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Terrestrial Ecosystems in a Changing World. (2006)

Canadell, Josep G.

Berlin, Heidelberg :Springer Berlin / Heidelberg,

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Keywords: Physical geography. ; Electronic books.

Type of Medium: Online Resource

Pages: 1 online resource (366 pages)

Edition: 1st ed.

ISBN: 9783540327301

Series Statement: Global Change - the IGBP Series

URL: https://ebookcentral.proquest.com/lib/geomar/detail.action?docID=324674

DDC: 333.95

Language: English

Note: Intro -- CONTENTS -- 1 Global Ecology, Networks, and Research Synthesis -- 1.1 Introduction -- 1.2 Carbon and Water Cycles in the 21 st Century -- 1.3 Changing Biodiversity and Ecosystem Functioning -- 1.4 Landscapes under Changing Disturbance Regimes -- 1.5 Managing Ecosystem Services -- 1.6 Regions under Stress -- 1.7 The Way Forward -- References -- Part A Carbon and Water Cycles in the 21 st Century -- 2 CO 2 Fertilization: When, Where, How Much? -- 2.1 Carbon a Limiting Plant Resource? -- 2.2 Long-Term Biomass Responses and Carbon Pools -- 2.2.1 Time Matters -- 2.2.2 Nutrients and Water Determine Biomass Responses at Elevated CO 2 -- 2.2.3 Scaling from Growth to Carbon Pools -- 2.3 Carbon to Nutrient Ratios and Consumer Responses -- 2.3.1 The C to N Ratio Widens -- 2.3.2 Consequences for Herbivory, Decomposition and Plant Nutrition -- 2.4 Plant Water Relations and Hydrological Implications -- 2.5 Stress Resistance under Elevated CO 2 -- 2.6 Biodiversity Effects May Outweigh Physiology Effects -- 2.6.1 Hydrology Implications of Elevated CO 2 Depend on Species Abundance -- 2.6.2 Biodiversity Effects on Forest Carbon Stocking and Grassland Responses -- 2.7 Summary and Conclusions -- References -- 3 Ecosystem Responses to Warming and Interacting Global Change Factors -- 3.1 The Multiple Factor Imperative in Global Change Research -- 3.2 Ecosystem Responses to Experimental Warming -- 3.2.1 The GCTE-NEWS Synthesis -- 3.2.2 The ITEX Synthesis -- 3.2.3 The Harvard Forest Soil Warming Experiment -- 3.3 Temperature and CO 2 Interactions in Trees: the TACIT Experiment -- 3.3.1 Experimental Design -- 3.3.2 Growth Responses -- 3.3.3 Higher-Order Responses -- 3.3.4 TACIT Summary -- 3.4 More Than Two Factors: the Jasper Ridge Global Change Experiment -- 3.4.1 Experimental Design -- 3.4.2 Net Primary Productivity -- 3.4.3 Community Composition. , 3.4.4 JRGCE Summary -- 3.5 Modeling Temperature, CO 2 and N Interactions in Trees and Grass -- 3.5.1 Global Change Simulations for a California Annual Grassland -- 3.5.2 Comparing Forest and Grassland with G'DAY -- 3.6 Summary and Conclusions -- Acknowledgments -- References -- 4 Insights from Stable Isotopes on the Role of Terrestrial Ecosystems in the Global Carbon Cycle -- 4.1 Introduction -- 4.2 Ecosystem Carbon Cycles -- 4.3 The Global Carbon Cycle -- 4.4 Future Directions -- Acknowledgments -- In Memoriam -- References -- 5 Effects of Urban Land-Use Change on Biogeochemical Cycles -- 5.1 Introduction -- 5.2 Urban Land-Use Change -- 5.3 Urban Environmental Factors -- 5.3.1 Climate and Atmospheric Composition -- 5.3.2 Atmospheric and Soil Pollution -- 5.3.3 Introductions of Exotic Species -- 5.4 Disturbance and Management Effects -- 5.4.1 Lawn and Horticultural Management -- 5.4.2 Management Effort -- 5.5 Effects of Built Environment -- 5.6 Assessing Biogeochemical Effects - the Importance of Scale -- 5.7 Summary and Conclusions -- Acknowledgments -- References -- 6 Saturation of the Terrestrial Carbon Sink -- 6.1 Introduction -- 6.2 Location of the Current Terrestrial Carbon Sinks -- 6.3 Dynamics of Processes that Contribute to Carbon Sink Saturation -- 6.4 Processes Contributing to Terrestrial Carbon Sink Saturation -- 6.4.1 Processes Driven by Atmospheric Composition Change -- 6.4.2 Processes Driven by Climate Change -- 6.4.3 Processes Driven by Land-Use Change and Land Management -- 6.5 Integration and Model Predictions -- 6.6 Summary and Conclusions -- Acknowledgments -- References -- Part B Changing Biodiversity and Ecosystem Functioning -- 7 Functional Diversity - at the Crossroads between Ecosystem Functioning and Environmental Filters -- 7.1 Introduction -- 7.2 Environmental Filters Affect FD -- 7.3 FD effects on Global Change Drivers. , 7.3.1 The Traits of the Dominants -- 7.3.2 The Role of Interactions -- 7.4 Summary and Conclusions -- Acknowledgments -- References -- 8 Linking Plant Invasions to Global Environmental Change -- 8.1 Introduction -- 8.2 Plant Invasions and Elevated CO 2 -- 8.3 Plant Invasions and Climatic Change -- 8.4 Plant Invasions and Land Eutrophication -- 8.5 Plant Invasions and Changes in Land Use/Cover -- 8.6 Multiple Interactions -- 8.7 Summary and Conclusions -- Acknowledgments -- References -- 9 Plant Biodiversity and Responses to Elevated Carbon Dioxide -- 9.1 Ten Years of GCTE Research: Apprehending Complexity -- 9.1.1 Effects of CO 2 on Plant Diversity Through