MEND model simulations against the experimental dataset used by Stolpovsky et al. (2011).

<p>(a) total live biomass, active and dormant biomass, and active fraction; (b) observed and simulated substrate concentration and prescribed O₂ concentration. There are three manipulations on the substrate and oxygen: (1) at time 0, the substrate (3 mg/L) and O₂ (0.025 mM) are added to the system; (2) after 12 h, the same amount of substrate is injected; (3) at 24 h, additional O₂ (0.04 mM) is injected to the system. The observed concentrations of substrate and total biomass are hourly data interpolated from the original observations in Stolpovsky et al. (2011). We scaled the substrate concentrations (with units of mM in original data) to match the magnitude of biomass concentration in units of mg/L.</p

Active and dormant microbial biomass pools in microbial physiology models (modified from Fig. 2 in Lennon & Jones, 2011).

<p>Active and dormant microbial biomass pools in microbial physiology models (modified from Fig. 2 in Lennon & Jones, 2011).</p

MEND model simulations against the respiration rates due to added ¹⁴C-labeled glucose in Colores et al. [<b>13</b>].

<p>(a) Fitting of the respiration rates in the exponentially-increasing phase using Equation 14, ‘Obs’ and ‘Sim’ denote observed and simulated data, respectively. (b) Fitting of the respiration rates in both exponentially-increasing and non-exponentially-increasing phases using Equation 12. (c) Simulated substrate (<i>S</i>), total live microbial biomass (<i>B</i>), active fraction (<i>r</i>) and substrate saturation level () based on <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0089252#pone.0089252.e027" target="_blank">Equation 12</a>.</p

Steady state active fraction (<i>r^ss</i>) and substrate saturation level () as a function of <i>α</i> and <i>β</i>; <i>α</i> = <i>m_R</i>/(<i>μ_G</i>+<i>m_R</i>), <i>μ_G</i> and <i>m_R</i> (h⁻¹) are maximum specific growth rate and specific maintenance rate for active microbial biomass, respectivly; <i>β</i> denotes the ratio of dormant specific maintenance rate to <i>m_R</i>.

<p>Steady state active fraction (<i>r^ss</i>) and substrate saturation level () as a function of <i>α</i> and <i>β</i>; <i>α</i>  =  <i>m_R</i>/(<i>μ_G</i>+<i>m_R</i>), <i>μ_G</i> and <i>m_R</i> (h⁻¹) are maximum specific growth rate and specific maintenance rate for active microbial biomass, respectivly; <i>β</i> denotes the ratio of dormant specific maintenance rate to <i>m_R</i>.</p

MEND model parameter values used for simulation of the experiment described in Fig. 3 of Stolpovsky et al. (2011).

<p>*Medians and 95% confidence intervals of the fitted values from 100 optimization runs, i.e., 100 different random seeds are used for the stochastic optimization algorithm.</p

Drought impacts on photosynthesis, isoprene emission and atmospheric formaldehyde in a mid-latitude forest

Isoprene plays a critical role in air quality and climate. Photosynthesis (gross primary productivity, GPP) and formaldehyde (HCHO) are both related to isoprene emission at large spatiotemporal scales, but neither is a perfect proxy. We apply multiple satellite products and site-level measurements to examine the impact of water deficit on the three interlinked variables at the Missouri Ozarks site during a 20-day mild dryness stress in summer 2011 and a 3-month severe drought in summer 2012. Isoprene emission shows opposite responses to the short- and long-term droughts, while GPP was substantially reduced in both cases. In 2012, both remote-sensed solar-induced fluorescence (SIF) and satellite HCHO column qualitatively capture reductions in flux-derived GPP and isoprene emission, respectively, on weekly to monthly time scales, but with muted responses. For instance, as flux-derived GPP approaches zero in late summer 2012, SIF drops by 29–33% (July) and 19–27% (August) relative to year 2011. A possible explanation is that electron transport and photosystem activity are maintained to a certain extent under the drought stress. Similarly, flux tower isoprene emissions in July 2012 are 54% lower than July 2011, while the relative reductions in July for 3 independent satellite-derived HCHO data products are 27%, 12% and 6%, respectively. We attribute the muted HCHO response to a photochemical feedback whereby reduced isoprene emission increases the oxidation capacity available to generate HCHO from other volatile organic compound sources. Satellite SIF offers a potential alternative indirect method to monitor isoprene variability at large spatiotemporal scales from space, although further research is needed under different environmental conditions and regions. Our analysis indicates that fairly moderate reductions in satellite SIF and HCHO column may imply severe drought conditions at the surface