Extreme events in gross primary production: a characterization across continents

Climate extremes can affect the functioning of ter- restrial ecosystems, for instance via a reduction of the photo- synthetic capacity or alterations of respiratory processes. Yet the dominant regional and seasonal effects of hydrometeoro- logical extremes are still not well documented and in the fo- cus of this paper. Specifically, we quantify and characterize the role of large spatiotemporal extreme events in gross pri- mary production (GPP) as triggers of continental anomalies. We also investigate seasonal dynamics of extreme impacts on continental GPP anomalies. We find that the 50 largest pos- itive extremes (i.e., statistically unusual increases in carbon uptake rates) and negative extremes (i.e., statistically unusual decreases in carbon uptake rates) on each continent can ex- plain most of the continental variation in GPP, which is in line with previous results obtained at the global scale. We show that negative extremes are larger than positive ones and demonstrate that this asymmetry is particularly strong in South America and Europe. Our analysis indicates that the overall impacts and the spatial extents of GPP extremes are power-law distributed with exponents that vary little across continents. Moreover, we show that on all continents and for all data sets the spatial extents play a more important role for the overall impact of GPP extremes compared to the dura- tions or maximal GPP. An analysis of possible causes across continents indicates that most negative extremes in GPP can be attributed clearly to water scarcity, whereas extreme tem- peratures play a secondary role. However, for Europe, South America and Oceania we also identify fire as an important driver. Our findings are consistent with remote sensing prod- ucts. An independent validation against a literature survey on specific extreme events supports our results to a large extent.

[1]  S. Seneviratne,et al.  Climate extremes and the carbon cycle , 2013, Nature.

[2]  Sassan Saatchi,et al.  Widespread Amazon forest tree mortality from a single cross‐basin squall line event , 2010 .

[3]  W. Pockman,et al.  Precipitation pulses and carbon fluxes in semiarid and arid ecosystems , 2004, Oecologia.

[4]  J. Touboul,et al.  Can Power-Law Scaling and Neuronal Avalanches Arise from Stochastic Dynamics? , 2009, PloS one.

[5]  P. Fearnside,et al.  Testing for criticality in ecosystem dynamics: the case of Amazonian rainforest and savanna fire. , 2010, Ecology letters.

[6]  N. Breda,et al.  Temperate forest trees and stands under severe drought: a review of ecophysiological responses, adaptation processes and long-term consequences , 2006 .

[7]  Guillaume Ramillien,et al.  Basin‐scale, integrated observations of the early 21st century multiyear drought in southeast Australia , 2009 .

[8]  J. Thepaut,et al.  The ERA‐Interim reanalysis: configuration and performance of the data assimilation system , 2011 .

[9]  Wolfgang Cramer,et al.  A simulation model for the transient effects of climate change on forest landscapes , 1993 .

[10]  M. Lomas,et al.  Evaluation of terrestrial carbon cycle models for their response to climate variability and to CO2 trends , 2013, Global change biology.

[11]  Maczarashvili Merabi Spring and Summer , 1998 .

[12]  Samuel S. P. Shen,et al.  Human amplification of drought-induced biomass burning in Indonesia since 1960 , 2009 .

[13]  N. Kiang,et al.  Land Surface Model Development for the GISS GCM: Effects of Improved Canopy Physiology on Simulated Climate , 2005 .

[14]  W. Kurz,et al.  Mountain pine beetle and forest carbon feedback to climate change , 2008, Nature.

[15]  Christian Körner,et al.  Slow in, Rapid out--Carbon Flux Studies and Kyoto Targets , 2003, Science.

[16]  T. Vesala,et al.  Reduction of ecosystem productivity and respiration during the European summer 2003 climate anomaly: a joint flux tower, remote sensing and modelling analysis , 2007 .

[17]  S. Seneviratne,et al.  Hot days induced by precipitation deficits at the global scale , 2012, Proceedings of the National Academy of Sciences.

[18]  Ronggao Liu,et al.  Retrospective retrieval of long-term consistent global leaf area index (1981-2011) from combined AVHRR and MODIS data , 2012 .

[19]  S. Page,et al.  The amount of carbon released from peat and forest fires in Indonesia during 1997 , 2002, Nature.

[20]  Dirceu Luis Herdies,et al.  On the severe drought of 1993 in North-East Brazil , 1995 .

[21]  C. Beierkuhnlein,et al.  Research frontiers in climate change: Effects of extreme meteorological events on ecosystems , 2008 .

[22]  I. C. Prentice,et al.  A dynamic global vegetation model for studies of the coupled atmosphere‐biosphere system , 2005 .

[23]  Sandy P. Harrison,et al.  The influence of vegetation, fire spread and fire behaviour on biomass burning and trace gas emissions: results from a process-based model , 2010 .

