Plants cope with fluctuating light by frequency-dependent nonphotochemical quenching and cyclic electron transport.

In natural environments, plants are exposed to rapidly changing light. Maintaining photosynthetic efficiency while avoiding photodamage requires equally rapid regulation of photoprotective mechanisms. We asked what the operation frequency range of regulation is in which plants can efficiently respond to varying light. Chlorophyll fluorescence, P700, plastocyanin, and ferredoxin responses of wild-types Arabidopsis thaliana were measured in oscillating light of various frequencies. We also investigated the npq1 mutant lacking violaxanthin de-epoxidase, the npq4 mutant lacking PsbS protein, and the mutants crr2-2, and pgrl1ab impaired in different pathways of the cyclic electron transport. The fastest was the PsbS-regulation responding to oscillation periods longer than 10 s. Processes involving violaxanthin de-epoxidase dampened changes in chlorophyll fluorescence in oscillation periods of 2 min or longer. Knocking out the PGR5/PGRL1 pathway strongly reduced variations of all monitored parameters, probably due to congestion in the electron transport. Incapacitating the NDH-like pathway only slightly changed the photosynthetic dynamics. Our observations are consistent with the hypothesis that nonphotochemical quenching in slow light oscillations involves violaxanthin de-epoxidase to produce, presumably, a largely stationary level of zeaxanthin. We interpret the observed dynamics of photosystem I components as being formed in slow light oscillations partially by thylakoid remodeling that modulates the redox rates.

Stomatal conductance tracks soil-to-leaf hydraulic conductance in faba bean and maize during soil drying.

Although regulation of stomatal conductance is widely assumed to be the most important plant response to soil drying, the picture is incomplete when hydraulic conductance from soil to the leaf, upstream of the stomata, is not considered. Here, we investigated to what extent soil drying reduces the conductance between soil and leaf, whether this reduction differs between species, how it affects stomatal regulation, and where in the hydraulic pathway it occurs. To this end, we noninvasively and continuously measured the total root water uptake rate, soil water potential, leaf water potential, and stomatal conductance of 4-week-old, pot-grown maize (Zea mays) and faba bean (Vicia faba) plants during 4 days of water restriction. In both species, the soil-plant conductance, excluding stomatal conductance, declined exponentially with soil drying and was reduced to 50% above a soil water potential of -0.1 MPa, which is far from the permanent wilting point. This loss of conductance has immediate consequences for leaf water potential and the associated stomatal regulation. Both stomatal conductance and soil-plant conductance declined at a higher rate in faba bean than in maize. Estimations of the water potential at the root surface and an incomplete recovery 22 h after rewatering indicate that the loss of conductance, at least partly, occurred inside the plants, for example, through root suberization or altered aquaporin gene expression. Our findings suggest that differences in the stomatal sensitivity among plant species are partly explained by the sensitivity of root hydraulic conductance to soil drying.

Deep-water uptake under drought improved due to locally increased root conductivity in maize, but not in faba bean.

Moderate soil drying can cause a strong decrease in the soil-root system conductance. The resulting impact on root water uptake depends on the spatial distribution of the altered conductance relatively to remaining soil water resources, which is largely unknown. Here, we analyzed the vertical distribution of conductance across root systems using a novel, noninvasive sensor technology on pot-grown faba bean and maize plants. Withholding water for 4 days strongly enhanced the vertical gradient in soil water potential. Therefore, roots in upper and deeper soil layers were affected differently: In drier, upper layers, root conductance decreased by 66%-72%, causing an amplification of the drop in leaf water potential. In wetter, deeper layers, root conductance increased in maize but not in faba bean. The consequently facilitated deep-water uptake in maize contributed up to 21% of total water uptake at the end of the measurement. Analysis of root length distributions with MRI indicated that the locally increased conductance was mainly caused by an increased intrinsic conductivity and not by additional root growth. Our findings show that plants can partly compensate for a reduced root conductance in upper, drier soil layers by locally increasing root conductivity in wetter layers, thereby improving deep-water uptake.

A meta-analysis of responses of C3 plants to atmospheric CO2 : dose-response curves for 85 traits ranging from the molecular to the whole-plant level.

