Anaëlle Dambreville

Deciphering structural and temporal interplays during the architectural development of mango trees

Plant architecture is commonly defined by the adjacency of organs within the structure and their properties. Few studies consider the effect of endogenous temporal factors, namely phenological factors, on the establishment of plant architecture. This study hypothesized that, in addition to the effect of environmental factors, the observed plant architecture results from both endogenous structural and temporal components, and their interplays. Mango tree, which is characterized by strong phenological asynchronisms within and between trees and by repeated vegetative and reproductive flushes during a growing cycle, was chosen as a plant model. During two consecutive growing cycles, this study described vegetative and reproductive development of 20 trees submitted to the same environmental conditions. Four mango cultivars were considered to assess possible cultivar-specific patterns. Integrative vegetative and reproductive development models incorporating generalized linear models as components were built. These models described the occurrence, intensity, and timing of vegetative and reproductive development at the growth unit scale. This study showed significant interplays between structural and temporal components of plant architectural development at two temporal scales. Within a growing cycle, earliness of bud burst was highly and positively related to earliness of vegetative development and flowering. Between growing cycles, flowering growth units delayed vegetative development compared to growth units that did not flower. These interplays explained how vegetative and reproductive phenological asynchronisms within and between trees were generated and maintained. It is suggested that causation networks involving structural and temporal components may give rise to contrasted tree architectures.

Contribution of crop model structure, parameters and climate projections to uncertainty in climate change impact assessments

Climate change impact assessments are plagued with uncertainties from many sources, such as climate projections or the inadequacies in structure and parameters of the impact model. Previous studies tried to account for the uncertainty from one or two of these. Here, we developed a triple-ensemble probabilistic assessment using seven crop models, multiple sets of model parameters and eight contrasting climate projections together to comprehensively account for uncertainties from these three important sources. We demonstrated the approach in assessing climate change impact on barley growth and yield at Jokioinen, Finland in the Boreal climatic zone and Lleida, Spain in the Mediterranean climatic zone, for the 2050s. We further quantified and compared the contribution of crop model structure, crop model parameters and climate projections to the total variance of ensemble output using Analysis of Variance (ANOVA). Based on the triple-ensemble probabilistic assessment, the median of simulated yield change was -4% and +16%, and the probability of decreasing yield was 63% and 31% in the 2050s, at Jokioinen and Lleida, respectively, relative to 1981-2010. The contribution of crop model structure to the total variance of ensemble output was larger than that from downscaled climate projections and model parameters. The relative contribution of crop model parameters and downscaled climate projections to the total variance of ensemble output varied greatly among the seven crop models and between the two sites. The contribution of downscaled climate projections was on average larger than that of crop model parameters. This information on the uncertainty from different sources can be quite useful for model users to decide where to put the most effort when preparing or choosing models or parameters for impact analyses. We concluded that the triple-ensemble probabilistic approach that accounts for the uncertainties from multiple important sources provide more comprehensive information for quantifying uncertainties in climate change impact assessments as compared to the conventional approaches that are deterministic or only account for the uncertainties from one or two of the uncertainty sources.

Plant growth co-ordination in natura: a unique temperature-controlled law among vegetative and reproductive organs in mango

The impact of temperature on plant growth is usually studied on the leaves of annuals. We studied in natura the effect of temperature on the growth of three plant organs: the growth unit (GU) axis; its attached leaves, considering their position along the axis; and the inflorescence axis. Mango tree was chosen as plant model. Organ growth was measured at different seasons and elevations, permitting a range of temperatures overlapping the optimal range for mango growth. Four growth parameters were investigated: the final organ size, the duration of growth, the maximal absolute growth rate (AGRmax) and the relative growth rate at the time of AGRmax (RGRip). Temporal growth dependencies were found between the axis and its leaves, regardless of their positions. Size dependencies were revealed only between the GU axis and its proximal leaf. Strong effects of temperature on duration of growth and on RGRip were observed regardless of the organ studied. A common allometric coefficient linked duration of growth and RGRip of all organs although the intercepts for axes and leaves were different. These relationships strongly suggested that regardless of the physiological mechanisms subtending the growth dynamics, e.g. auto- vs heterotrophy, a common temperature-controlled allometric constraint is probably underlying the growth of all these organs in mango.

A Model of Leaf Coordination to Scale-Up Leaf Expansion from the Organ to the Canopy

The coordination of the growth of wheat organs highlights robust functional rules used to model the dynamics of wheat leaf growth at the phytomer and canopy scales in response to abiotic constraints. Process-based crop growth models are popular tools with which to analyze and understand the impact of crop management, genotype-by-environment interactions, or climate change. The ability to predict leaf area development is critical to predict crop growth, particularly under conditions of limited resources. Here, we aimed at deciphering growth coordination rules between wheat (Triticum aestivum) plant organs (i.e. between leaves within a stem, between laminae and sheaths, and between the mainstem and axillary tillers) to model the dynamics of canopy development. We found a unique relationship between laminae area and leaf rank for the mainstem and its tillers, which was robust across a range of sowing dates and plant densities. Robust relationships between laminae and sheath areas also were found, highlighting the tight control of organ growth within and between phytomers. These relationships identified at the phytomer scale were used to develop a simulation model of leaf area dynamics at the canopy level that was integrated in the wheat model SiriusQuality. The model was then evaluated using several independent experiments. The model accurately predicts leaf area dynamics under different scenarios of nitrogen and water limitations. It accounted for 85%, 64%, and 73% of the variability of the surface area of leaf cohorts, total leaf area index, and total green area index, respectively. The process-based model of the dynamics of leaf area described here is a key element to quantify the value of candidate traits for use in plant breeding and to project the impact of climate change on wheat growth.

Phenotyping oilseed rape growth-related traits and their responses to water deficit: the disturbing pot size effect

Following the recent development of high-throughput phenotyping platforms for plant research, the number of individual plants grown together in a same experiment has raised, sometimes at the expense of pot size. However, root restriction in excessively small pots affects plant growth and carbon partitioning, and may interact with other stresses targeted in these experiments. In work reported here, we investigated the interactive effects of pot size and soil water deficit on multiple growth-related traits from the cellular to the whole-plant scale in oilseed rape (Brassica napus L.). The effects of pot size on responses to water deficit and allometric relationships revealed strong, multilevel interactions between pot size and watering regime. Notably, water deficit increased the root:shoot ratio in large pots, but not in small pots. At the cellular scale, water deficit decreased epidermal leaf cell area in large pots, but not in small pots. These results were consistent with changes in the level of endoreduplication factor in leaf cells. Our study illustrates the disturbing interaction of pot size with water deficit and raises the need to carefully consider this factor in the frame of the current development of high-throughput phenotyping experiments.

Characterization of mango tree patchiness using a tree-segmentation/clustering approach

In functional-structural plant models, inferring latent levels of organization from data while accounting for both connections between levels and within-individual heterogeneity is a challenging task. Here, we develop an approach based on multiple change-point models. It aims at partitioning a heterogeneous tree into homogeneous subtrees of consequent sizes. While multiple change-point models for sequences have been studied in depth, their transposition to tree-indexed data remains unaddressed. Since optimal algorithms of multiple change-point models for sequences cannot be transposed to trees, we propose here an efficient heuristic for tree segmentation. The segmented subtrees are grouped in a post-processing phase since similar disjoint patches in the canopy are observed. Application of such models is illustrated in mango tree where subtrees are assimilated to plant patches and clusters of patches to patch types (e.g. vegetative, flowering or resting patch).