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

Towards holistic insect monitoring: species discovery, description, identification and traits for all insects

Holistic insect monitoring needs scalable techniques to overcome taxon biases, determine species abundances, and gather functional traits for all species. This requires that we address taxonomic impediments and the paucity of data on abundance, biomass and functional traits. We here outline how these data deficiencies could be addressed at scale. The workflow starts with large-scale barcoding (megabarcoding) of all specimens from mass samples obtained at biomonitoring sites. The barcodes are then used to group the specimens into molecular operational taxonomic units that are subsequently tested/validated as species with a second data source (e.g. morphology). New species are described using barcodes, images and short diagnoses, and abundance data are collected for both new and described species. The specimen images used for species discovery then become the raw material for training artificial intelligence identification algorithms and collecting trait data such as body size, biomass and feeding modes. Additional trait data can be obtained from vouchers by using genomic tools developed by molecular ecologists. Applying this pipeline to a few samples per site will lead to greatly improved insect monitoring regardless of whether the species composition of a sample is determined with images, metabarcoding or megabarcoding. This article is part of the theme issue 'Towards a toolkit for global insect biodiversity monitoring'.

Being facially expressive is socially advantageous

Individuals vary in how they move their faces in everyday social interactions. In a first large-scale study, we measured variation in dynamic facial behaviour during social interaction and examined dyadic outcomes and impression formation. In Study 1, we recorded semi-structured video calls with 52 participants interacting with a confederate across various everyday contexts. Video clips were rated by 176 independent participants. In Study 2, we examined video calls of 1315 participants engaging in unstructured video-call interactions. Facial expressivity indices were extracted using automated Facial Action Coding Scheme analysis and measures of personality and partner impressions were obtained by self-report. Facial expressivity varied considerably across participants, but little across contexts, social partners or time. In Study 1, more facially expressive participants were more well-liked, agreeable, and successful at negotiating (if also more agreeable). Participants who were more facially competent, readable, and perceived as readable were also more well-liked. In Study 2, we replicated the findings that facial expressivity was associated with agreeableness and liking by their social partner, and additionally found it to be associated with extraversion and neuroticism. Findings suggest that facial behaviour is a stable individual difference that proffers social advantages, pointing towards an affiliative, adaptive function.

Island biodiversity in peril: Anticipating a loss of mammals' functional diversity with future species extinctions

Islands are biodiversity hotspots that host unique assemblages. However, a substantial proportion of island species are threatened and their long-term survival is uncertain. Identifying and preserving vulnerable species has become a priority, but it is also essential to combine this information with other facets of biodiversity like functional diversity, to understand how future extinctions might affect ecosystem stability and functioning. Focusing on mammals, we (i) assessed how much functional space would be lost if threatened species go extinct, (ii) determined the minimum number of extinctions that would cause a significant functional loss, (iii) identified the characteristics (e.g., biotic, climatic, geographic, or orographic) of the islands most vulnerable to future changes in the functional space, and (iv) quantified how much of that potential functional loss would be offset by introduced species. Using trait information for 1474 mammal species occurring in 318 islands worldwide, we built trait probability density functions to quantify changes in functional richness and functional redundancy in each island if the mammals categorized by IUCN as threatened disappeared. We found that the extinction of threatened mammals would reduce the functional space in 63% of the assessed islands, although these extinctions in general would cause a reduction of less than 15% of their overall functional space. Also, on most islands, the extinction of just a few species would be sufficient to cause a significant loss of functional diversity. The potential functional loss would be higher on small, isolated, and/or species-rich islands, and, in general, the functional space lost would not be offset by introduced species. Our results show that the preservation of native species and their ecological roles remains crucial for maintaining the current functioning of island ecosystems. Therefore, conservation measures considering functional diversity are imperative to safeguard the unique functional roles of threatened mammal species on islands.

