Evaluating Functional Diversity: Missing Trait Data and the Importance of Species Abundance Structure and Data Transformation

Functional diversity (FD) is an important component of biodiversity that quantifies the difference in functional traits between organisms. However, FD studies are often limited by the availability of trait data and FD indices are sensitive to data gaps. The distribution of species abundance and trait data, and its transformation, may further affect the accuracy of indices when data is incomplete. Using an existing approach, we simulated the effects of missing trait data by gradually removing data from a plant, an ant and a bird community dataset (12, 59, and 8 plots containing 62, 297 and 238 species respectively). We ranked plots by FD values calculated from full datasets and then from our increasingly incomplete datasets and compared the ranking between the original and virtually reduced datasets to assess the accuracy of FD indices when used on datasets with increasingly missing data. Finally, we tested the accuracy of FD indices with and without data transformation, and the effect of missing trait data per plot or per the whole pool of species. FD indices became less accurate as the amount of missing data increased, with the loss of accuracy depending on the index. But, where transformation improved the normality of the trait data, FD values from incomplete datasets were more accurate than before transformation. The distribution of data and its transformation are therefore as important as data completeness and can even mitigate the effect of missing data. Since the effect of missing trait values pool-wise or plot-wise depends on the data distribution, the method should be decided case by case. Data distribution and data transformation should be given more careful consideration when designing, analysing and interpreting FD studies, especially where trait data are missing. To this end, we provide the R package “traitor” to facilitate assessments of missing trait data.     

A global meta‐analysis of the relative extent of intraspecific trait variation in plant communities

Recent studies have shown that accounting for intraspecific trait variation (ITV) may better address major questions in community ecology. However, a general picture of the relative extent of ITV compared to interspecific trait variation in plant communities is still missing. Here, we conducted a meta‐analysis of the relative extent of ITV within and among plant communities worldwide, using a data set encompassing 629 communities (plots) and 36 functional traits. Overall, ITV accounted for 25% of the total trait variation within communities and 32% of the total trait variation among communities on average. The relative extent of ITV tended to be greater for whole‐plant (e.g. plant height) vs. organ‐level traits and for leaf chemical (e.g. leaf N and P concentration) vs. leaf morphological (e.g. leaf area and thickness) traits. The relative amount of ITV decreased with increasing species richness and spatial extent, but did not vary with plant growth form or climate. These results highlight global patterns in the relative importance of ITV in plant communities, providing practical guidelines for when researchers should include ITV in trait‐based community and ecosystem studies.     

The quest for trait convergence and divergence in community assembly: are null‐models the magic wand?

The relevance of neutral versus niche‐based community assembly rules (i.e. the processes sorting species present in a larger geographical region into local communities) remains to be demonstrated in ecology and biogeography. To attempt to do this, a number of complex null models are increasingly being used that compare observed community functional diversity (FD, i.e. the extent of trait dissimilarity between coexisting species) with randomly simulated FD. However, little is known about the performance of these null models in detecting non‐neutral community assembly rules such as trait convergence and divergence of communities (supposedly revealing habitat selection and limiting similarity, respectively). Here, using both simulated and field communities, I show that assembly rule detection varies systematically with the magnitude of the observed FD, so that these null models do not really succeed in breaking down the observed functional relationships between species. This is a particular concern, making detection of community assembly dependent on: (1) the pool of samples considered, and (2) the capacity of observed FD to correctly discriminate these rules. Null models should be more thoroughly described and validated before being considered as a magic wand to reveal assembly patterns.     

