Observational and model evidence together support wide-spread exposure to noncompensable heat under continued global warming.

As our planet warms, a critical research question is when and where temperatures will exceed the limits of what the human body can tolerate. Past modeling efforts have investigated the 35°C wet-bulb threshold, proposed as a theoretical upper limit to survivability taking into account physiological and behavioral adaptation. Here, we conduct an extreme value theory analysis of weather station observations and climate model projections to investigate the emergence of an empirically supported heat compensability limit. We show that the hottest parts of the world already experience these heat extremes on a limited basis and that under moderate continued warming parts of every continent, except Antarctica, will see a rapid increase in their extent and frequency. To conclude, we discuss the consequences of the emergence of this noncompensable heat and the need for incorporating different critical thermal limits into heat adaptation planning.

The Terrestrial Biosphere Model Farm.

Model Intercomparison Projects (MIPs) are fundamental to our understanding of how the land surface responds to changes in climate. However, MIPs are challenging to conduct, requiring the organization of multiple, decentralized modeling teams throughout the world running common protocols. We explored centralizing these models on a single supercomputing system. We ran nine offline terrestrial biosphere models through the Terrestrial Biosphere Model Farm: CABLE, CENTURY, HyLand, ISAM, JULES, LPJ-GUESS, ORCHIDEE, SiB-3, and SiB-CASA. All models were wrapped in a software framework driven with common forcing data, spin-up, and run protocols specified by the Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP) for years 1901-2100. We ran more than a dozen model experiments. We identify three major benefits and three major challenges. The benefits include: (a) processing multiple models through a MIP is relatively straightforward, (b) MIP protocols are run consistently across models, which may reduce some model output variability, and (c) unique multimodel experiments can provide novel output for analysis. The challenges are: (a) technological demand is large, particularly for data and output storage and transfer; (b) model versions lag those from the core model development teams; and (c) there is still a need for intellectual input from the core model development teams for insight into model results. A merger with the open-source, cloud-based Predictive Ecosystem Analyzer (PEcAn) ecoinformatics system may be a path forward to overcoming these challenges.

The global potential for increased storage of carbon on land.

Constraining the climate crisis requires urgent action to reduce anthropogenic emissions while simultaneously removing carbon dioxide from the atmosphere. Improved information about the maximum magnitude and spatial distribution of opportunities for additional land-based removals of CO2 is needed to guide on-the-ground decision-making about where to implement climate change mitigation strategies. Here, we present a globally consistent spatial dataset (approximately 500-m resolution) of current, potential, and unrealized potential carbon storage in woody plant biomass and soil organic matter. We also provide a framework for prioritizing actions related to the restoration, management, and maintenance of woody carbon stocks and associated soils. By comparing current to potential carbon storage, while excluding areas critical to food production and human habitation, we find 287 petagrams (PgC) of unrealized potential storage opportunity, of which 78% (224 PgC) is in biomass and 22% (63 PgC) is in soil. Improved management of existing forests may offer nearly three-fourths (206 PgC) of the total unrealized potential, with the majority (71%) concentrated in tropical ecosystems. However, climate change is a source of considerable uncertainty. While additional research is needed to understand the impact of natural disturbances and biophysical feedbacks, we project that the potential for additional carbon storage in woody biomass will increase (+17%) by 2050 despite projected decreases (−12%) in the tropics. Our results establish an absolute reference point and conceptual framework for national and jurisdictional prioritization of locations and actions to increase land-based carbon storage.

Temperature memory and non-structural carbohydrates mediate legacies of a hot drought in trees across the southwestern USA.

