New Phytologist

O_LIIn fluctuating environments, the kinetics of stomatal opening and closing influence the balance between carbon gain and water loss. Smaller guard cells may respond faster to fluctuating environmental conditions because of their greater surface area for osmolyte flux relative to cell volume. A related hypothesis is that operational stomatal conductance (gop) is often well below its theoretical maximum (gmax) because at this stomatal aperture, guard cell volume is poised to change rapidly with small changes in turgor pressure. C_LIO_LIWe analyzed 2,124 estimates of stomatal closure kinetics in response to an abrupt increase in vapor pressure deficit (VPD) among 29 diverse wild tomato populations in the genus Solanum. C_LIO_LILeaves with small guard cells and a lower gop to gmax ratio (fgmax) closed faster, but explained variation in kinetic parameters at different levels of biological organization. Guard cell size had high phylogenetic heritability and varied relatively little within populations, whereas fgmax varied mostly among individuals and between light intensity treatments. C_LIO_LISmaller stomata can be speedier, but only if stomata are held at an aperture where they are responsive to changing turgor pressure. Selection on stomatal speed may influence not only anatomical traits like guard cell size, but also physiological controls on gop. C_LI

How plants allocate carbon determines their productivity, responses to stress, and interactions with other organisms. A substantial amount of plant carbon is stored as non-structural carbohydrates (NSC), which sustain turgor via osmoregulation and fuel metabolism when carbon is limited. NSC also support root-colonizing mycorrhizal fungi, thus we hypothesized that under carbon-limiting conditions such as drought, a trade-off between feeding mycorrhizal fungi and maintaining turgor may arise. We reduced carbon allocation to ectomycorrhizal (EcM) networks by girdling Pinus ponderosa trees exposed to drought or ambient conditions and manipulated putative fungal connections between trees by trenching. We show that, in droughted plots, trees putatively connected to girdled trees by EcM networks had 33 % less needle NSC and >10% less turgor than those connected to ungirdled trees. Trees disconnected from the mycorrhizal network by trenching had increased NSC likely from the increased water availability with girdling, but these gains were offset in the presence of networks. Our results demonstrate that the increased carbon demand by EcM fungi in response to reduced carbon inputs from some trees can deplete NSC in neighboring trees via shared mycorrhizal networks. At least in the short term, allocation trade-offs under carbon-limiting conditions may expose networked trees to carbon deficits. This may increase vulnerability to drought, which may be particularly acute given shifts in climate.

O_LIBackground and Aims: Chemodiversity is a fitness-relevant trait shaped by genetics, environment, and their interaction. Populus trichocarpa naturally inhabits broad climatic gradients and shows extensive variation in specialised metabolism. We investigated whether provenance and climate of origin imprint leaf chemodiversity and class-level relationships under common-garden conditions, and how these patterns relate to gene expression. C_LIO_LIMethods: Leaves from 87 P. trichocarpa genotypes representing 22 provenances from the west coast of North America growing in a common garden were profiled by untargeted FT-ICR-MS (1030 features) and targeted LC-MS/MS. A subset of 41 genotypes was subject to RNA-seq analyses. We tested whether provenance influenced multivariate patterns and whether metabolomic differences were related to geographic and climatic distance, where chemodiversity was quantified as Functional Hill Diversity. C_LIO_LIKey Results: P. trichocarpa metabolomes differed among origins despite shared growth conditions and showed distance-decay with both geography and climate. North-south extremes were well separated, and within-drainage samples shared high similarity. Flavonoid and isoprenoid pools strongly co-varied across individuals, whereas isoprene synthase activity did not predict total isoprenoids. Transcriptomes showed within-pathway coherence but limited overall provenance separation. C_LIO_LIConclusions: Leaf chemistry in P. trichocarpa retains signatures of geographic origin even under common-garden conditions. Coordinated investment in flavonoids and isoprenoids, together with among-origin differences in functional chemodiversity, reveals provenance-linked chemical fingerprints that complement genomic and metabolic trait data for climate-informed deployment. C_LI

