Correction: The genetic identity of neighboring plants in intraspecific mixtures modulates disease susceptibility of both wheat and rice.

[This corrects the article DOI: 10.1371/journal.pbio.3002287.].

High exposure of global tree diversity to human pressure.

Safeguarding Earth's tree diversity is a conservation priority due to the importance of trees for biodiversity and ecosystem functions and services such as carbon sequestration. Here, we improve the foundation for effective conservation of global tree diversity by analyzing a recently developed database of tree species covering 46,752 species. We quantify range protection and anthropogenic pressures for each species and develop conservation priorities across taxonomic, phylogenetic, and functional diversity dimensions. We also assess the effectiveness of several influential proposed conservation prioritization frameworks to protect the top 17% and top 50% of tree priority areas. We find that an average of 50.2% of a tree species' range occurs in 110-km grid cells without any protected areas (PAs), with 6,377 small-range tree species fully unprotected, and that 83% of tree species experience nonnegligible human pressure across their range on average. Protecting high-priority areas for the top 17% and 50% priority thresholds would increase the average protected proportion of each tree species' range to 65.5% and 82.6%, respectively, leaving many fewer species (2,151 and 2,010) completely unprotected. The priority areas identified for trees match well to the Global 200 Ecoregions framework, revealing that priority areas for trees would in large part also optimize protection for terrestrial biodiversity overall. Based on range estimates for >46,000 tree species, our findings show that a large proportion of tree species receive limited protection by current PAs and are under substantial human pressure. Improved protection of biodiversity overall would also strongly benefit global tree diversity.

Can plants build their niche through modulation of soil microbial activities linked with nitrogen cycling? A test with Arabidopsis thaliana.

In natural systems, different plant species have been shown to modulate specific nitrogen (N) cycling processes so as to meet their N demand, thereby potentially influencing their own niche. This phenomenon might go beyond plant interactions with symbiotic microorganisms and affect the much less explored plant interactions with free-living microorganisms involved in soil N cycling, such as nitrifiers and denitrifiers. Here, we investigated variability in the modulation of soil nitrifying and denitrifying enzyme activities (NEA and DEA, respectively), and their ratio (NEA : DEA), across 193 Arabidopsis thaliana accessions. We studied the genetic and environmental determinants of such plant-soil interactions, and effects on plant biomass production in the next generation. We found that NEA, DEA, and NEA : DEA varied c. 30-, 15- and 60-fold, respectively, among A. thaliana genotypes and were related to genes linked with stress response, flowering, and nitrate nutrition, as well as to soil parameters at the geographic origin of the analysed genotypes. Moreover, plant-mediated N cycling activities correlated with the aboveground biomass of next-generation plants in home vs away nonautoclaved soil, suggesting a transgenerational impact of soil biotic conditioning on plant performance. Altogether, these findings suggest that nutrient-based plant niche construction may be much more widespread than previously thought.

Evolutionary pathways to lower biomass allocation to the seed coat in crops: insights from allometric scaling.

Crops generally have seeds larger than their wild progenitors´ and with reduced dormancy. In wild plants, seed mass and allocation to the seed coat (a proxy for physical dormancy) scale allometrically so that larger seeds tend to allocate less to the coats. Larger seeds and lightweight coats might thus have evolved as correlated traits in crops. We tested whether 34 crops and 22 of their wild progenitors fit the allometry described in the literature, which would indicate co-selection of both traits during crop evolution. Deviations from the allometry would suggest that other evolutionary processes contribute to explain the emergence of larger, lightweight-coated seeds in crops. Crops fitted the scaling slope but deviated from its intercept in a consistent way: Seed coats of crops were lighter than expected by their seed size. The wild progenitors of crops displayed the same trend, indicating that deviations cannot be solely attributed to artificial selection during or after domestication. The evolution of seeds with small coats in crops likely resulted from a combination of various pressures, including the selection of wild progenitors with coats smaller than other wild plants, further decreases during early evolution under cultivation, and indirect selection due to the seed coat-seed size allometry.

Links to rare climates do not translate into distinct traits for island endemics.

Current models of island biogeography treat endemic and non-endemic species as if they were functionally equivalent, focussing primarily on species richness. Thus, the functional composition of island biotas in relation to island biogeographical variables remains largely unknown. Using plant trait data (plant height, leaf area and flower length) for 895 native species in the Canary Islands, we related functional trait distinctiveness and climate rarity for endemic and non-endemic species and island ages. Endemics showed a link to climatically rare conditions that is consistent with island geological change through time. However, functional trait distinctiveness did not differ between endemics and non-endemics and remained constant with island age. Thus, there is no obvious link between trait distinctiveness and occupancy of rare climates, at least for the traits measured here, suggesting that treating endemic and non-endemic species as functionally equivalent in island biogeography is not fundamentally wrong.

