Scaling from individual trees to forests in an Earth system modeling framework using a mathematically tractable model of height-structured competition

Abstract. The long-term and large-scale dynamics of ecosystems are in large part determined by the performances of individual plants in competition with one another for light, water, and nutrients. Woody biomass, a pool of carbon (C) larger than 50% of atmospheric CO2, exists because of height-structured competition for light. However, most of the current Earth system models that predict climate change and C cycle feedbacks lack both a mechanistic formulation for height-structured competition for light and an explicit scaling from individual plants to the globe. In this study, we incorporate height-structured competition for light, competition for water, and explicit scaling from individuals to ecosystems into the land model version 3 (LM3) currently used in the Earth system models developed by the Geophysical Fluid Dynamics Laboratory (GFDL). The height-structured formulation is based on the perfect plasticity approximation (PPA), which has been shown to accurately scale from individual-level plant competition for light, water, and nutrients to the dynamics of whole communities. Because of the tractability of the PPA, the coupled LM3-PPA model is able to include a large number of phenomena across a range of spatial and temporal scales and still retain computational tractability, as well as close linkages to mathematically tractable forms of the model. We test a range of predictions against data from temperate broadleaved forests in the northern USA. The results show the model predictions agree with diurnal and annual C fluxes, growth rates of individual trees in the canopy and understory, tree size distributions, and species-level population dynamics during succession. We also show how the competitively optimal allocation strategy – the strategy that can competitively exclude all others – shifts as a function of the atmospheric CO2 concentration. This strategy is referred to as an evolutionarily stable strategy (ESS) in the ecological literature and is typically not the same as a productivity- or growth-maximizing strategy. Model simulations predict that C sinks caused by CO2 fertilization in forests limited by light and water will be down-regulated if allocation tracks changes in the competitive optimum. The implementation of the model in this paper is for temperate broadleaved forest trees, but the formulation of the model is general. It can be expanded to include other growth forms and physiologies simply by altering parameter values.

[1]  Ignacio Rodriguez-Iturbe,et al.  Decreased water limitation under elevated CO2 amplifies potential for forest carbon sinks , 2015, Proceedings of the National Academy of Sciences.

[2]  Dominique Gravel,et al.  Using dynamic vegetation models to simulate plant range shifts , 2014 .

[3]  Elena Shevliakova,et al.  An Enhanced Model of Land Water and Energy for Global Hydrologic and Earth-System Studies , 2014 .

[4]  C. Farrior Competitive optimization models, attempting to understand the diversity of life. , 2014, The New phytologist.

[5]  Benjamin Smith,et al.  A stand-alone tree demography and landscape structure module for Earth system models: integration with inventory data from temperate and boreal forests , 2014 .

[6]  J. Kattge,et al.  Plant functional types in Earth system models: past experiences and future directions for application of dynamic vegetation models in high-latitude ecosystems. , 2014, Annals of botany.

[7]  R. Birdsey,et al.  Spatial and temporal heterogeneity in the dynamics of eastern U.S. forests: Implications for developing broad-scale forest dynamics models , 2014 .

[8]  Pierre Friedlingstein,et al.  Uncertainties in CMIP5 Climate Projections due to Carbon Cycle Feedbacks , 2014 .

[9]  Russell K. Monson,et al.  Terrestrial Carbon Cycle: Climate Relations in Eight CMIP5 Earth System Models , 2013 .

[10]  Stephen W Pacala,et al.  Interspecific vs intraspecific patterns in leaf nitrogen of forest trees across nitrogen availability gradients. , 2013, The New phytologist.

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

[12]  G. McNickle,et al.  Game theory and plant ecology. , 2013, Ecology letters.

[13]  Andrew D Richardson,et al.  Seasonal dynamics and age of stemwood nonstructural carbohydrates in temperate forest trees. , 2013, The New phytologist.

[14]  S. Levin,et al.  Competition for Water and Light in Closed-Canopy Forests: A Tractable Model of Carbon Allocation with Implications for Carbon Sinks , 2013, The American Naturalist.

[15]  Krista,et al.  GFDL’s ESM2 Global Coupled Climate–Carbon Earth System Models. Part II: Carbon System Formulation and Baseline Simulation Characteristics* , 2013 .

[16]  J. Randerson,et al.  Causes of variation in soil carbon simulations from CMIP5 Earth system models and comparison with observations , 2012 .

