Both selection and plasticity drive niche differentiation in experimental grasslands

Trait-based community assembly and functional strategies across three subtropical karst forests, Southwestern China

Background

Variations in community-level plant functional traits are widely used to elucidate vegetation adaptation strategies across different environmental gradients. Moreover, studying functional variation among different forest types aids in understanding the mechanisms by which environmental factors and functional strategies shift community structure.

Methods

Based on five plant functional traits, including four leaf and one wood trait, for 150 woody species, we analyzed shifts in the community-weighted mean trait values across three forest types in a karst forest landscape: deciduous, mixed, and evergreen forests. We also assessed the relative contributions of stochastic processes, environmental filtering, and niche differentiation to drive community structure using a trait-based null model approach.

Results

We found marked changes in functional strategy, from resource acquisition on dry, fertile soil plots in deciduous forests to resource conservation on moist, infertile soil conditions in evergreen forests. The trait-based null model showed strong evidence of environmental filtering and convergent patterns in traits across three forest types, as well as low niche differentiation in most functional traits. Some evidence of overdispersion of LDMC and LT occurred to partially support the recent theory of Scheffer and Van Nes that competition could result in a clumped pattern of species along a niche axis.

Discussion

Our findings suggest a change in environmental gradient from deciduous to evergreen forest, together with a shift from acquisitive to conservative traits. Environmental filtering, stochastic processes, niche differentiation, and overdispersion mechanisms together drive community assembly in karst forest landscapes. These findings will contribute to a deeper understanding of the changes in functional traits among karst plants and their adaptive strategies, with important implications for understanding other community assemblies in subtropical forest systems.

Intraspecific variation in fine-root traits is larger than in aboveground traits in European herbaceous species regardless of drought

Differences within species (Intraspecific trait variation - ITV) contribute substantially to overall trait variability and environmental harshness can reduce among-species variation. While aboveground traits have received considerable attention, knowledge about ITV in fine-root traits and how it differs from ITV in aboveground traits remains limited. This study examined the partitioning of trait variation aboveground and fine-root traits in 52 European herbaceous species and how such proportions change in response to drought, offering valuable insights for accurate functional species characterization and inter-species comparisons. We studied seven morphological aboveground and fine-root traits under drought and well-watered conditions in a greenhouse experiment. Linear mixed effect models and permutational multivariate analysis of variance (PERMANOVA) were employed to decompose trait variation, ensuring the robustness of our results. We also calculated variance partitioning for the combination of aboveground traits and the combination of fine-root traits, as well as pairs of analogous leaf and fine-root traits (i.e., traits that fulfill similar functions) for each treatment (control and drought). Among-species trait differences explained a greater proportion of overall variance than within-species variation, except for root dry matter content (RDMC). Height and leaf area stood out, with species' identity accounting for 87-90% of total trait variation. Drought had no significant effect on the proportions of variation in any of the traits. However, the combination of fine-root traits exhibited higher intraspecific variability (44-44%) than aboveground traits (19-21%) under both drought and control. Analogous root traits also showed higher ITV (51-50%) than analogous leaf traits (27-31%). Our findings highlight substantial within-species variation and the nuanced responses of fine-root traits, particularly RDMC, suggesting root traits' flexibility to soil heterogeneity that fosters less differentiation among species. Among-species trait differences, especially aboveground, may underscore distinct strategies and competitive abilities for resource acquisition and utilization. This study contributes to elucidate the mechanisms underlying the multifunctionality of the above- and belowground plants compartments.

Beyond reaction norms: the temporal dynamics of phenotypic plasticity

Phenotypic plasticity can allow organisms to cope with environmental changes. Although reaction norms are commonly used to quantify plasticity along gradients of environmental conditions, they often miss the temporal dynamics of phenotypic change, especially the speed at which it occurs. Here, we argue that studying the rate of phenotypic plasticity is a crucial step to quantify and understand its adaptiveness. Iteratively measuring plastic traits allows us to describe the actual dynamics of phenotypic changes and avoid quantifying reaction norms at times that do not truly reflect the organism's capacity for plasticity. Integrating the temporal component in how we describe, quantify, and conceptualise phenotypic plasticity can change our understanding of its diversity, evolution, and consequences.

