Maximum carbon uptake rate dominates the interannual variability of global net ecosystem exchange

Terrestrial ecosystems contribute most of the interannual variability (IAV) in atmospheric carbon dioxide (CO₂) concentrations, but processes driving the IAV of net ecosystem CO₂ exchange (NEE) remain elusive. For a predictive understanding of the global C cycle, it is imperative to identify indicators associated with ecological processes that determine the IAV of NEE. Here, we decompose the annual NEE of global terrestrial ecosystems into their phenological and physiological components, namely maximum carbon uptake (MCU) and release (MCR), the carbon uptake period (CUP), and two parameters, α and β, that describe the ratio between actual versus hypothetical maximum C sink and source, respectively. Using long‐term observed NEE from 66 eddy covariance sites and global products derived from FLUXNET observations, we found that the IAV of NEE is determined predominately by MCU at the global scale, which explains 48% of the IAV of NEE on average while α, CUP, β, and MCR explain 14%, 25%, 2%, and 8%, respectively. These patterns differ in water‐limited ecosystems versus temperature‐ and radiation‐limited ecosystems; 31% of the IAV of NEE is determined by the IAV of CUP in water‐limited ecosystems, and 60% of the IAV of NEE is determined by the IAV of MCU in temperature‐ and radiation‐limited ecosystems. The Lund‐Potsdam‐Jena (LPJ) model and the Multi‐scale Synthesis and Terrestrial Model Inter‐comparison Project (MsTMIP) models underestimate the contribution of MCU to the IAV of NEE by about 18% on average, and overestimate the contribution of CUP by about 25%. This study provides a new perspective on the proximate causes of the IAV of NEE, which suggest that capturing the variability of MCU is critical for modeling the IAV of NEE across most of the global land surface.     

Interannual variability in carbon dioxide fluxes and flux–climate relationships on grazed and ungrazed northern mixed-grass prairie

The annual carbon (C) budget of grasslands is highly dynamic, dependent on grazing history and on effects of interannual variability (IAV) in climate on carbon dioxide (CO₂) fluxes. Variability in climatic drivers may directly affect fluxes, but also may indirectly affect fluxes by altering the response of the biota to the environment, an effect termed ‘functional change’. We measured net ecosystem exchange of CO₂ (NEE) and its diurnal components, daytime ecosystem CO₂ exchange (P_D) and night‐time respiration (R_E), on grazed and ungrazed mixed‐grass prairie in North Dakota, USA, for five growing seasons. Our primary objective was to determine how climatic anomalies influence variability in CO₂ exchange. We used regression analysis to distinguish direct effects of IAV in climate on fluxes from functional change. Functional change was quantified as the improvement in regression on fitting a model in which slopes of flux–climate relationships vary among years rather than remain invariant. Functional change and direct effects of climatic variation together explained about 20% of variance in weekly means of NEE, P_D, and R_E. Functional change accounted for more than twice the variance in fluxes of direct effects of climatic variability. Grazing did not consistently influence the contribution of functional change to flux variability, but altered which environmental variable best explained year‐to‐year differences in flux–climate slopes, reduced IAV in seasonal means of fluxes, lessened the strength of flux–climate correlations, and increased NEE by reducing R_E relatively more than P_D. Most of these trends are consistent with the interpretation that grazing reduced the influence of plants on ecosystem fluxes. Because relationships between weekly values of fluxes and climatic regulators changed annually, year‐to‐year differences in the C balance of these ecosystems cannot be predicted from knowledge of IAV in climate alone.     

