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Soil organic matter decomposition and its interactions with climate depend on whether the organic matter is associated with soil minerals. However, data limitations have hindered global-scale analyses of mineral-associated and particulate soil organic carbon pools and their benchmarking in Earth system models used to estimate carbon cycle–climate feedbacks. Here we analyse observationally derived global estimates of soil carbon pools to quantify their relative proportions and compute their climatological temperature sensitivities as the decline in carbon with increasing temperature. We find that the climatological temperature sensitivity of particulate carbon is on average 28% higher than that of mineral-associated carbon, and up to 53% higher in cool climates. Moreover, the distribution of carbon between these underlying soil carbon pools drives the emergent climatological temperature sensitivity of bulk soil carbon stocks. However, global models vary widely in their predictions of soil carbon pool distributions. We show that the global proportion of model pools that are conceptually similar to mineral-protected carbon ranges from 16 to 85% across Earth system models from the Coupled Model Intercomparison Project Phase 6 and offline land models, with implications for bulk soil carbon ages and ecosystem responsiveness. To improve projections of carbon cycle–climate feedbacks, it is imperative to assess underlying soil carbon pools to accurately predict the distribution and vulnerability of soil carbon.

Accurate representation of permafrost carbon emissions is crucial for climate projections, yet current Earth system models inadequately represent permafrost carbon. Sustained funding opportunities are needed from government and private sectors for prioritized model development.

Earlier leaf-out in response to climate warming has been recorded in northern temperate and boreal regions. In turn, this shift modifies climate by altering seasonal cycles of surface energy, water and carbon budgets. Here, we use the Community Earth System Model 1.2 to investigate climate feedbacks from advanced leaf-out in northern temperate and boreal vegetation. An imposed 12-day earlier leaf-out in this region, consistent with recent observations, enhances annual surface warming in the Northern Hemisphere. We identify warming hotspots in the Canadian Arctic Archipelago (~0.7 °C), east and west edges of Siberia (~0.4 °C) and southeastern Tibetan Plateau (~0.3 °C). We attribute this enhanced warming to combined effects of indirect water vapour, cloud and snow-albedo radiative feedbacks through intensified poleward water vapour transport rather than direct vegetation albedo and latent heat biophysical feedbacks. With continued warming, positive feedbacks between climate and leaf phenology are likely to amplify warming in the northern high latitudes.

Key uncertainties in terrestrial carbon cycle projections revolve around the timing, direction, and magnitude of the carbon cycle feedback to climate change. This is especially true in carbon‐rich Arctic ecosystems, where permafrost soils contain roughly one third of the world's soil carbon stocks, which are likely vulnerable to loss. Using an ensemble of soil biogeochemical models that reflect recent changes in the conceptual understanding of factors responsible for soil carbon persistence, we quantify potential soil carbon responses under two representative climate change scenarios. Our results illustrate that models disagree on the sign and magnitude of global soil changes through 2100, with disagreements primarily driven by divergent responses of Arctic systems. These results largely reflect different assumptions about the nature of soil carbon persistence and vulnerabilities, underscoring the challenges associated with setting allowable greenhouse gas emission targets that will limit global warming to 1.5°C. Soils store carbon, lots of carbon. Because of these large carbon stocks, exchanges of carbon dioxide between soils and the atmosphere are large, and the potential responses of soil carbon stocks and fluxes to projected changes in climate are uncertain. The understanding of factors responsible for the persistence of these vast soil carbon stores has changed dramatically, and models need to widely implement these new ideas. Here we evaluate three models that make different assumptions about factors responsible for persistence of carbon in soils. Our results show that although the different model formulations produce similar estimates for initial soil carbon stocks, they show large spread in the fate of soil carbon under projected changes in soil temperature, moisture, and plant growth through the end of this century. These results highlight that greater attention is needed to develop and test model formulations that are consistent with observations and understanding—especially in the Arctic which has large soil carbon stores that are likely to experience rapid change in upcoming decades. Different model structures simulate similar initial stocks but make divergent projections about soil carbon trajectories under global changeModel uncertainty exceeds scenario uncertainty and highlights challenges in representing factors controlling soil carbon persistenceDivergent responses are largely driven by the response of Arctic soil carbon stocks to projected climate changes in high latitude ecosystems