Crop improvement can enhance food security, but side effects, such as trade-offs between valuable agronomic traits, are common. Likewise, fertilisation helps ensure high yields, but can devalue mutualisms with soil microbes that would otherwise be essential for nutrient acquisition. If the need for nutritional mutualisms is reduced in crops, mutualisms could be disrupted by selection relaxation or allocation trade-offs. Thus, crops could achieve high yields in spite of, or because of, disruption of nutritional mutualisms. Alternatively, the highest-yielding plants might flourish because they maximise nutrient acquisition from both symbionts and the soil. Here, enhanced mutualism could evolve over the course of agricultural crop improvement. To investigate whether high yields in cultivars and wild accessions are negatively or positively genetically correlated with outcomes in the legume-rhizobia mutualism, we measured whether yield and symbiosis traits trade-off or are positively genetically correlated among cultivars and wild accessions. We also tested whether this relationship differs between accessions released before or after 1950. We measured genetic correlations between yield and mutualism traits in 87 domesticated pea (Pisum sativum) accessions in a common garden agricultural field across three years. Seed yield and N2 fixation (%Ndfa) were positively genetically correlated. While N fixation was more strongly predictive of yield in the pre-1950 accessions than the post-1950 accessions, the underlying positive genetic correlation between the traits did not differ between the groups. The positive genetic correlation between yield and N2 fixation indicates that selection to increase yields has maintained or increased the benefits of the rhizobial mutualism in pea. Our findings predict that breeding to increase yield may continue to produce pea cultivars that get a greater proportion of their N from rhizobia, enhancing symbiotic mutualism and reducing the proportion of N supplied by fertilisation.

Cytokinin (CK) N-glucosides are the most abundant CK metabolites in Arabidopsis and most angiosperms, yet their role in cytokinin activity and response is unclear. Here, we examined metabolomic, transcriptomic, and proteomic profiles of seven CK N-glucoside conjugates in detached Arabidopsis leaves across a 144-hour dark-induced senescence (DIS) timecourse. All tested N-glucosides were found to undergo a slow conversion to their corresponding base forms at position-dependent rates, with N9-glucosides releasing base faster than their corresponding N7-glucosides. Conversion during DIS was strictly isoform-specific and not accompanied by coordinated induction of CK biosynthesis genes, arguing against de novo synthesis as the source of accumulated base. Despite progressive base accumulation, N-glucoside-treated leaves produced substantially fewer Differentially Expressed Genes than direct base application at comparable base concentrations, revealing a disconnect between hormone presence and transcriptional output. Unbiased model comparison identified the base:glucoside ratio as a stronger predictor of CK-Two Component Signaling (TCS) gene expression than absolute base concentration, though modulated by base-type-specific receptor affinities. Early proteomic profiling further revealed a coordinated response shared across N-glucosides but largely absent from base treatments. Together, these findings support that CK N-glucosides as kinetically slow, position-dependent reservoirs whose presence in abundance modulate activation of CK-TCS elicited by bioactive forms. HighlightsPhysiology, metabolomic, transcriptomic, and proteomic findings here support CK N-glucosides as kinetically slow, position-dependent reservoirs whose presence in abundance modulate activation of CK-TCS elicited by bioactive forms.

Pattern recognition receptors (PRRs) mediate plant immune responses by detecting extracellular immunogenic patterns, including microbe-associated molecular patterns (MAMPs). PRR signaling is commonly assessed using assays such as reactive oxygen species (ROS) bursts, cytosolic calcium influx, mitogen-activated protein kinase (MAPK) activation, and seedling growth inhibition (SGI), which are performed in distinct experimental systems, including seedlings grown on artificial media and soil-grown rosettes. Here, we systematically compare receptor kinase immune outputs triggered by the bacterial MAMPs elf18 and flg22 in Arabidopsis thaliana seedlings and rosettes across a range of concentrations. Rosettes exhibited greater sensitivity than seedlings in ROS assays, whereas cytosolic calcium responses measured using the Aeqcyt/pMAQ2 reporter were stronger in seedlings, correlating with reduced reporter transcript accumulation in rosette tissue. MAPK activation was consistently stronger in rosettes, whereas SGI assays revealed higher sensitivity to elf18 than flg22 in seedlings despite flg22 inducing stronger early signaling outputs. Together, these results demonstrate that canonical PRR-mediated immune outputs are differentially sensitive to experimental context and should not be interpreted as interchangeable measures of immune activation. These findings highlight the importance of considering experimental conditions when comparing immune responses across assays and developmental stages.

