Instantaneous Q₁₀ of night‐time leaf respiratory CO₂ efflux:measurement and analytical protocol considerations

The temperature sensitivity (e.g. Q10) of night‐time leaf respiratory CO2 efflux (RCO2) is a fundamental aspect of leaf physiology. The Q10 typically exhibits a dependence on measurement temperature, and it is speculated that this is due to temperature‐dependent shifts in the relative control of leaf RCO2. Two decades ago, a review hypothesized that this mechanistically caused change in values of Q10 is predictable across plant taxa and biomes. Here, we discuss the most appropriate measuring protocol among existing data and for future data collection, to form the foundation for a future mechanistic understanding of Q10 of leaf RCO2 at different temperature ranges. We do this primarily via a review of existing literature on Q10 of night‐time RCO2 and only supplement to a lesser degree with own original data. Based on mechanistic considerations, we encourage that instantaneous Q10 of leaf RCO2 to represent night‐time should be measured: only at night‐time; only in response to short‐term narrow temperature variation (e.g. max. 10°C) to represent a given midpoint temperature at a time; in response to as many temperatures as possible within the chosen temperature range; and on still attached leaves

Does the growth response of woody plants to elevated CO2 increase with temperature? A model-oriented meta-analysis

The temperature dependence of the reaction kinetics of the Rubisco enzyme implies that, at the level of a chloroplast, the response of photosynthesis to rising atmospheric CO2 concentration (Ca) will increase with increasing air temperature. Vegetation models incorporating this interaction predict that the response of net primary productivity (NPP) to elevated CO2 (eCa) will increase with rising temperature and will be substantially larger in warm tropical forests than in cold boreal forests. We tested these model predictions against evidence from eCa experiments by carrying out two meta-analyses. Firstly, we tested for an interaction effect on growth responses in factorial eCa × temperature experiments. This analysis showed a positive, but nonsignificant interaction effect (95% CI for above-ground biomass response = −0.8, 18.0%) between eCa and temperature. Secondly, we tested field-based eCa experiments on woody plants across the globe for a relationship between the eCa effect on plant biomass and mean annual temperature (MAT). This second analysis showed a positive but nonsignificant correlation between the eCa response and MAT. The magnitude of the interactions between CO2 and temperature found in both meta-analyses were consistent with model predictions, even though both analyses gave nonsignificant results. Thus, we conclude that it is not possible to distinguish between the competing hypotheses of no interaction vs. an interaction based on Rubisco kinetics from the available experimental database. Experiments in a wider range of temperature zones are required. Until such experimental data are available, model predictions should aim to incorporate uncertainty about this interaction

Fragmentation-driven divergent trends in burned area in Amazonia and Cerrado

The two major Brazilian biomes, the Amazonia and the Cerrado (savanna), are increasingly exposed to fires. The Amazonian Forest is a fire sensitive ecosystem where fires are a typically rare disturbance while the Cerrado is naturally fire-dependent. Human activities, such as landscape fragmentation and land-use management, have modified the fire regime of the Cerrado and introduced fire into the Amazonian Forest. There is limited understanding of the role of landscape fragmentation on fire occurrence in the Amazonia and Cerrado biomes. Due to differences in vegetation structure, composition, and land use characteristics in each biome, we hypothesize that the emerging burned area (BA) patterns will result from biome-specific fire responses to fragmentation. The aim of this study was to test the general relationship between BA, landscape fragmentation, and agricultural land in the Amazonia and the Cerrado biomes. To estimate the trends and status of landscape fragmentation a Forest Area Density (FAD) index was calculated based on the MapBiomas land cover dataset for both biomes between 2002 and 2018. BA fraction was analyzed within native vegetation against the FAD and agricultural land fraction. Our results showed an increase in landscape fragmentation across 16% of Amazonia and 15% of Cerrado. We identified an opposite relationship between BA fraction, and landscape fragmentation and agricultural fraction contrasting the two biomes. For Amazonia, both landscape fragmentation and agricultural fraction increased BA fraction due to an increase of human ignition activities. For the Cerrado, on the other hand, an increase in landscape fragmentation and agricultural fraction caused a decrease in BA fraction within the native vegetation. For both biomes, we found that during drought years BA increases whilst the divergent trends driven by fragmentation in the two contrasting global biomes is maintained. This understanding will be critical to informing the representation of fire dynamics in fire-enable Dynamic Global Vegetation Models and Earth System Models for climate projection and future ecosystem service provision

Understanding water and energy fluxes in the Amazonia: Lessons from an observation-model intercomparison

Tropical forests are an important part of global water and energy cycles, but the mechanisms that drive seasonality of their land-atmosphere exchanges have proven challenging to capture in models. Here, we (1) report the seasonality of fluxes of latent heat (LE), sensible heat (H), and outgoing short and longwave radiation at four diverse tropical forest sites across Amazonia—along the equator from the Caxiuanã and Tapajós National Forests in the eastern Amazon to a forest near Manaus, and from the equatorial zone to the southern forest in Reserva Jaru; (2) investigate how vegetation and climate influence these fluxes; and (3) evaluate land surface model performance by comparing simulations to observations. We found that previously identified failure of models to capture observed dry-season increases in evapotranspiration (ET) was associated with model overestimations of (1) magnitude and seasonality of Bowen ratios (relative to aseasonal observations in which sensible was only 20%–30% of the latent heat flux) indicating model exaggerated water limitation, (2) canopy emissivity and reflectance (albedo was only 10%–15% of incoming solar radiation, compared to 0.15%–0.22% simulated), and (3) vegetation temperatures (due to underestimation of dry-season ET and associated cooling). These partially compensating model-observation discrepancies (e.g., higher temperatures expected from excess Bowen ratios were partially ameliorated by brighter leaves and more interception/evaporation) significantly biased seasonal model estimates of net radiation (Rn), the key driver of water and energy fluxes (LE ~ 0.6 Rn and H ~ 0.15 Rn), though these biases varied among sites and models. A better representation of energy-related parameters associated with dynamic phenology (e.g., leaf optical properties, canopy interception, and skin temperature) could improve simulations and benchmarking of current vegetation–atmosphere exchange and reduce uncertainty of regional and global biogeochemical models