Disentangling community functional components in a litter‐macrodetritivore model system reveals the predominance of the mass ratio hypothesis

Recent investigations have shown that two components of community trait composition are important for key ecosystem processes: (i) the community‐weighted mean trait value (CWM), related to the mass ratio hypothesis and dominant trait values in the community, and (ii) functional diversity (FD), related to the complementarity hypothesis and the divergence of trait values. However, no experiments controlling for the inherent dependence between CWM and FD have been conducted so far. We used a novel experimental framework to disentangle the unique and shared effects of CWM and FD in a leaf litter‐macrodetritivore model system. We manipulated isopod assemblages varying in species number, CWM and FD of litter consumption rate to test the relative contribution of these community parameters in the decomposition process. We showed that CWM, but also the combination of CWM and FD, is a main factor controlling litter decomposition. When we tested individual biodiversity components separately, CWM of litter consumption rate showed a significant effect on decomposition, while FD and species richness alone did not. Our study demonstrated that (i) trait composition rather than species diversity drives litter decomposition, (ii) dominant trait values in the community (CWM) play a chief role in driving ecosystem processes, corroborating the mass ratio hypothesis, and (iii) trait dissimilarity can contribute in modulating the overall biodiversity effects. Future challenge is to assess whether the generality of our finding, that is, that dominant trait values (CWM) predominate over trait dissimilarity (FD), holds for other ecosystem processes, environmental conditions and different spatial and temporal scales.     

A dimmer shade of pale: revealing the faint signature of local assembly processes on the structure of strongly filtered plant communities

Trait‐based ecology suggests that abiotic filtering is the main mechanism structuring the regional species pool in different subsets of habitat‐specific species. At more local spatial scales, other ecological processes may add on giving rise to complex patterns of functional diversity (FD). Understanding how assembly processes operating on the habitat‐specific species pools produce the locally observed plant assemblages is an ongoing challenge. Here, we evaluated the importance of different processes to community assembly in an alpine fellfield, assessing its effects on local plant trait FD. Using classical randomization tests and linear mixed models, we compared the observed FD with expectations from three null models that hierarchically incorporate additional assembly constraints: stochastic null models (random assembly), independence null models (each species responding individual and independently to abiotic environment), and co‐occurrence null models (species responding to environmental variation and to the presence of other species). We sampled species composition in 115 quadrats across 24 locations in the central Pyrenees (Spain) that differed in soil conditions, solar radiation and elevation. Overall, the classical randomization tests were unable to find differences between the observed and expected functional patterns, suggesting that the strong abiotic filters that sort out the flora of extreme regional environments blur any signal of other local processes. However, our approach based on linear mixed models revealed the signature of different ecological processes. In the case of seed mass and leaf thickness, observed FD significantly deviated from the expectations of the stochastic model, suggesting that fine‐scale abiotic filtering and facilitation can be behind these patterns. Our study highlights how the hierarchical incorporation of ecological additional constraints may shed light on the dim signal left by local assembly processes in alpine environments.     

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.     

Functional traits composition predict macrophytes community productivity along a water depth gradient in a freshwater lake

Functional trait composition of plant communities has been proposed as a helpful key for understanding the mechanisms of biodiversity effects on ecosystem functioning. In this study, we applied a step‐wise modeling procedure to test the relative effects of taxonomic diversity, functional identity, and functional diversity on macrophytes community productivity along water depth gradient. We sampled 42 plots and 1513 individual plants and measured 16 functional traits and abundance of 17 macrophyte species. Results showed that there was a significant decrease in taxonomic diversity, functional identity (i.e., stem dry mass content, leaf [C] and leaf [N]), and functional diversity (i.e., floating leaf, mean Julian flowering date and rooting depth) with increasing water depth. For the multiple‐trait functional diversity (FD) indices, functional richness decreased, while functional divergence increased with water depth gradient. Macrophyte community productivity was strongly determined by functional trait composition within community, but not significantly affected by taxonomic diversity. Community‐weighted means (CWM) showed a two times higher explanatory power relative to FD indices in determining variations in community productivity. For nine of sixteen traits, CWM and FD showed significant correlations with community productivity, although the strength and direction of those relations depended on selected trait. Furthermore, functional composition in a community affected productivity through either additive or opposite effects of CWM and FD, depending on the particular traits being considered. Our results suggested both mechanisms of mass ratio and niche complementarity can operate simultaneously on variations in community productivity, and considering both CWM and FD would lead to a more profound understanding of traits–productivity relationships.     