Alterations of the Physical Environment -- 9.2 Temporal Variation and Response to Elevated CO 2 -- 9.2.1 Reproductive and Evolutionary Aspects of the Response to Elevated CO 2 -- 9.2.2 Communities at Equilibrium Versus Dynamic Systems -- 9.3 Biodiversity Loss and Response to Elevated CO 2 -- 9.3.1 Species Diversity and Response to Elevated CO 2 -- 9.3.2 Ecosystem C Fluxes in a Species-Poor World -- 9.4 Summary and Conclusions -- References -- 10 Predicting the Ecosystem Consequences of Biodiversity Loss: the Biomerge Framework -- 10.1 Biodiversity and Ecosystem Functioning: a Synthesis -- 10.1.1 Why Biodiversity Matters to Global Change Ecology -- 10.1.2 Linking Change in Biodiversity with Change in Ecosystem Functioning -- 10.1.3 Lessons Learned from Early Debates -- 10.1.4 What We Have Learned about the Relationship between Biodiversity and Ecosystem Function -- 10.1.5 The Scientific Framework for Linking Biodiversity and Ecosystem Functioning -- 10.2 The BioMERGE Framework -- 10.2.1 The BioMERGE Structural Sub-Framework -- 10.2.2 The BioMERGE BEF Sub-Framework: an Expansion of the Vitousek-Hooper Framework -- 10.2.3 The BioMERGE Research Implementation Sub-Framework. , 10.3 Discussion: Towards a Large Scale BEF -- Acknowledgments -- References -- Part C Landscapes under Changing Disturbance Regimes -- 11 Plant Species Migration as a Key Uncertainty in Predicting Future Impacts of Climate Change on Ecosystems: Progress and Challenges -- 11.1 Introduction -- 11.2 Will Migration Be Necessary for Species Persistence? -- 11.2.1 Vegetation-Type Models -- 11.2.2 Species-Based Models -- 11.3 Measurements and Models of Migration Rates -- 11.4 Linking Migration and Niche Based Models -- 11.5 Summary and Conclusions -- Acknowledgments -- References -- 12 Understanding Global Fire Dynamics by Classifying and Comparing Spatial Models of Vegetation and Fire -- 12.1 Introduction -- 12.2 Background -- 12.3 Model Classification -- 12.4 Model Comparison -- 12.4.1 The Models -- 12.4.2 The Comparison Design -- 12.5 Results and Discussion -- 12.5.1 Model Classification -- 12.5.2 Model Comparison -- 12.6 Summary and Conclusions -- Acknowledgments -- References -- 13 Plant Functional Types: Are We Getting Any Closer to the Holy Grail? -- 13.1 In Search of the Holy Grail -- 13.2 Individual Plant Structure and Function -- 13.3 Traits and Environmental Gradients -- 13.3.1 Plant Functional Response to Mineral Resource Availability -- 13.3.2 Plant Functional Response to Disturbance -- 13.3.3 Projecting Changes in Plant Functional Traits in Response to Global Change -- 13.4 Scaling from Individual Plants to Communities: from Response Traits to Community Assembly -- 13.5 Scaling from Communities to Ecosystems: from Response Traits to Effect Traits -- 13.6 So, Are We Getting Closer to the Holy Grail? Scaling beyond Ecosystems -- 13.6.1 Plant Functional Traits and Landscape Dynamics -- 13.6.2 Regional to Global Models - Revisiting the Early Functional Classifications -- 13.6.3 Validation: the Contribution of Paleo-Data. , 13.7 Summary and Conclusions -- Acknowledgments -- References -- 14 Spatial Nonlinearities: Cascading Effects in the Earth System -- 14.1 Introduction -- 14.2 Conceptual Framework -- 14.3 Insights to Global Change Issues -- 14.3.1 Historical Example: the Dust Bowl of the 1930s -- 14.3.2 Wildfire -- 14.3.3 Invasive Species and Desertification -- 14.4 Forecasting Spatial Nonlinearities and Catastrophic Events -- 14.5 Summary and Conclusions -- Acknowledgments -- References -- 15 Dynamic Global Vegetation Modeling: Quantifying Terrestrial Ecosystem Responses to Large-Scale Environmental Change -- 15.1 Introduction -- 15.2 Historical Antecedents and Development of DGVMs -- 15.2.1 Plant Geography -- 15.2.2 Plant Physiology and Biogeochemistry -- 15.2.3 Vegetation Dynamics -- 15.2.4 Biophysics -- 15.2.5 Human Intervention -- 15.3 Principles and Construction of DGVMs -- 15.3.1 Model Architecture -- 15.3.2 Net Primary Production -- 15.3.3 Plant Growth and Vegetation Dynamics -- 15.3.4 Hydrology -- 15.3.5 Soil Organic Matter Transformations -- 15.3.6 Nitrogen (N) Cycling -- 15.3.7 Disturbance -- 15.4 Evaluating DGVMS -- 15.4.1 Net Primary Production -- 15.4.2 Remotely Sensed "Greenness" and Vegetation Composition -- 15.4.3 Atmospheric CO 2 Concentration -- 15.4.4 Runoff -- 15.4.5 CO 2 and Water Flux Measurements -- 15.5 Examples of Applications of DGVMS -- 15.5.1 Holocene Changes in Atmospheric CO 2 -- 15.5.2 Boreal "Greening" and the Contemporary Carbon Balance -- 15.5.3 The Pinatubo Effect -- 15.5.4 Future Carbon Balance Projections -- 15.5.5 Carbon-Cycle Feedbacks to Future Climate Change -- 15.5.6 Effects of Land-Use Change on the Carbon Cycle -- 15.6 Some Perspectives and Research Needs -- 15.6.1 Comparison with Field Experiments -- 15.6.2 Plant Functional Types -- 15.6.3 The Nitrogen Cycle -- 15.6.4 Plant Dispersal and Migration -- 15.6.5 Wetlands. , 15.6.6 Multiple Nutrient Limitations.

