Improving C4 photosynthesis to increase productivity under optimal and suboptimal conditions.

Although improving photosynthetic efficiency is widely recognized as an underutilized strategy to increase crop yields, research in this area is strongly biased towards species with C3 photosynthesis relative to C4 species. Here, we outline potential strategies for improving C4 photosynthesis to increase yields in crops by reviewing the major bottlenecks limiting the C4 NADP-malic enzyme pathway under optimal and suboptimal conditions. Recent experimental results demonstrate that steady-state C4 photosynthesis under non-stressed conditions can be enhanced by increasing Rubisco content or electron transport capacity, both of which may also stimulate CO2 assimilation at supraoptimal temperatures. Several additional putative bottlenecks for photosynthetic performance under drought, heat, or chilling stress or during photosynthetic induction await further experimental verification. Based on source-sink interactions in maize, sugarcane, and sorghum, alleviating these photosynthetic bottlenecks during establishment and growth of the harvestable parts are likely to improve yield. The expected benefits are also shown to be augmented by the increasing trend in planting density, which increases the impact of photosynthetic source limitation on crop yields

Subtle variation in shade avoidance responses may have profound consequences for plant competitiveness

Background and Aims: Although phenotypic plasticity has been shown to be beneficial for plant competitiveness for light, there is limited knowledge on how variation in these plastic responses plays a role in determining competitiveness. Methods: A combination of detailed plant experiments and functional–structural plant (FSP) modelling was used that captures the complex dynamic feedback between the changing plant phenotype and the within-canopy light environment in time and 3-D space. Leaf angle increase (hyponasty) and changes in petiole elongation rates in response to changes in the ratio between red and far-red light, two important shade avoidance responses in Arabidopsis thaliana growing in dense population stands, were chosen as a case study for plant plasticity. Measuring and implementing these responses into an FSP model allowed simulation of plant phenotype as an emergent property of the underlying growth and response mechanisms. Key Results: Both the experimental and model results showed that substantial differences in competitiveness may arise between genotypes with only marginally different hyponasty or petiole elongation responses, due to the amplification of plant growth differences by small changes in plant phenotype. In addition, this study illustrated that strong competitive responses do not necessarily have to result in a tragedy of the commons; success in competition at the expense of community performance. Conclusions: Together, these findings indicate that selection pressure could probably have played a role in fine-tuning the sensitive shade avoidance responses found in plants. The model approach presented here provides a novel tool to analyse further how natural selection could have acted on the evolution of plastic responses

Understanding and optimizing species mixtures using functional–structural plant modelling

Plant species mixtures improve productivity over monocultures by exploiting species complementarities for resource capture in time and space. Complementarity results in part from competition avoidance responses that maximize resource capture and growth of individual plants. Individual organs accommodate to local resource levels, e.g. with regard to nitrogen content and photosynthetic capacity or by size (e.g. shade avoidance). As a result, the resource acquisition in time and space is improved and performance of the community as a whole is increased. Modelling is needed to unravel the primary drivers and subsequent dynamics of complementary growth responses in mixtures. Here, we advocate using functional–structural plant (FSP) modelling to analyse the functioning of plant mixtures. In FSP modelling, crop performance is a result of the behaviour of the individual plants interacting through competitive and complementary resource acquisition. FSP models can integrate the interactions between structural and physiological plant responses to the local resource availability and strength of competition, which drive resource capture and growth of individuals in species mixtures. FSP models have the potential to accelerate mixed-species plant research, and thus support the development of knowledge that is needed to promote the use of mixtures towards sustainably increasing crop yields at acceptable input levels

Disentangling the effects of photosynthetically active radiation and red to far-red ratio on plant photosynthesis under canopy shading. A simulation study using a functional-structural plant model

