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1.
Trends Ecol Evol ; 2024 Jan 10.
Article in English | MEDLINE | ID: mdl-38212187

ABSTRACT

Trait-based ecology has improved our understanding of the functioning of organisms, communities, ecosystems, and beyond. However, its predictive ability remains limited as long as phenotypic integration and temporal dynamics are not considered. We highlight how the morphogenetic processes that shape the 3D development of a plant during its lifetime affect its performance. We show that the diversity of architectural traits allows us to go beyond organ-level traits in capturing the temporal and spatial dimensions of ecological niches and informing community assembly processes. Overall, we argue that consideration of multilevel topological, geometrical, and ontogenetic features provides a dynamic view of the whole-plant phenotype and a relevant framework for investigating phenotypic integration, plant adaptation and performance, and community structure and dynamics.

2.
PLoS One ; 19(1): e0296362, 2024.
Article in English | MEDLINE | ID: mdl-38206909

ABSTRACT

The wild species of the Coffea genus present a very wide morphological, genetic, and biochemical diversity. Wild species are recognized more resistant to diseases, pests, and environmental variations than the two species currently cultivated worldwide: C. arabica (Arabica) and C. canephora (Robusta). Consequently, wild species are now considered as a crucial resource for adapting cultivated coffee trees to climate change. Within the Coffea genus, 79 wild species are native to the Indian Ocean islands of Comoros, Mayotte, Mauritius, Réunion and Madagascar, out of a total of 141 taxa worldwide. Among them, a group of 9 species called "Baracoffea" are particularly atypical in their morphology and adaptation to the sandy soils of the dry deciduous forests of western Madagascar. Here, we have attempted to shed light on the evolutionary history of three Baracoffea species: C. ambongensis, C. boinensis and C. bissetiae by analyzing their chloroplast and nuclear genomes. We assembled the complete chloroplast genomes de novo and extracted 28,800 SNP (Single Nucleotide Polymorphism) markers from the nuclear genomes. These data were used for phylogenetic analysis of Baracoffea with Coffea species from Madagascar and Africa. Our new data support the monophyletic origin of Baracoffea within the Coffea of Madagascar, but also reveal a divergence with a sister clade of four species: C. augagneurii, C. ratsimamangae, C. pervilleana and C. Mcphersonii (also called C. vohemarensis), belonging to the Subterminal botanical series and living in dry or humid forests of northern Madagascar. Based on a bioclimatic analysis, our work suggests that Baracoffea may have diverged from a group of Malagasy Coffea from northern Madagascar and adapted to the specific dry climate and low rainfall of western Madagascar. The genomic data generated in the course of this work will contribute to the understanding of the adaptation mechanisms of these particularly singular species.


Subject(s)
Biological Evolution , Coffea , Phylogeny , Madagascar , Indian Ocean Islands , Chloroplasts , Coffea/genetics
3.
Database (Oxford) ; 20202020 11 20.
Article in English | MEDLINE | ID: mdl-33216899

ABSTRACT

Coffee is a beverage enjoyed by millions of people worldwide and an important commodity for millions of people. Beside the two cultivated species (Coffea arabica and Coffea canephora), the 139 wild coffee species/taxa belonging to the Coffea genus are largely unknown to coffee scientists and breeders although these species may be crucial for future coffee crop development to face climate changes. Here we present the Wild Coffee Species database (WCSdb) hosted by Pl@ntNet platform (http://publish.plantnet-project.org/project/wildcofdb_en), providing information for 141 coffee species/taxa, for which 84 contain a photo gallery and 82 contain sequencing data (genotyping-by-sequencing, chloroplast or whole genome sequences). The objective of this database is to better understand and characterize the species (identification, morphology, biochemical compounds, genetic diversity and sequence data) in order to better protect and promote them. DATABASE URL: http://publish.plantnet-project.org/project/wildcofdb_en.