Land models are often used to simulate terrestrial responses to future environmental changes, but these models are not commonly evaluated with data from experimental manipulations. Results from experimental manipulations can identify and evaluate model assumptions that are consistent with appropriate ecosystem responses to future environmental change. We conducted simulations using three coupled carbon‐nitrogen versions of the Community Land Model (CLM, versions 4, 4.5, and—the newly developed—5), and compared the simulated response to nitrogen (N) and atmospheric carbon dioxide (CO2) enrichment with meta‐analyses of observations from similar experimental manipulations. In control simulations, successive versions of CLM showed a poleward increase in gross primary productivity and an overall bias reduction, compared to FLUXNET‐MTE observations. Simulations with N and CO2enrichment demonstrate that CLM transitioned from a model that exhibited strong nitrogen limitation of the terrestrial carbon cycle (CLM4) to a model that showed greater responsiveness to elevated concentrations of CO2in the atmosphere (CLM5). Overall, CLM5 simulations showed better agreement with observed ecosystem responses to experimental N and CO2enrichment than previous versions of the model. These simulations also exposed shortcomings in structural assumptions and parameterizations. Specifically, no version of CLM captures changes in plant physiology, allocation, and nutrient uptake that are likely important aspects of terrestrial ecosystems' responses to environmental change. These highlight priority areas that should be addressed in future model developments. Moving forward, incorporating results from experimental manipulations into model benchmarking tools that are used to evaluate model performance will help increase confidence in terrestrial carbon cycle projections. How do changes in the availability of nitrogen in soils or carbon dioxide in the atmosphere affect the amount of carbon that can be stored on land? Answering this question is critical, but it remains difficult for land models that are used to make climate change projections—in part because of limited understanding in how terrestrial ecosystems will respond to environmental change. Experimental manipulations that increase the availability of nitrogen or carbon dioxide, however, provide insights into how ecosystems are likely to respond to changes in resource availability. We expect that models should exhibit similar responses to those observed in the real world. Our results show that over the course of model development later versions of the Community Land Model do a better job of simulating the global carbon cycle and capturing appropriate ecosystem responses to nitrogen and carbon dioxide enrichment. This improves our confidence in the future carbon cycle projections made by more recent versions of the Community Land Model. Our results also identify assumptions in the model that are not well supported by observations and can help to prioritize future model developments. Experimental manipulations provide critical insights into ecosystem responses to environmental change that can evaluate land modelsParametric and structural changes to the Community Land Model version 5 improve the simulated response to environmental changeModel assumptions related to nutrient acquisition strategies and trade‐offs between carbon and nitrogen limitation deserve further attention

Achieving the long-term temperature goal of the Paris Agreement requires forest-based mitigation. Collective progress towards this goal will be assessed by the Paris Agreement’s Global stocktake. At present, there is a discrepancy of about 4 GtCO2yr−1in global anthropogenic net land-use emissions between global models (reflected in IPCC assessment reports) and aggregated national GHG inventories (under the UNFCCC). We show that a substantial part of this discrepancy (about 3.2 GtCO2yr−1) can be explained by conceptual differences in anthropogenic forest sink estimation, related to the representation of environmental change impacts and the areas considered as managed. For a more credible tracking of collective progress under the Global stocktake, these conceptual differences between models and inventories need to be reconciled. We implement a new method of disaggregation of global land model results that allows greater comparability with GHG inventories. This provides a deeper understanding of model–inventory differences, allowing more transparent analysis of forest-based mitigation and facilitating a more accurate Global stocktake.