Trait-environment interactions of saproxylic beetles as a guide to biodiversity conservation strategies

Conservation of biodiversity requires in-depth knowledge of trait-environment interactions to understand the influence the environment has on species assemblages. Saproxylic beetles exhibit a wide range of traits and functions in the forest ecosystems. Understanding their responses to surrounding environment thus improves our capacity to identify habitats that should be restored or protected. We investigated potential interactions between ecological traits in saproxylic beetles (feeding guilds and habitat preferences) and environmental variables (deadwood, type and age of surrounding forest). We sampled beetles from 78 plots containing newly created high stumps of Scots pine and Silver birch in boreal forest landscapes in Sweden for three consecutive years. Using a model based approach, our aim was to explore potential interactions between ecological traits and the surrounding environment at close and distant scale (20 m and 500 m radius). We found that broadleaf-preferring beetle species are positively associated with the local broadleaf-originated deadwood and broadleaf-rich forests in the surrounding landscapes. Conifer-preferring species are positively associated with the local amount of coniferous deadwood and young and old forests in the surrounding landscape. Fungivorous and predatory beetles are positively associated with old forests in the surrounding landscapes. Our results indicate that both local amounts of deadwood and types of forests in the landscape are important in shaping saproxylic beetle communities. We particularly highlight the need to increase deadwood amounts of various qualities in the landscape, exempt older forests from production and to increase broadleaf-rich habitats in order to meet different beetle species' habitat requirements. Trait responses among saproxylic beetles provide insights into the significance of broadleaf forest and dead wood as essential attributes in boreal forest restoration, which helps conservation planning and management in forest landscapes.

Asynchrony in terrestrial insect abundance corresponds with species traits

Asynchrony in population abundance can buffer the effects of environmental change leading to greater community and ecosystem stability. Both environmental (abiotic) drivers and species functional (biotic) traits can influence population dynamics leading to asynchrony. However, empirical evidence linking dissimilarity in species traits to abundance asynchrony is limited, especially for understudied taxa such as insects. To fill this knowledge gap, we explored the relationship between pairwise species trait dissimilarity and asynchrony in interannual abundance change between pairs of species for 422 moth, butterfly, and bumblebee species in Great Britain. We also explored patterns differentiating traits that we assumed to capture 'sensitivity to environmental variables' (such as body mass), and traits that may reflect 'diversity in exposure' to environmental conditions and lead to niche partitioning (for example, habitat uses, and intra-annual emergence periods). As expected, species trait dissimilarity calculated overall and for many individual traits representing response and exposure was positively correlated with asynchrony in all three insect groups. We found that 'exposure' traits, especially those relating to the phenology of species, had the strongest relationship with abundance asynchrony from all tested traits. Positive relationships were not simply due to shared evolutionary history leading to similar life-history strategies: detected effects remained significant for most traits after accounting for phylogenetic relationships within models. Our results provide empirical support that dissimilarity in traits linked to species exposure and sensitivity to the environment could be important for temporal dissimilarity in insect abundance. Hence, we suggest that general trait diversity, but especially diversity in 'exposure' traits, could play a significant role in the resilience of insect communities to short-term environmental perturbations through driving asynchrony between species abundances.

Assessing the predictive value of morphological traits on primary lifestyle of birds through the extreme gradient boosting algorithm

The relationship between morphological traits and ecological performance in birds is an important area of research, as it can help us to understand how birds are able to adapt and how they are affected by changes in their environment. Many studies have investigated the relationship between morphological traits and certain aspects of the performance and ecological niche of these animals. However, the relationship between morphological traits and the primary lifestyle of birds has not previously been explored. This paper aims to evaluate the predictive potential of morphological data to determine the primary lifestyle of birds through a tree-based machine learning algorithm. By doing this, it is also possible to evaluate these artificial categories that we used to split up birds and know whether they are suitable for dividing them in function of shared morphological characteristics or need a redefinition under more discriminant criteria. Supplementary dataset 1 of the AVONET project was used, which comprises the 11 morphological predictors used in this work and the classification according to the primary lifestyle for more than 95% of the existing bird species. For all morphological traits used, statistically significant univariate differences were found between primary lifestyles. The three fitted machine learning models showed high accuracy, in all cases above 78% and superior to the ones achieved through traditional approaches used as contrasts. The results obtained provide evidence that primary lifestyle can be predicted in birds based on morphological traits, as well as more insights about the relevance of functional traits for ecological modeling. This is another step forward in our mechanistic understanding of bird ecology, while exploring how birds have adapted to their environments and how they interact with their surroundings.

