Individual-based modeling of amazon forests suggests that climate controls productivity while traits control demography

Sophie Fauset, Manuel Gloor, Nikolaos M. Fyllas, Oliver L. Phillips, Gregory P. Asner, Timothy R. Baker, Lisa Patrick Bentley, Roel J.W. Brienen, Bradley O. Christoffersen, Jhon del Aguila-Pasquel, Christopher E. Doughty, Ted R. Feldpausch, David R. Galbraith, Rosa C. Goodman, Cécile A.J. Girardin, Euridice N. Honorio Coronado, Abel Monteagudo, Norma Salinas, Alexander Shenkin, Javier E. Silva-EspejoGeertje van der Heijden, Rodolfo Vasquez, Esteban Alvarez-Davila, Luzmila Arroyo, Jorcely G. Barroso, Foster Brown, Wendeson Castro, Fernando Cornejo Valverde, Nallarett Davila Cardozo, Anthony Di Fiore, Terry Erwin, Isau Huamantupa-Chuquimaco, Percy Núñez Vargas, David Neill, Nadir Pallqui Camacho, Alexander Parada Gutierrez, Julie Peacock, Nigel Pitman, Adriana Prieto, Zorayda Restrepo, Agustín Rudas, Carlos A. Quesada, Marcos Silveira, Juliana Stropp, John Terborgh, Simone A. Vieira, Yadvinder Malhi

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Climate, species composition, and soils are thought to control carbon cycling and forest structure in Amazonian forests. Here, we add a demographics scheme (tree recruitment, growth, and mortality) to a recently developed non-demographic model—the Trait-based Forest Simulator (TFS)—to explore the roles of climate and plant traits in controlling forest productivity and structure. We compared two sites with differing climates (seasonal vs. aseasonal precipitation) and plant traits. Through an initial validation simulation, we assessed whether the model converges on observed forest properties (productivity, demographic and structural variables) using datasets of functional traits, structure, and climate to model the carbon cycle at the two sites. In a second set of simulations, we tested the relative importance of climate and plant traits for forest properties within the TFS framework using the climate from the two sites with hypothetical trait distributions representing two axes of functional variation (“fast” vs. “slow” leaf traits, and high vs. low wood density). The adapted model with demographics reproduced observed variation in gross (GPP) and net (NPP) primary production, and respiration. However, NPP and respiration at the level of plant organs (leaf, stem, and root) were poorly simulated. Mortality and recruitment rates were underestimated. The equilibrium forest structure differed from observations of stem numbers suggesting either that the forests are not currently at equilibrium or that mechanisms are missing from the model. Findings from the second set of simulations demonstrated that differences in productivity were driven by climate, rather than plant traits. Contrary to expectation, varying leaf traits had no influence on GPP. Drivers of simulated forest structure were complex, with a key role for wood density mediated by its link to tree mortality. Modeled mortality and recruitment rates were linked to plant traits alone, drought-related mortality was not accounted for. In future, model development should focus on improving allocation, mortality, organ respiration, simulation of understory trees and adding hydraulic traits. This type of model that incorporates diverse tree strategies, detailed forest structure and realistic physiology is necessary if we are to be able to simulate tropical forest responses to global change scenarios.

Original languageEnglish (US)
Article number83
JournalFrontiers in Earth Science
Volume7
DOIs
StatePublished - Apr 18 2019
Externally publishedYes

Fingerprint

demography
productivity
climate
modeling
mortality
respiration
simulation
simulator
stem
carbon cycle
global change
tropical forest
understory
physiology
primary production
drought
hydraulics
carbon

Keywords

  • Amazon
  • Carbon cycle
  • Climate
  • Forest dynamics
  • Functional traits
  • Leaf economics spectrum
  • Tropical forest
  • Vegetation model

ASJC Scopus subject areas

  • Earth and Planetary Sciences(all)