Generalised dose-response curves are essential to understand how plants acclimate to atmospheric CO2 . We carried out a meta-analysis of 630 experiments in which C3 plants were experimentally grown at different [CO2 ] under relatively benign conditions, and derived dose-response curves for 85 phenotypic traits. These curves were characterised by form, plasticity, consistency and reliability. Considered over a range of 200-1200 µmol mol-1 CO2 , some traits more than doubled (e.g. area-based photosynthesis; intrinsic water-use efficiency), whereas others more than halved (area-based transpiration). At current atmospheric [CO2 ], 64% of the total stimulation in biomass over the 200-1200 µmol mol-1 range has already been realised. We also mapped the trait responses of plants to [CO2 ] against those we have quantified before for light intensity. For most traits, CO2 and light responses were of similar direction. However, some traits (such as reproductive effort) only responded to light, others (such as plant height) only to [CO2 ], and some traits (such as area-based transpiration) responded in opposite directions. This synthesis provides a comprehensive picture of plant responses to [CO2 ] at different integration levels and offers the quantitative dose-response curves that can be used to improve global change simulation models.

Plant functional traits have globally consistent effects on competition.

Phenotypic traits and their associated trade-offs have been shown to have globally consistent effects on individual plant physiological functions, but how these effects scale up to influence competition, a key driver of community assembly in terrestrial vegetation, has remained unclear. Here we use growth data from more than 3 million trees in over 140,000 plots across the world to show how three key functional traits--wood density, specific leaf area and maximum height--consistently influence competitive interactions. Fast maximum growth of a species was correlated negatively with its wood density in all biomes, and positively with its specific leaf area in most biomes. Low wood density was also correlated with a low ability to tolerate competition and a low competitive effect on neighbours, while high specific leaf area was correlated with a low competitive effect. Thus, traits generate trade-offs between performance with competition versus performance without competition, a fundamental ingredient in the classical hypothesis that the coexistence of plant species is enabled via differentiation in their successional strategies. Competition within species was stronger than between species, but an increase in trait dissimilarity between species had little influence in weakening competition. No benefit of dissimilarity was detected for specific leaf area or wood density, and only a weak benefit for maximum height. Our trait-based approach to modelling competition makes generalization possible across the forest ecosystems of the world and their highly diverse species composition.

The global spectrum of plant form and function.

Earth is home to a remarkable diversity of plant forms and life histories, yet comparatively few essential trait combinations have proved evolutionarily viable in today's terrestrial biosphere. By analysing worldwide variation in six major traits critical to growth, survival and reproduction within the largest sample of vascular plant species ever compiled, we found that occupancy of six-dimensional trait space is strongly concentrated, indicating coordination and trade-offs. Three-quarters of trait variation is captured in a two-dimensional global spectrum of plant form and function. One major dimension within this plane reflects the size of whole plants and their parts; the other represents the leaf economics spectrum, which balances leaf construction costs against growth potential. The global plant trait spectrum provides a backdrop for elucidating constraints on evolution, for functionally qualifying species and ecosystems, and for improving models that predict future vegetation based on continuous variation in plant form and function.

Global patterns of biomass allocation in woody species with different tolerances of shade and drought: evidence for multiple strategies.

The optimal partitioning theory predicts that plants of a given species acclimate to different environments by allocating a larger proportion of biomass to the organs acquiring the most limiting resource. Are similar patterns found across species adapted to environments with contrasting levels of abiotic stress? We tested the optimal partitioning theory by analysing how fractional biomass allocation to leaves, stems and roots differed between woody species with different tolerances of shade and drought in plants of different age and size (seedlings to mature trees) using a global dataset including 604 species. No overarching biomass allocation patterns at different tolerance values across species were found. Biomass allocation varied among functional types as a result of phenological (deciduous vs evergreen broad-leaved species) and broad phylogenetical (angiosperms vs gymnosperms) differences. Furthermore, the direction of biomass allocation responses between tolerant and intolerant species was often opposite to that predicted by the optimal partitioning theory. We conclude that plant functional type is the major determinant of biomass allocation in woody species. We propose that interactions between plant functional type, ontogeny and species-specific stress tolerance adaptations allow woody species with different shade and drought tolerances to display multiple biomass partitioning strategies.

An integrated framework of plant form and function: the belowground perspective.