Leaf decomposition depends on nutritional trait values but increasing trait variability does not always increase decomposition efficiency

The mass ratio (MRH) and niche complementarity (NCH) hypotheses can explain how leaf trait composition drives decomposition, an ecosystem process linked to nutrient cycling and carbon sequestration. However, few studies have used an experiment designed to disentangle the role of the mechanisms proposed by these hypotheses. This is especially true regarding the role of leaf functional traits for decomposition rates in tropical ecosystems. Here, we quantified the biomass loss of 120 leaf mixtures assembled according to four quasi-orthogonal combinations of different mean trait values (community-weighted mean; CWM) and trait variability (functional diversity; FD) of three leaf functional traits (leaf nitrogen and leaf magnesium concentrations and specific leaf area). We found that CWM values of leaf nutritional traits were positively related to greater biomass loss. This supports the hypothesis that the mean trait values of leaf mixtures can drive biomass loss (MRH). However, contrary to NCH expectations, in some circumstances, increasing trait variability of leaf nutritional traits decreased biomass loss. Our results reinforce some previous evidence that, together, CWM and FD can explain leaf decomposition and highlight that the mean resource quality of leaf mixtures is a driver of biomass loss. Also, as previously reported for temperate ecosystems, trait variability does not always increase leaf decomposition in tropical ecosystems. Therefore, there is a need to consider simultaneously both MRH and NCH in future studies, using an appropriate design, keeping in mind that both mechanisms will always be present in any species mixture or combination.     

Toward molecular trait‐based ecology through integration of biogeochemical,geographical and metagenomic data

Using metagenomic ‘parts lists’ to infer global patterns on microbial ecology remains a significant challenge. To deduce important ecological indicators such as environmental adaptation, molecular trait dispersal, diversity variation and primary production from the gene pool of an ecosystem, we integrated 25 ocean metagenomes with geographical, meteorological and geophysicochemical data. We find that climatic factors (temperature, sunlight) are the major determinants of the biomolecular repertoire of each sample and the main limiting factor on functional trait dispersal (absence of biogeographic provincialism). Molecular functional richness and diversity show a distinct latitudinal gradient peaking at 20°N and correlate with primary production. The latter can also be predicted from the molecular functional composition of an environmental sample. Together, our results show that the functional community composition derived from metagenomes is an important quantitative readout for molecular trait‐based biogeography and ecology.     

Trait‐based ecology of terrestrial arthropods

In focusing on how organisms' generalizable functional properties (traits) interact mechanistically with environments across spatial scales and levels of biological organization, trait‐based approaches provide a powerful framework for attaining synthesis, generality and prediction. Trait‐based research has considerably improved understanding of the assembly, structure and functioning of plant communities. Further advances in ecology may be achieved by exploring the trait–environment relationships of non‐sessile, heterotrophic organisms such as terrestrial arthropods, which are geographically ubiquitous, ecologically diverse, and often important functional components of ecosystems. Trait‐based studies and trait databases have recently been compiled for groups such as ants, bees, beetles, butterflies, spiders and many others; however, the explicit justification, conceptual framework, and primary‐evidence base for the burgeoning field of ‘terrestrial arthropod trait‐based ecology’ have not been well established. Consequently, there is some confusion over the scope and relevance of this field, as well as a tendency for studies to overlook important assumptions of the trait‐based approach. Here we aim to provide a broad and accessible overview of the trait‐based ecology of terrestrial arthropods. We first define and illustrate foundational concepts in trait‐based ecology with respect to terrestrial arthropods, and justify the application of trait‐based approaches to the study of their ecology. Next, we review studies in community ecology where trait‐based approaches have been used to elucidate how assembly processes for terrestrial arthropod communities are influenced by niche filtering along environmental gradients (e.g. climatic, structural, and land‐use gradients) and by abiotic and biotic disturbances (e.g. fire, floods, and biological invasions). We also review studies in ecosystem ecology where trait‐based approaches have been used to investigate biodiversity–ecosystem function relationships: how the functional diversity of arthropod communities relates to a host of ecosystem functions and services that they mediate, such as decomposition, pollination and predation. We then suggest how future work can address fundamental assumptions and limitations by investigating trait functionality and the effects of intraspecific variation, assessing the potential for sampling methods to bias the traits and trait values observed, and enhancing the quality and consolidation of trait information in databases. A roadmap to guide observational trait‐based studies is also presented. Lastly, we highlight new areas where trait‐based studies on terrestrial arthropods are well positioned to advance ecological understanding and application. These include examining the roles of competitive, non‐competitive and (multi‐)trophic interactions in shaping coexistence, and macro‐scaling trait–environment relationships to explain and predict patterns in biodiversity and ecosystem functions across space and time. We hope this review will spur and guide future applications of the trait‐based framework to advance ecological insights from the most diverse eukaryotic organisms on Earth.     