The ecological causes of functional distinctiveness in communities.

Recent work has shown that evaluating functional trait distinctiveness, the average trait distance of a species to other species in a community offers promising insights into biodiversity dynamics and ecosystem functioning. However, the ecological mechanisms underlying the emergence and persistence of functionally distinct species are poorly understood. Here, we address the issue by considering a heterogeneous fitness landscape whereby functional dimensions encompass peaks representing trait combinations yielding positive population growth rates in a community. We identify four ecological cases contributing to the emergence and persistence of functionally distinct species. First, environmental heterogeneity or alternative phenotypic designs can drive positive population growth of functionally distinct species. Second, sink populations with negative population growth can deviate from local fitness peaks and be functionally distinct. Third, species found at the margin of the fitness landscape can persist but be functionally distinct. Fourth, biotic interactions (positive or negative) can dynamically alter the fitness landscape. We offer examples of these four cases and guidelines to distinguish between them. In addition to these deterministic processes, we explore how stochastic dispersal limitation can yield functional distinctiveness. Our framework offers a novel perspective on the relationship between fitness landscape heterogeneity and the functional composition of ecological assemblages.

A major genetic locus in neighbours controls changes of gene expression and susceptibility in intraspecific rice mixtures.

Reports indicate that intraspecific neighbours alter the physiology of focal plants, and with a few exceptions, their molecular responses to neighbours are unknown. Recently, changes in susceptibility to pathogen resulting from such interactions were demonstrated, a phenomenon called neighbour-modulated susceptibility (NMS). However, the genetics of NMS and the associated molecular responses are largely unexplored. Here, we analysed in rice the modification of biomass and susceptibility to the blast fungus pathogen in the Kitaake focal genotype in the presence of 280 different neighbours. Using genome-wide association studies, we identified the loci in the neighbour that determine the response in Kitaake. Using a targeted transcriptomic approach, we characterized the molecular responses in focal plants co-cultivated with various neighbours inducing a reduction in susceptibility. Our study demonstrates that NMS is controlled by one major locus in the rice genome of its neighbour. Furthermore, we show that this locus can be associated with characteristic patterns of gene expression in focal plant. Finally, we propose an hypothesis where Pi could play a role in explaining this case of NMS. Our study sheds light on how plants affect the physiology in their neighbourhood and opens perspectives for understanding plant-plant interactions.

Plant trait relationships are maintained within a major crop species: lack of artificial selection signal and potential for improved agronomic performance.

The exploration of phenotypic spaces of large sets of plant species has considerably increased our understanding of diversification processes in the plant kingdom. Nevertheless, such advances have predominantly relied on interspecific comparisons that hold several limitations. Here, we grew in the field a unique set of 179 inbred lines of durum wheat, Triticum turgidum spp. durum, characterized by variable degrees of artificial selection. We measured aboveground and belowground traits as well as agronomic traits to explore the functional and agronomic trait spaces and to investigate trait-to-agronomic performance relationships. We showed that the wheat functional trait space shared commonalities with global cross-species spaces previously described, with two main axes of variation: a root foraging axis and a slow-fast trade-off axis. Moreover, we detected a clear signature of artificial selection on the variation of agronomic traits, unlike functional traits. Interestingly, we identified alternative phenotypic combinations that can optimize crop performance. Our work brings insightful knowledge about the structure of phenotypic spaces of domesticated plants and the maintenance of phenotypic trade-offs in response to artificial selection, with implications for trade-off-free and multi-criteria selection in plant breeding.

Growth-defence trade-off in rice: fast-growing and acquisitive genotypes have lower expression of genes involved in immunity.

Plant ecologists and molecular biologists have long considered the hypothesis of a trade-off between plant growth and defence separately. In particular, how genes thought to control the growth-defence trade-off at the molecular level relate to trait-based frameworks in functional ecology, such as the slow-fast plant economics spectrum, is unknown. We grew 49 phenotypically diverse rice genotypes in pots under optimal conditions and measured growth-related functional traits and the constitutive expression of 11 genes involved in plant defence. We also quantified the concentration of silicon (Si) in leaves to estimate silica-based defences. Rice genotypes were aligned along a slow-fast continuum, with slow-growing, late-flowering genotypes versus fast-growing, early-flowering genotypes. Leaf dry matter content and leaf Si concentrations were not aligned with this axis and negatively correlated with each other. Live-fast genotypes exhibited greater expression of OsNPR1, a regulator of the salicylic acid pathway that promotes plant defence while suppressing plant growth. These genotypes also exhibited greater expression of SPL7 and GH3.2, which are also involved in both stress resistance and growth. Our results do not support the hypothesis of a growth-defence trade-off when leaf Si and leaf dry matter content are considered, but they do when hormonal pathway genes are considered. We demonstrate the benefits of combining ecological and molecular approaches to elucidate the growth-defence trade-off, opening new avenues for plant breeding and crop science.

