Functional–structural plant models: a growing paradigm for plant studies

A number of research groups in various areas of plant biology as well as computer science and applied mathematics have addressed modelling the spatiotemporal dynamics of growth and development of plants. This has resulted in development of functional–structural plant models (FSPMs). In FSPMs, the plant structure is always explicitly represented in terms of a network of elementary units. In this respect, FSPMs are different from more abstract models in which a simplified representation of the plant structure is frequently used (e.g. spatial density of leaves, total biomass, etc.). This key feature makes it possible to build modular models and creates avenues for efficient exchange of model components and experimental data. They are being used to deal with the complex 3-D structure of plants and to simulate growth and development occurring at spatial scales from cells to forest areas, and temporal scales from seconds to decades and many plant generations. The plant types studied also cover a broad spectrum, from algae to trees. This special issue of Annals of Botany features selected papers on FSPM topics such as models of morphological development, models of physical and biological processes, integrated models predicting dynamics of plants and plant communities, modelling platforms, methods for acquiring the 3-D structures of plants using automated measurements, and practical applications for agronomic purposes.     

Plant growth modelling and applications: the increasing importance of plant architecture in growth models

Background

Modelling plant growth allows us to test hypotheses and carry out virtual experiments concerning plant growth processes that could otherwise take years in field conditions. The visualization of growth simulations allows us to see directly and vividly the outcome of a given model and provides us with an instructive tool useful for agronomists and foresters, as well as for teaching. Functional–structural (FS) plant growth models are nowadays particularly important for integrating biological processes with environmental conditions in 3-D virtual plants, and provide the basis for more advanced research in plant sciences.

Scope

In this viewpoint paper, we ask the following questions. Are we modelling the correct processes that drive plant growth, and is growth driven mostly by sink or source activity? In current models, is the importance of soil resources (nutrients, water, temperature and their interaction with meristematic activity) considered adequately? Do classic models account for architectural adjustment as well as integrating the fundamental principles of development? Whilst answering these questions with the available data in the literature, we put forward the opinion that plant architecture and sink activity must be pushed to the centre of plant growth models. In natural conditions, sinks will more often drive growth than source activity, because sink activity is often controlled by finite soil resources or developmental constraints.

PMA06

This viewpoint paper also serves as an introduction to this Special Issue devoted to plant growth modelling, which includes new research covering areas stretching from cell growth to biomechanics. All papers were presented at the Second International Symposium on Plant Growth Modeling, Simulation, Visualization and Applications (PMA06), held in Beijing, China, from 13–17 November, 2006. Although a large number of papers are devoted to FS models of agricultural and forest crop species, physiological and genetic processes have recently been included and point the way to a new direction in plant modelling research.Key words: Biomechanics, carbon allocation, functional–structural plant models, meristem, nitrogen, phenotypic plasticity, root architecture, simulation, sink, source, PMA06     

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.     

A modelling framework to simulate foliar fungal epidemics using functional–structural plant models

Background and Aims

Sustainable agriculture requires the identification of new, environmentally responsible strategies of crop protection. Modelling of pathosystems can allow a better understanding of the major interactions inside these dynamic systems and may lead to innovative protection strategies. In particular, functional–structural plant models (FSPMs) have been identified as a means to optimize the use of architecture-related traits. A current limitation lies in the inherent complexity of this type of modelling, and thus the purpose of this paper is to provide a framework to both extend and simplify the modelling of pathosystems using FSPMs.

Methods

Different entities and interactions occurring in pathosystems were formalized in a conceptual model. A framework based on these concepts was then implemented within the open-source OpenAlea modelling platform, using the platform''s general strategy of modelling plant–environment interactions and extending it to handle plant interactions with pathogens. New developments include a generic data structure for representing lesions and dispersal units, and a series of generic protocols to communicate with objects representing the canopy and its microenvironment in the OpenAlea platform. Another development is the addition of a library of elementary models involved in pathosystem modelling. Several plant and physical models are already available in OpenAlea and can be combined in models of pathosystems using this framework approach.