Vegetation phenology plays an important role in regulating land‐atmosphere energy, water, and trace‐gas exchanges. Changes in spring greenup (SG) have been documented in the past half‐century in response to ongoing climate change. We use normalized difference vegetation index generated from NOAA's advanced very high resolution radiometer data in the Global Inventory Modeling and Monitoring Study project over the 1982–2005 period, coupled with climate reanalysis (Climate Research Unit‐National Centers for Environmental Prediction) to investigate the SG responses to preseason climate change in northern temperate and boreal regions. We compared these observed responses to the simulated SG responses to preseason climate inferred from the Earth system models (ESMs) participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5) over 1982–2005. The observationally inferred SG suggests that there has been an advance of about 1 days per decade between 1982 and 2005 in the northern midlatitude to high latitude, with significant spatial heterogeneity. The spatial heterogeneity of the SG advance results from heterogeneity in the change of the preseason climate as well as varied vegetation responses to the preseason climate across biomes. The SG to preseason temperature sensitivity is highest in forests other than deciduous needleleaf forests, followed by temperate grasslands and woody savannas. The SG in deciduous needleleaf forests, open shrublands, and tundra is relatively insensitive to preseason temperature. Although the extent of regions where the SG is sensitive to preseason precipitation is smaller than the extent of regions where the SG is sensitive to preseason temperature, the biomes that are more sensitive to temperature are also more sensitive to precipitation, suggesting the interactive control of temperature and precipitation. In the mean, the CMIP5 ESMs reproduced the dominant latitudinal preseason climate trends and SG advances. However, large biases in individual ESMs for the preseason period, climate, and SG sensitivity imply needed model improvements to climate prediction and phenological process parameterizations. The observationally inferred spring greenup suggests about 1 day per decade advance between 1982 and 2005 in the northern midlatitudesThe advance of spring greenup resulted from the interactive controls of temperature and precipitation, with temperature dominatingBiases in individual ESM predicted preseason climate and spring greenup sensitivity to preseason climate imply needed model improvements

The projected loss of soil carbon to the atmosphere resulting from climate change is a potentially large but highly uncertain feedback to warming. The magnitude of this feedback is poorly constrained by observations and theory, and is disparately represented in Earth system models (ESMs). To assess the climatological temperature sensitivity of soil carbon, we calculate apparent soil carbon turnover times that reflect long-term and broad-scale rates of decomposition. Here, we show that the climatological temperature control on carbon turnover in the top metre of global soils is more sensitive in cold climates than in warm climates and argue that it is critical to capture this emergent ecosystem property in global-scale models. We present a simplified model that explains the observed high cold-climate sensitivity using only the physical scaling of soil freeze–thaw state across climate gradients. Current ESMs fail to capture this pattern, except in an ESM that explicitly resolves vertical gradients in soil climate and carbon turnover. An observed weak tropical temperature sensitivity emerges in a different model that explicitly resolves mineralogical control on decomposition. These results support projections of strong carbon–climate feedbacks from northern soils and demonstrate a method for ESMs to capture this emergent behaviour.

Climate change can be thought of in terms of geographical shifts in climate properties. Examples include assessments of shifts in habitat distributions, of the movement needed to maintain constant temperature or precipitation, and of the emergence and disappearance of climate zones. Here I track the movement of analogue climates within climate models. From the model simulations, I define a set of vectors that link a historical reference climate for each location to the location in a changed climate whose seasonal temperature and precipitation cycles best match the reference climate. I use these vectors to calculate the change in vegetation carbon storage with climate change due to ecosystems following climate analogues. Comparing the derived carbon content change to direct carbon projections by coupled carbon–climate models reveals two regions of divergence. In the tropical forests, vector projections are fundamentally uncertain because of a lack of close climatic analogues. In the southern boreal forest, carbon losses are projected in the vector perspective because low-carbon ecosystems shift polewards. However, the majority of carbon–climate models—typically without explicit simulation of the disturbance and mortality processes behind such shifts—instead project vegetation carbon gains throughout the boreal region. Southern boreal carbon loss as a result of ecosystem shift is likely to offset carbon gains from northern boreal forest expansion.