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Online Resource

Ecosystem Collapse and Climate Change. (2021)

Canadell, Josep G.

Cham :Springer International Publishing AG,

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Keywords: Ecology-Handbooks, manuals, etc. ; Electronic books.

Type of Medium: Online Resource

Pages: 1 online resource (365 pages)

Edition: 1st ed.

ISBN: 9783030713300

Series Statement: Ecological Studies ; v.241

URL: https://ebookcentral.proquest.com/lib/geomar/detail.action?docID=6648082

DDC: 577.27

Language: English

Note: Intro -- Preface -- Contents -- 1: Ecosystem Collapse and Climate Change: An Introduction -- 1.1 Introduction -- 1.2 Defining Ecosystems Collapse -- 1.3 Observed Dynamics as They Occur -- 1.3.1 Polar and Boreal Ecosystems -- 1.3.2 Temperate and Semi-arid Ecosystems -- 1.3.3 Tropical and Temperate Coastal Ecosystems -- References -- Part I: Polar and Boreal Ecosystems -- 2: Ecosystem Collapse on a Sub-Antarctic Island -- 2.1 Background -- 2.2 The Collapse -- 2.2.1 Former State -- 2.2.2 Progression to the New State -- 2.2.3 Functional Changes -- 2.2.4 Context of the Change -- 2.3 Major Causes -- 2.4 Prognosis and Management Strategies -- 2.5 Wider Context -- References -- 3: Permafrost Thaw in Northern Peatlands: Rapid Changes in Ecosystem and Landscape Functions -- 3.1 Introduction -- 3.2 Current Distribution and Characteristics of Peatlands in the Northern Permafrost Region -- 3.2.1 Current Peatland Distribution and Major Regions -- 3.2.2 Peatland Characteristics Across Permafrost Zones -- 3.2.2.1 Peatlands in the Continuous Permafrost Zone -- 3.2.2.2 Peatlands in the Discontinuous Permafrost Zone -- 3.2.2.3 Peatlands in the Sporadic Permafrost Zone -- 3.3 Holocene Development of Peatlands in the Northern Permafrost Region -- 3.3.1 Timing and Mode of Peatland Initiation -- 3.3.2 Timing and Processes of Permafrost Aggradation -- 3.3.3 Holocene Carbon Accumulation in Permafrost Peatlands -- 3.4 Observed Peatland Change Associated with Permafrost Thaw -- 3.4.1 Peatland Change in the Continuous Permafrost Zone -- 3.4.2 Peatland Change in the Discontinuous and Sporadic Permafrost Zones -- 3.5 Implications of Permafrost Thaw -- 3.5.1 Hydrology and Water Quality -- 3.5.2 Ecology and Human Use -- 3.5.3 Carbon Cycling and Greenhouse Gas Exchange -- 3.5.4 Interactions Between Wildfire, Permafrost Thaw, and Peatland Carbon Balance -- 3.6 Conclusions. , References -- 4: Post-fire Recruitment Failure as a Driver of Forest to Non-forest Ecosystem Shifts in Boreal Regions -- 4.1 Introduction -- 4.2 Role of Fire in Boreal Forests -- 4.2.1 Post-fire Recruitment Dynamics -- 4.2.2 Post-fire Recruitment Failure -- 4.2.3 A Case Study of Post-fire Recruitment Failure in Southern Siberia -- 4.3 Drivers of Change in the Boreal Forest Zone -- 4.3.1 Climate Change -- 4.3.1.1 Climate Change and Increases in the Fire Regime -- 4.3.1.2 Climate Change and Decreased Ecosystem Resilience -- 4.3.2 Management and Human Influence -- 4.3.2.1 Forest Management and the Fire Regime -- 4.4 Measuring the Scale of the Problem -- 4.4.1 Disturbance Detection -- 4.4.2 Large-Scale Trends in Vegetation -- 4.4.3 Detecting Post-fire Recruitment Failure -- 4.4.4 Post-fire Recruitment Failure and the Prediction of Future Climate -- 4.5 Future Management -- References -- 5: A Paleo-perspective on Ecosystem Collapse in Boreal North America -- 5.1 Introduction -- 5.2 Ecosystem Collapse During the Late Pleistocene -- 5.2.1 Abrupt Climatic Changes -- 5.2.2 Human Disturbance -- 5.3 Ecosystem Building During Early- to Mid-Holocene -- 5.3.1 Creation of the Boreal Forest Environment -- 5.3.2 Peatland Expansion -- 5.3.3 Southern Conifer Forest and Insects -- 5.4 Ecosystem Collapse After the Mid-Holocene -- 5.4.1 Ecosystem Collapse in the Northern Part of the Boreal Forest -- 5.4.1.1 Climate-Fire Interactions -- 5.4.1.2 Collateral Effects of Forest Collapse -- 5.4.1.3 Extensive Collapse of Woodlands During the Little Ice Age -- 5.4.1.4 Wetland Ecosystem Collapse -- 5.4.1.5 Changing Water Levels of Subarctic Lakes and Rivers -- 5.4.2 Ecosystem Collapse in the Southern Part of the Boreal Forest -- 5.4.2.1 Shift of Closed-Crown Forests to Woodlands -- 5.4.2.2 Microclimatic Signatures of Closed-Crown Forests and Woodlands. , 5.5 Present Post-Little Ice Age Warming and Ecosystem Collapse and Recovery -- 5.5.1 Tree Line Advance, Regeneration and Consolidation of Pre-existing Forests of the Forest-Tundra Ecotone -- 5.5.2 Shrubification of the Northern Part of the Boreal Biome -- 5.5.3 Collapse and Recovery of Wetland and Riparian Ecosystems -- 5.6 Lessons Learned from the Past to Anticipate the Future -- References -- Part II: Temperate and Semi-arid Ecosystems -- 6: The 2016 Tasmanian Wilderness Fires: Fire Regime Shifts and Climate Change in a Gondwanan Biogeographic Refugium -- 6.1 Introduction -- 6.2 The 2016 Wilderness Fires -- 