The traits of “trait ecologists”: An analysis of the use of trait and functional trait terminology

Trait and functional trait approaches have revolutionized ecology improving our understanding of community assembly, species coexistence, and biodiversity loss. Focusing on traits promotes comparability across spatial and organizational scales, but terms must be used consistently. While several papers have offered definitions, it remains unclear how ecologists operationalize “trait” and “functional trait” terms. Here, we evaluate how researchers and the published literatures use these terms and explore differences among subdisciplines and study systems (taxa and biome). By conducting both a survey and a literature review, we test the hypothesis that ecologists’ working definition of “trait” is adapted or altered when confronting the realities of collecting, analyzing and presenting data. From 486 survey responses and 712 reviewed papers, we identified inconsistencies in the understanding and use of terminology among researchers, but also limited inclusion of definitions within the published literature. Discrepancies were not explained by subdiscipline, system of study, or respondent characteristics, suggesting there could be an inconsistent understanding even among those working in related topics. Consistencies among survey responses included the use of morphological, phonological, and physiological traits. Previous studies have called for unification of terminology; yet, our study shows that proposed definitions are not consistently used or accepted. Sources of disagreement include trait heritability, defining and interpreting function, and dealing with organisms in which individuals are not clearly recognizable. We discuss and offer guidelines for overcoming these disagreements. The diversity of life on Earth means traits can represent different features that can be measured and reported in different ways, and thus, narrow definitions that work for one system will fail in others. We recommend ecologists embrace the breadth of biodiversity using a simplified definition of “trait” more consistent with its common use. Trait‐based approaches will be most powerful if we accept that traits are at least as diverse as trait ecologists.     

funrar: An R package to characterize functional rarity

Emphasis has been put in recent ecological research on investigating phylogenetic, functional and taxonomic facets of biological diversity. While a flourishing number of indices have been proposed for assessing functional diversity, surprisingly few options are available to characterize functional rarity. Functional rarity can play a key role in community and ecosystem dynamics. We introduce here the funrar R package to quantify functional rarity based on species trait differences and species frequencies at local and regional scales. Because of the increasing availability of big datasets in macroecology and biogeography, we optimized funrar to work with large datasets of thousands of species and sites. We illustrate the use of the package to investigate the functional rarity of North and Central American mammals.     

Imputing missing data in plant traits: A guide to improve gap-filling

Aim

Globally distributed plant trait data are increasingly used to understand relationships between biodiversity and ecosystem processes. However, global trait databases are sparse because they are compiled from many, mostly small databases. This sparsity in both trait space completeness and geographical distribution limits the potential for both multivariate and global analyses. Thus, ‘gap-filling’ approaches are often used to impute missing trait data. Recent methods, like Bayesian hierarchical probabilistic matrix factorization (BHPMF), can impute large and sparse data sets using side information. We investigate whether BHPMF imputation leads to biases in trait space and identify aspects influencing bias to provide guidance for its usage.

