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Despite their sparse vegetation, dryland regions exert a huge influence over global biogeochemical cycles because they cover more than 40% of the world surface (Schimel 2010 Science 327 418–9). It is thought that drylands dominate the inter-annual variability (IAV) and long-term trend in the global carbon (C) cycle (Poulter et al 2014 Nature 509 600–3, Ahlstrom et al 2015 Science 348 895–9, Zhang et al 2018 Glob. Change Biol. 24 3954–68). Projections of the global land C sink therefore rely on accurate representation of dryland C cycle processes; however, the dynamic global vegetation models (DGVMs) used in future projections have rarely been evaluated against dryland C flux data. Here, we carried out an evaluation of 14 DGVMs (TRENDY v7) against net ecosystem exchange (NEE) data from 12 dryland flux sites in the southwestern US encompassing a range of ecosystem types (forests, shrub- and grasslands). We find that all the models underestimate both mean annual C uptake/release as well as the magnitude of NEE IAV, suggesting that improvements in representing dryland regions may improve global C cycle projections. Across all models, the sensitivity and timing of ecosystem C uptake to plant available moisture was at fault. Spring biases in gross primary production (GPP) dominate the underestimate of mean annual NEE, whereas models’ lack of GPP response to water availability in both spring and summer monsoon are responsible for inability to capture NEE IAV. Errors in GPP moisture sensitivity at high elevation forested sites were more prominent during the spring, while errors at the low elevation shrub and grass-dominated sites were more important during the monsoon. We propose a range of hypotheses for why model GPP does not respond sufficiently to changing water availability that can serve as a guide for future dryland DGVM developments. Our analysis suggests that improvements in modeling C cycle processes across more than a quarter of the Earth’s land surface could be achieved by addressing the moisture sensitivity of dryland C uptake.

The response of terrestrial carbon uptake to increasing atmospheric [CO2 ], that is the CO2 fertilization effect (CFE), remains a key area of uncertainty in carbon cycle science. Here we provide a perspective on how satellite observations could be better used to understand and constrain CFE. We then highlight data assimilation (DA) as an effective way to reconcile different satellite datasets and systematically constrain carbon uptake trends in Earth System Models. As a proof-of-concept, we show that joint DA of multiple independent satellite datasets reduced model ensemble error by better constraining unobservable processes and variables, including those directly impacted by CFE. DA of multiple satellite datasets offers a powerful technique that could improve understanding of CFE and enable more accurate forecasts of terrestrial carbon uptake.

Severe drought can cause lagged effects on tree physiology that negatively impact forest functioning for years. These "drought legacy effects" have been widely documented in tree-ring records and could have important implications for our understanding of broader scale forest carbon cycling. However, legacy effects in tree-ring increments may be decoupled from ecosystem fluxes due to (a) postdrought alterations in carbon allocation patterns; (b) temporal asynchrony between radial growth and carbon uptake; and (c) dendrochronological sampling biases. In order to link legacy effects from tree rings to whole forests, we leveraged a rich dataset from a Midwestern US forest that was severely impacted by a drought in 2012. At this site, we compiled tree-ring records, leaf-level gas exchange, eddy flux measurements, dendrometer band data, and satellite remote sensing estimates of greenness and leaf area before, during, and after the 2012 drought. After accounting for the relative abundance of tree species in the stand, we estimate that legacy effects led to ~10% reductions in tree-ring width increments in the year following the severe drought. Despite this stand-scale reduction in radial growth, we found that leaf-level photosynthesis, gross primary productivity (GPP), and vegetation greenness were not suppressed in the year following the 2012 drought. Neither temporal asynchrony between radial growth and carbon uptake nor sampling biases could explain our observations of legacy effects in tree rings but not in GPP. Instead, elevated leaf-level photosynthesis co-occurred with reduced leaf area in early 2013, indicating that resources may have been allocated away from radial growth in conjunction with postdrought upregulation of photosynthesis and repair of canopy damage. Collectively, our results indicate that tree-ring legacy effects were not observed in other canopy processes, and that postdrought canopy allocation could be an important mechanism that decouples tree-ring signals from GPP.