Background and AimsShading by an overhead canopy (i.e., canopy shading) entails simultaneous changes in both photosynthetically active radiation (PAR) and red to far-red ratio (R:FR). As plant responses to PAR (e.g. changes in leaf photosynthesis) are different from responses to R:FR (e.g. changes in plant architecture), and these responses occur at both organ and plant levels, understanding plant photosynthesis responses to canopy shading needs separate analysis of responses to reductions in PAR and R:FR at different levels.MethodsIn a greenhouse experiment we subjected plants of woody perennial rose (Rosa hybrida) to different light treatments, and so separately quantified the effects of reductions in PAR and R:FR on leaf photosynthetic- and plant architectural traits. Using a functional-structural plant model, we separately quantified the effects of responses in these traits on plant photosynthesis, and evaluated the relative importance of changes of individual traits for plant photosynthesis under mild and heavy shading caused by virtual overhead canopies.Key ResultsModel simulations showed that the individual trait responses to canopy shading could have positive and negative effects on plant photosynthesis. Under mild canopy shading, trait responses to reduced R:FR on photosynthesis were generally negative and with a larger magnitude than effects of responses to reduced PAR. Conversely, under heavy canopy shading, the positive effects of trait responses to reduced PAR became dominant. The combined effects of low-R:FR responses and low-PAR responses on plant photosynthesis were not equal to the sum of the separate effects, indicating interactions between individual trait responses.ConclusionsOur simulation results indicate that under canopy shading, the relative importance of plant responses to PAR and R:FR for plant photosynthesis changes with shade levels. This suggests that the adaptive significance of plant plasticity responses to one shading factor depends on plant responses to the other

Ecological interactions shape the adaptive value of plant defence : Herbivore attack versus competition for light

Plants defend themselves against diverse communities of herbivorous insects. This requires an investment of limited resources, for which plants also compete with neighbours. The consequences of an investment in defence are determined by the metabolic costs of defence as well as indirect or ecological costs through interactions with other organisms. These ecological costs have a potentially strong impact on the evolution of defensive traits, but have proven to be difficult to quantify. We aimed to quantify the relative impact of the direct and indirect or ecological costs and benefits of an investment in plant defence in relation to herbivory and intergenotypic competition for light. Additionally, we evaluated how the benefits of plant defence balance its costs in the context of herbivory and intergenotypic competition. To this end, we utilised a functional-structural plant (FSP) model of Brassica nigra that simulates plant growth and development, morphogenesis, herbivory and plant defence. In the model, a simulated investment in defences affected plant growth by competing with other plant organs for resources and affected the level and distribution of herbivore damage. Our results show that the ecological costs of intergenotypic competition for light are highly detrimental to the fitness of defended plants, as it amplifies the size difference between defended and undefended plants. This leads to herbivore damage counteracting the effects of intergenotypic competition under the assumption that herbivore damage scales with plant size. Additionally, we show that plant defence relies on reducing herbivore damage rather than the dispersion of herbivore damage, which is only beneficial under high levels of herbivore damage. We conclude that the adaptive value of plant defence is highly dependent on ecological interactions and is predominantly determined by the outcome of competition for light.</p

Ecological significance of light quality in optimizing plant defence

Plants balance the allocation of resources between growth and defence to optimize fitness in a competitive environment. Perception of neighbour-detection cues, such as a low ratio of red to far-red (R:FR) radiation, activates a suite of shade-avoidance responses that include stem elongation and upward leaf movement, whilst simultaneously downregulating defence. This downregulation is hypothesized to benefit the plant either by mediating the growth-defence balance in favour of growth in high plant densities or, alternatively, by mediating defence of individual leaves such that those most photosynthetically productive are best protected. To test these hypotheses, we used a 3D functional–structural plant model of Brassica nigra that mechanistically simulates the interactions between plant architecture, herbivory, and the light environment. Our results show that plant-level defence expression is a strong determinant of plant fitness and that leaf-level defence mediation by R:FR can provide a fitness benefit in high densities. However, optimal plant-level defence expression does not decrease monotonically with plant density, indicating that R:FR mediation of defence alone is not enough to optimize defence between densities. Therefore, assessing the ecological significance of R:FR-mediated defence is paramount to better understand the evolution of this physiological linkage and its implications for crop breeding.</p