Land-use history impacts functional diversity across multiple trophic groups.

Land-use change is a major driver of biodiversity loss worldwide. Although biodiversity often shows a delayed response to land-use change, previous studies have typically focused on a narrow range of current landscape factors and have largely ignored the role of land-use history in shaping plant and animal communities and their functional characteristics. Here, we used a unique database of 220,000 land-use records to investigate how 20-y of land-use changes have affected functional diversity across multiple trophic groups (primary producers, mutualists, herbivores, invertebrate predators, and vertebrate predators) in 75 grassland fields with a broad range of land-use histories. The effects of land-use history on multitrophic trait diversity were as strong as other drivers known to impact biodiversity, e.g., grassland management and current landscape composition. The diversity of animal mobility and resource-acquisition traits was lower in landscapes where much of the land had been historically converted from grassland to crop. In contrast, functional biodiversity was higher in landscapes containing old permanent grasslands, most likely because they offer a stable and high-quality habitat refuge for species with low mobility and specialized feeding niches. Our study shows that grassland-to-crop conversion has long-lasting impacts on the functional biodiversity of agricultural ecosystems. Accordingly, land-use legacy effects must be considered in conservation programs aiming to protect agricultural biodiversity. In particular, the retention of permanent grassland sanctuaries within intensive landscapes may offset ecological debts.

Plant community impact on productivity: Trait diversity or key(stone) species effects?

Outside controlled experimental plots, the impact of community attributes on primary productivity has rarely been compared to that of individual species. Here, we identified plant species of high importance for productivity (key species) in >29,000 diverse grassland communities in the European Alps, and compared their effects with those of community-level measures of functional composition (weighted means, variances, skewness and kurtosis). After accounting for the environment, the five most important key species jointly explained more deviance of productivity than any measure of functional composition alone. Key species were generally tall with high specific leaf areas. By dividing the observations according to distinct habitats, the explanatory power of key species and functional composition increased and key-species plant types and functional composition-productivity relationships varied systematically, presumably because of changing interactions and trade-offs between traits. Our results advocate for a careful consideration of species' individual effects on ecosystem functioning in complement to community-level measures.

Functionally distinct tree species support long-term productivity in extreme environments.

Despite evidence of a positive effect of functional diversity on ecosystem productivity, the importance of functionally distinct species (i.e. species that display an original combination of traits) is poorly understood. To investigate how distinct species affect ecosystem productivity, we used a forest-gap model to simulate realistic temperate forest successions along an environmental gradient and measured ecosystem productivity at the end of the successional trajectories. We performed 10 560 simulations with different sets and numbers of species, bearing either distinct or indistinct functional traits, and compared them to random assemblages, to mimic the consequences of a regional loss of species. Long-term ecosystem productivity dropped when distinct species were lost first from the regional pool of species, under the harshest environmental conditions. On the contrary, productivity was more dependent on ordinary species in milder environments. Our findings show that species functional distinctiveness, integrating multiple trait dimensions, can capture species-specific effects on ecosystem productivity. In a context of an environmentally changing world, they highlight the need to investigate the role of distinct species in sustaining ecosystem processes, particularly in extreme environmental conditions.

Matches and mismatches between the global distribution of major food crops and climate suitability.

Over the course of history, humans have moved crops from their regions of origin to new locations across the world. The social, cultural and economic drivers of these movements have generated differences not only between current distributions of crops and their climatic origins, but also between crop distributions and climate suitability for their production. Although these mismatches are particularly important to inform agricultural strategies on climate change adaptation, they have, to date, not been quantified consistently at the global level. Here, we show that the relationships between the distributions of 12 major food crops and climate suitability for their yields display strong variation globally. After investigating the role of biophysical, socio-economic and historical factors, we report that high-income world regions display a better match between crop distribution and climate suitability. In addition, although crops are farmed predominantly in the same climatic range as their wild progenitors, climate suitability is not necessarily higher there, a pattern that reflects the legacy of domestication history on current crop distribution. Our results reveal how far the global distribution of major crops diverges from their climatic optima and call for greater consideration of the multiple dimensions of the crop socio-ecological niche in climate change adaptive strategies.