Innovation

We use a fully observed trait data set from which entries are randomly removed, along with extensive but sparse additional data. We use BHPMF for imputation and evaluate bias by: (1) accuracy (residuals, RMSE, trait means), (2) correlations (bi- and multivariate) and (3) taxonomic and functional clustering (valuewise, uni- and multivariate). BHPMF preserves general patterns of trait distributions but induces taxonomic clustering. Data set–external trait data had little effect on induced taxonomic clustering and stabilized trait–trait correlations.

Main Conclusions

Our study extends the criteria for the evaluation of gap-filling beyond RMSE, providing insight into statistical data structure and allowing better informed use of imputed trait data, with improved practice for imputation. We expect our findings to be valuable beyond applications in plant ecology, for any study using hierarchical side information for imputation.     

Functional diversity (FD), species richness and community composition

Functional diversity is an important component of biodiversity, yet in comparison to taxonomic diversity, methods of quantifying functional diversity are less well developed. Here, we propose a means for quantifying functional diversity that may be particularly useful for determining how functional diversity is related to ecosystem functioning. This measure of functional diversity “FD” is defined as the total branch length of a functional dendrogram. Various characteristics of FD make it preferable to other measures of functional diversity, such as the number of functional groups in a community. Simulating species' trait values illustrates how the relative importance of richness and composition for FD depends on the effective dimensionality of the trait space in which species separate. Fewer dimensions increase the importance of community composition and functional redundancy. More dimensions increase the importance of species richness and decreases functional redundancy. Clumping of species in trait space increases the relative importance of community composition. Five natural communities show remarkably similar relationships between FD and species richness.     

On the importance of intraspecific variability for the quantification of functional diversity

Functional diversity (FD) is a key facet of biodiversity used to address central questions in ecology. Despite recent methodological advances, FD remains a complex concept and no consensus has been reached either on how to quantify it, or on how it influences ecological processes. Here we define FD as the distribution of trait values within a community. When and how to account for intraspecific trait variability (ITV) when measuring FD remains one of the main current debates. It remains however unclear to what extent accounting for population‐level ITV would modify FD quantification and associated conclusions. In this paper, we address two critical questions: (1) How sensitive are different components of FD to the inclusion of population‐level ITV? (2) Does the omission of ITV obscure the understanding of ecological patterns? Using a mixture of empirical data and simulation experiments, we conducted a sensitivity analysis of four commonly used FD indices (community weighted mean traits, functional richness, Rao's quadratic entropy, Petchey and Gaston's FD index) and their relationships with environmental gradients and species richness, by varying both the extent (plasticity or not) and the structure (contingency to environmental gradient due to local adaptation) of population‐level ITV. Our results suggest that ITV may strongly alter the quantification of FD and the detection of ecological patterns. Our analysis highlights that 1) species trait values distributions within communities are crucial to the sensitivity to ITV, 2) ITV structure plays a major role in this sensitivity and 3) different indices are not evenly sensitive to ITV, the single‐trait FD from Petchey and Gaston being the most sensitive among the four metrics tested. We conclude that the effects of intraspecific variability in trait values should be more systematically tested before drawing central conclusions on FD, and suggest the use of simulation studies for such sensitivity analyses.     

Identifying the Relative Importance of Leaf versus Shredder Species Loss on Litter Decomposition in Streams

Understanding how species loss influences ecosystem function is a contemporary issue in ecology. However, most research has focused on species loss at one trophic‐level. We explored the relationship between functional diversity (FD) and species richness separately for trees and aquatic leaf‐shredding detritivores. For trees, we collected information on species‐specific leaf tissue chemistry and species co‐occurrences in the mid‐Atlantic region (USA). For shredders, we used a published trait database with information on communities from 38 streams in the same region. We used a clustering algorithm to estimate FD for each community and for randomly assembled communities. If FD was high, we concluded that species loss was important to change in function; if low, species were functionally redundant and insensitive to species loss. We found tree FD to be significantly different than expected, but shredders exhibited FD levels similar to patterns based on random assembly. Furthermore, there were more leaf species exclusively associated with very high or very low levels of functional diversity compared to shredders. This approach revealed greater implications for leaf than shredder species loss for litter breakdown. (© 2009 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Loss of functional diversity under land use intensification across multiple taxa