[24]  Vladimir Kossobokov,et al.  Extreme events: dynamics, statistics and prediction , 2011 .

[25]  Mathieu Rouault,et al.  Intensity and spatial extension of drought in South Africa at different time scales , 2004 .

[26]  T. Stocker,et al.  Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation. A Special Report of Working Groups I and II of IPCC Intergovernmental Panel on Climate Change , 2012 .

[27]  Roberta E. Martin,et al.  Forest Canopy Gap Distributions in the Southern Peruvian Amazon , 2013, PloS one.

[28]  Robert E. Dickinson,et al.  Forest greenness after the massive 2008 Chinese ice storm: integrated effects of natural processes and human intervention , 2012 .

[29]  Bernhard Schölkopf,et al.  A few extreme events dominate global interannual variability in gross primary production , 2014 .

[30]  G. Asner,et al.  Convergent structural responses of tropical forests to diverse disturbance regimes. , 2009, Ecology letters.

[31]  P. Ciais,et al.  Europe-wide reduction in primary productivity caused by the heat and drought in 2003 , 2005, Nature.

[32]  Ricardo García-Herrera,et al.  The Hot Summer of 2010: Redrawing the Temperature Record Map of Europe , 2011, Science.

[33]  C. Korner Atmospheric science. Slow in, rapid out--carbon flux studies and Kyoto targets. , 2003, Science.

[34]  W. Oechel,et al.  FLUXNET: A New Tool to Study the Temporal and Spatial Variability of Ecosystem-Scale Carbon Dioxide, Water Vapor, and Energy Flux Densities , 2001 .

[35]  Fausto Guzzetti,et al.  Self-organization, the cascade model, and natural hazards , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[36]  R. Mishra,et al.  Self-Organization , 2021, Encyclopedic Dictionary of Archaeology.

[37]  H. Poincaré,et al.  Percolation ? , 1982 .

[38]  Nicolas Barbier,et al.  Remote sensing detection of droughts in Amazonian forest canopies. , 2010, The New phytologist.

[39]  W. Liu,et al.  Investigation of the 2006 drought and 2007 flood extremes at the Southern Great Plains through an integrative analysis of observations , 2010 .

[40]  J. Randerson,et al.  Assessing variability and long-term trends in burned area by merging multiple satellite fire products , 2009 .

[41]  Mark E. J. Newman,et al.  Power-Law Distributions in Empirical Data , 2007, SIAM Rev..

[42]  William F. Laurance,et al.  Does the disturbance hypothesis explain the biomass increase in basin‐wide Amazon forest plot data? , 2009 .

[43]  K. Ufnalski,et al.  Review of oak stand decline with special reference to the role of drought in Poland , 1998 .

[44]  R. Boone,et al.  Impacts of climate variability on East African pastoralists: linking social science and remote sensing , 2001 .

[45]  Mercedes Pascual,et al.  Criticality and disturbance in spatial ecological systems. , 2005, Trends in ecology & evolution.

[46]  J. Terborgh,et al.  Drought Sensitivity of the Amazon Rainforest , 2009, Science.

[47]  Andrew D. Friend,et al.  Carbon and nitrogen cycle dynamics in the O‐CN land surface model: 1. Model description, site‐scale evaluation, and sensitivity to parameter estimates , 2010 .

[48]  Markus Reichstein,et al.  Detection and attribution of large spatiotemporal extreme events in Earth observation data , 2013, Ecol. Informatics.

[49]  W. McGuire Managing the risks of extreme events and disasters , 2011 .

[50]  F. Woodward,et al.  Terrestrial Gross Carbon Dioxide Uptake: Global Distribution and Covariation with Climate , 2010, Science.

[51]  A. Waple,et al.  State of the Climate in 2002 , 2003 .

[52]  W. Vargas,et al.  Non-linear trends and low frequency oscillations in annual precipitation over Argentina and Chile, 1931-1999 , 2003 .

[53]  O. Phillips,et al.  The 2010 Amazon Drought , 2011, Science.

[54]  Fei-Fei Jin,et al.  Nonlinearity and Asymmetry of ENSO(. , 2004 .

[55]  L. Irland Ice storms and forest impacts. , 2000, The Science of the total environment.

[56]  M. Rietkerk,et al.  Spatial vegetation patterns and imminent desertification in Mediterranean arid ecosystems , 2007, Nature.

[57]  S. Running,et al.  Global Terrestrial Gross and Net Primary Productivity from the Earth Observing System , 2000 .

[58]  D. Sornette Critical Phenomena in Natural Sciences: Chaos, Fractals, Selforganization and Disorder: Concepts and Tools , 2000 .