6.2.1 2016 Fire Impacts on A. cupressoides Populations -- 6.3 Persistence of A. cupressoides Under Climate Change -- 6.4 Broader Ecological Impacts -- 6.5 Anthropocene Management Responses -- 6.6 Conclusions -- References -- 7: Climate-Induced Global Forest Shifts due to Heatwave-Drought -- 7.1 Overview of Forest Mortality Episodes at the Global Scale -- 7.2 Causes of Forest Mortality by Drought -- 7.3 Historical Perspective of Forest Shifts -- 7.4 Abrupt Forest Mortality Events and Ecosystem Trajectory -- 7.4.1 General Trends -- 7.4.2 Cases of Forest Collapse and Its Relation with Management -- 7.5 Enhancing Resilience -- 7.5.1 Water Demand Strategy -- 7.5.2 Population and Biodiversity-Based Strategies -- 7.5.3 Disturbance Regime-Based Strategy: Wildfires -- 7.6 Future Prognosis of Forest Collapse -- 7.7 Conclusion -- References -- 8: Extreme Events Trigger Terrestrial and Marine Ecosystem Collapses in the Southwestern USA and Southwestern Australia -- 8.1 Introduction -- 8.1.1 Progressively Intense Ecological Stresses: From Drought to Warming to Heatwaves -- 8.1.2 Legacy Effects, Disturbance Interactions, and Order of Events -- 8.1.3 Ecosystem Collapses in Southwestern Australia and the USA -- 8.2 Southwestern USA Case Study. , 8.2.1 Terrestrial Drivers and Ecosystem Responses in the Southwestern USA -- 8.2.2 Marine Drivers and Ecosystem Responses in Southwestern USA -- 8.3 Southwestern Australian Case Study -- 8.3.1 Terrestrial Drivers and Ecosystem Responses in Southwestern Australia -- 8.3.2 Marine Drivers and Ecosystem Responses in Southwestern Australia -- 8.4 Ecological Implications -- 8.4.1 Prognosis for the Future -- 8.5 Managing Ecosystem Collapse and Future Research -- References -- Part III: Tropical and Temperate Coastal Ecosystems -- 9: Processes and Factors Driving Change in Mangrove Forests: An Evaluation Based on the Mass Dieback Event in Australia´s Gulf... -- 9.1 Introduction -- 9.2 Dynamic Processes Influencing Tidal Wetlands and Mangroves -- 9.2.1 Level 1: Global Setting of Tidal Wetlands: Site Geomorphology, Sea Level and Climate -- 9.2.2 Level 2: Composition of Dominant Vegetation Types of Tidal Wetlands: Regional Influences of Temperature and Rainfall -- 9.2.3 Level 3: Sustainable Turnover and Replenishment of Mangrove Forests: Small-Scale, Natural Disturbance Driving Forest Re-... -- 9.2.4 Level 4: Severe Drivers of Change and Replacement of Tidal Wetland Habitat: Large-Scale Disturbance-Recovery Dynamics In... -- 9.3 Climate and Natural Drivers of Key Environmental Changes Along Mangrove Shorelines -- 9.3.1 Shoreline Erosion and Seafront Retreat: Severe Storms, Sea Level Rise -- 9.3.2 Estuarine Bank Erosion: Flood Events, Sea Level Rise -- 9.3.3 Terrestrial Retreat: Upland Erosion, Sea Level Rise -- 9.3.4 Saltpan Scouring: Pan Erosion, Sea Level Rise -- 9.3.5 Depositional Gain: Flood Events, Sea Level Rise -- 9.3.6 Severe Storm Damage: Mangrove Dieback, Cyclonic Winds, Large Waves -- 9.3.7 Light Gaps: Lightning Strikes, Herbivore Attacks, Mini Tornados. , 9.3.8 Zonal Retreat: Local-Scale Patterns of Single, Dual and Triple Zones of Concurrent Upper Zone Dieback -- 9.4 The Synchronous, Large-Scale Mass Dieback of Mangroves in Australia´s Remote Gulf of Carpentaria -- Box. Mangrove Diversity in the Area of Mass Dieback of Mangroves -- 9.4.1 Likely Causal Factors Observed Along the Impacted Shoreline -- 9.4.2 Linking Specific Factors with the Dieback Event -- 9.4.3 Did Human-Induced Climate Change Play a Role in the 2015-2016 Dieback of Mangroves? -- 9.5 Current Recommendations for Management Strategies -- 9.6 A Regional Mitigation and Monitoring Strategy for Tidal Wetlands -- 9.7 Vulnerability of Impacted Shorelines with Key Risks and Consequences -- References -- 10: Recurrent Mass-Bleaching and the Potential for Ecosystem Collapse on Australia´s Great Barrier Reef -- 10.1 Introduction -- 10.2 Considering the Criteria for Collapse of Coral Reefs -- 10.3 Background Trends on the Great Barrier Reef -- 10.4 Climate Change and Mass Coral Bleaching -- 10.5 Is the Great Barrier Reef Collapsing? -- 10.6 Recasting Conservation Goals for Coral Reefs -- References -- 11: Sliding Toward the Collapse of Mediterranean Coastal Marine Rocky Ecosystems -- 11.1 Introduction -- 11.2 Marine Heatwaves and Mass Mortality Events in the Mediterranean -- 11.2.1 Sea Surface Thermal Stress Signals in the Cold Northern Mediterranean Areas -- 11.2.2 Subsurface Thermal Stress Signals in the Cold NW Mediterranean -- 11.2.2.1 Subsurface MHWs Amplification -- 11.3 Immediate Impacts, Sublethal Effects, and Recovery of Habitat-Forming Gorgonians from Mass Mortalities Events -- 11.3.1 Immediate Impacts and Sublethal Effects of Mass Mortality Events -- 11.3.1.1 Immediate Impacts -- 11.3.1.2 Sublethal Effects with Long-Term Consequences -- 11.3.2 Recovery Trajectories. , Box 11.1 Description of Demographic and Genetic Features of Octocorals.

