Temperature responses of photosynthesis and respiration in evergreen trees from boreal to tropical latitudes

Evergreen species are widespread across the globe, representing two major plant functional forms in terrestrial models. We reviewed and analysed the responses of photosynthesis and respiration to warming in 101 evergreen species from boreal to tropical biomes. Summertime temperatures affected both latitudinal gas exchange rates and the degree of responsiveness to experimental warming. The decrease in net photosynthesis at 25 degrees C (A(net25)) was larger with warming in tropical climates than cooler ones. Respiration at 25 degrees C (R-25) was reduced by 14% in response to warming across species and biomes. Gymnosperms were more sensitive to greater amounts of warming than broadleaved evergreens, with A(net25) and R-25 reduced c. 30-40% with > 10 degrees C warming. While standardised rates of carboxylation (V-cmax25) and electron transport (J(max25)) adjusted to warming, the magnitude of this adjustment was not related to warming amount (range 0.6-16 degrees C). The temperature optimum of photosynthesis (T-optA) increased on average 0.34 degrees C per degrees C warming. The combination of more constrained acclimation of photosynthesis and increasing respiration rates with warming could possibly result in a reduced carbon sink in future warmer climates. The predictable patterns of thermal acclimation across biomes provide a strong basis to improve modelling predictions of the future terrestrial carbon sink with warming

Examining the sensitivity of the terrestrial carbon cycle to the expression of El Niño

The El Niño - Southern Oscillation (ENSO) influences the global climate and the variability in the terrestrial carbon cycle on interannual timescales. Two different expressions of El Niño have recently been identified: (i) central Pacific (CP) and (ii) eastern Pacific (EP). Both types of El Niño are characterised by above-average sea surface temperature anomalies at the respective locations. Studies exploring the impact of these expressions of El Niño on the carbon cycle have identified changes in the amplitude of the concentration of interannual atmospheric carbon dioxide (CO2) variability following increased tropical near-surface air temperature and decreased precipitation. We employ the dynamic global vegetation model LPJ-GUESS (Lund-Potsdam-Jena General Ecosystem Simulator) within a synthetic experimental framework to examine the sensitivity and potential long-term impacts of these two expressions of El Niño on the terrestrial carbon cycle. We manipulated the occurrence of CP and EP events in two climate reanalysis datasets during the latter half of the 20th and early 21st century by replacing all EP with CP and separately all CP with EP El Niño events. We found that the different expressions of El Niño affect interannual variability in the terrestrial carbon cycle. However, the effect on longer timescales was small for both climate reanalysis datasets. We conclude that capturing any future trends in the relative frequency of CP and EP El Niño events may not be critical for robust simulations of the terrestrial carbon cycle

Decoupling between ecosystem photosynthesis and transpiration: a last resort against overheating

Ecosystems are projected to face extreme high temperatures more frequently in the near future. Various biotic coping strategies exist to prevent heat stress. Controlled experiments have recently provided evidence for continued transpiration in woody plants during high air temperatures, even when photosynthesis is inhibited. Such a decoupling of photosynthesis and transpiration would represent an effective strategy (‘known as leaf or canopy cooling’) to prevent lethal leaf temperatures. At the ecosystem scale, continued transpiration might dampen the development and propagation of heat extremes despite further desiccating soils. However, at the ecosystem scale, evidence for the occurrence of this decoupling is still limited. Here, we aim to investigate this mechanism using eddy-covariance data of thirteen woody ecosystems located in Australia and a causal graph discovery algorithm. Working at half-hourly time resolution, we find evidence for a decoupling of photosynthesis and transpiration in four ecosystems which can be classified as Mediterranean woodlands. The decoupling occurred at air temperatures above 35 °C. At the nine other investigated woody sites, we found that vegetation CO2 exchange remained coupled to transpiration at the observed high air temperatures. Ecosystem characteristics suggest that the canopy energy balance plays a crucial role in determining the occurrence of a decoupling. Our results highlight the value of causal-inference approaches for the analysis of complex physiological processes. With regard to projected increasing temperatures and especially extreme events in future climates, further vegetation types might be pushed to threatening canopy temperatures. Our findings suggest that the coupling of leaf-level photosynthesis and stomatal conductance, common in land surface schemes, may need be re-examined when applied to high-temperature events