When Do Traits Tell More Than Species about a Metacommunity? A Synthesis across Ecosystems and Scales

AbstractLinking species traits with the variation in species assemblages across habitats has often proved useful for developing a more mechanistic understanding of species distributions in metacommunities. However, summarizing the rich tapestry of a species in all of its nuance with a few key ecological traits can also lead to an abstraction that provides less predictability than when using taxonomy alone. As a further complication, taxonomic and functional diversities can be inequitably compared, either by integrating taxonomic-level information into the calculation of how functional aspects of communities vary or by detecting spurious trait-environment relationships. To remedy this, we here synthesize analyses of 80 datasets on different taxa, ecosystems, and spatial scales that include information on abundance or presence/absence of species across sites with variable environmental conditions and the species' traits. By developing analyses that treat functional and taxonomic diversity equitably, we ask when functional diversity helps to explain metacommunity structure. We found that patterns of functional diversity explained metacommunity structure and response to environmental variation in only 25% of the datasets using a multitrait approach but up to 59% using a single-trait approach. Nevertheless, an average of only 19% (interquartile range = 0%-29%) of the traits showed a significant signal across environmental gradients. Species-level traits, as typically collected and analyzed through functional diversity patterns, often do not bring predictive advantages over what the taxonomic information already holds. While our assessment of a limited advantage of using traits to explain variation in species assemblages was largely true across ecosystems, traits played a more useful role in explaining variation when many traits were used and when trait constructs were more related to species' status, life history, and mobility. We propose future research directions to make trait-based approaches and data more helpful for inference in metacommunity ecology.

Leaf traits linked to structure and palatability drive plant-insect interactions within three forested ecosystems

PREMISE

Plant traits and insect herbivory have been highly studied within the modern record but only to a limited extent within the paleontological. Preservation influences what can be measured within the fossil record, but modern methods are also not compatible with paleobotanical methods. To remedy this knowledge gap, a comparable framework was created here using modern and paleobotanical methods, allowing for future comparisons within the fossil record.

METHODS

Insect feeding damage on selected tree species at Harvard Forest, the Smithsonian Environmental Research Center, and La Selva were characterized using the damage type system prevalent within paleobotanical studies and compared with leaf traits. Linear models and random forest analyses tested the influence of leaf traits on total, specialized, gall, and mine frequency and diversity.

RESULTS

Structural traits like leaf dry mass per area and palatability traits, including lignin and phosphorus concentrations, are important variables affecting gall and mine damage. The significance and strength of trait-herbivory relationships varied across forest types, which is likely driven by differences in local insect populations.

CONCLUSIONS

This work addresses the persistent gap between modern and paleoecological studies focusing on the influence of leaf traits on insect herbivory. This is important as modern climate change alters our understanding of plant-insect interactions, providing a need for contextualizing these relationships within evolutionary time. The fossil record provides information on terrestrial response to past climatic events and, thus, should be implemented when considering how to preserve biodiversity under current and future global change.

Pollination syndromes and the origins of floral traits

BACKGROUND

A general view in the study of pollination syndromes is that floral traits usually represent convergent floral adaptations to specific functional pollinator groups. However, the definition of convergence is elusive and contradictory in the literature. Is convergence the independent evolution of either the same trait or similar traits with the same function? A review of the concept of convergence in developmental biology and phylogenetic systematics may shed new light in studies of pollination syndromes.

SCOPE

The aims of this article are (1) to explore the notion of convergence and other concepts (analogy, homoplasy and parallelism) within the theory and practice of developmental evolution and phylogenetic systematics; (2) to modify the definitions of syndromes in order to embrace the concepts of analogy and convergence; (3) to revisit the bat pollination syndrome in the context of angiosperm phylogeny, with focus on the showy 'petaloid' organs associated with the syndrome; (4) to revisit the genetic-developmental basis of flower colour; (5) to raise evolutionary hypotheses of floral evolution associated with the bat pollination syndrome; and (6) to highlight some of the current frontiers of research on the origin and evolution of flowers and its impact on pollination syndrome studies in the 21st century.