Land use intensification can greatly reduce species richness and ecosystem functioning. However, species richness determines ecosystem functioning through the diversity and values of traits of species present. Here, we analyze changes in species richness and functional diversity (FD) at varying agricultural land use intensity levels. We test hypotheses of FD responses to land use intensification in plant, bird, and mammal communities using trait data compiled for 1600+ species. To isolate changes in FD from changes in species richness we compare the FD of communities to the null expectations of FD values. In over one-quarter of the bird and mammal communities impacted by agriculture, declines in FD were steeper than predicted by species number. In plant communities, changes in FD were indistinguishable from changes in species richness. Land use intensification can reduce the functional diversity of animal communities beyond changes in species richness alone, potentially imperiling provisioning of ecosystem services.     

Effects of soil resource availability on patterns of plant functional traits across spatial scales

Identifying patterns and drivers of plant community assembly has long been a central issue in ecology. Many studies have explored the above questions using a trait‐based approach; however, there are still unknowns around how patterns of plant functional traits vary with environmental gradients. In this study, the responses of individual and multivariate trait dispersions of 134 species to soil resource availability were examined based on correlational analysis and torus‐translation tests across four spatial scales in a subtropical forest, China. Results indicated that different degrees of soil resource availability had different effects on trait dispersions. Specifically, limited resource (available phosphorus) showed negative relationships with trait dispersions, non‐limited resource (available potassium) showed positive relationships with trait dispersions, and saturated resource (available nitrogen) had no effect on trait dispersions. Moreover, compared with the stem (wood density) and architectural trait (maximum height), we found that leaf functional traits can well reflect the response of plants to nutrient gradients. Lastly, the spatial scale only affected the magnitude but not the direction of the correlations between trait dispersions and environmental gradients. Overall, the results highlight the importance of soil resource availability and spatial scale in understanding how plant functional traits respond to environmental gradients.     

Coevolution by different functional mechanisms modulates the structure and dynamics of antagonistic and mutualistic networks

A central problem in the study of species interactions is to understand the underlying ecological and evolutionary mechanisms that shape and are shaped by trait evolution in interacting assemblages. The patterns of interaction among species (i.e. network structure) provide the pathways for evolution and coevolution, which are modulated by how traits affect individual fitness (i.e. functional mechanisms). Functional mechanisms, in turn, also affect the likelihood of an ecological interaction, shaping the structure of interaction networks. Here, we build adaptive network models to explore the potential role of coevolution by two functional mechanisms, trait matching and exploitation barrier, in driving trait evolution and the structure of interaction networks. We use these models to explore how different scenarios of coevolution and functional mechanisms reproduce the empirical network patterns observed in antagonistic and mutualistic interactions and affect trait evolution. Scenarios assuming coevolutionary feedback with a strong effect of functional mechanism better reproduce the empirical structure of networks. Antagonistic and mutualistic networks, however, are better explained by different functional mechanisms and the structure of antagonisms is better reproduced than that of mutualisms. Scenarios assuming coevolution by strong trait matching between interacting partners better explain the structure of antagonistic networks, whereas those assuming strong barrier effects better reproduce the structure of mutualistic networks. The dynamics resulting from the feedback between strong functional mechanisms and coevolution favor the stability of antagonisms and mutualisms. Selection favoring trait matching reduces temporal trait fluctuation and the magnitude of arms races in antagonisms, whereas selection due to exploitation barriers reduces temporal trait fluctuations in mutualisms. Our results indicate that coevolutionary models better reproduce the network structure of antagonisms than those of mutualisms and that different functional mechanisms may favor the persistence of antagonistic and mutualistic interacting assemblages.     

Heterogeneous flows foster heterogeneous assemblages: relationships between functional diversity and hydrological heterogeneity in riparian plant communities

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