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1. What is the influence of anthropogenic impact on the population structure of Attalea speciosa Mart. ex Spreng. in the Brazilian Amazonian region?

Author

Alessio Moreira dos Santos, Danielle Mitja, Izildinha de Souza Miranda, Patrice Loisel, Eric Delaître, and Laurent Demagistri

Subjects
Amazon, Attalea speciosa, population structure, anthropogenic impact, Botany, QK1-989
Abstract

ABSTRACT Attalea speciosa (babassu) is a native palm of the primary forest from Amazonian and Cerrado biomes, and has multiple economic and cultural uses. However, this palm can become dominant in open areas, with a long-term persistence in the community. The objective of this study was to compare the population structure and morphology of babassu in three habitat types characterizing forest succession: primary forest, pasture, and babaçual (babassu-dominated secondary forest). For this purpose, we monitored 6,333 individuals for three years at six life stages in 11 sites with 25 plots located in PA-Benfica, Itupiranga-Pará, Brazil. The morphological parameters showed differences between secondary environments (pasture and babaçual) and primary forests, suggesting that this species has a high capacity for phenotypic plasticity. The inverse J-shaped distribution was observed only in primary forests, with the density of all stages constant along the whole study, unlike pastures and babaçual areas. While the density of seedlings is highest in primary forests, stage 4 and 5 juveniles and adults are most numerous in babaçuals. Our results suggest that the higher dominance of A. speciosa in babaçual areas can be associated with the resilience of this species to anthropogenic disturbances.

Published
2022
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2. Coviability of social and ecological systems : reconnecting mankind to the biosphere in an era of global change. Vol. 2 : Coviability questioned by a diversity of situations

Author

Eric Delaître, Deiane Jorge Macedo, Izildinha Souza Miranda, Laurent Demagistri, Bénédicte Fontez, Nikolay Sirakov, Hélène Rey-Valette, Maria Regina Teixeira da Rocha, Patrice Loisel, Danielle Mitja, Thérèse Libourel, Sol González-Pérez, Alessio Moreira dos Santos, Institut de Recherche pour le Développement (IRD), Mathématiques, Informatique et STatistique pour l'Environnement et l'Agronomie (MISTEA), Institut National de la Recherche Agronomique (INRA)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Universidade Federal do Sul e Sudeste do Para (UNIFESSPA), Universidade Federal Rural da Amazônia (UFRA), Universidade Federal do Pará (UFPA), Centre d'Economie de l'Environnement - Montpellier - FRE2010 (CEE-M), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM), Université de Montpellier (UM), the Foundation Agropolis Open Science program (project sustainable management of the babassu palm, 2014-2017) and the CNES TOSCA program (project CIC-TOOB 2013-2014), Barrière, Olivier (ed.), Behnassi, M. (ed.), David, Gilbert (ed.), Douzal, V. (ed.), Fargette, Mireille (ed.), Libourel, T. (ed.), Loireau, Maud (ed.), Pascal, L. (ed.), Prost, C. (ed.), Ravena Canete, V. (ed.), Seyler, Frédérique (ed.), Morand, S. (ed.), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de la Recherche Agronomique (INRA)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM), and Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de la Recherche Agronomique (INRA)

Subjects
0106 biological sciences, [SDV.SA]Life Sciences [q-bio]/Agricultural sciences, eco-socio-system, écosociosystème, télédétection, Population, 010501 environmental sciences, 010603 evolutionary biology, 01 natural sciences, Amazonian rainforest, remote sensing, Attalea speciosa, education, uses, 0105 earth and related environmental sciences, education.field_of_study, babaçu, [SHS.SOCIO]Humanities and Social Sciences/Sociology, [SHS.STAT]Humanities and Social Sciences/Methods and statistics, biology, Land use, babassu, Agroforestry, 15. Life on land, biology.organism_classification, Tree (data structure), Geography, dynamique de population, [SHS.ENVIR]Humanities and Social Sciences/Environmental studies, Sustainability, extractivism, dynamics of the population, extractivisme, usages, Palm, Forage crop
Abstract

