46 results found
Prentice I, Stocker B, Zscheischler J, et al., Drought impacts on terrestrial primary production underestimated by satellite monitoring, Nature Geoscience, ISSN: 1752-0894
Satellite retrievals of information about the Earth’s surface are widely used to monitor global terrestrial photosynthesis and primary production and to examine the ecological impacts of droughts. Methods for estimating photosynthesis from space commonly combine information on vegetation greenness, incoming radiation, temperature, and atmospheric demand for water (vapour-pressure deficit), but do not account for the direct effects of low soil moisture. They instead rely on vapour-pressure deficit as a proxy for dryness, despite widespread evidence that soil moisture deficits have a direct impact on vegetation, independent of vapour-pressure deficit. Here, we use a globally distributed measurement network to assess the effect of soil moisture on photosynthesis, and identify a common bias in an ensemble of satellite-based estimates of photosynthesis that is governed by the magnitude of soil moisture effects on photosynthetic light-use efficiency. We develop methods to account for the influence of soil moisture and estimate that soil moisture effects reduce global annual photosynthesis by ~15%, increase interannual variability by more than 100% across 25% of the global vegetated land surface, and amplify the impacts of extreme events on primary production. These results demonstrate the importance of soil moisture effects for monitoring carbon-cycle variability and drought impacts on vegetation productivity from space.
Vicca S, Stocker BD, Reed S, et al., 2018, Using research networks to create the comprehensive datasets needed to assess nutrient availability as a key determinant of terrestrial carbon cycling, ENVIRONMENTAL RESEARCH LETTERS, Vol: 13, ISSN: 1748-9326
Wang Y, Ciais P, Goll D, et al., 2018, GOLUM-CNP v1.0: a data-driven modeling of carbon, nitrogen and phosphorus cycles in major terrestrial biomes, GEOSCIENTIFIC MODEL DEVELOPMENT, Vol: 11, Pages: 3903-3928, ISSN: 1991-959X
Stocker BD, Zscheischler J, Keenan TF, et al., 2018, Quantifying soil moisture impacts on light use efficiency across biomes., New Phytologist, Vol: 218, Pages: 1430-1449, ISSN: 0028-646X
Terrestrial primary productivity and carbon cycle impacts of droughts are commonly quantified using vapour pressure deficit (VPD) data and remotely sensed greenness, without accounting for soil moisture. However, soil moisture limitation is known to strongly affect plant physiology. Here, we investigate light use efficiency, the ratio of gross primary productivity (GPP) to absorbed light. We derive its fractional reduction due to soil moisture (fLUE), separated from VPD and greenness changes, using artificial neural networks trained on eddy covariance data, multiple soil moisture datasets and remotely sensed greenness. This reveals substantial impacts of soil moisture alone that reduce GPP by up to 40% at sites located in sub-humid, semi-arid or arid regions. For sites in relatively moist climates, we find, paradoxically, a muted fLUE response to drying soil, but reduced fLUE under wet conditions. fLUE identifies substantial drought impacts that are not captured when relying solely on VPD and greenness changes and, when seasonally recurring, are missed by traditional, anomaly-based drought indices. Counter to common assumptions, fLUE reductions are largest in drought-deciduous vegetation, including grasslands. Our results highlight the necessity to account for soil moisture limitation in terrestrial primary productivity data products, especially for drought-related assessments.