Climatic and biotic controls on annual carbon storage in Amazonian ecosystems

• 1 The role of undisturbed tropical land ecosystems in the global carbon budget is not well understood. It has been suggested that interannual climate variability can affect the capacity of these ecosystems to store carbon in the short term. In this paper, we use a transient version of the Terrestrial Ecosystem Model (TEM) to estimate annual carbon storage in undisturbed Amazonian ecosystems during the period 1980–94, and to understand the underlying causes of the year‐to‐year variations in net carbon storage for this region.
  • 2 We estimate that the total carbon storage in the undisturbed ecosystems of the Amazon Basin in 1980 was 127.6 Pg C, with about 94.3 Pg C in vegetation and 33.3 Pg C in the reactive pool of soil organic carbon. About 83% of the total carbon storage occurred in tropical evergreen forests. Based on our model’s results, we estimate that, over the past 15 years, the total carbon storage has increased by 3.1 Pg C (+ 2%), with a 1.9‐Pg C (+2%) increase in vegetation carbon and a 1.2‐Pg C (+4%) increase in reactive soil organic carbon. The modelled results indicate that the largest relative changes in net carbon storage have occurred in tropical deciduous forests, but that the largest absolute changes in net carbon storage have occurred in the moist and wet forests of the Basin.
    • 3 Our results show that the strength of interannual variations in net carbon storage of undisturbed ecosystems in the Amazon Basin varies from a carbon source of 0.2 Pg C/year to a carbon sink of 0.7 Pg C/year. Precipitation, especially the amount received during the drier months, appears to be a major controller of annual net carbon storage in the Amazon Basin. Our analysis indicates further that changes in precipitation combine with changes in temperature to affect net carbon storage through influencing soil moisture and nutrient availability.
      • 4 On average, our results suggest that the undisturbed Amazonian ecosystems accumulated 0.2 Pg C/year as a result of climate variability and increasing atmospheric CO₂ over the study period. This amount is large enough to have compensated for most of the carbon losses associated with tropical deforestation in the Amazon during the same period.
        • 5 Comparisons with empirical data indicate that climate variability and CO₂ fertilization explain most of the variation in net carbon storage for the undisturbed ecosystems. Our analyses suggest that assessment of the regional carbon budget in the tropics should be made over at least one cycle of El Niño–Southern Oscillation because of interannual climate variability. Our analyses also suggest that proper scaling of the site‐specific and subannual measurements of carbon fluxes to produce Basin‐wide flux estimates must take into account seasonal and spatial variations in net carbon storage.

     

How uncertainties in future climate change predictions translate into future terrestrial carbon fluxes

We forced a global terrestrial carbon cycle model by climate fields of 14 ocean and atmosphere general circulation models (OAGCMs) to simulate the response of terrestrial carbon pools and fluxes to climate change over the next century. These models participated in the second phase of the Coupled Model Intercomparison Project (CMIP2), where a 1% per year increase of atmospheric CO₂ was prescribed. We obtain a reduction in net land uptake because of climate change ranging between 1.4 and 5.7 Gt C yr^?1 at the time of atmospheric CO₂ doubling. Such a reduction in terrestrial carbon sinks is largely dominated by the response of tropical ecosystems, where soil water stress occurs. The uncertainty in the simulated land carbon cycle response is the consequence of discrepancies in land temperature and precipitation changes simulated by the OAGCMs. We use a statistical approach to assess the coherence of the land carbon fluxes response to climate change. The biospheric carbon fluxes and pools changes have a coherent response in the tropics, in the Mediterranean region and in high latitudes of the Northern Hemisphere. This is because of a good coherence of soil water content change in the first two regions and of temperature change in the high latitudes of the Northern Hemisphere. Then we evaluate the carbon uptake uncertainties to the assumptions on plant productivity sensitivity to atmospheric CO₂ and on decomposition rate sensitivity to temperature. We show that these uncertainties are on the same order of magnitude than the uncertainty because of climate change. Finally, we find that the OAGCMs having the largest climate sensitivities to CO₂ are the ones with the largest soil drying in the tropics, and therefore with the largest reduction of carbon uptake.     

A dynamic global vegetation model for use with climate models: concepts and description of simulated vegetation dynamics

Changes in vegetation structure and biogeography due to climate change feedback to alter climate by changing fluxes of energy, moisture, and momentum between land and atmosphere. While the current class of land process models used with climate models parameterizes these fluxes in detail, these models prescribe surface vegetation and leaf area from data sets. In this paper, we describe an approach in which ecological concepts from a global vegetation dynamics model are added to the land component of a climate model to grow plants interactively. The vegetation dynamics model is the Lund–Potsdam–Jena (LPJ) dynamic global vegetation model. The land model is the National Center for Atmospheric Research (NCAR) Land Surface Model (LSM). Vegetation is defined in terms of plant functional types. Each plant functional type is represented by an individual plant with the average biomass, crown area, height, and stem diameter (trees only) of its population, by the number of individuals in the population, and by the fractional cover in the grid cell. Three time‐scales (minutes, days, and years) govern the processes. Energy fluxes, the hydrologic cycle, and carbon assimilation, core processes in LSM, occur at a 20 min time step. Instantaneous net assimilated carbon is accumulated annually to update vegetation once a year. This is carried out with the addition of establishment, resource competition, growth, mortality, and fire parameterizations from LPJ. The leaf area index is updated daily based on prevailing environmental conditions, but the maximum value depends on the annual vegetation dynamics. The coupling approach is successful. The model simulates global biogeography, net primary production, and dynamics of tundra, boreal forest, northern hardwood forest, tropical rainforest, and savanna ecosystems, which are consistent with observations. This suggests that the model can be used with a climate model to study biogeophysical feedbacks in the climate system related to vegetation dynamics.     

