Author
Michelle Garneau
Other affiliations: Université du Québec, McGill University, Institut national de la recherche scientifique ...read more
Bio: Michelle Garneau is an academic researcher from Université du Québec à Montréal. The author has contributed to research in topics: Peat & Boreal. The author has an hindex of 33, co-authored 114 publications receiving 3365 citations. Previous affiliations of Michelle Garneau include Université du Québec & McGill University.
Topics: Peat, Boreal, Holocene, Ombrotrophic, Testate amoebae
Papers published on a yearly basis
Papers
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Lehigh University1, University of Hawaii at Manoa2, Bowdoin College3, University of Eastern Finland4, University of Exeter5, Eton College6, Stockholm University7, University of Southampton8, Queen Mary University of London9, University of Wisconsin–La Crosse10, University of Gloucestershire11, University of Toulouse12, Adam Mickiewicz University in Poznań13, University of Toronto14, Université du Québec à Montréal15, Lund University16, University of California, Los Angeles17, United States Geological Survey18, University of Copenhagen19, University of Helsinki20, University of Nottingham21, Laval University22, Geological Survey of Finland23, University of Aberdeen24, McGill University25, Columbia University26, Université de Montréal27, Champlain College28, Agriculture and Agri-Food Canada29, University of Guelph30, University of Amsterdam31, Southern Illinois University Carbondale32, Chinese Academy of Sciences33
TL;DR: In this paper, the authors present results from the most comprehensive compilation of Holocene peat soil properties with associated carbon and nitrogen accumulation rates for northern peatlands, which consists of 268 peat cores from 215 sites located north of 45°N.
Abstract: Here, we present results from the most comprehensive compilation of Holocene peat soil properties with associated carbon and nitrogen accumulation rates for northern peatlands. Our database consists of 268 peat cores from 215 sites located north of 45°N. It encompasses regions within which peat carbon data have only recently become available, such as the West Siberia Lowlands, the Hudson Bay Lowlands, Kamchatka in Far East Russia, and the Tibetan Plateau. For all northern peatlands, carbon content in organic matter was estimated at 42 ± 3% (standard deviation) for Sphagnum peat, 51 ± 2% for non-Sphagnum peat, and at 49 ± 2% overall. Dry bulk density averaged 0.12 ± 0.07 g/cm3, organic matter bulk density averaged 0.11 ± 0.05 g/cm3, and total carbon content in peat averaged 47 ± 6%. In general, large differences were found between Sphagnum and non-Sphagnum peat types in terms of peat properties. Time-weighted peat carbon accumulation rates averaged 23 ± 2 (standard error of mean) g C/m2/yr during the Holocene on the basis of 151 peat cores from 127 sites, with the highest rates of carbon accumulation (25-28 g C/m2/yr) recorded during the early Holocene when the climate was
404 citations
University of Exeter1, Queen's University Belfast2, Lehigh University3, University of Utah4, University of Gloucestershire5, Centro de Investigación en Matemáticas6, University of Bristol7, Lund University8, Macquarie University9, University of Southampton10, University of Wyoming11, University of Helsinki12, University of Aberdeen13, Trinity College, Dublin14, Imperial College London15, University of Toulouse16, University of Eastern Finland17, Memorial University of Newfoundland18, Université du Québec à Montréal19, Brown University20, University of Tartu21, Forschungszentrum Jülich22, Goddard Institute for Space Studies23, Finnish Forest Research Institute24, University of California, Los Angeles25, Wadia Institute of Himalayan Geology26, Heidelberg University27, Tallinn University28, University of Leeds29, Southern Illinois University Carbondale30, Chinese Academy of Sciences31
TL;DR: In this paper, the authors used a new extensive database of peat profiles across northern high latitudes to examine spatial and temporal patterns of carbon accumulation over the past millennium and found that the carbon accumulation rate in northern peatlands is linearly related to contemporary growing season length and photosynthetically active radiation, suggesting that variability in net primary productivity is more important than decomposition in determining longterm carbon accumulation.
