ALBERT

Description: 〈div data-abstract-type="normal"〉〈p〉Heading date (HD) and flowering date (FD) are critical for yield potential and stability, so understanding their genetic foundation is of great significance in wheat breeding. Three related recombinant inbred line populations with a common female parent were developed to identify quantitative trait loci (QTL) for HD and FD in four environments. In total, 25 putative additive QTL and 20 pairwise epistatic effect QTL were detected in four environments. The additive QTL were distributed across 17 wheat chromosomes. Of these, 〈span〉QHd-1A〈/span〉, 〈span〉QHd-1D〈/span〉, 〈span〉QHd-2B〈/span〉, 〈span〉QHd-3B〈/span〉, 〈span〉QHd-4A〈/span〉, 〈span〉QHd-4B〈/span〉 and 〈span〉QHd-6D〈/span〉 were major and stable QTL for HD. 〈span〉QFd-1A〈/span〉, 〈span〉QFd-2B〈/span〉, 〈span〉QFd-4A〈/span〉 and 〈span〉QFd-4B〈/span〉 were major and stable QTL for FD. In addition, an epistatic interaction test showed that epistasis played important roles in controlling wheat HD and FD. Genetic relationships between HD/FD and five yield-related traits (YRTs) were characterized and ten QTL clusters (C1–C10) simultaneously controlling YRTs and HD/FD were identified. The present work laid a genetic foundation for improving yield potential in wheat molecular breeding programmes.〈/p〉〈/div〉

Description: Land models, which have been developed by the modeling community in the past two 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 and evaluate performance of models against a set of defined standards. This paper proposes a benchmarking framework for evaluation of land models. 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. Component 4 may or may not be involved in a benchmark analysis but is an ultimate goal of general modeling research. Land models are required to simulate exchange of water, energy, carbon and sometimes other trace gases between the atmosphere and the land-surface, and should be evaluated for their simulations of biophysical processes, biogeochemical cycles, and vegetation dynamics across timescales in response to both weather and climate change. Benchmarks that are used to evaluate models generally consist of direct observations, data-model products, and data-derived patterns and relationships. Metrics of measuring mismatches between models and benchmarks 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 for future improvement. Iterations between model evaluation and improvement via benchmarking shall demonstrate progress of land modeling and help establish confidence in land models for their predictions of future states of ecosystems and climate.

Description: Future climate change has the potential to increase drought in many regions of the globe, making it essential that land surface models (LSMs) used in coupled climate models, realistically capture the drought responses of vegetation. Recent data syntheses show that drought sensitivity varies considerably among plants from different climate zones, but state-of-the-art LSMs currently assume the same drought sensitivity for all vegetation. We tested whether variable drought sensitivities are needed to explain the observed large-scale patterns of drought impact. We implemented data-driven drought sensitivities in the Community Atmosphere Biosphere Land Exchange (CABLE) LSM and evaluated alternative sensitivities across a latitudinal gradient in Europe during the 2003 heatwave. The model predicted an overly abrupt onset of drought unless average soil water potential was calculated with dynamic weighting across soil layers. We found that high drought sensitivity at the northernmost sites, and low drought sensitivity at the southernmost sites, was necessary to accurately model responses during drought. Our results indicate that LSMs will over-estimate drought impacts in drier climates unless different sensitivity of vegetation to drought is taken into account.