From cultivar mixtures to allelic mixtures: opposite effects of allelic richness between genotypes and genotype richness in wheat.

Agroecosystem diversification through increased crop genetic diversity could provide multiple services such as improved disease control or increased productivity. However, we still poorly understand how genetic diversity affects agronomic performance. We grew 179 inbred lines of durum wheat in pure stands and in 202 binary mixtures in field conditions. We then tested the effect of allelic richness between genotypes and genotype richness on grain yield and Septoria tritici blotch disease. Allelic richness was tested at 19K single nucleotide polymorphisms distributed along the durum wheat genome. Both genotype richness and allelic richness could be equal to 1 or 2. Mixtures were overall more productive and less diseased than their pure stand components. Yet, we identified one locus at which allelic richness between genotypes was associated with increased disease severity and decreased grain yield. The effect of allelic richness at this locus was stronger than the effect of genotype richness on grain yield (-7.6% vs +5.7%). Our results suggest that positive effects of crop diversity can be reversed by unfavourable allelic associations. This highlights the need to integrate genomic data into crop diversification strategies. More generally, investigating plant-plant interactions at the genomic level is promising to better understand biodiversity-ecosystem functioning relationships.

Solving the grand challenge of phenotypic integration: allometry across scales.

Phenotypic integration is a concept related to the cascade of trait relationships from the lowest organizational levels, i.e. genes, to the highest, i.e. whole-organism traits. However, the cause-and-effect linkages between traits are notoriously difficult to determine. In particular, we still lack a mathematical framework to model the relationships involved in the integration of phenotypic traits. Here, we argue that allometric models developed in ecology offer testable mathematical equations of trait relationships across scales. We first show that allometric relationships are pervasive in biology at different organizational scales and in different taxa. We then present mechanistic models that explain the origin of allometric relationships. In addition, we emphasized that recent studies showed that natural variation does exist for allometric parameters, suggesting a role for genetic variability, selection and evolution. Consequently, we advocate that it is time to examine the genetic determinism of allometries, as well as to question in more detail the role of genome size in subsequent scaling relationships. More broadly, a possible-but so far neglected-solution to understand phenotypic integration is to examine allometric relationships at different organizational levels (cell, tissue, organ, organism) and in contrasted species.

Nonlinear phenotypic variation uncovers the emergence of heterosis in Arabidopsis thaliana.

Heterosis describes the phenotypic superiority of hybrids over their parents in traits related to agronomic performance and fitness. Understanding and predicting nonadditive inheritance such as heterosis is crucial for evolutionary biology as well as for plant and animal breeding. However, the physiological bases of heterosis remain debated. Moreover, empirical data in various species have shown that diverse genetic and molecular mechanisms are likely to explain heterosis, making it difficult to predict its emergence and amplitude from parental genotypes alone. In this study, we examined a model of physiological dominance initially proposed by Sewall Wright to explain the nonadditive inheritance of traits like metabolic fluxes at the cellular level. We evaluated Wright's model for two fitness-related traits at the whole-plant level, growth rate and fruit number, using 450 hybrids derived from crosses among natural accessions of A. thaliana. We found that allometric relationships between traits constrain phenotypic variation in a nonlinear and similar manner in hybrids and accessions. These allometric relationships behave predictably, explaining up to 75% of heterosis amplitude, while genetic distance among parents at best explains 7%. Thus, our findings are consistent with Wright's model of physiological dominance and suggest that the emergence of heterosis on plant performance is an intrinsic property of nonlinear relationships between traits. Furthermore, our study highlights the potential of a geometric approach of phenotypic relationships for predicting heterosis of major components of crop productivity and yield.

Into the range: a latitudinal gradient or a center-margins differentiation of ecological strategies in Arabidopsis thaliana?

