What factors potentially influence the ability of phylogenetic distance to predict trait dispersion in a temperate forest?

Although phylogenetic‐based approaches have been frequently used to infer ecological processes, they have been increasingly criticized in recent years. To date, the factors that affect phylogenetic signals and further the ability of phylogenetic distance to predict trait dispersion have been assumed but not empirically tested. Therefore, we investigate which factors potentially influence the ability of phylogenetic distance to predict trait dispersion. We quantified the phylogenetic and trait dispersions across size classes and spatial scales in a 9‐ha old‐growth temperate forest dynamics plot in northeastern China. Phylogenetic signals at the community level were generally lower than those at the species pool level, and phylogenetically clustered communities showed lower phylogenetic signals than did overdispersed communities. This pattern might explain the other three findings of our study. First, phylogenetically overdispersed communities performed better at predicting trait dispersion than did clustered communities. Second, the mean pairwise distance (MPD)‐based metric exhibited a stronger correlation with trait dispersion than did the mean nearest taxon distance (MNTD)‐based metric. Finally, the MNTD‐based metric showed that the prediction accuracy for trait dispersion decreased with increasing spatial scales, whereas its effects were weak on the MPD‐based metric. In addition, phylogeny could not determine the dispersions of all functional axes but was able to predict certain traits depending on whether they were evolutionarily conserved. These results were conserved when we removed the effects of space and environment. Our findings highlighted that using phylogenetic distance as a proxy of trait similarity might work in a temperate forest depending on the species in local communities sampled from total pool as well as the traits measured. Utilizing these rules, we should rethink the conclusions of previous studies that were based on phylogenetic‐based approaches.     

DNA Barcoding for Species Assignment: The Case of Mediterranean Marine Fishes

Background

DNA barcoding enhances the prospects for species-level identifications globally using a standardized and authenticated DNA-based approach. Reference libraries comprising validated DNA barcodes (COI) constitute robust datasets for testing query sequences, providing considerable utility to identify marine fish and other organisms. Here we test the feasibility of using DNA barcoding to assign species to tissue samples from fish collected in the central Mediterranean Sea, a major contributor to the European marine ichthyofaunal diversity.

Methodology/Principal Findings

A dataset of 1278 DNA barcodes, representing 218 marine fish species, was used to test the utility of DNA barcodes to assign species from query sequences. We tested query sequences against 1) a reference library of ranked DNA barcodes from the neighbouring North East Atlantic, and 2) the public databases BOLD and GenBank. In the first case, a reference library comprising DNA barcodes with reliability grades for 146 fish species was used as diagnostic dataset to screen 486 query DNA sequences from fish specimens collected in the central basin of the Mediterranean Sea. Of all query sequences suitable for comparisons 98% were unambiguously confirmed through complete match with reference DNA barcodes. In the second case, it was possible to assign species to 83% (BOLD-IDS) and 72% (GenBank) of the sequences from the Mediterranean. Relatively high intraspecific genetic distances were found in 7 species (2.2%–18.74%), most of them of high commercial relevance, suggesting possible cryptic species.

Conclusion/Significance

We emphasize the discriminatory power of COI barcodes and their application to cases requiring species level resolution starting from query sequences. Results highlight the value of public reference libraries of reliability grade-annotated DNA barcodes, to identify species from different geographical origins. The ability to assign species with high precision from DNA samples of disparate quality and origin has major utility in several fields, from fisheries and conservation programs to control of fish products authenticity.     

Effect of environmental and spatial factors on the phylogenetic and functional diversity of the Mediterranean tree communities of Europe

• The tree flora of the Mediterranean Basin contains an outstanding taxonomic richness and a high proportion of endemic taxa. Contrary to other regions of the Mediterranean biome, a comprehensive phylogenetic analysis of the relationship between phylogenetic diversity, trait diversity and environmental factors in a spatial ecological context is lacking.
• We inferred the first calibrated phylogeny of 203 native tree species occurring in the European Mediterranean Basin based on 12 DNA regions. Using a set of four functional traits, we computed phylogenetic diversity for all 10,042 grid cells of 10 × 10 km spatial resolution to completely cover Mediterranean Europe. Then, we tested the spatial influence of environmental factors on tree diversity.
• Our results suggest that the nature of the relationship between traits and phylogeny varies among the different studied traits and according to the evolutionary distance considered. Phylogenetic diversity and functional diversity of European Mediterranean trees correlated strongly with species richness. High values of these diversity indices were located in the north of the study area, at high altitude, and minimum temperature of the coldest month. In contrast, the two phylogenetic indices that were not correlated with species richness (Mean Phylogenetic Distance, Phylogenetic Species Variability) were located in the south of the study area and were positively correlated with high altitude, soil organic carbon stock and sand soil texture.
• Our study provides support for the use of phylogenies in conservation biology to assess ecosystem functioning, and provides insights for the implementation of sustainable forest ecosystem management.

