Climate controls over ecosystem metabolism: insights from a fifteen-year inductive artificial neural network synthesis for a subalpine forest

Eddy covariance (EC) datasets have provided insight into climate determinants of net ecosystem productivity (NEP) and evapotranspiration (ET) in natural ecosystems for decades, but most EC studies were published in serial fashion such that one study's result became the following study's hypothesis. This approach reflects the hypothetico-deductive process by focusing on previously derived hypotheses. A synthesis of this type of sequential inference reiterates subjective biases and may amplify past assumptions about the role, and relative importance, of controls over ecosystem metabolism. Long-term EC datasets facilitate an alternative approach to synthesis: the use of inductive data-based analyses to re-examine past deductive studies of the same ecosystem. Here we examined the seasonal climate determinants of NEP and ET by analyzing a 15-year EC time-series from a subalpine forest using an ensemble of Artificial Neural Networks (ANNs) at the half-day (daytime/nighttime) time-step. We extracted relative rankings of climate drivers and driver-response relationships directly from the dataset with minimal a priori assumptions. The ANN analysis revealed temperature variables as primary climate drivers of NEP and daytime ET, when all seasons are considered, consistent with the assembly of past studies. New relations uncovered by the ANN approach include the role of soil moisture in driving daytime NEP during the snowmelt period, the nonlinear response of NEP to temperature across seasons, and the low relevance of summer rainfall for NEP or ET at the same daytime/nighttime time step. These new results offer a more complete perspective of climate-ecosystem interactions at this site than traditional deductive analyses alone

Disentangling drought-induced variation in ecosystem and soil respiration using stable carbon isotopes

Unger S, Maguas C, Pereira JS, Aires LM, David TS, Werner C. Disentangling drought-induced variation in ecosystem and soil respiration using stable carbon isotopes. Oecologia. 2010;163(4):1043-1057.Combining C flux measurements with information on their isotopic composition can yield a process-based understanding of ecosystem C dynamics. We studied the variations in both respiratory fluxes and their stable C isotopic compositions (delta C-13) for all major components (trees, understory, roots and soil microorganisms) in a Mediterranean oak savannah during a period with increasing drought. We found large drought-induced and diurnal dynamics in isotopic compositions of soil, root and foliage respiration (delta C-13(res)). Soil respiration was the largest contributor to ecosystem respiration (R (eco)), exhibiting a depleted isotopic signature and no marked variations with increasing drought, similar to ecosystem respired delta(CO2)-C-13, providing evidence for a stable C-source and minor influence of recent photosynthate from plants. Short-term and diurnal variations in delta C-13(res) of foliage and roots (up to 8 and 4aEuro degrees, respectively) were in agreement with: (1) recent hypotheses on post-photosynthetic fractionation processes, (2) substrate changes with decreasing assimilation rates in combination with increased respiratory demand, and (3) decreased phosphoenolpyruvate carboxylase activity in drying roots, while altered photosynthetic discrimination was not responsible for the observed changes in delta C-13(res). We applied a flux-based and an isotopic flux-based mass balance, yielding good agreement at the soil scale, while the isotopic mass balance at the ecosystem scale was not conserved. This was mainly caused by uncertainties in Keeling plot intercepts at the ecosystem scale due to small CO2 gradients and large differences in delta C-13(res) of the different component fluxes. Overall, stable isotopes provided valuable new insights into the drought-related variations of ecosystem C dynamics, encouraging future studies but also highlighting the need of improved methodology to disentangle short-term dynamics of isotopic composition of R (eco)