Water deficit in the atmosphere and soil are two key interactive factors that constrain transpiration and vegetation productivity. It is not clear which of these two factors is more important for the water and carbon flux response to drought stress in ecosystems. In this study, field data and numerical modeling were used to isolate their impact on evapotranspiration (ET) and gross primary productivity (GPP) at a tropical forest site in Barro Colorado Island (BCI), Panama, focusing on their response to the drought induced by the El Niño event of 2015–2016. Numerical simulations were performed using a plant hydrodynamic scheme (HYDRO) and a heuristic approach that ignores stomatal sensitivity to leaf water potential in the Energy Exascale Earth System Model (E3SM) Land Model (ELM). The sensitivity of canopy conductance (Gs) to vapor pressure deficit (VPD) obtained from eddy‐covariance fluxes and measured sap flux shows that, at both ecosystem and plant scale, soil water stress is more important in limiting Gsthan VPD at BCI during the El Niño event. The model simulations confirmed the importance of water stress limitation on Gs, but overestimated the VPD impact on Gscompared to that estimated from the observations. We also found that the predicted soil moisture is less sensitive to the diversity of plant hydraulic traits than ET and GPP. During the dry season at BCI, seasonal ET, especially soil evaporation at VPD > 0.42 kPa, simulated using HYDRO and ELM, were too strong and will require alternative parameterizations. Plants close stomata to regulate water loss through transpiration when stressed by the dry soil or high atmospheric water demand (vapor pressure deficit, VPD) or both. Tropical forests have experienced periodic droughts in the past. Recent drought‐related plant mortality has been attributed to increasing VPD associated with climate change. To evaluate whether water stress from dry soil or VPD has more limiting effect on plant transpiration, we analyzed the results from statistical models fitted to two types of field observation data and a land surface model which can simulate water movement in the soil and the water transport within the plant at a tropical forest site in Panama. We found dry soil is more important in limiting plant water loss at the site during the drought of the El Niño event of 2015–2016 and identified future model improvement need. Canopy conductance (Gs) sensitivity to vapor pressure deficit (VPD) was analyzed from observations using multiple methodsEstimated Gsindicates stronger limitation by soil water stress than VPD at Barro Colorado Island during the 2015 El Niño eventWith a plant hydrodynamics scheme in Energy Exascale Earth System Model (E3SM) Land Model, variation of plant hydraulic traits has greater effects on Gslimitation than on soil moisture Canopy conductance (Gs) sensitivity to vapor pressure deficit (VPD) was analyzed from observations using multiple methods Estimated Gsindicates stronger limitation by soil water stress than VPD at Barro Colorado Island during the 2015 El Niño event With a plant hydrodynamics scheme in Energy Exascale Earth System Model (E3SM) Land Model, variation of plant hydraulic traits has greater effects on Gslimitation than on soil moisture

The response of tropical ecosystems to elevated carbon dioxide (CO2) remains a critical uncertainty in projections of future climate. Here, we investigate how leaf trait plasticity in response to elevated CO2alters projections of tropical forest competitive dynamics and functioning. We use vegetation demographic model simulations to quantify how plasticity in leaf mass per area and leaf carbon to nitrogen ratio alter the responses of carbon uptake, evapotranspiration, and competitive ability to a doubling of CO2in a tropical forest. Observationally constrained leaf trait plasticity in response to CO2fertilization reduces the degree to which tropical tree carbon uptake is affected by a doubling of CO2(up to −14.7% as compared to a case with no plasticity; 95% confidence interval [CI95%] −14.4 to −15.0). It also diminishes evapotranspiration (up to −7.0%, CI95%−6.4 to −7.7), and lowers competitive ability in comparison to a tree with no plasticity. Consideration of leaf trait plasticity to elevated CO2lowers tropical ecosystem carbon uptake and evapotranspirative cooling in the absence of changes in plant‐type abundance. However, “plastic” responses to high CO2which maintain higher levels of plant productivity, many of which fall outside of the observed range of response, are potentially more competitively advantageous, thus, including changes in plant type abundance may mitigate these decreases in ecosystem functioning. Models that explicitly represent competition between plants with alternative leaf trait plasticity in response to elevated CO2are needed to capture these influences on tropical forest functioning and large‐scale climate. When tropical trees are grown in air with a high concentration of carbon dioxide (CO2) it has been observed that they grow leaves and change aspects of how leaves work, called leaf traits. We used computer simulations to look at how changes in two particular leaf traits, leaf thickness and the concentration of nitrogen in leaves, alter how much tropical trees grow when CO2concentrations are high. We find that trees grow less when they have lower concentrations of nitrogen in leaves, but that if they can simultaneously make their leaves thicker this alleviates the negative effects. This holds true both when plants are growing without any competition, and also corresponds to how likely they are to grow better than a neighbor with a different combination of leaf traits. Our findings suggest that if tropical trees change only the concentration of nitrogen in their leaves then tree growth and the related transfer of carbon into the land and water back to the atmosphere will be reduced. However, if the two trait changes occur simultaneously tropical forests could maintain exchanges of carbon and water close to the rates at which they currently occur. Including the observed response of leaf traits to higher CO2results in lower competitive ability for modeled tropical treesConcurrent changes in multiple leaf traits could help maintain per‐area photosynthetic rates and confer a competitive advantageResulting ecosystem‐scale carbon uptake depends on the magnitude of trait plasticity coupled with changes in plant type abundance Including the observed response of leaf traits to higher CO2results in lower competitive ability for modeled tropical trees Concurrent changes in multiple leaf traits could help maintain per‐area photosynthetic rates and confer a competitive advantage Resulting ecosystem‐scale carbon uptake depends on the magnitude of trait plasticity coupled with changes in plant type abundance

