Spatial and temporal variations in plant water-use efficiency inferred from tree-ring, eddy covariance and atmospheric observations

This is the final version of the article. Available from the European Geosciences Union (EGU) via the DOI in this record.Plant water-use efficiency (WUE), which is the ratio of the uptake of carbon dioxide through photosynthesis to the loss of water through transpiration, is a very useful metric of the functioning of the land biosphere. WUE is expected to increase with atmospheric CO2, but to decline with increasing atmospheric evaporative demand – which can arise from increases in near-surface temperature or decreases in relative humidity. We have used Δ13C measurements from tree rings, along with eddy covariance measurements from Fluxnet sites, to estimate the sensitivities of WUE to changes in CO2 and atmospheric humidity deficit. This enables us to reconstruct fractional changes in WUE, based on changes in atmospheric climate and CO2, for the entire period of the instrumental global climate record. We estimate that overall WUE increased from 1900 to 2010 by 48±22%, which is more than double that simulated by the latest Earth System Models. This long-term trend is largely driven by increases in CO2, but significant inter-annual variability and regional differences are evident due to variations in temperature and relative humidity. There are several highly populated regions, such as western Europe and East Asia, where the rate of increase of WUE has declined sharply in the last 2 decades. Our data-based analysis indicates increases in WUE that typically exceed those simulated by Earth System Models-implying that these models are either underestimating increases in photosynthesis or underestimating reductions in transpiration.The contributions of M. Groenendijk, C. Huntingford, and P. M. Cox were funded by the UK Natural Environment Research Council (NERC) HYDRA project. We thank Margaret Barbour for providing tree-ring data compiled from many different sources. This work used eddy covariance data acquired by the FLUXNET community and in particular by the following networks: AmeriFlux (US Department of Energy, Biological and Environmental Research, Terrestrial Carbon Program (DE-FG02-04ER63917 and DE-FG02-04ER63911)), AfriFlux, AsiaFlux, CarboAfrica, CarboEuropeIP, CarboItaly, CarboMont, ChinaFlux, Fluxnet-Canada (supported by CFCAS, NSERC, BIOCAP, Environment Canada, and NRCan), GreenGrass, KoFlux, LBA, NECC, OzFlux, TCOS-Siberia, USCCC. We acknowledge the financial support to the eddy covariance data harmonization provided by CarboEuropeIP, FAO-GTOS-TCO, iLEAPS, Max Planck Institute for Biogeochemistry, National Science Foundation, University of Tuscia, Université Laval and Environment Canada and US Department of Energy and the database development and technical support from Berkeley Water Center, Lawrence Berkeley National Laboratory, Microsoft Research eScience, Oak Ridge National Laboratory, University of California – Berkeley, University of Virginia

Spatial and temporal variations in plant water-use efficiency inferred from tree-ring, eddy covariance and atmospheric observations

Plant water-use efficiency (WUE), which is the ratio of the uptake of carbon dioxide through photosynthesis to the loss of water through transpiration, is a very useful metric of the functioning of the land biosphere. WUE is expected to increase with atmospheric CO2, but to decline with increasing atmospheric evaporative demand – which can arisefrom increases in near-surface temperature or decreases in relative humidity.We have used Δ13C measurements from tree rings, along witheddy covariance measurements from Fluxnet sites, to estimate thesensitivities of WUE to changes in CO2 and atmospheric humidity deficit.This enables us to reconstruct fractional changes in WUE, based on changes inatmospheric climate and CO2, for the entire period of the instrumental global climate record. We estimate that overall WUE increased from 1900 to2010 by 48 ± 22 %, which is more than double that simulated by thelatest Earth System Models. This long-term trend is largely driven byincreases in CO2, but significant inter-annual variability and regional differences are evident due to variations in temperature and relativehumidity. There are several highly populated regions, such as western Europeand East Asia, where the rate of increase of WUE has declined sharply in thelast 2 decades. Our data-based analysis indicates increases in WUE thattypically exceed those simulated by Earth System Models – implying thatthese models are either underestimating increases in photosynthesis orunderestimating reductions in transpiration

Extent of partial ice cover due to carbon cycle feedback in a zonal energy balance model

International audienceA global carbon cycle is introduced into a zonally averaged energy balance climate model. The physical model components are similar to those of Budyko (1969) and Sellers (1969). The new carbon components account for atmospheric carbon dioxide concentrations and the terrestrial and oceanic storage of carbon. Prescribing values for the sum of these carbon components, it is found that inclusion of a closed carbon cycle reduces the range of insolation over which stable partial ice cover solutions may occur. This highly simplified climate model also predicts that the estimated release of carbon from fossil fuel burning over the next hundred years could result in the eventual melting of the ice sheets. Keywords: climate, carbon cycle,zonal model, earth system modellin

