Plant Traits Research Articles

Glacier extinction homogenizes functional diversity via ecological succession

AbstractQuestionsThe disappearance of glaciers threatens biodiversity and the functioning of ecosystems. Yet, questions remain about the response of functional diversity to glacier retreat. How does glacier retreat influence functional diversity? How does glacier retreat influence the relationship between taxonomic diversity and functional diversity? How does glacier retreat impact community mean and intraspecific trait variability (ITV) of key functional traits?LocationFour retreating glacier ecosystems in the Italian Alps. Plant communities spanning 0 to ca 5000 years on average after glacier retreat, including a scenario of glacier extinction.MethodsWe quantified functional diversity analyzing twelve plant traits associated to carbon and nitrogen cycling, resource allocation, and reproduction of 117 plant species. We addressed how functional diversity changes with glacier retreat and taxonomic diversity (i.e., plant species richness).ResultsPlant functional diversity decreases with glacier extinction while increasing with species richness. The positive relationship between taxonomic and functional diversity becomes flatter, that is, less important, with glacier retreat. We document sharp changes in functional niche position and breadth with glacier retreat. Key functional traits associated with carbon cycling and resource allocation change substantially with ecological succession triggered by glacier retreat. Traits associated to nitrogen cycling show little change. We also found that flowering start shifted earlier in the season while flowering period increased with glacier retreat.ConclusionOur results demonstrate the pervasive impact of glacier extinction on the functioning of plant communities. Changes in functional mean and functional variation indicate shifts in niche position and niche breadth which could have implications for species adaptation to changing environments.

Regulatory networks of coresident subgenomes during rapid fiber cell elongation in upland cotton

Cotton, an intriguing plant species shaped by polyploidization, evolution, and domestication, holds particular interest due to the complex mechanisms governing fiber traits across its two subgenomes. However, the regulatory elements or transcriptional networks between subgenomes during fiber elongation remain to be fully clarified. Here, we analyzed 1462 cotton fiber samples to reconstruct the gene-expression regulatory networks that influence fiber cell elongation. Inter-subgenome expression quantitative trait loci (eQTLs) largely dictate gene transcription, with a notable tendency for the D subgenome to regulate A-subgenome eGenes. This regulation reveals synchronized homoeologous gene expression driven by co-localized eQTLs and divergent patterns that diminish genetic correlations, thus leading to preferential expression in the A and D subgenomes. Hotspot456 emerged as a key regulator of fiber initiation and elongation, and artificial selection of trans-eQTLs in hotspot456 that positively regulate KCS1 has facilitated cell elongation. Experiments designed to clarify the roles of trans-eQTLs in improved fiber breeding confirmed the inhibition of GhTOL9 by a specific trans-eQTL via GhWRKY28, which negatively affects fiber elongation. We propose a model in which the GhWRKY28–GhTOL9 module regulates this process through the ESCRT (endosomal sorting complex required for transport) pathway. This research significantly advances our understanding of cotton’s evolutionary and domestication processes and the intricate regulatory mechanisms that underlie significant plant traits.

Amplified photosynthetic responses to drought events offset the positive effects of warming on arid desert plants

Ongoing warming will influence plant photosynthesis via thermal effects and by enhancing water deficit. As the primary limiting factor for the growth and development of plants in arid deserts, water may alter the potential warming effects on plant photosynthesis and lead to increased uncertainty in plant dynamics. Here, we used open-top chambers (OTCs) to evaluate the impacts of in situ warming (+0.5 and +1.5 °C) on the photosynthesis and growth of two representative desert plants, Artemisia ordosica and Grubovia dasyphylla, from wet to dry spells. The plant traits associated with photosynthetic diffusive and biochemical processes were also measured to explore the underlying mechanisms involved. We found that warming significantly increased the net photosynthetic rate (Anet) during wet spells under 1.5 °C warming in both plants, while only increased that of A. ordosica under 0.5 °C warming. During dry spells, Anet decreased both in A. ordosica and G. dasyphylla, with the rates of declining being 48 % and 41 %, respectively, higher than control under warming. Consequently, warming significantly amplified photosynthetic responses to drought events, which offset the positive warming effects during wet spells and led to unchanged plant biomass in both species. Besides, alterations in plant traits tended to be associated with positive warming effects during wet spells, and the negative effects of drought were mainly due to stomatal limitation. Our results emphasised that the potential benefits of warming during wet spells may be reversed during drought events. Thus, the adverse effects of ongoing warming on desert productivity may increase during dry spells in growing seasons and during dry years.