Divergent apparent temperature sensitivity of terrestrial ecosystem respiration

Aims Recent studies revealed convergent temperature sensitivity of ecosystem respiration (R e) within aquatic ecosystems and between terrestrial and aquatic ecosystems. We do not know yet whether various terrestrial ecosystems have consistent or divergent temperature sensitivity. Here, we synthesized 163 eddy covariance flux sites across the world and examined the global variation of the apparent activation energy (Ea), which characterizes the apparent temperature sensitivity of and its interannual variability (IAV) as well as their controlling factors.Methods We used carbon fluxes and meteorological data across FLUXNET sites to calculate mean annual temperature, temperature range, precipitation, global radiation, potential radiation, gross primary productivity and R e by averaging the daily values over the years in each site. Furthermore, we analyzed the sites with>8 years data to examine the IAV of Ea and calculated the standard deviation of Ea across years at each site to characterize IAV.Important findings The results showed a widely global variation of Ea, with significantly lower values in the tropical and subtropical areas than in temperate and boreal areas, and significantly higher values in grasslands and wetlands than that in deciduous broadleaf forests and evergreen forests. Globally, spatial variations of Ea were explained by changes in temperature and an index of water availability with differing contribution of each explaining variable among climate zones and biomes. IAV and the corresponding coefficient of variation of Ea decreased with increasing latitude, but increased with radiation and corresponding mean annual temperature. The revealed patterns in the spatial and temporal variations of Ea and its controlling factors indicate divergent temperature sensitivity of R e, which could help to improve our predictive understanding of R e in response to climate change.     

FLUXNET and modelling the global carbon cycle

Measurements of the net CO₂ flux between terrestrial ecosystems and the atmosphere using the eddy covariance technique have the potential to underpin our interpretation of regional CO₂ source–sink patterns, CO₂ flux responses to forcings, and predictions of the future terrestrial C balance. Information contained in FLUXNET eddy covariance data has multiple uses for the development and application of global carbon models, including evaluation/validation, calibration, process parameterization, and data assimilation. This paper reviews examples of these uses, compares global estimates of the dynamics of the global carbon cycle, and suggests ways of improving the utility of such data for global carbon modelling. Net ecosystem exchange of CO₂ (NEE) predicted by different terrestrial biosphere models compares favourably with FLUXNET observations at diurnal and seasonal timescales. However, complete model validation, particularly over the full annual cycle, requires information on the balance between assimilation and decomposition processes, information not readily available for most FLUXNET sites. Site history, when known, can greatly help constrain the model‐data comparison. Flux measurements made over four vegetation types were used to calibrate the land‐surface scheme of the Goddard Institute for Space Studies global climate model, significantly improving simulated climate and demonstrating the utility of diurnal FLUXNET data for climate modelling. Land‐surface temperatures in many regions cool due to higher canopy conductances and latent heat fluxes, and the spatial distribution of CO₂ uptake provides a significant additional constraint on the realism of simulated surface fluxes. FLUXNET data are used to calibrate a global production efficiency model (PEM). This model is forced by satellite‐measured absorbed radiation and suggests that global net primary production (NPP) increased 6.2% over 1982–1999. Good agreement is found between global trends in NPP estimated by the PEM and a dynamic global vegetation model (DGVM), and between the DGVM and estimates of global NEE derived from a global inversion of atmospheric CO₂ measurements. Combining the PEM, DGVM, and inversion results suggests that CO₂ fertilization is playing a major role in current increases in NPP, with lesser impacts from increasing N deposition and growing season length. Both the PEM and the inversion identify the Amazon basin as a key region for the current net terrestrial CO₂ uptake (i.e. 33% of global NEE), as well as its interannual variability. The inversion's global NEE estimate of −1.2 Pg [C] yr⁻¹ for 1982–1995 is compatible with the PEM‐ and DGVM‐predicted trends in NPP. There is, thus, a convergence in understanding derived from process‐based models, remote‐sensing‐based observations, and inversion of atmospheric data. Future advances in field measurement techniques, including eddy covariance (particularly concerning the problem of night‐time fluxes in dense canopies and of advection or flow distortion over complex terrain), will result in improved constraints on land‐atmosphere CO₂ fluxes and the rigorous attribution of mechanisms to the current terrestrial net CO₂ uptake and its spatial and temporal heterogeneity. Global ecosystem models play a fundamental role in linking information derived from FLUXNET measurements to atmospheric CO₂ variability. A number of recommendations concerning FLUXNET data are made, including a request for more comprehensive site data (particularly historical information), more measurements in undisturbed ecosystems, and the systematic provision of error estimates. The greatest value of current FLUXNET data for global carbon cycle modelling is in evaluating process representations, rather than in providing an unbiased estimate of net CO₂ exchange.     