[17]  Alan Hastings,et al.  Ecosystem carbon storage capacity as affected by disturbance regimes: A general theoretical model , 2012 .

[18]  Ulf Dieckmann,et al.  Modeling carbon allocation in trees: a search for principles. , 2012, Tree physiology.

[19]  Amilcare Porporato,et al.  Global resorption efficiencies and concentrations of carbon and nutrients in leaves of terrestrial plants , 2012 .

[20]  Charles T. Garten,et al.  Soil carbon and nitrogen cycling and storage throughout the soil profile in a sweetgum plantation after 11 years of CO2‐enrichment , 2012 .

[21]  Ronald,et al.  GFDL’s ESM2 Global Coupled Climate–Carbon Earth System Models. Part I: Physical Formulation and Baseline Simulation Characteristics , 2012 .

[22]  Stephanie A. Bohlman,et al.  A forest structure model that determines crown layers and partitions growth and mortality rates for landscape‐scale applications of tropical forests , 2012 .

[23]  David T. Tissue,et al.  Age‐related decline of stand biomass accumulation is primarily due to mortality and not to reduction in NPP associated with individual tree physiology, tree growth or stand structure in a Quercus‐dominated forest , 2012 .

[24]  Charles T. Garten,et al.  Soil carbon and nitrogen cycling and storage throughout the soil profile in a sweetgum plantation after 11 years of CO 2-enrichment , 2012 .

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

[26]  Richard B Primack,et al.  Leaf-out phenology of temperate woody plants: from trees to ecosystems. , 2011, The New phytologist.

[27]  R. B. Jackson,et al.  A Large and Persistent Carbon Sink in the World’s Forests , 2011, Science.

[28]  Yiqi Luo,et al.  Relative information contributions of model vs. data to short- and long-term forecasts of forest carbon dynamics. , 2011, Ecological applications : a publication of the Ecological Society of America.

[29]  Yiqi Luo,et al.  Carbon and nitrogen dynamics during forest stand development: a global synthesis. , 2011, The New phytologist.

[30]  M. Goulden,et al.  Patterns of NPP, GPP, respiration, and NEP during boreal forest succession , 2011 .

[31]  S. Pacala,et al.  Evolutionarily Stable Strategy Carbon Allocation to Foliage, Wood, and Fine Roots in Trees Competing for Light and Nitrogen: An Analytically Tractable, Individual-Based Model and Quantitative Comparisons to Data , 2011, The American Naturalist.

[32]  C. Peng,et al.  Toward dynamic global vegetation models for simulating vegetation–climate interactions and feedbacks: recent developments, limitations, and future challenges , 2010 .

[33]  F. Woodward,et al.  Assessing uncertainties in a second-generation dynamic vegetation model caused by ecological scale limitations. , 2010, The New phytologist.

[34]  Anping Chen,et al.  Unlocking the forest inventory data: relating individual tree performance to unmeasured environmental factors. , 2010, Ecological applications : a publication of the Ecological Society of America.

[35]  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 .

[36]  S. Gerber,et al.  Nitrogen cycling and feedbacks in a global dynamic land model , 2010 .

[37]  Li Zhang,et al.  Estimated carbon residence times in three forest ecosystems of eastern China: Applications of probabilistic inversion , 2010 .

[38]  George W. Koch,et al.  Increasing wood production through old age in tall trees , 2010 .

[39]  Charles W. Cook,et al.  Re-assessment of plant carbon dynamics at the Duke free-air CO(2) enrichment site: interactions of atmospheric [CO(2)] with nitrogen and water availability over stand development. , 2010, The New phytologist.

[40]  Charles W. Cook,et al.  Increased belowground biomass and soil CO2 fluxes after a decade of carbon dioxide enrichment in a warm-temperate forest. , 2009, Ecology.

[41]  George C. Hurtt,et al.  Carbon cycling under 300 years of land use change: Importance of the secondary vegetation sink , 2009 .

[42]  S. Wofsy,et al.  Mechanistic scaling of ecosystem function and dynamics in space and time: Ecosystem Demography model version 2 , 2009 .

[43]  S. Pacala,et al.  Predicting and understanding forest dynamics using a simple tractable model , 2008, Proceedings of the National Academy of Sciences.

[44]  J. Dushoff,et al.  SCALING FROM TREES TO FORESTS: TRACTABLE MACROSCOPIC EQUATIONS FOR FOREST DYNAMICS , 2008 .

