Evolution of the Correlated Genomic Variation Landscape Across a Divergence Continuum in the Genus Castanopsis.

The heterogeneous landscape of genomic variation has been well documented in population genomic studies. However, disentangling the intricate interplay of evolutionary forces influencing the genetic variation landscape over time remains challenging. In this study, we assembled a chromosome-level genome for Castanopsis eyrei and sequenced the whole genomes of 276 individuals from 12 Castanopsis species, spanning a broad divergence continuum. We found highly correlated genomic variation landscapes across these species. Furthermore, variations in genetic diversity and differentiation along the genome were strongly associated with recombination rates and gene density. These results suggest that long-term linked selection and conserved genomic features have contributed to the formation of a common genomic variation landscape. By examining how correlations between population summary statistics change throughout the species divergence continuum, we determined that background selection alone does not fully explain the observed patterns of genomic variation; the effects of recurrent selective sweeps must be considered. We further revealed that extensive gene flow has significantly influenced patterns of genomic variation in Castanopsis species. The estimated admixture proportion correlated positively with recombination rate and negatively with gene density, supporting a scenario of selection against gene flow. Additionally, putative introgression regions exhibited strong signals of positive selection, an enrichment of functional genes, and reduced genetic burdens, indicating that adaptive introgression has played a role in shaping the genomes of hybridizing species. This study provides insights into how different evolutionary forces have interacted in driving the evolution of the genomic variation landscape.

Between but Not Within-Species Variation in the Distribution of Fitness Effects.

New mutations provide the raw material for evolution and adaptation. The distribution of fitness effects (DFE) describes the spectrum of effects of new mutations that can occur along a genome, and is, therefore, of vital interest in evolutionary biology. Recent work has uncovered striking similarities in the DFE between closely related species, prompting us to ask whether there is variation in the DFE among populations of the same species, or among species with different degrees of divergence, that is whether there is variation in the DFE at different levels of evolution. Using exome capture data from six tree species sampled across Europe we characterized the DFE for multiple species, and for each species, multiple populations, and investigated the factors potentially influencing the DFE, such as demography, population divergence, and genetic background. We find statistical support for the presence of variation in the DFE at the species level, even among relatively closely related species. However, we find very little difference at the population level, suggesting that differences in the DFE are primarily driven by deep features of species biology, and those evolutionarily recent events, such as demographic changes and local adaptation, have little impact.

ß-Aminobutyric acid promotes stress tolerance, physiological adjustments, as well as broad epigenetic changes at DNA and RNA nucleobases in field elms (Ulmus minor).

BACKGROUND: ß-Aminobutyric acid (BABA) has been successfully used to prime stress resistance in numerous plant species; however, its effectiveness in forest trees has been poorly explored thus far. This study aimed to investigate the influence of BABA on morphological, physiological, and epigenetic parameters in field elms under various growth conditions. Epigenetic changes were assessed in both DNA and RNA through the use of reversed-phase ultra-performance liquid chromatography (UPLC) coupled with sensitive mass spectrometry. RESULTS: The presented results confirm the influence of BABA on the development, physiology, and stress tolerance in field elms. However, the most important findings are related to the broad epigenetic changes promoted by this amino acid, which involve both DNA and RNA. Our findings confirm, for the first time, that BABA influences not only well-known epigenetic markers in plants, such as 5-methylcytosine, but also several other non-canonical nucleobases, such as 5-hydroxymethyluracil, 5-formylcytosine, 5-hydroxymethylcytosine, N6-methyladenine, uracil (in DNA) and thymine (in RNA). The significant effect on the levels of N6-methyladenine, the main bacterial epigenetic marker, is particularly noteworthy. In this case, the question arises as to whether this effect is due to epigenetic changes in the microbiome, the plant genome, or both. CONCLUSIONS: The plant phenotype is the result of complex interactions between the plant's DNA, the microbiome, and the environment. We propose that different types of epigenetic changes in the plant and microbiome may play important roles in the largely unknown memory process that enables plants to adapt faster to changing environmental conditions.

Genomic insights into hybrid zone formation: The role of climate, landscape, and demography in the emergence of a novel hybrid lineage.