Aerosol–light interactions reduce the carbon budget imbalance

Current estimates of the global land carbon sink contain substantial uncertainties on interannual timescales which contribute to a non-closure in the global carbon budget (GCB) in any given year. This budget imbalance (BIM) partly arises due to the use of imperfect models which are missing or misrepresenting processes. One such omission is the separate treatment of downward direct and diffuse solar radiation on photosynthesis. Here we evaluate and use an improved high-resolution (6-hourly), gridded dataset of surface solar diffuse and direct fluxes, over 1901–2017, constrained by satellite and ground-level observations, to drive two global land models. Results show that tropospheric aerosol–light interactions have the potential for substantial land carbon impacts (up to 0.4 PgCyr-1 enhanced sink) at decadal timescales, however large uncertainties remain, with models disagreeing on the direction of change in carbon uptake. On interannual timescales, results also show an enhancement of the land carbon sink (up to 0.9 PgCyr-1) and subsequent reduction in BIM by 55% in years following volcanic eruptions. We therefore suggest GCB assessments include this dataset in order to improve land carbon sink estimates

How can the First ISLSCP Field Experiment contribute to present-day efforts to evaluate water stress in JULESv5.0?

The First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE), Kansas, US, 1987–1989, made important contributions to the understanding of energy and CO2 exchanges between the land surface and the atmosphere, which heavily influenced the development of numerical land-surface modelling. Now, 30 years on, we demonstrate how the wealth of data collected during FIFE and its subsequent in-depth analysis in the literature continue to be a valuable resource for the current generation of land-surface models. To illustrate, we use the FIFE dataset to evaluate the representation of water stress on tallgrass prairie vegetation in the Joint UK Land Environment Simulator (JULES) and highlight areas for future development. We show that, while JULES is able to simulate a decrease in net carbon assimilation and evapotranspiration during a dry spell, the shape of the diurnal cycle is not well captured. Evaluating the model parameters and results against this dataset provides a case study on the assumptions in calibrating “unstressed” vegetation parameters and thresholds for water stress. In particular, the responses to low water availability and high temperatures are calibrated separately. We also illustrate the effect of inherent uncertainties in key observables, such as leaf area index, soil moisture and soil properties. Given these valuable lessons, simulations for this site will be a key addition to a compilation of simulations covering a wide range of vegetation types and climate regimes, which will be used to improve the way that water stress is represented within JULES

Vegetation distribution and terrestrial carbon cycle in a carbon cycle configuration of JULES4.6 with new plant functional types

Dynamic global vegetation models (DGVMs) are used for studying historical and future changes to vegetation and the terrestrial carbon cycle. JULES (the Joint UK Land Environment Simulator) represents the land surface in the Hadley Centre climate models and in the UK Earth System Model. Recently the number of plant functional types (PFTs) in JULES was expanded from five to nine to better represent functional diversity in global ecosystems. Here we introduce a more mechanistic representation of vegetation dynamics in TRIFFID, the dynamic vegetation component of JULES, which allows for any number of PFTs to compete based solely on their height; therefore, the previous hardwired dominance hierarchy is removed. With the new set of nine PFTs, JULES is able to more accurately reproduce global vegetation distribution compared to the former five PFT version. Improvements include the coverage of trees within tropical and boreal forests and a reduction in shrubs, the latter of which dominated at high latitudes. We show that JULES is able to realistically represent several aspects of the global carbon (C) cycle. The simulated gross primary productivity (GPP) is within the range of observations, but simulated net primary productivity (NPP) is slightly too high. GPP in JULES from 1982 to 2011 is 133PgCyr−1, compared to observation-based estimates (over the same time period) between 123±8 and 150–175PgCyr−1. NPP from 2000 to 2013 is 72PgCyr−1, compared to satellite-derived NPP of 55PgCyr−1 over the same period and independent estimates of 56.2±14.3PgCyr−1. The simulated carbon stored in vegetation is 542PgC, compared to an observation-based range of 400–600PgC. Soil carbon is much lower (1422PgC) than estimates from measurements ( > 2400PgC), with large underestimations of soil carbon in the tropical and boreal forests. We also examined some aspects of the historical terrestrial carbon sink as simulated by JULES. Between the 1900s and 2000s, increased atmospheric carbon dioxide levels enhanced vegetation productivity and litter inputs into the soils, while land use change removed vegetation and reduced soil carbon. The result is a simulated increase in soil carbon of 57PgC but a decrease in vegetation carbon of 98PgC. The total simulated loss of soil and vegetation carbon due to land use change is 138PgC from 1900 to 2009, compared to a recent observationally constrained estimate of 155±50PgC from 1901 to 2012. The simulated land carbon sink is 2.0±1.0PgCyr−1 from 2000 to 2009, in close agreement with estimates from the IPCC and Global Carbon Project