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1. Indices quantifying the functional aspect of biodiversity are essential in understanding relationships between biodiversity, ecosystem functioning and environmental constraints. Many indices of functional diversity have been published but we lack consensus about what indices quantify, how redundant they are and which ones are recommended. 2. This study aims to build a typology of functional diversity indices from artificial data sets encompassing various community structures (different assembly rules, various species richness levels) and to identify a set of independent indices able to discriminate community assembly rules. 3. Our results confirm that indices can be divided into three main categories, each of these corresponding to one aspect of functional diversity: functional richness, functional evenness and functional divergence. Most published indices are highly correlated and quantify functional richness while quadratic entropy (Q) represents a mix between functional richness and functional divergence. Conversely, two indices (FEve and FDiv respectively quantifying functional evenness and functional divergence) are rather independent to all the others. The power analysis revealed that some indices efficiently detect assembly rules while others performed poorly. 4. To accurately assess functional diversity and establish its relationships with ecosystem functioning and environmental constraints, we recommend investigating each functional component separately with the appropriate index. Guidelines are provided to help choosing appropriate indices given the issue being investigated. 5. This study demonstrates that functional diversity indices have the potential to reveal the processes that structure biological communities. Combined with complementary methods (phylogenetic and taxonomic diversity), the multifaceted framework of functional diversity will help improve our understanding of how biodiversity interacts with ecosystem processes and environmental constraints.

Hill numbers or the effective number of species are increasingly used to quantify species diversity of an assemblage. Hill numbers were recently extended to phylogenetic diversity, which incorporates species evolutionary history, as well as to functional diversity, which considers the differences among species traits. We review these extensions and integrate them into a framework of attribute diversity (the effective number of entities or total attribute value) based on Hill numbers of taxonomic entities (species), phylogenetic entities (branches of unit-length), or functional entities (species-pairs with unit-distance between species). This framework unifies ecologists' measures of species diversity, phylogenetic diversity, and distance-based functional diversity. It also provides a unified method of decomposing these diversities and constructing normalized taxonomic, phylogenetic, and functional similarity and differentiation measures, including N -assemblage phylogenetic or functional generalizations of the classic Jaccard, Sørensen, Horn, and Morisita-Horn indexes. A real example shows how this framework extracts ecological meaning from complex data.

Functional diversity is the diversity of species traits in ecosystems. This concept is increasingly used in ecological research, yet its formal definition and measurements are currently under discussion. As the overall behavior and consistency of functional diversity indices have not been described so far, the novice user risks choosing an inaccurate index or a set of redundant indices to represent functional diversity. In our study we closely examine functional diversity indices to clarify their accuracy, consistency, and independence. Following current theory, we categorize them into functional richness, evenness, or divergence indices. We considered existing indices as well as new indices developed in this study. The new indices aimed at remedying the weaknesses of currently used indices (e.g., by taking into account intraspecific variability). Using virtual data sets, we test (1) whether indices respond to community changes as expected from their category and (2) whether the indices within each category are consistent and independent of indices from other categories. We also test the accuracy of methods proposed for the use of categorical traits. Most classical functional richness indices either failed to describe functional richness or were correlated with functional divergence indices. We therefore recommend using the new functional richness indices that consider intraspecific variability and thus empty space in the functional niche space. In contrast, most functional evenness and divergence indices performed well with respect to all proposed tests. For categorical variables, we do not recommend blending discrete and real-valued traits (except for indices based on distance measures) since functional evenness and divergence have no transposable meaning for discrete traits. Nonetheless, species diversity indices can be applied to categorical traits (using trait levels instead of species) in order to describe functional richness and equitability.

