Functional trait
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Functional diversity (FD) has the potential to address many ecological questions, from impacts of global change on biodiversity to ecological restoration. There are several methods estimating the different components of FD. However, most of these methods can only be computed at limited spatial scales and cannot account for intraspecific trait variability (ITV), despite its significant contribution to FD. Trait probability density (TPD) functions (which explicitly account for ITV) reflect the probabilistic nature of niches. By doing so, the TPD approach reconciles existing methods for estimating FD within a unifying framework, allowing FD to be partitioned seamlessly across multiple scales (from individuals to species, and from local to global scales), and accounting for ITV. We present methods to estimate TPD functions at different spatial scales and probabilistic implementations of several FD concepts, including the primary components of FD (functional richness, evenness, and divergence), functional redundancy, functional rarity, and solutions to decompose beta FD into nested and unique components. The TPD framework has the potential to unify and expand analyses of functional ecology across scales, capturing the probabilistic and multidimensional nature of FD. The R package TPD (https://CRAN.R-project.org/package=TPD) will allow users to achieve more comparative results across regions and case studies.
- Klíčová slova
- functional diversity, functional trait, niche, probability density function, redundancy, uniqueness,
- MeSH
- biodiverzita * MeSH
- ekologie * MeSH
- fenotyp MeSH
- pravděpodobnostní funkce MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
Under global change, how biological diversity and ecosystem services are maintained in time is a fundamental question. Ecologists have long argued about multiple mechanisms by which local biodiversity might control the temporal stability of ecosystem properties. Accumulating theories and empirical evidence suggest that, together with different population and community parameters, these mechanisms largely operate through differences in functional traits among organisms. We review potential trait-stability mechanisms together with underlying tests and associated metrics. We identify various trait-based components, each accounting for different stability mechanisms, that contribute to buffering, or propagating, the effect of environmental fluctuations on ecosystem functioning. This comprehensive picture, obtained by combining different puzzle pieces of trait-stability effects, will guide future empirical and modeling investigations.
Trait-based research holds high potential to unveil ecological and evolutionary processes. Functional traits are fitness-related characteristics of individuals, which are measured at individual level and defined without using information external to the individual. Despite the usefulness of the functional approach to understand the performance of individuals in ecosystems, and parasitism being the most common life-history strategy on Earth, studies based on functional traits of parasites are still scarce. Since the choice of functional traits is a critical step for any study, we propose a core list of seven functional traits of metazoan parasites, related to three universal challenges faced by organisms (dispersal, establishment, and persistence), and give guidelines to define appropriate functional traits in future parasite community studies.
- Klíčová slova
- community ecology, dispersal, establishment, functional diversity, functional traits, persistence,
- MeSH
- biologické modely MeSH
- ekosystém MeSH
- interakce hostitele a parazita fyziologie MeSH
- paraziti fyziologie MeSH
- parazitologie MeSH
- stadia vývoje MeSH
- zvířata MeSH
- zvláštnosti životní historie * MeSH
- Check Tag
- zvířata MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- přehledy MeSH
The processes causing the latitudinal gradient in species richness remain elusive. Ecological theories for the origin of biodiversity gradients, such as competitive exclusion, neutral dynamics, and environmental filtering, make predictions for how functional diversity should vary at the alpha (within local assemblages), beta (among assemblages), and gamma (regional pool) scales. We test these predictions by quantifying hypervolumes constructed from functional traits representing major axes of plant strategy variation (specific leaf area, plant height, and seed mass) in tree assemblages spanning the temperate and tropical New World. Alpha-scale trait volume decreases with absolute latitude and is often lower than sampling expectation, consistent with environmental filtering theory. Beta-scale overlap decays with geographic distance fastest in the temperate zone, again consistent with environmental filtering theory. In contrast, gamma-scale trait space shows a hump-shaped relationship with absolute latitude, consistent with no theory. Furthermore, the overall temperate trait hypervolume was larger than the overall tropical hypervolume, indicating that the temperate zone permits a wider range of trait combinations or that niche packing is stronger in the tropical zone. Although there are limitations in the data, our analyses suggest that multiple processes have shaped trait diversity in trees, reflecting no consistent support for any one theory.
Complex processes related to biotic and abiotic forces can impose limitations to assembly and composition of plant communities. Quantifying the effects of these constraints on plant functional traits across environmental gradients, and among communities, remains challenging. We define ecological constraint (Ci ) as the combined, limiting effect of biotic interactions and environmental filtering on trait expression (i.e., the mean value and range of functional traits). Here, we propose a set of novel parameters to quantify this constraint by extending the trait-gradient analysis (TGA) methodology. The key parameter is ecological constraint, which is dimensionless and can be measured at various scales, for example, on population and community levels. It facilitates comparing the effects of ecological constraints on trait expressions across environmental gradients, as well as within and among communities. We illustrate the implementation of the proposed parameters using the bark thickness of 14 woody species along an aridity gradient on granite outcrops in southwestern Australia. We found a positive correlation between increasing environmental stress and strength of ecological constraint on bark thickness expression. Also, plants from more stressful habitats (shrublands on shallow soils and in sun-exposed locations) displayed higher ecological constraint for bark thickness than plants in more benign habitats (woodlands on deep soils and in sheltered locations). The relative ease of calculation and dimensionless nature of Ci allow it to be readily implemented at various scales and make it widely applicable. It therefore has the potential to advance the mechanistic understanding of the ecological processes shaping trait expression. Some future applications of the new parameters could be investigating the patterns of ecological constraints (1) among communities from different regions, (2) on different traits across similar environmental gradients, and (3) for the same trait across different gradient types.
