To limit global warming to <2 °C we must reduce the net amount of CO2 we release into the atmosphere, either by producing less CO2 (conventional mitigation) or by capturing more CO2 (negative ...emissions). Here, using state-of-the-art carbon-climate models, we quantify the trade-off between these two options in RCP2.6: an Intergovernmental Panel on Climate Change scenario likely to limit global warming below 2 °C. In our best-case illustrative assumption of conventional mitigation, negative emissions of 0.5-3 Gt C (gigatonnes of carbon) per year and storage capacity of 50-250 Gt C are required. In our worst case, those requirements are 7-11 Gt C per year and 1,000-1,600 Gt C, respectively. Because these figures have not been shown to be feasible, we conclude that development of negative emission technologies should be accelerated, but also that conventional mitigation must remain a substantial part of any climate policy aiming at the 2-°C target.
The authors assess the ability of 18 Earth system models to simulate the land and ocean carbon cycle for the present climate. These models will be used in the next Intergovernmental Panel on Climate ...Change (IPCC) Fifth Assessment Report (AR5) for climate projections, and such evaluation allows identification of the strengths and weaknesses of individual coupled carbon–climate models as well as identification of systematic biases of the models. Results show that models correctly reproduce the main climatic variables controlling the spatial and temporal characteristics of the carbon cycle. The seasonal evolution of the variables under examination is well captured. However, weaknesses appear when reproducing specific fields: in particular, considering the land carbon cycle, a general overestimation of photosynthesis and leaf area index is found for most of the models, while the ocean evaluation shows that quite a few models underestimate the primary production. The authors also propose climate and carbon cycle performance metrics in order to assess whether there is a set of consistently better models for reproducing the carbon cycle. Averaged seasonal cycles and probability density functions (PDFs) calculated from model simulations are compared with the corresponding seasonal cycles and PDFs from different observed datasets. Although the metrics used in this study allow identification of somemodels as better or worse than the average, the ranking of this study is partially subjective because of the choice of the variables under examination and also can be sensitive to the choice of reference data. In addition, it was found that the model performances show significant regional variations.
Soil phosphatase levels strongly control the biotic pathways of phosphorus (P), an essential element for life, which is often limiting in terrestrial ecosystems. We investigated the influence of ...climatic and soil traits on phosphatase activity in terrestrial systems using metadata analysis from published studies. This is the first analysis of global measurements of phosphatase in natural soils. Our results suggest that organic P (P
), rather than available P, is the most important P fraction in predicting phosphatase activity. Structural equation modeling using soil total nitrogen (TN), mean annual precipitation, mean annual temperature, thermal amplitude and total soil carbon as most available predictor variables explained up to 50% of the spatial variance in phosphatase activity. In this analysis, P
could not be tested and among the rest of available variables, TN was the most important factor explaining the observed spatial gradients in phosphatase activity. On the other hand, phosphatase activity was also found to be associated with climatic conditions and soil type across different biomes worldwide. The close association among different predictors like P
, TN and precipitation suggest that P recycling is driven by a broad scale pattern of ecosystem productivity capacity.
Earth system models predict that increases in atmospheric and soil dryness will reduce photosynthesis in the Amazon rainforest, with large implications for the global carbon cycle. Using in situ ...observations, solar-induced fluorescence, and nonlinear machine learning techniques, we show that, in reality, this is not necessarily the case: In many of the wettest parts of this region, photosynthesis and biomass tend to increase with increased atmospheric dryness, despite the associated reductions in canopy conductance to CO
These results can be largely explained by changes in canopy properties, specifically, new leaves flushed during the dry season have higher photosynthetic capacity than the leaves they replace, compensating for the negative stomatal response to increased dryness. As atmospheric dryness will increase with climate change, our study highlights the importance of reframing how we represent the response of ecosystem photosynthesis to atmospheric dryness in very wet regions, to accurately quantify the land carbon sink.
The present study aims at evaluating and comparing precipitation over the Amazon in two sets of historical and future climate simulations based on phase 3 (CMIP3) and 5 (CMIP5) of the Coupled Model ...Intercomparison Project. Thirteen models have been selected in order to discuss (1) potential improvements in the simulation of present-day climate and (2) the potential reduction in the uncertainties of the model response to increasing concentrations of greenhouse gases. While several features of present-day precipitation—including annual cycle, spatial distribution and co variability with tropical sea surface temperature (SST)—have been improved, strong uncertainties remain in the climate projections. A closer comparison between CMIP5 and CMIP3 highlights a weaker consensus on increased precipitation during the wet season, but a stronger consensus on a drying and lengthening of the dry season. The latter response is related to a northward shift of the boreal summer intertropical convergence zone in CMIP5, in line with a more asymmetric warming between the northern and southern hemispheres. The large uncertainties that persist in the rainfall response arise from contrasted anomalies in both moisture convergence and evapotranspiration. They might be related to the diverse response of tropical SST and ENSO (El Niño Southern Oscillation) variability, as well as to spurious behaviours among the models that show the most extreme response. Model improvements of present-day climate do not necessarily translate into more reliable projections and further efforts are needed for constraining the pattern of the SST response and the soil moisture feedback in global climate scenarios.
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