Penuelas J, Sardans J, Filella I, et al., 2017, Impacts of Global Change on Mediterranean Forests and Their Services, FORESTS, Vol: 8, ISSN: 1999-4907
Li W, Ciais P, Peng S, et al., 2017, Land-use and land-cover change carbon emissions between 1901 and 2012 constrained by biomass observations, BIOGEOSCIENCES, Vol: 14, Pages: 5053-5067, ISSN: 1726-4170
Terrer C, Vicca S, Stocker BD, et al., 2017, Ecosystem responses to elevated CO2 governed by plant-soil interactions and the cost of nitrogen acquisition., New Phytologist, Vol: 217, Pages: 507-522, ISSN: 0028-646X
Contents Summary I. II. III. IV. References SUMMARY: Land ecosystems sequester on average about a quarter of anthropogenic CO2 emissions. It has been proposed that nitrogen (N) availability will exert an increasingly limiting effect on plants' ability to store additional carbon (C) under rising CO2 , but these mechanisms are not well understood. Here, we review findings from elevated CO2 experiments using a plant economics framework, highlighting how ecosystem responses to elevated CO2 may depend on the costs and benefits of plant interactions with mycorrhizal fungi and symbiotic N-fixing microbes. We found that N-acquisition efficiency is positively correlated with leaf-level photosynthetic capacity and plant growth, and negatively with soil C storage. Plants that associate with ectomycorrhizal fungi and N-fixers may acquire N at a lower cost than plants associated with arbuscular mycorrhizal fungi. However, the additional growth in ectomycorrhizal plants is partly offset by decreases in soil C pools via priming. Collectively, our results indicate that predictive models aimed at quantifying C cycle feedbacks to global change may be improved by treating N as a resource that can be acquired by plants in exchange for energy, with different costs depending on plant interactions with microbial symbionts.
Davis TW, Prentice IC, Stocker BD, et al., 2017, Simple Process-Led Algorithms for Simulating Habitats (SPLASH v.1.0): Robust Indices of Radiation, Evapotranspiration and Plant-Available Moisture, Geoscientific Model Development, Vol: 10, Pages: 689-708, ISSN: 1991-959X
Bioclimatic indices for use in studies of ecosystemfunction, species distribution, and vegetation dynamics underchanging climate scenarios depend on estimates of surfacefluxes and other quantities, such as radiation, evapotranspi-ration and soil moisture, for which direct observations aresparse. These quantities can be derived indirectly from me-teorological variables, such as near-surface air temperature,precipitation and cloudiness. Here we present a consolidatedset of simple process-led algorithms for simulating habitats(SPLASH) allowing robust approximations of key quantitiesat ecologically relevant timescales. We specify equations,derivations, simplifications, and assumptions for the estima-tion of daily and monthly quantities of top-of-the-atmospheresolar radiation, net surface radiation, photosynthetic photonflux density, evapotranspiration (potential, equilibrium, andactual), condensation, soil moisture, and runoff, based onanalysis of their relationship to fundamental climatic drivers.The climatic drivers include a minimum of three meteoro-logical inputs: precipitation, air temperature, and fraction ofbright sunshine hours. Indices, such as the moisture index,the climatic water deficit, and the Priestley–Taylor coeffi-cient, are also defined. The SPLASH code is transcribed inC++, FORTRAN, Python, and R. A total of 1 year of resultsare presented at the local and global scales to exemplify thespatiotemporal patterns of daily and monthly model outputsalong with comparisons to other model results.
Davis T, Prentice IC, Stocker BD, et al., 2017, Simple process-led algorithms for simulating habitats (SPLASH v.1.0): robust indices of radiation, evapotranspiration and plant-available moisture, Geoscientific Model Development, Vol: 10, Pages: 689-708, ISSN: 1991-9603
Bioclimatic indices for use in studies of ecosystem function, species distribution, and vegetation dynamics under changing climate scenarios depend on estimates of surface fluxes and other quantities, such as radiation, evapotranspiration and soil moisture, for which direct observations are sparse. These quantities can be derived indirectly from meteorological variables, such as near-surface air temperature, precipitation and cloudiness. Here we present a consolidated set of simple process-led algorithms for simulating habitats (SPLASH) allowing robust approximations of key quantities at ecologically relevant timescales. We specify equations, derivations, simplifications, and assumptions for the estimation of daily and monthly quantities of top-of-the-atmosphere solar radiation, net surface radiation, photosynthetic photon flux density, evapotranspiration (potential, equilibrium, and actual), condensation, soil moisture, and runoff, based on analysis of their relationship to fundamental climatic drivers. The climatic drivers include a minimum of three meteorological inputs: precipitation, air temperature, and fraction of bright sunshine hours. Indices, such as the moisture index, the climatic water deficit, and the Priestley–Taylor coefficient, are also defined. The SPLASH code is transcribed in C++, FORTRAN, Python, and R. A total of 1 year of results are presented at the local and global scales to exemplify the spatiotemporal patterns of daily and monthly model outputs along with comparisons to other model results.