Description: Surface fluxes from land surface models (LSM) have traditionally been evaluated against monthly, seasonal or annual mean states. The limited ability of LSMs to reproduce observed evaporative fluxes under water-stressed conditions has been previously noted, but very few studies have systematically evaluated these models during rainfall deficits. We evaluated latent heat flux simulated by the Community Atmosphere Biosphere Land Exchange (CABLE) LSM across 20 flux tower sites at sub-annual to inter-annual time scales, in particular focusing on model performance during seasonal-scale rainfall deficits. The importance of key model processes in capturing the latent heat flux are explored by employing alternative representations of hydrology, leaf area index, soil properties and stomatal conductance. We found that the representation of hydrological processes was critical for capturing observed declines in latent heat during rainfall deficits. By contrast, the effects of soil properties, LAI and stomatal conductance are shown to be highly site-specific. Whilst the standard model performs reasonably well at annual scales as measured by common metrics, it grossly underestimates latent heat during rainfall deficits. A new version of CABLE, with a more physically consistent representation of hydrology, captures the variation in the latent heat flux during seasonal-scale rainfall deficits better than earlier versions but remaining biases point to future research needs. Our results highlight the importance of evaluating LSMs under water-stressed conditions and across multiple plant functional types and climate regimes.

Description: Heading date (HD) and flowering date (FD) are critical for yield potential and stability, so understanding their genetic foundation is of great significance in wheat breeding. Three related recombinant inbred line populations with a common female parent were developed to identify quantitative trait loci (QTL) for HD and FD in four environments. In total, 25 putative additive QTL and 20 pairwise epistatic effect QTL were detected in four environments. The additive QTL were distributed across 17 wheat chromosomes. Of these, QHd-1A, QHd-1D, QHd-2B, QHd-3B, QHd-4A, QHd-4B and QHd-6D were major and stable QTL for HD. QFd-1A, QFd-2B, QFd-4A and QFd-4B were major and stable QTL for FD. In addition, an epistatic interaction test showed that epistasis played important roles in controlling wheat HD and FD. Genetic relationships between HD/FD and five yield-related traits (YRTs) were characterized and ten QTL clusters (C1–C10) simultaneously controlling YRTs and HD/FD were identified. The present work laid a genetic foundation for improving yield potential in wheat molecular breeding programmes.

Description: We examine the impact of land use and land cover change (LULCC) over the period from 1850 to 2005 using an Earth System Model that incorporates nitrogen and phosphorous limitation on the terrestrial carbon cycle. We compare the estimated CO2 emissions and warming from land use change in a carbon only version of the model with those from simulations including nitrogen and phosphorous limitation. If we omit nutrients, our results suggest LULCC cools on the global average by about 0.1 °C. Including nutrients reduces this cooling to ~ 0.05 °C. Our results also suggest LULCC has a major impact on total land carbon over the period 1850–2005. In carbon only simulations, the inclusion of LULCC decreases the total additional land carbon stored in 2005 from around 210 Pg C to 85 Pg C. Including nitrogen and phosphorous limitation also decreases the scale of the terrestrial carbon sink to 80 Pg C. In particular, adding LULCC on top of the nutrient limited simulations changes the sign of the terrestrial carbon flux from a sink to a source (12 Pg C). The CO2 emission from LULCC from 1850 to 2005 is estimated to be 130 Pg C for carbon only simulation, or 97 Pg C if nutrient limitation is accounted for in our model. The difference between these two estimates of CO2 emissions from LULCC largely results from the weaker response of photosynthesis to increased CO2 and smaller carbon pool sizes, and therefore lower carbon loss from plant and wood product carbon pools under nutrient limitation. We suggest that nutrient limitation should be accounted in simulating the effects of LULCC on the past climate and on the past and future carbon budget.

