Great advances have been made in the last decade in quantifying and understanding the spatiotemporal patterns of terrestrial gross primary production (GPP) with ground, atmospheric, and space ...observations. However, although global GPP estimates exist, each data set relies upon assumptions and none of the available data are based only on measurements. Consequently, there is no consensus on the global total GPP and large uncertainties exist in its benchmarking. The objective of this review is to assess how the different available data sets predict the spatiotemporal patterns of GPP, identify the differences among data sets, and highlight the main advantages/disadvantages of each data set. We compare GPP estimates for the historical period (1990–2009) from two observation‐based data sets (Model Tree Ensemble and Moderate Resolution Imaging Spectroradiometer) to coupled carbon‐climate models and terrestrial carbon cycle models from the Fifth Climate Model Intercomparison Project and TRENDY projects and to a new hybrid data set (CARBONES). Results show a large range in the mean global GPP estimates. The different data sets broadly agree on GPP seasonal cycle in terms of phasing, while there is still discrepancy on the amplitude. For interannual variability (IAV) and trends, there is a clear separation between the observation‐based data that show little IAV and trend, while the process‐based models have large GPP variability and significant trends. These results suggest that there is an urgent need to improve observation‐based data sets and develop carbon cycle modeling with processes that are currently treated either very simplistically to correctly estimate present GPP and better quantify the future uptake of carbon dioxide by the world's vegetation.
Key Points
At global scale, direct measurements of GPP do not exist
Large uncertainties exist on terrestrial global GPP benchmarking
Models show large variability in mean global GPP estimates
Satellite observations show that leaf area index (LAI) has increased globally since 1981, but the impact of this vegetation structural change on the global terrestrial carbon cycle has not been ...systematically evaluated. Through process-based diagnostic ecosystem modeling, we find that the increase in LAI alone was responsible for 12.4% of the accumulated terrestrial carbon sink (95 ± 5 Pg C) from 1981 to 2016, whereas other drivers of CO
fertilization, nitrogen deposition, and climate change (temperature, radiation, and precipitation) contributed to 47.0%, 1.1%, and -28.6% of the sink, respectively. The legacy effects of past changes in these drivers prior to 1981 are responsible for the remaining 65.5% of the accumulated sink from 1981 to 2016. These results refine the attribution of the land sink to the various drivers and would help constrain prognostic models that often have large uncertainties in simulating changes in vegetation and their impacts on the global carbon cycle.
Grasslands absorb and release carbon dioxide (CO
), emit methane (CH
) from grazing livestock, and emit nitrous oxide (N
O) from soils. Little is known about how the fluxes of these three greenhouse ...gases, from managed and natural grasslands worldwide, have contributed to past climate change, or the roles of managed pastures versus natural grasslands. Here, global trends and regional patterns of the full greenhouse gas balance of grasslands are estimated for the period 1750 to 2012. A new spatially explicit land surface model is applied, to separate the direct effects of human activities from land management and the indirect effects from climate change, increasing CO
and regional changes in nitrogen deposition. Direct human management activities are simulated to have caused grasslands to switch from a sink to a source of greenhouse gas, because of increased livestock numbers and accelerated conversion of natural lands to pasture. However, climate change drivers contributed a net carbon sink in soil organic matter, mainly from the increased productivity of grasslands due to increased CO
and nitrogen deposition. The net radiative forcing of all grasslands is currently close to neutral, but has been increasing since the 1960s. Here, we show that the net global climate warming caused by managed grassland cancels the net climate cooling from carbon sinks in sparsely grazed and natural grasslands. In the face of future climate change and increased demand for livestock products, these findings highlight the need to use sustainable management to preserve and enhance soil carbon storage in grasslands and to reduce greenhouse gas emissions from managed grasslands.
Large interannual variations in the measured growth rate of atmospheric carbon dioxide (CO2) originate primarily from fluctuations in carbon uptake by land ecosystems13. It remains uncertain, ...however, to what extent temperature and water availability control the carbon balance of land ecosystems across spatial and temporal scales314. Here we use empirical models based on eddy covariance data15 and process-based models16,17 to investigate the effect of changes in temperature and water availability on gross primary productivity (GPP), terrestrial ecosystem respiration (TER) and net ecosystem exchange (NEE) at local and global scales. We find that water availability is the dominant driver of the local interannual variability in GPP and TER. To a lesser extent this is true also for NEE at the local scale, but when integrated globally, temporal NEE variability is mostly driven by temperature fluctuations. We suggest that this apparent paradox can be explained by two compensatory water effects. Temporal water-driven GPP and TER variations compensate locally, dampening water-driven NEE variability. Spatial water availability anomalies also compensate, leaving a dominant temperature signal in the year-to-year fluctuations of the land carbon sink. These findings help to reconcile seemingly contradictory reports regarding the importance of temperature and water in controlling the interannual variability of the terrestrial carbon balance36,9,11,12,14. Our study indicates that spatial climate covariation drives the global carbon cycle response.