Key Results

Two contrasting pathosystems are implemented using the framework and illustrate its generic utility. Simulations demonstrate the framework''s ability to simulate multiscaled interactions within pathosystems, and also show that models are modular components within the framework and can be extended. This is illustrated by testing the impact of canopy architectural traits on fungal dispersal.

Conclusions

This study provides a framework for modelling a large number of pathosystems using FSPMs. This structure can accommodate both previously developed models for individual aspects of pathosystems and new ones. Complex models are deconstructed into separate ‘knowledge sources’ originating from different specialist areas of expertise and these can be shared and reassembled into multidisciplinary models. The framework thus provides a beneficial tool for a potential diverse and dynamic research community.     

Dynamic root growth and architecture responses to limiting nutrient availability: linking physiological models and experimentation

In recent years the study of root phenotypic plasticity in response to sub-optimal environmental factors and the genetic control of these responses have received renewed attention. As a path to increased productivity, in particular for low fertility soils, several applied research projects worldwide target the improvement of crop root traits both in plant breeding and biotechnology contexts. To assist these tasks and address the challenge of optimizing root growth and architecture for enhanced mineral resource use, the development of realistic simulation models is of great importance. We review this research field from a modeling perspective focusing particularly on nutrient acquisition strategies for crop production on low nitrogen and low phosphorous soils. Soil heterogeneity and the dynamics of nutrient availability in the soil pose a challenging environment in which plants have to forage efficiently for nutrients in order to maintain their internal nutrient homeostasis throughout their life cycle. Mathematical models assist in understanding plant growth strategies and associated root phenes that have potential to be tested and introduced in physiological breeding programs. At the same time, we stress that it is necessary to carefully consider model assumptions and development from a whole plant-resource allocation perspective and to introduce or refine modules simulating explicitly root growth and architecture dynamics through ontogeny with reference to key factors that constrain root growth. In this view it is important to understand negative feedbacks such as plant–plant competition. We conclude by briefly touching on available and developing technologies for quantitative root phenotyping from lab to field, from quantification of partial root profiles in the field to 3D reconstruction of whole root systems. Finally, we discuss how these approaches can and should be tightly linked to modeling to explore the root phenome.     

植物间正相互作用对种群动态和群落结构的影响:基于个体模型的研究进展

植物间的相互作用对种群动态和群落结构有着重要的影响。大量的野外实验已经揭示了正相互作用(互利)在群落中的普遍存在及其重要性。为了弥补野外实验方法的不足, 模型方法被越来越多地应用于正相互作用及其生态学效应的研究中。该文基于个体模型研究, 探讨了植物间正相互作用对种群动态和群落结构的影响。介绍了植物间正相互作用的定义和发生机制、植物间相互作用与环境梯度的关系。正相互作用是指发生在相邻的植物个体之间, 至少对其中一个个体有益的相互作用。植物通过直接(生境改善或资源富集)或间接(协同防御等)作用使局部环境有利于邻体而发生正相互作用。胁迫梯度假说认为互利的强度或重要性随着环境胁迫度的增加而增加, 但是越来越多的经验研究认为胁迫梯度假说需要改进。以网格模型和影响域模型为例, 介绍了基于个体的植物间相互作用模型方法。基于个体模型, 对近年来国内外正相互作用对种群时间动态(如生物量-密度关系)、空间分布格局和群落结构(如群落生物量-物种丰富度关系)影响的研究进行了总结。指出未来的研究应集中在对正相互作用概念和机制的理解, 新的模型, 新的种群、群落, 甚至生态系统问题, 以及在全球变化背景下进行相关的研究。     

An approach to multiscale modelling with graph grammars

Background and Aims

Functional–structural plant models (FSPMs) simulate biological processes at different spatial scales. Methods exist for multiscale data representation and modification, but the advantages of using multiple scales in the dynamic aspects of FSPMs remain unclear. Results from multiscale models in various other areas of science that share fundamental modelling issues with FSPMs suggest that potential advantages do exist, and this study therefore aims to introduce an approach to multiscale modelling in FSPMs.

