Imputation of missing data in life-history trait datasets: which approach performs the best?

CoRRE Trait Data: A dataset of 17 categorical and continuous traits for 4079 grassland species worldwide

In our changing world, understanding plant community responses to global change drivers is critical for predicting future ecosystem composition and function. Plant functional traits promise to be a key predictive tool for many ecosystems, including grasslands; however, their use requires both complete plant community and functional trait data. Yet, representation of these data in global databases is sparse, particularly beyond a handful of most used traits and common species. Here we present the CoRRE Trait Data, spanning 17 traits (9 categorical, 8 continuous) anticipated to predict species' responses to global change for 4,079 vascular plant species across 173 plant families present in 390 grassland experiments from around the world. The dataset contains complete categorical trait records for all 4,079 plant species obtained from a comprehensive literature search, as well as nearly complete coverage (99.97%) of imputed continuous trait values for a subset of 2,927 plant species. These data will shed light on mechanisms underlying population, community, and ecosystem responses to global change in grasslands worldwide.

Using comparative extinction risk analysis to prioritize the IUCN Red List reassessments of amphibians

Assessing the extinction risk of species based on the International Union for Conservation of Nature (IUCN) Red List (RL) is key to guiding conservation policies and reducing biodiversity loss. This process is resource demanding, however, and requires continuous updating, which becomes increasingly difficult as new species are added to the RL. Automatic methods, such as comparative analyses used to predict species RL category, can be an efficient alternative to keep assessments up to date. Using amphibians as a study group, we predicted which species are more likely to change their RL category and thus should be prioritized for reassessment. We used species biological traits, environmental variables, and proxies of climate and land-use change as predictors of RL category. We produced an ensemble prediction of IUCN RL category for each species by combining 4 different model algorithms: cumulative link models, phylogenetic generalized least squares, random forests, and neural networks. By comparing RL categories with the ensemble prediction and accounting for uncertainty among model algorithms, we identified species that should be prioritized for future reassessment based on the mismatch between predicted and observed values. The most important predicting variables across models were species' range size and spatial configuration of the range, biological traits, climate change, and land-use change. We compared our proposed prioritization index and the predicted RL changes with independent IUCN RL reassessments and found high performance of both the prioritization and the predicted directionality of changes in RL categories. Ensemble modeling of RL category is a promising tool for prioritizing species for reassessment while accounting for models' uncertainty. This approach is broadly applicable to all taxa on the IUCN RL and to regional and national assessments and may improve allocation of the limited human and economic resources available to maintain an up-to-date IUCN RL.

A phylogeny-informed characterisation of global tetrapod traits addresses data gaps and biases

Tetrapods (amphibians, reptiles, birds, and mammals) are model systems for global biodiversity science, but continuing data gaps, limited data standardisation, and ongoing flux in taxonomic nomenclature constrain integrative research on this group and potentially cause biased inference. We combined and harmonised taxonomic, spatial, phylogenetic, and attribute data with phylogeny-based multiple imputation to provide a comprehensive data resource (TetrapodTraits 1.0.0) that includes values, predictions, and sources for body size, activity time, micro- and macrohabitat, ecosystem, threat status, biogeography, insularity, environmental preferences, and human influence, for all 33,281 tetrapod species covered in recent fully sampled phylogenies. We assess gaps and biases across taxa and space, finding that shared data missing in attribute values increased with taxon-level completeness and richness across clades. Prediction of missing attribute values using multiple imputation revealed substantial changes in estimated macroecological patterns. These results highlight biases incurred by nonrandom missingness and strategies to best address them. While there is an obvious need for further data collection and updates, our phylogeny-informed database of tetrapod traits can support a more comprehensive representation of tetrapod species and their attributes in ecology, evolution, and conservation research.

Machine Learning Approach for Cardiovascular Death Prediction among Nonalcoholic Steatohepatitis (NASH) Liver Transplant Recipients

Cardiovascular disease is the leading cause of mortality among nonalcoholic steatohepatitis (NASH) patients who undergo liver transplants. In the present study, machine learning algorithms were used to identify important risk factors for cardiovascular death and to develop a prediction model. The Standard Transplant Analysis and Research data were gathered from the Organ Procurement and Transplantation Network. After cleaning and preprocessing, the dataset comprised 10,871 patients and 92 features. Recursive feature elimination (RFE) and select from model (SFM) were applied to select relevant features from the dataset and avoid overfitting. Multiple machine learning algorithms, including logistic regression, random forest, decision tree, and XGBoost, were used with RFE and SFM. Additionally, prediction models were developed using a support vector machine, Gaussian naïve Bayes, K-nearest neighbors, random forest, and XGBoost algorithms. Finally, SHapley Additive exPlanations (SHAP) were used to increase interpretability. The findings showed that the best feature selection method was RFE with a random forest estimator, and the most critical features were recipient and donor blood type, body mass index, recipient and donor state of residence, serum creatinine, and year of transplantation. Furthermore, among all the outcomes, the XGBoost model had the highest performance, with an accuracy value of 0.6909 and an area under the curve value of 0.86. The findings also revealed a predictive relationship between features and cardiovascular death after liver transplant among NASH patients. These insights may assist clinical decision-makers in devising strategies to prevent cardiovascular complications in post-liver transplant NASH patients.

Species-level correlates of land-use responses and climate-change sensitivity in terrestrial vertebrates

Land-use and climate change are major pressures on terrestrial biodiversity. Species' extinction risk and responses to human pressures relate to ecological traits and other characteristics in some clades. However, large-scale comparative assessments of the associations between traits and responses to multiple human pressures across multiple clades are needed. We investigated whether a set of ecological characteristics that are commonly measured across terrestrial vertebrates (ecological traits and geographic range area) are associated with species' responses to different land-use types and species' likely sensitivity to climate change. We aimed to test whether generalizable patterns in response to these pressures arise across both pressures and across vertebrate clades, which could inform assessments of the global signature of human pressures on vertebrate biodiversity and guide conservation efforts. At the species level, we investigated associations between land-use responses and ecological characteristics with a space-for-time substitution approach, making use of the PREDICTS database. We investigated associations between ecological characteristics and expected climate-change sensitivity, estimated from properties of species realized climatic niches. Among the characteristics we considered, 3 were consistently associated with strong land-use responses and high climate-change sensitivity across terrestrial vertebrate classes: narrow geographic range, narrow habitat breadth, and specialization on natural habitats (which described whether a species occurs in artificial habitats or not). The associations of other traits with species' land-use responses and climate-change sensitivity often depended on species' class and land-use type, highlighting an important degree of context dependency. In all classes, invertebrate eaters and fruit and nectar eaters tended to be negatively affected in disturbed land-use types, whereas invertebrate-eating and plant- and seed-eating birds were estimated to be more sensitive to climate change, raising concerns about the continuation of ecological processes sustained by these species under global changes. Our results highlight a consistently higher sensitivity of narrowly distributed species and habitat specialists to land-use and climate change, which provides support for capturing such characteristics in large-scale vulnerability assessments.