A number of studies have suggested that the growing season duration has significantly lengthened during the past decades, but the connections between phenology variability and the terrestrial carbon ...(C) cycle are far from clear. In this study, we used the “ORganizing Carbon and Hydrology In Dynamic Ecosystems” (ORCHIDEE) process based ecosystem model together with observed climate data to investigate spatiotemporal changes in phenology and their impacts on carbon fluxes in the Northern Hemisphere (>25°N) during 1980–2002. We found that the growing season length (GSL) has increased by 0.30 days yr−1 (R2 = 0.27, P = 0.010), owing to the combination of an earlier onset in spring (0.16 days yr−1) and a later termination in autumn (0.14 days yr−1). Trends in the GSL are however highly variable across the regions. In Eurasia, there is a significant trend toward earlier vegetation green‐up with an overall advancement rate of 0.28 days yr−1 (R2 = 0.32, P = 0.005), while in North America there is a significantly delayed vegetation senescence by 0.28 days yr−1 (R2 = 0.26, P = 0.013) during the study period. Our results also suggested that the GSL strongly correlates with annual gross primary productivity (GPP) and net primary productivity (NPP), indicating that longer growing seasons may eventually enhance vegetation growth. A 1‐day extension in GSL leads to an increase in annual GPP of 5.8 gC m−2 yr−1 (or 0.6% per day), and an increase in NPP of 2.8 gC m−2 yr−1 per day. However, owing to enhanced soil carbon decomposition accompanying the GPP increase, a change in GSL correlates only poorly with a change in annual net ecosystem productivity (NEP).
Satellite-derived Normalized Difference Vegetation Index (NDVI), a proxy of vegetation productivity, is known to be correlated with temperature in northern ecosystems. This relationship, however, may ...change over time following alternations in other environmental factors. Here we show that above 30°N, the strength of the relationship between the interannual variability of growing season NDVI and temperature (partial correlation coefficient RNDVI-GT) declined substantially between 1982 and 2011. This decrease in RNDVI-GT is mainly observed in temperate and arctic ecosystems, and is also partly reproduced by process-based ecosystem model results. In the temperate ecosystem, the decrease in RNDVI-GT coincides with an increase in drought. In the arctic ecosystem, it may be related to a nonlinear response of photosynthesis to temperature, increase of hot extreme days and shrub expansion over grass-dominated tundra. Our results caution the use of results from interannual time scales to constrain the decadal response of plants to ongoing warming.
More than half of the solar energy absorbed by land surfaces is currently used to evaporate water. Climate change is expected to intensify the hydrological cycle and to alter evapotranspiration, with ...implications for ecosystem services and feedback to regional and global climate. Evapotranspiration changes may already be under way, but direct observational constraints are lacking at the global scale. Until such evidence is available, changes in the water cycle on land−a key diagnostic criterion of the effects of climate change and variability−remain uncertain. Here we provide a data-driven estimate of global land evapotranspiration from 1982 to 2008, compiled using a global monitoring network, meteorological and remote-sensing observations, and a machine-learning algorithm. In addition, we have assessed evapotranspiration variations over the same time period using an ensemble of process-based land-surface models. Our results suggest that global annual evapotranspiration increased on average by 7.1 ± 1.0 millimetres per year per decade from 1982 to 1997. After that, coincident with the last major El Niño event in 1998, the global evapotranspiration increase seems to have ceased until 2008. This change was driven primarily by moisture limitation in the Southern Hemisphere, particularly Africa and Australia. In these regions, microwave satellite observations indicate that soil moisture decreased from 1998 to 2008. Hence, increasing soil-moisture limitations on evapotranspiration largely explain the recent decline of the global land-evapotranspiration trend. Whether the changing behaviour of evapotranspiration is representative of natural climate variability or reflects a more permanent reorganization of the land water cycle is a key question for earth system science.