Cite this

Individual-based modeling of amazon forests suggests that climate controls productivity while traits control demography. / Fauset, Sophie; Gloor, Manuel; Fyllas, Nikolaos M.; Phillips, Oliver L.; Asner, Gregory P.; Baker, Timothy R.; Patrick Bentley, Lisa; Brienen, Roel J.W.; Christoffersen, Bradley O.; del Aguila-Pasquel, Jhon; Doughty, Christopher E.; Feldpausch, Ted R.; Galbraith, David R.; Goodman, Rosa C.; Girardin, Cécile A.J.; Honorio Coronado, Euridice N.; Monteagudo, Abel; Salinas, Norma; Shenkin, Alexander; Silva-Espejo, Javier E.; van der Heijden, Geertje; Vasquez, Rodolfo; Alvarez-Davila, Esteban; Arroyo, Luzmila; Barroso, Jorcely G.; Brown, Foster; Castro, Wendeson; Cornejo Valverde, Fernando; Davila Cardozo, Nallarett; Di Fiore, Anthony; Erwin, Terry; Huamantupa-Chuquimaco, Isau; Núñez Vargas, Percy; Neill, David; Pallqui Camacho, Nadir; Gutierrez, Alexander Parada; Peacock, Julie; Pitman, Nigel; Prieto, Adriana; Restrepo, Zorayda; Rudas, Agustín; Quesada, Carlos A.; Silveira, Marcos; Stropp, Juliana; Terborgh, John; Vieira, Simone A.; Malhi, Yadvinder.

In: Frontiers in Earth Science, Vol. 7, 83, 18.04.2019.

Research output: Contribution to journalArticle

Fauset, S, Gloor, M, Fyllas, NM, Phillips, OL, Asner, GP, Baker, TR, Patrick Bentley, L, Brienen, RJW, Christoffersen, BO, del Aguila-Pasquel, J, Doughty, CE, Feldpausch, TR, Galbraith, DR, Goodman, RC, Girardin, CAJ, Honorio Coronado, EN, Monteagudo, A, Salinas, N, Shenkin, A, Silva-Espejo, JE, van der Heijden, G, Vasquez, R, Alvarez-Davila, E, Arroyo, L, Barroso, JG, Brown, F, Castro, W, Cornejo Valverde, F, Davila Cardozo, N, Di Fiore, A, Erwin, T, Huamantupa-Chuquimaco, I, Núñez Vargas, P, Neill, D, Pallqui Camacho, N, Gutierrez, AP, Peacock, J, Pitman, N, Prieto, A, Restrepo, Z, Rudas, A, Quesada, CA, Silveira, M, Stropp, J, Terborgh, J, Vieira, SA & Malhi, Y 2019, 'Individual-based modeling of amazon forests suggests that climate controls productivity while traits control demography', Frontiers in Earth Science, vol. 7, 83. https://doi.org/10.3389/feart.2019.00083
Fauset, Sophie ; Gloor, Manuel ; Fyllas, Nikolaos M. ; Phillips, Oliver L. ; Asner, Gregory P. ; Baker, Timothy R. ; Patrick Bentley, Lisa ; Brienen, Roel J.W. ; Christoffersen, Bradley O. ; del Aguila-Pasquel, Jhon ; Doughty, Christopher E. ; Feldpausch, Ted R. ; Galbraith, David R. ; Goodman, Rosa C. ; Girardin, Cécile A.J. ; Honorio Coronado, Euridice N. ; Monteagudo, Abel ; Salinas, Norma ; Shenkin, Alexander ; Silva-Espejo, Javier E. ; van der Heijden, Geertje ; Vasquez, Rodolfo ; Alvarez-Davila, Esteban ; Arroyo, Luzmila ; Barroso, Jorcely G. ; Brown, Foster ; Castro, Wendeson ; Cornejo Valverde, Fernando ; Davila Cardozo, Nallarett ; Di Fiore, Anthony ; Erwin, Terry ; Huamantupa-Chuquimaco, Isau ; Núñez Vargas, Percy ; Neill, David ; Pallqui Camacho, Nadir ; Gutierrez, Alexander Parada ; Peacock, Julie ; Pitman, Nigel ; Prieto, Adriana ; Restrepo, Zorayda ; Rudas, Agustín ; Quesada, Carlos A. ; Silveira, Marcos ; Stropp, Juliana ; Terborgh, John ; Vieira, Simone A. ; Malhi, Yadvinder. / Individual-based modeling of amazon forests suggests that climate controls productivity while traits control demography. In: Frontiers in Earth Science. 2019 ; Vol. 7.
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abstract = "Climate, species composition, and soils are thought to control carbon cycling and forest structure in Amazonian forests. Here, we add a demographics scheme (tree recruitment, growth, and mortality) to a recently developed non-demographic model—the Trait-based Forest Simulator (TFS)—to explore the roles of climate and plant traits in controlling forest productivity and structure. We compared two sites with differing climates (seasonal vs. aseasonal precipitation) and plant traits. Through an initial validation simulation, we assessed whether the model converges on observed forest properties (productivity, demographic and structural variables) using datasets of functional traits, structure, and climate to model the carbon cycle at the two sites. In a second set of simulations, we tested the relative importance of climate and plant traits for forest properties within the TFS framework using the climate from the two sites with hypothetical trait distributions representing two axes of functional variation (“fast” vs. “slow” leaf traits, and high vs. low wood density). The adapted model with demographics reproduced observed variation in gross (GPP) and net (NPP) primary production, and respiration. However, NPP and respiration at the level of plant organs (leaf, stem, and root) were poorly simulated. Mortality and recruitment rates were underestimated. The equilibrium forest structure differed from observations of stem numbers suggesting either that the forests are not currently at equilibrium or that mechanisms are missing from the model. Findings from the second set of simulations demonstrated that differences in productivity were driven by climate, rather than plant traits. Contrary to expectation, varying leaf traits had no influence on GPP. Drivers of simulated forest structure were complex, with a key role for wood density mediated by its link to tree mortality. Modeled mortality and recruitment rates were linked to plant traits alone, drought-related mortality was not accounted for. In future, model development should focus on improving allocation, mortality, organ respiration, simulation of understory trees and adding hydraulic traits. This type of model that incorporates diverse tree strategies, detailed forest structure and realistic physiology is necessary if we are to be able to simulate tropical forest responses to global change scenarios.",
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T1 - Individual-based modeling of amazon forests suggests that climate controls productivity while traits control demography