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CO2 emissions and ancillary data for 343 cities from diverse sources (2017)

Nangini, Cathy ; Peregon, Anna ; Ciais, Philippe ; [et al.]

PANGAEA

In: Supplement to: Nangini, Cathy; Peregon, Anna; Ciais, Philippe; Weddige, Ulf; Vogel, Felix; Wang, Jun; Bréon, François-Marie; Bachra, Simeran; Wang, Yilong; Gurney, Kevin; Yamagata, Yoshiki; Appleby, Kyra; Telahoun, Sara; Canadell, Josep G; Grübler, Arnulf; Dhakal, Shobhakar; Creutzig, Felix (2019): A global dataset of CO2 emissions and ancillary data related to emissions for 343 cities. Scientific Data, 6, 180280, https://doi.org/10.1038/sdata.2018.280

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Publication Date: 2023-01-14

Description: A dataset of dimensions 343 × 179 consisting of CO2 emissions from CDP (187 cities, few in developing countries), the Bonn Center for Local Climate Action and Reporting (73 cities, mainly in developing countries), and data collected by Peking University (83 cities in China). Further, a set of socio-economic variables – called ancillary data – were collected from other datasets (e.g. socio-economic and traffic indices) or calculated (climate indices, urban area expansion), then combined with the emission data. The remaining attributes are descriptive (e.g. city name, country, etc.) or related to quality assurance/control checks. Please open using Tab as separator and " as text delimiter.

Type: Dataset

Format: application/zip, 1.8 MBytes

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The effects of elevated [CO2] on plant-soil carbon below-ground: A summary and synthesis (1995)

Canadell, Josep G. ; Pitelka, Louis F. ; Ingram, John S. I.

Springer

Plant and soil 187 (1995), S. 391-400

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ISSN: 1573-5036

Keywords: belowground respiration ; ecosystem carbon balance ; enhanced atmospheric [CO2] ; root symbionts ; root turnover ; soil carbon accumulation

Source: Springer Online Journal Archives 1860-2000

Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition

Notes: Abstract We undertake a synthesis of the most relevant results from the presentations at the meeting “Plant-Soil Carbon Below-Ground: The Effects of Elevated CO2” (Oxford-UK, September 1995), many of which are published in this Special Issue. Below-ground responses to elevated [CO2] are important because the capacity of soils for long-term carbon sequestration. We draw the following conclusions: (i) several ecosystems exposed to elevated [CO2] showed sustained increased CO2 uptake at the plot level for many years. A few systems, however, showed complete down-regulation of net CO2 uptake after several years of elevated [CO2] exposure; (ii) under elevated [CO2], a greater proportion of fixed carbon is generally allocated below-ground, potentially increasing the capacity of below-ground sinks; and (iii) some of the increased capacity of these sinks may lead to increased long-term soil carbon sequestration, although strong evidence is still lacking. We highlight the need for more soil studies to be undertaken within ongoing ecosystem-level experiments, and suggest that while some key experiments already established should be maintained to allow long term effects and feedbacks to take place, more research effort should be directed to mechanisms of soil organic matter stabilization.