Inferring plant–plant interactions using remote sensing

Rapid technological advancements and increasing data availability have improved the capacity to monitor and evaluate Earth's ecology via remote sensing. However, remote sensing is notoriously ‘blind’ to fine-scale ecological processes such as interactions among plants, which encompass a central topic in ecology. Here, we discuss how remote sensing technologies can help infer plant–plant interactions and their roles in shaping plant-based systems at individual, community and landscape levels. At each of these levels, we outline the key attributes of ecosystems that emerge as a product of plant–plant interactions and could possibly be detected by remote sensing data. We review the theoretical bases, approaches and prospects of how inference of plant–plant interactions can be assessed remotely. At the individual level, we illustrate how close-range remote sensing tools can help to infer plant–plant interactions, especially in experimental settings. At the community level, we use forests to illustrate how remotely sensed community structure can be used to infer dominant interactions as a fundamental force in shaping plant communities. At the landscape level, we highlight how remotely sensed attributes of vegetation states and spatial vegetation patterns can be used to assess the role of local plant–plant interactions in shaping landscape ecological systems. Synthesis. Remote sensing extends the domain of plant ecology to broader and finer spatial scales, assisting to scale ecological patterns and search for generic rules. Robust remote sensing approaches are likely to extend our understanding of how plant–plant interactions shape ecological processes across scales—from individuals to landscapes. Combining these approaches with theories, models, experiments, data-driven approaches and data analysis algorithms will firmly embed remote sensing techniques into ecological context and open new pathways to better understand biotic interactions

Quantifying the effect of crop spatial arrangement on weed suppression using functional-structural plant modelling

Suppression of weed growth in a crop canopy can be enhanced by improving crop competitiveness. One way to achieve this is by modifying the crop planting pattern. In this study, we addressed the question to what extent a uniform planting pattern increases the ability of a crop to compete with weed plants for light compared to a random and a row planting pattern, and how this ability relates to crop and weed plant density as well as the relative time of emergence of the weed. To this end, we adopted the functional-structural plant modelling approach which allowed us to explicitly include the 3D spatial configuration of the crop-weed canopy and to simulate intra- and interspecific competition between individual plants for light. Based on results of simulated leaf area development, canopy photosynthesis and biomass growth of the crop, we conclude that differences between planting pattern were small, particularly if compared to the effects of relative time of emergence of the weed, weed density and crop density. Nevertheless, analysis of simulated weed biomass demonstrated that a uniform planting of the crop improved the weed-suppression ability of the crop canopy. Differences in weed suppressiveness between planting patterns were largest with weed emergence before crop emergence, when the suppressive effect of the crop was only marginal. With simultaneous emergence a uniform planting pattern was 8 and 15 % more competitive than a row and a random planting pattern, respectively. When weed emergence occurred after crop emergence, differences between crop planting patterns further decreased as crop canopy closure was reached early on regardless of planting pattern. We furthermore conclude that our modelling approach provides promising avenues to further explore crop-weed interactions and aid in the design of crop management strategies that aim at improving crop competitiveness with weeds.</p

Functional—structural plant modeling of plants and crops

Crop models have been instrumental in predicting yields in wide ranges of current and future environmental conditions. However, they encounter problems in representing spatial heterogeneity of a plant stand and the associated plant responses to local conditions, as well as in simulating the effects of specific plant traits, management choices that influence plant architecture and lighting regimes such as those in greenhouses. For such purposes, functional–structural plant (FSP) models have been developed, which simulate individual plants that interact with each other in 3D, with the changes in plant architecture feeding back on the distribution of environmental drivers that make them grow and develop (light, water, nutrients). In this chapter, the authors outline the purposes of FSP models, the components they need to have in order to serve the purposes mentioned above and give an account of recent applications of such models