Inclusion of ecologically based trait variation in plant functional types reduces the projected land carbon sink in an earth system model

Earth system models demonstrate large uncertainty in projected changes in terrestrial carbon budgets. The lack of inclusion of adaptive responses of vegetation communities to the environment has been suggested to hamper the ability of modeled vegetation to adequately respond to environmental change. In this study, variation in functional responses of vegetation has been added to an earth system model (ESM) based on ecological principles. The restriction of viable mean trait values of vegetation communities by the environment, called 'habitat filtering', is an important ecological assembly rule and allows for determination of global scale trait-environment relationships. These relationships were applied to model trait variation for different plant functional types (PFTs). For three leaf traits (specific leaf area, maximum carboxylation rate at 25 °C, and maximum electron transport rate at 25 °C), relationships with multiple environmental drivers, such as precipitation, temperature, radiation, and CO2 , were determined for the PFTs within the Max Planck Institute ESM. With these relationships, spatiotemporal variation in these formerly fixed traits in PFTs was modeled in global change projections (IPCC RCP8.5 scenario). Inclusion of this environment-driven trait variation resulted in a strong reduction of the global carbon sink by at least 33% (2.1 Pg C yr(-1) ) from the 2nd quarter of the 21st century onward compared to the default model with fixed traits. In addition, the mid- and high latitudes became a stronger carbon sink and the tropics a stronger carbon source, caused by trait-induced differences in productivity and relative respirational costs. These results point toward a reduction of the global carbon sink when including a more realistic representation of functional vegetation responses, implying more carbon will stay airborne, which could fuel further climate change.

[1]  T. McMahon,et al.  Updated world map of the Köppen-Geiger climate classification , 2007 .

[2]  J. Peñuelas,et al.  Tree growth, mortality, and above-ground biomass accumulation in a holm oak forest under a five-year experimental field drought , 2007, Plant Ecology.

[3]  R. Aerts,et al.  Towards a functional basis for predicting vegetation patterns; incorporating plant traits in habitat distribution models , 2012 .

[4]  Darren T. Drewry,et al.  The Jena Diversity-Dynamic Global Vegetation Model (JeDi-DGVM): a diverse approach to representing t , 2012 .

[5]  Stan D. Wullschleger,et al.  Biochemical Limitations to Carbon Assimilation in C3 Plants—A Retrospective Analysis of the A/Ci Curves from 109 Species , 1993 .

[6]  J. Peñuelas,et al.  Changes in leaf δ13C and δ15N for three Mediterranean tree species in relation to soil water availability , 2008 .

[7]  Bill Shipley,et al.  Structured interspecific determinants of specific leaf area in 34 species of herbaceous angiosperms , 1995 .

[8]  X. Le Roux,et al.  Leaf gas exchange characteristics and water- and nitrogen-use efficiencies of dominant grass and tree species in a West African savanna , 2004, Plant Ecology.

[9]  Ranz,et al.  World Map of the Köppen-Geiger climate classification updated — Source link , 2006 .

[10]  G. Collatz,et al.  Coupled Photosynthesis-Stomatal Conductance Model for Leaves of C4 Plants , 1992 .

[11]  Federico Magnani,et al.  Seasonal and interannual variability of photosynthetic capacity in relation to leaf nitrogen in a deciduous forest plantation in northern Italy. , 2005, Tree physiology.

[12]  Peter M van Bodegom,et al.  Plant Strategies in Relation to Resource Supply in Mesic to Wet Environments: Does Theory Mirror Nature? , 2009, The American Naturalist.

[13]  Simon J. Ussher,et al.  Iron in the Sargasso Sea (Bermuda Atlantic Time‐series Study region) during summer: Eolian imprint, spatiotemporal variability, and ecological implications , 2005 .

[14]  P. V. van Bodegom,et al.  A fully traits-based approach to modeling global vegetation distribution , 2014, Proceedings of the National Academy of Sciences.

[15]  Pierre Friedlingstein,et al.  Twenty-First-Century Compatible CO2 Emissions and Airborne Fraction Simulated by CMIP5 Earth System Models under Four Representative Concentration Pathways , 2013, Journal of Climate.

[16]  L. Poorter,et al.  Causes and consequences of variation in leaf mass per area (LMA): a meta-analysis. , 2009, The New phytologist.

[17]  A. Thomson,et al.  The representative concentration pathways: an overview , 2011 .

[18]  Ülo Niinemets,et al.  GLOBAL-SCALE CLIMATIC CONTROLS OF LEAF DRY MASS PER AREA, DENSITY, AND THICKNESS IN TREES AND SHRUBS , 2001 .

[19]  Donald R. Zak,et al.  Ecological Lessons from Free-Air CO2 Enrichment (FACE) Experiments , 2011 .

[20]  T. Feldpausch,et al.  Co-limitation of photosynthetic capacity by nitrogen and phosphorus in West Africa woodlands. , 2010, Plant, cell & environment.

[21]  Ülo Niinemets,et al.  Research review. Components of leaf dry mass per area – thickness and density – alter leaf photosynthetic capacity in reverse directions in woody plants , 1999 .