Trees are long-lived organisms that integrate climate conditions across years or decades to produce secondary growth. This integration process is sometimes referred to as 'climatic memory.' While widely perceived, the physiological processes underlying this temporal integration, such as the storage and remobilization of non-structural carbohydrates (NSC), are rarely explicitly studied. This is perhaps most apparent when considering drought legacies (perturbed post-drought growth responses to climate), and the physiological mechanisms underlying these lagged responses to climatic extremes. Yet, drought legacies are likely to become more common if warming climate brings more frequent drought. To quantify the linkages between drought legacies, climate memory and NSC, we measured tree growth (via tree ring widths) and NSC concentrations in three dominant species across the southwestern USA. We analyzed these data with a hierarchical mixed effects model to evaluate the time-scales of influence of past climate (memory) on tree growth. We then evaluated the role of climate memory and the degree to which variation in NSC concentrations were related to forward-predicted growth during the hot 2011-2012 drought and subsequent 4-year recovery period. Populus tremuloides exhibited longer climatic memory compared to either Pinus edulis or Juniperus osteosperma, but following the 2011-2012 drought, P. tremuloides trees with relatively longer memory of temperature conditions showed larger (more negative) drought legacies. Conversely, Pinus edulis trees with longer temperature memory had smaller (less negative) drought legacies. For both species, higher NSC concentrations followed more negative (larger) drought legacies, though the relevant NSC fraction differed between P. tremuloides and P. edulis. Our results suggest that differences in tree NSC are also imprinted upon tree growth responses to climate across long time scales, which also underlie tree resilience to increasingly frequent drought events under climate change.

Patterns of post-drought recovery are strongly influenced by drought duration, frequency, post-drought wetness, and bioclimatic setting.

Understanding vegetation recovery after drought is critical for projecting vegetation dynamics in future climates. From 1997 to 2009, Australia experienced a long-lasting drought known as the Millennium Drought (MD), which led to widespread reductions in vegetation productivity. However, vegetation recovery post-drought and its determinants remain unclear. This study leverages remote sensing products from different sources-fraction of absorbed photosynthetically active radiation (FPAR), based on optical data, and canopy density, derived from microwave data-and random forest algorithms to assess drought recovery over Australian natural vegetation during a 20-year period centered on the MD. Post-drought recovery was prevalent across the continent, with 6 out of 10 drought events seeing full recovery within about 6 months. Canopy density was slower to recover than leaf area seen in FPAR. The probability of full recovery was most strongly controlled by drought return interval, post-drought hydrological condition, and drought length. Full recovery was seldom observed when drought events occurred at intervals of 3 months or less, and moderately dry (standardized water balance anomaly [SWBA] within [-1, -0.76]) post-drought conditions resulted in less complete recovery than wet (SWBA > 0.3) post-drought conditions. Press droughts, which are long term but not extreme, delayed recovery more than pulse droughts (short term but extreme) and led to a higher frequency of persistent decline. Following press droughts, the frequency of persistent decline differed little among biome types but peaked in semi-arid regions across aridity levels. Forests and savanna required the longest recovery times for press drought, while grasslands were the slowest to recover for pulse drought. This study provides quantitative thresholds that could be used to improve the modeling of ecosystem dynamics post-drought.

How close are we to the temperature tipping point of the terrestrial biosphere?

The temperature dependence of global photosynthesis and respiration determine land carbon sink strength. While the land sink currently mitigates ~30% of anthropogenic carbon emissions, it is unclear whether this ecosystem service will persist and, more specifically, what hard temperature limits, if any, regulate carbon uptake. Here, we use the largest continuous carbon flux monitoring network to construct the first observationally derived temperature response curves for global land carbon uptake. We show that the mean temperature of the warmest quarter (3-month period) passed the thermal maximum for photosynthesis during the past decade. At higher temperatures, respiration rates continue to rise in contrast to sharply declining rates of photosynthesis. Under business-as-usual emissions, this divergence elicits a near halving of the land sink strength by as early as 2040.

Temporal controls on crown nonstructural carbohydrates in southwestern US tree species.

In trees, large uncertainties remain in how nonstructural carbohydrates (NSCs) respond to variation in water availability in natural, intact ecosystems. Variation in NSC pools reflects temporal fluctuations in supply and demand, as well as physiological coordination across tree organs in ways that differ across species and NSC fractions (e.g., soluble sugars vs starch). Using landscape-scale crown (leaves and twigs) NSC concentration measurements in three foundation tree species (Populus tremuloides, Pinus edulis, Juniperus osteosperma), we evaluated in situ, seasonal variation in NSC responses to moisture stress on three timescales: short-term (via predawn water potential), seasonal (via leaf δ13C) and annual (via current year's ring width index). Crown NSC responses to moisture stress appeared to depend on hydraulic strategy, where J. osteosperma appears to regulate osmotic potentials (via higher sugar concentrations), P. edulis NSC responses suggest respiratory depletion and P. tremuloides responses were consistent with direct sink limitations. We also show that overly simplistic models can mask seasonal and tissue variation in NSC responses, as well as strong interactions among moisture stress at different timescales. In general, our results suggest large seasonal variation in crown NSC concentrations reflecting the multiple cofunctions of NSCs in plant tissues, including storage, growth and osmotic regulation of hydraulically vulnerable leaves. We emphasize that crown NSC pool size cannot be viewed as a simple physiological metric of stress; in situ NSC dynamics are complex, varying temporally, across species, among NSC fractions and among tissue types.

