Disentangling the impact of nested sources of variability on species growth processes: A mixture of multilevel mixed model approach

The understanding of tree growth processes is crucial for promoting sustainable forest management strategies. This is a challenging task in highly biodiverse ecosystems where many tree species are observed on very few individuals and the small sample sizes hinder a good fit of species-specific models. We propose the use of finite mixture of random coefficient regression models with multilevel nested random effects to infer guild specific fixed and random effects while evaluating the relative importance of the nested sources of variability on goodness-of-fit. This approach extends finite mixture of linear mixed model used for longitudinal or single group structured data contexts. A dedicated expectation–maximisation algorithm is introduced for parameter estimation. Simulations are performed for the evaluation of the misspecification of nested-grouping structures. This work has been motivated by data collected biennially in Central African rainforests from 1986 to 2010. We show the accuracy of the proposed approach in successfully reproducing individual growth processes and classifying tree species into well-differentiated clusters with clear ecological interpretations. Moreover, results confirm that interindividual variability appears as the most important factor to explain tropical tree species growth process variability from Central Africa forests.

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Main Authors: Moudjieu Leumbe, Etienne Fabrice, Mortier, Frédéric, Takam Soh, Patrice, Picard, Nicolas, Allah-Barem, Félix, Baya, Fidèle, Tadesse, Mahlet G., Rossi, Vivien
Format: article biblioteca
Language:eng
Subjects:K01 - Foresterie - Considérations générales, U10 - Informatique, mathématiques et statistiques, F40 - Écologie végétale, forêt tropicale humide, modèle de simulation, séquestration du carbone, croissance, méthode statistique, modèle mathématique, forêt tropicale, http://aims.fao.org/aos/agrovoc/c_7976, http://aims.fao.org/aos/agrovoc/c_24242, http://aims.fao.org/aos/agrovoc/c_331583, http://aims.fao.org/aos/agrovoc/c_3394, http://aims.fao.org/aos/agrovoc/c_7377, http://aims.fao.org/aos/agrovoc/c_24199, http://aims.fao.org/aos/agrovoc/c_24904,
Online Access:http://agritrop.cirad.fr/609605/
http://agritrop.cirad.fr/609605/1/moudjieu24.pdf
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spelling dig-cirad-fr-6096052024-08-06T13:51:16Z http://agritrop.cirad.fr/609605/ http://agritrop.cirad.fr/609605/ Disentangling the impact of nested sources of variability on species growth processes: A mixture of multilevel mixed model approach. Moudjieu Leumbe Etienne Fabrice, Mortier Frédéric, Takam Soh Patrice, Picard Nicolas, Allah-Barem Félix, Baya Fidèle, Tadesse Mahlet G., Rossi Vivien. 2024. Stat, 13 (2):e695, 14 p.https://doi.org/10.1002/sta4.695 <https://doi.org/10.1002/sta4.695> Disentangling the impact of nested sources of variability on species growth processes: A mixture of multilevel mixed model approach Moudjieu Leumbe, Etienne Fabrice Mortier, Frédéric Takam Soh, Patrice Picard, Nicolas Allah-Barem, Félix Baya, Fidèle Tadesse, Mahlet G. Rossi, Vivien eng 2024 Stat K01 - Foresterie - Considérations générales U10 - Informatique, mathématiques et statistiques F40 - Écologie végétale forêt tropicale humide modèle de simulation séquestration du carbone croissance méthode statistique modèle mathématique forêt tropicale http://aims.fao.org/aos/agrovoc/c_7976 http://aims.fao.org/aos/agrovoc/c_24242 http://aims.fao.org/aos/agrovoc/c_331583 http://aims.fao.org/aos/agrovoc/c_3394 http://aims.fao.org/aos/agrovoc/c_7377 http://aims.fao.org/aos/agrovoc/c_24199 http://aims.fao.org/aos/agrovoc/c_24904 The understanding of tree growth processes is crucial for promoting sustainable forest management strategies. This is a challenging task in highly biodiverse ecosystems where many tree species are observed on very few individuals and the small sample sizes hinder a good fit of species-specific models. We propose the use of finite mixture of random coefficient regression models with multilevel nested random effects to infer guild specific