Methods

A three-part graph data structure and grammar is revisited, and presented with a conceptual framework for multiscale modelling. The framework is used for identifying roles, categorizing and describing scale-to-scale interactions, thus allowing alternative approaches to model development as opposed to correlation-based modelling at a single scale. Reverse information flow (from macro- to micro-scale) is catered for in the framework. The methods are implemented within the programming language XL.

Key Results

Three example models are implemented using the proposed multiscale graph model and framework. The first illustrates the fundamental usage of the graph data structure and grammar, the second uses probabilistic modelling for organs at the fine scale in order to derive crown growth, and the third combines multiscale plant topology with ozone trends and metabolic network simulations in order to model juvenile beech stands under exposure to a toxic trace gas.

Conclusions

The graph data structure supports data representation and grammar operations at multiple scales. The results demonstrate that multiscale modelling is a viable method in FSPM and an alternative to correlation-based modelling. Advantages and disadvantages of multiscale modelling are illustrated by comparisons with single-scale implementations, leading to motivations for further research in sensitivity analysis and run-time efficiency for these models.     

Comparison of plant and fungal gravitropic responses using imitational modelling

The mechanisms of gravity perception are still hypothetical, but there are sufficient data from experiments with plants to enable mathematical modelling to imitate the behaviour of gravitropic response systems. We have a much less complete picture of gravitropic kinetics in agaric mushrooms. However, some existing mathematical models which imitate plant responses are in principle universal because their conceptual components are not limited to any specific cellular entities. In this work we have used such models to compare plant and fungal gravitropism, using recently acquired kinetic data from the agarics Coprinus cinereius and Flammulina velutipes. The results show striking similarities between plants and fungi. First, it is evident that the basic assumptions of the plant models are logically applicable to fungi. Secondly, the mechanism of bending is the same (differential growth of opposite flanks of the growing organ). Thirdly, the distribution of growth seems very similar: in both plants and fungi growth of the organ is most intensive just behind the apex and is almost absent at the apex and at the base. Fourthly, in both fungi and plants the gravitropic response exhibits a substantial time delay suggesting that many time-consuming processes are involved in reception, transduction and realization of gravitropic stimuli. Important differences in plant and fungal gravitropism kinetics were: (i) the agaric stem apex always returned to the vertical, whereas some plant organs show stable plagiogravitropic growth; (ii) inflections were usually seen in C. cinereus stem gravitropism time courses suggesting that a curvature compensation process delayed bending for a time; (iii) C. cinercus stems very rarely overshot or oscillated around the vertical although many plant subjects oscillate and the (limited) data for F. velutipes showed a single, exaggerated overshoot and oscillation. In this latter case, experimental modelling with parameters characteristic of a low level of perception improved the fit to the F. velutipes data, indicating that the two fungi may differ in this factor. Application of the plant models focused future research attention on the urgent need for data bearing on angle-response and acceleration–response relationships in fungi, and their detection–level thresholds for gravitational acceleration. Since the modelling also highlighted some fundamental kinetic differences between the only two fungi for which sufficient data are available at the moment, it is also clear that detailed observations need to be made of gravitropism kinetics in a larger number and wider range of fungi.     