Type of Medium: Electronic Resource

URL: http://dx.doi.org/10.1007/BF00017102

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Global Carbon Budget 2018 (2018)

Le Quéré, Corinne ; Andrew, Robbie M. ; Friedlingstein, Pierre ; [et al.]

Copernicus Publications (EGU)

In: Earth System Science Data, 10 (4). pp. 2141-2194.

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Publication Date: 2021-02-08

Description: Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere – the “global carbon budget” – 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 methodology to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions (EFF) are based on energy statistics and cement production data, while emissions from land use and land-use change (ELUC), mainly deforestation, are based on land use and land-use change data and bookkeeping models. Atmospheric CO2 concentration is measured directly and its growth rate (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) and terrestrial CO2 sink (SLAND) are estimated with global process models constrained by observations. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the last decade available (2008–2017), EFF was 9.4±0.5 GtC yr−1, ELUC 1.5±0.7 GtC yr−1, GATM 4.7±0.02 GtC yr−1, SOCEAN 2.4±0.5 GtC yr−1, and SLAND 3.2±0.8 GtC yr−1, with a budget imbalance BIM of 0.5 GtC yr−1 indicating overestimated emissions and/or underestimated sinks. For the year 2017 alone, the growth in EFF was about 1.6 % and emissions increased to 9.9±0.5 GtC yr−1. Also for 2017, ELUC was 1.4±0.7 GtC yr−1, GATM was 4.6±0.2 GtC yr−1, SOCEAN was 2.5±0.5 GtC yr−1, and SLAND was 3.8±0.8 GtC yr−1, with a BIM of 0.3 GtC. The global atmospheric CO2 concentration reached 405.0±0.1 ppm averaged over 2017. For 2018, preliminary data for the first 6–9 months indicate a renewed growth in EFF of +2.7 % (range of 1.8 % to 3.7 %) based on national emission projections for China, the US, the EU, and India and projections of gross domestic product corrected for recent changes in the carbon intensity of the economy for the rest of the world. The analysis presented here shows that the mean and trend in the five components of the global carbon budget are consistently estimated over the period of 1959–2017, but discrepancies of up to 1 GtC yr−1 persist for the representation of semi-decadal variability in CO2 fluxes. A detailed comparison among individual estimates and the introduction of a broad range of observations show (1) no consensus in the mean and trend in land-use change emissions, (2) a persistent low agreement among the different methods on the magnitude of the land CO2 flux in the northern extra-tropics, and (3) an apparent underestimation of the CO2 variability by ocean models, originating outside the tropics. This living data update documents changes in the methods and data sets used in this new global carbon budget and the progress in understanding the global carbon cycle compared with previous publications of this data set (Le Quéré et al., 2018, 2016, 2015a, b, 2014, 2013)

Type: Article , PeerReviewed

Format: text

DOI: 10.5194/essd-10-2141-2018

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Global Carbon Budget 2017 (2018)

Le Quéré, Corinne ; Andrew, Robbie M. ; Friedlingstein, Pierre ; [et al.]

Copernicus Publications (EGU)

In: Earth System Science Data, 10 (1). pp. 405-448.

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Publication Date: 2021-02-08

Description: Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere – the "global carbon budget" – 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 methodology to quantify the five major components of the global carbon budget and their uncertainties. CO2 emissions from fossil fuels and industry (EFF) are based on energy statistics and cement production data, respectively, while emissions from land-use change (ELUC), mainly deforestation, are based on land-cover change data and bookkeeping models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) and terrestrial CO2 sink (SLAND) are estimated with global process models constrained by observations. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the last decade available (2007–2016), EFF was 9.4 ± 0.5 GtC yr−1, ELUC 1.3 ± 0.7 GtC yr−1, GATM 4.7 ± 0.1 GtC yr−1, SOCEAN 2.4 ± 0.5 GtC yr−1, and SLAND 3.0 ± 0.8 GtC yr−1, with a budget imbalance BIM of 0.6 GtC yr−1 indicating overestimated emissions and/or underestimated sinks. For year 2016 alone, the growth in EFF was approximately zero and emissions remained at 9.9 ± 0.5 GtC yr−1. Also for 2016, ELUC was 1.3 ± 0.7 GtC yr−1, GATM was 6.1 ± 0.2 GtC yr−1, SOCEAN was 2.6 ± 0.5 GtC yr−1, and SLAND was 2.7 ± 1.0 GtC yr−1, with a small BIM of −0.3 GtC. GATM continued to be higher in 2016 compared to the past decade (2007–2016), reflecting in part the high fossil emissions and the small SLAND consistent with El Niño conditions. The global atmospheric CO2 concentration reached 402.8 ± 0.1 ppm averaged over 2016. For 2017, preliminary data for the first 6–9 months indicate a renewed growth in EFF of +2.0 % (range of 0.8 to 3.0 %) based on national emissions projections for China, USA, and India, and projections of gross domestic product (GDP) corrected for recent changes in the carbon intensity of the economy for the rest of the world. This living data update documents changes in the methods and data sets used in this new global carbon budget compared with previous publications of this data set (Le Quéré et al., 2016, 2015b, a, 2014, 2013). All results presented here can be downloaded from https://doi.org/10.18160/GCP-2017 (GCP, 2017).

Type: Article , PeerReviewed

Format: text

DOI: 10.5194/essd-10-405-2018

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Global Carbon Budget 2016 (2016)

Le Quéré, Corinne ; Andrew, Robbie M. ; Canadell, Josep G. ; [et al.]