International audience; Atmospheric carbon dioxide concentration ([CO 2 ]) is increasing, which increases leaf-scale photosynthesis and intrinsic water-use efficiency. These direct responses have the potential to increase plant growth, vegetation biomass, and soil organic matter; transferring carbon from the atmosphere into terrestrial ecosystems (a carbon sink). A substantial global terrestrial carbon sink would slow the rate of [CO 2] increase and thus climate change. However, ecosystem CO2 responses are complex or confounded by concurrent changes in multiple agents of global change and evidence for a [CO 2]-driven terrestrial carbon sink can appear contradictory. Here we synthesize theory and broad, multidisciplinary evidence for the effects of increasing [CO 2] (iCO 2) on the global terrestrial carbon sink. Evidence suggests a substantial increase in global photosynthesis since pre-industrial times. Established theory, supported by experiments, indicates that iCO 2 is likely responsible for about half of the increase. Global carbon budgeting, atmospheric data, and forest inventories indicate a historical carbon sink, and these apparent iCO 2 responses are high in comparison to experiments and predictions from theory. Plantmortality and soil carbon iCO 2 responses are highly uncertain. In conclusion, a range of evidence supports a positive terrestrial carbon sink in response to iCO2 , albeit with uncertain magnitude and strong suggestion of a role for additional agents of global change.

Atmospheric carbon dioxide concentration ([CO

The magnitude and persistence of land carbon (C) pools influence long‐term climate feedbacks. Interactive ecological processes influence land C pools and our understanding of these processes is imperfect so land surface models have errors and biases when compared to each other and to real observations. Here we implement an Ensemble Adjustment Kalman Filter (EAKF), a sequential state data assimilation technique to reduce these errors and biases. We implement the EAKF using the Data Assimilation Research Testbed coupled with the Community Land Model (CLM 4.5 in CESM 1.2). We assimilated simulated and real satellite observations for a site in central New Mexico, United States. A series of observing system simulation experiments allowed assessment of the data assimilation system without model error. This showed that assimilating biomass and leaf area index observations decreased model error in C dynamics forecasts (29% using biomass observations and 40% using leaf area index observations) and that assimilation in combination shows greater improvement (51% using both observation streams). Assimilating real observations highlighted likely model structural errors and we implemented an adaptive model‐variance‐inflation technique to allow the model to track the observations. Monthly and longer model forecasts using real observations were improved relative to forecasts without data assimilation. The reliable forecast lead‐time varied by model pool and is dependent on how tightly the C pool is coupled to meteorologically driven processes. The EAKF and similar state data assimilation techniques could reduce errors in projections of the land C sink and provide more robust forecasts of C pools and land‐atmosphere exchanges.

Bark beetle outbreaks are widespread in western North American forests, reducing primary productivity and transpiration, leading to forest mortality across large areas and altering ecosystem carbon cycling. Here the carbon isotope composition (δ(13) C) of soil respiration (δJ ) was monitored in the decade after disturbance for forests affected naturally by mountain pine beetle infestation and artificially by stem girdling. The seasonal mean δJ changed along both chronosequences. We found (a) enrichment of δJ relative to controls (