     

Selection of pairings reaching evenly across the data (SPREAD): A simple algorithm to design maximally informative fully crossed mating experiments

We present a novel algorithm for the design of crossing experiments. The algorithm identifies a set of individuals (a ‘crossing-set'') from a larger pool of potential crossing-sets by maximizing the diversity of traits of interest, for example, maximizing the range of genetic and geographic distances between individuals included in the crossing-set. To calculate diversity, we use the mean nearest neighbor distance of crosses plotted in trait space. We implement our algorithm on a real dataset of Neurospora crassa strains, using the genetic and geographic distances between potential crosses as a two-dimensional trait space. In simulated mating experiments, crossing-sets selected by our algorithm provide better estimates of underlying parameter values than randomly chosen crossing-sets.     

A fuzzy-set-theory-based approach to analyse species membership in DNA barcoding

Reliable assignment of an unknown query sequence to its correct species remains a methodological problem for the growing field of DNA barcoding. While great advances have been achieved recently, species identification from barcodes can still be unreliable if the relevant biodiversity has been insufficiently sampled. We here propose a new notion of species membership for DNA barcoding-fuzzy membership, based on fuzzy set theory-and illustrate its successful application to four real data sets (bats, fishes, butterflies and flies) with more than 5000 random simulations. Two of the data sets comprise especially dense species/population-level samples. In comparison with current DNA barcoding methods, the newly proposed minimum distance (MD) plus fuzzy set approach, and another computationally simple method, 'best close match', outperform two computationally sophisticated Bayesian and BootstrapNJ methods. The new method proposed here has great power in reducing false-positive species identification compared with other methods when conspecifics of the query are absent from the reference database.     

吉林蛟河针阔混交林功能性状分布格局及其对地形因素的响应

森林群落的构建过程及其内在机制是生态学研究的热点问题。植物功能性状是指能够代表植物的生活史策略,反映植物对环境变化响应的一系列植物属性。通过植物功能性状的分布格局及其对环境因素的响应有助于推测群落的构建过程及其内在作用机制。以吉林蛟河21.12hm²温带针阔混交林样地为研究对象,采集并测量了样地内34种木本植物的6种不同的功能性状。以20m×20m的样方为研究单元,通过计算平均成对性状距离指数（mean pairwise trait distance;PW）和平均最近邻体性状距离指数（mean nearest neighbor trait distance;NN）来探讨群落中单个性状和综合性状的分布格局。同时结合地形因子采用回归分析探讨功能性状的分布格局对局域生境变化的响应。基于PW的结果显示：单个性状中除叶面积外,其余性状的分布格局均为聚集分布多于离散分布;基于NN的结果显示：除叶面积和最大树高外,其余性状的分布格局为聚集分布多于离散分布。此外,由6种单个性状组成的综合性状的分布格局同样为聚集分布多于离散分布。基于回归分析的结果显示：森林群落中功能性状的分布格局受到海拔、坡度和坡向等因素的显著影响,而凹凸度的影响则不显著。研究结果表明包括环境过滤和生物相互作用的非随机过程能够影响温带针阔混交林的群落构建过程,中性过程对该区域群落构建过程的影响不显著。     

Genetic distance predicts trait differentiation at the subpopulation but not the individual level in eelgrass,Zostera marina

Ecological studies often assume that genetically similar individuals will be more similar in phenotypic traits, such that genetic diversity can serve as a proxy for trait diversity. Here, we explicitly test the relationship between genetic relatedness and trait distance using 40 eelgrass (Zostera marina) genotypes from five sites within Bodega Harbor, CA. We measured traits related to nutrient uptake, morphology, biomass and growth, photosynthesis, and chemical deterrents for all genotypes. We used these trait measurements to calculate a multivariate pairwise trait distance for all possible genotype combinations. We then estimated pairwise relatedness from 11 microsatellite markers. We found significant trait variation among genotypes for nearly every measured trait; however, there was no evidence of a significant correlation between pairwise genetic relatedness and multivariate trait distance among individuals. However, at the subpopulation level (sites within a harbor), genetic (F_ST) and trait differentiation were positively correlated. Our work suggests that pairwise relatedness estimated from neutral marker loci is a poor proxy for trait differentiation between individual genotypes. It remains to be seen whether genomewide measures of genetic differentiation or easily measured “master” traits (like body size) might provide good predictions of overall trait differentiation.     