Copernicus Publications (EGU)

In: Earth System Science Data, 8 (2). pp. 605-649.

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Publication Date: 2019-09-23

Description: Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere – the “global carbon budget” – 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 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 and 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, 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. 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 (2006–2015), EFF was 9.3 ± 0.5 GtC yr−1, ELUC 1.0 ± 0.5 GtC yr−1, GATM 4.5 ± 0.1 GtC yr−1, SOCEAN 2.6 ± 0.5 GtC yr−1, and SLAND 3.1 ± 0.9 GtC yr−1. For year 2015 alone, the growth in EFF was approximately zero and emissions remained at 9.9 ± 0.5 GtC yr−1, showing a slowdown in growth of these emissions compared to the average growth of 1.8 % yr−1 that took place during 2006–2015. Also, for 2015, ELUC was 1.3 ± 0.5 GtC yr−1, GATM was 6.3 ± 0.2 GtC yr−1, SOCEAN was 3.0 ± 0.5 GtC yr−1, and SLAND was 1.9 ± 0.9 GtC yr−1. GATM was higher in 2015 compared to the past decade (2006–2015), reflecting a smaller SLAND for that year. The global atmospheric CO2 concentration reached 399.4 ± 0.1 ppm averaged over 2015. For 2016, preliminary data indicate the continuation of low growth in EFF with +0.2 % (range of −1.0 to +1.8 %) based on national emissions projections for China and USA, and projections of gross domestic product corrected for recent changes in the carbon intensity of the economy for the rest of the world. In spite of the low growth of EFF in 2016, the growth rate in atmospheric CO2 concentration is expected to be relatively high because of the persistence of the smaller residual terrestrial sink (SLAND) in response to El Niño conditions of 2015–2016. From this projection of EFF and assumed constant ELUC for 2016, cumulative emissions of CO2 will reach 565 ± 55 GtC (2075 ± 205 GtCO2) for 1870–2016, about 75 % from EFF and 25 % from ELUC. This living data update documents changes in the methods and data sets used in this new carbon budget compared with previous publications of this data set (Le Quéré et al., 2015b, a, 2014, 2013). All observations presented here can be downloaded from the Carbon Dioxide Information Analysis Center (doi:10.3334/CDIAC/GCP_2016).

Type: Article , PeerReviewed

Format: text

DOI: 10.5194/essd-8-605-2016

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Gas hydrates: entrance to a methane age or climate threat? (2009)

Krey, Volker ; Canadell, Josep G ; Nakicenovic, Nebojsa ; [et al.]

IOP Publishing

In: Environmental Research Letters, 4 (3). 034007.

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Publication Date: 2015-11-18

Description: Methane hydrates, ice-like compounds in which methane is held in crystalline cages formed by water molecules, are widespread in areas of permafrost such as the Arctic and in sediments on the continental margins. They are a potentially vast fossil fuel energy source but, at the same time, could be destabilized by changing pressure–temperature conditions due to climate change, potentially leading to strong positive carbon–climate feedbacks. To enhance our understanding of both the vulnerability of and the opportunity pr ovided by methane hydrates, it is necessary (i) to conduct basic research that improves the highly uncertain estimates of hydrate occurrences and their response to changing environmental conditions, and (ii) to integrate the agendas of energy security and climate change which can provide an opportunity for methane hydrates—in particular if combined with carbon capture and storage—to be used as a ‘bridge fuel’ between carbon-intensive fossil energies and zero-emission energies. Taken one step further, exploitation of dissociating methane hydrates could even mitigate against escape of methane to the atmosphere. Despite these opportunities, so far, methane hydrates have been largely absent from energy and climate discussions, including global hydrocarbon assessments and the Fourth Assessment Report of the Intergovernmental Panel on Climate Change.

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Format: text

DOI: 10.1088/1748-9326/4/3/034007

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Variability and quasi-decadal changes in the methane budget over the period 2000–2012 (2017)

Saunois, Marielle ; Bousquet, Philippe ; Poulter, Ben ; [et al.]

Copernicus Publications (EGU)

In: Atmospheric Chemistry and Physics, 17 (18). pp. 11135-11161.

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Publication Date: 2021-12-15

