Increasing plant group productivity through latent genetic variation for cooperation

Historic yield advances in the major crops have, to a large extent, been achieved by selection for improved productivity of groups of plant individuals such as high-density stands. Research suggests that such improved group productivity depends on “cooperative” traits (e.g., erect leaves, short stems) that—while beneficial to the group—decrease individual fitness under competition. This poses a problem for some traditional breeding approaches, especially when selection occurs at the level of individuals, because “selfish” traits will be selected for and reduce yield in high-density monocultures. One approach, therefore, has been to select individuals based on ideotypes with traits expected to promote group productivity. However, this approach is limited to architectural and physiological traits whose effects on growth and competition are relatively easy to anticipate. Here, we developed a general and simple method for the discovery of alleles promoting cooperation in plant stands. Our method is based on the game-theoretical premise that alleles increasing cooperation benefit the monoculture group but are disadvantageous to the individual when facing noncooperative neighbors. Testing the approach using the model plant Arabidopsis thaliana, we found a major effect locus where the rarer allele was associated with increased cooperation and productivity in high-density stands. The allele likely affects a pleiotropic gene, since we find that it is also associated with reduced root competition but higher resistance against disease. Thus, even though cooperation is considered evolutionarily unstable except under special circumstances, conflicting selective forces acting on a pleiotropic gene might maintain latent genetic variation for cooperation in nature. Such variation, once identified in a crop, could rapidly be leveraged in modern breeding programs and provide efficient routes to increase yields

Managing understory light conditions in boreal mixedwoods through variation in the intensity and spatial pattern of harvest: A modelling approach

In the context of partial harvesting, adequately managing post-harvest light conditions are essential to obtain a desired composition of tree species regeneration. The objective of this study was to determine how varying the intensity and spatial pattern of harvest would affect understory light conditions in boreal mixedwood stands of northwestern Quebec using the spatially explicit SORTIE-ND light model. The model was evaluated based on comparisons of observed and predicted light levels in both mapped and un-mapped plots. In mapped plots, reasonably accurate predictions of the overall variation in light levels were obtained, but predictions tended to lack spatial precision. In un-mapped plots, SORTIE-ND accurately predicted stand-level mean GLI (Gap Light Index) under a range of harvest intensities. The model was then used to simulate nine silvicultural treatments based on combinations of three intensities of overstory removal (30%, 45% and 60% of basal area) and three harvest patterns (uniform, narrow strips, large gaps). Simulations showed that increasing overstory removal had less impact on light conditions with uniform harvests, and a more marked effect with more aggregated harvest patterns. Whatever the harvest intensity, uniform cuts almost never created high light conditions (GLI > 50%). Gap cuts, on the other hand, resulted in up to 40% of microsites receiving GLI > 50%. Our results suggest that either a 30% strip or gap cut or a 45–60% uniform partial harvest could be used to accelerate the transition from an aspen dominated composition to a mixedwood stand because both types of cut generate the greatest proportion of moderately low light levels (e.g., 15–40% GLI). These light levels tend to favour an accelerated growth response among shade-tolerant conifers, while preventing excessive recruitment of shade-intolerant species. A better understanding of how spatial patterns of harvest interact with tree removal intensity to affect understory light conditions can provide opportunities for designing silvicultural prescriptions that are tailored to species’ traits and better suited to meet a variety of management objectives

Life After AREDS 2: What Should We Recommend to Patients With or at Risk of AMD?

Purpose: To establish a consensus on clinical recommendation of oral supplementation for patients with or at risk of developing age-related macular degeneration (AmD), from the perspective of the Age-Related eye Disease Study 2 (AReDS 2) and other studies. Methods: Panel discussion based on a literature review of pertinent articles related to the prevention of AmD with oral supplementation. Results: on the basis of the findings, patients must first be encouraged to modify their diet and to eliminate modifiable risk factors before being recommended any type of oral supplementation. Then, recommendations must be customized on the basis of a patient’s individual risk profile (i.e., age, gender, heredity, etc.) and severity of disease (i.e., category 1 to 4). essential fatty acids (omega-3s) and vitamins may play a role, in a given clinical population, to prevent the occurrence or the progression of AmD disease. However, there is no single formula that can be applied to all patients with or at risk of AmD. Conclusions: This group concluded that the full body of literature must be taken into consideration in order to justify clinical recommendations for patients. A single study such as AReDS 2 cannot, by itself, guide clinical practice. In all cases, recommendations must be individualized and patients should be monitored regularly

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Variation and Integration of Ecophysiological Traits across Scales in Tropical and Temperate Trees: Patterns, Drivers and Consequences