fixed and random effects while evaluating the relative importance of the nested sources of variability on goodness-of-fit. This approach extends finite mixture of linear mixed model used for longitudinal or single group structured data contexts. A dedicated expectation–maximisation algorithm is introduced for parameter estimation. Simulations are performed for the evaluation of the misspecification of nested-grouping structures. This work has been motivated by data collected biennially in Central African rainforests from 1986 to 2010. We show the accuracy of the proposed approach in successfully reproducing individual growth processes and classifying tree species into well-differentiated clusters with clear ecological interpretations. Moreover, results confirm that interindividual variability appears as the most important factor to explain tropical tree species growth process variability from Central Africa forests. article info:eu-repo/semantics/article Journal Article info:eu-repo/semantics/publishedVersion http://agritrop.cirad.fr/609605/1/moudjieu24.pdf text Cirad license info:eu-repo/semantics/restrictedAccess https://agritrop.cirad.fr/mention_legale.html https://doi.org/10.1002/sta4.695 10.1002/sta4.695 info:eu-repo/semantics/altIdentifier/doi/10.1002/sta4.695 info:eu-repo/semantics/altIdentifier/purl/https://doi.org/10.1002/sta4.695 info:eu-repo/grantAgreement///ANR-18-CE02-0025//(FRA) Nouvelles avancées dans la modélisation de la biodiversité et des services écosystémiques : améliorations statistiques et pertinences écologiques des modèles de distribution multi-espèces/GAMBAS info:eu-repo/grantAgreement/////(FRA) Partenariat Public-Privé pour gérer durablement les Forêts d'Afrique centrale/P3FAC
institution CIRAD FR
collection DSpace
country Francia
countrycode FR
component Bibliográfico
access En linea
databasecode dig-cirad-fr
tag biblioteca
region Europa del Oeste
libraryname Biblioteca del CIRAD Francia
language eng
topic K01 - Foresterie - Considérations générales
U10 - Informatique, mathématiques et statistiques
F40 - Écologie végétale
forêt tropicale humide
modèle de simulation
séquestration du carbone
croissance
méthode statistique
modèle mathématique
forêt tropicale
http://aims.fao.org/aos/agrovoc/c_7976
http://aims.fao.org/aos/agrovoc/c_24242
http://aims.fao.org/aos/agrovoc/c_331583
http://aims.fao.org/aos/agrovoc/c_3394
http://aims.fao.org/aos/agrovoc/c_7377
http://aims.fao.org/aos/agrovoc/c_24199
http://aims.fao.org/aos/agrovoc/c_24904
K01 - Foresterie - Considérations générales
U10 - Informatique, mathématiques et statistiques
F40 - Écologie végétale
forêt tropicale humide
modèle de simulation
séquestration du carbone
croissance
méthode statistique
modèle mathématique
forêt tropicale
http://aims.fao.org/aos/agrovoc/c_7976
http://aims.fao.org/aos/agrovoc/c_24242
http://aims.fao.org/aos/agrovoc/c_331583
http://aims.fao.org/aos/agrovoc/c_3394
http://aims.fao.org/aos/agrovoc/c_7377
http://aims.fao.org/aos/agrovoc/c_24199
http://aims.fao.org/aos/agrovoc/c_24904
spellingShingle K01 - Foresterie - Considérations générales
U10 - Informatique, mathématiques et statistiques
F40 - Écologie végétale
forêt tropicale humide
modèle de simulation
séquestration du carbone
croissance
méthode statistique
modèle mathématique
forêt tropicale
http://aims.fao.org/aos/agrovoc/c_7976
http://aims.fao.org/aos/agrovoc/c_24242
http://aims.fao.org/aos/agrovoc/c_331583
http://aims.fao.org/aos/agrovoc/c_3394
http://aims.fao.org/aos/agrovoc/c_7377
http://aims.fao.org/aos/agrovoc/c_24199
http://aims.fao.org/aos/agrovoc/c_24904
K01 - Foresterie - Considérations générales
U10 - Informatique, mathématiques et statistiques
F40 - Écologie végétale
forêt tropicale humide
modèle de simulation
séquestration du carbone
croissance
méthode statistique
modèle mathématique
forêt tropicale
http://aims.fao.org/aos/agrovoc/c_7976
http://aims.fao.org/aos/agrovoc/c_24242
http://aims.fao.org/aos/agrovoc/c_331583
http://aims.fao.org/aos/agrovoc/c_3394
http://aims.fao.org/aos/agrovoc/c_7377
http://aims.fao.org/aos/agrovoc/c_24199
http://aims.fao.org/aos/agrovoc/c_24904
Moudjieu Leumbe, Etienne Fabrice
Mortier, Frédéric
Takam Soh, Patrice
Picard, Nicolas
Allah-Barem, Félix
Baya, Fidèle
Tadesse, Mahlet G.