Abstract: Peatlands are a major terrestrial carbon store and a persistent natural carbon sink during the Holocene, but there is considerable uncertainty over the fate of peatland carbon in a changing climate. It is generally assumed that higher temperatures will increase peat decay, causing a positive feedback to climate warming and contributing to the global positive carbon cycle feedback. Here we use a new extensive database of peat profiles across northern high latitudes to examine spatial and temporal patterns of carbon accumulation over the past millennium. Opposite to expectations, our results indicate a small negative carbon cycle feedback from past changes in the long-term accumulation rates of northern peatlands. Total carbon accumulated over the last 1000 yr is linearly related to contemporary growing season length and photosynthetically active radiation, suggesting that variability in net primary productivity is more important than decomposition in determining long-term carbon accumulation. Furthermore, northern peatland carbon sequestration rate declined over the climate transition from the Medieval Climate Anomaly (MCA) to the Little Ice Age (LIA), probably because of lower LIA temperatures combined with increased cloudiness suppressing net primary productivity. Other factors including changing moisture status, peatland distribution, fire, nitrogen deposition, permafrost thaw and methane emissions will also influence future peatland carbon cycle feedbacks, but our data suggest that the carbon sequestration rate could increase over many areas of northern peatlands in a warmer future.
292 citations
University of Exeter1, University of Utah2, University of Leicester3, Imperial College London4, University of Hawaii at Manoa5, Lund University6, Russian Academy of Sciences7, Lehigh University8, University of Wisconsin–La Crosse9, Bowdoin College10, Uppsala University11, University of York12, University of Toulouse13, Adam Mickiewicz University in Poznań14, University of Toronto15, Université du Québec à Montréal16, University of California, Los Angeles17, University of Southampton18, Met Office19, United States Geological Survey20, University of Tartu21, University of Alaska Anchorage22, University of Helsinki23, University of Victoria24, University of Nottingham25, Laval University26, Texas A&M University27, Newcastle University28, Geological Survey of Finland29, Oeschger Centre for Climate Change Research30, University of Santiago de Compostela31, University of Aberdeen32, Trinity College, Dublin33, University of Queensland34, Lamont–Doherty Earth Observatory35, University of Lapland36, Norwegian Polar Institute37, Ontario Ministry of Natural Resources38, Champlain College39, Stockholm University40, University of Leeds41, Forestry Commission42, University of Amsterdam43, Chinese Academy of Sciences44, Northeast Normal University45
TL;DR: This article examined the global relationship between peatland carbon accumulation rates during the last millennium and planetary-scale climate space and found a positive relationship between carbon accumulation and cumulative photosynthetically active radiation during the growing season for mid-to high-latitude peatlands in both hemispheres.
Abstract: The carbon sink potential of peatlands depends on the balance of carbon uptake by plants and microbial decomposition The rates of both these processes will increase with warming but it remains unclear which will dominate the global peatland response Here we examine the global relationship between peatland carbon accumulation rates during the last millennium and planetary-scale climate space A positive relationship is found between carbon accumulation and cumulative photosynthetically active radiation during the growing season for mid- to high-latitude peatlands in both hemispheres However, this relationship reverses at lower latitudes, suggesting that carbon accumulation is lower under the warmest climate regimes Projections under Representative Concentration Pathway (RCP)26 and RCP85 scenarios indicate that the present-day global sink will increase slightly until around ad 2100 but decline thereafter Peatlands will remain a carbon sink in the future, but their response to warming switches from a negative to a positive climate feedback (decreased carbon sink with warming) at the end of the twenty-first century
176 citations
TL;DR: In this article, a lack in representation of biosphere-atmosphere interactions in current climate models is addressed by introducing vegetation dynamics in surface transfer schemes or couple globa-graphs.
Abstract: There is a lack in representation of biosphere–atmosphere interactions in current climate models. To fill this gap, one may introduce vegetation dynamics in surface transfer schemes or couple globa...
155 citations
Texas A&M University1, University of Exeter2, University of Helsinki3, Université du Québec à Montréal4, Tanjungpura University5, University of Hawaii at Manoa6, University of Bristol7, Bowdoin College8, Chulalongkorn University9, University of California, Los Angeles10, Max Planck Society11, University of Nottingham12, University of Magallanes13, Oeschger Centre for Climate Change Research14, Université de Montréal15, Lehigh University16, Northeast Normal University17, Mount Holyoke College18, McGill University19, Stockholm University20, University of Leicester21, Katholieke Universiteit Leuven22, University of St Andrews23, Florida State University24, Aarhus University25, University of Toronto26, University of New Hampshire27, University of Łódź28, Centre national de la recherche scientifique29, Cranfield University30, University of Alberta31, Stockholm Environment Institute32, Lawrence Berkeley National Laboratory33, United States Geological Survey34, Texas A&M University at Galveston35, University of Victoria36, Adam Mickiewicz University in Poznań37, Finnish Meteorological Institute38, Royal Holloway, University of London39, University of Queensland40, Lamont–Doherty Earth Observatory41, National Park Service42, University of York43, Hope College44, University of Reading45, Uva Wellassa University46, Queen's University Belfast47, University of California, Berkeley48, Memorial University of Newfoundland49
TL;DR: In this article, the authors define and quantify the leading drivers of change that have impacted peatland carbon stocks during the Holocene and predict their effect during this century and in the far future.
