Where do functional traits come from? The role of theory and models

Identifying species traits that predict vulnerability to climate change

Accurately predicting the vulnerabilities of species to climate change requires a more detailed understanding of the functional and life-history traits that make some species more susceptible to declines and extinctions in shifting climates. This is because existing trait-based correlates of extinction risk from climate and environmental disturbances vary widely, often being idiosyncratic and context dependent. A powerful solution is to analyse the growing volume of biological data on changes in species ranges and abundances using process-explicit ecological models that run at fine temporal and spatial scales and across large geographical extents. These simulation-based approaches can unpack complex interactions between species' traits and climate and other threats. This enables species-responses to climatic change to be contextualised and integrated into future biodiversity projections and to be used to formulate and assess conservation policy goals. By providing a more complete understanding of the traits and contexts that regulate different responses of species to climate change, these process-driven approaches are likely to result in more certain predictions of the species that are most vulnerable to climate change.

Seasonal changes in hydraulic functions of eight temperate tree species: divergent responses to freeze-thaw cycles in spring and autumn

Freeze-thaw cycles (FTCs) are the major seasonal environment stress in the temperate and boreal forests, inducing hydraulic dysfunction and limiting tree growth and distribution. There are two types of FTCs in the field: FTCs with increasing temperature from winter to spring (spring FTCs); and FTCs with decreasing temperature from autumn to winter (autumn FTCs). While previous studies have evaluated the hydraulic function during the growing season, its seasonal changes and how it adapts to different types of FTCs remain unverified. To fill this knowledge gap, the eight tree species from three wood types (ring- and diffuse-porous, tracheid) were selected in a temperate forest undergoing seasonal FTCs. We measured the branch hydraulic traits in spring, summer, autumn, and early, middle and late winter. Ring-porous trees always showed low native hydraulic conductance (Kbranch), and high percentage loss of maximum Kbranch (PLCB) and water potential that loss of 50% maximum Kbranch (P50B) in non-growing seasons (except summer). Kbranch decreased, and PLCB and P50B increased in diffuse-porous trees after several spring FTCs. In tracheid trees, Kbranch decreased after spring FTCs while the P50B did not change. All sampled trees gradually recovered their hydraulic functions from spring to summer. Kbranch, PLCB and P50B of diffuse-porous and tracheid trees were relatively constant after autumn FTCs, indicating almost no effect of autumn FTCs on hydraulic functions. These results suggested that hydraulic functions of temperate trees showed significant seasonal changes, and spring FTCs induced more hydraulic damage (except ring-porous trees) than autumn FTCs, which should be determined by the number of FTCs and trees' vitality before FTCs. These findings advance our understanding of seasonal changes in hydraulic functions and how they cope with different types of FTC in temperate forests.

Refocusing the microbial rare biosphere concept through a functional lens

The influential concept of the rare biosphere in microbial ecology has underscored the importance of taxa occurring at low abundances yet potentially playing key roles in communities and ecosystems. Here, we refocus the concept of rare biosphere through a functional trait-based lens and provide a framework to characterize microbial functional rarity, a combination of numerical scarcity across space or time and trait distinctiveness. We demonstrate how this novel interpretation of the rare biosphere, rooted in microbial functions, can enhance our mechanistic understanding of microbial community structure. It also sheds light on functionally distinct microbes, directing conservation efforts towards taxa harboring rare yet ecologically crucial functions.