Description: Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe datasets and a methodology to quantify all major components of the global carbon budget, including their uncertainties, based on the combination of a range of data, algorithms, statistics and model estimates and their interpretation by a broad scientific community. We discuss changes compared to previous estimates, consistency within and among components, alongside methodology and data limitations. CO2 emissions from fossil fuel combustion and cement production (EFF) are based on energy statistics and cement production data, respectively, while emissions from Land-Use Change (ELUC), mainly deforestation, are based on combined evidence from land-cover change data, fire activity associated with deforestation, and models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the annual changes in concentration. The mean ocean CO2 sink (SOCEAN) is based on observations from the 1990s, while the annual anomalies and trends are estimated with ocean models. The variability in SOCEAN is evaluated with data products based on surveys of ocean CO2 measurements. The global residual terrestrial CO2 sink (SLAND) is estimated by the difference of the other terms of the global carbon budget and compared to results of independent Dynamic Global Vegetation Models forced by observed climate, CO2 and land cover change (some including nitrogen-carbon interactions). We compare the variability and mean land and ocean fluxes to estimates from three atmospheric inverse methods for three broad latitude bands. All uncertainties are reported as ±1σ, reflecting the current capacity to characterise the annual estimates of each component of the global carbon budget. For the last decade available (2004–2013), EFF was 8.9 ± 0.4 GtC yr−1, ELUC 0.9 ± 0.5 GtC yr−1, GATM 4.3 ± 0.1 GtC yr−1, SOCEAN 2.6 ± 0.5 GtC yr−1, and SLAND 2.9 ± 0.8 GtC yr−1. For year 2013 alone, EFF grew to 9.9 ± 0.5 GtC yr−1, 2.3% above 2012, contining the growth trend in these emissions. ELUC was 0.9 ± 0.5 GtC yr−1, GATM was 5.4 ± 0.2 GtC yr−1, SOCEAN was 2.9 ± 0.5 GtC yr−1 and SLAND was 2.5 ± 0.9 GtC yr−1. GATM was high in 2013 reflecting a steady increase in EFF and smaller and opposite changes between SOCEAN and SLAND compared to the past decade (2004–2013). The global atmospheric CO2 concentration reached 395.31 ± 0.10 ppm averaged over 2013. We estimate that EFF will increase by 2.5% (1.3–3.5%) to 10.1 ± 0.6 GtC in 2014 (37.0 ± 2.2 GtCO2 yr−1), 65% above emissions in 1990, based on projections of World Gross Domestic Product and recent changes in the carbon intensity of the economy. From this projection of EFF and assumed constant ELUC for 2014, cumulative emissions of CO2 will reach about 545 ± 55 GtC (2000 ± 200 GtCO2) for 1870–2014, about 75% from EFF and 25% from ELUC. This paper documents changes in the methods and datasets used in this new carbon budget compared with previous publications of this living dataset (Le Quéré et al., 2013, 2014). All observations presented here can be downloaded from the Carbon Dioxide Information Analysis Center (doi:10.3334/CDIAC/GCP_2014). Italic font highlights significant methodological changes and results compared to the Le Quéré et al. (2014) manuscript that accompanies the previous version of this living data.

Description: Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and a methodology to quantify all major components of the global carbon budget, including their uncertainties, based on the combination of a range of data, algorithms, statistics, and model estimates and their interpretation by a broad scientific community. We discuss changes compared to previous estimates, consistency within and among components, alongside methodology and data limitations. CO2 emissions from fossil fuel combustion and cement production (EFF) are based on energy statistics and cement production data, respectively, while emissions from land-use change (ELUC), mainly deforestation, are based on combined evidence from land-cover-change data, fire activity associated with deforestation, and models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the annual changes in concentration. The mean ocean CO2 sink (SOCEAN) is based on observations from the 1990s, while the annual anomalies and trends are estimated with ocean models. The variability in SOCEAN is evaluated with data products based on surveys of ocean CO2 measurements. The global residual terrestrial CO2 sink (SLAND) is estimated by the difference of the other terms of the global carbon budget and compared to results of independent dynamic global vegetation models forced by observed climate, CO2, and land-cover-change (some including nitrogen–carbon interactions). We compare the mean land and ocean fluxes and their variability to estimates from three atmospheric inverse methods for three broad latitude bands. All uncertainties are reported as ±1σ, reflecting the current capacity to characterise the annual estimates of each component of the global carbon budget. For the last decade available (2004–2013), EFF was 8.9 ± 0.4 GtC yr−1, ELUC 0.9 ± 0.5 GtC yr−1, GATM 4.3 ± 0.1 GtC yr−1, SOCEAN 2.6 ± 0.5 GtC yr−1, and SLAND 2.9 ± 0.8 GtC yr−1. For year 2013 alone, EFF grew to 9.9 ± 0.5 GtC yr−1, 2.3% above 2012, continuing the growth trend in these emissions, ELUC was 0.9 ± 0.5 GtC yr−1, GATM was 5.4 ± 0.2 GtC yr−1, SOCEAN was 2.9 ± 0.5 GtC yr−1, and SLAND was 2.5 ± 0.9 GtC yr−1. GATM was high in 2013, reflecting a steady increase in EFF and smaller and opposite changes between SOCEAN and SLAND compared to the past decade (2004–2013). The global atmospheric CO2 concentration reached 395.31 ± 0.10 ppm averaged over 2013. We estimate that EFF will increase by 2.5% (1.3–3.5%) to 10.1 ± 0.6 GtC in 2014 (37.0 ± 2.2 GtCO2 yr−1), 65% above emissions in 1990, based on projections of world gross domestic product and recent changes in the carbon intensity of the global economy. From this projection of EFF and assumed constant ELUC for 2014, cumulative emissions of CO2 will reach about 545 ± 55 GtC (2000 ± 200 GtCO2) for 1870–2014, about 75% from EFF and 25% from ELUC. This paper documents changes in the methods and data sets used in this new carbon budget compared with previous publications of this living data set (Le Quéré et al., 2013, 2014). All observations presented here can be downloaded from the Carbon Dioxide Information Analysis Center (doi:10.3334/CDIAC/GCP_2014).

