Modelling fruit-temperature dynamics within apple tree crowns using virtual plants

Parameter estimation for functional-structural plant models when data are scarce: using multiple patterns for rejecting unsuitable parameter sets

BACKGROUND AND AIMS

Functional-structural plant (FSP) models provide insights into the complex interactions between plant architecture and underlying developmental mechanisms. However, parameter estimation of FSP models remains challenging. We therefore used pattern-oriented modelling (POM) to test whether parameterization of FSP models can be made more efficient, systematic and powerful. With POM, a set of weak patterns is used to determine uncertain parameter values, instead of measuring them in experiments or observations, which often is infeasible.

METHODS

We used an existing FSP model of avocado (Persea americana 'Hass') and tested whether POM parameterization would converge to an existing manual parameterization. The model was run for 10 000 parameter sets and model outputs were compared with verification patterns. Each verification pattern served as a filter for rejecting unrealistic parameter sets. The model was then validated by running it with the surviving parameter sets that passed all filters and then comparing their pooled model outputs with additional validation patterns that were not used for parameterization.

KEY RESULTS

POM calibration led to 22 surviving parameter sets. Within these sets, most individual parameters varied over a large range. One of the resulting sets was similar to the manually parameterized set. Using the entire suite of surviving parameter sets, the model successfully predicted all validation patterns. However, two of the surviving parameter sets could not make the model predict all validation patterns.

CONCLUSIONS

Our findings suggest strong interactions among model parameters and their corresponding processes, respectively. Using all surviving parameter sets takes these interactions into account fully, thereby improving model performance regarding validation and model output uncertainty. We conclude that POM calibration allows FSP models to be developed in a timely manner without having to rely on field or laboratory experiments, or on cumbersome manual parameterization. POM also increases the predictive power of FSP models.

Pattern-oriented modelling as a novel way to verify and validate functional-structural plant models: a demonstration with the annual growth module of avocado

Background and Aims

Functional-structural plant (FSP) models have been widely used to understand the complex interactions between plant architecture and underlying developmental mechanisms. However, to obtain evidence that a model captures these mechanisms correctly, a clear distinction must be made between model outputs used for calibration and thus verification, and outputs used for validation. In pattern-oriented modelling (POM), multiple verification patterns are used as filters for rejecting unrealistic model structures and parameter combinations, while a second, independent set of patterns is used for validation.

Methods

To test the potential of POM for FSP modelling, a model of avocado (Persea americana 'Hass') was developed. The model of shoot growth is based on a conceptual model, the annual growth module (AGM), and simulates photosynthesis and adaptive carbon allocation at the organ level. The model was first calibrated using a set of observed patterns from a published article. Then, for validation, model predictions were compared with a different set of empirical patterns from various field studies that were not used for calibration.

Key Results

After calibration, our model simultaneously reproduced multiple observed architectural patterns. The model then successfully predicted, without further calibration, the validation patterns. The model supports the hypothesis that carbon allocation can be modelled as being dependent on current organ biomass and sink strength of each organ type, and also predicted the observed developmental timing of the leaf sink-source transition stage.

Conclusions

These findings suggest that POM can help to improve the 'structural realism' of FSP models, i.e. the likelihood that a model reproduces observed patterns for the right reasons. Structural realism increases predictive power so that the response of an AGM to changing environmental conditions can be predicted. Accordingly, our FSP model provides a better but still parsimonious understanding of the mechanisms underlying known patterns of AGM growth.

Fine-Scale Microclimatic Variation Can Shape the Responses of Organisms to Global Change in Both Natural and Urban Environments

When predicting the response of organisms to global change, models use measures of climate at a coarse resolution from general circulation models or from downscaled regional models. Organisms, however, do not experience climate at such large scales. The climate heterogeneity over a landscape and how much of that landscape an organism can sample will determine ultimately the microclimates experienced by organisms. This past few decades has seen an important increase in the number of studies reporting microclimatic patterns at small scales. This synthesis intends to unify studies reporting microclimatic heterogeneity (mostly temperature) at various spatial scales, to infer any emerging trends, and to discuss the causes and consequences of such heterogeneity for organismal performance and with respect to changing land use patterns and climate. First, we identify the environmental drivers of heterogeneity across the various spatial scales that are pertinent to ectotherms. The thermal heterogeneity at the local and micro-scales is mostly generated by the architecture or the geometrical features of the microhabitat. Then, the thermal heterogeneity experienced by individuals is modulated by behavior. Second, we survey the literature to quantify thermal heterogeneity from the micro-scale up to the scale of a landscape in natural habitats. Despite difficulties in compiling studies that differ much in their design and aims, we found that there is as much thermal heterogeneity across micro-, local and landscape scales, and that the temperature range is large in general (>9 °C on average, and up to 26 °C). Third, we examine the extent to which urban habitats can be used to infer the microclimatic patterns of the future. Urban areas generate globally drier and warmer microclimatic patterns and recent evidence suggest that thermal traits of ectotherms are adapted to them. Fourth, we explore the interplay between microclimate heterogeneity and the behavioral thermoregulatory abilities of ectotherms in setting their overall performance. We used a random walk framework to show that the thermal heterogeneity allows a more precise behavioral thermoregulation and a narrower temperature distribution of the ectotherm compared to less heterogeneous microhabitats. Finally, we discuss the potential impacts of global change on the fine scale mosaics of microclimates. The amplitude of change may differ between spatial scales. In heterogeneous microhabitats, the amplitude of change at micro-scale, caused by atmospheric warming, can be substantial while it can be limited at the local and landscape scales. We suggest that the warming signal will influence species performance and biotic interactions by modulating the mosaic of microclimates.