Cathemerality: a key temporal niche

Given the marked variation in abiotic and biotic conditions between day and night, many species specialise their physical activity to being diurnal or nocturnal, and it was long thought that these strategies were commonly fairly fixed and invariant. The term 'cathemeral', was coined in 1987, when Tattersall noted activity in a Madagascan primate during the hours of both daylight and darkness. Initially thought to be rare, cathemerality is now known to be a quite widespread form of time partitioning amongst arthropods, fish, birds, and mammals. Herein we provide a synthesis of present understanding of cathemeral behaviour, arguing that it should routinely be included alongside diurnal and nocturnal strategies in schemes that distinguish and categorise species across taxa according to temporal niche. This synthesis is particularly timely because (i) the study of animal activity patterns is being revolutionised by new and improved technologies; (ii) it is becoming apparent that cathemerality covers a diverse range of obligate to facultative forms, each with their own common sets of functional traits, geographic ranges and evolutionary history; (iii) daytime and nighttime activity likely plays an important but currently neglected role in temporal niche partitioning and ecosystem functioning; and (iv) cathemerality may have an important role in the ability of species to adapt to human-mediated pressures.

Cone allometry and seed protection from fire are similar in serotinous and nonserotinous conifers

Serotiny is an adaptive trait that allows certain woody plants to persist in stand-replacing fire regimes. However, the mechanisms by which serotinous cones avoid seed necrosis and nonserotinous species persist in landscapes with short fire cycles and serotinous competitors remain poorly understood. To investigate whether ovulate cone traits that enhance seed survival differ between serotinous and nonserotinous species, we examined cone traits in 24 species within Pinaceae and Cupressaceae based on physical measurements and cone heating simulations using a computational fluid dynamics model. Fire-relevant cone traits were largely similar between cone types; those that differed (e.g. density and moisture) conferred little seed survival advantage under simulated fire. The most important traits influencing seed survival were cone size and seed depth within the cone, which was found to be an allometric function of cone mass for both cone types. Thus, nonserotinous cones should not suffer significantly greater seed necrosis than serotinous cones of equal size. Closed nonserotinous cones containing mature seeds may achieve substantial regeneration after fire if they are sufficiently large relative to fire duration and temperature. To our knowledge, this is the most comprehensive study of the effects of fire-relevant cone traits on conifer regeneration supported by physics-based fire simulation.

Inconsistent shifts in warming and temperature variability are linked to reduced avian fitness

As the climate has warmed, many birds have advanced their breeding timing. However, as climate change also changes temperature distributions, breeding earlier might increase nestling exposure to either extreme heat or cold. Here, we combine >300,000 breeding records from 24 North American birds with historical temperature data to understand how exposure to extreme temperatures has changed. Average spring temperature increased since 1950 but change in timing of extremes was inconsistent in direction and magnitude; thus, populations could not track both average and extreme temperatures. Relative fitness was reduced following heatwaves and cold snaps in 11 and 16 of 24 species, respectively. Latitudinal variation in sensitivity in three widespread species suggests that vulnerability to extremes at range limits may contribute to range shifts. Our results add to evidence demonstrating that understanding individual sensitivity and its links to population level processes is critical for predicting vulnerability to changing climates.

Parameterizing mechanistic niche models in biophysical ecology: a review of empirical approaches

Mechanistic niche models are computational tools developed using biophysical principles to address grand challenges in ecology and evolution, such as the mechanisms that shape the fundamental niche and the adaptive significance of traits. Here, we review the empirical basis of mechanistic niche models in biophysical ecology, which are used to answer a broad array of questions in ecology, evolution and global change biology. We describe the experiments and observations that are frequently used to parameterize these models and how these empirical data are then incorporated into mechanistic niche models to predict performance, growth, survival and reproduction. We focus on the physiological, behavioral and morphological traits that are frequently measured and then integrated into these models. We also review the empirical approaches used to incorporate evolutionary processes, phenotypic plasticity and biotic interactions. We discuss the importance of validation experiments and observations in verifying underlying assumptions and complex processes. Despite the reliance of mechanistic niche models on biophysical theory, empirical data have and will continue to play an essential role in their development and implementation.