Description: Following the recent Global Carbon Project (GCP) synthesis of the decadal methane (CH4) budget over 2000–2012 (Saunois et al., 2016), we analyse here the same dataset with a focus on quasi-decadal and inter-annual variability in CH4 emissions. The GCP dataset integrates results from top-down studies (exploiting atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up models (including process-based models for estimating land surface emissions and atmospheric chemistry), inventories of anthropogenic emissions, and data-driven approaches. The annual global methane emissions from top-down studies, which by construction match the observed methane growth rate within their uncertainties, all show an increase in total methane emissions over the period 2000–2012, but this increase is not linear over the 13 years. Despite differences between individual studies, the mean emission anomaly of the top-down ensemble shows no significant trend in total methane emissions over the period 2000–2006, during the plateau of atmospheric methane mole fractions, and also over the period 2008–2012, during the renewed atmospheric methane increase. However, the top-down ensemble mean produces an emission shift between 2006 and 2008, leading to 22 [16–32] Tg CH4 yr−1 higher methane emissions over the period 2008–2012 compared to 2002–2006. This emission increase mostly originated from the tropics, with a smaller contribution from mid-latitudes and no significant change from boreal regions. The regional contributions remain uncertain in top-down studies. Tropical South America and South and East Asia seem to contribute the most to the emission increase in the tropics. However, these two regions have only limited atmospheric measurements and remain therefore poorly constrained. The sectorial partitioning of this emission increase between the periods 2002–2006 and 2008–2012 differs from one atmospheric inversion study to another. However, all top-down studies suggest smaller changes in fossil fuel emissions (from oil, gas, and coal industries) compared to the mean of the bottom-up inventories included in this study. This difference is partly driven by a smaller emission change in China from the top-down studies compared to the estimate in the Emission Database for Global Atmospheric Research (EDGARv4.2) inventory, which should be revised to smaller values in a near future. We apply isotopic signatures to the emission changes estimated for individual studies based on five emission sectors and find that for six individual top-down studies (out of eight) the average isotopic signature of the emission changes is not consistent with the observed change in atmospheric 13CH4. However, the partitioning in emission change derived from the ensemble mean is consistent with this isotopic constraint. At the global scale, the top-down ensemble mean suggests that the dominant contribution to the resumed atmospheric CH4 growth after 2006 comes from microbial sources (more from agriculture and waste sectors than from natural wetlands), with an uncertain but smaller contribution from fossil CH4 emissions. In addition, a decrease in biomass burning emissions (in agreement with the biomass burning emission databases) makes the balance of sources consistent with atmospheric 13CH4 observations. In most of the top-down studies included here, OH concentrations are considered constant over the years (seasonal variations but without any inter-annual variability). As a result, the methane loss (in particular through OH oxidation) varies mainly through the change in methane concentrations and not its oxidants. For these reasons, changes in the methane loss could not be properly investigated in this study, although it may play a significant role in the recent atmospheric methane changes as briefly discussed at the end of the paper.

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DOI: 10.5194/acp-17-11135-2017

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The global methane budget 2000–2012 (2016)

Saunois, Marielle ; Bousquet, Philippe ; Poulter, Ben ; [et al.]

Copernicus Publications (EGU)

In: Earth System Science Data, 8 (2). pp. 697-751.

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Publication Date: 2021-12-15

Description: The global methane (CH4) budget is becoming an increasingly important component for managing realistic pathways to mitigate climate change. This relevance, due to a shorter atmospheric lifetime and a stronger warming potential than carbon dioxide, is challenged by the still unexplained changes of atmospheric CH4 over the past decade. Emissions and concentrations of CH4 are continuing to increase, making CH4 the second most important human-induced greenhouse gas after carbon dioxide. Two major difficulties in reducing uncertainties come from the large variety of diffusive CH4 sources that overlap geographically, and from the destruction of CH4 by the very short-lived hydroxyl radical (OH). To address these difficulties, we have established a consortium of multi-disciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate research on the methane cycle, and producing regular (∼ biennial) updates of the global methane budget. This consortium includes atmospheric physicists and chemists, biogeochemists of surface and marine emissions, and socio-economists who study anthropogenic emissions. Following Kirschke et al. (2013), we propose here the first version of a living review paper that integrates results of top-down studies (exploiting atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up models, inventories and data-driven approaches (including process-based models for estimating land surface emissions and atmospheric chemistry, and inventories for anthropogenic emissions, data-driven extrapolations). For the 2003–2012 decade, global methane emissions are estimated by top-down inversions at 558 Tg CH4 yr−1, range 540–568. About 60 % of global emissions are anthropogenic (range 50–65 %). Since 2010, the bottom-up global emission inventories have been closer to methane emissions in the most carbon-intensive Representative Concentrations Pathway (RCP8.5) and higher than all other RCP scenarios. Bottom-up approaches suggest larger global emissions (736 Tg CH4 yr−1, range 596–884) mostly because of larger natural emissions from individual sources such as inland waters, natural wetlands and geological sources. Considering the atmospheric constraints on the top-down budget, it is likely that some of the individual emissions reported by the bottom-up approaches are overestimated, leading to too large global emissions. Latitudinal data from top-down emissions indicate a predominance of tropical emissions (∼ 64 % of the global budget, 〈 30° N) as compared to mid (∼ 32 %, 30–60° N) and high northern latitudes (∼ 4 %, 60–90° N). Top-down inversions consistently infer lower emissions in China (∼ 58 Tg CH4 yr−1, range 51–72, −14 %) and higher emissions in Africa (86 Tg CH4 yr−1, range 73–108, +19 %) than bottom-up values used as prior estimates. Overall, uncertainties for anthropogenic emissions appear smaller than those from natural sources, and the uncertainties on source categories appear larger for top-down inversions than for bottom-up inventories and models. The most important source of uncertainty on the methane budget is attributable to emissions from wetland and other inland waters. We show that the wetland extent could contribute 30–40 % on the estimated range for wetland emissions. Other priorities for improving the methane budget include the following: (i) the development of process-based models for inland-water emissions, (ii) the intensification of methane observations at local scale (flux measurements) to constrain bottom-up land surface models, and at regional scale (surface networks and satellites) to constrain top-down inversions, (iii) improvements in the estimation of atmospheric loss by OH, and (iv) improvements of the transport models integrated in top-down inversions. The data presented here can be downloaded from the Carbon Dioxide Information Analysis Center (http://doi.org/10.3334/CDIAC/GLOBAL_METHANE_BUDGET_2016_V1.1) and the Global Carbon Project.

Type: Article , PeerReviewed

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DOI: 10.5194/essd-8-697-2016

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