Plant trait variation drives plant function, community composition and ecosystem processes. However, our current understanding of trait variation disproportionately relies on aboveground observations. Here we integrate root traits into the global framework of plant form and function. We developed and tested an overarching conceptual framework that integrates two recently identified root trait gradients with a well-established aboveground plant trait framework. We confronted our novel framework with published relationships between above- and belowground trait analogues and with multivariate analyses of above- and belowground traits of 2510 species. Our traits represent the leaf and root conservation gradients (specific leaf area, leaf and root nitrogen concentration, and root tissue density), the root collaboration gradient (root diameter and specific root length) and the plant size gradient (plant height and rooting depth). We found that an integrated, whole-plant trait space required as much as four axes. The two main axes represented the fast-slow 'conservation' gradient on which leaf and fine-root traits were well aligned, and the 'collaboration' gradient in roots. The two additional axes were separate, orthogonal plant size axes for height and rooting depth. This perspective on the multidimensional nature of plant trait variation better encompasses plant function and influence on the surrounding environment.

Root traits as drivers of plant and ecosystem functioning: current understanding, pitfalls and future research needs.

The effects of plants on the biosphere, atmosphere and geosphere are key determinants of terrestrial ecosystem functioning. However, despite substantial progress made regarding plant belowground components, we are still only beginning to explore the complex relationships between root traits and functions. Drawing on the literature in plant physiology, ecophysiology, ecology, agronomy and soil science, we reviewed 24 aspects of plant and ecosystem functioning and their relationships with a number of root system traits, including aspects of architecture, physiology, morphology, anatomy, chemistry, biomechanics and biotic interactions. Based on this assessment, we critically evaluated the current strengths and gaps in our knowledge, and identify future research challenges in the field of root ecology. Most importantly, we found that belowground traits with the broadest importance in plant and ecosystem functioning are not those most commonly measured. Also, the estimation of trait relative importance for functioning requires us to consider a more comprehensive range of functionally relevant traits from a diverse range of species, across environments and over time series. We also advocate that establishing causal hierarchical links among root traits will provide a hypothesis-based framework to identify the most parsimonious sets of traits with the strongest links on functions, and to link genotypes to plant and ecosystem functioning.

A starting guide to root ecology: strengthening ecological concepts and standardising root classification, sampling, processing and trait measurements.

In the context of a recent massive increase in research on plant root functions and their impact on the environment, root ecologists currently face many important challenges to keep on generating cutting-edge, meaningful and integrated knowledge. Consideration of the below-ground components in plant and ecosystem studies has been consistently called for in recent decades, but methodology is disparate and sometimes inappropriate. This handbook, based on the collective effort of a large team of experts, will improve trait comparisons across studies and integration of information across databases by providing standardised methods and controlled vocabularies. It is meant to be used not only as starting point by students and scientists who desire working on below-ground ecosystems, but also by experts for consolidating and broadening their views on multiple aspects of root ecology. Beyond the classical compilation of measurement protocols, we have synthesised recommendations from the literature to provide key background knowledge useful for: (1) defining below-ground plant entities and giving keys for their meaningful dissection, classification and naming beyond the classical fine-root vs coarse-root approach; (2) considering the specificity of root research to produce sound laboratory and field data; (3) describing typical, but overlooked steps for studying roots (e.g. root handling, cleaning and storage); and (4) gathering metadata necessary for the interpretation of results and their reuse. Most importantly, all root traits have been introduced with some degree of ecological context that will be a foundation for understanding their ecological meaning, their typical use and uncertainties, and some methodological and conceptual perspectives for future research. Considering all of this, we urge readers not to solely extract protocol recommendations for trait measurements from this work, but to take a moment to read and reflect on the extensive information contained in this broader guide to root ecology, including sections I-VII and the many introductions to each section and root trait description. Finally, it is critical to understand that a major aim of this guide is to help break down barriers between the many subdisciplines of root ecology and ecophysiology, broaden researchers' views on the multiple aspects of root study and create favourable conditions for the inception of comprehensive experiments on the role of roots in plant and ecosystem functioning.

Dividing the pie: A quantitative review on plant density responses.