Biophysical models accurately characterize the thermal energetics of a small invasive passerine bird

Effective management of invasive species requires accurate predictions of their invasion potential in different environments. By considering species' physiological tolerances and requirements, biophysical mechanistic models can potentially deliver accurate predictions of where introduced species are likely to establish. Here, we evaluate biophysical model predictions of energy use by comparing them to experimentally obtained energy expenditure (EE) and thermoneutral zones (TNZs) for the common waxbill Estrilda astrild, a small-bodied avian invader. We show that biophysical models accurately predict TNZ and EE and that they perform better than traditional time-energy budget methods. Sensitivity analyses indicate that body temperature, metabolic rate, and feather characteristics were the most influential traits affecting model accuracy. This evaluation of common waxbill energetics represents a crucial step toward improved parameterization of biophysical models, eventually enabling accurate predictions of invasion risk for small (sub)tropical passerines.

Mutualisms in a warming world

Predicting the impacts of global warming on mutualisms poses a significant challenge given the functional and life history differences that usually exist among interacting species. However, this is a critical endeavour since virtually all species on Earth depend on other species for survival and/or reproduction. The field of thermal ecology can provide physiological and mechanistic insights, as well as quantitative tools, for addressing this challenge. Here, we develop a conceptual and quantitative framework that connects thermal physiology to species' traits, species' traits to interacting mutualists' traits and interacting traits to the mutualism. We first identify the functioning of reciprocal mutualism-relevant traits in diverse systems as the key temperature-dependent mechanisms driving the interaction. We then develop metrics that measure the thermal performance of interacting mutualists' traits and that approximate the thermal performance of the mutualism itself. This integrated approach allows us to additionally examine how warming might interact with resource/nutrient availability and affect mutualistic species' associations across space and time. We offer this framework as a synthesis of convergent and critical issues in mutualism science in a changing world, and as a baseline to which other ecological complexities and scales might be added.

Mechanistic models project bird invasions with accuracy

Invasive species pose a major threat to biodiversity and inflict massive economic costs. Effective management of bio-invasions depends on reliable predictions of areas at risk of invasion, as they allow early invader detection and rapid responses. Yet, considerable uncertainty remains as to how to predict best potential invasive distribution ranges. Using a set of mainly (sub)tropical birds introduced to Europe, we show that the true extent of the geographical area at risk of invasion can accurately be determined by using ecophysiological mechanistic models that quantify species' fundamental thermal niches. Potential invasive ranges are primarily constrained by functional traits related to body allometry and body temperature, metabolic rates, and feather insulation. Given their capacity to identify tolerable climates outside of contemporary realized species niches, mechanistic predictions are well suited for informing effective policy and management aimed at preventing the escalating impacts of invasive species.

Climate drives global functional trait variation in lizards

A major challenge in ecology and evolution is to disentangle the mechanisms driving broad-scale variation in biological traits such as body size, colour, thermal physiology traits and behaviour. Climate has long been thought to drive trait evolution and abiotic filtering of trait variation in ectotherms because their thermal performance and fitness are closely related to environmental conditions. However, previous studies investigating climatic variables associated with trait variation have lacked a mechanistic description of the underpinning processes. Here, we use a mechanistic model to predict how climate affects thermal performance of ectotherms and thereby the direction and strength of the effect of selection on different functional traits. We show that climate drives macro-evolutionary patterns in body size, cold tolerance and preferred body temperatures among lizards, and that trait variation is more constrained in regions where selection is predicted to be stronger. These findings provide a mechanistic explanation for observations on how climate drives trait variation in ectotherms through its effect on thermal performance. By connecting physical, physiological and macro-evolutionary principles, the model and results provide an integrative, mechanistic framework for predicting organismal responses to present climates and climate change.

How to improve scaling from traits to ecosystem processes

Scaling approaches in ecology assume that traits are the main attributes by which organisms influence ecosystem functioning. However, several recent empirical papers have found only weak links between traits and ecosystem functioning, questioning the usefulness of trait-based ecology (TBE). We argue that these studies often suffer from one or more widespread misconceptions. Specifically, these studies often (i) conflict with the conceptual foundations of TBE, (ii) lack theory- or hypothesis-driven selection and use of traits, (iii) tend to ignore intraspecific variation, and (iv) use experimental or study designs that are not well suited to make strong tests of TBE assumptions. Addressing these aspects could significantly improve our ability to scale from traits to ecosystem functioning.

