Terrestrial ecosystems remove about 30 per cent of the carbon dioxide (CO2) emitted by human activities each year1, yet the persistence ofthis carbon sink depends partly on how plant biomass and soil ...organic carbon (SOC) stocks respond to future increases in atmospheric CO2 (refs. 23). Although plant biomass often increases in elevated CO2 (eCO2) experiments4-6, SOC has been observed to increase, remain unchanged or even decline7. The mechanisms that drive this variation across experiments remain poorly understood, creating uncertainty in climate projections8,9. Here we synthesized data from 108 eCO2 experiments and found that the effect of eCO2 on SOC stocks is best explained by a negative relationship with plant biomass: when plant biomass is strongly stimulated by eCO2, SOC storage declines; conversely, when biomass is weakly stimulated, SOC storage increases. This trade-off appears to be related to plant nutrient acquisition, in which plants increase their biomass by mining the soil for nutrients, which decreases SOC storage. We found that, overall, SOC stocks increase with eCO2 in grasslands (8 ± 2 per cent) but not in forests (0 ± 2 per cent), even though plant biomass in grasslands increase less (9 ± 3 per cent) than in forests (23 ± 2 per cent). Ecosystem models do not reproduce this trade-off, which implies that projections of SOC may need to be revised.
Land evapotranspiration (ET) estimates are available from several global data sets. Here, monthly global land ET synthesis products, merged from these individual data sets over the time periods ...1989–1995 (7 yr) and 1989–2005 (17 yr), are presented. The merged synthesis products over the shorter period are based on a total of 40 distinct data sets while those over the longer period are based on a total of 14 data sets. In the individual data sets, ET is derived from satellite and/or in situ observations (diagnostic data sets) or calculated via land-surface models (LSMs) driven with observations-based forcing or output from atmospheric reanalyses. Statistics for four merged synthesis products are provided, one including all data sets and three including only data sets from one category each (diagnostic, LSMs, and reanalyses). The multi-annual variations of ET in the merged synthesis products display realistic responses. They are also consistent with previous findings of a global increase in ET between 1989 and 1997 (0.13 mm yr−2 in our merged product) followed by a significant decrease in this trend (−0.18 mm yr−2), although these trends are relatively small compared to the uncertainty of absolute ET values. The global mean ET from the merged synthesis products (based on all data sets) is 493 mm yr−1 (1.35 mm d−1) for both the 1989–1995 and 1989–2005 products, which is relatively low compared to previously published estimates. We estimate global runoff (precipitation minus ET) to 263 mm yr−1 (34 406 km3 yr−1) for a total land area of 130 922 000 km2. Precipitation, being an important driving factor and input to most simulated ET data sets, presents uncertainties between single data sets as large as those in the ET estimates. In order to reduce uncertainties in current ET products, improving the accuracy of the input variables, especially precipitation, as well as the parameterizations of ET, are crucial.
Land models, which have been developed by the modeling community in the past few decades to predict future states of ecosystems and climate, have to be critically evaluated for their performance ...skills of simulating ecosystem responses and feedback to climate change. Benchmarking is an emerging procedure to measure performance of models against a set of defined standards. This paper proposes a benchmarking framework for evaluation of land model performances and, meanwhile, highlights major challenges at this infant stage of benchmark analysis. The framework includes (1) targeted aspects of model performance to be evaluated, (2) a set of benchmarks as defined references to test model performance, (3) metrics to measure and compare performance skills among models so as to identify model strengths and deficiencies, and (4) model improvement. Land models are required to simulate exchange of water, energy, carbon and sometimes other trace gases between the atmosphere and land surface, and should be evaluated for their simulations of biophysical processes, biogeochemical cycles, and vegetation dynamics in response to climate change across broad temporal and spatial scales. Thus, one major challenge is to select and define a limited number of benchmarks to effectively evaluate land model performance. The second challenge is to develop metrics of measuring mismatches between models and benchmarks. The metrics may include (1) a priori thresholds of acceptable model performance and (2) a scoring system to combine data-model mismatches for various processes at different temporal and spatial scales. The benchmark analyses should identify clues of weak model performance to guide future development, thus enabling improved predictions of future states of ecosystems and climate. The near-future research effort should be on development of a set of widely acceptable benchmarks that can be used to objectively, effectively, and reliably evaluate fundamental properties of land models to improve their prediction performance skills.
T-cell trafficking at vascular sites has emerged as a key step in antitumour immunity. Chemokines are credited with guiding the multistep recruitment of CD8(+) T cells across tumour vessels. However, ...the multiplicity of chemokines within tumours has obscured the contributions of individual chemokine receptor/chemokine pairs to this process. Moreover, recent studies have challenged whether T cells require chemokine receptor signalling at effector sites. Here we investigate the hierarchy of chemokine receptor requirements during T-cell trafficking to murine and human melanoma. These studies reveal a non-redundant role for Gαi-coupled CXCR3 in stabilizing intravascular adhesion and extravasation of adoptively transferred CD8(+) effectors that is indispensable for therapeutic efficacy. In contrast, functional CCR2 and CCR5 on CD8(+) effectors fail to support trafficking despite the presence of intratumoral cognate chemokines. Taken together, these studies identify CXCR3-mediated trafficking at the tumour vascular interface as a critical checkpoint to effective T-cell-based cancer immunotherapy.