Belowground plant trait research has predominantly focused on trade-offs in fine root traits via the root economics space. Yet, this fine root framework captures only a fraction of the functional strategies plants employ beneath the soil surface. Here, we broaden the perspective on belowground plant functioning by integrating traits related to root system extent, clonality and bud banks, using data from the new UNDERPLOT database. This integration links measurable traits to key belowground functions: resource acquisition, spatial exploration, and persistence. Our analysis shows that the fine root economics space explains less than 5% of the variation in traits related to root system extent, clonality, and bud banks. Instead, an expanded trait analysis reveals three significant dimensions, explaining 62% of total trait variation. The third dimension, represents an independent, persistence-related gradient, not captured by existing root economics frameworks. We propose that understanding belowground plant strategies requires embracing additional functional gradients. The strategy of persistence, in particular, varies significantly across growth forms and is a critical dimension of plant response to resource limitation and stress, becoming increasingly important as global change shifts disturbance regimes.

Accurate and reproducible assessment of foliar disease severity is essential for evaluating the performance of heterogeneous plant communities and understanding host-pathogen interactions. However, traditional visual scoring methods remain subjective, with limited precision, and difficult to scale in large phenotyping experiments. Here, we present a semi-automated image analysis workflow designed to quantify multiple foliar disease symptoms simultaneously on wheat flag leaves sampled from varietal mixtures. The workflow combines three methodological components: (i) a standardized protocol for leaf sampling and imaging, (ii) supervised machine learning segmentation using Random Forest implemented in Ilastik to classify multiple symptoms (powdery mildew and yellow rust), and (iii) a graphical user interface facilitating pipeline deployment by non-specialist operators. To evaluate the influence of image representation on classification performance, four color spaces (RGB, HSV, HLS, LAB) were systematically compared. The approach was validated using images of durum wheat flag leaves collected from a field experiment assessing eight-way varietal mixtures under natural fungal pressure. Cross-validation against manually annotated images demonstrated high segmentation accuracy across all symptom. Comparison among color spaces revealed only minor differences in performance. Overall, this workflow offers a cost-effective, annotation-efficient and reproducible alternative to deep learning approaches, leveraging open-source and actively maintained tools while requiring limited training data and enabling objective, reproducible and scalable disease phenotyping.

Pollen development and fertilization are considered the most heat-sensitive stages of plant reproduction. While heat stress severely impairs pollen germination and tube growth, the physiological diversity within a single flowers pollen load suggests that subpopulations may exhibit differential climate resilience. In this study, we tested the hypothesis that this heterogeneity reflects a dormancy-based reserve mechanism that preserves fertilization under heat stress. Using flow cytometry and fluorescence-activated cell sorting in Arabidopsis thaliana and Solanum lycopersicum (MicroTom), we resolved pollen subpopulations by reactive oxygen species (ROS) status and examined their behavior under increasing heat stress. In both species, ROS-defined metabolic state was tightly associated with pollen size: high-ROS pollen was larger and readily germination-competent, whereas low-ROS pollen was smaller and showed low basal germination, consistent with dormancy. Heat stress preferentially depleted the high-ROS fraction, whereas the low-ROS fraction persisted and, under heat stress, increased metabolic activity and size. By isolating low-ROS and high-ROS pollen, we further show that a brief heat treatment suppresses germination of active high-ROS pollen but promotes germination of dormant low-ROS pollen. These findings provide direct evidence that heat can release dormancy in low-ROS pollen and support a conserved model in which dormant pollen serves as a heat-resilient reproductive reserve.