When the neighborhood matters: contextual selection on seedling traits in native and non-native California grasses

Plants interact extensively with their neighbors, but the evolutionary consequences of variation in neighbor identity are not well understood. Seedling traits are likely to experience selection that depends on the identity of neighbors because they influence competitive outcomes. To explore this, we evaluated selection on seed mass and emergence time in two California grasses, the native perennial Stipa pulchra, and the non-native annual Bromus diandrus, in the field with six other native and non-native neighbor grasses in single- and mixed-species treatments. We also quantified characteristics of each neighbor treatment to further investigate factors influencing their effects on fitness and phenotypic selection. Selection favored larger seeds in both focal species and this was largely independent of neighbor identity. Selection generally favored earlier emergence in both focal species, but neighbor identity influenced the strength and direction of selection on emergence time in S. pulchra, but not B. diandrus. Greater light interception, higher soil moisture, and greater productivity of neighbors were associated with more intense selection for earlier emergence and larger seeds. Our findings suggest that changes in plant community composition can alter patterns of selection in seedling traits, and that these effects can be associated with measurable characteristics of the community.

Species richness drives selection of individuals within wetlands based on traits related to acquisition and utilization of light

Selection within natural communities has mainly been studied along large abiotic gradients, while the selection of individuals within populations should occur locally in response to biotic filters. To better leverage the role of the latter, we considered the hierarchal nature of environmental selection for the multiple dimensions of the trait space across biological levels, that is, from the species to the community and the ecosystem levels. We replicated a natural species richness gradient where communities included from two to 16 species within four wetlands (bog, fen, meadow, and marsh) contrasting in plant productivity. We sampled functional traits from individuals in each community and used hierarchical distributional modeling in order to analyze the independent variation of the mean and dispersion of functional trait space at ecosystem, community, and species levels. The plant productivity gradient observed between wetlands led to species turnover and selection of traits related to leaf nutrient conservation/acquisition strategy. Within wetlands, plant species richness drove trait variation across both communities and species. Among communities, variation of species richness correlated with the selection of individuals according to their use of vertical space and leaf adaptations to light conditions. Within species, intraspecific light-related trait variation in response to species richness was associated with stable population density for some species, while others reached low population density in more diverse communities. Within ecosystems, variation in biotic conditions selects individuals along functional dimensions that are independent of those selected across ecosystems. Within-species variations of light-related traits are related to demographic responses, linking biotic selection of individuals within communities to eco-evolutionary dynamics of species.

Linking quantitative genetics with community-level performance: Are there operational models for plant breeding?

Plant breeding is focused on the genotype and population levels while targeting effects at higher levels of biodiversity, from crop covers to agroecosystems. Making predictions across nested levels of biodiversity is therefore a major challenge for the development of intercropping practices. New prediction tools and concepts are required to design breeding strategies with desirable outcomes at the crop community level. We reviewed theoretical advances in the field of evolutionary ecology to identify potentially operational ways of predicting the effects of artificial selection on community-level performances. We identified three main types of approaches differing in the way they model interspecific indirect genetic effects (IIGEs) at the community level: (1) The community heritability approach estimates the variance for IIGE induced by a focal species at the community level; (2) the joint phenotype approach quantifies genetic constraints between direct genetic effects and IIGE for a set of interacting species; (3) the community-trait genetic gradient approach decomposes the IIGE for a focal species across a multivariate set of its functional traits. We discuss the potential operational capacities of these approaches and stress that each is a special case of a general multitrait and multispecies selection index. Choosing one therefore involves assumptions and goals regarding the breeding target and strategy. Obtaining reliable quantitative, community-level predictions at the genetic level is constrained by the size and complexity of the experimental designs usually required. Breeding strategies should instead be compared using theoretically informed qualitative predictions. The need to estimate genetic covariances between traits measured both within and among species (for IIGE) is another obstacle, as the two are not determined by the exact same biological processes. We suggest future research directions and strategies to overcome these limits. Our synthesis offers an integrative theoretical framework for breeders interested in the genetic improvement of crop communities but also for scientists interested in the genetic bases of plant community functioning.

