Forests play a vital role in atmospheric CO2 sequestration among terrestrial ecosystems, mitigating the greenhouse effect induced by human activity in a changing climate. The LUE (light use efficiency) model is a popular algorithm for calculating terrestrial GPP (gross primary production) based on physiological mechanisms and is easy to implement. Different versions have been applied for many years to simulate the GPP of different ecosystem types at regional or global scales. For estimating forest GPP using different approaches, we implemented five LUE models (EC-LUE, VPM, GOL-PEM, CASA, and C-Fix) in forests of type DBF, EBF, ENF, and MF, using the FLUXNET2015 dataset, remote sensing observations, and Köppen–Geiger climate zones. We then fused these models to additionally improve the ability of the GPP estimation using an RF (random forest) and an SVM (support vector machine). Our results indicated that under a unified parameterization scheme, EC-LUE and VPM yielded the best performance in simulating GPP variations, followed by GLO-PEM, CASA, and C-fix, while MODIS also demonstrated reliable GPP estimation ability. The results of the model fusion across different forest types and flux net sites indicated that the RF could capture more GPP variation magnitudes with higher R2 and lower RMSE than the SVM. Both RF and SVM were validated using cross-validation for all forest types and flux net sites, showing that the accuracy of the GPP simulation could be improved by the RF and SVM by 28% and 27%.

Terrestrial ecosystem respiration increases exponentially with temperature, constituting a positive feedback loop accelerating global warming. However, the response of ecosystem respiration to temperature strongly depends on water availability, yet where and when the water effects are important, is presently poorly constrained, introducing uncertainties in climate-carbon cycle feedback projections. Here, we disentangle the effects of temperature and precipitation (a proxy for water availability) on ecosystem respiration by analysing eddy covariance CO2 flux measurements across 212 globally distributed sites. We reveal a threshold precipitation function, determined by the balance between precipitation and ecosystem water demand, which separates temperature-limited and water-limited respiration. Respiration is temperature limited for precipitation above that threshold function, whereas in drier areas water limitation reduces the temperature sensitivity of respiration and its positive feedback to global warming. If the trend of expansion of water-limited areas with warming climate over the last decades continues, the positive feedback of ecosystem respiration is likely to be weakened and counteracted by the increasing water limitation.

Global soils store more carbon than the atmosphere and terrestrial vegetation combined, with a significant proportion located in colder regions. Earth system models incorporating climate-carbon feedback suggest that a warming climate can potentially destabilize soil carbon storage, leading to carbon release into the atmosphere. However, existing models are based on limited measurements of soil organic carbon (SOC) loss and a comprehensive global-scale climate indices that effectively characterizes climate-SOC relationships is currently lacking. In this study, we present a synthetic analysis that evaluates the effectiveness of different climate indices in estimating SOC stocks using a global compilation of SOC data and the Boltzmann Sigmoidal Model (BSM). Our findings reveal that a climate index, defined as ${\rm TD}\hbox{-}{\rm Index} = {\rm exp}\lpar {-0.002T-0.8D} \rpar$TD-Index=exp(-0.002T-0.8D), where T and D are mean century temperature (MCT) and dryness respectively, serves as the most reliable predictor for SOC stocks. Furthermore, we observed temperature tipping points for SOC, ranging from -4.5 to -3 degrees C for different soil layers. As the temperature transitions from being below to above the tipping point, the SOC shifts from a stable, high state to a rapid decline. An analysis of the projected temperatures for SOC under various future greenhouse gas emissions scenarios showed a northward shift in the northern hemisphere, potentially opening up vast areas of arctic territory to increased SOC loss from the soils, with corresponding emissions of the stored carbon into the atmosphere. Our findings open up new avenues for research on and management strategies for climate-related SOC dynamics.