[22]  Terry V. Callaghan,et al.  Leaf digestibility and litter decomposability are related in a wide range of subarctic plant species and types , 2004 .

[23]  S. Lavorel,et al.  Predicting changes in community composition and ecosystem functioning from plant traits: revisiting the Holy Grail , 2002 .

[24]  Dennis D. Baldocchi,et al.  Are temporal variations of leaf traits responsible for seasonal and inter‐annual variability in ecosystem CO2 exchange? , 2011 .

[25]  Peter B. Reich,et al.  Global quantification of contrasting leaf life span strategies for deciduous and evergreen species in response to environmental conditions , 2012 .

[26]  B. Stevens,et al.  Climate and carbon cycle changes from 1850 to 2100 in MPI‐ESM simulations for the Coupled Model Intercomparison Project phase 5 , 2013 .

[27]  Nicholas G Smith,et al.  Plant respiration and photosynthesis in global‐scale models: incorporating acclimation to temperature and CO2 , 2013, Global change biology.

[28]  Alexander Loew,et al.  Evaluation of vegetation cover and land‐surface albedo in MPI‐ESM CMIP5 simulations , 2013 .

[29]  Jeannine Cavender-Bares,et al.  Phylogenetic structure of Floridian plant communities depends on taxonomic and spatial scale. , 2006, Ecology.

[30]  Chun-jing Zou,et al.  Effects of elevated CO2, warming and precipitation change on plant growth, photosynthesis and peroxidation in dominant species from North China grassland , 2013, Planta.

[31]  Sönke Zaehle,et al.  Towards a more objective evaluation of modelled land-carbon trends using atmospheric CO 2 and satellite-based vegetation activity observations , 2013 .

[32]  Peter E. Thornton,et al.  Parameterization and Sensitivity Analysis of the BIOME–BGC Terrestrial Ecosystem Model: Net Primary Production Controls , 2000 .

[33]  A. Rogers,et al.  The response of photosynthesis and stomatal conductance to rising [CO2]: mechanisms and environmental interactions. , 2007, Plant, cell & environment.

[34]  D. Ackerly,et al.  A trait-based test for habitat filtering: convex hull volume. , 2006, Ecology.

[35]  Sebastian Schmidtlein,et al.  Future no‐analogue vegetation produced by no‐analogue combinations of temperature and insolation , 2014 .

[36]  I. Schmidt,et al.  High Resilience in Heathland Plants to Changes in Temperature, Drought, and CO2 in Combination: Results from the CLIMAITE Experiment , 2011, Ecosystems.

[37]  J. P. Grime,et al.  The plant traits that drive ecosystems: Evidence from three continents , 2004 .

[38]  M. Navas,et al.  Plant growth and competition at elevated CO2 : on winners, losers and functional groups. , 2003, The New phytologist.

[39]  M. Maestro,et al.  Functional traits of woody plants: correspondence of species rankings between field adults and laboratory-grown seedlings? , 2003 .

[40]  G D Farquhar.  Models relating subcellular effects of temperature to whole plant responses. , 1988, Symposia of the Society for Experimental Biology.

[41]  A. Michelsen,et al.  Root growth and N dynamics in response to multi-year experimental warming, summer drought and elevated CO2 in a mixed heathland-grass ecosystem. , 2013, Functional plant biology : FPB.

[42]  R. Leuningb,et al.  Assessing parameter variability in a photosynthesis model within and between plant functional types using global Fluxnet eddy covariance data , 2010 .

[43]  M. Pärtel,et al.  Ecological assembly rules in plant communities—approaches, patterns and prospects , 2012, Biological reviews of the Cambridge Philosophical Society.

[44]  M. Hulme,et al.  A high-resolution data set of surface climate over global land areas , 2002 .

[45]  V. Pyankov,et al.  Leaf structure and specific leaf mass: the alpine desert plants of the Eastern Pamirs, Tadjikistan , 1999 .

[46]  L. S. Pereira,et al.  Crop evapotranspiration : guidelines for computing crop water requirements , 1998 .

[47]  Carolyn Hull Sieg,et al.  A multi‐trait test of the leaf‐height‐seed plant strategy scheme with 133 species from a pine forest flora , 2010 .

[48]  Yadvinder Malhi,et al.  Basin-wide variations in foliar properties of Amazonian forest: phylogeny, soils and climate. , 2009 .

[49]  J. Etterson,et al.  Rapid climate change and the rate of adaptation: insight from experimental quantitative genetics. , 2012, The New phytologist.

[50]  William G. Lee,et al.  Modulation of leaf economic traits and trait relationships by climate , 2005 .

[51]  B. Stevens,et al.  Atmospheric component of the MPI‐M Earth System Model: ECHAM6 , 2013 .

[52]  P. Reich,et al.  Nitrogen limitation constrains sustainability of ecosystem response to CO2 , 2006, Nature.

[53]  W. Knorr,et al.  Quantifying photosynthetic capacity and its relationship to leaf nitrogen content for global‐scale terrestrial biosphere models , 2009 .

[54]  Ian J. Wright,et al.  Impacts of trait variation through observed trait–climate relationships on performance of an Earth system model: a conceptual analysis , 2012 .