Wave attenuation by intertidal vegetation is mediated by trade‐offs between shoot‐ and canopy‐scale plant traits

Abstract Nature‐based solutions, through conservation or (re)creation of vegetated shorelines, are recognized to mitigate the impact of waves and erosion risks on shorelines. Wave attenuation is known to be dependent on plant traits, resulting in increasing wave attenuation rates with increasing shoot density, shoot thickness, height, and stiffness. However, following the allometric scaling theory, we hypothesize that increasing shoot density (a canopy‐scale trait) may be associated with decreasing shoot thickness and stiffness (a shoot‐scale trait), with potential opposing effects on overall wave attenuation. This study investigates (1) the presence of such allometric relations across intertidal shore plant species via existing literature and (2) the trade‐off effects on the overall wave attenuation capacity of shore vegetation through a flume experiment. Our results reveal for the first time the presence of allometric relationships between shoot‐scale and canopy‐scale plant properties in perennial intertidal plant species. Across different species, increasing shoot densities are indeed associated with decreasing shoot thickness and shoot stiffness. Next, we performed a wave flume experiment with plant mimics, showing that wave attenuation rate follows a logarithmic increase with increasing shoot density, even though the increasing shoot density was associated with thinner and more flexible individual shoots. Synthesis and applications. We conclude that wave attenuation is predominantly governed by canopy‐scale properties, but a trade‐off with shoot‐scale properties mediates the overall wave attenuation capacity of the vegetated shore. Our findings imply that nature‐based projects (re‐)creating vegetated shorelines should account for potential trade‐off effects of species‐specific plant traits at the canopy scale and individual shoot scale.

Differential responses of community‐level functional traits to mid‐ and late‐season experimental drought in a temperate grassland

Abstract Extreme precipitation events are becoming more intense and frequent due to climate change. This climatic shift is impacting the structure and dynamics of natural communities and the key ecosystem services they provide. Changes in species abundance under these conditions are thought to be mediated by functional traits, morpho‐physiological characteristics of an organism that impact its fitness. Future environmental conditions may, therefore, favour different traits to those in present‐day communities. After 6 years of manipulated precipitation levels, including drought (−50% of ambient precipitation), irrigation (+50% of ambient precipitation), and control (ambient precipitation), we measured five key functional traits (plant height, leaf dry matter content [LDMC], leaf thickness, specific leaf area [SLA], and leaf phosphorus concentration) in 586 individual vascular plants to study the effects of precipitation changes on community‐weighted functional traits. Additionally, we tested whether the precipitation change effects on the traits depend on the time of the growing season. As expected, reduced precipitation impacted community composition only for the late‐season timing, after the seasonal field mowing, but led to a significant change in all community‐level plant traits between season timings. Under drought, communities shifted towards shorter individuals with thicker but small leaves and lower phosphorous content. Overall, a combination of community reassembly and intraspecific variation contributed to community‐weighted differences between control and drought plots for plant height, SLA, and LDMC traits. Species turnover was the main driver of community‐weighted means (CWMs) shifts in all traits in the late‐season but SLA. Whereas all traits showed variations at the community level with drought, SLA and LDMC were the most responsive traits at the species level. Nevertheless, our results suggest underestimation of intraspecific variation due to sensitive species lower abundance under stress. No differences in CWMs of functional traits were observed between control and irrigated plots. Synthesis: Our findings suggest that functional trait composition of grassland communities may shift under climate change‐induced drought, depending on the growing season timings. Trait‐based attempts to predict ecosystem functioning must account for such temporal variation in community trait values.