Effects of 21st‐century climate,land use,and disturbances on ecosystem carbon balance in California

Terrestrial ecosystems are an important sink for atmospheric carbon dioxide (CO₂), sequestering ~30% of annual anthropogenic emissions and slowing the rise of atmospheric CO₂. However, the future direction and magnitude of the land sink is highly uncertain. We examined how historical and projected changes in climate, land use, and ecosystem disturbances affect the carbon balance of terrestrial ecosystems in California over the period 2001–2100. We modeled 32 unique scenarios, spanning 4 land use and 2 radiative forcing scenarios as simulated by four global climate models. Between 2001 and 2015, carbon storage in California's terrestrial ecosystems declined by ?188.4 Tg C, with a mean annual flux ranging from a source of ?89.8 Tg C/year to a sink of 60.1 Tg C/year. The large variability in the magnitude of the state's carbon source/sink was primarily attributable to interannual variability in weather and climate, which affected the rate of carbon uptake in vegetation and the rate of ecosystem respiration. Under nearly all future scenarios, carbon storage in terrestrial ecosystems was projected to decline, with an average loss of ?9.4% (?432.3 Tg C) by the year 2100 from current stocks. However, uncertainty in the magnitude of carbon loss was high, with individual scenario projections ranging from ?916.2 to 121.2 Tg C and was largely driven by differences in future climate conditions projected by climate models. Moving from a high to a low radiative forcing scenario reduced net ecosystem carbon loss by 21% and when combined with reductions in land‐use change (i.e., moving from a high to a low land‐use scenario), net carbon losses were reduced by 55% on average. However, reconciling large uncertainties associated with the effect of increasing atmospheric CO₂ is needed to better constrain models used to establish baseline conditions from which ecosystem‐based climate mitigation strategies can be evaluated.     

Interannual variability in global soil respiration, 1980–94

We used a climate‐driven regression model to develop spatially resolved estimates of soil‐CO₂ emissions from the terrestrial land surface for each month from January 1980 to December 1994, to evaluate the effects of interannual variations in climate on global soil‐to‐atmosphere CO₂ fluxes. The mean annual global soil‐CO₂ flux over this 15‐y period was estimated to be 80.4 (range 79.3–81.8) Pg C. Monthly variations in global soil‐CO₂ emissions followed closely the mean temperature cycle of the Northern Hemisphere. Globally, soil‐CO₂ emissions reached their minima in February and peaked in July and August. Tropical and subtropical evergreen broad‐leaved forests contributed more soil‐derived CO₂ to the atmosphere than did any other vegetation type (～30% of the total) and exhibited a biannual cycle in their emissions. Soil‐CO₂ emissions in other biomes exhibited a single annual cycle that paralleled the seasonal temperature cycle. Interannual variability in estimated global soil‐CO₂ production is substantially less than is variability in net carbon uptake by plants (i.e., net primary productivity). Thus, soils appear to buffer atmospheric CO₂ concentrations against far more dramatic seasonal and interannual differences in plant growth. Within seasonally dry biomes (savannas, bushlands and deserts), interannual variability in soil‐CO₂ emissions correlated significantly with interannual differences in precipitation. At the global scale, however, annual soil‐CO₂ fluxes correlated with mean annual temperature, with a slope of 3.3 Pg C y^?1 per °C. Although the distribution of precipitation influences seasonal and spatial patterns of soil‐CO₂ emissions, global warming is likely to stimulate CO₂ emissions from soils.     