Stocker BD, Yu Z, Massa C, et al., 2017, Holocene peatland and ice-core data constraints on the timing and magnitude of CO2 emissions from past land use, PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, Vol: 114, Pages: 1492-1497, ISSN: 0027-8424
Arneth A, Sitch S, Pongratz J, et al., 2017, Historical carbon dioxide emissions caused by land-use changes are possibly larger than assumed, NATURE GEOSCIENCE, Vol: 10, Pages: 79-+, ISSN: 1752-0894
Terrer C, Vicca S, Hungate BA, et al., 2017, Response to Comment on "Mycorrhizal association as a primary control of the CO2 fertilization effect", Science, Vol: 355, ISSN: 0036-8075
Norby et al. center their critique on the design of the data set and the response variable used. We address these criticisms and reinforce the conclusion that plants that associate with ectomycorrhizal fungi exhibit larger biomass and growth responses to elevated CO2 compared with plants that associate with arbuscular mycorrhizae.
Zhang Y, Xiao X, Guanter L, et al., 2016, Precipitation and carbon-water coupling jointly control the interannual variability of global land gross primary production, SCIENTIFIC REPORTS, Vol: 6, ISSN: 2045-2322
Cervarich M, Shu S, Jain AK, et al., 2016, The terrestrial carbon budget of South and Southeast Asia, ENVIRONMENTAL RESEARCH LETTERS, Vol: 11, ISSN: 1748-9326
Zhao F, Zeng N, Asrar G, et al., 2016, Role of CO2, climate and land use in regulating the seasonal amplitude increase of carbon fluxes in terrestrial ecosystems: a multimodel analysis, BIOGEOSCIENCES, Vol: 13, Pages: 5121-5137, ISSN: 1726-4170
Calle L, Canadell JG, Patra P, et al., 2016, Regional carbon fluxes from land use and land cover change in Asia, 1980-2009, ENVIRONMENTAL RESEARCH LETTERS, Vol: 11, ISSN: 1748-9326
Mendelsohn R, Prentice IC, Schmitz O, et al., 2016, The Ecosystem Impacts of Severe Warming, 128th Annual Meeting of the American Economic Association, Publisher: American Economic Association, Pages: 612-614, ISSN: 0002-8282
Stocker BD, Prentice IC, Cornell SE, et al., 2016, Terrestrial nitrogen cycling in Earth system models revisited., New Phytologist, Vol: 210, Pages: 1165-1168, ISSN: 1469-8137
Global environmental change is rapidly altering the dynamics of terrestrial vegetation, with consequences for the functioning of the Earth system and provision of ecosystem services1, 2. Yet how global vegetation is responding to the changing environment is not well established. Here we use three long-term satellite leaf area index (LAI) records and ten global ecosystem models to investigate four key drivers of LAI trends during 1982–2009. We show a persistent and widespread increase of growing season integrated LAI (greening) over 25% to 50% of the global vegetated area, whereas less than 4% of the globe shows decreasing LAI (browning). Factorial simulations with multiple global ecosystem models suggest that CO2 fertilization effects explain 70% of the observed greening trend, followed by nitrogen deposition (9%), climate change (8%) and land cover change (LCC) (4%). CO2 fertilization effects explain most of the greening trends in the tropics, whereas climate change resulted in greening of the high latitudes and the Tibetan Plateau. LCC contributed most to the regional greening observed in southeast China and the eastern United States. The regional effects of unexplained factors suggest that the next generation of ecosystem models will need to explore the impacts of forest demography, differences in regional management intensities for cropland and pastures, and other emerging productivity constraints such as phosphorus availability.