L1-Tree: A novel algorithm for constructing 3D tree models and estimating branch architectural traits using terrestrial laser scanning data

Branch architecture provides crucial information for the understanding of plant trait variability and the adaptive strategies employed by trees in response to their environment. High-fidelity terrestrial laser scanning (TLS) data provide an accurate, efficient, and non-destructive means for constructing three-dimensional (3D) tree models and estimating architectural traits. However, the complex canopy structure of trees in natural forests and the presence of occlusion in TLS data pose significant challenges to achieving this goal. In this study, we present a novel algorithm, L1-Tree, for the construction of 3D tree models and the estimation of architectural traits from TLS data. This algorithm is grounded in the L1-Median algorithm and integrates a tree skeleton optimization procedure that considers the structural characteristics of tree branches. By comparing modeling results and manually derived branch traits for 24 trees of 24 species, we found that the L1-Tree algorithm achieved precision, recall, and F-score values of 0.94 for branch identification, coefficient of determination, root-mean-squared error, and normalized root-mean-squared error of 0.998, 0.068 m, and 0.3 % for branch length estimation, and a respective value of 0.958, 0.257 cm and 0.9 % for branch radius estimation. Additionally, the branch identification accuracy and accuracy in branch architectural trait estimation remained satisfactory across branch orders. Compared to established 3D tree model construction algorithms (e.g., TreeQSM), our L1-Tree algorithm demonstrated a superior capability in handling noisy environments and data gaps, making it a robust tool for TLS data-based tree architecture studies. Leaf-wood separation emerged as a crucial step influencing the performance of the L1-Tree algorithm. We observed significant drop in branch identification accuracy when using an automatic leaf-wood separation algorithm as input, highlighting the urgent need to develop effective leaf-wood separation algorithms to generate high-quality wood point clouds for tree architecture studies.

Setting the stage for plant–soil feedback: Mycorrhizal influences over conspecific recruitment, plant and fungal communities, and coevolution

Abstract Plant–soil feedback (PSF) plays a central role in determining plant community dynamics, yet our understanding of how different combinations of plants and microbes influence PSF remains limited. Plants of different mycorrhizal types often exhibit contrasting PSF outcomes, influencing plant recruitment and spatial structure. Generalizing across plant species based on mycorrhizal type creates the potential to examine broader effects on ecological communities. We review mechanisms contributing to different PSF outcomes between arbuscular mycorrhizal and ectomycorrhizal trees. We focus on how plant and fungal traits that differ between mycorrhizal types interact with pathogenic and saprotrophic microorganisms and nutrient and carbon cycling. Synthesis. Building on this framework, we propose several new research directions. First, mycorrhizal‐induced changes in soils can operate beyond the conspecific level, spilling over from abundant plant species onto less abundant ones. This community‐level ‘mycorrhizal spillover’ is hypothesized to affect PSF in ways that are additive and interactive with conspecific density dependence. Second, we describe how mycorrhizal effects on PSF could structure the way plant communities respond to global change. Third, we discuss how they may influence plant evolution by altering the balance of selection pressures on traits and genes related to pathogen defence and mutualism formation.

Plant functional types and tissue stoichiometry explain nutrient transfer in common arbuscular mycorrhizal networks of temperate grasslands

Abstract Plants and mycorrhizal fungi form mutualistic relationships that affect how resources flow between organisms and within ecosystems. Common mycorrhizal networks (CMNs) could facilitate preferential transfer of carbon and limiting nutrients, but this remains difficult to predict. Do CMNs favour fungal resource acquisition at the expense of plant resource demands (a fungi‐centric view), or are they passive channels through which plants regulate resource fluxes (a plant‐centric view)? We used stable isotope tracers (13CO2 and 15NH3), plant traits, and mycorrhizal DNA to quantify above‐ and below‐ground carbon and nitrogen transfer between 18 plant species along a 520‐km latitudinal gradient in the Pacific Northwest, USA. Plant functional type and tissue stoichiometry were the most important predictors of interspecific resource transfer. Of ‘donor’ plants, 98% were 13C‐enriched, but we detected transfer in only 2% of ‘receiver’ plants. However, all donors were 15N‐enriched and we detected transfer in 81% of receivers. Nitrogen was preferentially transferred to annuals (0.26 ± 0.50 mg N per g leaf mass) compared with perennials (0.13 ± 0.30 mg N per g leaf mass). This corresponded with tissue stoichiometry differences. Synthesis Our findings suggest that plants and fungi that are located closer together in space and with stronger demand for resources over time are more likely to receive larger amounts of those limiting resources. Read the free Plain Language Summary for this article on the Journal blog.