Temporal β-diversity decomposition: Insights into fish biodiversity dynamics in the Moroccan South Atlantic

Understanding the various aspects of temporal β-diversity and their relationships can profoundly enhance the knowledge of the intricate dynamics of biodiversity over temporal scales. In this study, we examined extensive data on fish in the Moroccan South Atlantic, to quantify taxonomic and functional temporal β-diversity over three five-year periods, determine the relative contributions of turnover and nestedness to each facet, and elucidate the relationship between taxonomic and functional temporal β-diversity including their components using temporal and spatial comparisons. Our findings revealed a complex relationship between taxonomic and functional temporal β-diversity, with decoupled variation often observed. Furthermore, the predominant component of functional temporal β-diversity was functional nestedness, while species turnover had a greater impact on taxonomic temporal β-diversity. A noteworthy observation was the significant fluctuation in the turnover and nestedness components, despite consistent temporal β-diversity. These insights underscore the pivotal role of temporal β-diversity decomposition and advocate for the integration of functional aspects in temporal biodiversity research to provide additional key indicators for biodiversity sustainable management.

Worldwide diversity in mammalian life histories: Environmental realms and evolutionary adaptations

Mammalian life history strategies can be characterised by a few axes of variation, conforming a space where species are positioned based on the life history strategies favoured in the environment they exploit. Yet, we still lack global descriptions of the diversity of realised mammalian life history and how this diversity is shaped by the environment. We used six life history traits to build a life history space covering worldwide mammalian adaptation, and we explored how environmental realms (land, air, water) influence mammalian life history strategies. We demonstrate that realms are tightly linked to distinct life history strategies. Aquatic and aerial species predominantly adhere to slower life history strategies, while terrestrial species exhibit faster life histories. Highly encephalised terrestrial species are a notable exception to these patterns. Furthermore, we show that different mode of life may play a significant role in expanding the set of strategies exploitable in the terrestrial realm. Additionally, species transitioning between terrestrial and aquatic realms, such as seals, exhibit intermediate life history strategies. Our results provide compelling evidence of the link between environmental realms and the life history diversity of mammals, highlighting the importance of differences in mode of life to expand life history diversity.

Effects of plant diversity on productivity strengthen over time due to trait-dependent shifts in species overyielding

Plant diversity effects on community productivity often increase over time. Whether the strengthening of diversity effects is caused by temporal shifts in species-level overyielding (i.e., higher species-level productivity in diverse communities compared with monocultures) remains unclear. Here, using data from 65 grassland and forest biodiversity experiments, we show that the temporal strength of diversity effects at the community scale is underpinned by temporal changes in the species that yield. These temporal trends of species-level overyielding are shaped by plant ecological strategies, which can be quantitatively delimited by functional traits. In grasslands, the temporal strengthening of biodiversity effects on community productivity was associated with increasing biomass overyielding of resource-conservative species increasing over time, and with overyielding of species characterized by fast resource acquisition either decreasing or increasing. In forests, temporal trends in species overyielding differ when considering above- versus belowground resource acquisition strategies. Overyielding in stem growth decreased for species with high light capture capacity but increased for those with high soil resource acquisition capacity. Our results imply that a diversity of species with different, and potentially complementary, ecological strategies is beneficial for maintaining community productivity over time in both grassland and forest ecosystems.

Evaluating plant lineage losses and gains in temperate forest understories: a phylogenetic perspective on climate change and nitrogen deposition

Global change has accelerated local species extinctions and colonizations, often resulting in losses and gains of evolutionary lineages with unique features. Do these losses and gains occur randomly across the phylogeny? We quantified: temporal changes in plant phylogenetic diversity (PD); and the phylogenetic relatedness (PR) of lost and gained species in 2672 semi-permanent vegetation plots in European temperate forest understories resurveyed over an average period of 40 yr. Controlling for differences in species richness, PD increased slightly over time and across plots. Moreover, lost species within plots exhibited a higher degree of PR than gained species. This implies that gained species originated from a more diverse set of evolutionary lineages than lost species. Certain lineages also lost and gained more species than expected by chance, with Ericaceae, Fabaceae, and Orchidaceae experiencing losses and Amaranthaceae, Cyperaceae, and Rosaceae showing gains. Species losses and gains displayed no significant phylogenetic signal in response to changes in macroclimatic conditions and nitrogen deposition. As anthropogenic global change intensifies, temperate forest understories experience losses and gains in specific phylogenetic branches and ecological strategies, while the overall mean PD remains relatively stable.

Transnational conservation to anticipate future plant shifts in Europe

To meet the COP15 biodiversity framework in the European Union (EU), one target is to protect 30% of its land by 2030 through a resilient transnational conservation network. The European Alps are a key hub of this network hosting some of the most extensive natural areas and biodiversity hotspots in Europe. Here we assess the robustness of the current European reserve network to safeguard the European Alps' flora by 2080 using semi-mechanistic simulations. We first highlight that the current network needs strong readjustments as it does not capture biodiversity patterns as well as our conservation simulations. Overall, we predict a strong shift in conservation need through time along latitudes, and from lower to higher elevations as plants migrate upslope and shrink their distribution. While increasing species, trait and evolutionary diversity, migration could also threaten 70% of the resident flora. In the face of global changes, the future European reserve network will need to ensure strong elevation and latitudinal connections to complementarily protect multifaceted biodiversity beyond national borders.