RCP8.5 tracks cumulative CO2 emissions.

Climate simulation-based scenarios are routinely used to characterize a range of plausible climate futures. Despite some recent progress on bending the emissions curve, RCP8.5, the most aggressive scenario in assumed fossil fuel use for global climate models, will continue to serve as a useful tool for quantifying physical climate risk, especially over near- to midterm policy-relevant time horizons. Not only are the emissions consistent with RCP8.5 in close agreement with historical total cumulative CO2 emissions (within 1%), but RCP8.5 is also the best match out to midcentury under current and stated policies with still highly plausible levels of CO2 emissions in 2100.

Author Correction: Modeling suggests fossil fuel emissions have been driving increased land carbon uptake since the turn of the 20th Century.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Modeling suggests fossil fuel emissions have been driving increased land carbon uptake since the turn of the 20th Century.

Terrestrial vegetation removes CO2 from the atmosphere; an important climate regulation service that slows global warming. This 119 Pg C per annum transfer of CO2 into plants-gross primary productivity (GPP)-is the largest land carbon flux globally. While understanding past and anticipated future GPP changes is necessary to support carbon management, the factors driving long-term changes in GPP are largely unknown. Here we show that 1901 to 2010 changes in GPP have been dominated by anthropogenic activity. Our dual constraint attribution approach provides three insights into the spatiotemporal patterns of GPP change. First, anthropogenic controls on GPP change have increased from 57% (1901 decade) to 94% (2001 decade) of the vegetated land surface. Second, CO2 fertilization and nitro gen deposition are the most important drivers of change, 19.8 and 11.1 Pg C per annum (2001 decade) respectively, especially in the tropics and industrialized areas since the 1970's. Third, changes in climate have functioned as fertilization to enhance GPP (1.4 Pg C per annum in the 2001 decade). These findings suggest that, from a land carbon balance perspective, the Anthropocene began over 100 years ago and that global change drivers have allowed GPP uptake to keep pace with anthropogenic emissions.

Ghosts of the past: how drought legacy effects shape forest functioning and carbon cycling.

Multi-year lags in tree drought recovery, termed 'drought legacy effects', are important for understanding the impacts of drought on forest ecosystems, including carbon (C) cycle feedbacks to climate change. Despite the ubiquity of lags in drought recovery, large uncertainties remain regarding the mechanistic basis of legacy effects and their importance for the C cycle. In this review, we identify the approaches used to study legacy effects, from tree rings to whole forests. We then discuss key knowledge gaps pertaining to the causes of legacy effects, and how the various mechanisms that may contribute these lags in drought recovery could have contrasting implications for the C cycle. Furthermore, we conduct a novel data synthesis and find that legacy effects differ drastically in both size and length across the US depending on if they are identified in tree rings versus gross primary productivity. Finally, we highlight promising approaches for future research to improve our capacity to model legacy effects and predict their impact on forest health. We emphasise that a holistic view of legacy effects - from tissues to whole forests - will advance our understanding of legacy effects and stimulate efforts to investigate drought recovery via experimental, observational and modelling approaches.

Global vegetation biomass production efficiency constrained by models and observations.

Plants use only a fraction of their photosynthetically derived carbon for biomass production (BP). The biomass production efficiency (BPE), defined as the ratio of BP to photosynthesis, and its variation across and within vegetation types is poorly understood, which hinders our capacity to accurately estimate carbon turnover times and carbon sinks. Here, we present a new global estimation of BPE obtained by combining field measurements from 113 sites with 14 carbon cycle models. Our best estimate of global BPE is 0.41 ± 0.05, excluding cropland. The largest BPE is found in boreal forests (0.48 ± 0.06) and the lowest in tropical forests (0.40 ± 0.04). Carbon cycle models overestimate BPE, although models with carbon-nitrogen interactions tend to be more realistic. Using observation-based estimates of global photosynthesis, we quantify the global BP of non-cropland ecosystems of 41 ± 6 Pg C/year. This flux is less than net primary production as it does not contain carbon allocated to symbionts, used for exudates or volatile carbon compound emissions to the atmosphere. Our study reveals a positive bias of 24 ± 11% in the model-estimated BP (10 of 14 models). When correcting models for this bias while leaving modeled carbon turnover times unchanged, we found that the global ecosystem carbon storage change during the last century is decreased by 67% (or 58 Pg C).