Mycorrhizal inoculation alters rhizosphere fungal community and root morphology to improve drought tolerance of resource-acquisitive but not resource-conservative Quercus species

The mutualistic association between mycorrhizal fungi and plants is well known to improve plant drought resistance. However, the influence of external inoculants on the interactions between soil microbial communities and plant functional traits and how these interactions improve plant drought tolerance under drought stress remain unclear. We conducted a pot inoculation experiment to assess the effect of two inoculated fungal strains (Clitopolius hobsonii NL-19 and C. sp. HSL-YX-7-A) on morphological traits and rhizosphere fungal communities of eight Quercus species seedlings. Plant and soil fungal traits were measured 2 months after inoculation and then underwent a short-term (33 days) drought rewetting treatment. The biomass of all tree species reduced significantly under drought stress followed by rewetting (drought treatment) compared with that in the control treatment (well-watered); however, inoculated mycorrhizal fungi (drought + mycorrhizal inoculation treatment) increased the biomass of five Quercus species (growth-promoting species (GPS) exhibiting a significant increase in biomass under mycorrhizal inoculation treatment than under the uninoculated treatment during drought stress, characterized by a resource-use acquisitive strategy) and had no effect on the other three Quercus species (non-growth-promoting species (NGPS) exhibiting no significant difference in biomass between mycorrhizal inoculation and uninoculated treatments during drought stress, characterized by a resource-use conservative strategy). The leaf traits of the two species groups (GPS and NGPS) varied little among the three treatments. The values of most root traits (e.g., specific root length and root length) of GPS increased significantly under drought and drought + mycorrhizal inoculation treatments compared with those in the control, whereas relatively minor variations were observed in NGPS among the three treatments. The fungal community composition and functional groups (primary trophic modes) in the drought treatment were altered for NGPS but not for GPS; additionally, they changed in the drought + mycorrhizal inoculation treatment for GPS but not for NGPS when compared with those in the drought treatment. Furthermore, the drought tolerance of GPS was improved directly by fungal functional groups (i.e., Pathotroph-Saprotroph- Symbiotrophs proliferation) and indirectly by root traits (e.g., increased specific root length), whereas NGPS may adapt to drought stress through other pathways (e.g., physiological and biochemical regulation). Overall, drought and mycorrhizal inoculation affected the root traits and fungal community structure of Quercus seedlings, which rely on plant resource-use strategies. Our results provide new insights into the relationship between plant resource-use strategies and soil microbes for improving plant performance under drought stress.

Experimental evolution suggests rapid assembly of the 'selfing syndrome' from standing variation in Mimulus guttatus.

Ecological and evolutionary changes are likely to occur rapidly when outcrossing populations experience pollinator loss. However, the number and identify of plant traits that will respond to this form of selection, as well as the overall predictability of evolutionary responses, remain unclear. We experimentally evolved 20 large replicate populations of Mimulus guttatus for 10 generations under three treatments: pure outcrossing, mixed mating (10% outcrossing) and pure selfing. These populations were founded from the same genetically diverse and outcrossing natural population. After 10 generations, all measured traits evolved with flower size, phenology, and reproductive traits diverging consistently among mating system treatments. Autogamy increased dramatically in the selfing treatment, but the magnitude of adaptation only becomes clear once inbreeding depression is factored out. Selfing treatment plants evolved reduced stigma-anther separation, and also exhibited declines in flower size and per-flower reproductive capacity. Flower size also declined in selfing populations but this was driven mainly by inbreeding depression and cannot be attributed to adaptation towards the selfing syndrome. Generally, the mixed mating populations evolved trait values intermediate to the fully selfing and outcrossing populations. Overall, our experimental treatments reiterated differences that have been documented in interspecific comparisons between selfing and outcrossing species pairs. Given that such contrasts involve species separated by thousands or even millions of generations, it is noteworthy that large evolutionary responses were obtained from genetic variation segregating within a single natural population.

Genomic analyses of agronomic traits in tea plants and related Camellia species.

The genus Camellia contains three types of domesticates that meet various needs of ancient humans: the ornamental C. japonica, the edible oil-producing C. oleifera, and the beverage-purposed tea plant C. sinensis. The genomic drivers of the functional diversification of Camellia domesticates remain unknown. Here, we present the genomic variations of 625 Camellia accessions based on a new genome assembly of C. sinensis var. assamica ('YK10'), which consists of 15 pseudo-chromosomes with a total length of 3.35 Gb and a contig N50 of 816,948 bp. These accessions were mainly distributed in East Asia, South Asia, Southeast Asia, and Africa. We profiled the population and subpopulation structure in tea tree Camellia to find new evidence for the parallel domestication of C. sinensis var. assamica (CSA) and C. sinensis var. sinensis (CSS). We also identified candidate genes associated with traits differentiating CSA, CSS, oilseed Camellia, and ornamental Camellia cultivars. Our results provide a unique global view of the genetic diversification of Camellia domesticates and provide valuable resources for ongoing functional and molecular breeding research.