Moderate plant–soil feedbacks have small effects on the biodiversity–productivity relationship: A field experiment

Plant–soil feedback (PSF) has gained attention as a mechanism promoting plant growth and coexistence. However, most PSF research has measured monoculture growth in greenhouse conditions. Translating PSFs into effects on plant growth in field communities remains an important frontier for PSF research. Using a 4‐year, factorial field experiment in Jena, Germany, we measured the growth of nine grassland species on soils conditioned by each of the target species (i.e., 72 PSFs). Plant community models were parameterized with or without these PSF effects, and model predictions were compared to plant biomass production in diversity–productivity experiments. Plants created soils that changed subsequent plant biomass by 40%. However, because they were both positive and negative, the average PSF effect was 14% less growth on “home” than on “away” soils. Nine‐species plant communities produced 29 to 37% more biomass for polycultures than for monocultures due primarily to selection effects. With or without PSF, plant community models predicted 28%–29% more biomass for polycultures than for monocultures, again due primarily to selection effects. Synthesis: Despite causing 40% changes in plant biomass, PSFs had little effect on model predictions of plant community biomass across a range of species richness. While somewhat surprising, a lack of a PSF effect was appropriate in this site because species richness effects in this study were caused by selection effects and not complementarity effects (PSFs are a complementarity mechanism). Our plant community models helped us describe several reasons that even large PSF may not affect plant productivity. Notably, we found that dominant species demonstrated small PSF, suggesting there may be selective pressure for plants to create neutral PSF. Broadly, testing PSFs in plant communities in field conditions provided a more realistic understanding of how PSFs affect plant growth in communities in the context of other species traits.     

Spatio-temporal development of forests – current trends in field methods and models

We present a critical review of current trends in research of spatio-temporal development of forests. The paper addresses (1) field methods for the development of spatially-explicit models of forest dynamics and their integration in models of forest dynamics, (2) strengths and limitations of traditional patch models versus spatially-explicit, individual-based models, and (3) the potential for moment-based methods in the analysis of forest dynamics. These topics are discussed with reference to their potential for solving open questions in the studies of forest dynamics. The study of spatio-temporal processes provides a link between pattern and process in plant communities, and plays a crucial role in understanding ecosystem dynamics. In the last decade, the development of spatially-explicit, individual-based models shifted the focus of forest dynamics modelling from the dynamics of discrete patches to the interactions among individual organisms, thus encapsulating the theory of “neighbourhood” dynamics. In turn, the stochastic properties and the complexity of spatially-explicit, individual-based models gave rise to the development of a new suite of so-called moment-based models. These new models describe the dynamics of individuals and of pairs of individuals in terms of their densities, thus directly capturing second-order information on spatial structure. So far, this approach has not been applied to forests; we indicate extensions needed for such applications. Moment-based models may be an important complement to spatially explicit individual-based models in developing a general spatial theory of forest dynamics. However, both kinds of models currently focus on fine scales, whereas a critical issue in forest dynamics is to understand the interaction of fine-scale processes with coarser-scale disturbances. To obtain a more complete picture of forest dynamics, the relevant links and interactions between fine-, intermediate-, and coarse-scale processes ought to be identified. Intensive links between modelling work and field studies designed across different scales are a promising means to create a new perspective on forest dynamics.     

Linking water stress effects on carbon partitioning by introducing a xylem circuit into L-PEACH

Background and Aims

Many physiological processes such as photosynthesis, respiration and transpiration can be strongly influenced by the diurnal patterns of within-tree water potential. Despite numerous experiments showing the effect of water potential on fruit-tree development and growth, there are very few models combining carbohydrate allocation with water transport. The aim of this work was to include a xylem circuit into the functional–structural L-PEACH model.

Methods

The xylem modelling was based on an electrical circuit analogy and the Hagen–Poisseuille law for hydraulic conductance. Sub-models for leaf transpiration, soil water potential and the soil–plant interface were also incorporated to provide the driving force and pathway for water flow. The model was assessed by comparing model outputs to field measurements and published knowledge.

Key Results

The model was able to simulate both the water uptake over a season and the effect of different irrigation treatments on tree development, growth and fruit yield.

Conclusions

This work opens the way to a new field of modelling where complex interactions between water transport, carbohydrate allocation and physiological functions can be simulated at the organ level and describe functioning and behaviour at the tree scale.     