Development of arbuscular mycorrhiza (AM), a symbiosis between plants and beneficial Glomeromycotan fungi, is largely under plant control. Several genes, required for AM development, are proposed to be regulated by the karrikin signalling module, comprising the alpha/beta hydrolase receptor KARRIKIN INSENSITIVE 2 (KAI2), the F-box protein MORE AXILLARY GROWTH2 (MAX2) and the transcriptional repressor SUPPRESSOR OF MAX2 1 (SMAX1), which is ubiquitylated for proteasomal degradation upon KAI2-ligand-induced binding to the KAI2-MAX2 complex. Rice and Brachypodium distachyon kai2 mutants are incapable of forming AM. Here, we show that in Lotus japonicus, Pisum sativum, and Nicotiana benthamiana, KAI2 only quantitatively affects AM development, indicating angiosperms vary in their requirement for KAI2-signalling to support AM. Comparative transcriptomics of L. japonicus and B. distachyon roots after treatment with fungal signalling molecules revealed some AM-relevant genes respond KAI2-independently in L. japonicus but not in B. distachyon. Consistently we obtained evidence for low-level degradation of SMAX1 in Ljkai2a,b observed through a ratiometric reporter for the SMAX1 degron (SMAX1D2). Further, we found an unexpected accumulation of SMAX1D2 in in response to AM even in wild type. Together, this suggests an unexpected role of SMAX1 accumulation in AM roots and that in AM symbiosis of L. japonicus, redundant mechanisms drive SMAX1 degradation and gene activation independently of KAI2.

Growth kinematics and soil mechanics are key to explain how roots overcome the mechanical resistance of soil, yet few studies are linking these two factors. Formulas for cone penetration tests are typically used to infer the friction experienced by roots, but these fail to consider how growth affects the external forces applied on the root. This study formalised how expansive growth in the root apical meristem can reduce soil friction, and applied the framework to analyse the growth strategy of 6 plant species. The results of the analysis revealed trade-offs between reducing frictions, maintaining a desired growth trajectory and elongation rate. A shorter elongation zone can reduce the fraction of the mechanical energy lost to friction, but this is done at the expense of the elongation rate. A sharper tip or increased radius can help roots maintain the elongation rate at no energetic cost, but these strategies come with the cost of growth instability (tortuous roots) and decrease in specific root length respectively. During establishment, root strategies may therefore occupy a 2-dimensional trait space in which the mechanical efficiency of growth is balanced against the explorative-exploitative trade-off. HighlightsGrowth and form of root tips explain how plants overcome mechanical resistance from the soil Trade-offs link the energy lost by friction, growth stability and elongation rate of roots Larger roots allow faster growth independently of these trade-offs New framework formalises plants strategies to acquire soil resources

Phenotypic plasticity can buffer the potential fitness consequences of environmental change, yet limited understanding of its genetic basis constrains its application to predicting population response to future climates. Hybrid zones provide powerful systems to study the genetic basis of plasticity because admixture can create novel allele combinations that generate new reaction norms for selection to act upon. Here, we combine two clonally replicated common gardens of Populus trichocarpa x P. balsamifera genotypes with whole-genome resequencing to identify genetic variation underlying plasticity for physiological traits. Admixed genotypes exhibited broader, and in some cases novel, reaction norms relative to parental genotypes, particularly for key stomatal traits. Admixture mapping of genotype-specific reaction norms identified ten candidate genes on chromosome 15, including TWIST, associated with plasticity in adaxial stomatal occurrence and density. Using random forest models, we projected allele-specific responses to climate warming within the hybrid zone to link genetic variation in plasticity with predicted warming. Random forest models forecast that future climates would favor P. trichocarpa alleles at TWIST, while P. balsamifera alleles would be maintained in heterozygous genotypes. These results suggest that hybridization can expand reaction norms and maintain genetic variation that may facilitate rapid phenotypic response needed to adapt to climate change.