[45]  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 .

[46]  Christopher B. Field,et al.  Changing feedbacks in the climate–biosphere system , 2008 .

[47]  Benjamin Smith,et al.  Representation of vegetation dynamics in the modelling of terrestrial ecosystems: comparing two contrasting approaches within European climate space , 2008 .

[48]  G. Bonan Forests and Climate Change: Forcings, Feedbacks, and the Climate Benefits of Forests , 2008, Science.

[49]  Fernando Valladares,et al.  Ecological limits to plant phenotypic plasticity. , 2007, The New phytologist.

[50]  Peter E. Thornton,et al.  Influence of carbon‐nitrogen cycle coupling on land model response to CO2 fertilization and climate variability , 2007 .

[51]  Markus Reichstein,et al.  CO2 balance of boreal, temperate, and tropical forests derived from a global database , 2007 .

[52]  Drew W. Purves,et al.  Crown Plasticity and Competition for Canopy Space: A New Spatially Implicit Model Parameterized for 250 North American Tree Species , 2007, PloS one.

[53]  Hisashi Sato,et al.  SEIB–DGVM: A new Dynamic Global Vegetation Model using a spatially explicit individual-based approach , 2007 .

[54]  P. Raats Uptake of water from soils by plant roots , 2007 .

[55]  G. Nowacki,et al.  Ecological Subregions: Sections and Subsections for the conterminous United States , 2007 .

[56]  N. Zimmermann,et al.  TreeMig: A forest-landscape model for simulating spatio-temporal patterns from stand to landscape scale , 2006 .

[57]  T. Wesol̸owski,et al.  Timing of bud burst and tree-leaf development in a multispecies temperate forest , 2006 .

[58]  Y. Iwasa,et al.  Correction to “Tragedy of the commons in plant water use” , 2006 .

[59]  E. Wood,et al.  Development of a 50-Year High-Resolution Global Dataset of Meteorological Forcings for Land Surface Modeling , 2006 .

[60]  Yoh Iwasa,et al.  Tragedy of the commons in plant water use , 2006 .

[61]  Chuankuan Wang,et al.  Biomass allometric equations for 10 co-occurring tree species in Chinese temperate forests , 2006 .

[62]  R. Dickinson,et al.  Simplifying the Interaction of Land Surfaces with Radiation for Relating Remote Sensing Products to Climate Models , 2006 .

[63]  R. Schnur,et al.  Climate-carbon cycle feedback analysis: Results from the C , 2006 .

[64]  K. Davis,et al.  Comparing net ecosystem exchange of carbon dioxide between an old-growth and mature forest in the upper Midwest, USA , 2005 .

[65]  Michael G. Ryan,et al.  AN EXPERIMENTAL TEST OF THE CAUSES OF FOREST GROWTH DECLINE WITH STAND AGE , 2004 .

[66]  L. Poorter,et al.  Light environment and tree strategies in a Bolivian tropical moist forest: an evaluation of the light partitioning hypothesis , 2003, Plant Ecology.

[67]  C. Lorimer,et al.  Frequency of partial and missing rings in Acer saccharum in relation to canopy position and growth rate , 1999, Plant Ecology.

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

[69]  É. Kisdi,et al.  Evolutionarily singular strategies and the adaptive growth and branching of the evolutionary tree , 2004, Evolutionary Ecology.

[70]  Christian Messier,et al.  Use of a spatially explicit individual-tree model (SORTIE/BC) to explore the implications of patchiness in structurally complex forests , 2003 .

[71]  Andreas Richter,et al.  Non‐structural carbon compounds in temperate forest trees , 2003 .

[72]  Josep G. Canadell,et al.  Sustainability of terrestrial carbon sequestration: A case study in Duke Forest with inversion approach , 2003 .

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

[74]  R. Birdsey,et al.  National-Scale Biomass Estimators for United States Tree Species , 2003, Forest Science.

[75]  Hans Peter Schmid,et al.  Biometric and eddy-covariance based estimates of annual carbon storage in five eastern North American deciduous forests , 2002 .

[76]  S. Pacala,et al.  A METHOD FOR SCALING VEGETATION DYNAMICS: THE ECOSYSTEM DEMOGRAPHY MODEL (ED) , 2001 .

[77]  Joel s. Brown,et al.  Tragedy of the commons as a result of root competition , 2001 .