Population demographic changes, alongside landscape, geographic and climate heterogeneity, can influence the timing, stability and extent of introgression where species hybridise. Thus, quantifying interactions across diverged lineages, and the relative contributions of interspecific genetic exchange and selection to divergence at the genome-wide level is needed to better understand the drivers of hybrid zone formation and maintenance. We used seven latitudinally arrayed transects to quantify the contributions of climate, geography and landscape features to broad patterns of genetic structure across the hybrid zone of Populus trichocarpa and P. balsamifera and evaluated the demographic context of hybridisation over time. We found genetic structure differed among the seven transects. While ancestry was structured by climate, landscape features influenced gene flow dynamics. Demographic models indicated a secondary contact event may have influenced contemporary hybrid zone formation with the origin of a putative hybrid lineage that inhabits regions with higher aridity than either of the ancestral groups. Phylogenetic relationships based on chloroplast genomes support the origin of this hybrid lineage inferred from demographic models based on the nuclear data. Our results point towards the importance of climate and landscape patterns in structuring the contact zones between P. trichocarpa and P. balsamifera and emphasise the value whole genome sequencing can have to advancing our understanding of how neutral processes influence divergence across space and time.

Hybridization mediated range expansion and climate change resilience in two keystone tree species of boreal forests.

Current global climate change is expected to affect biodiversity negatively at all scales leading to mass biodiversity loss. Many studies have shown that the distribution of allele frequencies across a species' range is often influenced by specific genetic loci associated with local environmental variables. This association reflects local adaptation and allele changes at those loci could thereby contribute to the evolutionary response to climate change. However, predicting how species will adapt to climate change from this type of data alone remains challenging. In the present study, we combined exome capture sequences and environmental niche reconstruction, to test multiple methods for assessing local adaptation and climate resilience in two widely distributed conifers, Norway spruce and Siberian spruce. Both species are keystone species of the boreal forest and share a vast hybrid zone. We show that local adaptation in conifers can be detected through allele frequency variation, population-level ecological preferences, and historical niche movement. Moreover, we integrated genetic and ecological information into genetic offset predictive models to show that hybridization plays a central role in expanding the niche breadth of the two conifer species and may help both species to cope better with future changing climates. This joint genetic and ecological analysis also identified spruce populations that are at risk under current climate change.

Elevated atmospheric carbon dioxide and plant immunity to fungal pathogens: do the risks outweigh the benefits?

Anthropogenic emissions have caused atmospheric carbon dioxide (CO2) concentrations to double since the industrial revolution. Although this could benefit plant growth from the 'CO2 fertilisation' effect, recent studies report conflicting impacts of elevated CO2 (eCO2) on plant-pathogen interactions. Fungal pathogens are the leading cause of plant disease. Since climate change has been shown to affect the distribution and virulence of these pathogens, it is important to understand how their plant hosts may also respond. This review assesses existing reports of positive, negative, and neutral effects of eCO2 on plant immune responses to fungal pathogen infection. The interaction between eCO2 and immunity appears specific to individual pathosystems, dependent on environmental context and driven by the interactions between plant defence mechanisms, suggesting no universal effect can be predicted for the future. This research is vital for assessing how plants may become more at risk under climate change and could help to guide biotechnological efforts to enhance resistance in vulnerable species. Despite the importance of understanding the effects of eCO2 on plant immunity for protecting global food security, biodiversity, and forests in a changing climate, many plant-pathogen interactions are yet to be investigated. In addition, further research into the effects of eCO2 in combination with other environmental factors associated with climate change is needed. In this review, we highlight the risks of eCO2 to plants and point to the research required to address current unknowns.

Dynamic Adaptation Attack Detection Model for a Distributed Multi-Access Edge Computing Smart City.