Murray-Tortarolo G, Friedlingstein P, Sitch S, et al., 2016, The carbon cycle in Mexico: past, present and future of C stocks and fluxes, Biogeosciences, Vol: 13, Pages: 223-238, ISSN: 1726-4189
We modeled the carbon (C) cycle in Mexico with a process-based approach. We used different available products (satellite data, field measurements, models and flux towers) to estimate C stocks and fluxes in the country at three different time frames: present (defined as the period 2000–2005), the past century (1901–2000) and the remainder of this century (2010–2100). Our estimate of the gross primary productivity (GPP) for the country was 2137 ± 1023 TgC yr−1 and a total C stock of 34 506 ± 7483 TgC, with 20 347 ± 4622 TgC in vegetation and 14 159 ± 3861 in the soil.Contrary to other current estimates for recent decades, our results showed that Mexico was a C sink over the period 1990–2009 (+31 TgC yr−1) and that C accumulation over the last century amounted to 1210 ± 1040 TgC. We attributed this sink to the CO2 fertilization effect on GPP, which led to an increase of 3408 ± 1060 TgC, while both climate and land use reduced the country C stocks by −458 ± 1001 and −1740 ± 878 TgC, respectively. Under different future scenarios, the C sink will likely continue over the 21st century, with decreasing C uptake as the climate forcing becomes more extreme. Our work provides valuable insights on relevant driving processes of the C cycle such as the role of drought in drylands (e.g., grasslands and shrublands) and the impact of climate change on the mean residence time of soil C in tropical ecosystems.
Fowler D, Steadman CE, Stevenson D, et al., 2015, Effects of global change during the 21st century on the nitrogen cycle, Atmospheric Chemistry and Physics, Vol: 15, Pages: 13849-13893, ISSN: 1680-7324
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 as well as consistency within and among components, alongside methodology and data limitations. CO2 emissions from fossil fuels and industry (EFF) are based on energy statistics and cement production data, 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 o
Osborne JM, Lambert FH, Groenendijk M, et al., 2015, Reconciling Precipitation with Runoff: Observed Hydrological Change in the Midlatitudes, JOURNAL OF HYDROMETEOROLOGY, Vol: 16, Pages: 2403-2420, ISSN: 1525-755X
Stocker BD, Joos F, 2015, Quantifying differences in land use emission estimates implied by definition discrepancies, Earth System Dynamics, Vol: 6, Pages: 731-744, ISSN: 2190-4987
The quantification of CO2 emissions from anthropogenic land use and land use change (eLUC) is essential to understand the drivers of the atmospheric CO2 increase and to inform climate change mitigation policy. Reported values in synthesis reports are commonly derived from different approaches (observation-driven bookkeeping and process-modelling) but recent work has emphasized that inconsistencies between methods may imply substantial differences in eLUC estimates. However, a consistent quantification is lacking and no concise modelling protocol for the separation of primary and secondary components of eLUC has been established. Here, we review differences of eLUC quantification methods and apply an Earth System Model (ESM) of Intermediate Complexity to quantify them. We find that the magnitude of effects due to merely conceptual differences between ESM and offline vegetation model-based quantifications is ~ 20 % for today. Under a future business-as-usual scenario, differences tend to increase further due to slowing land conversion rates and an increasing impact of altered environmental conditions on land-atmosphere fluxes. We establish how coupled Earth System Models may be applied to separate secondary component fluxes of eLUC arising from the replacement of potential C sinks/sources and the land use feedback and show that secondary fluxes derived from offline vegetation models are conceptually and quantitatively not identical to either, nor their sum. Therefore, we argue that synthesis studies should resort to the "least common denominator" of different methods, following the bookkeeping approach where only primary land use emissions are quantified under the assumption of constant environmental boundary conditions.