Integrated Analysis of Metabolomics, Flavoromics, and Transcriptomics for Evaluating New Varieties of Amomum villosum Lour.

Amomum villosum Lour. (A. villosum) is the original plant of the medicinal and culinary spice Amomi Fructus (Sharen) and is an important economic crop in the Lingnan region of China. During the cultivation and production of A. villosum, prolonged reliance on single asexual reproduction has exacerbated the degradation of its varieties, leading to inconsistent yields and quality. Building upon earlier cultivar selection efforts, this study provides a comprehensive evaluation of two newly bred A. villosum varieties (A11 and A12) from perspectives including plant traits, product characteristics, active ingredients, and multi-omics analysis. It was found that A12 plants display enhanced robustness, more aromatic fruits, higher yields, and elevated levels of bornyl acetate, A11 shows the advantage of a high camphor content, and the different metabolites and differentially expressed genes of the two varieties were significantly enriched in multiple metabolic pathways. Additionally, A12 contained more terpenoids and substances with aromatic odors such as sweet, fruity, floral, and green. Furthermore, a key gene (Wv_032842) regulating the acetylation of bornyl was discovered, and its significantly higher expression, in A12. In conclusion, this study has a guiding significance for the evaluation of germplasm resources and the breeding of excellent varieties of A. villosum.

Trade-Offs in Plant Functional Traits Driven by Soil Changes under Urban Hardened Surfaces

The large-scale surface hardening has changed the urban environment and affected the normal growth of urban plants. However, it is still unclear how the urban hardened surface affects the functional urban plant traits. To explore whether the urban hardened surface affects the ecological strategies of plants by changing the urban soil properties and reflecting them on the plant traits, we studied the physical and chemical properties and plant functional traits of three different types of hardened surface in Shandong Province, China. Our results showed that the physical and chemical properties (soil bulk density, soil total porosity, capillary porosity, non-capillary porosity, soil moisture content, pH, organic carbon, total nitrogen, total phosphorus, total potassium, available phosphorus, and available potassium) of urban soils showed obvious differences with the increase of hardening strength. In this case, the plant functional traits (branch diameter, branch length, leaf thickness, branch weight, internode length, leaf dry weight, leafing intensity, leaf area, specific leaf area, and leaf dry matter content) were also differentiated to varying degrees. Meanwhile, there was a strong correlation among plant functional traits. Nevertheless, hardened surfaces break the quantitative relationship among functional traits of urban trees. They do not affect their stable correlation: as the hardening intensity gradually increases, its correlation weakens. In addition, plant functional traits have a significant response mechanism to soil physicochemical properties. There was a transformation of plant resource utilization strategy by changing plant functional traits to adapt to the hardened environment. Urban trees exhibit strong and rapid resource-allocation strategies. They are mainly reflected in the reduction of branch diameter, branch weight, leaf dry matter content, leaf area, mass ratio of branches and leaves, and the improvement of leafing intensity and leaf thickness. Overall, there were tight connections among urban soil properties, plant branches, and leaves functional properties. This finding reveals that urban trees can change their functional traits and the plasticity of their trait combinations under the background of hardened urban surface expansion, which is conducive to survival and growth.