Ensuring global food security under rapid climate change demands accelerated genetic gain and breeding strategies that address complex Genotype-by-Environment (GxE) interactions. Traditional genomic selection models often fail to account for novel or extreme climates.Furthermore, integrating mechanistic crop growth models (CGMs) using traditional Bayesian frameworks to solve this issue presents severe computational bottlenecks. Here, we introduce DeepBioGS, a novel hybrid framework that integrates genomic selection with biophysical growth modelling via a fully differentiable deep learning architecture. DeepBioGS utilises a parameter-prediction multi-layer perceptron to map high-dimensional genomic markers to latent, highly heritable physiological traits (Genotype-Specific Parameters; GSP). These parameters mechanistically predict crop phenology across diverse environments. Using two multi-environment wheat datasets comprising over 6,000 genotypes, DeepBioGS extracted latent traits with near-perfect SNP-based heritability values (0.95-1.00). Crucially, the framework demonstrated superior or comparable predictive accuracy (up to r2 = 0.77) against standard genomic best linear unbiased prediction (GBLUP) and traditional Bayesian CGM-WGP models. Its architecture drastically improved computational scalability by enabling standard backpropagation, effectively bypassing the stochastic sampling limitations of approximate Bayesian methods. Most importantly for climate adaptation, DeepBioGS allowed accurate forecasting of genotype performance in entirely unobserved environmental conditions. By merging the representational power of deep learning with the structural constraints of biophysics, DeepBioGS provides a highly scalable, interpretable tool to navigate GxE interactions, enabling the assessment of cultivars under future climate scenarios, thus optimising crop breeding for a changing global environment.

Mediterranean forest restoration depends critically on autumn seedling outplanting and establishment, a period increasingly threatened by delayed and irregular precipitation. Although critical, drought at moderate temperatures, decoupled from summer heat stress, remains poorly characterized in terms of plant physiology and root microbiome responses. In the present study we simulated a short but severe drought under moderate air temperatures (5-25{degrees}C) in Pinus halepensis Mill. seedlings to examine the independent effects of water deficit on physiology and root-associated microbial communities. Drought reduced stomatal conductance to one-third of control values and induced a decoupling between stomatal conductance and net photosynthesis upon rewatering. This decoupling is rather due to the residual hydraulic and biochemical limitations rather than transpirational cooling demands. Drought-treated seedlings diverged into distinct phenotypic classes differing in recovery capacity, with a subset failing to recover despite being phenotypically identical to the controls. Root microbiome restructuring was phenotype-dependent and differed between active and resident fractions: bacterial richness and evenness increased while bacterial assembly shifted progressively toward determinism with increasing phenotype severity (29% to 37%), whereas fungal communities shifted toward stochastic drift (up to 89%). Functionally, drought disrupted symbiotic associations and drove a shift toward a fungal saprotrophic lifestyle. Network analyses revealed displacement of Rhizobium from its central hub position, reducing connectivity and compromising functional resilience. These results demonstrate that short, severe drought at moderate temperatures fundamentally affect plant-microbiome interactions through phenotype-dependent assembly processes, with direct consequences for seedling establishment and Mediterranean reforestation under climate change.

Accurate quantification of leaf lesion severity is essential for plant disease research and phenotyping but is often limited by subjective visual scoring and time-intensive manual image analysis. We present LIME, a fully automated, open-source image analysis pipeline for high-throughput quantification of leaf lesions from disease assay images. LIME integrates zero-shot leaf segmentation using the Segment Anything Model with a convolutional neural network for lesion area estimation. Applied to Arabidopsis thaliana leaves infected with Sclerotinia sclerotiorum, the proposed approach achieved a mean absolute percentage error of 12.9%, comparable to observed intrarater variability in manual scoring. Stratified evaluation across lesion-size groups demonstrated consistent prediction accuracy for small, intermediate, and large lesions, and comparative analysis showed that the deep learning-based model substantially outperformed color-based baseline methods. Under GPU-accelerated execution, LIME processed complete assays containing approximately 200 leaves in 15 minutes, representing an approximate 13-fold reduction in processing time relative to manual annotation. Together, these results indicate that LIME enables objective, reproducible, and scalable quantification of leaf lesion severity in standardized plant pathology assays. The pipeline is released as an open-source tool to support quantitative phenotyping studies.