The internet of things (IoT) technology presents an intelligent way to improve our lives and contributes to many fields such as industry, communications, agriculture, etc. Unfortunately, IoT networks are exposed to many attacks that may destroy the entire network and consume network resources. This paper aims to propose intelligent process automation and an auto-configured intelligent automation detection model (IADM) to detect and prevent malicious network traffic and behaviors/events at distributed multi-access edge computing in an IoT-based smart city. The proposed model consists of two phases. The first phase relies on the intelligent process automation (IPA) technique and contains five modules named, specifically, dataset collection and pre-processing module, intelligent automation detection module, analysis module, detection rules and action module, and database module. In the first phase, each module composes an intelligent connecting module to give feedback reports about each module and send information to the next modules. Therefore, any change in each process can be easily detected and labeled as an intrusion. The intelligent connection module (ICM) may reduce the search time, increase the speed, and increase the security level. The second phase is the dynamic adaptation of the attack detection model based on reinforcement one-shot learning. The first phase is based on a multi-classification technique using Random Forest Trees (RFT), k-Nearest Neighbor (K-NN), J48, AdaBoost, and Bagging. The second phase can learn the new changed behaviors based on reinforced learning to detect zero-day attacks and malicious events in IoT-based smart cities. The experiments are implemented using a UNSW-NB 15 dataset. The proposed model achieves high accuracy rates using RFT, K-NN, and AdaBoost of approximately 98.8%. It is noted that the accuracy rate of the J48 classifier achieves 85.51%, which is lower than the others. Subsequently, the accuracy rates of AdaBoost and Bagging based on J48 are 98.9% and 91.41%, respectively. Additionally, the error rates of RFT, K-NN, and AdaBoost are very low. Similarly, the proposed model achieves high precision, recall, and F1-measure high rates using RFT, K-NN, AdaBoost, and Bagging. The second phase depends on creating an auto-adaptive model through the dynamic adaptation of the attack detection model based on reinforcement one-shot learning using a small number of instances to conserve the memory of any smart device in an IoT network. The proposed auto-adaptive model may reduce false rates of reporting by the intrusion detection system (IDS). It can detect any change in the behaviors of smart devices quickly and easily. The IADM can improve the performance rates for IDS by maintaining the memory consumption, time consumption, and speed of the detection process.

Genetic and Epigenetic Mechanisms of Longevity in Forest Trees.

Trees are unique in terms of development, sustainability and longevity. Some species have a record lifespan in the living world, reaching several millennia. The aim of this review is to summarize the available data on the genetic and epigenetic mechanisms of longevity in forest trees. In this review, we have focused on the genetic aspects of longevity of a few well-studied forest tree species, such as Quercus robur, Ginkgo biloba, Ficus benghalensis and F. religiosa, Populus, Welwitschia and Dracaena, as well as on interspecific genetic traits associated with plant longevity. A key trait associated with plant longevity is the enhanced immune defense, with the increase in gene families such as RLK, RLP and NLR in Quercus robur, the expansion of the CC-NBS-LRR disease resistance families in Ficus species and the steady expression of R-genes in Ginkgo biloba. A high copy number ratio of the PARP1 family genes involved in DNA repair and defense response was found in Pseudotsuga menziesii, Pinus sylvestris and Malus domestica. An increase in the number of copies of the epigenetic regulators BRU1/TSK/MGO3 (maintenance of meristems and genome integrity) and SDE3 (antiviral protection) was also found in long-lived trees. CHG methylation gradually declines in the DAL 1 gene in Pinus tabuliformis, a conservative age biomarker in conifers, as the age increases. It was shown in Larix kaempferi that grafting, cutting and pruning change the expression of age-related genes and rejuvenate plants. Thus, the main genetic and epigenetic mechanisms of longevity in forest trees were considered, among which there are both general and individual processes.

A comprehensive genomic scan reveals gene dosage balance impacts on quantitative traits in Populus trees.

Gene dosage variation and the associated changes in gene expression influence a wide variety of traits, ranging from cancer in humans to yield in plants. It is also expected to affect important traits of ecological and agronomic importance in forest trees, but this variation has not been systematically characterized or exploited. Here we performed a comprehensive scan of the Populus genome for dosage-sensitive loci affecting quantitative trait variation for spring and fall phenology and biomass production. The study population was a large collection of clonally propagated F1 hybrid lines of Populus that saturate the genome 10-fold with deletions and insertions (indels) of known sizes and positions. As a group, the phenotypic means of the indel lines consistently differed from control nonindel lines, with an overall negative effect of both insertions and deletions on all biomass-related traits but more diverse effects and an overall wider phenotypic distribution of the indel lines for the phenology-related traits. We also investigated the correlation between gene dosage at specific chromosomal locations and phenotype, to identify dosage quantitative trait loci (dQTL). Such dQTL were detected for most phenotypes examined, but stronger effect dQTL were identified for the phenology-related traits than for the biomass traits. Our genome-wide screen for dosage sensitivity in a higher eukaryote demonstrates the importance of global genomic balance and the impact of dosage on life history traits.

Repeated Emergence of Sudden Oak Death in Oregon: Chronology, Impact, and Management.