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.

Choosing among correlative, mechanistic, and hybrid models of species' niche and distribution

Different models are available to estimate species' niche and distribution. Mechanistic and correlative models have different underlying conceptual bases, thus generating different estimates of a species' niche and geographic extent. Hybrid models, which combining correlative and mechanistic approaches, are considered a promising strategy; however, no synthesis in the literature assessed their applicability for terrestrial vertebrates to allow best-choice model considering their strengths and trade-offs. Here, we provide a systematic review of studies that compared or integrated correlative and mechanistic models to estimate species' niche for terrestrial vertebrates under climate change. Our goal was to understand their conceptual, methodological, and performance differences, and the applicability of each approach. The studies we reviewed directly compared mechanistic and correlative predictions in terms of accuracy or estimated suitable area, however, without any quantitative analysis to support comparisons. Contrastingly, many studies suggest that instead of comparing approaches, mechanistic and correlative methods should be integrated (hybrid models). However, we stress that the best approach is highly context-dependent. Indeed, the quality and effectiveness of the prediction depends on the study's objective, methodological design, and which type of species' niche and geographic distribution estimated are more appropriate to answer the study's issue.

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.

Dynamic Energy Budget models: fertile ground for understanding resource allocation in plants in a changing world

Climate change is having dramatic effects on the diversity and distribution of species. Many of these effects are mediated by how an organism's physiological patterns of resource allocation translate into fitness through effects on growth, survival and reproduction. Empirically, resource allocation is challenging to measure directly and so has often been approached using mathematical models, such as Dynamic Energy Budget (DEB) models. The fact that all plants require a very similar set of exogenous resources, namely light, water and nutrients, integrates well with the DEB framework in which a small number of variables and processes linked through pathways represent an organism's state as it changes through time. Most DEB theory has been developed in reference to animals and microorganisms. However, terrestrial vascular plants differ from these organisms in fundamental ways that make resource allocation, and the trade-offs and feedbacks arising from it, particularly fundamental to their life histories, but also challenging to represent using existing DEB theory. Here, we describe key features of the anatomy, morphology, physiology, biochemistry, and ecology of terrestrial vascular plants that should be considered in the development of a generic DEB model for plants. We then describe possible approaches to doing so using existing DEB theory and point out features that may require significant development for DEB theory to accommodate them. We end by presenting a generic DEB model for plants that accounts for many of these key features and describing gaps that would need to be addressed for DEB theory to predict the responses of plants to climate change. DEB models offer a powerful and generalizable framework for modelling resource allocation in terrestrial vascular plants, and our review contributes a framework for expansion and development of DEB theory to address how plants respond to anthropogenic change.

The Pace of Life: Metabolic Energy, Biological Time, and Life History

New biophysical theory and electronic databases raise the prospect of deriving fundamental rules of life, a conceptual framework for how the structures and functions of molecules, cells and individual organisms give rise to emergent patterns and processes of ecology, evolution and biodiversity. This framework is very general, applying across taxa of animals from 10-10 g protists to 108 g whales, and across environments from deserts and abyssal depths to rain forests and coral reefs. It has several hallmarks: 1) Energy is the ultimate limiting resource for organisms and the currency of biological fitness. 2) Most organisms are nearly equally fit, because in each generation at steady state they transfer an equal quantity of energy (22.4 kJ/g) and biomass (1 g/g) to surviving offspring. This is the equal fitness paradigm (EFP) of Brown et al. (2018). 3) The enormous diversity of life histories is due largely to variation in metabolic rates (e.g., energy uptake and expenditure via assimilation, respiration and production) and biological times (e.g., generation time). As in standard allometric and metabolic theory, most physiological and life history traits scale approximately as quarter-power functions of body mass, m (rates as ∼m-1/4 and times as ∼m1/4), and as exponential functions of temperature. 4) Time is the fourth dimension of life. Generation time is the pace of life. 5) There is, however, considerable variation not accounted for by the above scalings and existing theories. Much of this "unexplained" variation is due to natural selection on life history traits to adapt the biological times of generations to the clock times of geochronological environmental cycles. 7) Most work on biological scaling and metabolic ecology has focused on respiration rate. The emerging synthesis applies conceptual foundations of energetics and the EFP to shift the focus to production rate and generation time.