Aldoximes are amino acid-derived metabolites that serve as precursors of auxins and modulate phenylpropanoid production in Arabidopsis. However, the enzymes responsible for aldoxime production in Solanaceae remain unknown. Here, we report the identification of aldoxime-producing enzymes in tomato (Solanum lycopersicum) and examine how altered aldoxime production affects auxin production and phenylpropanoid metabolism. Through homology-based analysis, we identified five putative CYP79 homologs in tomato, among which SlCYP79DB32 and SlCYP79DB52 exhibited aldoxime-producing activity toward multiple amino acids, including phenylalanine and tryptophan. SlCYP79DB32 and SlCYP79DB52 converted phenylalanine into phenylacetaldoxime (PAOx), whereas only SlCYP79DB52 converted tryptophan into indole-3-acetaldoxime (IAOx). Stable isotope-labeled feeding experiments revealed that IAOx and PAOx can be converted to the auxins indole-3-acetic acid (IAA) and phenylacetic acid (PAA), respectively. Consistently, tomato plants engineered to overproduce IAOx and PAOx accumulated elevated levels of IAA and PAA. These plants also accumulated lower levels of phenylpropanoids. In Brassicaceae plants such as Arabidopsis and Camelina, aldoxime accumulation represses phenylpropanoid production by promoting degradation of phenylalanine ammonia-lyase (PAL). However, aldoxime accumulation did not reduce PAL activity in tomato, suggesting an alternative mechanism in this species. Transcriptome analysis revealed extensive transcriptional reprogramming in aldoxime-overaccumulating tomato plants, including upregulation of stress- and defense-related genes. Despite the observed reduction in phenylpropanoid levels, transcript levels of most phenylpropanoid biosynthetic genes were not decreased, suggesting possible post-transcriptional regulation of this repression. Together, our findings demonstrate that aldoximes can serve as intermediates in auxin biosynthesis in tomato and reveal that aldoxime-mediated repression of phenylpropanoid metabolism extends beyond Brassicaceae.

O_LIPhotoperiod is a stable seasonal signal. Although the photoperiodic flowering is well understood in short-day (SD) and long-day (LD) annual plants, regulatory mechanisms in perennials remain elusive. In a perennial woodland strawberry (Fragaria vesca L.), flowering is induced in SDs in autumn and plants flower following spring, while in plants with mutated FvTERMINAL FLOWER1 (FvTFL1), LDs induce flowering. C_LIO_LIWe investigated photoperiodic flowering of F. vesca through phenotypic and molecular characterization of transgenic lines and their crosses. We studied natural variation in flowering time and gene expression in European accessions, and explored their correlations with climatic, geographical and genetic origins. C_LIO_LIWe showed that FvGIGANTEA (FvGI) and FvCONSTANS (FvCO) activate FvFLOWERING LOCUS T1 (FvFT1) in LDs resulting in early flowering in fvtfl1 mutant, while in SD F. vesca, activation of FvTFL1 by FvFT1 reverses the photoperiodic requirement of flowering. In natural accessions, decreasing expression of FvFT1 and FvTFL1 towards colder climates in the east and north correlated with earlier flowering. C_LIO_LIWe define a photoperiodic flowering mechanism controlling floral transition of perennial F. vesca in autumn that differs from known mechanisms in annual and perennial plants. Our findings open new avenues to understand how perennial plants cope with changing seasons across climatic and geographical ranges. C_LI

