Several lines of evidence point to European managed grassland ecosystems being a sink of carbon. In this study, we apply ORCHIDEE‐GM a process‐based carbon cycle model that describes specific ...management practices of pastures and the dynamics of carbon cycling in response to changes in climatic and biogeochemical drivers. The model is used to simulate changes in the carbon balance i.e., net biome production (NBP) of European grasslands over 1991–2010 on a 25 km × 25 km grid. The modeled average trend in NBP is 1.8–2.0 g C m−2 yr−2 during the past two decades. Attribution of this trend suggests management intensity as the dominant driver explaining NBP trends in the model (36–43% of the trend due to all drivers). A major change in grassland management intensity has occurred across Europe resulting from reduced livestock numbers. This change has ‘inadvertently’ enhanced soil C sequestration and reduced N2O and CH4 emissions by 1.2–1.5 Gt CO2‐equivalent, offsetting more than 7% of greenhouse gas emissions in the whole European agricultural sector during the period 1991–2010. Land‐cover change, climate change and rising CO2 also make positive and moderate contributions to the NBP trend (between 24% and 31% of the trend due to all drivers). Changes in nitrogen addition (including fertilization and atmospheric deposition) are found to have only marginal net effect on NBP trends. However, this may not reflect reality because our model has only a very simple parameterization of nitrogen effects on photosynthesis. The sum of NBP trends from each driver is larger than the trend obtained when all drivers are varied together, leaving a residual – nonattributed – term (22–26% of the trend due to all drivers) indicating negative interactions between drivers.
Understanding the role of climate extremes and their impact on the carbon (C) cycle is increasingly a focus of Earth system science. Climate extremes such as droughts, heat waves, or heavy ...precipitation events can cause substantial changes in terrestrial C fluxes. On the other hand, extreme changes in C fluxes are often, but not always, driven by extreme climate conditions. Here we present an analysis of how extremes in temperature and precipitation, and extreme changes in terrestrial C fluxes are related to each other in 10 state‐of‐the‐art terrestrial carbon models, all driven by the same climate forcing. We use model outputs from the North American Carbon Program Multi‐scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP). A global‐scale analysis shows that both droughts and heat waves translate into anomalous net releases of CO2 from the land surface via different mechanisms: Droughts largely decrease gross primary production (GPP) and to a lower extent total respiration (TR), while heat waves slightly decrease GPP but increase TR. Cold and wet periods have a smaller opposite effect. Analyzing extremes in C fluxes reveals that extreme changes in GPP and TR are often caused by strong shifts in water availability, but for extremes in TR shifts in temperature are also important. Extremes in net CO2 exchange are equally strongly driven by deviations in temperature and precipitation. Models mostly agree on the sign of the C flux response to climate extremes, but model spread is large. In tropical forests, C cycle extremes are driven by water availability, whereas in boreal forests temperature plays a more important role. Models are particularly uncertain about the C flux response to extreme heat in boreal forests.
Key Points
Models largely agree on the sign of the carbon flux response to climate extremes
Models are uncertain in the carbon flux response to heat waves in boreal forests
Droughts and heat waves strongly compound each other in their impact on C fluxes
•A process-based model (ORCHIDEE-crop) is calibrated efficiently with particle filter.•LGP of different rice types show varied response to change in climate and management.•Change in managements have ...larger impacts than climate change for early & single rice.•Regional modelling should consider multiple rice types & changing management practices.•Improved records on management & observation error are vital for reducing uncertainty.
Whether crop phenology changes are caused by change in managements or by climate change belongs to the category of problems known as detection-attribution. Three type of rice (early, late and single rice) in China show an average increase in Length of Growing Period (LGP) during 1991–2012: 1.0±4.8day/decade (±standard deviation across sites) for early rice, 0.2±4.5day/decade for late rice and 2.0±6.0day/decade for single rice, based on observations from 141 long-term monitoring stations. Positive LGP trends are widespread, but only significant (P<0.05) at 25% of early rice, 22% of late rice and 38% of single rice sites. We developed a Bayes-based optimization algorithm, and optimized five parameters controlling phenological development in a process-based crop model (ORCHIDEE-crop) for discriminating effects of managements from those of climate change on rice LGP. The results from the optimized ORCHIDEE-crop model suggest that climate change has an effect on LGP trends dependent on rice types. Climate trends have shortened LGP of early rice (−2.0±5.0day/decade), lengthened LGP of late rice (1.1±5.4day/decade) and have little impacts on LGP of single rice (−0.4±5.4day/decade). ORCHIDEE-crop simulations further show that change in transplanting date caused widespread LGP change only for early rice sites, offsetting 65% of climate change induced LGP shortening. The primary drivers of LGP change are thus different among the three types of rice. Management are predominant driver of LGP change for early and single rice. This study shows that complex regional variations of LGP can be reproduced with an optimized crop model. We further suggest that better documenting observational error and management practices can help reduce large uncertainties existed in attribution of LGP change, and future rice crop modelling in global/regional scales should consider different types of rice and variable transplanting dates in order to better account impacts of management and climate change.