Carbon and Water Use Efficiencies: A Comparative Analysis of Ten Terrestrial Ecosystem Models under Changing Climate.

Terrestrial ecosystems carbon and water cycles are tightly coupled through photosynthesis and evapotranspiration processes. The ratios of carbon stored to carbon uptake and water loss to carbon gain are key ecophysiological indicators essential to assess the magnitude and response of the terrestrial plant to the changing climate. Here, we use estimates from 10 terrestrial ecosystem models to quantify the impacts of climate, atmospheric CO2 concentration, and nitrogen (N) deposition on water use efficiency (WUE), and carbon use efficiency (CUE). We find that across models, WUE increases over the 20th Century particularly due to CO2 fertilization and N deposition and compares favorably to experimental studies. Also, the results show a decrease in WUE with climate for the last 3 decades, in contrasts with up-scaled flux observations that demonstrate a constant WUE. Modeled WUE responds minimally to climate with modeled CUE exhibiting no clear trend across space and time. The divergence between simulated and observationally-constrained WUE and CUE is driven by modeled NPP and autotrophic respiration, nitrogen cycle, carbon allocation, and soil moisture dynamics in current ecosystem models. We suggest that carbon-modeling community needs to reexamine stomatal conductance schemes and the soil-vegetation interactions for more robust modeling of carbon and water cycles.

Ecological memory of daily carbon exchange across the globe and its importance in drylands.

How do antecedent (past) conditions influence land-carbon dynamics after those conditions no longer persist? In particular, quantifying such memory effects associated with the influence of past environmental (exogenous) and biological (endogenous) conditions is crucial for understanding and predicting the carbon cycle. Here we show, using data from 42 eddy covariance sites across six major biomes, that ecological memory-decomposed into environmental and biological memory components-of daily net carbon exchange (NEE) is critical for understanding the land-carbon metabolism, especially in drylands for which memory explains ~ 32% of the variation in NEE. The strong environmental memory in drylands was primarily driven by short- and long-term moisture status. Moreover, the strength of environmental memory scales with increasing water stress. This universal scaling relationship, emerging within and among major biomes, suggests a potential adaptive response to water limitation. Our findings underscore the necessity of considering ecological memory in experiments, observations and modelling.

The FLUXCOM ensemble of global land-atmosphere energy fluxes.

Although a key driver of Earth's climate system, global land-atmosphere energy fluxes are poorly constrained. Here we use machine learning to merge energy flux measurements from FLUXNET eddy covariance towers with remote sensing and meteorological data to estimate global gridded net radiation, latent and sensible heat and their uncertainties. The resulting FLUXCOM database comprises 147 products in two setups: (1) 0.0833° resolution using MODIS remote sensing data (RS) and (2) 0.5° resolution using remote sensing and meteorological data (RS + METEO). Within each setup we use a full factorial design across machine learning methods, forcing datasets and energy balance closure corrections. For RS and RS + METEO setups respectively, we estimate 2001-2013 global (±1 s.d.) net radiation as 75.49 ± 1.39 W m-2 and 77.52 ± 2.43 W m-2, sensible heat as 32.39 ± 4.17 W m-2 and 35.58 ± 4.75 W m-2, and latent heat flux as 39.14 ± 6.60 W m-2 and 39.49 ± 4.51 W m-2 (as evapotranspiration, 75.6 ± 9.8 × 103 km3 yr-1 and 76 ± 6.8 × 103 km3 yr-1). FLUXCOM products are suitable to quantify global land-atmosphere interactions and benchmark land surface model simulations.

Land carbon models underestimate the severity and duration of drought's impact on plant productivity.