Filling the gap in functional trait databases: use of ecological hypotheses to replace missing data

Functional trait databases are powerful tools in ecology, though most of them contain large amounts of missing values. The goal of this study was to test the effect of imputation methods on the evaluation of trait values at species level and on the subsequent calculation of functional diversity indices at community level using functional trait databases. Two simple imputation methods (average and median), two methods based on ecological hypotheses, and one multiple imputation method were tested using a large plant trait database, together with the influence of the percentage of missing data and differences between functional traits. At community level, the complete‐case approach and three functional diversity indices calculated from grassland plant communities were included. At the species level, one of the methods based on ecological hypothesis was for all traits more accurate than imputation with average or median values, but the multiple imputation method was superior for most of the traits. The method based on functional proximity between species was the best method for traits with an unbalanced distribution, while the method based on the existence of relationships between traits was the best for traits with a balanced distribution. The ranking of the grassland communities for their functional diversity indices was not robust with the complete‐case approach, even for low percentages of missing data. With the imputation methods based on ecological hypotheses, functional diversity indices could be computed with a maximum of 30% of missing data, without affecting the ranking between grassland communities. The multiple imputation method performed well, but not better than single imputation based on ecological hypothesis and adapted to the distribution of the trait values for the functional identity and range of the communities. Ecological studies using functional trait databases have to deal with missing data using imputation methods corresponding to their specific needs and making the most out of the information available in the databases. Within this framework, this study indicates the possibilities and limits of single imputation methods based on ecological hypothesis and concludes that they could be useful when studying the ranking of communities for their functional diversity indices.     

High functional diversity in deep‐sea fish communities and increasing intraspecific trait variation with increasing latitude

Variation in both inter‐ and intraspecific traits affects community dynamics, yet we know little regarding the relative importance of external environmental filters versus internal biotic interactions that shape the functional space of communities along broad‐scale environmental gradients, such as latitude, elevation, or depth. We examined changes in several key aspects of functional alpha diversity for marine fishes along depth and latitude gradients by quantifying intra‐ and interspecific richness, dispersion, and regularity in functional trait space. We derived eight functional traits related to food acquisition and locomotion and calculated seven complementary indices of functional diversity for 144 species of marine ray‐finned fishes along large‐scale depth (50–1200 m) and latitudinal gradients (29°–51° S) in New Zealand waters. Traits were derived from morphological measurements taken directly from footage obtained using Baited Remote Underwater Stereo‐Video systems and museum specimens. We partitioned functional variation into intra‐ and interspecific components for the first time using a PERMANOVA approach. We also implemented two tree‐based diversity metrics in a functional distance‐based context for the first time: namely, the variance in pairwise functional distance and the variance in nearest neighbor distance. Functional alpha diversity increased with increasing depth and decreased with increasing latitude. More specifically, the dispersion and mean nearest neighbor distances among species in trait space and intraspecific trait variability all increased with depth, whereas functional hypervolume (richness) was stable across depth. In contrast, functional hypervolume, dispersion, and regularity indices all decreased with increasing latitude; however, intraspecific trait variation increased with latitude, suggesting that intraspecific trait variability becomes increasingly important at higher latitudes. These results suggest that competition within and among species are key processes shaping functional multidimensional space for fishes in the deep sea. Increasing morphological dissimilarity with increasing depth may facilitate niche partitioning to promote coexistence, whereas abiotic filtering may be the dominant process structuring communities with increasing latitude.     

