Ecological theories suggest that higher plant genetic diversity can increase productivity in natural ecosystems. So far, varietal mixtures, that is, the cultivation of different genotypes within a field, have shown contrasting results, notably for grain yield where both positive and negative mixing effects have been reported. Such discrepancy between ecological theories and agronomical applications calls for a better understanding of plant–plant interactions in crops.
Using durum wheat Triticum turgidum ssp. durum as a model species, we investigated the effect of functional trait composition on productivity and grain quality of varietal mixtures by growing 179 highly diverse genotypes in pure stands and 197 two-way mixtures in field conditions. We quantified the agronomic performance of the mixtures relative to their components grown in pure stands on two variables related to productivity, vegetative biomass yield and grain yield, and one variable related to grain quality, grain protein content. We then analysed the relationship between the relative performance of the mixtures and their functional composition that we characterized with trait means and trait differences on 19 above- and below-ground traits.
We found that biomass and grain yield increased by 4% overall in mixtures relative to single varieties, but that mixing effects were non-significant for grain protein content. The combined effects of trait means and trait differences explained 12%, 17% and 22% of the variability of relative grain yield, biomass yield and grain protein content, respectively, with different traits affecting productivity and grain quality. Clustering varieties into functional groups allowed us to identify the most beneficial associations for multifaceted agronomic performance.
Synthesis and applications. Functional traits explained a significant part of the relative agronomic performance of mixtures compared to monocultures (12%–22%, depending on the yield component). They can thus serve as a basis to identify groups of varieties whose combinations are expected to generate positive mixing effects, especially for productivity, and without compromising grain quality. Selection could then target convergence between groups for some traits and divergence between groups for other traits using empirically derived relationships between functional traits and agronomic performance as a guideline.
Data analysis is often at the heart of our teachings, however it generates many difficulties with the use of tools such as R or Rstudio even in face-to-face situations. With confinement these problems are exacerbated because it is difficult to interact with the students’ code or even ensure that they have downloaded the right software.
However, there are effective solutions for coding, running the code, sharing it and editing it with others online. One of them is rdrr.io, which is a site that offers both the possibility to run code online and also to create « notebooks » for code, run the code, save it and share it.
1. Fine‐roots play key roles in the capacity of plants to face environmental constraints and their traits reflect adaptations to the environment, including soil structure, resource availability and climate. However, the inaccuracy of global soil and climate databases to account for the large environmental variation occurring at small spatial scale prevents accurate estimations of the linkages between environmental variables and fine‐root strategies.
2. Here, using two global databases on fine‐root traits (Rhizopolis‐db) and species phylogenetic relatedness, and a regional database of species ecological indicator values (Baseflor), we quantified the predictive value of ecological indicator values, as an alternative to classical coarse soil and climate indicators, on the variation in four major fine‐root traits.
3. A strong phylogenetic signal was found among species for fine‐root mean diameter, specific root length (SRL) and root tissue density (RTD), but less so for root nitrogen concentration (RNC). After accounting for this relatedness, ecological indicators still explained a large part of trait variation in our dataset for SRL, RTD and RNC. Multi‐indicators best model R2 reached 0.40 for SRL and RTD, and 0.44 for RNC, whereas it was only 0.10 for diameter. Ecological indicators of nutrient availability and soil texture were those that most strongly related to SRL, RTD and RNC. Specifically, plant fast resources use strategies characterized by high SRL, RNC and low RTD occurred more frequently in nutrient‐rich soils and in soils with light sandy textures. Additionally, light availability and atmospheric temperature were negatively related with SRL and continentality negatively influenced RNC.
4. With respect to both nutrient and water availability ecological indicator values, opposite adaptations were observed between growth forms, particularly between woody and herbaceous species, limiting our ability to define simple, widely applicable patterns of trait‐environment relationships.
Synthesis: Our analysis demonstrates that species ecological indicator values are valuable predictors of plant below‐ground strategies. It provides original evidence that herbaceous species with fine‐root traits representative of fast resource use strategies typically occur in more favourable soil habitats (high nutrient and water availability), meanwhile woody species may show the opposite trend. Other important environmental parameters concomitantly influence fine‐root trait variation in contrasting ways.