Hydroponics: A Versatile System to Study Nutrient Allocation and Plant Responses to Nutrient Availability and Exposure to Toxic Elements

Hydroponic systems have been utilized as one of the standard methods for plant biology research and are also used in commercial production for several crops, including lettuce and tomato. Within the plant research community, numerous hydroponic systems have been designed to study plant responses to biotic and abiotic stresses. Here we present a hydroponic protocol that can be easily implemented in laboratories interested in pursuing studies on plant mineral nutrition.This protocol describes the hydroponic system set up in detail and the preparation of plant material for successful experiments. Most of the materials described in this protocol can be found outside scientific supply companies, making the set up for hydroponic experiments less expensive and convenient.The use of a hydroponic growth system is most advantageous in situations where the nutrient media need to be well controlled and when intact roots need to be harvested for downstream applications. We also demonstrate how nutrient concentrations can be modified to induce plant responses to both essential nutrients and toxic non-essential elements.     

Role of modelling in improving nutrient efficiency in cropping systems

The applicability of models in addressing resource management issues in agriculture has been widely promoted by the research community, yet examples of real impacts of such modelling efforts on current farming practices are rare. Nevertheless, simulation models can compliment traditional field experimentation in researching alternative management options. The first objective of this paper is, therefore, to provide four case study examples of where models were used to help research issues relating to improved nutrient efficiency in low-input cropping systems. The first two cases addressed strategies of augmenting traditional farming practices with small applications of chemical fertilizer (N and P). The latter two cases explicitly addressed the question of what plant genetic traits can be beneficial in low-nutrient farming systems. In each of these case studies, the APSIM (Agricultural Production Systems Simulator) systems model was used to simulate the impacts of alternative crop management systems.The question of whether simulation models can assist the research community in contributing to purposeful change in farming practice is also addressed. Recent experiences in Australia are reported where simulation models have contributed to practice change by farmers. Finally, current initiatives aimed at testing whether models can also contribute to improving the nutrient efficiency of smallholder farmers in the SAT are discussed.     

Development of arbuscular mycorrhizal biotechnology and industry: current achievements and bottlenecks

Advanced scientific knowledge on arbuscular mycorrhizal symbioses recently enhanced potential for implementation of mycorrhizal biotechnology in horticulture and agriculture plant production, landscaping, phytoremediation and other segments of the plant market. The advances consist in significant findings regarding:—new molecular detection tools for tracing inoculated fungi in the field;—the coexistence mechanisms of various fungi in the single root system;—new knowledge on in vitro physiology of the AM fungi grown in root organ cultures;—mechanisms of synergistic interactions with other microbes like PGPR or saprotrophic fungi; discovery of mycorrhiza supportive compounds such as strigolactones. Scientific knowledge has been followed by technological developments like novel formulations for liquid applications or seed coating, mycorrhiza stimulating compounds or new application modes. Still the missing components of biotechnology are appropriate, cheap, highly reproducible and effective methods for inocula purity testing and quality control. Also there is a weak traceability of the origin of the mycorrhizal fungi strains used in commercial inocula. Numerous poor quality products can still be found on the markets claiming effective formation mycorrhiza which have very low capacity to do so. These products usually rely in their effects on plant growth not on support of host plants via formation of effective mycorrhizal symbiosis but on fertilizing compounds added to products. There is growing number of enterprises producing mycorrhiza based inocula recently not only in developed world but increasingly in emerging markets. Also collaboration between private sector and scientific community has an improving trend as the development of private sector can fuel further research activities. Last but not least there is apparent growing pull of the market and increasing tendency of reduction of agrochemical inputs and employment of alternative strategies in planting and plant production. These circumstances support further developments of mycorrhizal inocula production and applications and maturation of the industry.     

Towards aspect-oriented functional--structural plant modelling

Background and Aims

Functional–structural plant models (FSPMs) are used to integrate knowledge and test hypotheses of plant behaviour, and to aid in the development of decision support systems. A significant amount of effort is being put into providing a sound methodology for building them. Standard techniques, such as procedural or object-oriented programming, are not suited for clearly separating aspects of plant function that criss-cross between different components of plant structure, which makes it difficult to reuse and share their implementations. The aim of this paper is to present an aspect-oriented programming approach that helps to overcome this difficulty.