- Klíčová slova
- bark thickness, biotic interactions, ecological forces, environmental filters, functional trait space, gradient analysis, trait‐based community ecology,
- Publikační typ
- časopisecké články MeSH
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.
Trait based ecology has developed fast in the last decades, aiming to both explain mechanisms of community assembly, and predict patterns in nature, such as the effects of biodiversity shifts on key ecosystem processes. This body of work has stimulated the development of several conceptual frameworks and analytical methods, as well as the production of trait databases covering a growing number of taxa and organizational levels (from individuals to guilds). However, this breeding ground of novel concepts and tools currently lacks a general and coherent framework, under which functional traits can help ecologists organize their research aims, and serve as the common currency to unify several scientific disciplines. Specifically, we see a need to bridge the gaps between community ecology, ecosystem ecology, and evolutionary biology, in order to address the most pressing environmental issues of our time. To achieve this integration goal, we define a trait-integration continuum, which reconciles alternative trait definitions and approaches in ecology. This continuum outlines a coherent progression of biological scales, along which traits interact and hierarchically integrate from genetic information, to whole organism fitness-related traits, to trait syndromes and functional groups. Our conceptual scheme proposes that lower-level trait integration is closer to the inference of ecoevolutionary mechanisms determining population and community properties, whereas higher-level trait integration is most suited to the prediction of ecosystem processes. Within these two extremes, trait integration varies on a continuous scale, which relates directly to the inductive-deductive loop that should characterize the scientific method. With our proposed framework, we aim to facilitate scientists in contextualising their research based on the trait-integration levels that matter most to their specific goals. Explicitly acknowledging the existence of a trait-integration continuum is a promising way for framing the appropriate questions, thus obtaining reliable answers and results that are comparable across studies and disciplines.
- Klíčová slova
- biological scales, community assembly mechanisms, ecosystem processes, functional trait interactions, inference, interdisciplinarity, performance, prediction,
- MeSH
- biodiverzita MeSH
- biologická evoluce MeSH
- ekologie * MeSH
- ekosystém * MeSH
- fenotyp MeSH
- lidé MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
Understanding the relationship between biodiversity and ecosystem functioning has been a core ecological research topic over the last decades. Although a key hypothesis is that the diversity of functional traits determines ecosystem functioning, we do not know how much trait diversity is needed to maintain multiple ecosystem functions simultaneously (multifunctionality). Here, we uncovered a scaling relationship between the abundance distribution of two key plant functional traits (specific leaf area, maximum plant height) and multifunctionality in 124 dryland plant communities spread over all continents except Antarctica. For each trait, we found a strong empirical relationship between the skewness and the kurtosis of the trait distributions that cannot be explained by chance. This relationship predicted a strikingly high trait diversity within dryland plant communities, which was associated with a local maximization of multifunctionality. Skewness and kurtosis had a much stronger impact on multifunctionality than other important multifunctionality drivers such as species richness and aridity. The scaling relationship identified here quantifies how much trait diversity is required to maximize multifunctionality locally. Trait distributions can be used to predict the functional consequences of biodiversity loss in terrestrial ecosystems.
- Publikační typ
- časopisecké články MeSH
Understanding the relationship between biodiversity and ecosystem functioning has been a core ecological research topic over the past decades. Although a key hypothesis is that the diversity of functional traits determines ecosystem functioning, we do not know how much trait diversity is needed to maintain multiple ecosystem functions simultaneously (multifunctionality). Here, we uncovered a scaling relationship between the abundance distribution of two key plant functional traits (specific leaf area, maximum plant height) and multifunctionality in 124 dryland plant communities spread over all continents except Antarctica. For each trait, we found a strong empirical relationship between the skewness and the kurtosis of the trait distributions that cannot be explained by chance. This relationship predicted a strikingly high trait diversity within dryland plant communities, which was associated with a local maximization of multifunctionality. Skewness and kurtosis had a much stronger impact on multifunctionality than other important multifunctionality drivers such as species richness and aridity. The scaling relationship identified here quantifies how much trait diversity is required to maximize multifunctionality locally. Trait distributions can be used to predict the functional consequences of biodiversity loss in terrestrial ecosystems.
- Publikační typ
- časopisecké články MeSH
While an increasing number of indices for estimating the functional trait diversity of biological communities are being proposed, there is a growing demand by ecologists to clarify their actual implications and simplify index selection. Several key indices relate to mean trait dissimilarity between species within biological communities. Among them, the most widely used include (a) the mean species pairwise dissimilarity (MPD) and (b) the Rao quadratic entropy (and related indices). These indices are often regarded as redundant and promote the unsubstantiated yet widely held view that Rao is a form of MPD. Worryingly, existing R functions also do not always simplify the use and differentiation of these indices. In this paper, we show various distinctions between these two indices that warrant mathematical and biological consideration. We start by showing an existing form of MPD that considers species abundances and is different from Rao both mathematically and conceptually. We then show that the mathematical relationship between MPD and Rao can be presented simply as Rao = MPD × Simpson, where the Simpson diversity index is defined as 1 - dominance. We further show that this relationship is maintained for both species abundances and presence/absence. This evidence dismantles the paradigm that the Rao diversity is an abundance-weighted form of MPD and indicates that both indices can differ substantially at low species diversities. We discuss the different interpretations of trait diversity patterns in biological communities provided by Rao and MPD and then provide a simple R function, called "melodic," which avoids the unintended results that arise from existing mainstream functions.
- Klíčová slova
- Assembly rules, Biodiversity indices, Community, Phylogenetic diversity, Trait variance,
- MeSH
- algoritmy * MeSH
- biodiverzita * MeSH
- biologické modely MeSH
- ekologie normy MeSH
- fenotyp * MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