Terrestrial gross primary production (GPP) represents the magnitude of CO 2 uptake through vegetation photosynthesis, and is a key variable for carbon cycles between the biosphere and atmosphere. Light use efficiency (LUE) models have been widely used to estimate GPP for its physiological mechanisms and availability of data acquisition and implementation, yet each individual GPP model has exhibited large uncertainties due to input errors and model structure, and further studies of systematic validation, comparison, and fusion of those models with eddy covariance (EC) site data across diverse ecosystem types are still needed in order to further improve GPP estimation. We here compared and fused five GPP models (VPM, EC‐LUE, GOL‐PEM, CHJ, and C‐Fix) across eight ecosystems based on FLUXNET2015 data set using the ensemble methods of Bayesian Model Averaging (BMA), Support Vector Machine (SVM), and Random Forest (RF) separately. Our results showed that for individual models, EC‐LUE gave a better performance to capture interannual variability of GPP than other models, followed by VPM and GLO‐PEM, while CHJ and C‐Fix were more limited in their estimation performance. We found RF and SVM were superior to BMA on merging individual models at various plant functional types (PFTs) and at the scale of individual sites. On the basis of individual models, the fusion methods of BMA, SVM, and RF were examined by a five‐fold cross validation for each ecosystem type, and each method successfully improved the average accuracy of estimation by 8%, 18%, and 19%, respectively.

Nearly 70% of Earth's terrestrial surface is covered with hills and mountains, which substantially affect many aspects of air motion, moisture properties, and the land-surface exchange with the atmosphere. In this chapter, we elaborate key physics of persistent phenomena associated with hills and mountains focusing on answers to questions: (1) why are the windward sides of mountains wet (or green) and the leeward sides dry (or barren)? (2) what are the major controls of slope flows? (3) why do instruments above the canopy on a slope fail to account for the processes within the canopy? and (4) what is recirculation and what influence does it have on land-atmosphere exchanges?

Canopy flow resulting from interaction between thermo-topographic slope flow and large-scale synoptic flow is very complicated and has been poorly understood. We apply a Reynolds-averaged Navier-Stokes (RANS) turbulence model to investigate how the interactions between local flow and synoptic winds affect CO2 movement in the canopy layer at the Renon site in the Italian Alps. Since the RANS simulations are compared to the data measured by multiple-tower experiments conducted during CarboEurope-IP advection campaigns (ADVEX) at Renon, our study can be viewed as a case study of a relatively common wooded slope. The thermal condition in the canopy is directly related to the canopy morphology: the dense canopy at our site causes stronger cooling but limits vertical exchange of heat flux, resulting in weak temperature inversion in the deep canopy. Under conditions with no synoptic wind, local flow leads to CO2 build-up mainly at downslope locations and no recirculation is formed. Recirculation that holds high CO2 mole fraction in the canopy is developed only under the condition that local slope wind is enhanced by northerly synoptic winds. No recirculation forms when southerly synoptic wind direction is opposite to the local wind direction, in which case CO2 is quite well mixed. This numerical study approach brings to light a better understanding of the CO2 closure problem: the measured net ecosystem exchange of CO2 is more likely to be underestimated in local non-synoptic slope flow and local synoptic-enhanced slope flow regimes at Renon. However, small-scale heterogeneity in canopy structure, variability in the CO2 source from soil and higher-resolution and larger-scale topography still challenge the application of this numerical approach in the FLUXNET community. (C) 2017 Elsevier B.V. All rights reserved.

This study generated eddy covariance data to investigate atmospheric dynamics leeward of a small, forested hillside in upstate New York. The causes and effects of recirculation eddies were examined to support the larger goal of improving measurement of the exchange of energy, moisture, and trace gases between the terrestrial biosphere and the atmosphere over complex terrain. Sensors operated at five different altitudes on two separate towers—one at the top of the hill and one down the slope to the east—for approximately 8 weeks in the spring of 2013. During the experiment, the vertical potential temperature gradient was found to be the primary factor for determining whether winds interacting with the terrain features caused a recirculating eddy leeward of the hill. The study found evidence that the recirculation influenced carbon dioxide flux and caused the air column to be vertically well mixed.