Selection of the fittest can promote individual competitiveness but often results in the erosion of group performance. Recently, several authors revisited this idea in crop production and proposed new practices based on selection for cooperative phenotypes, i.e. phenotypes that increase crop yield through decreased competitiveness. These recommendations, however, remain difficult to evaluate without a formal description of crop evolutionary dynamics under different selection strategies. Here, we develop a theoretical framework to investigate the evolution of cooperation-related traits in crops, using plant height as a case study. Our model is tailored to realistic agricultural practices and shows that combining high plant density, high relatedness and selection among groups favours the evolution of shorter plants that maximize grain yield. Our model allows us to revisit past and current breeding practices in light of kin selection theory, and yields practical recommendations to increase cooperation among crops and promote sustainable agriculture
Background: Competition is a critical process that shapes plant communities and interacts with environmental constraints. There are surprising knowledge gaps related to mechanisms that belie competitive processes, though important to natural communities and agricultural systems: the contribution of different plant parts on competitive outcomes and the effect of environmental constraints on these outcomes. Objective: Studies that partition competition into root-only and shoot-only interactions assess whether plant parts impose different competitive intensities using physical partitions and serve as an important way to fill knowledge gaps. Given predicted drought escalation due to climate change, we focused a systematic review–including a meta-analysis on the effects of water supply and competitive outcomes. Methods: We searched ISI Web of Science for peer-reviewed studies and found 2042 results. From which eleven suitable studies, five of which had extractable information of 80 effect sizes on 10 species to test these effects. We used a meta-analysis to compare the log response ratios (lnRR) on biomass for responses to competition between roots, shoots, and full plants at two water levels. Results: Water availability treatment and competition treatment (root-only, shoot-only, and full plant competition) significantly interacted to affect plant growth responses (p < 0.0001). Root-only and full plant competition are more intense in low water availability (-1.2 and -0.9 mean lnRR, respectively) conditions than shoot-only competition (-0.2 mean lnRR). However, shoot-only competition in high water availability was the most intense (— 0.78 mean lnRR) compared to root-only and full competition (-0.5 and 0.61 mean lnRR, respectively) showing the opposite pattern to low water availability. These results also show that the intensity of full competition is similar to root-only competition and that low water availability intensifies root competition while weakening shoot competition. Conclusions: The outcome that competition is most intense between roots at low water availability emphasizes the importance of root competition and these patterns of competition may shift in a changing climate, creating further urgency for further studies to fil knowledge gaps addressing issues of drought on plant interactions and communities.
Plants respond to resource stress by changing multiple aspects of their biomass allocation, morphology, physiology and architecture. To date, we lack an integrated view of the relative importance of these plastic responses in alleviating resource stress and of the consistency/variability of these responses among species.
We subjected nine species (legumes, forbs and graminoids) to nitrogen and/or light shortages and measured 11 above-ground and below-ground trait adjustments critical in the alleviation of these stresses (plus several underlying traits).
Nine traits out of 11 showed adjustments that improved plants’ potential capacity to acquire the limiting resource at a given time. Above ground, aspects of plasticity in allocation, morphology, physiology and architecture all appeared important in improving light capture, whereas below ground, plasticity in allocation and physiology were most critical to improving nitrogen acquisition. Six traits out of 11 showed substantial heterogeneity in species plasticity, with little structuration of these differences within trait covariation syndromes.
Such comprehensive assessment of the complex nature of phenotypic responses of plants to multiple stress factors, and the comparison of plant responses across multiple species, makes a clear case for the high (but largely overlooked) diversity of potential plastic responses of plants, and for the need to explore the potential rules structuring them.
Genotypic mixtures have been receiving a growing interest as genetic diversity could increase crop productivity. Resource-use complementarity is an expected key underlying mechanism, provided that varieties in the mixture differ in resource-related traits, notably root traits. We aimed at examining how trait differences and resource-use complementarity drive biomass production of genotypic mixtures.
Four rice (Oryza sativa) genotypes including two Near-Isogenic Lines only differing in root depth were grown in monoculture and in two-way mixtures in pots under two levels of phosphorus supply. We analyzed the relative difference between mixture biomass and the best monoculture biomass in relation to between-genotype phenotypic distance on ten resource-related traits.
Mixtures never outperformed the best monoculture. However, relative mixture productivity increased with increasing between-genotype distance in biovolume, specific leaf area and top soil root biomass. This was mainly driven by a “selection effect”: trait differences led to competitive ability differences and the dominant genotypes tended to gain more in mixture than the subdominant genotypes lost compared to monoculture.
Rather than trying to minimize competition through resource-use complementarity, we argue that promoting interactions between genotypes that have different competitive abilities may be a more promising approach to design productive crop mixtures.