Subject(s)
Coffea , Coffea/genetics , Coffee , Humans , Sequence Analysis
4.
Ann Bot ; 126(4): 687-699, 2020 09 14.
Article in English | MEDLINE | ID: mdl-32756867

ABSTRACT

BACKGROUND AND AIMS: Using internal trophic pressure as a regulating variable to model the complex interaction loops between organogenesis, production of assimilates and partitioning in functional-structural models of plant growth has attracted increasing interest in recent years. However, this approach is hampered by the fact that internal trophic pressure is a non-measurable quantity that can be assessed only through model parametric estimation, for which the methodology is not straightforward, especially when the model is stochastic. METHODS: A stochastic GreenLab model of plant growth (called 'GL4') is developed with a feedback effect of internal trophic competition, represented by the ratio of biomass supply to demand (Q/D), on organogenesis. A methodology for its parameter estimation is presented and applied to a dataset of 15 two-year-old Coffea canephora trees. Based on the fitting results, variations in Q/D are reconstructed and analysed in relation to the estimated variations in organogenesis parameters. KEY RESULTS: Our stochastic retroactive model was able to simulate realistically the progressive set-up of young plant architecture and the branch pruning effect. Parameter estimation using real data for Coffea trees provided access to the internal trophic dynamics. These dynamics correlated with the organogenesis probabilities during the establishment phase. CONCLUSIONS: The model can satisfactorily reproduce the measured data, thus opening up promising avenues for further applying this original procedure to other experimental data. The framework developed can serve as a model-based toolkit to reconstruct the hidden internal trophic dynamics of plant growth.


Subject(s)
Coffea , Plant Development , Biomass , Computer Simulation , Models, Biological
5.
Ann Bot ; 126(5): 849-863, 2020 10 06.
Article in English | MEDLINE | ID: mdl-32303759

ABSTRACT

BACKGROUND AND AIMS: Like other clades, the Coffea genus is highly diversified on the island of Madagascar. The 66 endemic species have colonized various environments and consequently exhibit a wide diversity of morphological, functional and phenological features and reproductive strategies. The trends of interspecific trait variation, which stems from interactions between genetically defined species and their environment, still needed to be addressed for Malagasy coffee trees. METHODS: Data acquisition was done in the most comprehensive ex situ collection of Madagascan wild Coffea. The structure of endemic wild coffees maintained in an ex situ collection was explored in terms of morphological, phenological and functional traits. The environmental (natural habitat) effect was assessed on traits in species from distinct natural habitats. Phylogenetic signal (Pagel's λ, Blomberg's K) was used to quantify trait proximities among species according to their phylogenetic relatedness. KEY RESULTS: Despite the lack of environmental difference in the ex situ collection, widely diverging phenotypes were observed. Phylogenetic signal was found to vary greatly across and even within trait categories. The highest values were exhibited by the ratio of internode mass to leaf mass, the length of the maturation phase and leaf dry matter content (ratio of dry leaf mass to fresh leaf mass). By contrast, traits weakly linked to phylogeny were either constrained by the original natural environment (leaf size) or under selective pressures (phenological traits). CONCLUSIONS: This study gives insight into complex patterns of trait variability found in an ex situ collection, and underlines the opportunities offered by living ex situ collections for research characterizing phenotypic variation.


Subject(s)
Coffee , Plant Leaves , Islands , Madagascar , Phenotype , Phylogeny
6.
AoB Plants ; 10(4): ply045, 2018 Aug.
Article in English | MEDLINE | ID: mdl-30151094