Functional trait dataset of European groundwater Amphipoda: Niphargidae and Typhlogammaridae

Groundwater represents a vast, but mostly hidden and inaccessible ecosystem. Although often overlooked in freshwater research, groundwater organisms form a significant part of freshwater biodiversity, whereas their functions are crucial in different ecosystem processes. Knowledge on functional traits is generally lacking for most groundwater species worldwide, yet European groundwater amphipods, particularly the family Niphargidae, are an exception. They are well-researched and used as a model system in ecological and evolutionary studies. We focused on this group to assemble a first functional trait dataset dedicated to groundwater species. We gathered data for eight morphological functional traits quantified through 27 measurements for 1123 individuals which represent 180 species and 314 MOTUs. Besides functional trait data, every entry is accompanied with locality information, including habitat type, and DNA sequences if available. The structure of the dataset and data processing information provided along enable wide applicability and extension to other amphipod taxa. When coupled with phylogeny, the dataset may further enhance different aspects of groundwater research, including biodiversity patterns, community assembly processes, and trait evolution.

Contrasting impacts of non-native and threatened species on morphological, life history, and phylogenetic diversity in bird assemblages

Human activities have altered the species composition of assemblages through introductions and extinctions, but it remains unclear how those changes can affect the different facets of biodiversity. Here we assessed the impact of changes in species composition on taxonomic, functional, and phylogenetic diversity across 281 bird assemblages worldwide. To provide a more nuanced understanding of functional diversity, we distinguished morphological from life-history traits. We showed that shifts in species composition could trigger a global decline in avian biodiversity due to the high number of potential extinctions. Moreover, these extinctions were not random but unique in terms of function and phylogeny at the regional level. Our findings demonstrated that non-native species cannot compensate for these losses, as they are both morphologically and phylogenetically close to the native fauna. In the context of the ongoing biodiversity crisis, such alterations in the functional and phylogenetic structure of bird assemblages could heighten ecosystem vulnerability.

The coevolution of rostral keratin and tooth distribution in dinosaurs

Teeth evolved early in vertebrate evolution, and their morphology reflects important specializations in diet and ecology among species. The toothless jaws (edentulism) in extant birds likely coevolved with beak keratin, which functionally replaced teeth. However, extinct dinosaurs lost teeth multiple times independently and exhibited great variation in toothrow distribution and rhamphotheca-like keratin structures. Here, we use rostral jawbone surface texture as a proxy for rostral keratin covering and phylogenetic comparative models to test for the influence of rostral keratin on toothrow distribution in Mesozoic dinosaurs. We find that the evolution of rostral keratin covering explains partial toothrow reduction but not jaw toothlessness. Toothrow reduction preceded the evolution of rostral keratin cover in theropods. Non-theropod dinosaurs evolved continuous toothrows despite evolving rostral keratin covers (e.g. some ornithischians and sauropodomorphs). We also show that rostral keratin covers did not significantly increase the evolutionary rate of tooth loss, which further delineates the antagonistic relationship between these structures. Our results suggest that the evolution of rostral keratin had a limited effect on suppressing tooth development. Independent changes in jaw development may have facilitated further tooth loss. Furthermore, the evolution of strong chemical digestion, a gizzard, and a dietary shift to omnivory or herbivory likely alleviated selective pressures for tooth development.

Evolution of masting in plants is linked to investment in low tissue mortality

Masting, a variable and synchronized variation in reproductive effort is a prevalent strategy among perennial plants, but the factors leading to interspecific differences in masting remain unclear. Here, we investigate interannual patterns of reproductive investment in 517 species of terrestrial perennial plants, including herbs, graminoids, shrubs, and trees. We place these patterns in the context of the plants' phylogeny, habitat, form and function. Our findings reveal that masting is widespread across the plant phylogeny. Nonetheless, reversion from masting to regular seed production is also common. While interannual variation in seed production is highest in temperate and boreal zones, our analysis controlling for environment and phylogeny indicates that masting is more frequent in species that invest in tissue longevity. Our modeling exposes masting-trait relationships that would otherwise remain hidden and provides large-scale evidence that the costs of delayed reproduction play a significant role in the evolution of variable reproduction in plants.

Shifting taxonomic and functional community composition of rivers under land use change

Land use intensification has led to conspicuous changes in plant and animal communities across the world. Shifts in trait-based functional composition have recently been hypothesized to manifest at lower levels of environmental change when compared to species-based taxonomic composition; however, little is known about the commonalities in these responses across taxonomic groups and geographic regions. We investigated this hypothesis by testing for taxonomic and geographic similarities in the composition of riverine fish and insect communities across gradients of land use in major hydrological regions of the conterminous United States. We analyzed an extensive data set representing 556 species and 33 functional trait modalities from 8023 fish communities and 1434 taxa and 50 trait modalities from 5197 aquatic insect communities. Our results demonstrate abrupt threshold changes in both taxonomic and functional community composition due to land use conversion. Functional composition consistently demonstrated lower land use threshold responses compared to taxonomic composition for both fish (urban p = 0.069; agriculture p = 0.029) and insect (urban p = 0.095; agriculture p = 0.043) communities according to gradient forest models. We found significantly lower thresholds for urban versus agricultural land use for fishes (taxonomic and functional p < 0.001) and insects (taxonomic p = 0.001; functional p = 0.033). We further revealed that threshold responses in functional composition were more geographically consistent than for taxonomic composition to both urban and agricultural land use change. Traits contributing the most to overall functional composition change differed along urban and agricultural land gradients and conformed to predicted ecological mechanisms underpinning community change. This study points to reliable early-warning thresholds that accurately forecast compositional shifts in riverine communities to land use conversion, and highlight the importance of considering trait-based indicators of community change to inform large-scale land use management strategies and policies.

A global assessment of the Raunkiaeran shortfall in plants: geographic biases in our knowledge of plant traits

This article is part of the Special Collection ‘Global plant diversity and distribution’. See https://www.newphytologist.org/global-plant-diversity for more details.