© 2017 Elsevier B.V. AmeriFlux scientists were early adopters of a network-enabled approach to ecosystem science that continues to transform the study of land-atmosphere interactions. In the 20 years since its formation, AmeriFlux has grown to include more than 260 flux tower sites in the Americas that support continuous observation of ecosystem carbon, water, and energy fluxes. Many of these sites are co-located within a similar climate regime, and more than 50 have data records that exceed 10 years in length. In this prospective assessment of AmeriFlux's strengths in a new era of network-enabled ecosystem science, we discuss how the longevity and spatial distribution of AmeriFlux data make them exceptionally well suited for disentangling ecosystem response to slowly evolving changes in climate and land-cover, and to rare events like droughts and biological disturbances. More recently, flux towers have also been integrated into environmental observation networks that have broader scientific goals; in North America these include the National Ecological Observatory Network (NEON), Critical Zone Observatory network (CZO), and Long-Term Ecological Research network (LTER). AmeriFlux stands apart from these other networks in its reliance on voluntary participation of individual sites, which receive funding from diverse sources to pursue a wide, transdisciplinary array of research topics. This diffuse, grassroots approach fosters methodological and theoretical innovation, but also challenges network-level data synthesis and data sharing to the network. While AmeriFlux has had strong ties to other regional flux networks and FLUXNET, better integration with networks like NEON, CZO and LTER provides opportunities for new types of cooperation and synergies that could strengthen the scientific output of all these networks.

A recent unprecedented epidemic of beetle-induced tree mortality has occurred in the lodgepole pine forests of Western North America. Here, we present the results of studies in two subalpine forests in the Rocky Mountains, one that experienced natural pine beetle disturbance and one that experienced simulated disturbance imposed through bole girdling. We assessed changes to soil microclimate and biogeochemical pools in plots representing different post-disturbance chronosequences. High plot tree mortality, whether due to girdling or beetle infestation, caused similar alterations in soil nutrient pools. During the first 4 years after disturbance, sharp declines were observed in the soil dissolved organic carbon (DOC) concentration (45-51 %), microbial biomass carbon concentration (33-39 %), dissolved organic nitrogen (DON) concentration (31-42%), and inorganic phosphorus (PO4(3-)) concentration (53-55%). Five to six years after disturbance, concentrations of DOC, DON, and PO4(3-) recovered to 71-140 % of those measured in undisturbed plots. Recovery was coincident with observed increases in litter depth and the sublitter, soil O-horizon. During the 4 years following disturbance, soil ammonium, but not nitrate, increased to 2-3 times the levels measured in undisturbed plots. Microbial biomass N increased in plots where increased ammonium was available. Our results show that previously observed declines in soil respiration following beetle-induced disturbance are accompanied by losses in key soil nutrients. Recovery of the soil nutrient pool occurs only after several years following disturbance, and is correlated with progressive mineralization of dead tree litter.

[1] Forecasting the carbon uptake potential of terrestrial ecosystems in the face of future climate change has proven challenging. Process models, which have been increasingly used to study ecosystem-atmosphere carbon and water exchanges when conditioned with tower-based eddy covariance data, have the potential to inform us about biogeochemical processes in future climate regimes, but only if we can reconcile the spatial and temporal scales used for observed fluxes and projected climate. Here, we used weather generator and ecosystem process models conditioned on observed weather dynamics and carbon/water fluxes, and embedded them within climate projections from a suite of six Earth Systems Models. Using this combination of models, we studied carbon cycle processes in a subalpine forest within the context of future (2080–2099) climate regimes. The assimilation of daily averaged, observed net ecosystem CO2 exchange (NEE) and evapotranspiration (ET) into the ecosystem process model resulted in retrieval of projected NEE with a level of accuracy that was similar to that following the assimilation of half-daily averaged observations; the assimilation of 30 min averaged fluxes or monthly averaged fluxes caused degradation in the model's capacity to accurately simulate seasonal patterns in observed NEE. Using daily averaged flux data with daily averaged weather data projected for the period 2080–2099, we predicted greater forest net CO2 uptake in response to a lengthening of the growing season. These results contradict our previous observations of reduced CO2 uptake in response to longer growing seasons in the current (1999–2008) climate regime. The difference between these analyses is due to a projected increase in the frequency of rain versus snow during warmer winters of the future. Our results demonstrate the sensitivity of modeled processes to local variation in meteorology, which is often left unresolved in traditional approaches to earth systems modeling, and the importance of maintaining similarity in the timescales used in ecosystem process models driven by downscaled climate projections.