Vol. 2: Coviability Questioned by a Diversity of Situations Chapitre 40 La version en français sera publiée ultérieurement aux éditions Matériologiques en co-édition avec les éditions IRD; International audience; The babassu palm tree (Attalea speciosa Mart. ex Spreng.) is a species native to the Amazonian rainforest. The invasive nature of this palm tree results in a high density of babassu palm trees with a subsequent decrease in forage crop production. This is a serious problem for local farmers who have tried to resolve it by removing mature palms, seedlings and young individuals. Within these conditions, is coviability between the babassu palm tree and society possible? Our work consisted in developing tools and methods with the aim of producing knowledge and providing answers to this issue within a given territory. To understand the eco-socio-system, we have explored the available knowledge in the literature, produced specific field data, tools and methods such as mathematical modeling (dynamics of the palm tree population) and remote sensing (land use analysis thanks to Landsat high-resolution images and automatic detection of mature palm trees using Pleiades and GeoEye very high-resolution images). This multidisciplinary research in progress has already given us a good overview of the current situation of this eco-socio-system, enabling us to consider the best way to ensure its sustainability.

Published
2019
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3. A stage-structured hierarchical Bayes model for the babassu palm tree population dynamics – Estimated from anthropogenic open area data sets

Author

Patrice Loisel, Danielle Mitja, Bénédicte Fontez, Alessio Moreira dos Santos, Thérèse Libourel, Nikolay Sirakov, Mathématiques, Informatique et STatistique pour l'Environnement et l'Agronomie (MISTEA), Institut National de la Recherche Agronomique (INRA)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), UMR 228 Espace-Dev, Espace pour le développement, Institut de Recherche pour le Développement (IRD)-Université de Perpignan Via Domitia (UPVD)-Avignon Université (AU)-Université de La Réunion (UR)-Université de Montpellier (UM)-Université de Guyane (UG)-Université des Antilles (UA), Université de Montpellier (UM), SARH – Instituto Ambiental e de Recursos Hídricos, Universidade Federal Rural da Amazônia (UFRA), This research work has been accomplished as a part of the Open Science research project (under the reference ID 1403-026) financed by the Agropolis Foundation and by the French National Institute of Agronomical Research (INRA) and Montpellier SupAgro., Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de la Recherche Agronomique (INRA), Université de Guyane (UG)-Université des Antilles (UA)-Institut de Recherche pour le Développement (IRD)-Université de Perpignan Via Domitia (UPVD)-Avignon Université (AU)-Université de La Réunion (UR)-Université de Montpellier (UM), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA), and Université des Antilles (UA)-Université de Guyane (UG)-Université de Montpellier (UM)-Université de La Réunion (UR)-Avignon Université (AU)-Université de Perpignan Via Domitia (UPVD)-Institut de Recherche pour le Développement (IRD)

Subjects
0106 biological sciences, Population dynamics, Population, Bayesian statistics, palmier, 010603 evolutionary biology, 01 natural sciences, Bottleneck, Bayes' theorem, modèle mathématique, Deforestation, [MATH.MATH-ST]Mathematics [math]/Statistics [math.ST], Attalea speciosa, population dynamics, mathematical modelling, education, estimation statistique, education.field_of_study, Mathematical modelling, biology, Amazon rainforest, Agroforestry, 010604 marine biology & hydrobiology, Ecological Modeling, 15. Life on land, biology.organism_classification, modèle bayésien, Tree (data structure), statistical estimation, dynamique des populations, Geography, palm tree, Babassu palm tree, mathematical model
Abstract

The babassu palm tree (Attalea speciosa Mart. ex Spreng.) is an endemic species of Amazon forests, and has social and economical impact/utility. Deforestation highlights this palm tree in anthropogenic open areas (pastures and cultivated fields). Simultaneously, knowledge concerning the sustainable functioning of the species within these manmade environments is sorely lacking: its life cycle is not well known, and its population dynamics remains unstudied. In this study, our objective was to generate a model of the population dynamics of the babassu palm tree, validated by in situ analysis, to understand how babassu, a forest species, adapts to pastureland and, under certain conditions, becomes invasive. We propose a random matrix model with aggregated variables based on the biological stages of the species as the input. The probabilities of the between-stage transition matrix were modelled using a Dirichlet-multinomial model with a hierarchy taking geographical organization, i.e. transect level, into account. The integration of prior information was formulated through a Bayesian approach. This Bayesian hierarchical matrix model enabled us to demonstrate a bottleneck in the population dynamics and a high year-dependent mortality rate at an early stage.

Published
2019
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