AU - Fauset, Sophie

AU - Gloor, Manuel

AU - Fyllas, Nikolaos M.

AU - Phillips, Oliver L.

AU - Asner, Gregory P.

AU - Baker, Timothy R.

AU - Patrick Bentley, Lisa

AU - Brienen, Roel J.W.

AU - Christoffersen, Bradley O.

AU - del Aguila-Pasquel, Jhon

AU - Doughty, Christopher E.

AU - Feldpausch, Ted R.

AU - Galbraith, David R.

AU - Goodman, Rosa C.

AU - Girardin, Cécile A.J.

AU - Honorio Coronado, Euridice N.

AU - Monteagudo, Abel

AU - Salinas, Norma

AU - Shenkin, Alexander

AU - Silva-Espejo, Javier E.

AU - van der Heijden, Geertje

AU - Vasquez, Rodolfo

AU - Alvarez-Davila, Esteban

AU - Arroyo, Luzmila

AU - Barroso, Jorcely G.

AU - Brown, Foster

AU - Castro, Wendeson

AU - Cornejo Valverde, Fernando

AU - Davila Cardozo, Nallarett

AU - Di Fiore, Anthony

AU - Erwin, Terry

AU - Huamantupa-Chuquimaco, Isau

AU - Núñez Vargas, Percy

AU - Neill, David

AU - Pallqui Camacho, Nadir

AU - Gutierrez, Alexander Parada

AU - Peacock, Julie

AU - Pitman, Nigel

AU - Prieto, Adriana

AU - Restrepo, Zorayda

AU - Rudas, Agustín

AU - Quesada, Carlos A.