Forest insects and pathogens are major disturbance agents that have affected millions of hectares in North America in recent decades, implying significant impacts to the carbon (C) cycle. Here, we review and synthesize published studies of the effects of biotic disturbances on forest C cycling in the United States and Canada. Primary productivity in stands was reduced, sometimes considerably, immediately following insect or pathogen attack. After repeated growth reductions caused by some insects or pathogens or a single infestation by some bark beetle species, tree mortality occurred, altering productivity and decomposition. In the years following disturbance, primary productivity in some cases increased rapidly as a result of enhanced growth by surviving vegetation, and in other cases increased slowly because of lower forest regrowth. In the decades following tree mortality, decomposition increased as a result of the large amount of dead organic matter. Net ecosystem productivity decreased immediately following attack, with some studies reporting a switch to a C source to the atmosphere, and increased afterward as the forest regrew and dead organic matter decomposed. Large variability in C cycle responses arose from several factors, including type of insect or pathogen, time since disturbance, number of trees affected, and capacity of remaining vegetation to increase growth rates following outbreak. We identified significant knowledge gaps, including limited understanding of carbon cycle impacts among different biotic disturbance types (particularly pathogens), their impacts at landscape and regional scales, and limited capacity to predict disturbance events and their consequences for carbon cycling. We conclude that biotic disturbances can have major impacts on forest C stocks and fluxes and can be large enough to affect regional C cycling. However, additional research is needed to reduce the uncertainties associated with quantifying biotic disturbance effects on the North American C budget.

The earth’s future climate state is highly dependent upon changes in terrestrial C storage in response to rising concentrations of atmospheric CO2. Here we show that consistently enhanced rates of net primary production (NPP) are sustained by a C-cascade through the root-microbe-soil system; increases in the flux of C belowground under elevated CO2 stimulated microbial activity, accelerated the rate of soil organic matter decomposition and stimulated tree uptake of N bound to this SOM. This process set into motion a positive feedback maintaining greater C gain under elevated CO2 as a result of increases in canopy N content and higher photosynthetic N-use efficiency. The ecosystem-level consequence of the enhanced requirement for N and the exchange of plant C for N belowground is the dominance of C storage in tree biomass but the preclusion of a large C sink in the soil.

As global temperatures increase, the potential for longer growing seasons to enhance the terrestrial carbon sink has been proposed as a mechanism to reduce the rate of further warming. At the Niwot Ridge AmeriFlux site, a subalpine forest in the Colorado Rocky Mountains, we used a 9-year record (1999-2007) of continuous eddy flux observations to show that longer growing season length (GSL) actually resulted in less annual CO 2 uptake. Years with a longer GSL were correlated with a shallower snow pack, as measured using snow water equivalent (SWE). Furthermore, years with a lower SWE correlated with an earlier start of spring. For three years, 2005, 2006, and 2007, we used observations of stable hydrogen isotopes (δD) of snow vs. rain, and extracted xylem water from the three dominant tree species, lodgepole pine, Engelmann spruce, and subalpine fir, to show that the trees relied heavily on snow melt water even late into the growing season. By mid-August, 57% to 68% of xylem water reflected the isotopic signature of snow melt. By coupling the isotopic water measurements with an ecosystem model, SIPNET, we found that annual forest carbon uptake was highly dependent on snow water, which decreases in abundance during years with longer growing seasons. Once again, for the 3 years 2005, 2006, and 2007, annual gross primary productivity, which was derived as an optimized parameter from the SIPNET model was estimated to be 67% 77%, and 71% dependent on snow melt water, respectively. Past studies have shown that the mean winter snow pack in mountain ecosystems of the Western US has been declining for decades and is correlated with positive winter temperature anomalies. Since climate change models predict continuation of winter warming and reduced snow in mountains of the Western US, the strength of the forest carbon sink is likely to decline further.