Cross-scale modelling of transpiration from stomata via the leaf boundary layer

BACKGROUND AND AIMS

Leaf transpiration is a key parameter for understanding land surface-climate interactions, plant stress and plant structure–function relationships. Transpiration takes place at the microscale level, namely via stomata that are distributed discretely over the leaf surface with a very low surface coverage (approx. 0·2-5%). The present study aims to shed more light on the dependency of the leaf boundary-layer conductance (BLC) on stomatal surface coverage and air speed.

METHODS

An innovative three-dimensional cross-scale modelling approach was applied to investigate convective mass transport from leaves, using computational fluid dynamics. The gap between stomatal and leaf scale was bridged by including all these scales in the same computational model (10⁻⁵-10⁻¹ m), which implies explicitly modelling individual stomata.

KEY RESULTS

BLC was strongly dependent on stomatal surface coverage and air speed. Leaf BLC at low surface coverage ratios (CR), typical for stomata, was still relatively high, compared with BLC of a fully wet leaf (hypothetical CR of 100%). Nevertheless, these conventional BLCs (CR of 100%), as obtained from experiments or simulations on leaf models, were found to overpredict the convective exchange. In addition, small variations in stomatal CR were found to result in large variations in BLCs. Furthermore, stomata of a certain size exhibited a higher mass transfer rate at lower CRs.

CONCLUSIONS

The proposed cross-scale modelling approach allows us to increase our understanding of transpiration at the sub-leaf level as well as the boundary-layer microclimate in a way currently not feasible experimentally. The influence of stomatal size, aperture and surface density, and also flow-field parameters can be studied using the model, and prospects for further improvement of the model are presented. An important conclusion of the study is that existing measures of conductances (e.g. from artificial leaves) can be significantly erroneous because they do not account for microscopic stomata, but instead assume a uniform distribution of evaporation such as found for a fully-wet leaf. The model output can be used to correct or upgrade existing BLCs or to feed into higher-scale models, for example within a multiscale framework.

Influence of the variation of geometrical and topological traits on light interception efficiency of apple trees: sensitivity analysis and metamodelling for ideotype definition

BACKGROUND AND AIMS

The impact of a fruit tree's architecture on its performance is still under debate, especially with regard to the definition of varietal ideotypes and the selection of architectural traits in breeding programmes. This study aimed at providing proof that a modelling approach can contribute to this debate, by using in silico exploration of different combinations of traits and their consequences on light interception, here considered as one of the key parameters to optimize fruit tree production.

METHODS

The variability of organ geometrical traits, previously described in a bi-parental population, was used to simulate 1- to 5-year-old apple trees (Malus × domestica). Branching sequences along trunks observed during the first year of growth of the same hybrid trees were used to initiate the simulations, and hidden semi-Markov chains previously parameterized were used in subsequent years. Tree total leaf area (TLA) and silhouette to total area ratio (STAR) values were estimated, and a sensitivity analysis was performed, based on a metamodelling approach and a generalized additive model (GAM), to analyse the relative impact of organ geometry and lateral shoot types on STAR.

KEY RESULTS

A larger increase over years in TLA mean and variance was generated by varying branching along trunks than by varying organ geometry, whereas the inverse was observed for STAR, where mean values stabilized from year 3 to year 5. The internode length and leaf area had the highest impact on STAR, whereas long sylleptic shoots had a more significant effect than proleptic shoots. Although the GAM did not account for interactions, the additive effects of the geometrical factors explained >90% of STAR variation, but much less in the case of branching factors.

CONCLUSIONS

This study demonstrates that the proposed modelling approach could contribute to screening architectural traits and their relative impact on tree performance, here viewed through light interception. Even though trait combinations and antagonism will need further investigation, the approach opens up new perspectives for breeding and genetic selection to be assisted by varietal ideotype definition.

Using functional–structural plant models to study, understand and integrate plant development and ecophysiology

Functional–structural plant models (FSPMs) explore and integrate relationships between a plant’s structure and processes that underlie its growth and development. In recent years, the range of topics being addressed by scientists interested in functional–structural plant modelling has expanded greatly. FSPM techniques are now being used to dynamically simulate growth and development occurring at the microscopic scale involving cell division in plant meristems to the macroscopic scales of whole plants and plant communities. The plant types studied also cover a broad spectrum from algae to trees. FSPM is highly interdisciplinary and involves scientists with backgrounds in plant physiology, plant anatomy, plant morphology, mathematics, computer science, cellular biology, ecology and agronomy. This special issue of Annals of Botany features selected papers that provide examples of comprehensive functional–structural models, models of key processes such as partitioning of resources, software for modelling plants and plant environments, data acquisition and processing techniques and applications of functional–structural plant models for agronomic purposes.