A detailed study on Amazon Forest structure and mortality rates through LPJ-GUESS vegetation model
(2021) In Student thesis series INES NGEK01 20202Dept of Physical Geography and Ecosystem Science
- Abstract (Swedish)
- Nowadays it has become relevant for scientists to understand the impact of tropical forest structure on the Global Carbon Cycle. Dynamic vegetation models have been developed to pursue this issue, specifically by improving algorithms that could analyze the allometry, biomass content and mortality rate of each singular simulated plant individual and how this responds to climate change, management and rising CO2 concentrations.
In these studies, I use and test the LPJ-GUESS vegetation model, which is an ecosystem framework for modelling the structure and dynamics of terrestrial ecosystems at landscape, regional and global scales (Smith. et al., 2001). It was used in order to simulate a better reproduction of structural tropical tree... (More) - Nowadays it has become relevant for scientists to understand the impact of tropical forest structure on the Global Carbon Cycle. Dynamic vegetation models have been developed to pursue this issue, specifically by improving algorithms that could analyze the allometry, biomass content and mortality rate of each singular simulated plant individual and how this responds to climate change, management and rising CO2 concentrations.
In these studies, I use and test the LPJ-GUESS vegetation model, which is an ecosystem framework for modelling the structure and dynamics of terrestrial ecosystems at landscape, regional and global scales (Smith. et al., 2001). It was used in order to simulate a better reproduction of structural tropical tree dynamics through the use of allometric equations for the scaling of the tropical tree growth in the Amazon forest. Specifically, in four locations from the Amazon forest, stand structure and developments were well reproduced by the model in comparison to observations of tropical forest structure available from the TEAM network, which provides observational information on the number of individual trees and their sizes on a range of plots across the tropics. Specifically, allometries were both investigated by adjusting standard settings in the model to reach better performances and assess how these settings impact size structure and observations. My results show that the model is not fitting the observation by not simulating accurately directly the size structure of the trees. Improper algorithms and the use of inappropriate parameter values were identified as possible explanations for the lack of agreement of the model with the TEAM network observations. (Less) - Popular Abstract
- Competition between neighbouring trees has a big impact on their growth. Trees have different strategies to deal with competing neighbours. Some grow quickly and tall, overshadowing neighbouring trees, but die young (Georges K., 2015). Others grow more slowly, but outlive the fast-growing ones and cast shade on them over a longer period. These interactions have a strong influence on the dynamics of forests and their functioning as ecosystems (Georges K., 2015).
In this study, I am going to analyze tropical tree structure in the Amazon forest through LPJ-GUESS dynamic vegetation model. The model has the capacity to simulate individual plants belonging to different species, or also called PFTs, plant functional types. The average of each... (More) - Competition between neighbouring trees has a big impact on their growth. Trees have different strategies to deal with competing neighbours. Some grow quickly and tall, overshadowing neighbouring trees, but die young (Georges K., 2015). Others grow more slowly, but outlive the fast-growing ones and cast shade on them over a longer period. These interactions have a strong influence on the dynamics of forests and their functioning as ecosystems (Georges K., 2015).
In this study, I am going to analyze tropical tree structure in the Amazon forest through LPJ-GUESS dynamic vegetation model. The model has the capacity to simulate individual plants belonging to different species, or also called PFTs, plant functional types. The average of each across individuals within a cohort/age class in a patch is simulated on a number of patches that are representing the smallest spatial resolution. The simulations happen by considering a series of mathematical equations inserted in the model throughout algorithms which are representing daily and yearly plant processes of interaction within the ecosystem and environment. In my studies, in particular, I analyze which are the impacts of changes of allometric equations parameters by testing different model runs. What I am aiming for, in specific, is to see if particular changes in allometric equations parameters will drive a significant change in simulating tropical tree size, structure and biomass. Moreover, NPP and tree mortality have also been investigated to check if the simulated productivity (in terms of biomass) of each chosen site was affected more or less by those variables. Finally, a detailed exploration was given by comparing simulations with observations given by TEAM NETWORK to test how the model was reproducing tropical tree structure in the four selected countries in the Amazon (Peru’, Ecuador, Suriname, Brazil). (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/9046937
- author
- Mazzuoli, Sara LU
- supervisor
-
- Jonas Ardö LU
- Thomas Pugh LU
- Benjamin Smith LU
- organization
- alternative title
- Evaluation of Amazon’s tropical forest allometry and mortality through LPJ-GUESS dynamic global vegetation model in comparison with observation from TEAM NETWORK
- course
- NGEK01 20202
- year
- 2021
- type
- M2 - Bachelor Degree
- subject
- keywords
- Amazon's Forest, LPJ-GUESS, simulation, TEAM-NETWORK, dynamic vegetation model, observation, mortality, allometry, tree stand structure, biomass, cohort, PFTs, plant functional types, NPP
- publication/series
- Student thesis series INES
- report number
- 534
- language
- English
- id
- 9046937
- date added to LUP
- 2021-06-06 18:00:27
- date last changed
- 2021-06-06 18:00:27
@misc{9046937,
abstract = {{Nowadays it has become relevant for scientists to understand the impact of tropical forest structure on the Global Carbon Cycle. Dynamic vegetation models have been developed to pursue this issue, specifically by improving algorithms that could analyze the allometry, biomass content and mortality rate of each singular simulated plant individual and how this responds to climate change, management and rising CO2 concentrations.
In these studies, I use and test the LPJ-GUESS vegetation model, which is an ecosystem framework for modelling the structure and dynamics of terrestrial ecosystems at landscape, regional and global scales (Smith. et al., 2001). It was used in order to simulate a better reproduction of structural tropical tree dynamics through the use of allometric equations for the scaling of the tropical tree growth in the Amazon forest. Specifically, in four locations from the Amazon forest, stand structure and developments were well reproduced by the model in comparison to observations of tropical forest structure available from the TEAM network, which provides observational information on the number of individual trees and their sizes on a range of plots across the tropics. Specifically, allometries were both investigated by adjusting standard settings in the model to reach better performances and assess how these settings impact size structure and observations. My results show that the model is not fitting the observation by not simulating accurately directly the size structure of the trees. Improper algorithms and the use of inappropriate parameter values were identified as possible explanations for the lack of agreement of the model with the TEAM network observations.}},
author = {{Mazzuoli, Sara}},
language = {{eng}},
note = {{Student Paper}},
series = {{Student thesis series INES}},
title = {{A detailed study on Amazon Forest structure and mortality rates through LPJ-GUESS vegetation model}},
year = {{2021}},
}