Temperate forest understory vegetation shifts after 40 years of conservation

Understanding how vegetation composition and diversity respond to global changes is crucial for effective ecosystem management and conservation. This study evaluated shifts in understory vegetation after 40 years of conservation within Drawa National Park (NW Poland), to check which plant communities changed the most, and whether vegetation shifts reflect global change symptoms (climate change and pollution) or natural forest dynamics. Using ordination and generalized mixed-effects linear models, we assessed changes in alpha diversity metrics, accounting for taxonomic, functional, and phylogenetic aspects within 170 quasi-permanent plots, surveyed in 1973-85 and resurveyed in 2015-19. We found an overall homogenization of forest vegetation and specific shift patterns in certain forest associations. In coniferous and nutrient-poor broadleaved forests, the overall number of species increased due to the replacement of functionally distinct or specialized species with more ubiquitous species that could exploit increased resource availability. In riparian forests and alder carrs we found either shifts from riparian forest to alder carrs or to mesic broadleaved forests. The most stable communities were fertile broadleaved forests. Our study quantified shifts in taxonomic, functional, and phylogenetic diversity after 40 years of conservation and provides important insights into the shifts in vegetation composition in temperate forest communities. In coniferous and nutrient-poor broadleaved forests we found an increase in species richness and replacement of functionally distinct or specialized species by ubiquitous species, indicating increased resource availability. Shifts between wet broadleaved forests and transition into mesic forests suggest water limitation, which can be related to climate change. The most stable were fertile broadleaved forests fluctuating due to natural stand dynamics. The findings highlight the need for ongoing monitoring and management of ecological systems to preserve their diversity and functionality in the face of global changes.

The NEAT Equating Via Chaining Random Forests in the Context of Small Sample Sizes: A Machine-Learning Method

The part of responses that is absent in the nonequivalent groups with anchor test (NEAT) design can be managed to a planned missing scenario. In the context of small sample sizes, we present a machine learning (ML)-based imputation technique called chaining random forests (CRF) to perform equating tasks within the NEAT design. Specifically, seven CRF-based imputation equating methods are proposed based on different data augmentation methods. The equating performance of the proposed methods is examined through a simulation study. Five factors are considered: (a) test length (20, 30, 40, 50), (b) sample size per test form (50 versus 100), (c) ratio of common/anchor items (0.2 versus 0.3), and (d) equivalent versus nonequivalent groups taking the two forms (no mean difference versus a mean difference of 0.5), and (e) three different types of anchors (random, easy, and hard), resulting in 96 conditions. In addition, five traditional equating methods, (1) Tucker method; (2) Levine observed score method; (3) equipercentile equating method; (4) circle-arc method; and (5) concurrent calibration based on Rasch model, were also considered, plus seven CRF-based imputation equating methods for a total of 12 methods in this study. The findings suggest that benefiting from the advantages of ML techniques, CRF-based methods that incorporate the equating result of the Tucker method, such as IMP_total_Tucker, IMP_pair_Tucker, and IMP_Tucker_cirlce methods, can yield more robust and trustable estimates for the "missingness" in an equating task and therefore result in more accurate equated scores than other counterparts in short-length tests with small samples.

An experimental machine learning study investigating the decision-making process of students and qualified radiographers when interpreting radiographic images

AI is becoming more prevalent in healthcare and is predicted to be further integrated into workflows to ease the pressure on an already stretched service. The National Health Service in the UK has prioritised AI and Digital health as part of its Long-Term Plan. Few studies have examined the human interaction with such systems in healthcare, despite reports of biases being present with the use of AI in other technologically advanced fields, such as finance and aviation. Understanding is needed of how certain user characteristics may impact how radiographers engage with AI systems in use in the clinical setting to mitigate against problems before they arise. The aim of this study is to determine correlations of skills, confidence in AI and perceived knowledge amongst student and qualified radiographers in the UK healthcare system. A machine learning based AI model was built to predict if the interpreter was either a student (n = 67) or a qualified radiographer (n = 39) in advance, using important variables from a feature selection technique named Boruta. A survey, which required the participant to interpret a series of plain radiographic examinations with and without AI assistance, was created on the Qualtrics survey platform and promoted via social media (Twitter/LinkedIn), therefore adopting convenience, snowball sampling This survey was open to all UK radiographers, including students and retired radiographers. Pearson's correlation analysis revealed that males who were proficient in their profession were more likely than females to trust AI. Trust in AI was negatively correlated with age and with level of experience. A machine learning model was built, the best model predicted the image interpreter to be qualified radiographers with 0.93 area under curve and a prediction accuracy of 93%. Further testing in prospective validation cohorts using a larger sample size is required to determine the clinical utility of the proposed machine learning model.

Functional traits explain waterbirds' host status, subtype richness, and community-level infection risk for avian influenza

Species functional traits can influence pathogen transmission processes, and consequently affect species' host status, pathogen diversity, and community-level infection risk. We here investigated, for 143 European waterbird species, effects of functional traits on host status and pathogen diversity (subtype richness) for avian influenza virus at species level. We then explored the association between functional diversity and HPAI H5Nx occurrence at the community level for 2016/17 and 2021/22 epidemics in Europe. We found that both host status and subtype richness were shaped by several traits, such as diet guild and dispersal ability, and that the community-weighted means of these traits were also correlated with community-level risk of H5Nx occurrence. Moreover, functional divergence was negatively associated with H5Nx occurrence, indicating that functional diversity can reduce infection risk. Our findings highlight the value of integrating trait-based ecology into the framework of diversity-disease relationship, and provide new insights for HPAI prediction and prevention.

Accelerated body size evolution in upland environments is correlated with recent speciation in South American freshwater fishes

Speciation rates vary greatly among taxa and regions and are shaped by both biotic and abiotic factors. However, the relative importance and interactions of these factors are not well understood. Here we investigate the potential drivers of speciation rates in South American freshwater fishes, the most diverse continental vertebrate fauna, by examining the roles of multiple biotic and abiotic factors. We integrate a dataset on species geographic distribution, phylogenetic, morphological, climatic, and habitat data. We find that Late Neogene-Quaternary speciation events are strongly associated with body-size evolution, particularly in lineages with small body sizes that inhabit higher elevations near the continental periphery. Conversely, the effects of temperature, area, and diversity-dependence, often thought to facilitate speciation, are negligible. By evaluating multiple factors simultaneously, we demonstrate that habitat characteristics associated with elevation, as well as body size evolution, correlate with rapid speciation in South American freshwater fishes. Our study emphasizes the importance of integrative approaches that consider the interplay of biotic and abiotic factors in generating macroecological patterns of species diversity.