Evaluation of the terrestrial carbon cycle, future plant geography and climate-carbon cycle feedbacks using five Dynamic Global Vegetation Models (DGVMs)

This study tests the ability of five Dynamic Global Vegetation Models (DGVMs), forced with observed climatology and atmospheric CO₂, to model the contemporary global carbon cycle. The DGVMs are also coupled to a fast ‘climate analogue model’, based on the Hadley Centre General Circulation Model (GCM), and run into the future for four Special Report Emission Scenarios (SRES): A1FI, A2, B1, B2. Results show that all DGVMs are consistent with the contemporary global land carbon budget. Under the more extreme projections of future environmental change, the responses of the DGVMs diverge markedly. In particular, large uncertainties are associated with the response of tropical vegetation to drought and boreal ecosystems to elevated temperatures and changing soil moisture status. The DGVMs show more divergence in their response to regional changes in climate than to increases in atmospheric CO₂ content. All models simulate a release of land carbon in response to climate, when physiological effects of elevated atmospheric CO₂ on plant production are not considered, implying a positive terrestrial climate‐carbon cycle feedback. All DGVMs simulate a reduction in global net primary production (NPP) and a decrease in soil residence time in the tropics and extra‐tropics in response to future climate. When both counteracting effects of climate and atmospheric CO₂ on ecosystem function are considered, all the DGVMs simulate cumulative net land carbon uptake over the 21st century for the four SRES emission scenarios. However, for the most extreme A1FI emissions scenario, three out of five DGVMs simulate an annual net source of CO₂ from the land to the atmosphere in the final decades of the 21st century. For this scenario, cumulative land uptake differs by 494 Pg C among DGVMs over the 21st century. This uncertainty is equivalent to over 50 years of anthropogenic emissions at current levels.     

Carbon cycle responses of semi‐arid ecosystems to positive asymmetry in rainfall

Recent evidence shows that warm semi‐arid ecosystems are playing a disproportionate role in the interannual variability and greening trend of the global carbon cycle given their mean lower productivity when compared with other biomes (Ahlström et al. 2015 Science, 348, 895). Using multiple observations (land‐atmosphere fluxes, biomass, streamflow and remotely sensed vegetation cover) and two state‐of‐the‐art biospheric models, we show that climate variability and extremes lead to positive or negative responses in the biosphere, depending on vegetation type. We find Australia to be a global hot spot for variability, with semi‐arid ecosystems in that country exhibiting increased carbon uptake due to both asymmetry in the interannual distribution of rainfall (extrinsic forcing), and asymmetry in the response of gross primary production (GPP) to rainfall change (intrinsic response). The latter is attributable to the pulse‐response behaviour of the drought‐adapted biota of these systems, a response that is estimated to be as much as half of that from the CO₂ fertilization effect during 1990–2013. Mesic ecosystems, lacking drought‐adapted species, did not show an intrinsic asymmetric response. Our findings suggest that a future more variable climate will induce large but contrasting ecosystem responses, differing among biomes globally, independent of changes in mean precipitation alone. The most significant changes are occurring in the extensive arid and semi‐arid regions, and we suggest that the reported increased carbon uptake in response to asymmetric responses might be contributing to the observed greening trends there.     

Using model‐data fusion to interpret past trends,and quantify uncertainties in future projections,of terrestrial ecosystem carbon cycling