It has been two decades since the first detection of the sudden oak death pathogen Phytophthora ramorum in Oregon forests. Although the epidemic was managed since its first discovery in 2001, at least three invasions of three separate variants (clonal lineages), NA1, EU1, and NA2, are documented to have occurred to date. Control of this epidemic has cost over US$32 million from 2001 to 2020. This is dwarfed by the predicted cost of the closure to the Coos Bay export terminal, estimated at $58 million per year, if the epidemic was allowed to spread unchecked. Management efforts in Oregon have reduced inoculum and limited the spread of the pathogen. An outreach and citizen scientist program has been piloted to help in early detection efforts and search for disease-resistant tanoak. This feature article documents the repeated emergence, impact, costs, and lessons learned from managing this devastating invasive pathogen.

The Intersection of Non-Coding RNAs Contributes to Forest Trees' Response to Abiotic Stress.

Non-coding RNAs (ncRNAs) play essential roles in plants by modulating the expression of genes at the transcriptional or post-transcriptional level. In recent years, ncRNAs have been recognized as crucial regulators for growth and development in forest trees, and ncRNAs that respond to various abiotic stresses are now under intense study. In this review, we summarized recent advances in the understanding of abiotic stress-responsive microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs) in forest trees. Furthermore, we analyzed the intersection of miRNAs, and epigenetic modified ncRNAs of forest trees in response to abiotic stress. In particular, the abiotic stress-related lncRNA/circRNA-miRNA-mRNA regulatory network of forest trees was explored.

Comparative Genomics of Seasonal Senescence in Forest Trees.

In the course of evolution, both flowering plants and some gymnosperms have developed such an adaptation to winter and unfavorable living conditions as deciduousness. Of particular interest is Siberian larch (Larix sibirica Ledeb.), which is the only species in the pine family (Pinaceae) with a seasonal deciduousness. New generation sequencing technologies make it possible to study this phenomenon at the genomic level and to reveal the genetic mechanisms of leaf and needle aging in angiosperms and gymnosperms. Using a comparative analysis of the genomes of evergreen and deciduous trees, it was found that the genes that control EXORDIUM LIKE 2 (EXL2) and DORMANCY-ASSOCIATED PROTEIN 1 (DRM1) proteins are most represented in Siberian larch, while an excess of genes that control proteins acting as immune receptors were found in evergreens. Orthologs from the family of genes that control leucine-rich repeat receptor-like kinases (LRR-RLK) contributed mostly to the distinction between evergreens and deciduous plants.

Above-ground biomass references for urban trees from terrestrial laser scanning data.

BACKGROUND AND AIMS: Within extending urban areas, trees serve a multitude of functions (e.g. carbon storage, suppression of air pollution, mitigation of the 'heat island' effect, oxygen, shade and recreation). Many of these services are positively correlated with tree size and structure. The quantification of above-ground biomass (AGB) is of especial importance to assess its carbon storage potential. However, quantification of AGB is difficult and the allometries applied are often based on forest trees, which are subject to very different growing conditions, competition and form. In this article we highlight the potential of terrestrial laser scanning (TLS) techniques to extract highly detailed information on urban tree structure and AGB. METHODS: Fifty-five urban trees distributed over seven cities in Switzerland were measured using TLS and traditional forest inventory techniques before they were felled and weighed. Tree structure, volume and AGB from the TLS point clouds were extracted using quantitative structure modelling. TLS-derived AGB estimates were compared with AGB estimates based on forest tree allometries dependent on diameter at breast height only. The correlations of various tree metrics as AGB predictors were assessed. KEY RESULTS: Estimates of AGB derived by TLS showed good performance when compared with destructively harvested references, with an R2 of 0.954 (RMSE = 556 kg) compared with 0.837 (RMSE = 1159 kg) for allometrically derived AGB estimates. A correlation analysis showed that different TLS-derived wood volume estimates as well as trunk diameters and tree crown metrics show high correlation in describing total wood AGB, outperforming tree height. CONCLUSIONS: Wood volume estimates based on TLS show high potential to estimate tree AGB independent of tree species, size and form. This allows us to retrieve highly accurate non-destructive AGB estimates that could be used to establish new allometric equations without the need for extensive destructive harvesting.

A Machine Learning Approach as a Surrogate for a Finite Element Analysis: Status of Research and Application to One Dimensional Systems.