The ability to accurately predict ecosystem drought response and recovery is necessary to produce reliable forecasts of land carbon uptake and future climate. Using a suite of models from the Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP), we assessed modeled net primary productivity (NPP) response to, and recovery from, drought events against a benchmark derived from tree ring observations between 1948 and 2008 across forested regions of the US and Europe. We find short lag times (0-6 months) between climate anomalies and modeled NPP response. Although models accurately simulate the direction of drought legacy effects (i.e. NPP decreases), projected effects are approximately four times shorter and four times weaker than observations suggest. This discrepancy between observed and simulated vegetation recovery from drought reveals a potential critical model deficiency. Since productivity is a crucial component of the land carbon balance, models that underestimate drought recovery time could overestimate predictions of future land carbon sink strength and, consequently, underestimate forecasts of atmospheric CO2.

Enhanced peak growth of global vegetation and its key mechanisms.

The annual peak growth of vegetation is critical in characterizing the capacity of terrestrial ecosystem productivity and shaping the seasonality of atmospheric CO2 concentrations. The recent greening of global lands suggests an increasing trend of terrestrial vegetation growth, but whether or not the peak growth has been globally enhanced still remains unclear. Here, we use two global datasets of gross primary productivity (GPP) and a satellite-derived Normalized Difference Vegetation Index (NDVI) to characterize recent changes in annual peak vegetation growth (that is, GPPmax and NDVImax). We demonstrate that the peak in the growth of global vegetation has been linearly increasing during the past three decades. About 65% of the NDVImax variation is evenly explained by expanding croplands (21%), rising CO2 (22%) and intensifying nitrogen deposition (22%). The contribution of expanding croplands to the peak growth trend is substantiated by measurements from eddy-flux towers, sun-induced chlorophyll fluorescence and a global database of plant traits, all of which demonstrate that croplands have a higher photosynthetic capacity than other vegetation types. The large contribution of CO2 is also supported by a meta-analysis of 466 manipulative experiments and 15 terrestrial biosphere models. Furthermore, we show that the contribution of GPPmax to the change in annual GPP is less in the tropics than in other regions. These multiple lines of evidence reveal an increasing trend in the peak growth of global vegetation. The findings highlight the important roles of agricultural intensification and atmospheric changes in reshaping the seasonality of global vegetation growth.

Accelerating rates of Arctic carbon cycling revealed by long-term atmospheric CO2 measurements.

The contemporary Arctic carbon balance is uncertain, and the potential for a permafrost carbon feedback of anywhere from 50 to 200 petagrams of carbon (Schuur et al., 2015) compromises accurate 21st-century global climate system projections. The 42-year record of atmospheric CO2 measurements at Barrow, Alaska (71.29 N, 156.79 W), reveals significant trends in regional land-surface CO2 anomalies (ΔCO2), indicating long-term changes in seasonal carbon uptake and respiration. Using a carbon balance model constrained by ΔCO2, we find a 13.4% decrease in mean carbon residence time (50% confidence range = 9.2 to 17.6%) in North Slope tundra ecosystems during the past four decades, suggesting a transition toward a boreal carbon cycling regime. Temperature dependencies of respiration and carbon uptake suggest that increases in cold season Arctic labile carbon release will likely continue to exceed increases in net growing season carbon uptake under continued warming trends.

Global patterns of drought recovery.

Drought, a recurring phenomenon with major impacts on both human and natural systems, is the most widespread climatic extreme that negatively affects the land carbon sink. Although twentieth-century trends in drought regimes are ambiguous, across many regions more frequent and severe droughts are expected in the twenty-first century. Recovery time-how long an ecosystem requires to revert to its pre-drought functional state-is a critical metric of drought impact. Yet the factors influencing drought recovery and its spatiotemporal patterns at the global scale are largely unknown. Here we analyse three independent datasets of gross primary productivity and show that, across diverse ecosystems, drought recovery times are strongly associated with climate and carbon cycle dynamics, with biodiversity and CO2 fertilization as secondary factors. Our analysis also provides two key insights into the spatiotemporal patterns of drought recovery time: first, that recovery is longest in the tropics and high northern latitudes (both vulnerable areas of Earth's climate system) and second, that drought impacts (assessed using the area of ecosystems actively recovering and time to recovery) have increased over the twentieth century. If droughts become more frequent, as expected, the time between droughts may become shorter than drought recovery time, leading to permanently damaged ecosystems and widespread degradation of the land carbon sink.