BACKGROUND AND AIMS: Determining within-species large-scale variation in phenotypic traits is central to elucidate the drivers of species' ranges. Intraspecific comparisons offer the opportunity to understand how trade-offs and biogeographical history constrain adaptation to contrasted environmental conditions. Here we test whether functional traits, ecological strategies from the CSR scheme and phenotypic plasticity in response to abiotic stress vary along a latitudinal or a center- margins gradient within the native range of Arabidopsis thaliana. METHODS: We experimentally examined the phenotypic outcomes of plant adaptation at the center and margins of its geographic range using 30 accessions from southern, central and northern Europe. We characterized the variation of traits related to stress tolerance, resource use, colonization ability, CSR strategy scores, survival and fecundity in response to high temperature (34 °C) or frost (- 6 °C), combined with a water deficit treatment. KEY RESULTS: We found evidence for both a latitudinal and a center-margins differentiation for the traits under scrutiny. Age at maturity, leaf dry matter content, specific leaf area and leaf nitrogen content varied along a latitudinal gradient. Northern accessions presented a greater survival to stress than central and southern accessions. Leaf area, C-scores, R-scores and fruit number followed a center-margins differentiation. Central accessions displayed a higher phenotypic plasticity than northern and southern accessions for most studied traits. CONCLUSIONS: Traits related to an acquisitive/conservative resource-use trade-off followed a latitudinal gradient. Traits associated with a competition/colonization trade-off differentiated along the historic colonization of the distribution range and then followed a center-margins differentiation. Our findings pinpoint the need to consider the joint effect of evolutionary history and environmental factors when examining phenotypic variation across the distribution range of a species.

Increasing crop heterogeneity enhances multitrophic diversity across agricultural regions.

Agricultural landscape homogenization has detrimental effects on biodiversity and key ecosystem services. Increasing agricultural landscape heterogeneity by increasing seminatural cover can help to mitigate biodiversity loss. However, the amount of seminatural cover is generally low and difficult to increase in many intensively managed agricultural landscapes. We hypothesized that increasing the heterogeneity of the crop mosaic itself (hereafter "crop heterogeneity") can also have positive effects on biodiversity. In 8 contrasting regions of Europe and North America, we selected 435 landscapes along independent gradients of crop diversity and mean field size. Within each landscape, we selected 3 sampling sites in 1, 2, or 3 crop types. We sampled 7 taxa (plants, bees, butterflies, hoverflies, carabids, spiders, and birds) and calculated a synthetic index of multitrophic diversity at the landscape level. Increasing crop heterogeneity was more beneficial for multitrophic diversity than increasing seminatural cover. For instance, the effect of decreasing mean field size from 5 to 2.8 ha was as strong as the effect of increasing seminatural cover from 0.5 to 11%. Decreasing mean field size benefited multitrophic diversity even in the absence of seminatural vegetation between fields. Increasing the number of crop types sampled had a positive effect on landscape-level multitrophic diversity. However, the effect of increasing crop diversity in the landscape surrounding fields sampled depended on the amount of seminatural cover. Our study provides large-scale, multitrophic, cross-regional evidence that increasing crop heterogeneity can be an effective way to increase biodiversity in agricultural landscapes without taking land out of agricultural production.

Unveiling ecological assembly rules from commonalities in trait distributions.

Deciphering the effect of neutral and deterministic processes on community assembly is critical to understand and predict diversity patterns. The information held in community trait distributions is commonly assumed as a signature of these processes, but empirical and modelling attempts have most often failed to untangle their confounding, sometimes opposing, impacts. Here, we simulated the assembly of trait distributions through stochastic (dispersal limitation) and/or deterministic scenarios (environmental filtering and niche differentiation). We characterized the shape of trait distributions using the skewness-kurtosis relationship. We identified commonalities in the co-variation between the skewness and the kurtosis of trait distributions with a unique signature for each simulated assembly scenario. Our findings were robust to variation in the composition of regional species pools, dispersal limitation and environmental conditions. While ecological communities can exhibit a high degree of idiosyncrasy, identification of commonalities across multiple communities can help to unveil ecological assembly rules in real-world ecosystems.

The dimensionality and structure of species trait spaces.

Trait-based ecology aims to understand the processes that generate the overarching diversity of organismal traits and their influence on ecosystem functioning. Achieving this goal requires simplifying this complexity in synthetic axes defining a trait space and to cluster species based on their traits while identifying those with unique combinations of traits. However, so far, we know little about the dimensionality, the robustness to trait omission and the structure of these trait spaces. Here, we propose a unified framework and a synthesis across 30 trait datasets representing a broad variety of taxa, ecosystems and spatial scales to show that a common trade-off between trait space quality and operationality appears between three and six dimensions. The robustness to trait omission is generally low but highly variable among datasets. We also highlight invariant scaling relationships, whatever organismal complexity, between the number of clusters, the number of species in the dominant cluster and the number of unique species with total species richness. When species richness increases, the number of unique species saturates, whereas species tend to disproportionately pack in the richest cluster. Based on these results, we propose some rules of thumb to build species trait spaces and estimate subsequent functional diversity indices.