A research agenda for scaling up agroecology in European countries

A profound transformation of agricultural production methods has become unavoidable due to the increase in the world's population, and environmental and climatic challenges. Agroecology is now recognized as a challenging model for agricultural systems, promoting their diversification and adaptation to environmental and socio-economic contexts, with consequences for the entire agri-food system and the development of rural and urban areas. Through a prospective exercise performed at a large interdisciplinary institute, INRAE, a research agenda for agroecology was built that filled a gap through its ambition and interdisciplinarity. It concerned six topics. For genetics, there is a need to study genetic aspects of complex systems (e.g., mixtures of genotypes) and to develop breeding methods for them. For landscapes, challenges lie in effects of heterogeneity at multiple scales, in multifunctionality and in the design of agroecological landscapes. Agricultural equipment and digital technologies show high potential for monitoring dynamics of agroecosystems. For modeling, challenges include approaches to complexity, consideration of spatial and temporal dimensions and representation of the cascade from cropping practices to ecosystem services. The agroecological transition of farms calls for modeling and observational approaches as well as for creating new design methods. Integration of agroecology into food systems raises the issues of product specificity, consumer behavior and organization of markets, standards and public policies. In addition, transversal priorities were identified: (i) generating sets of biological data, through research and participatory mechanisms, that are appropriate for designing agroecological systems and (ii) collecting and using coherent sets of data to enable assessment of vulnerability, resilience and risk in order to evaluate the performance of agroecological systems and to contribute to scaling up. The main lessons learned from this collective exercise can be useful for the entire scientific community engaged in research into agroecology.

Phenotypic plasticity of light use favors a plant invader in nitrogen-enriched ecosystems

Eutrophication is believed to promote plant invasion, resulting in high growth performances of invasive plants and, hence, great potential for growth-induced intraspecific competition for light. Current hypotheses predict how eutrophication promotes plant invasion but fail to explain how great invasiveness is maintained under eutrophic conditions. In diverse native communities, cooccurring plants of varying sizes can avoid light competition by exploiting light complementarily; however, whether this mechanism applies to intraspecific competition in invasive plant populations remains unknown. Using a two-year field nitrogen (N)-enrichment experiment on one of the global invasive plants, Spartina alterniflora, we found that the plasticity of light use reduced intraspecific competition and increased biomass production in S. alterniflora. Such a plasticity effect was enhanced when S. alterniflora had no nutrient limitations. In the N-enrichment treatments, the height difference among S. alterniflora ramets increased as light intensity decreased under the canopy. Compared with ambient N, under N enrichment, shorter individuals increased their light-use efficiency and specific leaf area in response to the reduced light intensity under the canopy. However, such ecophysiological plasticity was not found for taller individuals. Our findings reveal that the light use plasticity of short individuals can be envisaged as a novel mechanism by which an invasive plant alleviates intraspecific competition and increases its invasiveness, challenging the prevailing perspective that the invasiveness of exotic plants is constrained by intraspecific competition.

Local Victory: Assessing Interspecific Competition in Seagrass From a Trait-Based Perspective

Tropical seagrass meadows are formed by an array of seagrass species that share the same space. Species sharing the same plot are competing for resources, namely light and inorganic nutrients, which results in the capacity of some species to preempt space from others. However, the drivers behind seagrass species competition are not completely understood. In this work, we studied the competitive interactions among tropical seagrass species of Unguja Island (Zanzibar, Tanzania) using a trait-based approach. We quantified the abundance of eight seagrass species under different trophic states, and selected nine traits related to light and inorganic nutrient preemption to characterize the functional strategy of the species (leaf maximum length and width, leaves per shoot, leaf mass area, vertical rhizome length, shoots per meter of ramet, rhizome diameter, roots per meter of ramet, and root maximum length). From the seagrass abundance we calculated the probability of space preemption between pairs of seagrass species and for each individual seagrass species under the different trophic states. Species had different probabilities of space preemption, with the climax species Thalassodendron ciliatum, Enhalus acoroides, Thalassia hemprichii, and the opportunistic Cymodocea serrulata having the highest probability of preemption, while the pioneer and opportunistic species Halophila ovalis, Syringodium isoetifolium, Halodule uninervis, and Cymodocea rotundata had the lowest. Traits determining the functional strategy showed that there was a size gradient across species. For two co-occurring seagrass species, probability of preemption was the highest for the larger species, it increased as the size difference between species increased and was unaffected by the trophic state. Competitive interactions among seagrass species were asymmetrical, i.e., negative effects were not reciprocal, and the driver behind space preemption was determined by plant size. Seagrass space preemption is a consequence of resource competition, and the probability of a species to exert preemption can be calculated using a trait-based approach.