A dataset on African bats' functional traits

Trait-based approaches are becoming extremely common in ecological modeling and the availability of traits databases is increasing. However, data availability is often biased towards particular regions and taxa, with many taxa (e.g., bats) often under-represented. Here, we present the AfroBaT dataset, a compilation of trait data on 320 African bat species containing 76,914 values for 86 traits focusing on morphology, reproduction, life-history, trophic ecology, and species distributions. All data were gathered from published literature following the ecological trait-data standard procedure. Missing data for both numerical and categorical traits were imputed with a machine learning approach including species phylogeny. Trophic ecology traits showed the highest coverage in the literature (72% of the species averaged over all traits), while reproductive traits the lowest. Our data imputation improved the coverage of AfroBaT especially for reproductive traits, going from 27% to 58% of the species covered. AfroBaT has a range of potential applications in macroecology and community ecology, and the availability of open-access data on African bats will enable collaboration and data-sharing among researchers.

Sources of intraspecific variation in the isotopic niche of a semi-aquatic predator in a human-modified landscape

Intraspecific variation modulates patterns of resource use by species, potentially affecting the structure and stability of food webs. In human-modified landscapes, habitat disturbance modifies trophic interactions and intraspecific niche variation, impacting population persistence. Here, we investigated the relationship of sex, ontogeny, and habitat factors with the trophic niche of Caiman crocodilus in an agricultural landscape. We evaluated temporal variation in the trophic niche parameters using carbon and nitrogen stable isotope analysis from different body tissues. We found that caimans exploit the same carbon and nitrogen pools through time, with low isotopic variability between seasons, partly due to the slow isotope turnover rates of tissues in crocodilians. Conversely, the trophic niche of caimans varied across habitats, but with no evidence of a difference between natural and anthropogenic habitats. It apparently results from the influence of habitat suitability, connectivity, and caiman movements during the foraging. Our findings highlight the broader niches of juvenile caimans relative to adults, possibly in response of territorialism and opportunistic foraging strategy. Although using similar resources, females had a larger niche than males, probably associated with foraging strategies during nesting. Considering the sex and body size categories, caimans occupied distinct isotopic regions in some habitats, indicating apparent niche segregation. Ontogenetic trophic shifts in the isotopes (δ13C and δ15N) depended on sex, leading to resource partitioning that can potentially reduce intraspecific competition. Decision-makers and stakeholders should consider the trophic dynamics of sex and body size groups for the sustainable management and conservation of caiman populations, which implies in the maintenance of wetland habitats and landscape heterogeneity in the Formoso River floodplain.

How do urbanization and alien species affect the plant taxonomic, functional, and phylogenetic diversity in different types of urban green areas?

Human pressure on urban landscapes has serious consequences for urban plant species. Therefore, environmental and anthropogenic factors affect the assembly of urban wildlife in plant communities. For biodiversity conservation and ecosystem services in urban areas, it is crucial to understand the impacts of urbanization as well as the introduction of alien plant species on urban plant communities. On 47 sites in Poznań (W Poland), we studied variation within and between three management greenery habitats, i.e., urban parks, greenery associated with housing estates, and urban grasslands, as they relate to taxonomical, functional, and phylogenetic alpha and beta diversity. We also examined how urbanization (measured by ISA) and alien plant species relate to vegetation compositional differences. We found that both urbanization and alien plant species cover decreased alpha diversity, while urbanization had various impacts on beta diversity within each studied habitat. Our results suggest that human pressure leads to similarities in the urban flora, where plant species with specific functional traits adapted to the urban environment. To achieve sustainable urbanization, urban planners should not only create diverse green spaces but also eliminate alien plants, increasing the role of urban land management in promoting the wildness of plant biodiversity in cities.

The predictive power of phylogeny on growth rates in soil bacterial communities

Predicting ecosystem function is critical to assess and mitigate the impacts of climate change. Quantitative predictions of microbially mediated ecosystem processes are typically uninformed by microbial biodiversity. Yet new tools allow the measurement of taxon-specific traits within natural microbial communities. There is mounting evidence of a phylogenetic signal in these traits, which may support prediction and microbiome management frameworks. We investigated phylogeny-based trait prediction using bacterial growth rates from soil communities in Arctic, boreal, temperate, and tropical ecosystems. Here we show that phylogeny predicts growth rates of soil bacteria, explaining an average of 31%, and up to 58%, of the variation within ecosystems. Despite limited overlap in community composition across these ecosystems, shared nodes in the phylogeny enabled ancestral trait reconstruction and cross-ecosystem predictions. Phylogenetic relationships could explain up to 38% (averaging 14%) of the variation in growth rates across the highly disparate ecosystems studied. Our results suggest that shared evolutionary history contributes to similarity in the relative growth rates of related bacteria in the wild, allowing phylogeny-based predictions to explain a substantial amount of the variation in taxon-specific functional traits, within and across ecosystems.

Assembly of functional diversity in an oceanic island flora

Oceanic island floras are well known for their morphological peculiarities and exhibit striking examples of trait evolution1-3. These morphological shifts are commonly attributed to insularity and are thought to be shaped by the biogeographical processes and evolutionary histories of oceanic islands2,4. However, the mechanisms through which biogeography and evolution have shaped the distribution and diversity of plant functional traits remain unclear5. Here we describe the functional trait space of the native flora of an oceanic island (Tenerife, Canary Islands, Spain) using extensive field and laboratory measurements, and relate it to global trade-offs in ecological strategies. We find that the island trait space exhibits a remarkable functional richness but that most plants are concentrated around a functional hotspot dominated by shrubs with a conservative life-history strategy. By dividing the island flora into species groups associated with distinct biogeographical distributions and diversification histories, our results also suggest that colonization via long-distance dispersal and the interplay between inter-island dispersal and archipelago-level speciation processes drive functional divergence and trait space expansion. Contrary to our expectations, speciation via cladogenesis has led to functional convergence, and therefore only contributes marginally to functional diversity by densely packing trait space around shrubs. By combining biogeography, ecology and evolution, our approach opens new avenues for trait-based insights into how dispersal, speciation and persistence shape the assembly of entire native island floras.

How do distinct facets of tree diversity and community assembly respond to environmental variables in the subtropical Atlantic Forest?