Uncertainties in model projections of carbon cycling in terrestrial ecosystems stem from inaccurate parameterization of incorporated processes (endogenous uncertainties) and processes or drivers that are not accounted for by the model (exogenous uncertainties). Here, we assess endogenous and exogenous uncertainties using a model‐data fusion framework benchmarked with an artificial neural network (ANN). We used 18 years of eddy‐covariance carbon flux data from the Harvard forest, where ecosystem carbon uptake has doubled over the measurement period, along with 15 ancillary ecological data sets relative to the carbon cycle. We test the ability of combinations of diverse data to constrain projections of a process‐based carbon cycle model, both against the measured decadal trend and under future long‐term climate change. The use of high‐frequency eddy‐covariance data alone is shown to be insufficient to constrain model projections at the annual or longer time step. Future projections of carbon cycling under climate change in particular are shown to be highly dependent on the data used to constrain the model. Endogenous uncertainties in long‐term model projections of future carbon stocks and fluxes were greatly reduced by the use of aggregated flux budgets in conjunction with ancillary data sets. The data‐informed model, however, poorly reproduced interannual variability in net ecosystem carbon exchange and biomass increments and did not reproduce the long‐term trend. Furthermore, we use the model‐data fusion framework, and the ANN, to show that the long‐term doubling of the rate of carbon uptake at Harvard forest cannot be explained by meteorological drivers, and is driven by changes during the growing season. By integrating all available data with the model‐data fusion framework, we show that the observed trend can only be reproduced with temporal changes in model parameters. Together, the results show that exogenous uncertainty dominates uncertainty in future projections from a data‐informed process‐based model.     

CO2 balance of boreal, temperate, and tropical forests derived from a global database

Terrestrial ecosystems sequester 2.1 Pg of atmospheric carbon annually. A large amount of the terrestrial sink is realized by forests. However, considerable uncertainties remain regarding the fate of this carbon over both short and long timescales. Relevant data to address these uncertainties are being collected at many sites around the world, but syntheses of these data are still sparse. To facilitate future synthesis activities, we have assembled a comprehensive global database for forest ecosystems, which includes carbon budget variables (fluxes and stocks), ecosystem traits (e.g. leaf area index, age), as well as ancillary site information such as management regime, climate, and soil characteristics. This publicly available database can be used to quantify global, regional or biome‐specific carbon budgets; to re‐examine established relationships; to test emerging hypotheses about ecosystem functioning [e.g. a constant net ecosystem production (NEP) to gross primary production (GPP) ratio]; and as benchmarks for model evaluations. In this paper, we present the first analysis of this database. We discuss the climatic influences on GPP, net primary production (NPP) and NEP and present the CO₂ balances for boreal, temperate, and tropical forest biomes based on micrometeorological, ecophysiological, and biometric flux and inventory estimates. Globally, GPP of forests benefited from higher temperatures and precipitation whereas NPP saturated above either a threshold of 1500 mm precipitation or a mean annual temperature of 10 °C. The global pattern in NEP was insensitive to climate and is hypothesized to be mainly determined by nonclimatic conditions such as successional stage, management, site history, and site disturbance. In all biomes, closing the CO₂ balance required the introduction of substantial biome‐specific closure terms. Nonclosure was taken as an indication that respiratory processes, advection, and non‐CO₂ carbon fluxes are not presently being adequately accounted for.     

Regional atmospheric CO2 inversion reveals seasonal and geographic differences in Amazon net biome exchange

Understanding tropical rainforest carbon exchange and its response to heat and drought is critical for quantifying the effects of climate change on tropical ecosystems, including global climate–carbon feedbacks. Of particular importance for the global carbon budget is net biome exchange of CO₂ with the atmosphere (NBE), which represents nonfire carbon fluxes into and out of biomass and soils. Subannual and sub‐Basin Amazon NBE estimates have relied heavily on process‐based biosphere models, despite lack of model agreement with plot‐scale observations. We present a new analysis of airborne measurements that reveals monthly, regional‐scale (~1–8 × 10⁶ km²) NBE variations. We develop a regional atmospheric CO₂ inversion that provides the first analysis of geographic and temporal variability in Amazon biosphere–atmosphere carbon exchange and that is minimally influenced by biosphere model‐based first guesses of seasonal and annual mean fluxes. We find little evidence for a clear seasonal cycle in Amazon NBE but do find NBE sensitivity to aberrations from long‐term mean climate. In particular, we observe increased NBE (more carbon emitted to the atmosphere) associated with heat and drought in 2010, and correlations between wet season NBE and precipitation (negative correlation) and temperature (positive correlation). In the eastern Amazon, pulses of increased NBE persisted through 2011, suggesting legacy effects of 2010 heat and drought. We also identify regional differences in postdrought NBE that appear related to long‐term water availability. We examine satellite proxies and find evidence for higher gross primary productivity (GPP) during a pulse of increased carbon uptake in 2011, and lower GPP during a period of increased NBE in the 2010 dry season drought, but links between GPP and NBE changes are not conclusive. These results provide novel evidence of NBE sensitivity to short‐term temperature and moisture extremes in the Amazon, where monthly and sub‐Basin estimates have not been previously available.     