Quantification of global land evapotranspiration (ET) has long been associated with large uncertainties due to the lack of reference observations. Several recently developed products now provide the ...capacity to estimate ET at global scales. These products, partly based on observational data, include satellite based products, land surface model (LSM) simulations, atmospheric reanalysis output, estimates based on empirical upscaling of eddycovariance flux measurements, and atmospheric water balance datasets. The LandFlux-EVAL project aims to evaluate and compare these newly developed datasets. Additionally, an evaluation of IPCC AR4 global climate model (GCM) simulations is presented, providing an assessment of their capacity to reproduce flux behavior relative to the observations based products. Though differently constrained with observations, the analyzed reference datasets display similar large-scale ET patterns. ET from the IPCC AR4 simulations was significantly smaller than that from the other products for India (up to 1 mm/d) and parts of eastern South America, and larger in the western USA, Australia and China. The inter-product variance is lower across the IPCC AR4 simulations than across the reference datasets in several regions, which indicates that uncertainties may be underestimated in the IPCC AR4 models due to shared biases of these simulations.
From 2007 to 2013, the globally averaged mole fraction of methane in the atmosphere increased by 5.7 ± 1.2 ppb yr−1. Simultaneously, δ13CCH4 (a measure of the 13C/12C isotope ratio in methane) has ...shifted to significantly more negative values since 2007. Growth was extreme in 2014, at 12.5 ± 0.4 ppb, with a further shift to more negative values being observed at most latitudes. The isotopic evidence presented here suggests that the methane rise was dominated by significant increases in biogenic methane emissions, particularly in the tropics, for example, from expansion of tropical wetlands in years with strongly positive rainfall anomalies or emissions from increased agricultural sources such as ruminants and rice paddies. Changes in the removal rate of methane by the OH radical have not been seen in other tracers of atmospheric chemistry and do not appear to explain short‐term variations in methane. Fossil fuel emissions may also have grown, but the sustained shift to more 13C‐depleted values and its significant interannual variability, and the tropical and Southern Hemisphere loci of post‐2007 growth, both indicate that fossil fuel emissions have not been the dominant factor driving the increase. A major cause of increased tropical wetland and tropical agricultural methane emissions, the likely major contributors to growth, may be their responses to meteorological change.
Plain Language Summary
Atmospheric methane, which is a powerful greenhouse gas, is increasing rapidly. In the 20th century, methane growth was primarily driven by emissions from fossil fuel sources, such as the natural gas industry and coal mining. Then, in the early years of the 21st century, came a period of stability in methane. However, since 2007, growth has resumed, with especially strong growth in 2014. Evidence from carbon isotopes implies that the primary cause of the new growth is an increase in biogenic emissions, probably from wetlands and also agricultural sources, such as rice fields and cattle. The evidence presented in this research study, from a wide range of measurement sites both in the northern and southern hemispheres, suggests increased tropical emissions, for example from tropical wetlands, may be a principal cause of the global rise in methane. Contributions to the growth may also come from agricultural sources and perhaps some fossil fuel emissions also.
Key Points
Atmospheric methane is growing rapidly
Isotopic evidence implies that the growth is driven by biogenic sources
Growth is dominated by tropical sources
Although plant photosynthetic capacity as determined by the maximum carboxylation rate (i.e., Vc, max25) and the maximum electron transport rate (i.e., Jmax25) at a reference temperature (generally ...25 °C) is known to vary considerably in space and time in response to environmental conditions, it is typically parameterized in Earth system models (ESMs) with tabulated values associated with plant functional types. In this study, we have developed a mechanistic model of leaf utilization of nitrogen for assimilation (LUNA) to predict photosynthetic capacity at the global scale under different environmental conditions. We adopt an optimality hypothesis to nitrogen allocation among light capture, electron transport, carboxylation and respiration. The LUNA model is able to reasonably capture the measured spatial and temporal patterns of photosynthetic capacity as it explains ∼ 55 % of the global variation in observed values of Vc, max25 and ∼ 65 % of the variation in the observed values of Jmax25. Model simulations with LUNA under current and future climate conditions demonstrate that modeled values of Vc, max25 are most affected in high-latitude regions under future climates. ESMs that relate the values of Vc, max25 or Jmax25 to plant functional types only are likely to substantially overestimate future global photosynthesis.