Methods

The L-system-based plant modelling language L+C was used to develop an aspect-oriented approach to plant modelling based on multi-modules. Each element of the plant structure was represented by a sequence of L-system modules (rather than a single module), with each module representing an aspect of the element''s function. Separate sets of productions were used for modelling each aspect, with context-sensitive rules facilitated by local lists of modules to consider/ignore. Aspect weaving or communication between aspects was made possible through the use of pseudo-L-systems, where the strict-predecessor of a production rule was specified as a multi-module.

Key Results

The new approach was used to integrate previously modelled aspects of carbon dynamics, apical dominance and biomechanics with a model of a developing kiwifruit shoot. These aspects were specified independently and their implementation was based on source code provided by the original authors without major changes.

Conclusions

This new aspect-oriented approach to plant modelling is well suited for studying complex phenomena in plant science, because it can be used to integrate separate models of individual aspects of plant development and function, both previously constructed and new, into clearly organized, comprehensive FSPMs. In a future work, this approach could be further extended into an aspect-oriented programming language for FSPMs.     

Towards predictive resistance models for agrochemicals by combining chemical and protein similarity via proteochemometric modelling

Resistance to pesticides is an increasing problem in agriculture. Despite practices such as phased use and cycling of ‘orthogonally resistant’ agents, resistance remains a major risk to national and global food security. To combat this problem, there is a need for both new approaches for pesticide design, as well as for novel chemical entities themselves. As summarized in this opinion article, a technique termed ‘proteochemometric modelling’ (PCM), from the field of chemoinformatics, could aid in the quantification and prediction of resistance that acts via point mutations in the target proteins of an agent. The technique combines information from both the chemical and biological domain to generate bioactivity models across large numbers of ligands as well as protein targets. PCM has previously been validated in prospective, experimental work in the medicinal chemistry area, and it draws on the growing amount of bioactivity information available in the public domain. Here, two potential applications of proteochemometric modelling to agrochemical data are described, based on previously published examples from the medicinal chemistry literature.     

Modelling Plant Responses to Elevated CO2: How Important is Leaf Area Index?

BACKGROUND AND AIMS: The problem of increasing CO(2) concentration [CO(2)] and associated climate change has generated much interest in modelling effects of [CO(2)] on plants. While variation in growth and productivity is closely related to the amount of intercepted radiation, largely determined by leaf area index (LAI), effects of elevated [CO(2)] on growth are primarily via stimulation of leaf photosynthesis. Variability in LAI depends on climatic and growing conditions including [CO(2)] concentration and can be high, as is known for agricultural crops which are specifically emphasized in this report. However, modelling photosynthesis has received much attention and photosynthesis is often represented inadequately detailed in plant productivity models. Less emphasis has been placed on the modelling of leaf area dynamics, and relationships between plant growth, elevated [CO(2)] and LAI are not well understood. This Botanical Briefing aims at clarifying the relative importance of LAI for canopy assimilation and growth in biomass under conditions of rising [CO(2)] and discusses related implications for process-based modelling. MODEL: A simulation exercise performed for a wheat crop demonstrates recent experimental findings about canopy assimilation as affected by LAI and elevation of [CO(2)]. While canopy assimilation largely increases with LAI below canopy light saturation, effects on canopy assimilation of [CO(2)] elevation are less pronounced and tend to decline as LAI increases. Results from selected model-testing studies indicate that simulation of LAI is often critical and forms an important source of uncertainty in plant productivity models, particularly under conditions of limited resource supply. CONCLUSIONS: Progress in estimating plant growth and productivity under rising [CO(2)] is unlikely to be achieved without improving the modelling of LAI. This will depend on better understanding of the processes of substrate allocation, leaf area development and senescence, and the role of LAI in controlling plant adaptation to environmental changes.     