A new method for species identification via protein-coding and non-coding DNA barcodes by combining machine learning with bioinformatic methods

Species identification via DNA barcodes is contributing greatly to current bioinventory efforts. The initial, and widely accepted, proposal was to use the protein-coding cytochrome c oxidase subunit I (COI) region as the standard barcode for animals, but recently non-coding internal transcribed spacer (ITS) genes have been proposed as candidate barcodes for both animals and plants. However, achieving a robust alignment for non-coding regions can be problematic. Here we propose two new methods (DV-RBF and FJ-RBF) to address this issue for species assignment by both coding and non-coding sequences that take advantage of the power of machine learning and bioinformatics. We demonstrate the value of the new methods with four empirical datasets, two representing typical protein-coding COI barcode datasets (neotropical bats and marine fish) and two representing non-coding ITS barcodes (rust fungi and brown algae). Using two random sub-sampling approaches, we demonstrate that the new methods significantly outperformed existing Neighbor-joining (NJ) and Maximum likelihood (ML) methods for both coding and non-coding barcodes when there was complete species coverage in the reference dataset. The new methods also out-performed NJ and ML methods for non-coding sequences in circumstances of potentially incomplete species coverage, although then the NJ and ML methods performed slightly better than the new methods for protein-coding barcodes. A 100% success rate of species identification was achieved with the two new methods for 4,122 bat queries and 5,134 fish queries using COI barcodes, with 95% confidence intervals (CI) of 99.75-100%. The new methods also obtained a 96.29% success rate (95%CI: 91.62-98.40%) for 484 rust fungi queries and a 98.50% success rate (95%CI: 96.60-99.37%) for 1094 brown algae queries, both using ITS barcodes.     

Plant DNA barcodes and the influence of gene flow

Success of species assignment using DNA barcodes has been shown to vary among plant lineages because of a wide range of different factors. In this study, we confirm the theoretical prediction that gene flow influences species assignment with simulations and a literature survey. We show that the genome experiencing the highest gene flow is, in the majority of the cases, the best suited for species delimitation. Our results clearly suggest that, for most angiosperm groups, plastid markers will not be the most appropriate for use as DNA barcodes. We therefore advocate shifting the focus from plastid to nuclear markers to achieve an overall higher success using DNA barcodes.     

FuzzyID2: A software package for large data set species identification via barcoding and metabarcoding using hidden Markov models and fuzzy set methods

Species identification through DNA barcoding or metabarcoding has become a key approach for biodiversity evaluation and ecological studies. However, the rapid accumulation of barcoding data has created some difficulties: for instance, global enquiries to a large reference library can take a very long time. We here devise a two‐step searching strategy to speed identification procedures of such queries. This firstly uses a Hidden Markov Model (HMM) algorithm to narrow the searching scope to genus level and then determines the corresponding species using minimum genetic distance. Moreover, using a fuzzy membership function, our approach also estimates the credibility of assignment results for each query. To perform this task, we developed a new software pipeline, FuzzyID2, using Python and C++. Performance of the new method was assessed using eight empirical data sets ranging from 70 to 234,535 barcodes. Five data sets (four animal, one plant) deployed the conventional barcode approach, one used metabarcodes, and two were eDNA‐based. The results showed mean accuracies of generic and species identification of 98.60% (with a minimum of 95.00% and a maximum of 100.00%) and 94.17% (with a range of 84.40%–100.00%), respectively. Tests with simulated NGS sequences based on realistic eDNA and metabarcode data demonstrated that FuzzyID2 achieved a significantly higher identification success rate than the commonly used Blast method, and the TIPP method tends to find many fewer species than either FuzztID2 or Blast. Furthermore, data sets with tens of thousands of barcodes need only a few seconds for each query assignment using FuzzyID2. Our approach provides an efficient and accurate species identification protocol for biodiversity‐related projects with large DNA sequence data sets.     

Both rare and common species make unique contributions to functional diversity in an ecosystem unaffected by human activities

Aim

Rare species typically contribute more to functional diversity than common species. However, humans have altered the occupancy and abundance patterns of many species—the basis upon which we define “rarity.” Here, we use a globally unique dataset from hydrothermal vents—an untouched ecosystem—to test whether rare species over‐contribute to functional diversity.

Location

Juan de Fuca Ridge hydrothermal vent fields, Northeast Pacific Ocean.

Methods

We first conduct a comprehensive review to set up expectations for the relative contributions of rare and common species to functional diversity. We then quantify the rarity and commonness of 37 vent species with relevant trait information to assess the relationship between rarity and functional distinctiveness—a measure of the uniqueness of the traits of a species relative to traits of coexisting species. Next, we randomly assemble communities to test whether rare species over‐contribute to functional diversity in artificial assemblages ranging in species richness. Then, we test whether biotic interactions influence functional diversity contributions by comparing the observed contribution of each species to a null expectation. Finally, we identify traits driving functional distinctiveness using a distance‐based redundancy analysis.