Litter production is a fundamental ecosystem process, which plays an important role in regulating terrestrial carbon and nitrogen cycles. However, there are substantial differences in the litter ...production simulations among ecosystem models, and a global benchmarking evaluation to measure the performance of these models is still lacking. In this study, we generated a global dataset of aboveground litterfall production (i.e. cLitter), a benchmark as the defined reference to test model performance, by combining systematic measurements taken from a substantial number of surveys (1079 sites) with a machine learning technique (i.e. random forest, RF). Our study demonstrated that the RF model is an effective tool for upscaling local litterfall production observations to the global scale. On average, the model predicted 23.15 Pg C yr−1 of aboveground litterfall production. Our results revealed substantial differences in the aboveground litterfall production simulations among the five investigated ecosystem models. Compared to the reference data at the global scale, most of models could reproduce the spatial patterns of aboveground litterfall production, but the magnitude of simulations differed substantially from the reference data. Overall, ORCHIDEE-MICT performed the best among the five investigated ecosystem models.
Increasing atmospheric methane (CH4) concentrations have contributed to approximately 20% of anthropogenic climate change. Despite the importance of CH4 as a greenhouse gas, its atmospheric growth ...rate and dynamics over the past two decades, which include a stabilization period (1999-2006), followed by renewed growth starting in 2007, remain poorly understood. We provide an updated estimate of CH4 emissions from wetlands, the largest natural global CH4 source, for 2000-2012 using an ensemble of biogeochemical models constrained with remote sensing surface inundation and inventory-based wetland area data. Between 2000-2012, boreal wetland CH4 emissions increased by 1.2 Tg yr−1 (−0.2-3.5 Tg yr−1), tropical emissions decreased by 0.9 Tg yr−1 (−3.2−1.1 Tg yr−1), yet globally, emissions remained unchanged at 184 ± 22 Tg yr−1. Changing air temperature was responsible for increasing high-latitude emissions whereas declines in low-latitude wetland area decreased tropical emissions; both dynamics are consistent with features of predicted centennial-scale climate change impacts on wetland CH4 emissions. Despite uncertainties in wetland area mapping, our study shows that global wetland CH4 emissions have not contributed significantly to the period of renewed atmospheric CH4 growth, and is consistent with findings from studies that indicate some combination of increasing fossil fuel and agriculture-related CH4 emissions, and a decrease in the atmospheric oxidative sink.
Surface ozone (O3) is a threat to forests by decreasing photosynthesis and, consequently, influencing the strength of land carbon sink. However, due to the lack of continuous surface O3 measurements, ...observational-based assessments of O3 impacts on forests are largely missing at hemispheric to global scales.
Currently, some metrics are used for regulatory purposes by governments or national agencies to protect forests against the negative impacts of ozone: in particular, both Europe and United States (US) makes use of two different exposure-based metrics, i.e. AOT40 and W126, respectively. However, because of some limitations in these metrics, a new standard is under consideration by the European Union (EU) to replace the current exposure metric.
We analyse here the different air quality standards set or proposed for use in Europe and in the US to protect forests from O3 and to evaluate their spatial and temporal consistency while assessing their effectiveness in protecting northern-hemisphere forests. Then, we compare their results with the information obtained from a complex land surface model (ORCHIDEE).
We find that present O3 uptake decreases gross primary production (GPP) in 37.7% of the NH forested area of northern hemisphere with a mean loss of 2.4% year−1. We show how the proposed US (W126) and the currently used European (AOT40) air quality standards substantially overestimate the extension of potential vulnerable regions, predicting that 46% and 61% of the Northern Hemisphere (NH) forested area are at risk of O3 pollution. Conversely, the new proposed European standard (POD1) identifies lower extension of vulnerability regions (39.6%).
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•Ozone exposure and uptake have different spatial distribution over northern hemisphere.•Exceedance for ozone exposure in NH is 46% for AOT40 and 61% for W126.•Exceedance for ozone uptake over NH are 39.6% for POD1.•GPP decrease due to ozone concentrations in NH forests is estimated in 2.4% a year.
This work presents a new dynamic global vegetation model designed as an extension of an existing surface‐vegetation‐atmosphere transfer scheme which is included in a coupled ocean‐atmosphere general ...circulation model. The new dynamic global vegetation model simulates the principal processes of the continental biosphere influencing the global carbon cycle (photosynthesis, autotrophic and heterotrophic respiration of plants and in soils, fire, etc.) as well as latent, sensible, and kinetic energy exchanges at the surface of soils and plants. As a dynamic vegetation model, it explicitly represents competitive processes such as light competition, sapling establishment, etc. It can thus be used in simulations for the study of feedbacks between transient climate and vegetation cover changes, but it can also be used with a prescribed vegetation distribution. The whole seasonal phenological cycle is prognostically calculated without any prescribed dates or use of satellite data. The model is coupled to the IPSL‐CM4 coupled atmosphere‐ocean‐vegetation model. Carbon and surface energy fluxes from the coupled hydrology‐vegetation model compare well with observations at FluxNet sites. Simulated vegetation distribution and leaf density in a global simulation are evaluated against observations, and carbon stocks and fluxes are compared to available estimates, with satisfying results.