Plant population density is an important variable in agronomy and forestry and offers an experimental way to better understand plant-plant competition. We made a meta-analysis of responses of even-aged mono-specific stands to population density by quantifying for 3 stand and 33 individual plant variables in 334 experiments how much both plant biomass and phenotypic traits change with a doubling in density. Increasing density increases standing crop per area, but decreases the mean size of its individuals, mostly through reduced tillering and branching. Among the phenotypic traits, stem diameter is negatively affected, but plant height remains remarkably similar, partly due to an increased stem length-to-mass ratio and partly by increased allocation to stems. The reduction in biomass is caused by a lower photosynthetic rate, mainly due to shading of part of the foliage. Total seed mass per plant is also strongly reduced, marginally by lower mass per seed, but mainly because of lower seed numbers. Plants generally have fewer shoot-born roots, but their overall rooting depth seems hardly affected. The phenotypic plasticity responses to high densities correlate strongly with those to low light, and less with those to low nutrients, suggesting that at high density, shading affects plants more than nutrient depletion.

Computational aspects underlying genome to phenome analysis in plants.

Recent advances in genomics technologies have greatly accelerated the progress in both fundamental plant science and applied breeding research. Concurrently, high-throughput plant phenotyping is becoming widely adopted in the plant community, promising to alleviate the phenotypic bottleneck. While these technological breakthroughs are significantly accelerating quantitative trait locus (QTL) and causal gene identification, challenges to enable even more sophisticated analyses remain. In particular, care needs to be taken to standardize, describe and conduct experiments robustly while relying on plant physiology expertise. In this article, we review the state of the art regarding genome assembly and the future potential of pangenomics in plant research. We also describe the necessity of standardizing and describing phenotypic studies using the Minimum Information About a Plant Phenotyping Experiment (MIAPPE) standard to enable the reuse and integration of phenotypic data. In addition, we show how deep phenotypic data might yield novel trait-trait correlations and review how to link phenotypic data to genomic data. Finally, we provide perspectives on the golden future of machine learning and their potential in linking phenotypes to genomic features.

Enabling reusability of plant phenomic datasets with MIAPPE 1.1.

Enabling data reuse and knowledge discovery is increasingly critical in modern science, and requires an effort towards standardising data publication practices. This is particularly challenging in the plant phenotyping domain, due to its complexity and heterogeneity. We have produced the MIAPPE 1.1 release, which enhances the existing MIAPPE standard in coverage, to support perennial plants, in structure, through an explicit data model, and in clarity, through definitions and examples. We evaluated MIAPPE 1.1 by using it to express several heterogeneous phenotyping experiments in a range of different formats, to demonstrate its applicability and the interoperability between the various implementations. Furthermore, the extended coverage is demonstrated by the fact that one of the datasets could not have been described under MIAPPE 1.0. MIAPPE 1.1 marks a major step towards enabling plant phenotyping data reusability, thanks to its extended coverage, and especially the formalisation of its data model, which facilitates its implementation in different formats. Community feedback has been critical to this development, and will be a key part of ensuring adoption of the standard.

A meta-analysis of plant responses to light intensity for 70 traits ranging from molecules to whole plant performance.

By means of meta-analyses we determined how 70 traits related to plant anatomy, morphology, chemistry, physiology, growth and reproduction are affected by daily light integral (DLI; mol photons m-2  d-1 ). A large database including 500 experiments with 760 plant species enabled us to determine generalized dose-response curves. Many traits increase with DLI in a saturating fashion. Some showed a more than 10-fold increase over the DLI range of 1-50 mol m-2  d-1 , such as the number of seeds produced per plant and the actual rate of photosynthesis. Strong decreases with DLI (up to three-fold) were observed for leaf area ratio and leaf payback time. Plasticity differences among species groups were generally small compared with the overall responses to DLI. However, for a number of traits, including photosynthetic capacity and realized growth, we found woody and shade-tolerant species to have lower plasticity. We further conclude that the direction and degree of trait changes adheres with responses to plant density and to vertical light gradients within plant canopies. This synthesis provides a strong quantitative basis for understanding plant acclimation to light, from molecular to whole plant responses, but also identifies the variables that currently form weak spots in our knowledge, such as respiration and reproductive characteristics.

How are nitrogen availability, fine-root mass, and nitrogen uptake related empirically? Implications for models and theory.