Carbon budget for 1.5 and 2oC targets lowered by natural wetland and permafrost feedbacks

Methane emissions from natural wetlands and carbon release from permafrost thaw have a positive feedback on climate, yet are not represented in most state-of-the-art climate models. Furthermore, a fraction of the thawed permafrost carbon is released as methane, enhancing the combined feedback strength. We present simulations with an intermediate complexity climate model which follow prescribed global warming pathways to stabilisation at 1.5°C or 2.0°C above pre-industrial levels by the year 2100, and that incorporates a state-of-the-art global land surface model with updated descriptions of wetland and permafrost carbon release. We demonstrate that the climate feedbacks from those two processes are substantial. Specifically, permissible anthropogenic fossil fuel CO2 emission budgets are reduced by 17-23% (47-56 GtC) for stabilisation at 1.5°C, and 9-13% (52-57 GtC) for 2.0°C stabilisation. In our simulations these feedback processes respond faster at temperatures below 1.5°C, and the differences between the 1.5°C and 2°C targets are disproportionately small. This key finding is due to our interest in transient emission pathways to the year 2100 and does not consider the longer term implications of these feedback processes. We conclude that natural feedback processes from wetlands and permafrost must be considered in assessments of transient emission pathways to limit global warming

Characterisation of the immune-related transcriptome in resected biliary tract cancers

Although biliary tract cancers (BTCs) are known to have an inflammatory component, a detailed characterisation of immune-related transcripts has never been performed. In these studies, nCounter PanCancer Immune Profiling Panel was used to assess the expression of 770 immune-related transcripts in the tumour tissues (TTs) and matched adjacent tissues (ATs) of resected BTCs. Cox regression analysis and Kaplan-Meier methods were used to correlate findings with relapse-free survival (RFS). The first analysis in the TT and AT of an exploratory set (n = 22) showed deregulation of 39 transcripts associated with T-cell activation. Risk of recurrence was associated with a greater number of genes deregulated in AT in comparison to TT. Analysis in the whole set (n = 53) showed a correlation between AT cytotoxic T-lymphocyte antigen-4 (CTLA4) expression and RFS, which maintained statistical significance at multivariate analysis. CTLA4 expression correlated with forkhead box P3 (FOXP3) expression, suggesting enrichment in T regulatory cells. CTLA4 is known to act by binding to the cluster of differentiation 80 (CD80). No association was seen between AT CD80 expression and RFS. However, CD80 expression differentiated prognosis in patients who received adjuvant chemotherapy. We showed that the immunomodulatory transcriptome is deregulated in resected BTCs. Our study includes a small number of patients and does not enable to draw definitive conclusions; however, it provides useful insights into potential transcripts that may deserve further investigation in larger cohorts of patients. TRANSCRIPT PROFILING: Nanostring data have been submitted to GEO repository: GSE90698 and GSE906

Comparison of the HadGEM2 climate-chemistry model against in situ and SCIAMACHY atmospheric methane data

Wetlands are a major emission source of methane (CH4) globally. In this study, we evaluate wetland emission estimates derived using the UK community land surface model (JULES, the Joint UK Land Earth Simulator) against atmospheric observations of methane, including, for the first time, total methane columns derived from the SCIAMACHY instrument on board the ENVISAT satellite. Two JULES wetland emission estimates are investigated: (a) from an offline run driven with Climatic Research Unit–National Centers for Environmental Prediction (CRU-NCEP) meteorological data and (b) from the same offline run in which the modelled wetland fractions are replaced with those derived from the Global Inundation Extent from Multi-Satellites (GIEMS) remote sensing product. The mean annual emission assumed for each inventory (181 Tg CH4 per annum over the period 1999–2007) is in line with other recently published estimates. There are regional differences as the unconstrained JULES inventory gives significantly higher emissions in the Amazon (by ~36 Tg CH4 yr−1) and lower emissions in other regions (by up to 10 Tg CH4 yr−1) compared to the JULES estimates constrained with the GIEMS product. Using the UK Hadley Centre's Earth System model with atmospheric chemistry (HadGEM2), we evaluate these JULES wetland emissions against atmospheric observations of methane. We obtain improved agreement with the surface concentration measurements, especially at high northern latitudes, compared to previous HadGEM2 runs using the wetland emission data set of Fung et al. (1991). Although the modelled monthly atmospheric methane columns reproduce the large-scale patterns in the SCIAMACHY observations, they are biased low by 50 part per billion by volume (ppb). Replacing the HadGEM2 modelled concentrations above 300 hPa with HALOE–ACE assimilated TOMCAT output results in a significantly better agreement with the SCIAMACHY observations. The use of the GIEMS product to constrain the JULES-derived wetland fraction improves the representation of the wetland emissions in JULES and gives a good description of the seasonality observed at surface sites influenced by wetlands, especially at high latitudes. We find that the annual cycles observed in the SCIAMACHY measurements and at many of the surface sites influenced by non-wetland sources cannot be reproduced in these HadGEM2 runs. This suggests that the emissions over certain regions (e.g. India and China) are possibly too high and/or the monthly emission patterns for specific sectors are incorrect. The comparisons presented in this paper show that the performance of the JULES wetland scheme is comparable to that of other process-based land surface models. We identify areas for improvement in this and the atmospheric chemistry components of the HadGEM Earth System model. The Earth Observation data sets used here will be of continued value in future evaluations of JULES and the HadGEM family of models