Modeling how the role of forests in the carbon cycle will respond to predicted changes in water availability hinges on an understanding of the processes controlling water use in ecosystems. Recent studies in forest ecosystem modeling have employed data-assimilation techniques to generate parameter sets that conform to observations, and predict net ecosystem CO2 exchange (NEE) and its component processes. Since the carbon and water cycles are linked, there should be additional process information available from ecosystem H2O exchange. We coupled SIPNET (Simple Photosynthesis EvapoTranspiration), a simplified model of ecosystem function, with a data-assimilation system to estimate parameters leading to model predictions most closely matching the net CO2 and H2O fluxes measured by eddy covariance in a high-elevation, subalpine forest ecosystem. When optimized using measurements of CO2 exchange, the model matched observed NEE (RMSE = 0.49 g C m−2) but underestimated transpiration calculated independently from sap flow measurements by a factor of 4. Consequently, the carbon-only optimization was insensitive to imposed changes in water availability. Including eddy flux data from both CO2 and H2O exchange to the optimization reduced the model fit to the observed NEE fluxes only slightly (RME = 0.53 g C m−2), however this parameterization also reproduced transpiration calculated from independent sap flow measurements (r2 = 0.67, slope = 0.6). A significant amount of information can be extracted from simultaneous analysis of CO2 and H2O exchange, which improved the accuracy of transpiration estimates from measured evapotranspiration. Conversely, failure to include both CO2 and H2O data streams can generate results that mask the responses of ecosystem carbon cycling to variation in the precipitation. In applying the model conditioned on both CO2 and H2O fluxes to the subalpine forest at the Niwot Ridge AmeriFlux site, we observed that the onset of transpiration is coincident with warm soil temperatures. However, after snow has covered the ground in the fall, we observed significant inter-annual variability in the fraction of evapotranspiration composed of transpiration; evapotranspiration was dominated by transpiration in years when late fall air temperatures were high enough to maintain photosynthesis, but by sublimation from the surface of the snowpack in years when late fall air temperatures were colder and forest photosynthetic activity had ceased. Data-assimilation techniques and simultaneous measurements of carbon and water exchange can be used to quantify the response of net carbon uptake to changes in water availability by using an ecosystem model where the carbon and water cycles are linked.

Tree-ring records can provide valuable information to advance our understanding of contemporary terrestrial carbon cycling and to reconstruct key metrics in the decades preceding monitoring data. The growing use of tree rings in carbon-cycle research is being facilitated by increasing recognition of reciprocal benefits among research communities. Yet, basic questions persist regarding what tree rings represent at the ecosystem level, how to optimally integrate them with other data streams, and what related challenges need to be overcome. It is also apparent that considerable unexplored potential exists for tree rings to refine assessments of terrestrial carbon cycling across a range of temporal and spatial domains. Here, we summarize recent advances and highlight promising paths of investigation with respect to (1) growth phenology, (2) forest productivity trends and variability, (3) CO2 fertilization and water-use efficiency, (4) forest disturbances, and (5) comparisons between observational and computational forest productivity estimates. We encourage the integration of tree-ring data: with eddy-covariance measurements to investigate carbon allocation patterns and water-use efficiency; with remotely sensed observations to distinguish the timing of cambial growth and leaf phenology; and with forest inventories to develop continuous, annually-resolved and long-term carbon budgets. In addition, we note the potential of tree-ring records and derivatives thereof to help evaluate the performance of earth system models regarding the simulated magnitude and dynamics of forest carbon uptake, and inform these models about growth responses to (non-)climatic drivers. Such efforts are expected to improve our understanding of forest carbon cycling and place current developments into a long-term perspective.