We evaluated how climate change, rising atmospheric CO2 concentration, and land use change influenced the terrestrial carbon (C) cycle for the last century using a process‐based ecosystem model. Over ...the last century, the modeled land use change emitted about 129 Pg of C to the atmosphere. About 76% (or 98 Pg C) of this emission, however, was offset by net C uptake on land driven by climate changes and rising atmospheric CO2 concentration. Thus, the modeled net release of C from the terrestrial ecosystems to the atmosphere from 1901 to 2002 is about 31 Pg C. Global net primary productivity (NPP) has significantly increased by 14% during the last century, especially since the 1970s. From 1980 to 2002, global NPP increased with an average increase rate of 0.4% yr−1. At global scale, such an increase seems to be primarily attributed to the increase in atmospheric CO2 concentration, and then to precipitation change. Over the last 2 decades, climate change and rising CO2 forced the land carbon sink (1.6 Pg C yr−1 for 1980s and 2.2 Pg C yr−1 for 1990s) to be larger than land use change driven carbon emissions (1.0 Pg C yr−1 for 1980s and 1.2 Pg C yr−1 for 1990s), resulting a net land sink of 0.5 Pg C yr−1 in the 1980s and of 1.0 Pg C yr−1 in the 1990s. The largest C emission from land use change appeared in tropical regions with an average emission of 0.6 Pg C yr−1 in 1980s and 0.7 Pg C yr−1 in 1990s, which is slightly larger than net carbon uptake due to CO2 fertilization and climate change. Thus, net carbon balance of tropical lands is close to neutral over the past 2 decades (about 0.13 Pg C yr−1 in 1980s and 0.03 Pg C yr−1 in 1990s). We also found that current global warming has already started accelerating C loss from terrestrial ecosystems, by enhanced decomposition of soil organic carbon. In response to warming trends only, the global net carbon uptake significantly decreased, offsetting about 70% of the increase in global net carbon uptake owing to CO2 fertilization during 1980–2002. The global terrestrial C cycle also shows large year‐to‐year variations, and different regions have quite distinct dominant drivers. Generally, interannual changes of carbon fluxes in tropical and temperate ecosystems are mainly explained by precipitation variability, while temperature variability plays a major role in boreal ecosystems.
Quantitative reconstruction of past plant abundance from fossil pollen data is still a challenging task for palynologists. During the last decades, mechanistic methods have been developed to convert ...pollen assemblages from peat and lake deposits into vegetation abundance at regional and local scale. Coastal areas are particularly sensitive to climate and environmental hazards. Thus, quantitative estimates of past vegetation are important to better understand their history and address potential effects of future environmental changes. However, assumptions of the mechanistic models of pollen dispersal and deposition originally designed for near-circular lakes and bogs located inland are violated when applied to coastal sites because of different basin shape and wind direction distribution. This study investigates how to adapt a model of pollen dispersal and deposition developed for lakes to coastal lagoons. A new geometry is defined, and it is demonstrated how some of the major formulas from previous models can be used without any modification in this singular context.
In this study, we assessed the performance of discharge simulations by coupling the runoff from seven Dynamic Global Vegetation Models (DGVMs; LPJ, ORCHIDEE, Sheffield‐DGVM, TRIFFID, LPJ‐GUESS, ...CLM4CN, and OCN) to one river routing model for 16 large river basins. The results show that the seasonal cycle of river discharge is generally modeled well in the low and middle latitudes but not in the high latitudes, where the peak discharge (due to snow and ice melting) is underestimated. For the annual mean discharge, the DGVMs chained with the routing model show an underestimation. Furthermore, the 30 year trend of discharge is also underestimated. For the interannual variability of discharge, a skill score based on overlapping of probability density functions (PDFs) suggests that most models correctly reproduce the observed variability (correlation coefficient higher than 0.5; i.e., models account for 50% of observed interannual variability) except for the Lena, Yenisei, Yukon, and the Congo river basins. In addition, we compared the simulated runoff from different simulations where models were forced with either fixed or varying land use. This suggests that both seasonal and annual mean runoff has been little affected by land use change but that the trend itself of runoff is sensitive to land use change. None of the models when considered individually show significantly better performances than any other and in all basins. This suggests that based on current modeling capability, a regional‐weighted average of multimodel ensemble projections might be appropriate to reduce the bias in future projection of global river discharge.
Key Points
The seasonal cycle of river discharge is well reproduced in low and middle latitudes
DGVMs generally underestimate annual mean discharge
Most DGVMs correctly reproduce observed interannual variability of discharge
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