diameter) in the organic layer of Norway spruce (Picea abies) forests in southern Sweden to test if different models are able to reconcile the apparently contradicting turnover time estimates from both techniques. We present a framework based on survival functions that is able to jointly model bomb-radiocarbon and minirhizotron data. At the same time we integrate prior knowledge about biases of both techniques--the classification of dead roots in minirhizotrons and the use of carbon reserves to grow new roots. Two-pool models, either in parallel or in serial setting, were able to reconcile the bomb-radiocarbon and minirhizotron data. These models yielded a mean residence time of 3.80 ± 0.16 yr (mean ± SD). On average 60 ± 2% of fine roots turned over within 0.75 ± 0.10 yr, while the rest was turning over within 8.4 ± 0.2 yr. Bomb-radiocarbon and minirhizotron data alone give a biased estimate of fine-root turnover. The two-pool models allow a mechanistic interpretation for the coexistence of fast- and slow-cycling roots--suberization and branching for the serial-two-pool model and branching due to ectomycorrhizal fungi-root interactions for the parallel-two-pool model.

Using near-infrared-enabled digital repeat photography to track structural and physiological phenology in mediterranean tree–grass ecosystems

Tree–grass ecosystems are widely distributed. However, their phenology has not yet been fully characterized. The technique of repeated digital photographs for plant phenology monitoring (hereafter referred as PhenoCam) provide opportunities for long-term monitoring of plant phenology, and extracting phenological transition dates (PTDs, e.g., start of the growing season). Here, we aim to evaluate the utility of near-infrared-enabled PhenoCam for monitoring the phenology of structure (i.e., greenness) and physiology (i.e., gross primary productivity—GPP) at four tree–grass Mediterranean sites. We computed four vegetation indexes (VIs) from PhenoCams: (1) green chromatic coordinates (GCC), (2) normalized difference vegetation index (CamNDVI), (3) near-infrared reflectance of vegetation index (CamNIRv), and (4) ratio vegetation index (CamRVI). GPP is derived from eddy covariance flux tower measurement. Then, we extracted PTDs and their uncertainty from different VIs and GPP. The consistency between structural (VIs) and physiological (GPP) phenology was then evaluated. CamNIRv is best at representing the PTDs of GPP during the Green-up period, while CamNDVI is best during the Dry-down period. Moreover, CamNIRv outperforms the other VIs in tracking growing season length of GPP. In summary, the results show it is promising to track structural and physiology phenology of seasonally dry Mediterranean ecosystem using near-infrared-enabled PhenoCam. We suggest using multiple VIs to better represent the variation of GPP.

Partitioning eddy covariance water flux components using physiological and micrometeorological approaches

Eddy covariance (EC) provides ecosystem-scale estimates of photosynthesis (Ph) and evapotranspiration (ET; the sum of plant transpiration [T] and evaporation [Es]). Separating ET into its components is becoming necessary for linking plant-water use strategies to environmental variability. Based on optimality principles, a data-model based approach for partitioning ET was proposed and independently tested. Short-term responses of canopy-scale internal leaf-to-ambient CO2 (χ) were predicted based on a big-leaf representation of the canopy accounting for the influence of boundary-layer conductance. This representation allowed investigating stomatal behavior in accordance with the Ph estimates. With the objective of minimizing the carbon cost of transpiration, a novel optimization approach was implemented to develop solutions for an optimal stomatal conductance model as the basis to derive T. The Es was then calculated as a residual between the observed ET and modeled T. The proposed method was applied to long-term EC measurements collected above a Mediterranean tree-grass ecosystem. Estimated Es agreed with independent lysimeter measurements (r = 0.69). They also agreed with other partitioning methods derived from similarity theory and conditional sampling applied to turbulence measurements. These similarity schemes appeared to be sensitive to different χ parameterization. Measured Es was underestimated by 30% when χ was assumed constant (= 0.8). Diel and seasonal χ patterns were characterized in response to soil dryness. A surprising result was a large Es/ET throughout the seasons. The robustness of the results provides a new perspective on EC ET partitioning, which can be utilized across a wide range of climates and biomes.