Isolating significant signals from temporal variations in autotrophic and heterotrophic components of ecosystem respiration (Reco) is required to better quantify the temperature sensitivity of the land carbon cycle processes. Here we present diurnal and seasonal patterns in field and model-based components of respiration and investigate their responses to environmental conditions at a dry eucalypt forest, the Cumberland Plain SuperSite of the Australian Terrestrial Ecosystem Research Network. We conducted measurement campaigns of total CO2 flux from the soil surface (Rsoil), soil microbial respiration (Rmicrobe), root respiration (Rroot), litter respiration (Rlitter), and stem respiration (Rstem) in 2018. In total, six infrared gas analyzers with closed, dynamic auto-chambers and six forced diffusion auto-chambers were used for periodic campaigns. Further, Reco and its components were simulated using the Community Atmosphere-Biosphere Land Exchange model (CABLE), constrained by eddy covariance measurements and chamber measurements of Rsoil. A new version of CABLE was implemented with the Dual Arrhenius Michaelis Menten (DAMM) formulation to assess the importance of substrate availability for simulating Rmicrobe. We found that respiration rates showed similar diurnal patterns among the components, showing diurnal hysteresis between respiration components and temperature. In this dry ecosystem, the respiratory components were more responsive to seasonally increasing temperature in wet than in dry periods, and the responses were dependent on atmospheric relative humidity affecting the litter layer moisture content. The temperature sensitivity was significantly higher in Rstem than in other components. Based on observed fluxes of Rmicrobe in trenched plots and Rsoil in intact soil plots, the mean contribution of Rroot to Rsoil was less than 20 % for the dry seasons, while mean Rstem was two times greater than mean Rsoil suggesting that Rstem should be not overlooked in ecosystem flux estimations. This study highlights that partitioning the respiratory components and accounting for their different temperature-responses will be necessary to reduce uncertainty in modelling carbon-climate feedbacks.

Forest carbon and water fluxes are often assumed to be coupled as a result of stomatal regulation during dry conditions. However, recent observations have indicated increased transpiration rates during isolated heat waves across a range of eucalypt species under experimental and natural conditions, with inconsistent effects on photosynthesis (ranging from an increase to a near total decline). To improve the empirical basis for understanding carbon and water fluxes in forests under hotter and drier climates, we measured the water use of dominant trees, and the ecosystem-scale carbon and water exchange in a mature temperate eucalypt forest over three summer seasons. The forest maintained photosynthesis within 16% of peak photosynthesis rates during all conditions, despite up to 70% reductions in canopy conductance during a 5-day heatwave. While carbon and water fluxes both decreased by 16% on exceptionally dry summer days, GPP was sustained at the cost of up to 74% increased water loss on the hottest days and during the heatwave. This led to ~40% variation in ecosystem water use efficiency over the three summers, and ~two-fold differences depending on the way water use efficiency is calculated. Furthermore, the forest became a net source of carbon following a 137% increase in ecosystem respiration during the heat wave, highlighting that the potential for temperate eucalypt forests to remain net carbon sinks under future climates will depend not only on their potential to maintain photosynthesis during higher temperatures, but also on responses of ecosystem respiration to changes in climate.

Grassland responses to drought are strongly mediated by leaf phenology, with greening and browning being highly sensitive to soil moisture. However, this process is represented overly simplistically in most vegetation models, limiting their capacity to predict grassland responses to global change factors. We derive functions representing grassland phenological responses to soil water content (SWC), by fitting an empirical model to greenness data. Data were obtained from fixed cameras (phenocams) monitoring phenology at several grassland experiments in Sydney, Australia. The data-model synthesis showed that the sensitivity of growth to SWC exhibited a concave-down response in most species. For senescence, we found a strong nonlinear increase in senescence rate with declining SWC. Both findings contradict common assumptions in vegetation models. Incorporating nonlinear responses in the empirical model reduced the error in cover predictions by 12%. Model evaluation against data from drought treatments indicated that differential sensitivity of phenology to SWC helps explain differences among species’ responses to variable rainfall. Our work provides a new methodology, and new evidence, to support the development of improved representations of grassland phenology for vegetation models.