About 25% of European livestock intake is based on permanent and sown grasslands. To fulfill rising demand for animal products, an intensification of livestock production may lead to an increased ...consumption of crop and compound feeds. In order to preserve an economically and environmentally sustainable agriculture, a more forage based livestock alimentation may be an advantage. However, besides management, grassland productivity is highly vulnerable to climate (i.e., temperature, precipitation, CO2 concentration), and spatial information about European grassland productivity in response to climate change is scarce. The process-based vegetation model ORCHIDEE-GM, containing an explicit representation of grassland management (i.e., herbage mowing and grazing), is used here to estimate changes in potential productivity and potential grass-fed ruminant livestock density across European grasslands over the period 1961-2010. Here "potential grass-fed ruminant livestock density" denotes the maximum density of livestock that can be supported by grassland productivity in each 25 km × 25 km grid cell. In reality, livestock density could be higher than potential (e.g., if additional feed is supplied to animals) or lower (e.g., in response to economic factors, pedo-climatic and biotic conditions ignored by the model, or policy decisions that can for instance reduce livestock numbers). When compared to agricultural statistics (Eurostat and FAOstat), ORCHIDEE-GM gave a good reproduction of the regional gradients of annual grassland productivity and ruminant livestock density. The model however tends to systematically overestimate the absolute values of productivity in most regions, suggesting that most grid cells remain below their potential grassland productivity due to possible nutrient and biotic limitations on plant growth. When ORCHIDEE-GM was run for the period 1961-2010 with variable climate and rising CO2, an increase of potential annual production (over 3%) per decade was found: 97% of this increase was attributed to the rise in CO2, -3% to climate trends and 15% to trends in nitrogen fertilization and deposition. When compared with statistical data, ORCHIDEE-GM captures well the observed phase of climate-driven interannual variability in grassland production well, whereas the magnitude of the interannual variability in modeled productivity is larger than the statistical data. Regional grass-fed livestock numbers can be reproduced by ORCHIDEE-GM based on its simple assumptions and parameterization about productivity being the only limiting factor to define the sustainable number of animals per unit area. Causes for regional model-data misfits are discussed, including uncertainties in farming practices (e.g., nitrogen fertilizer application, and mowing and grazing intensity) and in ruminant diet composition, as well as uncertainties in the statistical data and in model parameter values.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Proxy‐based reconstructions show that the climate during the mid‐Holocene (MH) was warmer and wetter than the present day in most regions of China, characterized by a northwestward extension of the ...East Asian summer monsoon and an increase in woody cover. However, climate simulations that neglect vegetation shifts yield cooler climates than proxy‐based reconstructions for the MH. Here, we simulate MH vegetation cover, productivity, and terrestrial parameters in China using a state‐of‐the‐art land surface model forced with realistic proxy‐based climate data. Our simulations corroborate MH vegetation cover inferred from 246 pollen sites, and indicate a higher vegetation productivity in China, despite the lower CO2 concentration during the MH compared to the present day. Enhanced vegetation growth during the MH could have affected land surface energy and hydrological budgets through biophysical feedbacks. Our findings highlight the impact of vegetation dynamics on the terrestrial carbon cycle and regional climate in China.
Plain Language Summary
Multiple paleoclimate archives illustrate warmer and wetter climate during the mid‐Holocene (MH; ∼6,000 years ago) than at present in most regions of China. However, current model results and proxy‐based reconstructions have some key discrepancies in climate reconstructions, possibly because these climate simulations have overlooked vegetation changes. Therefore, it is essential to develop a vegetation cover map for China to examine the vegetation‐climate feedback during the MH. Here, we present reconstructions of mid‐Holocene vegetation cover, productivity and terrestrial parameters in China at a very high resolution using a land surface model. Simulation results can reproduce MH vegetation cover indicated by paleo‐records and suggest increased tree cover and vegetation productivity in China. Vegetation changes during the MH likely had an important impact on regional climate in China through altering terrestrial parameters. In contrast, multiple‐model ensembles in the latest Paleoclimate Modeling Intercomparison Project significantly underestimated MH vegetation growth primarily because of inherent bias in prescribed vegetation maps. This work reveals the critical impact of MH vegetation cover on terrestrial carbon, energy and hydrological budgets in China, and underlines the need to incorporate vegetation dynamics in terrestrial or climate simulations for the past and future.
Key Points
Our work provides a reliable and spatially continuous mid‐Holocene vegetation map for China at a resolution of 0.5°
Calculated mid‐Holocene vegetation gross primary productivity of ∼7.5 PgC/yr in China is higher than the present day
Vegetation dynamics should be considered in simulating mid‐Holocene terrestrial carbon cycle and climate change for China
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