Results

Across functional diversity metrics and species richness levels, we find that both rare and common species can contribute functional uniqueness. Some species always offer unique trait combinations, and these species host bacterial symbionts and provide habitat complexity. Moreover, we find that contributions of species to functional diversity may be influenced by biotic interactions.

Main conclusions

Our findings show that many common species make persistent, unique contributions to functional diversity. Thus, it is key to consider whether the abundance and occupancy of species have been reduced, relative to historical baselines, when interpreting the contributions of rare species to functional diversity. Our work highlights the importance of testing ecological theory in ecosystems unaffected by human activities for the conservation of biodiversity.     

Generalized DNA barcode design based on Hamming codes

The diversity and scope of multiplex parallel sequencing applications is steadily increasing. Critically, multiplex parallel sequencing applications methods rely on the use of barcoded primers for sample identification, and the quality of the barcodes directly impacts the quality of the resulting sequence data. Inspection of the recent publications reveals a surprisingly variable quality of the barcodes employed. Some barcodes are made in a semi empirical fashion, without quantitative consideration of error correction or minimal distance properties. After systematic comparison of published barcode sets, including commercially distributed barcoded primers from Illumina and Epicentre, methods for improved, Hamming code-based sequences are suggested and illustrated. Hamming barcodes can be employed for DNA tag designs in many different ways while preserving minimal distance and error-correcting properties. In addition, Hamming barcodes remain flexible with regard to essential biological parameters such as sequence redundancy and GC content. Wider adoption of improved Hamming barcodes is encouraged in multiplex parallel sequencing applications.     

林冠结构是局域尺度木本植物功能性状beta多样性形成的重要驱动力

功能性状beta多样性反映了群落间功能性状组成的差异, 解析其形成机制是群落生态学研究的核心内容之一。本研究以云南西双版纳热带季节雨林20 ha动态监测样地为研究对象, 测定木本植物11个重要的功能性状, 采用多度加权的平均最近邻体性状距离度量不同取样尺度的功能性状beta多样性, 基于距离矩阵的多元回归方法解析林冠结构差异、环境异质性、空间距离在功能性状beta多样性格局形成中的相对作用。结果表明, 对于所有木本植物个体(DBH ≥ 1 cm)而言, 同时考虑林冠结构、环境和空间距离的模型为解释功能性状beta多样性格局的最优模型; 在3个不同取样尺度上, 林冠结构差异和环境距离都对功能性状beta多样性具有较大的解释力, 且随着取样尺度的增大而上升, 空间距离的作用基本可以忽略。本研究证实了林冠结构是局域尺度木本植物功能性状beta多样性格局形成的重要驱动力, 这一发现更新了环境异质性和空间距离是驱动功能性状beta多样性格局形成的主要因素的传统认知, 为将来研究功能性状beta多样性形成机制提供新的视角, 并证实了取样尺度在解析木本植物功能性状beta多样性格局形成机制中的重要性。     

Phylogenetic diversity,trait diversity and niches: species assembly of ferns along a tropical elevational gradient

Aim To analyse the structure of pteridophyte assemblages, based on phylogenetic relatedness and trait properties, along an elevational gradient. Ecological theory predicts that co‐occurring species may be: randomly selected from a regional pool; ecologically sorted so that they are functionally different hence resulting in reduced competition (overdispersion); or functionally similar as an adaptation to specific ecological conditions (clustering). Location Braulio Carrillo National Park and Cerro de la Muerte, Costa Rica, Central America. Methods We used an empirical dataset of the quantitative pattern of species occurrences and individual numbers of ferns within 156 plots along a tropical elevational gradient to test whether directed ecological sorting might cause deviations in patterns of trait and phylogenetic diversity. Mean pairwise distances of species based on phylogenetic and trait properties were compared with two different sets of null assemblages, one maintaining species frequency distributions (constrained) and one not (unconstrained). Results Applying different null models resulted in varying degrees of overdispersion and clustering, but overall patterns of deviation from random expectations remained the same. Contrary to theoretical predictions, phylogenetic and trait diversity were relatively independent from one another. Phylogenetic diversity showed no patterns along the elevational gradient, whereas trait diversity showed significant trends for epiphytes. Main conclusions Under stressful environmental conditions (drought at low elevations and frost at high elevations), epiphytic fern assemblages tended to be clustered with respect to trait characteristics, which suggests environmental filtering. Conversely, under less extreme environmental conditions (middle of the transect), the sorting was biased towards high differentiation (overdispersion), presumably because of interspecific competition and trait shifts among closely related species (character displacement).     