Abstract: The carbon balance of peatlands is predicted to shift from a sink to a source this century. However, peatland ecosystems are still omitted from the main Earth system models that are used for future climate change projections, and they are not considered in integrated assessment models that are used in impact and mitigation studies. By using evidence synthesized from the literature and an expert elicitation, we define and quantify the leading drivers of change that have impacted peatland carbon stocks during the Holocene and predict their effect during this century and in the far future. We also identify uncertainties and knowledge gaps in the scientific community and provide insight towards better integration of peatlands into modelling frameworks. Given the importance of the contribution by peatlands to the global carbon cycle, this study shows that peatland science is a critical research area and that we still have a long way to go to fully understand the peatland–carbon–climate nexus. Peatlands are impacted by climate and land-use changes, with feedback to warming by acting as either sources or sinks of carbon. Expert elicitation combined with literature review reveals key drivers of change that alter peatland carbon dynamics, with implications for improving models.
141 citations
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Uppsala University1, Iowa State University2, University of Minnesota3, University of Siena4, United States Geological Survey5, Trent University6, University of Regina7, University of North Carolina at Chapel Hill8, Miami University9, Finnish Environment Institute10, Marine Institute of Memorial University of Newfoundland11, University of Oslo12, Université du Québec13, Virginia Commonwealth University14, University of Colorado Boulder15, University of California, Santa Barbara16, University of the Sciences17, Université du Québec à Montréal18, Universidade Federal de Juiz de Fora19, Commonwealth Scientific and Industrial Research Organisation20, University of Alberta21, ETH Zurich22, Hydro-Québec23
TL;DR: The role of lakes in carbon cycling and global climate, examine the mechanisms influencing carbon pools and transformations in lakes, and discuss how the metabolism of carbon in the inland waters is likely to change in response to climate.
Abstract: We explore the role of lakes in carbon cycling and global climate, examine the mechanisms influencing carbon pools and transformations in lakes, and discuss how the metabolism of carbon in the inland waters is likely to change in response to climate. Furthermore, we project changes as global climate change in the abundance and spatial distribution of lakes in the biosphere, and we revise the estimate for the global extent of carbon transformation in inland waters. This synthesis demonstrates that the global annual emissions of carbon dioxide from inland waters to the atmosphere are similar in magnitude to the carbon dioxide uptake by the oceans and that the global burial of organic carbon in inland water sediments exceeds organic carbon sequestration on the ocean floor. The role of inland waters in global carbon cycling and climate forcing may be changed by human activities, including construction of impoundments, which accumulate large amounts of carbon in sediments and emit large amounts of methane to the atmosphere. Methane emissions are also expected from lakes on melting permafrost. The synthesis presented here indicates that (1) inland waters constitute a significant component of the global carbon cycle, (2) their contribution to this cycle has significantly changed as a result of human activities, and (3) they will continue to change in response to future climate change causing decreased as well as increased abundance of lakes as well as increases in the number of aquatic impoundments.
2,140 citations
TL;DR: It is recommended that block cross-validation be used wherever dependence structures exist in a dataset, even if no correlation structure is visible in the fitted model residuals, or if the fitted models account for such correlations.