This study assessed the impact of altitude, precipitation, and soil conditions on species richness (SR), phylogenetic diversity (PD), and functional diversity (FD) standardized effect sizes in subtropical Brazilian Atlantic Forest tree communities. We considered specific trait information (FDs) for FD, reflecting recent adaptive evolution, contrasting with deeper phylogenetic constraints in FD. Three functional traits (leaf area-LA, wood density-WD, and seed mass-SM) were examined for their response to these gradients. Generalized least squares models with environmental variables as predictors and diversity metrics as response variables were used, and a fourth-corner correlation test explored trait-environmental relationships. SR decreased with altitude, while PD increased, indicating niche convergence at higher altitudes. Leaf area and seed mass diversity also decreased with altitude. For LA, both FD and FDs were significant, reflecting filtering processes influenced by phylogenetic inheritance and recent trait evolution. For SM, only the specific trait structure responded to altitude. LA and SM showed significant trait-environmental relationships, with smaller-leaved and lighter-seeded species dominant at higher altitudes. Soil gradients affect diversity. Fertile soils have a wider range of LA, indicating coexistence of species with different nutrient acquisition strategies. WD variation is lower for FDs. SM diversity has different relationships with soil fertility for FDs and FD, suggesting phylogeny influences trait variation. Soil pH influences WD and LA under acidic soils, with deeper phylogenetic constraints (FD). Environmental factors impact tree communities, with evidence of trait variation constraints driven by conditions and resources. Subtropical Atlantic forests' tree assemblies are mainly influenced by altitude, pH, and soil fertility, selecting fewer species and narrower trait spectra under specific conditions (e.g., higher altitudes, pH). Functional diversity patterns reflect both phylogenetic and recent evolution constraints, with varying strength across traits and conditions. These findings highlight the intricate processes shaping long-lived species assembly across diverse environments in the Southern Brazilian Atlantic Forest.

Humanity's diverse predatory niche and its ecological consequences

Although humans have long been predators with enduring nutritive and cultural relationships with their prey, seldom have conservation ecologists considered the divergent predatory behavior of contemporary, industrialized humans. Recognizing that the number, strength and diversity of predator-prey relationships can profoundly influence biodiversity, here we analyze humanity's modern day predatory interactions with vertebrates and estimate their ecological consequences. Analysing IUCN 'use and trade' data for ~47,000 species, we show that fishers, hunters and other animal collectors prey on more than a third (~15,000 species) of Earth's vertebrates. Assessed over equivalent ranges, humans exploit up to 300 times more species than comparable non-human predators. Exploitation for the pet trade, medicine, and other uses now affects almost as many species as those targeted for food consumption, and almost 40% of exploited species are threatened by human use. Trait space analyses show that birds and mammals threatened by exploitation occupy a disproportionally large and unique region of ecological trait space, now at risk of loss. These patterns suggest far more species are subject to human-imposed ecological (e.g., landscapes of fear) and evolutionary (e.g., harvest selection) processes than previously considered. Moreover, continued overexploitation will likely bear profound consequences for biodiversity and ecosystem function.

A network-based approach to identifying correlations between phylogeny, morphological traits and occurrence of fish species in US river basins

The complex network framework has been successfully used to model interactions between entities in Complex Systems in the Biological Sciences such as Proteomics, Genomics, Neuroscience, and Ecology. Networks of organisms at different spatial scales and in different ecosystems have provided insights into community assembly patterns and emergent properties of ecological systems. In the present work, we investigate two questions pertaining to fish species assembly rules in US river basins, a) if morphologically similar fish species also tend to be phylogenetically closer, and b) to what extent are co-occurring species that are phylogenetically close also morphologically similar? For the first question, we construct a network of Hydrologic Unit Code 8 (HUC8) regions as nodes with interaction strengths (edges) governed by the number of common species. For each of the modules of this network, which are found to be geographically separated, there is differential yet significant evidence that phylogenetic distance predicts morphological distance. For the second question, we construct and analyze nearest neighbor directed networks of species based on their morphological distances and phylogenetic distances. Through module detection on these networks and comparing the module-level mean phylogenetic distance and mean morphological distance with the number of basins of common occurrence of species in modules, we find that both phylogeny and morphology of species have significant roles in governing species co-occurrence, i.e. phylogenetically and morphologically distant species tend to co-exist more. In addition, between the two quantities (morphological distance and phylogentic distance), we find that morphological distance is a stronger determinant of species co-occurrences.

Species invasiveness and community invasibility of North American freshwater fish fauna revealed via trait-based analysis

While biological invasions are recognized as a major threat to global biodiversity, determining non-native species' abilities to establish in new areas (species invasiveness) and the vulnerability of those areas to invasions (community invasibility) is challenging. Here, we use trait-based analysis to profile invasive species and quantify the community invasibility for >1,800 North American freshwater fish communities. We show that, in addition to effects attributed to propagule pressure caused by human intervention, species with higher fecundity, longer lifespan and larger size tend to be more invasive. Community invasibility peaks when the functional distance among native species was high, leaving unoccupied functional space for the establishment of potential invaders. Our findings illustrate how the functional traits of non-native species determining their invasiveness, and the functional characteristics of the invaded community determining its invasibility, may be identified. Considering those two determinants together will enable better predictions of invasions.

Global beta-diversity of angiosperm trees is shaped by Quaternary climate change

As Earth's climate has varied strongly through geological time, studying the impacts of past climate change on biodiversity helps to understand the risks from future climate change. However, it remains unclear how paleoclimate shapes spatial variation in biodiversity. Here, we assessed the influence of Quaternary climate change on spatial dissimilarity in taxonomic, phylogenetic, and functional composition among neighboring 200-kilometer cells (beta-diversity) for angiosperm trees worldwide. We found that larger glacial-interglacial temperature change was strongly associated with lower spatial turnover (species replacements) and higher nestedness (richness changes) components of beta-diversity across all three biodiversity facets. Moreover, phylogenetic and functional turnover was lower and nestedness higher than random expectations based on taxonomic beta-diversity in regions that experienced large temperature change, reflecting phylogenetically and functionally selective processes in species replacement, extinction, and colonization during glacial-interglacial oscillations. Our results suggest that future human-driven climate change could cause local homogenization and reduction in taxonomic, phylogenetic, and functional diversity of angiosperm trees worldwide.