[78]  L. Sloan,et al.  Trends, Rhythms, and Aberrations in Global Climate 65 Ma to Present , 2001, Science.

[79]  S. Davies TREE MORTALITY AND GROWTH IN 11 SYMPATRIC MACARANGA SPECIES IN BORNEO , 2001 .

[80]  J. R. Runkle CANOPY TREE TURNOVER IN OLD‐GROWTH MESIC FORESTS OF EASTERN NORTH AMERICA , 2000 .

[81]  K. Woods DYNAMICS IN LATE‐SUCCESSIONAL HEMLOCK–HARDWOOD FORESTS OVER THREE DECADES , 2000 .

[82]  J. Reynolds,et al.  Responses of a loblolly pine ecosystem to CO(2) enrichment: a modeling analysis. , 1999, Tree physiology.

[83]  J. Cermak,et al.  Mapping tree root systems with ground-penetrating radar. , 1999, Tree physiology.

[84]  R. B. Jackson,et al.  A global budget for fine root biomass, surface area, and nutrient contents. , 1997, Proceedings of the National Academy of Sciences of the United States of America.

[85]  Andrew D. Friend,et al.  A process-based, terrestrial biosphere model of ecosystem dynamics (Hybrid v3.0) , 1997 .

[86]  I. C. Prentice,et al.  An integrated biosphere model of land surface processes , 1996 .

[87]  S. Pacala,et al.  Forest models defined by field measurements : Estimation, error analysis and dynamics , 1996 .

[88]  E. Schulze,et al.  Leaf nitrogen, photosynthesis, conductance and transpiration : scaling from leaves to canopies , 1995 .

[89]  J. Randerson,et al.  Terrestrial ecosystem production: A process model based on global satellite and surface data , 1993 .

[90]  Steven W. Running,et al.  Numerical Terradynamic Simulation Group 4-1993 A Physiology-Based Gap Model of Forest Dynamics , 2017 .

[91]  W. Cramer,et al.  A global biome model based on plant physiology and dominance, soil properties and climate , 1992 .

[92]  David B. Clark,et al.  LIFE HISTORY DIVERSITY OF CANOPY AND EMERGENT TREES IN A NEOTROPICAL RAIN FOREST , 1992 .

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

[94]  G. Collatz,et al.  Physiological and environmental regulation of stomatal conductance, photosynthesis and transpiration: a model that includes a laminar boundary layer , 1991 .

[95]  R. Burns,et al.  Silvics of North America: 1. Conifers; 2. Hardwoods , 1990 .

[96]  W. Parton,et al.  Analysis of factors controlling soil organic matter levels in Great Plains grasslands , 1987 .

[97]  J. Finn A Theory of Forest Dynamics: The Ecological Implications of Forest Succession Models , 1986 .

[98]  Herman H. Shugart,et al.  Computer Models of Forest Succession , 1984 .

[99]  H. Shugart A Theory of Forest Dynamics , 1984 .

[100]  C. Bohren,et al.  An introduction to atmospheric radiation , 1981 .

[101]  W. Weaver,et al.  Two-Stream Approximations to Radiative Transfer in Planetary Atmospheres: A Unified Description of Existing Methods and a New Improvement , 1980 .

[102]  J. R. Wallis,et al.  Some ecological consequences of a computer model of forest growth , 1972 .

[103]  P. G. Adlard,et al.  Simulation of the Growth of Even-Aged Stands of White Spruce , 1971 .

[104]  T. Kira,et al.  A QUANTITATIVE ANALYSIS OF PLANT FORM-THE PIPE MODEL THEORY : II. FURTHER EVIDENCE OF THE THEORY AND ITS APPLICATION IN FOREST ECOLOGY , 1964 .

[105]  T. Kira,et al.  A QUANTITATIVE ANALYSIS OF PLANT FORM-THE PIPE MODEL THEORY : I.BASIC ANALYSES , 1964 .

[106]  W. R. Gardner DYNAMIC ASPECTS OF WATER AVAILABILITY TO PLANTS , 1960 .

[107]  M. P.R.,et al.  A METHOD FOR SCALING VEGETATION DYNAMICS: THE ECOSYSTEM DEMOGRAPHY MODEL (ED) , 2022 .

[108]  S S I T C H,et al.  Evaluation of Ecosystem Dynamics, Plant Geography and Terrestrial Carbon Cycling in the Lpj Dynamic Global Vegetation Model , 2022 .