The overarching goal of my dissertation is to explore the potential and limits of a trait-based approach to plant ecology. Together, the different studies presented here address two explicit and implicit foundational assumptions underpinning the trait-based approach: (1) that the correlation patterns and biological significance of traits transfer across scales and (2) that the phenotypic complexity of plants can accurately be synthesized into a few meaningful traits to study their ecology. Moreover, the last chapter focuses on a third key assumption: (3) that traits are strong predictors of plant performance (Shipley et al. In Press). I examine these assumptions by exploring multivariate patterns of phenotypic variation and integration across different ecological scales (e.g., individuals, populations, species) while explicitly considering the phenotypic complexity of trees, both in terms of their multidimensional and integrated nature. Two themes thus permeate this body of work: scales and phenotypic complexity. Much of what we know about the relationships among key traits comes from species-scale studies. Trait variation at smaller scales are often interpreted in the context of these interspecific relationships, but it is not clear that interspecific patterns observed at global scales apply to smaller scales. Moreover, although plants are complex, integrated organisms with intricate relationships among their traits, single traits are often studied and interpreted without considering the rest of the phenotype. Yet, examining individual traits outside of their phenotypic context might provide limited insight or be misleading. To address these shortcomings, this body of work examines multidimensional patterns of trait variation and correlation across ecological scales. It uses (1) a set of six ecophysiological leaf traits from mature trees in a lowland tropical rainforest, and (2) a set of twenty leaf, root, stem, branch and whole-plant ecophysiological traits from deciduous saplings in a temperate forest. The combination of our findings point to three main conclusions: (i) local interspecific and intra-population trait integration structures differ from each other and from the global interspecific patterns reported in the literature, such that global-scale interspecific patterns cannot readily be transferred to more local scales; (ii) considering the complexity of the plant phenotype provides better insights into ecological patterns and processes than what we can learn from considering individual or a handful of traits; and (iii) traits strongly affect individual plant performance, although there is no relationship between a species' trait correlation structure and its environmental niche, which suggests that there are multiple alternative optimal phenotypes in a given environment

How do leaf functional traits vary across ecological scales?

Functional traits, measurements of adaptive aspects of the phenotype, are increasingly used for the study of plant community ecology. Despite their importance, we do not know which ecological scales contain the most variation in a given trait, which hampers assessment of the wider relevance of findings from studies conducted at only one scale. To address this deficiency, I studied the variance distribution of two key leaf functional traits (leaf mass per area - LMA and leaf dry matter content - LDMC) across six nested ecological scales (site, plot, species, tree, strata, leaf) in lowland tropical rainforests of Panama. Variance in both traits is uniformly distributed across all scales except the plot level, which shows virtually no variance despite high species turnover among plots. This contradicts the widely held belief that species-level variation predominates in organizing species distribution and abundance and indicates that communities regulate plant ensembles by filtering on leaf functional traits regardless of species.Les traits fonctionnels, attributs indicatifs des aspects adaptatifs du phénotype, sont de plus en plus utilisés pour étudier l’écologie des communautés végétales. Malgré l’importance des traits fonctionnels, nous ne savons pas à quelle échelle écologique un trait donné varie le plus, ce qui nous empêche de mettre dans un contexte général les découvertes des études conduites à une seule échelle. Pour combler cette lacune, j’ai étudié dans les forêts tropicales humides tropical du Panama la distribution de la variance de deux traits fonctionnels foliaires clés (la masse par surface foliaire - LMA et le contenu foliaire en matière sèche - LDMC) à travers six échelles écologiques emboitées (le site, la parcelle, l’espèce, l’arbre, la strate et la feuille). La variance de ces deux traits est uniformément distribuée à travers toutes les échelles, sauf à l’échelle de la parcelle qui ne présente aucune variance malgré la forte différence de composition d’espèces entre les parcelles d’un même site. Ces résultats vont à l’encontre de la croyance populaire selon laquelle la variation interspécifique joue un rôle prédominant dans le contrôle de la distribution et l’abondance des espèces. Ils indiquent plutôt que les communautés régulent l’assemblage des végétaux en exerçant un filtre sur les traits fonctionnels, indépendamment de l’espèce

Fitness of multidimensional phenotypes in dynamic adaptive landscapes

Phenotypic traits influence species distributions, but ecology lacks established links between multidimensional phenotypes and fitness for predicting species responses to environmental change. The common focus on single traits rather than multiple trait combinations limits our understanding of their adaptive value, and intraspecific trait covariation has been neglected in ecology despite its importance in evolutionary theory and its likely impact on species distributions. Here, we extend the adaptive landscape framework to ecological sorting of multidimensional phenotypes across environments and discuss how two analytical approaches can be used to quantify fitness as a function of the interaction between the phenotype and the environment. We encourage ecologists to consider how phenotypic integration will constrain species responses to environmental change