[55]  Eric Garnier,et al.  Assessing the effects of land-use change on plant traits, communities and ecosystem functioning in grasslands: a standardized methodology and lessons from an application to 11 European sites. , 2007, Annals of botany.

[56]  B. Rudolf,et al.  World Map of the Köppen-Geiger climate classification updated , 2006 .

[57]  P. Reich,et al.  Irradiance, temperature and rainfall influence leaf dark respiration in woody plants: evidence from comparisons across 20 sites. , 2006, The New phytologist.

[58]  T. Holmes,et al.  Global land-surface evaporation estimated from satellite-based observations , 2010 .

[59]  P. De Angelis,et al.  Effects of elevated (CO2) on photosynthesis in European forest species: a meta-analysis of model parameters , 1999 .

[60]  Victor Brovkin,et al.  Global biogeophysical interactions between forest and climate , 2009 .

[61]  O. Phillips,et al.  Coordination of physiological and structural traits in Amazon forest trees , 2011 .

[62]  Jens Kattge,et al.  Will the tropical land biosphere dominate the climate–carbon cycle feedback during the twenty-first century? , 2007 .

[63]  S. Long,et al.  What have we learned from 15 years of free-air CO2 enrichment (FACE)? A meta-analytic review of the responses of photosynthesis, canopy properties and plant production to rising CO2. , 2004, The New phytologist.

[64]  Ian J. Wright,et al.  Leaf phosphorus influences the photosynthesis–nitrogen relation: a cross-biome analysis of 314 species , 2009, Oecologia.

[65]  Martin Hermy,et al.  The LEDA Traitbase: a database of life‐history traits of the Northwest European flora , 2008 .

[66]  Jeffrey M. Warren,et al.  CO2 enhancement of forest productivity constrained by limited nitrogen availability , 2010, Proceedings of the National Academy of Sciences.

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

[68]  Stephen Sitch,et al.  Analysing Amazonian forest productivity using a new individual and trait-based model (TFS v.1) , 2014 .

[69]  Jan-Philip M. Witte,et al.  Going beyond limitations of plant functional types when predicting global ecosystem–atmosphere fluxes: exploring the merits of traits‐based approaches , 2012 .

[70]  Michael Bahn,et al.  Inter‐specific variation of the biochemical limitation to photosynthesis and related leaf traits of 30 species from mountain grassland ecosystems under different land use , 1999 .

[71]  Bill Shipley,et al.  Dry matter content as a measure of dry matter concentration in plants and their parts , 2002 .

[72]  Simon Scheiter,et al.  Next-generation dynamic global vegetation models: learning from community ecology. , 2013, The New phytologist.

[73]  Sean C. Thomas,et al.  The worldwide leaf economics spectrum , 2004, Nature.

[74]  Jan-Philip M. Witte,et al.  A combination of functionally different plant traits provides a means to quantitatively predict a broad range of species assemblages in NW Europe , 2012 .

[75]  Paul A. Keddy,et al.  Assembly and response rules: two goals for predictive community ecology , 1992 .

[76]  Peter B Reich,et al.  Scaling of respiration to nitrogen in leaves, stems and roots of higher land plants. , 2008, Ecology letters.

[77]  Eric Garnier,et al.  Ecosystem productivity can be predicted from potential relative growth rate and species abundance. , 2006, Ecology letters.

[78]  Corinne Le Quéré,et al.  Carbon and Other Biogeochemical Cycles , 2014 .

[79]  V. Brovkin,et al.  Representation of natural and anthropogenic land cover change in MPI‐ESM , 2013 .

[80]  Daniel S. Goll,et al.  Nutrient limitation reduces land carbon uptake in simulations with a model of combined carbon, nitrogen and phosphorus cycling , 2012 .

[81]  A. Starfield,et al.  TIME LAGS AND NOVEL ECOSYSTEMS IN RESPONSE TO TRANSIENT CLIMATIC CHANGE IN ARCTIC ALASKA , 1997 .

[82]  P. Reich,et al.  A global study of relationships between leaf traits, climate and soil measures of nutrient fertility , 2009 .

[83]  S. Higgins,et al.  TRY – a global database of plant traits , 2011, Global Change Biology.

[84]  Xin-Guang Zhu,et al.  Photosynthesis in a CO2-Rich Atmosphere , 2012 .

[85]  Stephen Sitch,et al.  Effects of parameter uncertainties on the modeling of terrestrial biosphere dynamics , 2005 .

[86]  D. Ackerly,et al.  A trait-based approach to community assembly: partitioning of species trait values into within- and among-community components. , 2007, Ecology letters.

[87]  Tohru Nakashizuka,et al.  Leaf herbivory and decomposability in a Malaysian tropical rain forest. , 2008, Ecology.

[88]  I. C. Prentice,et al.  Evaluation of the terrestrial carbon cycle, future plant geography and climate‐carbon cycle feedbacks using five Dynamic Global Vegetation Models (DGVMs) , 2008 .

[89]  S. Zaehle,et al.  Robust dynamics of Amazon dieback to climate change with perturbed ecosystem model parameters , 2010 .