We developed vertically resolved soil biogeochemistry (carbon and nitrogen) module and implemented it into a land surface model, ISAM. The model captures the vertical heterogeneity of the northern high latitudes permafrost soil organic carbon (SOC). We also implemented Δ14C to estimate SOC turnover time, a critical determinant of SOC stocks, sequestration potential, and the carbon cycle feedback under changing atmospheric CO2concentration [CO2] and climate. ISAM accounted for the vertical movement of SOC caused by cryoturbation and its linkage to frost heaving process, oxygen availability, organo‐mineral interaction, and depth‐dependent environmental modifiers. After evaluating the model processes using the site and regional level heterotrophic respiration, SOC stocks, and soil Δ14C profiles, the vertically resolved soil biogeochemistry version of the model (ISAM‐1D) estimated permafrost SOC turnover time of 1,443 years, which is about 3 times more than the estimation based on the without vertically resolved version of ISAM (ISAM‐0D). ISAM‐1D‐simulated SOC stocks for permafrost regions was 319 Pg C in the top 1 m soil depth by the 2000s, about 80% higher than the estimates based on ISAM‐0D. ISAM‐1D SOC stock and turnover time were compared well with the observations. However, the longer SOC turnover time preserves less SOC stocks due to the lower carbon use efficiency (CUE) for SOC than ISAM‐0D and thus respires more SOC than being transferred downward by cryoturbation. ISAM‐1D simulated reduced SOC sequestration (3.7 Pg C) compared to ISAM‐0D (4.8 Pg C) and published Earth system models (ESMs) over the 1860s–2000s, due to weaker [CO2]‐carbon cycle and stronger climate‐carbon cycle feedbacks, highlighting the importance of the vertically heterogeneous soil for understanding the permafrost SOC sinks. Vertically resolved SOC cryoturbation process is implemented in ISAM for capturing the observed permafrost SOC stock and turnover timeISAM‐1D Calibrated carbon use efficiency for SOC pools shows increased respiration and less SOC transported downward through cryoturbationISAM‐1D estimates reduced SOC sequestration due to weaker CO2fertilization effect and stronger climate‐carbon cycle feedback during the 2000s

There is large uncertainty whether Amazon forests will remain a carbon sink as atmospheric CO2increases. Hence, we simulated an old‐growth tropical forest using six versions of four terrestrial models differing in scale of vegetation structure and representation of biogeochemical (BGC) cycling, all driven with CO2forcing from the preindustrial period to 2100. The models were benchmarked against tree inventory and eddy covariance data from a Brazilian site for present‐day predictions. All models predicted positive vegetation growth that outpaced mortality, leading to continual increases in present‐day biomass accumulation. Notably, the two vegetation demographic models (VDMs) (ED2 and ELM‐FATES) always predicted positive stem diameter growth in all size classes. The field data, however, indicated that a quarter of canopy trees didn't grow over the 15‐year period, and while high interannual variation existed, biomass change was near neutral. With a doubling of CO2, three of the four models predicted an appreciable biomass sink (0.77 to 1.24 Mg ha−1year−1). ELMv1‐ECA, the only model used here that includes phosphorus constraints, predicted the lowest biomass sink relative to initial biomass stocks (+21%), lower than the other BGC model, CLM5 (+48%). Models projections differed primarily through variations in nutrient constraints, then carbon allocation, initial biomass, and density‐dependent mortality. The VDM's performance was similar or better than the BGC models run in carbon‐only mode, suggesting that nutrient competition in VDMs will improve predictions. We demonstrate that VDMs are comparable to nondemographic (i.e., “big‐leaf”) models but also include finer scale demography and competition that can be evaluated against field observations. We evaluate four terrestrial models, some in multiple versions, against a 15‐year dataset of forest dynamics in BrazilAnnual biomass increments from models were within field data uncertainty, but over 15 years large biomass accumulations emerged, inconsistent with field dataWith elevating CO2out to 2100, carbon‐only models predicted large sinks, demography reduced this sink, and the model with phosphorus constraints predicted a substantially lower sink