Current maintenance intervals of mechanical systems are scheduled a priori based on the life of the system, resulting in expensive maintenance scheduling, and often undermining the safety of passengers. Going forward, the actual usage of a vehicle will be used to predict stresses in its structure, and therefore, to define a specific maintenance scheduling. Machine learning (ML) algorithms can be used to map a reduced set of data coming from real-time measurements of a structure into a detailed/high-fidelity finite element analysis (FEA) model of the same system. As a result, the FEA-based ML approach will directly estimate the stress distribution over the entire system during operations, thus improving the ability to define ad-hoc, safe, and efficient maintenance procedures. The paper initially presents a review of the current state-of-the-art of ML methods applied to finite elements. A surrogate finite element approach based on ML algorithms is also proposed to estimate the time-varying response of a one-dimensional beam. Several ML regression models, such as decision trees and artificial neural networks, have been developed, and their performance is compared for direct estimation of the stress distribution over a beam structure. The surrogate finite element models based on ML algorithms are able to estimate the response of the beam accurately, with artificial neural networks providing more accurate results.

Can Forest Trees Cope with Climate Change?-Effects of DNA Methylation on Gene Expression and Adaptation to Environmental Change.

Epigenetic modifications, including chromatin modifications and DNA methylation, play key roles in regulating gene expression in both plants and animals. Transmission of epigenetic markers is important for some genes to maintain specific expression patterns and preserve the status quo of the cell. This article provides a review of existing research and the current state of knowledge about DNA methylation in trees in the context of global climate change, along with references to the potential of epigenome editing tools and the possibility of their use for forest tree research. Epigenetic modifications, including DNA methylation, are involved in evolutionary processes, developmental processes, and environmental interactions. Thus, the implications of epigenetics are important for adaptation and phenotypic plasticity because they provide the potential for tree conservation in forest ecosystems exposed to adverse conditions resulting from global warming and regional climate fluctuations.

Evolutionary network genomics of wood formation in a phylogenetic survey of angiosperm forest trees.

Wood formation was present in early angiosperms, but has been highly modified through evolution to generate the anatomical diversity seen in extant angiosperm lineages. In this project, we modeled changes in gene coexpression relationships associated with the evolution of wood formation in a phylogenetic survey of 13 angiosperm tree species. Gravitropic stimulation was used as an experimental treatment to alter wood formation and also perturb gene expression. Gene transcript abundances were determined using RNA sequencing of developing wood tissues from upright trees, and from the top (tension wood) and bottom (opposite wood) tissues of gravistimulated trees. A network-based approach was employed to align gene coexpression networks across species based on orthologous relationships. A large-scale, multilayer network was modeled that identified both lineage-specific gene coexpression modules and modules conserved across multiple species. Functional annotation and analysis of modules identified specific regulatory processes associated with conserved modules, including regulation of hormones, protein phosphorylation, meristem development and epigenetic processes. Our results provide novel insights into the evolution and development of wood formation, and demonstrate the ability to identify biological processes and genes important for the evolution of a foundational trait in nonmodel, undomesticated forest trees.

Population structure, diversifying selection, and local adaptation in Pinus patula.

PREMISE: Climate change is predicted to affect natural and plantation forests. The responses of conifers to overcome changing environments will depend on their adaptation to local conditions; however, intraspecific adaptive genetic variation is unknown for most gymnosperms. Studying genetic diversity associated with phenotypic variability along environmental gradients will enhance our understanding of adaptation and may reveal genetic pools important for conservation and management. METHODS: We used target enrichment and genome skimming to obtain single nucleotide polymorphisms (SNPs) from 61 individuals of Pinus patula, a pine tree native to Mexico widely used in plantation forestry. We investigated the adaptive genetic variation of two varieties with morphological and distributional differences potentially related to genetic and adaptive divergence. RESULTS: Population structure and haplotype network analyses revealed that genetic diversity between P. patula var. patula and P. patula var. longipedunculata was structured, even within populations of P. patula var. longipedunculata. We observed high genetic diversity, low inbreeding rate, and rapid linkage disequilibrium (LD) decay in the varieties. Based on outlier tests, loci showing signatures of natural selection were detected in geographically distant P. patula var. longipedunculata populations. For both varieties, we found significant correlations between climate-related environmental variation and SNP diversity at loci involved in abiotic stress, cell transport, defense, and cell wall biogenesis, pointing to local adaptation. CONCLUSIONS: Overall, significant intraspecific adaptive genetic variation in P. patula was detected, highlighting the presence of different genetic pools and signs of local adaptation that should be considered in forestry and conservation.