[59]  J. Castilla,et al.  Scaling Population Density to Body Size in Rocky Intertidal Communities , 1990, Science.

[60]  D. Fischer,et al.  Atmospheric Science , 1973, Nature.

[61]  D. Easterling,et al.  Changes in climate extremes and their impacts on the natural physical environment , 2012 .

[62]  Melinda D. Smith An ecological perspective on extreme climatic events: a synthetic definition and framework to guide future research , 2011 .

[63]  Philippe Ciais,et al.  Terrestrial biosphere model performance for inter‐annual variability of land‐atmosphere CO2 exchange , 2012 .

[64]  M. England,et al.  What causes southeast Australia's worst droughts? , 2009 .

[65]  Ranga B. Myneni,et al.  Satellite‐based identification of linked vegetation index and sea surface temperature Anomaly areas from 1982–1990 for Africa, Australia and South America , 1996 .

[66]  E. Gumbel,et al.  Statistics of extremes , 1960 .

[67]  J. Lawton,et al.  Fractal dimension of vegetation and the distribution of arthropod body lengths , 1985, Nature.

[68]  Stefan Rahmstorf,et al.  A decade of weather extremes , 2012 .

[69]  Jerome Namias,et al.  Spring and Summer 1988 Drought over the Contiguous United States—Causes and Prediction , 1991 .

[70]  T. Swetnam,et al.  Warming and Earlier Spring Increase Western U.S. Forest Wildfire Activity , 2006, Science.

[71]  A. Huete,et al.  Overview of the radiometric and biophysical performance of the MODIS vegetation indices , 2002 .

[72]  F. Rembold,et al.  Assessing drought probability for agricultural areas in Africa with coarse resolution remote sensing imagery , 2011 .

[73]  Peter Nijkamp,et al.  Accessibility of Cities in the Digital Economy , 2004, cond-mat/0412004.

[74]  Maosheng Zhao,et al.  Drought-Induced Reduction in Global Terrestrial Net Primary Production from 2000 Through 2009 , 2010, Science.

[75]  Eric P. Smith,et al.  An Introduction to Statistical Modeling of Extreme Values , 2002, Technometrics.

[76]  I. Prentice,et al.  A general model for the light-use efficiency of primary production , 1996 .

[77]  R. Q. Thomas,et al.  Clustered disturbances lead to bias in large-scale estimates based on forest sample plots. , 2008, Ecology letters.

[78]  Srinivasa R. S. Varadhan,et al.  Asymptotic probabilities and differential equations , 1966 .

[79]  C. Müller,et al.  Modelling the role of agriculture for the 20th century global terrestrial carbon balance , 2007 .

[80]  Markus Reichstein,et al.  Benchmark products for land evapotranspiration: LandFlux-EVAL multi-data set synthesis , 2013 .

[81]  Christof Bigler,et al.  Drought induces lagged tree mortality in a subalpine forest in the Rocky Mountains , 2007 .

[82]  W. Lucht,et al.  Terrestrial vegetation and water balance-hydrological evaluation of a dynamic global vegetation model , 2004 .

[83]  Benjamin Lloyd-Hughes,et al.  A spatio‐temporal structure‐based approach to drought characterisation , 2012 .

[84]  Christopher von Nagy,et al.  Prolonged suppression of ecosystem carbon dioxide uptake after an anomalously warm year , 2008, Nature.

[85]  G. D. Jenerette,et al.  Dependence of carbon sequestration on the differential responses of ecosystem photosynthesis and respiration to rain pulses in a semiarid steppe , 2009 .

[86]  David B Baker,et al.  Impacts of tropical cyclones on U.S. forest tree mortality and carbon flux from 1851 to 2000 , 2009, Proceedings of the National Academy of Sciences.

[87]  A. Arneth,et al.  Global patterns of land-atmosphere fluxes of carbon dioxide, latent heat, and sensible heat derived from eddy covariance, satellite, and meteorological observations , 2011 .

[88]  Martin F. Lambert,et al.  A compound event framework for understanding extreme impacts , 2014 .

[89]  M. Newman Power laws, Pareto distributions and Zipf's law , 2005 .

[90]  S. Franz,et al.  Critical Phenomena in Natural Sciences: Chaos, Fractals, Selforganization and Disorder: Concepts and Tools , 2004 .

[91]  Maosheng Zhao,et al.  A Continuous Satellite-Derived Measure of Global Terrestrial Primary Production , 2004 .

[92]  I. C. Prentice,et al.  Evaluation of ecosystem dynamics, plant geography and terrestrial carbon cycling in the LPJ dynamic global vegetation model , 2003 .

[93]  J. Berry,et al.  A biochemical model of photosynthetic CO2 assimilation in leaves of C3 species , 1980, Planta.