Murray-Tortarolo G, Friedlingstein P, Sitch S, et al., 2015, The carbon cycle in Mexico: past, present and future of C stocks and fluxes, Biogeosciences Discussions, Vol: 12, Pages: 12501-12541
<jats:p>We modelled the carbon (C) cycle in Mexico with a process-based approach. We used different available products (satellite data, field measurements, models and flux towers) to estimate C stocks and fluxes in the country at three different time frames: present (defined as the period 2000–2005), the past century (1901–2000) and the remainder of this century (2010–2100). Our estimate of the gross primary productivity (GPP) for the country was 2137 ± 1023 Tg C yr<sup>−1</sup> and a total C stock of 34 506 ± 7483 Tg C, with 20 347 ± 4622 Pg C in vegetation and 14 159 ± 3861 in the soil. <br></br> Contrary to other current estimates for recent decades, our results showed that Mexico was a C sink over the period 1990–2009 (+31 Tg C yr<sup>−1</sup>) and that C accumulation over the last century amounted to 1210 ± 1040 Tg C. We attributed this sink to the CO<sub>2</sub> fertilization effect on GPP, which led to an increase of 3408 ± 1060 Tg C, while both climate and land use reduced the country C stocks by &minus;458 ± 1001 and &minus;1740 ± 878 Tg C, respectively. Under different future scenarios the C sink will likely continue over 21st century, with decreasing C uptake as the climate forcing becomes more extreme. Our work provides valuable insights on relevant driving processes of the C-cycle such as the role of drought in marginal lands (e.g. grasslands and shrublands) and the impact of climate change on the mean residence time of C in tropical ecosystems.</jats:p>
Olin S, Lindeskog M, Pugh TAM, et al., 2015, Soil carbon management in large-scale Earth system modelling: implications for crop yields and nitrogen leaching, Earth System Dynamics Discussions, Vol: 6, Pages: 1047-1100
<jats:p>We explore cropland management alternatives and the effect these can have on future C and N pools and fluxes using the land use-enabled dynamic vegetation model LPJ-GUESS. Simulated crop production, cropland carbon storage, carbon sequestration and nitrogen leaching from croplands are evaluated and discussed. Compared to the version of LPJ-GUESS that does not include land use dynamics, estimates of soil carbon stocks and nitrogen leaching from terrestrial to aquatic ecosystems were improved. <br><br> We explore trade-offs between important ecosystem services that can be provided from agricultural fields such as crop yields, retention of nitrogen and carbon storage. These trade-offs are evaluated for current land use and climate and further explored for future conditions within the two future climate change scenarios, RCP 2.6 and 8.5. Our results show that the potential for carbon sequestration due to typical cropland management practices such as no-till and cover-crops proposed in literature is not realised, globally or over larger climatic regions. Our results highlight important considerations to be made when modelling C–N interactions in agricultural ecosystems under future environmental change, and the effects these have on terrestrial biogeochemical cycles.</jats:p>
Bohn TJ, Melton JR, Ito A, et al., 2015, WETCHIMP-WSL: intercomparison of wetland methane emissions models over West Siberia, Biogeosciences, Vol: 12, Pages: 3321-3349, ISSN: 1726-4189
Wetlands are the world's largest natural source of methane, a powerful greenhouse gas. The strong sensitivity of methane emissions to environmental factors such as soil temperature and moisture has led to concerns about potential positive feedbacks to climate change. This risk is particularly relevant at high latitudes, which have experienced pronounced warming and where thawing permafrost could potentially liberate large amounts of labile carbon over the next 100 years. However, global models disagree as to the magnitude and spatial distribution of emissions, due to uncertainties in wetland area and emissions per unit area and a scarcity of in situ observations. Recent intensive field campaigns across the West Siberian Lowland (WSL) make this an ideal region over which to assess the performance of large-scale process-based wetland models in a high-latitude environment. Here we present the results of a follow-up to the Wetland and Wetland CH4 Intercomparison of Models Project (WETCHIMP), focused on the West Siberian Lowland (WETCHIMP-WSL). We assessed 21 models and 5 inversions over this domain in terms of total CH4 emissions, simulated wetland areas, and CH4 fluxes per unit wetland area and compared these results to an intensive in situ CH4 flux data set, several wetland maps, and two satellite surface water products. We found that (a) despite the large scatter of individual estimates, 12-year mean estimates of annual total emissions over the WSL from forward models (5.34 ± 0.54 Tg CH4 yr−1), inversions (6.06 ± 1.22 Tg CH4 yr−1), and in situ observations (3.91 ± 1.29 Tg CH4 yr−1) largely agreed; (b) forward models using surface water products alone to estimate wetland areas suffered from severe biases in CH4 emissions; (c) the interannual time series of models that lacked either soil thermal physics appropriate to the high latitudes or realistic emissions from unsaturated peatlands tended to be dominated by a single environmen
Ahlstrom A, Raupach MR, Schurgers G, et al., 2015, The dominant role of semi-arid ecosystems in the trend and variability of the land CO2 sink, SCIENCE, Vol: 348, Pages: 895-899, ISSN: 0036-8075
This data is extracted from the Web of Science and reproduced under a licence from Thomson Reuters. You may not copy or re-distribute this data in whole or in part without the written consent of the Science business of Thomson Reuters.