Breeding Beyond Monoculture: Putting the "Intercrop" Into Crops

Intercropping is both a well-established and yet novel agricultural practice, depending on one's perspective. Such perspectives are principally governed by geographic location and whether monocultural practices predominate. Given the negative environmental effects of monoculture agriculture (loss of biodiversity, reliance on non-renewable inputs, soil degradation, etc.), there has been a renewed interest in cropping systems that can reduce the impact of modern agriculture while maintaining (or even increasing) yields. Intercropping is one of the most promising practices in this regard, yet faces a multitude of challenges if it is to compete with and ultimately replace the prevailing monocultural norm. These challenges include the necessity for more complex agricultural designs in space and time, bespoke machinery, and adapted crop cultivars. Plant breeding for monocultures has focused on maximizing yield in single-species stands, leading to highly productive yet specialized genotypes. However, indications suggest that these genotypes are not the best adapted to intercropping systems. Re-designing breeding programs to accommodate inter-specific interactions and compatibilities, with potentially multiple different intercropping partners, is certainly challenging, but recent technological advances offer novel solutions. We identify a number of such technology-driven directions, either ideotype-driven (i.e., "trait-based" breeding) or quantitative genetics-driven (i.e., "product-based" breeding). For ideotype breeding, plant growth modeling can help predict plant traits that affect both inter- and intraspecific interactions and their influence on crop performance. Quantitative breeding approaches, on the other hand, estimate breeding values of component crops without necessarily understanding the underlying mechanisms. We argue that a combined approach, for example, integrating plant growth modeling with genomic-assisted selection and indirect genetic effects, may offer the best chance to bridge the gap between current monoculture breeding programs and the more integrated and diverse breeding programs of the future.

Co-occurrence history increases ecosystem stability and resilience in experimental plant communities

Understanding factors that maintain ecosystem stability is critical in the face of environmental change. Experiments simulating species loss from grassland have shown that losing biodiversity decreases ecosystem stability. However, as the originally sown experimental communities with reduced biodiversity develop, plant evolutionary processes or the assembly of interacting soil organisms may allow ecosystems to increase stability over time. We explored such effects in a long-term grassland biodiversity experiment with plant communities with either a history of co-occurrence (selected communities) or no such history (naïve communities) over a 4-yr period in which a major flood disturbance occurred. Comparing communities of identical species composition, we found that selected communities had temporally more stable biomass than naïve communities, especially at low species richness. Furthermore, selected communities showed greater biomass recovery after flooding, resulting in more stable post-flood productivity. In contrast to a previous study, the positive diversity-stability relationship was maintained after the flooding. Our results were consistent across three soil treatments simulating the presence or absence of co-selected microbial communities. We suggest that prolonged exposure of plant populations to a particular community context and abiotic site conditions can increase ecosystem temporal stability and resilience due to short-term evolution. A history of co-occurrence can in part compensate for species loss, as can high plant diversity in part compensate for the missing opportunity of such adaptive adjustments.

How community adaptation affects biodiversity-ecosystem functioning relationships

Evidence is growing that evolutionary dynamics can impact biodiversity-ecosystem functioning (BEF) relationships. However the nature of such impacts remains poorly understood. Here we use a modelling approach to compare random communities, with no trait evolutionary fine-tuning, and co-adapted communities, where traits have co-evolved, in terms of emerging biodiversity-productivity, biodiversity-stability and biodiversity-invasion relationships. Community adaptation impacted most BEF relationships, sometimes inverting the slope of the relationship compared to random communities. Biodiversity-productivity relationships were generally less positive among co-adapted communities, with reduced contribution of sampling effects. The effect of community-adaptation, though modest regarding invasion resistance, was striking regarding invasion tolerance: co-adapted communities could remain very tolerant to invasions even at high diversity. BEF relationships are thus contingent on the history of ecosystems and their degree of community adaptation. Short-term experiments and observations following recent changes may not be safely extrapolated into the future, once eco-evolutionary feedbacks have taken place.