[1] High-elevation forests represent a large fraction of potential carbon uptake in North America, but this uptake is not well constrained by observations. Additionally, forests in the Rocky Mountains have recently been severely damaged by drought, fire, and insect outbreaks, which have been quantified at local scales but not assessed in terms of carbon uptake at regional scales. The Airborne Carbon in the Mountains Experiment was carried out in 2007 partly to assess carbon uptake in western U.S. mountain ecosystems. The magnitude and seasonal change of carbon uptake were quantified by (1) paired upwind-downwind airborne CO2 observations applied in a boundary layer budget, (2) a spatially explicit ecosystem model constrained using remote sensing and flux tower observations, and (3) a downscaled global tracer transport inversion. Top-down approaches had mean carbon uptake equivalent to flux tower observations at a subalpine forest, while the ecosystem model showed less. The techniques disagreed on temporal evolution. Regional carbon uptake was greatest in the early summer immediately following snowmelt and tended to lessen as the region experienced dry summer conditions. This reduction was more pronounced in the airborne budget and inversion than in flux tower or upscaling, possibly related to lower snow water availability in forests sampled by the aircraft, which were lower in elevation than the tower site. Changes in vegetative greenness associated with insect outbreaks were detected using satellite reflectance observations, but impacts on regional carbon cycling were unclear, highlighting the need to better quantify this emerging disturbance effect on montane forest carbon cycling.

The earth's future climate state is highly dependent upon changes in terrestrial C storage in response to rising concentrations of atmospheric CO₂. Here we show that consistently enhanced rates of net primary production (NPP) are sustained by a C-cascade through the root-microbe-soil system; increases in the flux of C belowground under elevated CO₂ stimulated microbial activity, accelerated the rate of soil organic matter decomposition and stimulated tree uptake of N bound to this SOM. This process set into motion a positive feedback maintaining greater C gain under elevated CO₂ as a result of increases in canopy N content and higher photosynthetic N-use efficiency. The ecosystem-level consequence of the enhanced requirement for N and the exchange of plant C for N belowground is the dominance of C storage in tree biomass but the preclusion of a large C sink in the soil.

We conducted an inverse modeling analysis, using a variety of data streams (tower-based eddy covariance measurements of net ecosystem exchange, NEE, of CO2, chamber-based measurements of soil respiration, and ancillary ecological measurements of leaf area index, litterfall, and woody biomass increment) to estimate parameters and initial carbon (C) stocks of a simple forest C-cycle model, DALEC, using Monte Carlo procedures. Our study site is the spruce-dominated Howland Forest AmeriFlux site, in central Maine, USA. Our analysis focuses on: (1) full characterization of data uncertainties, and treatment of these uncertainties in the parameter estimation; (2) evaluation of how combinations of different data streams influence posterior parameter distributions and model uncertainties; and (3) comparison of model performance (in terms of both predicted fluxes and pool dynamics) during a 4-year calibration period (1997–2000) and a 4-year validation period (“forward run”, 2001–2004). We find that woody biomass increment, and, to a lesser degree, soil respiration, measurements contribute to marked reductions in uncertainties in parameter estimates and model predictions as these provide orthogonal constraints to the tower NEE measurements. However, none of the data are effective at constraining fine root or soil C pool dynamics, suggesting that these should be targets for future measurement efforts. A key finding is that adding additional constraints not only reduces uncertainties (i.e., narrower confidence intervals) on model predictions, but at the same time also results in improved model predictions by greatly reducing bias associated with predictions during the forward run.

We examined the environmental variables that influence the delta(13)C value of needle and phloem sugars in trees in a subalpine forest. We collected sugars from Pinus contorta, Picea engelmannii and Abies lasiocarpa from 2006 to 2008. Phloem and needle sugars were enriched in (13)C during the autumn, winter and early spring, but depleted during the growing season. We hypothesized that the late-winter and early-spring (13)C enrichment was due to the mobilization of carbon assimilated the previous autumn; however, needle starch concentrations were completely exhausted by autumn, and we observed evidence of new starch production during episodic warm weather events during the winter and early-spring. Instead, we found that (13)C enrichment was best explained by the occurrence of cold night-time temperatures. We also observed seasonal decoupling in the (13)C/(12)C ratios of needle and phloem sugars. We hypothesized that this was due to seasonally-changing source-sink patterns, which drove carbon translocation from the needles towards the roots early in the season, before bud break, but from the roots towards the needles later in the season, after bud break. Overall, our results demonstrate that the (13)C/(12)C ratio of recently-assimilated sugars can provide a sensitive record of the short-term coupling between climate and tree physiology.

