TY - JOUR
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
N1 - Publisher Copyright:
© 2019 Fauset, Gloor, Fyllas, Phillips, Asner, Baker, Patrick Bentley, Brienen, Christoffersen, del Aguila-Pasquel, Doughty, Feldpausch, Galbraith, Goodman, Girardin, Honorio Coronado, Monteagudo, Salinas, Shenkin, Silva-Espejo, van der Heijden, Vasquez, Alvarez-Davila, Arroyo, Barroso, Brown, Castro, Cornejo Valverde, Davila Cardozo, Di Fiore, Erwin, Huamantupa-Chuquimaco, Núñez Vargas, Neill, Pallqui Camacho, Gutierrez, Peacock, Pitman, Prieto, Restrepo, Rudas, Quesada, Silveira, Stropp, Terborgh, Vieira and Malhi.
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
UR - http://www.scopus.com/inward/record.url?scp=85067407474&partnerID=8YFLogxK
U2 - 10.3389/feart.2019.00083
DO - 10.3389/feart.2019.00083
M3 - Article
AN - SCOPUS:85067407474
SN - 2296-6463
VL - 7
JO - Frontiers in Earth Science
JF - Frontiers in Earth Science
M1 - 83
ER -