Extra‐pair paternity and sexual dimorphism in birds

Differences in the strength of sexual selection between males and females can lead to sexual dimorphism. Extra-pair paternity (EPP) can increase the variance in male reproductive success and hence the opportunity for sexual selection. Previous research on birds suggests that EPP drives the evolution of dimorphism in plumage colour and in body size. Because EPP increases the intensity of sexual selection in males, it should lead to increased dimorphism in species with larger or more colourful males, but decreased dimorphism in species with larger or more colourful females. We explored the covariation between EPP and sexual dimorphism in wing length and plumage colouration in 401 bird species, while controlling for other, potentially confounding variables. Wing length dimorphism was associated positively with the frequency of EPP, but also with social polygamy, sex bias in parental behaviour and body size and negatively with migration distance. The frequency of EPP was the only predictor of plumage colour dimorphism. In support of our prediction, high EPP levels were associated with sexual dichromatism, positively in species in which males are more colourful and negatively in those in which females are more colourful. Contrary to our prediction, high EPP rates were associated with increased wing length dimorphism in species with both male- and female-biased dimorphism. The results support a role for EPP in the evolution of both size and plumage colour dimorphism. The two forms of dimorphism were weakly correlated and predicted by different reproductive, social and life-history traits, suggesting an independent evolution.

A real data-driven simulation strategy to select an imputation method for mixed-type trait data

Missing observations in trait datasets pose an obstacle for analyses in myriad biological disciplines. Considering the mixed results of imputation, the wide variety of available methods, and the varied structure of real trait datasets, a framework for selecting a suitable imputation method is advantageous. We invoked a real data-driven simulation strategy to select an imputation method for a given mixed-type (categorical, count, continuous) target dataset. Candidate methods included mean/mode imputation, k-nearest neighbour, random forests, and multivariate imputation by chained equations (MICE). Using a trait dataset of squamates (lizards and amphisbaenians; order: Squamata) as a target dataset, a complete-case dataset consisting of species with nearly complete information was formed for the imputation method selection. Missing data were induced by removing values from this dataset under different missingness mechanisms: missing completely at random (MCAR), missing at random (MAR), and missing not at random (MNAR). For each method, combinations with and without phylogenetic information from single gene (nuclear and mitochondrial) or multigene trees were used to impute the missing values for five numerical and two categorical traits. The performances of the methods were evaluated under each missing mechanism by determining the mean squared error and proportion falsely classified rates for numerical and categorical traits, respectively. A random forest method supplemented with a nuclear-derived phylogeny resulted in the lowest error rates for the majority of traits, and this method was used to impute missing values in the original dataset. Data with imputed values better reflected the characteristics and distributions of the original data compared to complete-case data. However, caution should be taken when imputing trait data as phylogeny did not always improve performance for every trait and in every scenario. Ultimately, these results support the use of a real data-driven simulation strategy for selecting a suitable imputation method for a given mixed-type trait dataset.

Understanding the Psychophysiological and Sensitization Mechanisms Behind Fibromyalgia Syndrome: A Network Analysis Approach

OBJECTIVE

Current evidence suggests that fibromyalgia syndrome (FMS) involves complex underlying mechanisms. This study aimed to quantify the multivariate relationships between clinical, psychophysical, and psychological outcomes in women with FMS by using network analysis to understand the psychobiological mechanisms driving FMS and generating new research questions for improving treatment strategies.

METHODS

Demographic (age, height, weight), clinical (pain history, pain intensity at rest and during daily living activities), psychophysical (widespread pressure pain thresholds [PPT]), sensory-related (PainDETECT, S-LANSS, Central Sensitization Inventory [CSI]) and psychological (depressive and anxiety levels) variables were collected in 126 women with FMS. Network analysis was conducted to quantify the adjusted correlations between the modeled variables and to assess their centrality indices (i.e., the connectivity with other symptoms in the network and the importance in the system modelled as network).

RESULTS

The network showed several local associations between psychophysical and clinical sensory-related variables. Multiple positive correlations between PPTs were observed, being the strongest weight between PPTs on the knee and tibialis anterior muscle (ρ: 0.33). PainDETECT was associated with LANSS (ρ: 0.45) and CSI (ρ: 0.24), whereas CSI was associated with HADS-A (ρ: 0.28). The most central variables were PPTs over the tibialis anterior (the highest Strength centrality) and CSI (the highest Closeness and Betweenness centrality).

CONCLUSION

Our findings support a model where clinical sensory-related, psychological, and psycho-physical variables are connected, albeit in separate clusters, reflecting a nociplastic condition with a relevant role of sensitization. Clinical implications of the findings, such as developing treatments targeting these mechanisms, are discussed.

Correlated evolution of social organization and lifespan in mammals

Discerning the relationship between sociality and longevity would permit a deeper understanding of how animal life history evolved. Here, we perform a phylogenetic comparative analysis of ~1000 mammalian species on three states of social organization (solitary, pair-living, and group-living) and longevity. We show that group-living species generally live longer than solitary species, and that the transition rate from a short-lived state to a long-lived state is higher in group-living than non-group-living species, altogether supporting the correlated evolution of social organization and longevity. The comparative brain transcriptomes of 94 mammalian species identify 31 genes, hormones and immunity-related pathways broadly involved in the association between social organization and longevity. Further selection features reveal twenty overlapping pathways under selection for both social organization and longevity. These results underscore a molecular basis for the influence of the social organization on longevity.

Diel niche variation in mammalian declines in the Anthropocene

Biodiversity is being eroded worldwide. Many human pressures are most forcefully exerted or have greatest effect during a particular period of the day. Therefore when species are physically active (their diel niche) may influence their risk of population decline. We grouped 5032 terrestrial extant mammals by their dominant activity pattern (nocturnal, crepuscular, cathemeral and diurnal), and determine variation in population decline across diel niches. We find an increased risk of population decline in diurnal (52.1% of species), compared to nocturnal (40.1% of species), crepuscular (39.1% of species) and cathemeral (43.0% of species) species, associated with the larger proportion of diurnal mammals that are primates. Those species with declining populations whose activity predominantly coincides with that of humans (cathemeral, diurnal) face an increased number of anthropogenic threats than those principally active at night, with diurnal species more likely to be declining from harvesting. Across much of the land surface habitat loss is the predominant driver of population decline, however, harvesting is a greater threat to day-active species in sub-Saharan Africa and mainland tropical Asia, associated with declines in megafauna and arboreal foragers. Deepening understanding of diel variation in anthropogenic pressures and resulting population declines will help target conservation actions.