Increased autumn productivity permits temperate trees to compensate for spring frost damage.

Climate warming is leading to earlier budburst and therefore an increased risk of spring frost injury to young leaves. But to what extent are second-cohort leaves, which trees put out after leaf-killing frosts, able to compensate incurred losses? To investigate whether second-cohort leaves behave differently from first-cohort leaves, we exposed saplings of beech (Fagus sylvatica), oak (Quercus robur), and honeysuckle (Lonicera xylosteum) to experimental treatments mimicking either a warm spring or a warm spring with a leaf-killing frost. Refoliation took 48, 43, and 36 d for beech, oak and honeysuckle, respectively. In beech and oak, autumn Chl content and photosynthesis rates were higher in second- than in first-cohort leaves, senescence in second-cohort leaves occurred c. 2-wk-later, and autumn bud growth in beech was elevated 66% in frost-damaged plants compared with the warm spring treatment. No differences in autumn phenology and growth were observed for honeysuckle. Overall, in beech and oak, delayed Chl breakdown in second-cohort leaves mitigated 31% and 25%, respectively, of the deficit in growing-season length incurred by spring frost damage. These results reveal an unexpected ability of second-cohort leaves of beech and oak to compensate for spring frost damage, and demonstrate that long-lived trees vary their autumnal phenology depending on preceding productivity.

Life cycle expression of inbreeding depression in Eucalyptus regnans and inter-generational stability of its mixed mating system.

BACKGROUND AND AIMS: Many plants exhibit a mixed mating system. Published models suggest that this might be an evolutionarily stable rather than a transitional state despite the presence of inbreeding depression, but there is little empirical evidence. Through field experimentation, we studied the role of inbreeding depression in eliminating inbred progeny from the reproductive cohort of the forest tree Eucalyptus regnans, and demonstrate a stable mixed primary mating system over two successive generations. METHODS: Two field experiments were conducted using seed from natural populations. We sowed open-pollinated seeds to simulate a natural regeneration event and determined isozyme genotypes of dominant and suppressed individuals over 10 years. We also planted a mixture of open-pollinated, outcross and selfed families with common maternal parentage; monitored survival of cross types over 29 years; and determined the percentage of outcrosses in open-pollinated seed from a sample of reproductively mature trees using microsatellite analysis. KEY RESULTS: Both experiments demonstrated progressive competitive elimination of inbred plants. By 29 years, the reproductive cohort in the planted experiment consisted only of outcrosses which produced seed which averaged 66 % outcrosses, similar to the estimate for the parental natural population (74 %). CONCLUSIONS: Selective elimination of inbred genotypes during the intense intra-specific competition characteristic of the pre-reproductive phase of the life cycle of E. regnans results in a fully outcrossed reproductive population, in which self-fertility is comparable with that of its parental generation. The mixed mating system may be viewed as an unavoidable consequence of the species' reproductive ecology, which includes the demonstrated effects of inbreeding depression, rather than a strategy which is actively favoured by natural selection.

Sequence of flower and leaf emergence in deciduous trees is linked to ecological traits, phylogenetics, and climate.

While much research has focused on the timing of individual plant phenological events, the sequence of phenological events has received considerably less attention. Here we identify drivers and patterns of flower and leaf emergence sequence (FLS) in deciduous tree species of the Great Lakes region of North America. Five hypotheses related to cold tolerance, water dynamics, seed mass, pollination syndrome, and xylem anatomy type were compared for their ability to explain FLS. Phylogenetic and geographic patterns of FLS were also assessed. We identified additional traits associated with FLS using Random Forest models. Of the hypotheses assessed, those related to species' water dynamics and seed mass had the greatest support. The spatial pattern of FLS was found to be strongly related to minimum monthly temperature and the phylogenetic pattern was clustered among species. Based on results from Random Forest models, species' fruiting characteristics were found to be the most important variables in explaining FLS. Our results show that FLS is related to a suite of plant traits and environmental tolerances. We emphasize the need to expand phenological research to include both the timing and sequence of plant's entire phenology, in particular in relation to plant physiology and global change.