Aim Patterns of benthic biodiversity at the macroecological scale remain poorly characterised throughout the Chilean latitudinal gradient, in part due to the lack of integrated databases, uneven sampling effort, and the use of species richness alone to quantify biodiversity. Different diversity measures, encompassing taxonomic and functional components, may give us extra information on biodiversity relevant to conservation planning and management. Thus, evaluating the spatial complementarity of these measures is essential. Location Coast and continental shelf of Chile. Methods The latitudinal gradient of Chile was divided into five ecoregions according to the Marine Ecosystems of the World classification. Using a 55 × 55 km equal area grid, we estimated the incidence coverage‐based estimator (ICE), taxonomic distinctness (Δ+) and three measures of functional diversity: functional richness (FRic), functional evenness (FEve) and functional divergence (FDiv). For each measure, we described spatial patterns, identified hotspots, evaluated hotspot congruence and evaluated complementarity between measures. Results Diversity patterns varied between ecoregions and over the latitudinal gradient. ICE and Δ+ peaked in the Chiloense and Channels and Fjords ecoregions. Δ+ and FRic present a similar pattern at mid‐latitudes. FEve showed a contrary pattern, principally with FRic. Areas with high numbers of hotspots differed spatially according to each metric, and three latitudinal bands were observed. ICE, Δ+ and FRic were positively correlated, but the hotspot overlap at the grid cell level was more limited. Main Conclusions The complementarity between taxonomic and functional diversity measures is limited when we observe the overlap between grid cells representing hotspots. However, some regions are consistently identified as highly diverse, with the Magellanic Province (Chiloense and Channels and Fjords ecoregions) being the most important for the richness, taxonomic and functional diversity of benthos. Confirmation of the importance of this region can help prioritise conservation efforts.

Urbanisation is an ongoing process associated with multiple environmental changes affecting ecosystems worldwide. Temperature and habitat are main drivers of animal communities within cities, but quantifying their relative weights remains a challenge, as urban heat islands (UHI) often co-vary with land-cover. This study aims to disentangle the effects and relevant scale of temperature and habitat on ground-dwelling spider communities. Based on an original sampling design, we collected 20,761 spider individuals belonging to 137 species at 36 sampling sites in the city of Rennes (northwest France). We characterised communities by assessing the number of trapped individuals at each site, as well as calculating several metrics to estimate taxonomic and functional diversities. Temperature metrics were obtained from two sensor networks monitoring UHI (100-m resolution) and near-ground temperature (1-m resolution) independently. Land-cover and isolation were used to describe landscapes, and vegetation structure to describe local habitats. We used generalized linear mixed models to disentangle the effects of temperature from those of habitat at the landscape and local scales, and identified relationships between community descriptors and predictors. We show that temperature-related metrics are important predictors of spider communities, and that the landscape and local scales have independent effects. Near-ground temperature alone explained 24% of the number of trapped individuals, whereas UHI explained 20% of taxonomic diversity. Local vegetation height and cover were significant predictors of functional diversity, and explained 22% and 25% of variance, respectively. We conclude that locally applied planning measures could mitigate the loss of taxonomic diversity induced by the atmospheric UHI and promote the establishment of more diverse communities.

Elemental sulfur is widely used in fungicide applications to control crop diseases in agricultural systems, but its effects on soil microbial communities are largely unknown. In China, significant amounts of elemental sulfur are sprayed annually on rubber plantations to support crop performance. To investigate the effects of sulfur spraying on microbial diversity, composition, interactions, and functionalities in rubber plantation soil, soil samples from rubber plantations in Yunnan, South China, were collected, and bacterial and fungal communities were analyzed through high-throughput sequencing. Results showed that sulfur application did not alter the alpha diversity but the beta diversity of the soil bacterial community. Notably, sulfur disturbed the relative abundances of Chloroflexi and Planctomycetes. Certain bacteria (e.g., Bacillus and Sinomonas ) thrived under sulfur treatment, influencing nutrient cycling. The ecological network analysis revealed enhanced bacterial and fungal interconnections. Sulfur application had a limited impact on microbial phenotypes and community functions, yet it inhibited sulfur compound respiration. These findings indicate that sulfur spraying can shift microbial community composition and influence nutrient cycling by favoring specific microbial groups. Despite its limited impact on microbial phenotypes, sulfur affects key metabolic processes, such as sulfur respiration, which are vital for soil health and microbial activity. The results highlight the need for sustainable sulfur management to optimize nutrient cycling and soil health on rubber plantations.

Agricultural intensification is recognised as a major driver of biodiversity loss in human-modified landscapes. Several agro-environmental measures at different spatial scales have been suggested to mitigate the negative impact of intensification on biodiversity and ecosystem services. The effect of these measures on the functional structure of service-providing communities remains, however, largely unexplored. Using two distinct landscape designs, we examined how the management options of organic farming at the field scale and crop diversification at the landscape level affect the taxonomic and functional structure of generalist predator communities and how these effects vary along a landscape complexity gradient. Organic farming as well as landscapes with longer and more diversified crop rotations enhanced the activity-density of spiders and rove beetles, but not the species richness or evenness. Our results indicate that the two management options affected the functional composition of communities, as they primarily enhanced the activity-density of functionally similar species. The two management options increased the functional similarity between spider species in regards to hunting mode and habitat preference. Organic farming enhanced the functional similarity of rove beetles. Management options at field and landscape levels were generally more important predictors of community structure when compared to landscape complexity. Our study highlights the importance of considering the functional composition of generalist predators in order to understand how agro-environmental measures at various scales shape community assemblages and ecosystem functioning in agricultural landscapes.