Despite the fundamental importance of soil temperature for Earth's carbon and energy budgets, ecosystem functioning, and agricultural production, studies of climate change impacts on soil processes have mainly relied on air temperatures, assuming they are accurate proxies for soil temperatures. We evaluated changes in soil temperature, moisture, and air temperature predicted over the 21st century from 14 Earth system models. The model ensemble predicted a global mean soil warming of 2.3 ± 0.7 and 4.5 ± 1.1 °C at 100‐cm depth by the end of the 21st century for RCPs 4.5 and 8.5, respectively. Soils at 100 cm warmed at almost exactly the same rate as near‐surface (~1 cm) soils. Globally, soil warming was slightly slower than air warming above it, and this difference increased over the 21st century. Regionally, soil warming kept pace with air warming in tropical and arid regions but lagged air warming in colder regions. Thus, air warming is not necessarily a good proxy for soil warming in cold regions where snow and ice impede the direct transfer of sensible heat from the atmosphere to soil. Despite this effect, high‐latitude soils were still projected to warm faster than elsewhere, albeit at slower rates than surface air above them. When compared with observations, the models were able to capture soil thermal dynamics in most biomes, but some failed to recreate thermal properties in permafrost regions. Particularly in cold regions, using soil warming rather than air warming projections may improve predictions of temperature‐sensitive soil processes. Soil warming over the 21st century keeps pace with air warming in tropical and snow‐free regions but lags air warming in colder regionsAir warming is not a good proxy for soil warming in regions where snow and ice impede transfer of sensible heat from the atmosphere to soilDeep (100 cm) and near‐surface (~1 cm) soil layers warm at the same rate across all soil orders globally

Climate change is expected to increase the frequency of flooding events and, thus, the risks of flood‐related mortality and infrastructure damage. Global‐scale assessments of future flooding from Earth system models based only on precipitation changes neglect important processes that occur within the land surface, particularly plant physiological responses to rising CO2. Higher CO2can reduce stomatal conductance and transpiration, which may lead to increased soil moisture and runoff in some regions, promoting flooding even without changes in precipitation. Here we assess the relative impacts of plant physiological and radiative greenhouse effects on changes in daily runoff intensity over tropical continents using the Community Earth System Model. We find that extreme percentile rates increase significantly more than mean runoff in response to higher CO2. Plant physiological effects have a small impact on precipitation intensity but are a dominant driver of runoff intensification, contributing to one half of the 99th and one third of the 99.9th percentile runoff intensity changes. Floods are one of the most devastating natural disasters in the world, contributing to thousands of deaths and billions of dollars in damages annually. Climate change is expected to increase flood exposure considerably through the 21st century. However, recent studies assessing future flood risk on global scales by downscaling precipitation from Earth system models often neglect important plant physiological responses to rising CO2. In particular, higher CO2concentrations may lower stomatal conductance and, in the absence of significant plant growth, reduce water loss through transpiration, increasing soil moisture in many regions. For a given precipitation rate, higher soil moisture can decrease the amount of rain that infiltrates the soil and increase runoff. Here we apply a simulation design that isolates the independent effects of higher CO2on radiatively driven precipitation intensification from plant‐driven soil moisture changes. We show that plant‐physiological responses to increasing CO2are major drivers of the runoff intensity change in the tropics. Land surface changes contribute to one half of the 99th percentile runoff change and one third of the 99.9th percentile change. Our results suggest that comprehensive flood assessments should account for plant physiology as well as radiative impacts of higher CO2in order to better inform flood prediction and mitigation practice. Plant physiological responses drive a larger increase in the daily intensity of runoff than the annual mean in simulations with rising CO2Plant physiological responses to rising CO2contribute as much as radiative greenhouse effects to changes in the 99th percentile daily runoffAssessments of future flood risk on global scales should include both atmosphere and land‐driven impacts on rainfall and runoff intensity