Pattern scaling using ClimGen: monthly-resolution future climate scenarios including changes in the variability of precipitation

Development, testing and example applications of the pattern-scaling approach for generating future climate change projections are reported here, with a focus on a particular software application called “ClimGen”. A number of innovations have been implemented, including using exponential and logistic functions of global-mean temperature to represent changes in local precipitation and cloud cover, and interpolation from climate model grids to a finer grid while taking into account land-sea contrasts in the climate change patterns. Of particular significance is a new approach for incorporating changes in the inter-annual variability of monthly precipitation simulated by climate models. This is achieved by diagnosing simulated changes in the shape of the gamma distribution of monthly precipitation totals, applying the pattern-scaling approach to estimate changes in the shape parameter under a future scenario, and then perturbing sequences of observed precipitation anomalies so that their distribution changes according to the projected change in the shape parameter. The approach cannot represent changes to the structure of climate timeseries (e.g. changed autocorrelation or teleconnection patterns) were they to occur, but is shown here to be more successful at representing changes in low precipitation extremes than previous pattern-scaling methods

High chance that current atmospheric greenhouse concentrations commit to warmings greater than 1.5 °C over land

This is the final version of the article. Available from Springer Nature via the DOI in this record.The recent Paris UNFCCC climate meeting discussed the possibility of limiting global warming to 2 °C since pre-industrial times, or possibly even 1.5 °C, which would require major future emissions reductions. However, even if climate is stabilised at current atmospheric greenhouse gas (GHG) concentrations, those warming targets would almost certainly be surpassed in the context of mean temperature increases over land only. The reason for this is two-fold. First, current transient warming lags significantly below equilibrium or "committed" warming. Second, almost all climate models indicate warming rates over land are much higher than those for the oceans. We demonstrate this potential for high eventual temperatures over land, even for contemporary GHG levels, using a large set of climate models and for which climate sensitivities are known. Such additional land warming has implications for impacts on terrestrial ecosystems and human well-being. This suggests that even if massive and near-immediate emissions reductions occur such that atmospheric GHGs increase further by only small amounts, careful planning is needed by society to prepare for higher land temperatures in an eventual equilibrium climatic state.CH Acknowledges the NERC CEH National Capability fund

Towards quantifying uncertainty in predictions of Amazon 'dieback'.

This is the final version of the article. It first appeared from The Royal Society via http://dx.doi.org/10.1098/rstb.2007.0028Simulations with the Hadley Centre general circulation model (HadCM3), including carbon cycle model and forced by a 'business-as-usual' emissions scenario, predict a rapid loss of Amazonian rainforest from the middle of this century onwards. The robustness of this projection to both uncertainty in physical climate drivers and the formulation of the land surface scheme is investigated. We analyse how the modelled vegetation cover in Amazonia responds to (i) uncertainty in the parameters specified in the atmosphere component of HadCM3 and their associated influence on predicted surface climate. We then enhance the land surface description and (ii) implement a multilayer canopy light interception model and compare with the simple 'big-leaf' approach used in the original simulations. Finally, (iii) we investigate the effect of changing the method of simulating vegetation dynamics from an area-based model (TRIFFID) to a more complex size- and age-structured approximation of an individual-based model (ecosystem demography). We find that the loss of Amazonian rainforest is robust across the climate uncertainty explored by perturbed physics simulations covering a wide range of global climate sensitivity. The introduction of the refined light interception model leads to an increase in simulated gross plant carbon uptake for the present day, but, with altered respiration, the net effect is a decrease in net primary productivity. However, this does not significantly affect the carbon loss from vegetation and soil as a consequence of future simulated depletion in soil moisture; the Amazon forest is still lost. The introduction of the more sophisticated dynamic vegetation model reduces but does not halt the rate of forest dieback. The potential for human-induced climate change to trigger the loss of Amazon rainforest appears robust within the context of the uncertainties explored in this paper. Some further uncertainties should be explored, particularly with respect to the representation of rooting depth