Evaluation of the CABLEv2.3.4 land surface model coupled to NU‐WRFv3.9.1.1 in simulating temperature and precipitation means and extremes over CORDEX AustralAsia within a WRF physics ensemble

The Community Atmosphere Biosphere Land Exchange (CABLE) model is a third‐generation land surface model (LSM). CABLE is commonly used as a stand‐alone LSM, coupled to the Australian Community Climate and Earth Systems Simulator global climate model and coupled to the Weather Research and Forecasting (WRF) model for regional applications. Here, we evaluate an updated version of CABLE within a WRF physics ensemble over the COordinated Regional Downscaling EXperiment (CORDEX) AustralAsia domain. The ensemble consists of different cumulus, radiation and planetary boundary layer (PBL) schemes. Simulations are carried out within the NASA Unified WRF modeling framework, NU‐WRF. Our analysis did not identify one configuration that consistently performed the best for all diagnostics and regions. Of the cumulus parameterizations the Grell‐Freitas cumulus scheme consistently overpredicted precipitation, while the new Tiedtke scheme was the best in simulating the timing of precipitation events. For the radiation schemes, the RRTMG radiation scheme had a general warm bias. For the PBL schemes, the YSU scheme had a warm bias, and the MYJ PBL scheme a cool bias. Results are strongly dependent on the region of interest, with the northern tropics and southwest Western Australia being more sensitive to the choice of physics options compared to southeastern Australia which showed less overall variation and overall better performance across the ensemble. Comparisons with simulations using the Unified Noah LSM showed that CABLE in NU‐WRF has a more realistic simulation of evapotranspiration when compared to GLEAM estimates

Applying the concept of ecohydrological equilibrium to predict steady state leaf area index

Leaf area index (LAI) is a key variable in modeling terrestrial vegetation because it has a major impact on carbon and water fluxes. However, several recent intercomparisons have shown that modeled LAI differs significantly among models and between models and satellite‐derived estimates. Empirical studies show that LAI is strongly related to precipitation. This observation is predicted by the ecohydrological equilibrium theory, which provides an alternative means to predict steady state LAI. We implemented this theory in a simple optimization model. We hypothesized that, when water availability is limited, plants should adjust steady state LAI and stomatal behavior to maximize net canopy carbon export, under the constraint that canopy transpiration is a fixed fraction of total precipitation. We evaluated the predicted LAI (Lopt) for Australia against ground‐based observations of LAI at 135 sites and continental‐scale satellite‐derived estimates. For the site‐level data, the root‐mean‐square error of predicted Lopt was 1.07 m2 m−2, similar to the root‐mean‐square error of a comparison of the data against 9‐year mean satellite‐derived LAI (Lsat) at those sites. Continentally, Lopt had an R2 of 0.7 when compared to Lsat. The predicted Lopt increased continental‐wide with rising atmospheric [CO2] over 1982–2010, which agreed with satellite‐derived estimations, while the predicted stomatal behavior responded differently in dry and wet regions. Our results indicate that long‐term equilibrium LAI can be successfully predicted from a simple application of ecohydrological theory. We suggest that this theory could be usefully incorporated into terrestrial vegetation models to improve their predictions of LAI

Quantifying land surface temperature variability for two Sahelian mesoscale regions during the wet season

Land-atmosphere feedbacks play an important role in the weather and climate of many semi-arid regions. These feedbacks are strongly controlled by how the surface responds to precipitation events, which regulate the return of heat and moisture to the atmosphere. Characteristics of the surface can result in both differing amplitudes and rates of warming following rain. We used spectral analysis to quantify these surface responses to rainfall events using land surface temperature (LST) derived from Earth Observations (EO). We analysed two mesoscale regions in the Sahel and identified distinct differences in the strength of the short-term (< 5–day) spectral variance, notably a shift towards lower frequency variability in forest pixels relative to non-forest areas, and an increase in amplitude with decreasing vegetation cover. Consistent with these spectral signatures, we found that areas of forest, and to a lesser extent grassland regions, warm up more slowly than sparsely vegetated or barren pixels. We applied the same spectral analysis method to simulated LST data from the the Joint UK Land Environment Simulator (JULES) land surface model. We found a reasonable level of agreement with the EO spectral analysis, for two contrasting land surface regions. However JULES shows a significant underestimate in the magnitude of the observed response to rain compared to EO. A sensitivity analysis of the JULES model highlights an unrealistically high level of soil water availability as a key deficiency, which dampens the models response to rainfall events