Molecular Marker Techniques and Genotypic Characterization Approaches in Plant Breeding

Plant breeding, often known as the science of plant development, is the study and practice of modifying a plant’s genetic makeup through a variety of breeding techniques to produce higher-quality, more prolific, and more resistant to harsh environmental circumstances. Classical breeding programs are indispensable techniques for increasing yields and improving plant characteristics, but they are progressing too slowly to meet the increasing food demand of the rapidly growing world population alone. Considering that the development periods of plants are generally long in traditional plant breeding, the opportunity to develop higher quality and more productive species that are more resistant to abiotic and biotic stress factors is very limited. Because there are multiple steps required in producing new plant varieties, including hybridization, selection, and testing, the process of creating a new variation takes several years. However, it is important to rapidly develop plant varieties with desirable characteristics to meet the increasing food demand of the rapidly growing world population, so the application of biotechnological methods integrated into plant breeding and combined with traditional methods can help reduce food shortages. Today, with the quick acceleration of biotechnology, molecular DNA marker technology has been developed in plant breeding and very important developments have been experienced. Thanks to the development of molecular tools for genetic research aimed at improving agricultural traits in plants related to crop yield, crop quality, or tolerance to adverse environmental conditions, we now have a much better understanding of plant genetics and the architecture and function of plant genomes. Therefore, it is of critical importance to revise current breeding procedures by incorporating molecular markers into breeding programs in the future.

Genomic structure and marker-trait association for plant and fruit traits in Capsicum chinense and Capsicum baccatum germplasm

ObjectivesCapsicum baccatum and C. chinense are domesticated pepper species originating from Latin America recognized for their unique flavor and taste and widely diffused as spicy food for fresh uses or for processing. Owing to their capacity for adaptation to diverse habitats in tropical regions, these species serve as a valuable resource for agronomic traits and tolerance to both biotic and abiotic challenges in breeding projects. This study aims to dissect the genetic diversity of C. baccatum and C. chinense germplasm and to detect candidate genes underlying the variation of plant morphological and fruit size and shape traits. To that goal, SNP data from genotyping by sequencing have been used to investigate the genetic diversity and population structure of 103 accessions belonging to the two species. Further, plants have been assessed with main plant descriptors and fruit imaging analysis and association between markers and traits has been performed.ResultsThe population structure based on 29,820 SNPs revealed 4 subclusters separating C. chinense and C. baccatum individuals. A deeper analysis within each species highlighted three subpopulations in C. chinense and two in C. baccatum. Phenotypic characterization of 54 traits provided approximately 125 thousand datapoints highlighting main differences between species for flower and fruit traits rather than plant architecture. Marker-traits association, performed with the CMLM model, revealed a total of 6 robust SNPs responsible for change in flower traits and fruit shape. This is the first attempt for mapping morphological traits and fruit features in the two domesticated species, paving the way for further genomic assisted breeding.

What is the Relationship Between Plant Trait Diversity and Geodiversity? A Plot‐Based, Pan‐European Analysis

What is the Relationship Between Plant Trait Diversity and Geodiversity? A Plot‐Based, Pan‐European Analysis

Phenotyping Alfalfa (Medicago sativa L.) Root Structure Architecture via Integrating Confident Machine Learning with ResNet-18.

Background: Root system architecture (RSA) is of growing interest in implementing plant improvements with belowground root traits. Modern computing technology applied to images offers new pathways forward to plant trait improvements and selection through RSA analysis (using images to discern/classify root types and traits). However, a major stumbling block to image-based RSA phenotyping is image label noise, which reduces the accuracies of models that take images as direct inputs. To address the label noise problem, this study utilized an artificial intelligence model capable of classifying the RSA of alfalfa (Medicago sativa L.) directly from images and coupled it with downstream label improvement methods. Images were compared with different model outputs with manual root classifications, and confident machine learning (CL) and reactive machine learning (RL) methods were tested to minimize the effects of subjective labeling to improve labeling and prediction accuracies. Results: The CL algorithm modestly improved the Random Forest model's overall prediction accuracy of the Minnesota dataset (1%) while larger gains in accuracy were observed with the ResNet-18 model results. The ResNet-18 cross-population prediction accuracy was improved (~8% to 13%) with CL compared to the original/preprocessed datasets. Training and testing data combinations with the highest accuracies (86%) resulted from the CL- and/or RL-corrected datasets for predicting taproot RSAs. Similarly, the highest accuracies achieved for the intermediate RSA class resulted from corrected data combinations. The highest overall accuracy (~75%) using the ResNet-18 model involved CL on a pooled dataset containing images from both sample locations. Conclusions: ResNet-18 DNN prediction accuracies of alfalfa RSA image labels are increased when CL and RL are employed. By increasing the dataset to reduce overfitting while concurrently finding and correcting image label errors, it is demonstrated here that accuracy increases by as much as ~11% to 13% can be achieved with semi-automated, computer-assisted preprocessing and data cleaning (CL/RL).