CONCLUSIONS

The inclusion of the concepts of analogy and convergence within the concept of syndromes will constitute a new agenda of inquiry that integrates floral biology, phylogenetic systematics and developmental biology. Phyllostomid and pteropodid bat pollination syndrome traits in eudicots and monocots represent cases of analogous and convergent evolution. Pollination syndromes are a multivariate concept intrinsically related to the understanding of flower organogenesis and evolution. The formulation of hypotheses of pollination syndromes must consider the phylogenetic levels of universality for both plant and animal taxa, flower development, genetics, homology and evolution, and a clear definition of evolutionary concepts, including analogy, convergence, homoplasy and parallelism.

Low baseline intraspecific variation in leaf pressure-volume traits: Biophysical basis and implications for spectroscopic sensing

Intra-specific trait variation (ITV) plays a role in processes at a wide range of scales from organs to ecosystems across climate gradients. Yet, ITV remains rarely quantified for many ecophysiological traits typically assessed for species means, such as pressure volume (PV) curve parameters including osmotic potential at full turgor and modulus of elasticity, which are important in plant water relations. We defined a baseline "reference ITV" (ITVref ) as the variation among fully exposed, mature sun leaves of replicate individuals of a given species grown in similar, well-watered conditions, representing the conservative sampling design commonly used for species-level ecophysiological traits. We hypothesized that PV parameters would show low ITVref relative to other leaf morphological traits, and that their intraspecific relationships would be similar to those previously established across species and proposed to arise from biophysical constraints. In a database of novel and published PV curves and additional leaf structural traits for 50 diverse species, we found low ITVref for PV parameters relative to other morphological traits, and strong intraspecific relationships among PV traits. Simulation modeling showed that conservative ITVref enables the use of species-mean PV parameters for scaling up from spectroscopic measurements of leaf water content to enable sensing of leaf water potential.

Mechanistic forecasts of species responses to climate change: The promise of biophysical ecology

A core challenge in global change biology is to predict how species will respond to future environmental change and to manage these responses. To make such predictions and management actions robust to novel futures, we need to accurately characterize how organisms experience their environments and the biological mechanisms by which they respond. All organisms are thermodynamically connected to their environments through the exchange of heat and water at fine spatial and temporal scales and this exchange can be captured with biophysical models. Although mechanistic models based on biophysical ecology have a long history of development and application, their use in global change biology remains limited despite their enormous promise and increasingly accessible software. We contend that greater understanding and training in the theory and methods of biophysical ecology is vital to expand their application. Our review shows how biophysical models can be implemented to understand and predict climate change impacts on species' behavior, phenology, survival, distribution, and abundance. It also illustrates the types of outputs that can be generated, and the data inputs required for different implementations. Examples range from simple calculations of body temperature at a particular site and time, to more complex analyses of species' distribution limits based on projected energy and water balances, accounting for behavior and phenology. We outline challenges that currently limit the widespread application of biophysical models relating to data availability, training, and the lack of common software ecosystems. We also discuss progress and future developments that could allow these models to be applied to many species across large spatial extents and timeframes. Finally, we highlight how biophysical models are uniquely suited to solve global change biology problems that involve predicting and interpreting responses to environmental variability and extremes, multiple or shifting constraints, and novel abiotic or biotic environments.

Planktonic functional diversity changes in synchrony with lake ecosystem state

Managing ecosystems to effectively preserve function and services requires reliable tools that can infer changes in the stability and dynamics of a system. Conceptually, functional diversity (FD) appears as a sensitive and viable monitoring metric stemming from suggestions that FD is a universally important measure of biodiversity and has a mechanistic influence on ecological processes. It is however unclear whether changes in FD consistently occur prior to state responses or vice versa, with no current work on the temporal relationship between FD and state to support a transition towards trait-based indicators. There is consequently a knowledge gap regarding when functioning changes relative to biodiversity change and where FD change falls in that sequence. We therefore examine the lagged relationship between planktonic FD and abundance-based metrics of system state (e.g. biomass) across five highly monitored lake communities using both correlation and cutting edge non-linear empirical dynamic modelling approaches. Overall, phytoplankton and zooplankton FD display synchrony with lake state but each lake is idiosyncratic in the strength of relationship. It is therefore unlikely that changes in plankton FD are identifiable before changes in more easily collected abundance metrics. These results highlight the power of empirical dynamic modelling in disentangling time lagged relationships in complex multivariate ecosystems, but suggest that FD cannot be generically viable as an early indicator. Individual lakes therefore require consideration of their specific context and any interpretation of FD across systems requires caution. However, FD still retains value as an alternative state measure or a trait representation of biodiversity when considered at the system level.