Norway spruce (Picea abies) responds to attacks by the spruce bark beetle (Ips typographus) through the rapid activation of local defense mechanisms, but field studies can be difficult to standardize due to variable attack pressure and environmental heterogeneity. Here, we developed a phytotron-based assay that mimics early beetle-associated stress using insect-derived protein extracts, enabling reproducible molecular analyses under controlled conditions. Ten-week-old spruce seedlings were stem-treated with mock buffer or beetle protein extracts, followed by transcriptomic analyses of stem tissues and targeted metabolomic profiling of needles at 2 and 48 h post-inoculation. RT-qPCR analysis revealed rapid transcriptional activation of signaling and defense genes in Norway spruce, with NP-40-based protein extracts producing the most consistent early response. RNA-seq analysis revealed transcriptional dynamics, with 488 differentially expressed genes detected at 2 h and 84 at 48 h post-inoculation relative to mock-treated controls. Early responses at 2 h were characterized by activation of genes associated with immune perception and signal transduction. By 48 h, the response shifted toward accumulation of transcripts encoding defense proteins such as chitinases, defensins, proteinase inhibitors, and pathogenesis-related (PR) proteins. Importantly, a substantial proportion of differentially expressed genes overlapped with those previously identified in mature Norway spruce trees during pioneer bark beetle attack under field conditions, supporting the biological relevance of the assay. In contrast, targeted analyses of secondary metabolites performed in needle tissue revealed limited systemic changes across time points, suggesting that early induced defenses may remain largely localized to the stem. Together, these results demonstrate that beetle-derived proteins trigger a rapid and temporally structured defense response in Norway spruce seedlings and establish a reproducible elicitor-based platform for dissecting conifer immune responses and screening spruce genotypes for bark beetle resistance. HighlightBark beetle protein elicitors trigger temporally structured immune responses in Norway spruce seedlings that overlap with responses observed in mature trees, with rapid immune signaling at 2 h followed by defense protein accumulation at 48 h.

AO_SCPLOWBSTRACTC_SCPLOWO_LIAirborne imaging spectroscopy enables species-level classification in hyperdiverse tropical forests, but accuracy varies enormously among species. We asked which ecological and evolutionary attributes make a tropical tree species spectrally separable. C_LIO_LIUsing 3,256 field-verified crowns spanning 169 species in a hyperdiverse moist forest in French Guiana, we tested seven hypothesised determinants of classification accuracy at species, pairwise, and individual-crown scales using random forest, beta regression, elastic net, and binomial GLMM analyses. C_LIO_LIPhenological regularity - the strength and consistency of seasonal leaf-cycling - was the single strongest predictor of separability, emerging as the top-ranked variable across all analyses. The presence of congeneric species in the classification pool also reduced accuracy, while broader phylogenetic isolation contributed in multivariate models. At the crown level, crown area was the strongest predictor of correct classification, while liana infestation reduced odds of correct identification by 38%. Leaf chemical traits did not predict separability. C_LIO_LIIt is the consistency of a species ecological signal - its phenological rhythm, spatial sampling, and freedom from canopy contamination - rather than any single functional trait, that determines whether it can be reliably mapped from imaging spectroscopy. C_LI

Meloidogyne incognita is a major plant-parasitic nematode responsible for substantial yield losses in tomato worldwide. Current control strategies rely heavily on chemical nematicides, which raise environmental concerns and face increasing regulatory restrictions, underscoring the need for sustainable alternatives. Here, we show that foliar application of an aqueous extract from cavalcade (Centrosema pascuorum) enhances tomato resistance against M. incognita. Pre-inoculation treatment with cavalcade extract prior to inoculation with root-knot nematodes (RKN) significantly reduced root gall formation, delayed nematode development, and limited second-stage juvenile penetration compared with untreated infected controls, whereas post-inoculation application conferred partial protection. Transcriptomic analyses revealed the activation of multiple defense-related pathways, including salicylic acid- and jasmonic acid-associated signaling and phenylpropanoid metabolism, supported by the upregulation of PR1 and PAL. Additional induction of lipid transfer proteins, leucine-rich repeat receptor-like kinases, resistance proteins, mitochondrial calcium uniporter, and GA2ox5 suggests coordinated activation of pathogen recognition, calcium signaling, and hormone-regulated defense networks. These findings demonstrate that cavalcade extract primes broad-spectrum defense responses in tomato and highlight its potential as an environmentally sustainable strategy for nematode management.