Rossi, Vivien
Disentangling the impact of nested sources of variability on species growth processes: A mixture of multilevel mixed model approach
description The understanding of tree growth processes is crucial for promoting sustainable forest management strategies. This is a challenging task in highly biodiverse ecosystems where many tree species are observed on very few individuals and the small sample sizes hinder a good fit of species-specific models. We propose the use of finite mixture of random coefficient regression models with multilevel nested random effects to infer guild specific fixed and random effects while evaluating the relative importance of the nested sources of variability on goodness-of-fit. This approach extends finite mixture of linear mixed model used for longitudinal or single group structured data contexts. A dedicated expectation–maximisation algorithm is introduced for parameter estimation. Simulations are performed for the evaluation of the misspecification of nested-grouping structures. This work has been motivated by data collected biennially in Central African rainforests from 1986 to 2010. We show the accuracy of the proposed approach in successfully reproducing individual growth processes and classifying tree species into well-differentiated clusters with clear ecological interpretations. Moreover, results confirm that interindividual variability appears as the most important factor to explain tropical tree species growth process variability from Central Africa forests.
format article
topic_facet K01 - Foresterie - Considérations générales
U10 - Informatique, mathématiques et statistiques
F40 - Écologie végétale
forêt tropicale humide
modèle de simulation
séquestration du carbone
croissance
méthode statistique
modèle mathématique
forêt tropicale
http://aims.fao.org/aos/agrovoc/c_7976
http://aims.fao.org/aos/agrovoc/c_24242
http://aims.fao.org/aos/agrovoc/c_331583
http://aims.fao.org/aos/agrovoc/c_3394
http://aims.fao.org/aos/agrovoc/c_7377
http://aims.fao.org/aos/agrovoc/c_24199
http://aims.fao.org/aos/agrovoc/c_24904
author Moudjieu Leumbe, Etienne Fabrice
Mortier, Frédéric
Takam Soh, Patrice
Picard, Nicolas
Allah-Barem, Félix
Baya, Fidèle
Tadesse, Mahlet G.
Rossi, Vivien
author_facet Moudjieu Leumbe, Etienne Fabrice
Mortier, Frédéric
Takam Soh, Patrice
Picard, Nicolas
Allah-Barem, Félix
Baya, Fidèle
Tadesse, Mahlet G.
Rossi, Vivien
author_sort Moudjieu Leumbe, Etienne Fabrice
title Disentangling the impact of nested sources of variability on species growth processes: A mixture of multilevel mixed model approach
title_short Disentangling the impact of nested sources of variability on species growth processes: A mixture of multilevel mixed model approach
title_full Disentangling the impact of nested sources of variability on species growth processes: A mixture of multilevel mixed model approach
title_fullStr Disentangling the impact of nested sources of variability on species growth processes: A mixture of multilevel mixed model approach
title_full_unstemmed Disentangling the impact of nested sources of variability on species growth processes: A mixture of multilevel mixed model approach
title_sort disentangling the impact of nested sources of variability on species growth processes: a mixture of multilevel mixed model approach
url http://agritrop.cirad.fr/609605/
http://agritrop.cirad.fr/609605/1/moudjieu24.pdf
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