AU - Silveira, Marcos

AU - Stropp, Juliana

AU - Terborgh, John

AU - Vieira, Simone A.

AU - Malhi, Yadvinder

PY - 2019/4/18

Y1 - 2019/4/18

N2 - Climate, species composition, and soils are thought to control carbon cycling and forest structure in Amazonian forests. Here, we add a demographics scheme (tree recruitment, growth, and mortality) to a recently developed non-demographic model—the Trait-based Forest Simulator (TFS)—to explore the roles of climate and plant traits in controlling forest productivity and structure. We compared two sites with differing climates (seasonal vs. aseasonal precipitation) and plant traits. Through an initial validation simulation, we assessed whether the model converges on observed forest properties (productivity, demographic and structural variables) using datasets of functional traits, structure, and climate to model the carbon cycle at the two sites. In a second set of simulations, we tested the relative importance of climate and plant traits for forest properties within the TFS framework using the climate from the two sites with hypothetical trait distributions representing two axes of functional variation (“fast” vs. “slow” leaf traits, and high vs. low wood density). The adapted model with demographics reproduced observed variation in gross (GPP) and net (NPP) primary production, and respiration. However, NPP and respiration at the level of plant organs (leaf, stem, and root) were poorly simulated. Mortality and recruitment rates were underestimated. The equilibrium forest structure differed from observations of stem numbers suggesting either that the forests are not currently at equilibrium or that mechanisms are missing from the model. Findings from the second set of simulations demonstrated that differences in productivity were driven by climate, rather than plant traits. Contrary to expectation, varying leaf traits had no influence on GPP. Drivers of simulated forest structure were complex, with a key role for wood density mediated by its link to tree mortality. Modeled mortality and recruitment rates were linked to plant traits alone, drought-related mortality was not accounted for. In future, model development should focus on improving allocation, mortality, organ respiration, simulation of understory trees and adding hydraulic traits. This type of model that incorporates diverse tree strategies, detailed forest structure and realistic physiology is necessary if we are to be able to simulate tropical forest responses to global change scenarios.

AB - Climate, species composition, and soils are thought to control carbon cycling and forest structure in Amazonian forests. Here, we add a demographics scheme (tree recruitment, growth, and mortality) to a recently developed non-demographic model—the Trait-based Forest Simulator (TFS)—to explore the roles of climate and plant traits in controlling forest productivity and structure. We compared two sites with differing climates (seasonal vs. aseasonal precipitation) and plant traits. Through an initial validation simulation, we assessed whether the model converges on observed forest properties (productivity, demographic and structural variables) using datasets of functional traits, structure, and climate to model the carbon cycle at the two sites. In a second set of simulations, we tested the relative importance of climate and plant traits for forest properties within the TFS framework using the climate from the two sites with hypothetical trait distributions representing two axes of functional variation (“fast” vs. “slow” leaf traits, and high vs. low wood density). The adapted model with demographics reproduced observed variation in gross (GPP) and net (NPP) primary production, and respiration. However, NPP and respiration at the level of plant organs (leaf, stem, and root) were poorly simulated. Mortality and recruitment rates were underestimated. The equilibrium forest structure differed from observations of stem numbers suggesting either that the forests are not currently at equilibrium or that mechanisms are missing from the model. Findings from the second set of simulations demonstrated that differences in productivity were driven by climate, rather than plant traits. Contrary to expectation, varying leaf traits had no influence on GPP. Drivers of simulated forest structure were complex, with a key role for wood density mediated by its link to tree mortality. Modeled mortality and recruitment rates were linked to plant traits alone, drought-related mortality was not accounted for. In future, model development should focus on improving allocation, mortality, organ respiration, simulation of understory trees and adding hydraulic traits. This type of model that incorporates diverse tree strategies, detailed forest structure and realistic physiology is necessary if we are to be able to simulate tropical forest responses to global change scenarios.

KW - Amazon

KW - Carbon cycle

KW - Climate

KW - Forest dynamics

KW - Functional traits

KW - Leaf economics spectrum

KW - Tropical forest

KW - Vegetation model

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