Functional impairment in daily activities, such as work and socializing, is part of the diagnostic criteria for major depressive disorder and most anxiety disorders. Despite evidence that symptom severity and functional impairment are partially distinct, functional impairment is often overlooked. To assess whether functional impairment captures diagnostically relevant genetic liability beyond that of symptoms, we aimed to estimate the heritability of, and genetic correlations between, key measures of current depression symptoms, anxiety symptoms, and functional impairment. In 17,130 individuals with lifetime depression or anxiety from the Genetic Links to Anxiety and Depression (GLAD) Study, we analyzed total scores from the Patient Health Questionnaire-9 (depression symptoms), Generalized Anxiety Disorder-7 (anxiety symptoms), and Work and Social Adjustment Scale (functional impairment). Genome-wide association analyses were performed with REGENIE. Heritability was estimated using GCTA-GREML and genetic correlations with bivariate-GREML. The phenotypic correlations were moderate across the three measures (Pearson's  = 0.50-0.69). All three scales were found to be under low but significant genetic influence (single-nucleotide polymorphism-based heritability [ ] = 0.11-0.19) with high genetic correlations between them (  = 0.79-0.87). Among individuals with lifetime depression or anxiety from the GLAD Study, the genetic variants that underlie symptom severity largely overlap with those influencing functional impairment. This suggests that self-reported functional impairment, while clinically relevant for diagnosis and treatment outcomes, does not reflect substantial additional genetic liability beyond that captured by symptom-based measures of depression or anxiety.

Flower strips are a fundamental part of agri-environment schemes in the Common Agricultural Policy (CAP). Although vegetation is central for many arthropod groups, a few studies have evaluated the effects of flower strip structural and functional attributes on arthropod communities. In this study, we explored the relationship between flower strip attributes and the abundance of different arthropod functional groups in annual flower strips located in an organic apple orchard. We surveyed plant and arthropod communities in 30 1 m × 6 m plots. In each plot, we collected data on species composition and vegetation structure (e.g., total cover, density, number of floral displays). For each plant species, we also retrieved data on leaf palatability and nutritional value. Arthropods were collected using sweep netting technique. Structural and functional attributes of the flower strip revealed a crucial role in regulating arthropod abundance, which however depended on the specific arthropod functional group. We identified three main attributes (plant species richness, composition, and vegetation density) of flower strips that should be considered when implementing multifunctional flower strips. Specifically, plant species richness to ensure complementarity of resources and niches, plant species composition to ensure complementary floral resources, and vegetation density to ensure sheltering microhabitats and suitable microclimatic conditions and to increase the density of floral resources. Our results suggest that by considering structural and functional attributes of flower strips, it is possible to design multifunctional flower strips with greater effectiveness as measures for ecological intensification.

Making inferences about variation within and among various operational units may depend on the ability of a selected approach to diversity analysis to utilize correctly all information available in the raw data. Frequency-based genotypic and gene diversity parameters, methods of ‘true diversity’ and functional diversity, as well as two types of dissimilarity based approaches (by means of averaging pairwise dissimilarities, and solution of the assignment problem) are comprehensively discussed. The dissimilarity based approaches need a suitable assessment of dissimilarity between individual operational units (individuals, communities, populations, clusters, functions, phylogenetic trees etc.). Many commonly used diversity parameters can be derived in terms of the average based measures. The assignment based methods are able to address some limitations and shortcomings of the commonly used measures of population diversity, and they are preferable in the case of possible association between traits. They are always mathematically valid, whereas validity of the average based methods depends on the selected dissimilarity measure. The dissimilarity based methods actually assess functional diversity in the space of the selected traits, and they allow measuring complex diversity and assessment of total γ-diversity as the sum of the independent components of α- and β-diversity with descriptors of different types. The dissimilarity based method for diversity analysis can be consistently employed together with other approaches to data analysis (e.g. clustering). In particular, they may provide valid diversity estimates and replace Nei’s diversity measures, which are often inconsistently used with binary molecular marker data.