Original Research ARTICLE
Individual-based modelling of Amazon forests suggests that climate controls productivity while traits control demography
- 1School of Geography, Earth and Environmental Sciences, University of Plymouth, United Kingdom
- 2School of Geography, University of Leeds, United Kingdom
- 3Biodiversity Conservation Laboratory, University of the Aegean, Greece
- 4Department of Global Ecology, Department of Plant Biology, Carnegie Institution for Science, United States
- 5Sonoma State University, United States
- 6University of Texas Rio Grande Valley Edinburg, United States
- 7Instituto de Investigaciones de la Amazonia Peruana, Peru
- 8Northern Arizona University, United States
- 9University of Exeter, United Kingdom
- 10Swedish University of Agricultural Sciences, Sweden
- 11University of Oxford, United Kingdom
- 12Jardin Botanico de Missouri, Peru
- 13Pontificia Universidad Católica del Perú, Peru
- 14National University of Saint Anthony the Abbot in Cuzco, Peru
- 15University of Nottingham, United Kingdom
- 16Universidad Nacional Abierta y a Distancia (UNAD), Colombia
- 17Universidad Autónoma Gabriel René Moreno, Bolivia
- 18Universidade Federal do Acre, Brazil
- 19Woods Hole Research Center, United States
- 20Andes to Amazon Biodiversity Program, Peru
- 21University of the State of Amazonas, Brazil
- 22University of Texas at Austin, United States
- 23Smithsonian Institution, United States
- 24Instituto de Pesquisas Jardim Botânico do Rio de Janeiro, Brazil
- 25Universidad Estatal Amazónica, Ecuador
- 26Field Museum of Natural History, United States
- 27Duke University, United States
- 28Universidad Nacional de Colombia, Colombia
- 29Corporación COL-TREE y Fundación Con Vida, Colombia
- 30National Institute of Amazonian Research (INPA), Brazil
- 31Federal University of Alagoas, Brazil
- 32Campinas State University, Brazil
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 versus 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’ versus ‘slow’ leaf traits, and high versus 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. Modelled 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.
Keywords: Amazon, Carbon Cycle, climate, Forest dynamics, functional traits, Leaf economics spectrum, Tropical Forest, Vegetation model
Received: 27 Jul 2018;
Accepted: 08 Apr 2019.
Edited by:Ken Takahashi, Servicio Nacional de Meteorología e Hidrología del Perú (SENAMHI), Peru
Reviewed by:Jennifer Holm, Lawrence Berkeley National Laboratory, United States
Liam J. Langan, Senckenberg Biodiversity and Climate Research Centre, Germany
Isabelle Maréchaux, Institut National de la Recherche Agronomique Centre Montpellier, France
Copyright: © 2019 Fauset, Gloor, Fyllas, Phillips, Asner, Baker, Bentley, Brienen, Christoffersen, del Aguilar-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, Di Fiore, Erwin, Huamantupa-Chuquimaco, Núñez Vargas, Neill, Pallqui, Gutierrez, Peacock, Pitman, Prieto, Restrepo, Rudas, Quesada, Silviera, Stropp, Terborgh, Vieira and Malhi. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Dr. Sophie Fauset, University of Plymouth, School of Geography, Earth and Environmental Sciences, Plymouth, United Kingdom, email@example.com