群落/生态系统功能多样性研究方法及展望

功能多样性是指影响群落/生态系统功能的物种性状值和范围,是解释和预测生态系统结构和功能的有效手段之一,可将植物个体尺度与群落尺度和生态系统尺度的相关生态学问题联系起来。虽已发展出多种功能多样性定量化研究方法,但不同方法结果差异较大,难以进行多研究间的比较研究。比较探讨各功能多样性研究方法的优缺点有利于拓展功能多样性内涵,也有助于功能生态学的应用与发展。回顾了当前10种功能多样性的定量化研究方法,并指出选取合适功能多样性方法的关键在于,应考虑选取群落/生态系统中的哪些物种、哪些功能性状、选取的功能性状数目、以及如何对功能性状权重等。对比发现,功能分散性指数和Rao二次熵系数的研究方法在众多方法中优势明显,具有较高的应用潜力;标准化功能多样性的研究方法在未来仍需进一步完善。利用功能多样性指数预测群落/生态系统过程和功能当前仍多侧重于理论研究,野外实证研究较为缺乏,是功能生态学未来研究的重点和难点之一。     

Impact of grazing on germination trait selection in an alpine grassland on the Tibet Plateau

放牧对青藏高原高寒草地种子萌发性状选择的影响 以前的研究表明放牧能够引起草地生物与非生物环境的显著变化,但这种变化影响草地群落对种子萌发特征的选择机制尚不清楚。因此,我们旨在回答：放牧是否对草地群落中萌发特征的组成和多样性产生显著影响。我们在实验室检测了研究草地群落内主要物种种子的萌发特性,并比较了这些植物在放牧和非放牧草地上的表现。在此基础上,比较了放牧草地和非放牧草地的各萌发性状的群落加权平均值和萌发性状多样性,从而了解放牧草地和非放牧草地是否存在不同的萌发性状结构。研究结果表明,在物种水平上,放牧和非放牧草地各物种的多度变化与物种的萌发性状无显著关系。但在群落水平上,与非放牧草地相比,放牧草地的物种普遍具有较高的种子萌发率;放牧草地种子萌发对变温的正响应显著大于非放牧草地,而且放牧草地种子萌发温度生态位宽度小于非放牧草地。与非放牧草地相比,放牧草地种子萌发性状多样性增加,萌发性状均匀度降低。放牧可以改变微生境,从而通过环境过滤改变草地群落对萌发性状的选择,导致草地群落的萌发性状于放牧前后在群落水平上存 在显著差异。     

genotype and genodive: two programs for the analysis of genetic diversity of asexual organisms

Investigating diversity in asexual organisms using molecular markers involves the assignment of individuals to clonal lineages and the subsequent analysis of clonal diversity. Assignment is possible using a distance matrix in combination with a user‐specified threshold, defined as the maximum distance between two individuals that are considered to belong to the same clonal lineage. Analysis of clonal diversity requires tests for differences in diversity and clonal composition between populations. We developed two programs, genotype and genodive for such analyses of clonal diversity in asexually reproducing organisms. Additionally, genotype can be used for detecting genotyping errors in studies of sexual organisms.     

Testing Darwin's naturalization hypothesis in the Azores

Invasive species are a threat for ecosystems worldwide, especially oceanic islands. Predicting the invasive potential of introduced species remains difficult, and only a few studies have found traits correlated to invasiveness. We produced a molecular phylogenetic dataset and an ecological trait database for the entire Azorean flora and find that the phylogenetic nearest neighbour distance (PNND), a measure of evolutionary relatedness, is significantly correlated with invasiveness. We show that introduced plant species are more likely to become invasive in the absence of closely related species in the native flora of the Azores, verifying Darwin's 'naturalization hypothesis'. In addition, we find that some ecological traits (especially life form and seed size) also have predictive power on invasive success in the Azores. Therefore, we suggest a combination of PNND with ecological trait values as a universal predictor of invasiveness that takes into account characteristics of both introduced species and receiving ecosystem.