ABSTRACT

Knowledge of plant architecture allows retrospective study of plant development, hence provides powerful tools, through modelling and simulation, to link this development with environmental constraints, and then predict its response to global change. The present study aims to determine some of the main endogenous and exogenous variables driving the architectural development of three North American conifers. We measured architectural traits retrospectively on the trunk, branches and twigs of whole tree crowns for each species: annual shoot length (ASL), needle length, branching patterns and reproduction organs (male and female). We fitted a partial least square (PLS) regression to explain each architectural trait with respect to topological, ontogenic and climatic variables. Results showed a significant weight of these three groups of variables for previous and current year, corresponding, respectively, to organogenesis and elongation. Topological and ontogenic variables had the greatest weight in models. Particularly, all architectural traits were strongly correlated with ASL. We highlighted a negative architectural response of two species to higher than average temperatures, whereas the third one took advantage of these higher temperatures to some degree. Tree architectural development weekly but significantly improved with higher precipitation. Our study underlines the strong weight of topology and ontogeny in tree growth patterns at twig and branch scales. The correlation between ASL and other tree architectural traits should be integrated into architectural development models. Climate variables are secondary in importance at the twig scale. However, interannual climate variations influence all axis categories and branching orders and therefore significantly impact crown development as a whole. This latter impact may increase with climate change, especially as climate affects architectural traits over at least 2 years, through organogenesis and elongation.

7.
Ann Bot ; 121(7): 1397-1410, 2018 06 08.
Article in English | MEDLINE | ID: mdl-29596559

ABSTRACT

Background and aims: For a given genotype, the observed variability of tree forms results from the stochasticity of meristem functioning and from changing and heterogeneous environmental factors affecting biomass formation and allocation. In response to climate change, trees adapt their architecture by adjusting growth processes such as pre- and neoformation, as well as polycyclic growth. This is the case for the teak tree. The aim of this work was to adapt the plant model, GreenLab, in order to take into consideration both these processes using existing data on this tree species. Methods: This work adopted GreenLab formalism based on source-sink relationships at organ level that drive biomass production and partitioning within the whole plant over time. The stochastic aspect of phytomer production can be modelled by a Bernoulli process. The teak model was designed, parameterized and analysed using the architectural data from 2- to 5-year-old teak trees in open field stands. Key results: Growth and development parameters were identified, fitting the observed compound organic series with the theoretical series, using generalized least squares methods. Phytomer distributions of growth units and branching pattern varied depending on their axis category, i.e. their physiological age. These emerging properties were in accordance with the observed growth patterns and biomass allocation dynamics during a growing season marked by a short dry season. Conclusions: Annual growth patterns observed on teak, including shoot pre- and neoformation and polycyclism, were reproduced by the new version of the GreenLab model. However, further updating is discussed in order to ensure better consideration of radial variation in basic specific gravity of wood. Such upgrading of the model will enable teak ideotypes to be defined for improving wood production in terms of both volume and quality.


Subject(s)
Lamiaceae/anatomy & histology , Plant Leaves/growth & development , Trees/anatomy & histology , Biomass , Lamiaceae/growth & development , Lamiaceae/metabolism , Plant Leaves/metabolism , Stochastic Processes , Trees/growth & development , Trees/metabolism
8.
J Exp Bot ; 62(15): 5283-96, 2011 Nov.
Article in English | MEDLINE | ID: mdl-21841174

ABSTRACT

Developmental plasticity, the acclimation of plants to their local environment, is known to be crucial for the fitness of perennial organisms such as trees. However, deciphering the many possible developmental and environmental influences involved in such plasticity in natural conditions requires dedicated statistical models integrating developmental phases, environmental factors, and interindividual heterogeneity. These models should be able to analyse retrospective data (number of leaves or length of annual shoots along the main stem in the present case). In this study Markov switching linear mixed models were applied to the analysis of the developmental plasticity of walnut saplings during the establishment phase in a mixed Mediterranean forest. In the Markov switching linear mixed models estimated from walnut data sets, the underlying Markov chain represents both the succession and lengths of growth phases, while the linear mixed models represent both the influence of climatic factors and interindividual heterogeneity within each growth phase. On the basis of these integrative statistical models, it is shown that walnut saplings have an opportunistic mode of development that is primarily driven by the changing light environment. In particular, light availability explains the ability of a tree to reach a phase of strong growth where the first branches can appear. It is also shown that growth fluctuation amplitudes in response to climatic factors increased while interindividual heterogeneity decreased during tree development.


Subject(s)
Climate , Juglans/growth & development , Light , Juglans/radiation effects , Markov Chains
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