Climate change predictions derived from coupled carbon-climate models are highly dependent on assumptions about feedbacks between the biosphere and atmosphere. One critical feedback occurs if C uptake by the biosphere increases in response to the fossil-fuel driven increase in atmospheric [CO 2 ] (“CO 2 fertilization”), thereby slowing the rate of increase in atmospheric [CO 2 ]. Carbon exchanges between the terrestrial biosphere and atmosphere are often first represented in models as net primary productivity (NPP). However, the contribution of CO 2 fertilization to the future global C cycle has been uncertain, especially in forest ecosystems that dominate global NPP, and models that include a feedback between terrestrial biosphere metabolism and atmospheric [CO 2 ] are poorly constrained by experimental evidence. We analyzed the response of NPP to elevated CO 2 (≈550 ppm) in four free-air CO 2 enrichment experiments in forest stands. We show that the response of forest NPP to elevated [CO 2 ] is highly conserved across a broad range of productivity, with a stimulation at the median of 23 ± 2%. At low leaf area indices, a large portion of the response was attributable to increased light absorption, but as leaf area indices increased, the response to elevated [CO 2 ] was wholly caused by increased light-use efficiency. The surprising consistency of response across diverse sites provides a benchmark to evaluate predictions of ecosystem and global models and allows us now to focus on unresolved questions about carbon partitioning and retention, and spatial variation in NPP response caused by availability of other growth limiting resources.

Soil microbial respiration (Rh) is a large but uncertain component of the terrestrial carbon cycle. Carbon‐climate feedbacks associated with changes to Rh are likely, but Rh parameterization in Earth System Models (ESMs) has not been rigorously evaluated largely due to a lack of appropriate measurements. Here we assess, for the first time, Rh estimates from eight ESMs and their environmental drivers across several biomes against a comprehensive soil respiration database (SRDB-V2). Climatic, vegetation, and edaphic factors exert strong controls on annual Rh in ESMs, but these simple controls are not as apparent in the observations. This raises questions regarding the robustness of ESM projections of Rh in response to future climate change. Since there are many more soil respiration (Rs) observations than Rh data, two ‘reality checks’ for ESMs are also created using the Rs data. Guidance is also provided on the Rh improvement in ESMs.

How forest growth responds to climate change will impact the global carbon cycle. The sensitivity of tree growth and thus forest productivity to climate can be inferred from tree-ring increments, but individual tree responses may differ from the overall forest response. Tree-ring data have also been used to estimate interannual variability in aboveground biomass, but a shortage of robust uncertainty estimates often limits comparisons with other measurements of the carbon cycle across variable ecological settings. Here we identify and quantify four important sources of uncertainty that affect tree-ring-based aboveground biomass estimates: subsampling, allometry, forest density (sampling), and mortality. In addition, we investigate whether transforming rings widths into biomass affects the underlying growth-climate relationships at two coniferous forests located in the Valles Caldera in northern New Mexico. Allometric and mortality sources of uncertainty contributed most (34–57 and 24–42%, respectively) and subsampling uncertainty least (7–8%) to the total uncertainty for cumulative biomass estimates. Subsampling uncertainty, however, was the largest source of uncertainty for year-to-year variations in biomass estimates, and its large contribution indicates that between-tree growth variability remains influential to changes in year-to-year biomass estimates for a stand. The effect of the large contribution of the subsampling uncertainty is reflected by the different climate responses of large and small trees. Yet, the average influence of climate on tree growth persisted through the biomass transformation, and the biomass growth-climate relationship is comparable to that found in traditional climate reconstruction-oriented tree-ring chronologies. Including the uncertainties in estimates of aboveground biomass will aid comparisons of biomass increment across disparate forests, as well as further the use of these data in vegetation modeling frameworks.