Abstract: Ecological data often show temporal, spatial, hierarchical (random effects), or phylogenetic structure. Modern statistical approaches are increasingly accounting for such dependencies. However, when performing cross-validation, these structures are regularly ignored, resulting in serious underestimation of predictive error. One cause for the poor performance of uncorrected (random) cross-validation, noted often by modellers, are dependence structures in the data that persist as dependence structures in model residuals, violating the assumption of independence. Even more concerning, because often overlooked, is that structured data also provides ample opportunity for overfitting with non-causal predictors. This problem can persist even if remedies such as autoregressive models, generalized least squares, or mixed models are used. Block cross-validation, where data are split strategically rather than randomly, can address these issues. However, the blocking strategy must be carefully considered. Blocking in space, time, random effects or phylogenetic distance, while accounting for dependencies in the data, may also unwittingly induce extrapolations by restricting the ranges or combinations of predictor variables available for model training, thus overestimating interpolation errors. On the other hand, deliberate blocking in predictor space may also improve error estimates when extrapolation is the modelling goal. Here, we review the ecological literature on non-random and blocked cross-validation approaches. We also provide a series of simulations and case studies, in which we show that, for all instances tested, block cross-validation is nearly universally more appropriate than random cross-validation if the goal is predicting to new data or predictor space, or for selecting causal predictors. We recommend that block cross-validation be used wherever dependence structures exist in a dataset, even if no correlation structure is visible in the fitted model residuals, or if the fitted models account for such correlations.
998 citations
Northern Arizona University1, United States Geological Survey2, Loughborough University3, University of Washington4, University of Colorado Boulder5, University of Oregon6, University of New Brunswick7, Bates College8, Geological Survey of Canada9, Norwegian University of Science and Technology10, University of Cincinnati11, University of Ottawa12, University of Iceland13, University of Illinois at Urbana–Champaign14, University of Edinburgh15, University of Denver16, University of California, Los Angeles17, University of South Carolina18, National Center for Atmospheric Research19, California State University, Long Beach20, Queen's University21, Wilfrid Laurier University22
TL;DR: In this paper, a spatio-temporal pattern of peak Holocene warmth (Holocene thermal maximum, HTM) is traced over 140 sites across the Western Hemisphere of the Arctic (0−180°W; north of ∼60°N).
838 citations
01 Mar 1979
TL;DR: In this article, the authors developed the theory behind Krishnaiah and Schuurmann's theoretical work reported in their report Approximations to the Distributions of the Traces of Complex Multivariate Beta and F Matrices.
Abstract: : One use of spectral analysis of time series is to determine if two different time series are realizations from the same process This thesis develops the theory behind Krishnaiah and Schuurmann's theoretical work reported in their report Approximations to the Distributions of the Traces of Complex Multivariate Beta and F Matrices We take the trace of a test statistic calculated from the spectral density matrices of the time series and test it The thesis applies the theory to two small sample simulations (Author)
683 citations
TL;DR: A review of peat carbon stock estimates can be found in this article, where the best estimate of C stocks and uncertainty is 500 ± 100 gigatons of C (Gt C) in northern peatlands.
Abstract: . Peatlands contain a large belowground carbon (C) stock in the biosphere, and their dynamics have important implications for the global carbon cycle. However, there are still large uncertainties in C stock estimates and poor understanding of C dynamics across timescales. Here I review different approaches and associated uncertainties of C stock estimates in the literature, and on the basis of the literature review my best estimate of C stocks and uncertainty is 500 ± 100 (approximate range) gigatons of C (Gt C) in northern peatlands. The greatest source of uncertainty for all the approaches is the lack or insufficient representation of data, including depth, bulk density and carbon accumulation data, especially from the world's large peatlands. Several ways to improve estimates of peat carbon stocks are also discussed in this paper, including the estimates of C stocks by regions and further utilizations of widely available basal peat ages. Changes in peatland carbon stocks over time, estimated using Sphagnum (peat moss) spore data and down-core peat accumulation records, show different patterns during the Holocene, and I argue that spore-based approach underestimates the abundance of peatlands in their early histories. Considering long-term peat decomposition using peat accumulation data allows estimates of net carbon sequestration rates by peatlands, or net (ecosystem) carbon balance (NECB), which indicates more than half of peat carbon (> 270 Gt C) was sequestrated before 7000 yr ago during the Holocene. Contemporary carbon flux studies at 5 peatland sites show much larger NECB during the last decade (32 ± 7.8 (S.E.) g C m−2 yr–1) than during the last 7000 yr (∼ 11 g C m−2 yr–1), as modeled from peat records across northern peatlands. This discrepancy highlights the urgent need for carbon accumulation data and process understanding, especially at decadal and centennial timescales, that would bridge current knowledge gaps and facilitate comparisons of NECB across all timescales.
529 citations