Description: We examine the impact of land use and land cover change (LULCC) over the period from 1850 to 2005 using an Earth system model that incorporates nitrogen and phosphorous limitation on the terrestrial carbon cycle. We compare the estimated CO2 emissions and warming from land use change in a carbon-only version of the model with those from simulations, including nitrogen and phosphorous limitation. If we omit nutrients, our results suggest LULCC cools on the global average by about 0.1 °C. Including nutrients reduces this cooling to ~ 0.05 °C. Our results also suggest LULCC has a major impact on total land carbon over the period 1850–2005. In carbon-only simulations, the inclusion of LULCC decreases the total additional land carbon stored in 2005 from around 210 Pg C to 85 Pg C. Including nitrogen and phosphorous limitation also decreases the scale of the terrestrial carbon sink to 80 Pg C. Shown as corresponding fluxes, adding LULCC on top of the nutrient-limited simulations changes the sign of the terrestrial carbon flux from a sink to a source (12 Pg C). The CO2 emission from LULCC from 1850 to 2005 is estimated to be 130 Pg C for carbon only simulation, or 97 Pg C if nutrient limitation is accounted for in our model. The difference between these two estimates of CO2 emissions from LULCC largely results from the weaker response of photosynthesis to increased CO2 and smaller carbon pool sizes, and therefore lower carbon loss from plant and wood product carbon pools under nutrient limitation. We suggest that nutrient limitation should be accounted for in simulating the effects of LULCC on the past climate and on the past and future carbon budget.

Description: The CSIRO Mk3L climate system model, a reduced-resolution coupled general circulation model, has previously been described in this journal. The model is configured for millennium scale or multiple century scale simulations. This paper reports the impact of replacing the relatively simple land surface scheme that is the default parameterisation in Mk3L with a sophisticated land surface model that simulates the terrestrial energy, water and carbon balance in a physically and biologically consistent way. An evaluation of the new model's near-surface climatology highlights strengths and weaknesses, but overall the atmospheric variables, including the near-surface air temperature and precipitation, are simulated well. The impact of the more sophisticated land surface model on existing variables is relatively small, but generally positive. More significantly, the new land surface scheme allows an examination of surface carbon-related quantities including net primary productivity which adds significantly to the capacity of Mk3L. Overall, results demonstrate that this reduced-resolution climate model is a good foundation for exploring long time scale phenomena. The addition of the more sophisticated land surface model enables an exploration of important Earth System questions including land cover change and abrupt changes in terrestrial carbon storage.