Observed and dark diversity dynamics over millennial time scales: fast life-history traits linked to expansion lags of plants in northern Europe

Global change drivers (e.g. climate and land use) affect the species and functional traits observed in a local site but also its dark diversity-the set of species and traits locally suitable but absent. Dark diversity links regional and local scales and, over time, reveals taxa under expansion lags by depicting the potential biodiversity that remains suitable but is absent locally. Since global change effects on biodiversity are both spatially and temporally scale dependent, examining long-term temporal dynamics in observed and dark diversity would be relevant to assessing and foreseeing biodiversity change. Here, we used sedimentary pollen data to examine how both taxonomic and functional observed and dark diversity changed over the past 14 500 years in northern Europe. We found that taxonomic and functional observed and dark diversity increased over time, especially after the Late Glacial and during the Late Holocene. However, dark diversity dynamics revealed expansion lags related to species' functional characteristics (dispersal limitation and stress intolerance) and an extensive functional redundancy when compared to taxa in observed diversity. We highlight that assessing observed and dark diversity dynamics is a promising tool to examine biodiversity change across spatial scales, its possible causes, and functional consequences.

To harness traits for ecology, let’s abandon ‘functionality’

Traits are measurable features of organisms. Functional traits aspire to more. They quantify an organism's ecology and, ultimately, predict ecosystem functions based on local communities. Such predictions are useful, but only if 'functional' really means 'ecologically relevant'. Unfortunately, many 'functional' traits seem to be characterized primarily by availability and implied importance - not by their ecological information content. Better traits are needed, but a prevailing trend is to 'functionalize' existing traits. The key may be to invert the process, that is, to identify functions of interest first and then identify traits as quantifiable proxies. We propose two distinct, yet complementary, perspectives on traits and provide a 'taxonomy of traits', a conceptual compass to navigate the diverse applications of traits in ecology.

DNA metabarcoding suggests adaptive seasonal variation of individual trophic traits in a critically endangered fish

Dietary studies are critical for understanding foraging strategies and have important applications in conservation and habitat management. We applied a robust metabarcoding protocol to characterize the diet of the critically endangered freshwater fish Zingel asper (the Rhone streber). We conducted modelling and simulation analyses to identify and characterize some of the drivers of individual trophic trait variation in this species. We found that population density and ontogeny had minor effects on the trophic niche of Z. asper. Instead, our results suggest that the majority of trophic niche variation was driven by seasonal variation in ecological opportunity. The total trophic niche width of Z. asper seasonally expanded to include a broader range of prey. Furthermore, null model simulations revealed that the increase of between-individual variation in autumn indicates that Z. asper become more opportunistic relative to summer and spring, rather than being associated with a seasonal specialization of individuals. Overall, our results suggest an adaptive variation of individual trophic traits in Z. asper: the species mainly consumes a few ephemeropteran taxa (Baetis fuscatus and Ecdyonurus) but seems to be capable of adapting its foraging strategy to maintain its body condition. This study illustrates how metabarcoding data obtained from faeces can be validated and combined with individual-based modelling and simulation approaches to explore inter- and intrapopulational individual trophic traits variation and to test hypotheses in the conventional analytic framework of trophic ecology.

What are mycorrhizal traits?

Traits are inherent properties of organisms, but how are they defined for organismal networks such as mycorrhizal symbioses? Mycorrhizal symbioses are complex and diverse belowground symbioses between plants and fungi that have proved challenging to fit into a unified and coherent trait framework. We propose an inclusive mycorrhizal trait framework that classifies traits as morphological, physiological, and phenological features that have functional implications for the symbiosis. We further classify mycorrhizal traits by location - plant, fungus, or the symbiosis - which highlights new questions in trait-based mycorrhizal ecology designed to charge and challenge the scientific community. This new framework is an opportunity for researchers to interrogate their data to identify novel insights and gaps in our understanding of mycorrhizal symbioses.