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.

Trait phenology and fire seasonality co-drive seasonal variation in fire effects on tree crowns

The plume of hot gases rising above a wildfire can heat and kill the buds in tree crowns. This can reduce leaf area and rates of photosynthesis, growth, and reproduction, and may ultimately lead to mortality. These effects vary seasonally, but the mechanisms governing this seasonality are not well understood. A trait-based physical model combining buoyant plume and energy budget theories shows the seasonality of bud necrosis height may originate from temporal variation in climate, fire behaviour, and/or bud functional traits. To assess the relative importance of these drivers, we parameterized the model with time-series data for air temperature, fireline intensity, and bud traits from Pinus contorta, Picea glauca, and Populus tremuloides. Air temperature, fireline intensity, and bud traits all varied significantly through time, causing significant seasonal variation in predicted necrosis height. Bud traits and fireline intensity explained almost all the variation in necrosis height, with air temperature explaining relatively minor amounts of variation. The seasonality of fire effects on tree crowns appears to originate from seasonal variation in functional traits and fire behaviour. Our approach and results provide needed insight into the physical mechanisms linking environmental variation to plant performance via functional traits.

Who can pass the urban filter? A multi-taxon approach to disentangle pollinator trait-environmental relationships

Cities are considered important refuges for insect pollinators. This has been shown repeatedly for wild bees, but may also be true for other diverse taxa such as hoverflies. However, our understanding of how urban environmental filters shape pollinator species communities and their traits is still limited. Here, we used wild bee and hoverfly species, communities and their functional traits to illustrate how environmental filters on the landscape and local scale shape urban species pools. The multi-taxon approach revealed that environmental filtering predominantly occurred at the landscape scale as urbanisation and 3D connectivity significantly structured the taxonomic and functional composition of wild bee (sociality, nesting, diet, body size) and hoverfly (larval food type, migratory status) communities. We identified urban winners and losers attributed to taxon-specific responses to urban filters. Our results suggest that insect pollinator conservation needs to take place primarily at the landscape level while considering species traits, especially by increasing habitat connectivity.

Multidimensional scaling for animal traits in the context of dynamic energy budget theory

The method of multidimensional scaling (MDS) has long existed, but could only recently be applied to animal traits in the context of dynamic energy budget (DEB) theory. The application became possible because of the following: (i) the Add-my-Pet (AmP) collection of DEB parameters and traits (approximately 280) recently reached 3000 animal species with 45000 data sets of measurements; (ii) we found a natural distance measure for species based on their traits as a side result of our research on parameter estimation in DEB context; and (iii) we developed plotting code for visualization that allows labelling of taxonomic relationships. Traits, here defined as DEB parameters or any function of these parameters, have different dimensions, which hamper application of many popular distance measures since they (implicitly) assume that all traits have the same dimensions. The AmP collection follows the workflow that measured data determine parameters and parameters determine trait values. In this way we could fill up the species traits table completely, which we could not do by using measured values only, as data availability varies considerably between species and is typically poor. The goodness of fit of predictions for all data sets is generally excellent. This paper discusses links between the MDS method and parameter estimation and illustrates the application of MDS for the AmP collection to five taxa, three ectothermic and two endothermic, which we consider to be 'complete', in the sense that we expect that it will be difficult to find more species with data in the open literature. This application of MDS shows links between traits and taxonomy that supplements our efforts to find patterns in the co-variation of parameter values. Knowledge about metabolic performance is key to conservation biology, sustainable management and environmental risk assessment, which are seen as interlinked fields.