Precipitation Pattern Determines the Inter-annual Variation of Herbaceous Layer and Carbon Fluxes in a Phreatophyte-Dominated Desert Ecosystem

Arid and semi-arid ecosystems dominated by shrubby species are an important component in the global carbon cycle but are largely under-represented in studies of the effect of climate change on carbon flux. This study synthesizes data from long-term eddy covariance measurements and experiments to assess how changes in ecosystem composition, driven by precipitation patterns, affect inter-annual variability of carbon flux and their components in a halophyte desert community dominated by deep-rooted shrubs (phreatophytes, which depend on groundwater as their primary water source). Our results demonstrated that the carbon balance of this community responded strongly to precipitation variations. Both pre-growing season precipitation and growing season precipitation frequency significantly affected inter-annual variations in ecosystem carbon flux. Heavy pre-growing season precipitation (November–April, mostly as snow) increased annual net ecosystem carbon exchange, by facilitating the growth and carbon assimilation of shallow-rooted annual plants, which used spring and summer precipitation to increase community productivity. Sufficient pre-growing season precipitation led to more germination and growth of shallow-rooted annual plants. When followed by high-frequency growing season precipitation, community productivity of this desert ecosystem was lifted to the level of grassland or forest ecosystems. The long-term observations and experimental results confirmed that precipitation patterns and the herbaceous component were dominant drivers of the carbon dynamics in this phreatophyte-dominated desert ecosystem. This study illustrates the importance of inter-annual variations in climate and ecosystem composition for the carbon flux in arid and semi-arid ecosystems. It also highlights the important effect of changing frequency and seasonal pattern of precipitation on the regional and global carbon cycle in the coming decades.     

Systematic assessment of terrestrial biogeochemistry in coupled climate–carbon models

With representation of the global carbon cycle becoming increasingly complex in climate models, it is important to develop ways to quantitatively evaluate model performance against in situ and remote sensing observations. Here we present a systematic framework, the Carbon‐LAnd Model Intercomparison Project (C‐LAMP), for assessing terrestrial biogeochemistry models coupled to climate models using observations that span a wide range of temporal and spatial scales. As an example of the value of such comparisons, we used this framework to evaluate two biogeochemistry models that are integrated within the Community Climate System Model (CCSM) – Carnegie‐Ames‐Stanford Approach′ (CASA′) and carbon–nitrogen (CN). Both models underestimated the magnitude of net carbon uptake during the growing season in temperate and boreal forest ecosystems, based on comparison with atmospheric CO₂ measurements and eddy covariance measurements of net ecosystem exchange. Comparison with MODerate Resolution Imaging Spectroradiometer (MODIS) measurements show that this low bias in model fluxes was caused, at least in part, by 1–3 month delays in the timing of maximum leaf area. In the tropics, the models overestimated carbon storage in woody biomass based on comparison with datasets from the Amazon. Reducing this model bias will probably weaken the sensitivity of terrestrial carbon fluxes to both atmospheric CO₂ and climate. Global carbon sinks during the 1990s differed by a factor of two (2.4 Pg C yr^?1 for CASA′ vs. 1.2 Pg C yr^?1 for CN), with fluxes from both models compatible with the atmospheric budget given uncertainties in other terms. The models captured some of the timing of interannual global terrestrial carbon exchange during 1988–2004 based on comparison with atmospheric inversion results from TRANSCOM (r=0.66 for CASA′ and r=0.73 for CN). Adding (CASA′) or improving (CN) the representation of deforestation fires may further increase agreement with the atmospheric record. Information from C‐LAMP has enhanced model performance within CCSM and serves as a benchmark for future development. We propose that an open source, community‐wide platform for model‐data intercomparison is needed to speed model development and to strengthen ties between modeling and measurement communities. Important next steps include the design and analysis of land use change simulations (in both uncoupled and coupled modes), and the entrainment of additional ecological and earth system observations. Model results from C‐LAMP are publicly available on the Earth System Grid.     