Multiple time scale optimization explains functional trait responses to leaf water potential.

Plant response to water stress involves multiple timescales. In the short term, stomatal adjustments optimize some fitness function commonly related to carbon uptake, while in the long term, traits including xylem resilience are adjusted. These optimizations are usually considered independently, the former involving stomatal aperture and the latter carbon allocation. However, short- and long-term adjustments are interdependent, as 'optimal' in the short term depends on traits set in the longer term. An economics framework is used to optimize long-term traits that impact short-term stomatal behavior. Two traits analyzed here are the resilience of xylem and the resilience of nonstomatal limitations (NSLs) to photosynthesis at low-water potentials. Results show that optimality requires xylem resilience to increase with climatic aridity. Results also suggest that the point at which xylem reach 50% conductance and the point at which NSLs reach 50% capacity are constrained to approximately a 2 : 1 linear ratio; however, this awaits further experimental verification. The model demonstrates how trait coordination arises mathematically, and it can be extended to many other traits that cross timescales. With further verification, these results could be used in plant modelling when information on plant traits is limited.

Spatial and Temporal Variation in the Antagonistic and Mutualistic Interactions among Seed Predator Arthropods, Seed-Dispersing Birds, and the Spanish Juniper.

Plants interact with both antagonistic and mutualistic animals during reproduction, with the outcomes of these interactions significantly influencing plant reproductive success, population dynamics, and the evolution of plant traits. Here, we investigated the spatial and temporal variations in the interactions between Juniperus thurifera, its seed-dispersing birds, and three specific arthropod species that attack the fleshy cones during the predispersal period. We assessed how plant traits affect levels of cone damage by arthropods and seed dispersal by birds, the occurrence of competition among arthropod species, and the impact of seed predators on the activity of frugivores. Plant traits, cone damage by arthropods, and seed dispersal by birds showed spatiotemporal variability. Fluctuation in cone abundance was the leading factor determining damage by arthropods and bird dispersal with a secondary role of cone traits. Large crops satiated predispersal seed predators, although the amount of frugivory did not increase significantly, suggesting a potential satiation of bird dispersers. Crop size and cone traits at individual trees determined preferences by seed predator species and the foraging activity of bird dispersers. Competition among arthropods increased during years of low cone production, and seed predators sometimes negatively affected bird frugivory. High supra-annual variations in cone production appear to be a key evolutionary mechanism enhancing J. thurifera reproductive success. This strategy reduces the impact of specialized seed predators during years of high seed production, despite the potential drawback of satiating seed dispersers.

Leaf trait networks shift toward high modularity during the succession of a subtropical forest, in southwest China

During the process of forest succession, coexisting plant species fulfill diverse functions by modifying the interrelationships among functional traits. Examining the interrelationships of functional traits across multiple dimensions would enable a comprehensive understanding of the plants’ adaptive strategies during forest succession. Plant trait networks (PTNs) comprehensively capture and visualize these intricate relationships among functional traits. Nonetheless, the changes in PTNs during forest secondary succession remain unclear. In this study, we measured 24 functional traits related to leaf resource acquisition, photosynthesis, hydraulics, and physical defense across tree species at three successional stages: young forest (YF), intermediate forest (IF), and old-growth forest (OF) in the Ailao Mountains, Southwest China. We established leaf trait networks (LTNs) to investigate the interrelationships among functional traits during forest succession. Our results revealed a decrease in the Edge Density decreased and an increase in the Modularity as succession advanced. In the YF stage, leaf nitrogen, photosynthetic rate, and force to punch were the hub traits; whereas, canopy exposure and leaf dry mass were highly connected traits in the IF and OF stages, respectively. The connectivity of highly connected traits was related to the plant’s life-history strategies and environmental adaptations at different successional stages. In terms of the importance of the four trait dimensions, resource acquisition and photosynthetic traits consistently demonstrated strong connectivity within LTNs throughout the succession. We concluded that co-occurring tree species adapted to the changing environmental conditions by adjusting trait modules through alternative strategies during secondary succession. Specifically, resource acquisition and trait coordination were more advantageous in the YF stage, while higher modularity offered greater opportunities for niche differentiation in the OF stage. This study provides new insights into exploring the mechanisms of forest succession through the analysis of trait correlation networks.