Terrestrial ecosystems play a vital role in regulating the accumulation of carbon (C) in the atmosphere. Understanding the factors controlling land C uptake is critical for reducing uncertainties in ...projections of future climate. The relative importance of changing climate, rising atmospheric CO
, and other factors, however, remains unclear despite decades of research. Here, we use an ensemble of land models to show that models disagree on the primary driver of cumulative C uptake for 85% of vegetated land area. Disagreement is largest in model sensitivity to rising atmospheric CO
which shows almost twice the variability in cumulative land uptake since 1901 (1 s.d. of 212.8 PgC vs. 138.5 PgC, respectively). We find that variability in CO
and temperature sensitivity is attributable, in part, to their compensatory effects on C uptake, whereby comparable estimates of C uptake can arise by invoking different sensitivities to key environmental conditions. Conversely, divergent estimates of C uptake can occur despite being based on the same environmental sensitivities. Together, these findings imply an important limitation to the predictability of C cycling and climate under unprecedented environmental conditions. We suggest that the carbon modeling community prioritize a probabilistic multi-model approach to generate more robust C cycle projections.
The WAter Cycle Multi-mission Observation Strategy – EvapoTranspiration (WACMOS-ET) project aims to advance the development of land evaporation estimates on global and regional scales. Its main ...objective is the derivation, validation, and intercomparison of a group of existing evaporation retrieval algorithms driven by a common forcing data set. Three commonly used process-based evaporation methodologies are evaluated: the Penman–Monteith algorithm behind the official Moderate Resolution Imaging Spectroradiometer (MODIS) evaporation product (PM-MOD), the Global Land Evaporation Amsterdam Model (GLEAM), and the Priestley–Taylor Jet Propulsion Laboratory model (PT-JPL). The resulting global spatiotemporal variability of evaporation, the closure of regional water budgets, and the discrete estimation of land evaporation components or sources (i.e. transpiration, interception loss, and direct soil evaporation) are investigated using river discharge data, independent global evaporation data sets and results from previous studies. In a companion article (Part 1), Michel et al. (2016) inspect the performance of these three models at local scales using measurements from eddy-covariance towers and include in the assessment the Surface Energy Balance System (SEBS) model. In agreement with Part 1, our results indicate that the Priestley and Taylor products (PT-JPL and GLEAM) perform best overall for most ecosystems and climate regimes. While all three evaporation products adequately represent the expected average geographical patterns and seasonality, there is a tendency in PM-MOD to underestimate the flux in the tropics and subtropics. Overall, results from GLEAM and PT-JPL appear more realistic when compared to surface water balances from 837 globally distributed catchments and to separate evaporation estimates from ERA-Interim and the model tree ensemble (MTE). Nonetheless, all products show large dissimilarities during conditions of water stress and drought and deficiencies in the way evaporation is partitioned into its different components. This observed inter-product variability, even when common forcing is used, suggests that caution is necessary in applying a single data set for large-scale studies in isolation. A general finding that different models perform better under different conditions highlights the potential for considering biome- or climate-specific composites of models. Nevertheless, the generation of a multi-product ensemble, with weighting based on validation analyses and uncertainty assessments, is proposed as the best way forward in our long-term goal to develop a robust observational benchmark data set of continental evaporation.
The oil and gas (O&G) sector is a significant source
of methane (CH4) emissions. Quantifying these emissions remains
challenging, with many studies highlighting discrepancies between
measurements and ...inventory-based estimates. In this study, we present
CH4 emission fluxes from 21 offshore O&G facilities collected in 10
O&G fields over two regions of the Norwegian continental shelf in 2019.
Emissions of CH4 derived from measurements during 13 aircraft surveys
were found to range from 2.6 to 1200 t yr−1 (with a mean of 211 t yr−1 across all 21 facilities). Comparing this with aggregated
operator-reported facility emissions for 2019, we found excellent agreement
(within 1σ uncertainty), with mean aircraft-measured fluxes only
16 % lower than those reported by operators. We also compared
aircraft-derived fluxes with facility fluxes extracted from a global gridded
fossil fuel CH4 emission inventory compiled for 2016. We found that the
measured emissions were 42 % larger than the inventory for the area
covered by this study, for the 21 facilities surveyed (in aggregate). We
interpret this large discrepancy not to reflect a systematic error in the
operator-reported emissions, which agree with measurements, but rather the
representativity of the global inventory due to the methodology used to
construct it and the fact that the inventory was compiled for 2016 (and thus
not representative of emissions in 2019). This highlights the need for
timely and up-to-date inventories for use in research and policy. The
variable nature of CH4 emissions from individual facilities requires
knowledge of facility operational status during measurements for data to be
useful in prioritising targeted emission mitigation solutions. Future
surveys of individual facilities would benefit from knowledge of facility
operational status over time. Field-specific aggregated emissions (and
uncertainty statistics), as presented here for the Norwegian Sea, can be
meaningfully estimated from intensive aircraft surveys. However,
field-specific estimates cannot be reliably extrapolated to other production
fields without their own tailored surveys, which would need to capture a
range of facility designs, oil and gas production volumes, and facility
ages. For year-on-year comparison to annually updated inventories and
regulatory emission reporting, analogous annual surveys would be needed for
meaningful top-down validation. In summary, this study demonstrates the
importance and accuracy of detailed, facility-level emission accounting and
reporting by operators and the use of airborne measurement approaches to
validate bottom-up accounting.
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