Gene-based modelling for rice: an opportunity to enhance the simulation of rice growth and development?

Process-based crop simulation models require employment of new knowledge for continuous improvement. To simulate growth and development of different genotypes of a given crop, most models use empirical relationships or parameters defined as genetic coefficients to represent the various cultivar characteristics. Such a loose introduction of different cultivar characteristics can result in bias within a simulation, which could potentially integrate to a high simulation error at the end of the growing season when final yield at maturity is predicted. Recent advances in genetics and biomolecular analysis provide important opportunities for incorporating genetic information into process-based models to improve the accuracy of the simulation of growth and development and ultimately the final yield. This improvement is especially important for complex applications of models. For instance, the effect of the climate change on the crop growth processes in the context of natural climatic and soil variability and a large range of crop management options (e.g., N management) make it difficult to predict the potential impact of the climate change on the crop production. Quantification of the interaction of the environmental variables with the management factors requires fine tuning of the crop models to consider differences among different genotypes. In this paper we present this concept by reviewing the available knowledge of major genes and quantitative trait loci (QTLs) for important traits of rice for improvement of rice growth modelling and further requirements. It is our aim to review the assumption of the adequacy of the available knowledge of rice genes and QTL information to be introduced into the models. Although the rice genome sequence has been completed, the development of gene-based rice models still requires additional information than is currently unavailable. We conclude that a multidiscipline research project would be able to introduce this concept for practical applications.     

The role of maintenance respiration in plant growth

Abstract Plant growth is the balance of photosynthetic gains and respiratory losses, and it is therefore essential to consider respiration in analyses of plant productivity. The partitioning of dark respiratory losses into two functional components, a growth component and a maintenance component, has proved useful. The growth loss is that associated with synthesis of new biomass while the maintenance loss is that associated with maintenance of existing biomass. Experimental evidence indicates that the respiratory cost of maintenance in herbaceous plants is about equal to the cost of growth over a growing season, with daily maintenace expenditures less important in the small, rapidly growing plant but increasing in significance as plant size increases and the relative growth rate decreases. Because it is such a large fraction of the total carbon budget of a plant, any variations in maintenance requirements may result in significant alterations in productivity. In the present work the theoretical and empirical bases of maintenance respiration are described: magnitudes of maintenance expenditures are summarized; and applications to models of plant growth and productivity are discussed. It is concluded that the costs of maintenance should be included in analyses of plant growth.     

Successes,failures, and opportunities in the practical application of drift-foraging models

Accurately measuring productive capacity in streams is challenging, and field methods have generally focused on the limiting role of physical habitat attributes (e.g. channel gradient, depth, velocity, substrate). Because drift-foraging models uniquely integrate the effects of both physical habitat (velocity and depth) and prey abundance (invertebrate drift) on energy intake for drift-feeding fishes, they provide a coherent and transferable framework for modelling individual growth that includes the effects of both physical habitat and biological production. Despite this, drift-foraging models have been slow to realize their potential in an applied context. Practical applications have been hampered by difficulties in predicting growth (rather than habitat choice), and scaling predictions of individual growth to reach scale habitat capacity, which requires modelling the partitioning of resources among individuals and depletion of drift through predation. There has also been a general failure of stream ecologists to adequately characterize spatial and temporal variation in invertebrate drift within and among streams, so that sources of variation in this key component of drift-foraging models remain poorly understood. Validation of predictions of habitat capacity have been patchy or lacking, until recent studies demonstrating strong relationships between drift flux, modeled Net Energy Intake, and fish biomass. Further advances in the practical application of drift-foraging models will require i) a better understanding of the factors that cause variation in drift, better approaches for modelling drift, and more standardized methods for characterizing it; ii) identification of simple diagnostic metrics that correlate strongly with more precise but time-consuming bioenergetic assessments of habitat quality; and iii) a better understanding of how variation in drift-foraging strategies are associated with other suites of co-evolved traits that ecologically differentiate taxa of drift-feeding salmonids.