Human selection, changes in environmental conditions and management practices drove the phenotypic trajectory of crops during domestication. The characterization of the crop domestication syndrome lies mostly on reproductive characters. However, biophysical and ecophysiological constraints during vegetative growth are also at play and can strongly impact crop phenotypes. It has been argued that a broadened examination of crop phenotypes through a functional trait‐based lens should improve our understanding of the domestication syndrome.
We used a collection of 39 genotypes representative of key steps during tetraploid wheat domestication and grew them in a common garden experiment. We quantified the vegetative phenotype of each genotype through the measurements of 13 functional traits related to root, leaf and whole‐plant dimensions.
In modern cultivars, compared to ancestral forms, leaf longevity was shorter, while net photosynthetic rate, leaf production rate and nitrogen content were higher. Modern cultivars had a shallower root system and exhibited a larger proportion of fine roots, preferring to invest biomass above‐rather than below‐ground. We found ancestral forms to be integrated phenotypes characterized by coordination between above‐ and below‐ground functioning. Conversely, in modern forms, human selection appeared to have broken this coordination and to have generated a new type of network of trait covariations.
Synthesis and applications. The examination of leaf, root and whole‐plant traits of wheat accessions indicated a strong shift in plant functional strategies over the course of domestication. Elite genotypes tended to better optimize resource‐use acquisition strategies than ancestral ones. The characterization of the crop phenotype based on vegetative traits thus suggests a much more complete domestication syndrome. Our findings highlight the benefits of using a functional trait‐based characterization of crop phenotypes to document the extent of domestication syndrome and to further advance the agroecological management of cereals.
Grégoire T. Freschet, Oscar J. Valverde‐Barrantes, Caroline M. Tucker, Joseph M. Craine, M. Luke McCormack, Cyrille Violle, Florian Fort, Christopher B. Blackwood, Katherine R. Urban‐Mead, Colleen M. Iversen, Anne Bonis, Louise H. Comas, Johannes H. C. Cornelissen, Ming Dong, Dali Guo, Sarah E. Hobbie, Robert J. Holdaway, Steven W. Kembel, Naoki Makita, Vladimir G. Onipchenko, Catherine Picon‐Cochard, Peter B. Reich, Enrique G. de la Riva, Stuart W. Smith, Nadejda A. Soudzilovskaia, Mark G. Tjoelker, David A. Wardle, Catherine Roumet
Ecosystem functioning relies heavily on below‐ground processes, which are largely regulated by plant fine‐roots and their functional traits. However, our knowledge of fine‐root trait distribution relies to date on local‐ and regional‐scale studies with limited numbers of species, growth forms and environmental variation.
We compiled a world‐wide fine‐root trait dataset, featuring 1115 species from contrasting climatic areas, phylogeny and growth forms to test a series of hypotheses pertaining to the influence of plant functional types, soil and climate variables, and the degree of manipulation of plant growing conditions on species fine‐root trait variation. Most particularly, we tested the competing hypotheses that fine‐root traits typical of faster return on investment would be most strongly associated with conditions of limiting versus favourable soil resource availability. We accounted for both data source and species phylogenetic relatedness.
We demonstrate that: (i) Climate conditions promoting soil fertility relate negatively to fine‐root traits favouring fast soil resource acquisition, with a particularly strong positive effect of temperature on fine‐root diameter and negative effect on specific root length (SRL), and a negative effect of rainfall on root nitrogen concentration; (ii) Soil bulk density strongly influences species fine‐root morphology, by favouring thicker, denser fine‐roots; (iii) Fine‐roots from herbaceous species are on average finer and have higher SRL than those of woody species, and N2‐fixing capacity positively relates to root nitrogen; and (iv) Plants growing in pots have higher SRL than those grown in the field.
Synthesis. This study reveals both the large variation in fine‐root traits encountered globally and the relevance of several key plant functional types and soil and climate variables for explaining a substantial part of this variation. Climate, particularly temperature, and plant functional types were the two strongest predictors of fine‐root trait variation. High trait variation occurred at local scales, suggesting that wide‐ranging below‐ground resource economics strategies are viable within most climatic areas and soil conditions.
I explore the relationship between roots functional traits and leaves syndromes and their consequences on the plants ability to face interaction with other plants and abiotic stress mainly water and phosphorus.
I’m particularly interested in the functioning of the grassland and crops communities and on how fertility and climate change impact communities performances in interaction with their functional structure.