Understanding the effects of global change in terrestrial communities requires an understanding of how limiting resources interact with plant traits to affect productivity. Here, we focus on nitrogen and ask whether plant community nitrogen uptake rate is determined (a) by nitrogen availability alone or (b) by the product of nitrogen availability and fine-root mass. Surprisingly, this is not empirically resolved. We performed controlled microcosm experiments and reanalyzed published pot experiments and field data to determine the relationship between community-level nitrogen uptake rate, nitrogen availability, and fine-root mass for 46 unique combinations of species, nitrogen levels, and growing conditions. We found that plant community nitrogen uptake rate was unaffected by fine-root mass in 63% of cases and saturated with fine-root mass in 29% of cases (92% in total). In contrast, plant community nitrogen uptake rate was clearly affected by nitrogen availability. The results support the idea that although plants may over-proliferate fine roots for individual-level competition, it comes without an increase in community-level nitrogen uptake. The results have implications for the mechanisms included in coupled carbon-nitrogen terrestrial biosphere models (CN-TBMs) and are consistent with CN-TBMs that operate above the individual scale and omit fine-root mass in equations of nitrogen uptake rate but inconsistent with the majority of CN-TBMs, which operate above the individual scale and include fine-root mass in equations of nitrogen uptake rate. For the much smaller number of CN-TBMs that explicitly model individual-based belowground competition for nitrogen, the results suggest that the relative (not absolute) fine-root mass of competing individuals should be included in the equations that determine individual-level nitrogen uptake rates. By providing empirical data to support the assumptions used in CN-TBMs, we put their global climate change predictions on firmer ground.

The anatomical and compositional basis of leaf mass per area.

Leaf dry mass per unit leaf area (LMA) is a central trait in ecology, but its anatomical and compositional basis has been unclear. An explicit mathematical and physical framework for quantifying the cell and tissue determinants of LMA will enable tests of their influence on species, communities and ecosystems. We present an approach to explaining LMA from the numbers, dimensions and mass densities of leaf cells and tissues, which provided unprecedented explanatory power for 11 broadleaved woody angiosperm species diverse in LMA (33-262 g m-2 ; R2  = 0.94; P < 0.001). Across these diverse species, and in a larger comparison of evergreen vs. deciduous angiosperms, high LMA resulted principally from larger cell sizes, greater major vein allocation, greater numbers of mesophyll cell layers and higher cell mass densities. This explicit approach enables relating leaf anatomy and composition to a wide range of processes in physiological, evolutionary, community and macroecology.

Physiological and structural tradeoffs underlying the leaf economics spectrum.

The leaf economics spectrum (LES) represents a suite of intercorrelated leaf traits concerning construction costs per unit leaf area, nutrient concentrations, and rates of carbon fixation and tissue turnover. Although broad trade-offs among leaf structural and physiological traits have been demonstrated, we still do not have a comprehensive view of the fundamental constraints underlying the LES trade-offs. Here, we investigated physiological and structural mechanisms underpinning the LES by analysing a novel data compilation incorporating rarely considered traits such as the dry mass fraction in cell walls, nitrogen allocation, mesophyll CO2 diffusion and associated anatomical traits for hundreds of species covering major growth forms. The analysis demonstrates that cell wall constituents are major components of leaf dry mass (18-70%), especially in leaves with high leaf mass per unit area (LMA) and long lifespan. A greater fraction of leaf mass in cell walls is typically associated with a lower fraction of leaf nitrogen (N) invested in photosynthetic proteins; and lower within-leaf CO2 diffusion rates, as a result of thicker mesophyll cell walls. The costs associated with greater investments in cell walls underpin the LES: long leaf lifespans are achieved via higher LMA and in turn by higher cell wall mass fraction, but this inevitably reduces the efficiency of photosynthesis.

Building a better foundation: improving root-trait measurements to understand and model plant and ecosystem processes.

Trait-based approaches provide a useful framework to investigate plant strategies for resource acquisition, growth, and competition, as well as plant impacts on ecosystem processes. Despite significant progress capturing trait variation within and among stems and leaves, identification of trait syndromes within fine-root systems and between fine roots and other plant organs is limited. Here we discuss three underappreciated areas where focused measurements of fine-root traits can make significant contributions to ecosystem science. These include assessment of spatiotemporal variation in fine-root traits, integration of mycorrhizal fungi into fine-root-trait frameworks, and the need for improved scaling of traits measured on individual roots to ecosystem-level processes. Progress in each of these areas is providing opportunities to revisit how below-ground processes are represented in terrestrial biosphere models. Targeted measurements of fine-root traits with clear linkages to ecosystem processes and plant responses to environmental change are strongly needed to reduce empirical and model uncertainties. Further identifying how and when suites of root and whole-plant traits are coordinated or decoupled will ultimately provide a powerful tool for modeling plant form and function at local and global scales.