Improving predictions of tropical forest response to climate change through integration of field studies and ecosystem modeling

Tropical forests play a critical role in carbon and water cycles at a global scale. Rapid climate change is anticipated in tropical regions over the coming decades and, under a warmer and drier climate, tropical forests are likely to be net sources of carbon rather than sinks. However, our understanding of tropical forest response and feedback to climate change is very limited. Efforts to model climate change impacts on carbon fluxes in tropical forests have not reached a consensus. Here, we use the Ecosystem Demography model (ED2) to predict carbon fluxes of a Puerto Rican tropical forest under realistic climate change scenarios. We parameterized ED2 with species‐specific tree physiological data using the Predictive Ecosystem Analyzer workflow and projected the fate of this ecosystem under five future climate scenarios. The model successfully captured interannual variability in the dynamics of this tropical forest. Model predictions closely followed observed values across a wide range of metrics including aboveground biomass, tree diameter growth, tree size class distributions, and leaf area index. Under a future warming and drying climate scenario, the model predicted reductions in carbon storage and tree growth, together with large shifts in forest community composition and structure. Such rapid changes in climate led the forest to transition from a sink to a source of carbon. Growth respiration and root allocation parameters were responsible for the highest fraction of predictive uncertainty in modeled biomass, highlighting the need to target these processes in future data collection. Our study is the first effort to rely on Bayesian model calibration and synthesis to elucidate the key physiological parameters that drive uncertainty in tropical forests responses to climatic change. We propose a new path forward for model‐data synthesis that can substantially reduce uncertainty in our ability to model tropical forest responses to future climate.     

Interannual variations in GPP in forest ecosystems in Southwest China and regional differences in the climatic contributions

Forest ecosystem plays an important role as carbon sinks in Southwest China. Currently, remote sensing technology has been widely used to substantially model the high temporal and spatial variation in gross primary production (GPP) at a site or regional scale. However, during the growing season, the regional uncertainty of GPP in the forest ecosystem and the relative contributions of climate variations to interannual variation (IAV) of GPP are not well understood across Southwest China. Our research focuses on the joint analysis of the three-cornered hat (TCH) algorithm and uses the contribution index to analyse the model's uncertainties varying with plant functional types (PFTs), climate zones, and the contribution of climate variabilities to GPP IAV. Here, three GPP datasets are used to investigate how climate variabilities contribute to the GPP IAV during the growing season. The uncertainties in GPP vary from 829.33 g C m⁻² year⁻¹ to 2031.86 g C m⁻² year⁻¹ for different models in different climate zones and different PFTs. Additionally, the results highlight that precipitation dominates the interannual variation in GPP in forest ecosystem during the growing season in Southwest China. It makes the largest contribution (34.46%) to the IAV of GPP in the climate zone of E (cold subtropical highland area) and the largest contribution (80.83%) to PFTs of the MF (mixed forest). Our study suggests the availability and applicability of GPP products can be used to assess GPP uncertainties and analyse the contributions of climate factors to GPP IAV in forest ecosystem or other ecosystems.     

Dominant regions and drivers of the variability of the global land carbon sink across timescales

Net biome productivity (NBP) dominates the observed large variation of atmospheric CO₂ annual increase over the last five decades. However, the dominant regions controlling inter‐annual to multi‐decadal variability of global NBP are still controversial (semi‐arid regions vs. temperate or tropical forests). By developing a theory for partitioning the variance of NBP into the contributions of net primary production (NPP) and heterotrophic respiration (R_h) at different timescales, and using both observation‐based atmospheric CO₂ inversion product and the outputs of 10 process‐based terrestrial ecosystem models forced by 110‐year observational climate, we tried to reconcile the controversy by showing that semi‐arid lands dominate the variability of global NBP at inter‐annual (<10 years) and tropical forests dominate at multi‐decadal scales (>30 years). Results further indicate that global NBP variability is dominated by the NPP component at inter‐annual timescales, and is progressively controlled by R_h with increasing timescale. Multi‐decadal NBP variations of tropical rainforests are modulated by the Pacific Decadal Oscillation (PDO) through its significant influences on both temperature and precipitation. This study calls for long‐term observations for the decadal or longer fluctuations in carbon fluxes to gain insights on the future evolution of global NBP, particularly in the tropical forests that dominate the decadal variability of land carbon uptake and are more effective for climate mitigation.