Species life-history strategies affect population responses to temperature and land-cover changes

Human-induced environmental changes have a direct impact on species populations, with some species experiencing declines while others display population growth. Understanding why and how species populations respond differently to environmental changes is fundamental to mitigate and predict future biodiversity changes. Theoretically, species life-history strategies are key determinants shaping the response of populations to environmental impacts. Despite this, the association between species life histories and the response of populations to environmental changes has not been tested. In this study, we analysed the effects of recent land-cover and temperature changes on rates of population change of 1,072 populations recorded in the Living Planet Database. We selected populations with at least 5 yearly consecutive records (after imputation of missing population estimates) between 1992 and 2016, and for which we achieved high population imputation accuracy (in the cases where missing values had to be imputed). These populations were distributed across 553 different locations and included 461 terrestrial amniote vertebrate species (273 birds, 137 mammals, and 51 reptiles) with different life-history strategies. We showed that populations of fast-lived species inhabiting areas that have experienced recent expansion of cropland or bare soil present positive populations trends on average, whereas slow-lived species display negative population trends. Although these findings support previous hypotheses that fast-lived species are better adapted to recover their populations after an environmental perturbation, the sensitivity analysis revealed that model outcomes are strongly influenced by the addition or exclusion of populations with extreme rates of change. Therefore, the results should be interpreted with caution. With climate and land-use changes likely to increase in the future, establishing clear links between species characteristics and responses to these threats is fundamental for designing and conducting conservation actions. The results of this study can aid in evaluating population sensitivity, assessing the likely conservation status of species with poor data coverage, and predicting future scenarios of biodiversity change.

Environmentally driven phenotypic convergence and niche conservatism accompany speciation in hoary bats

Species that are geographically widespread may exist across environmentally heterogeneous landscapes that could influence patterns of occupation and phylogeographic structure. Previous studies have suggested that geographic range size should be positively correlated with niche breadth, allowing widespread species to sustain viable populations over diverse environmental gradients. We examined the congruence of phenotypic and phylogenetic divergence with the environmental factors that help maintain species level diversity in the geographically widespread hoary bats (Lasiurus cinereus sensu lato) across their distribution. Genetic sequences were analyzed using multiple phylogenetic and species delimitation methods, and phenotypic data were analyzed using supervised and unsupervised machine learning approaches. Spatial data from environmental, geographic, and topographic features were analyzed in a multiple regression analysis to determine their relative effect on phenotypic diversity. Ecological niches of each hoary bat species were examined in environmental space to quantify niche overlap, equivalency, and the magnitude of niche differentiation. Phylogenetic and species delimitation analyses support existence of three geographically structured species of hoary bat, each of which is phenotypically distinct. However, the Hawaiian hoary bat is morphologically more similar to the South American species than to the North American species despite a closer phylogenetic relationship to the latter. Multiple regression and niche analyses revealed higher environmental similarities between the South American and Hawaiian species. Hoary bats thus exhibit a pattern of phenotypic variation that disagrees with well-supported genetic divergences, instead indicating phenotypic convergence driven by similar environmental features and relatively conserved niches occupied in tropical latitudes.

Trophic ecology of Gymnodactylus geckoides Spix, 1825 (Squamata, Phyllodactylidae) from Caatinga, Northeastern Brazil

The diet of lizards is mainly composed of arthropods. It can be affected by biotic and abiotic factors, which influence the energy supply provided by the composition of the animal´s diet. The richness and abundance of many arthropod species can be influenced by environmental seasonality, especially in the Caatinga ecoregion, due to the rainfall regimes. The present study aims to describe aspects of the seasonal and morphological variation in the lizard Gymnodactylus geckoides diet and their energy content. We collected 157 individuals (63 females, 68 males, and 26 juveniles) at the Catimbau National Park, Northeastern Brazil, of which 72 were analyzed for the dry season and 59 for the rainy season. Our data indicates Isoptera to be the most common prey in G. geckoides’s diet. Energy content, prey number was higher in the dry season, whereas prey volume and glycogen content increased in the rainy season. Proteins and lipids did not show marked differences. The present study represents the first effort to understand variations in G. geckoide’s trophic ecology, indicating that this specie presents a wide variation in their diet, especially when considering seasonal factors, revealing their needs and restrictions according to prey availability and environmental conditions.

Adaptive division of growth and development between hosts in helminths with two-host life cycles

Parasitic worms (helminths) with complex life cycles divide growth and development between successive hosts. Using data from 597 species of acanthocephalans, cestodes, and nematodes with two-host life cycles, we found that helminths with larger intermediate hosts were more likely to infect larger, endothermic definitive hosts, although some evolutionary shifts in definitive host mass occurred without changes in intermediate host mass. Life-history theory predicts parasites to shift growth to hosts in which they can grow rapidly and/or safely. Accordingly, helminth species grew relatively less as larvae and more as adults if they infected smaller intermediate hosts and/or larger, endothermic definitive hosts. Growing larger than expected in one host, relative to host mass/endothermy, was not associated with growing less in the other host, implying a lack of cross-host trade-offs. Rather, some helminth orders had both large larvae and large adults. Within these taxa, however, size at maturity in the definitive host was unaffected by changes to larval growth, as predicted by optimality models. Parasite life-history strategies were mostly (though not entirely) consistent with theoretical expectations, suggesting that helminths adaptively divide growth and development between the multiple hosts in their complex life cycles.

Building trait datasets: effect of methodological choice on a study of invasion

Trait-based approaches are commonly used to understand ecological phenomena and processes. Trait data are typically gathered by measuring local specimens, retrieving published records, or a combination of the two. Implications of methodological choices in trait-based ecological studies—including source of data, imputation technique, and species selection criteria—are poorly understood. We ask: do different approaches for dataset-building lead to meaningful differences in trait datasets? If so, do these differences influence findings of a trait-based examination of plant invasiveness, measured as abundance and spread rate? We collected on-site (Victoria, Australia) and off-site (TRY database) height and specific leaf area records for as many species as possible out of 157 exotic herbaceous plants. For each trait, we built six datasets of species-level means using records collected on-site, off-site, on-site and off-site combined, and off-site supplemented via imputation based on phylogeny and/or trait correlations. For both traits, the six datasets were weakly correlated (ρ = 0.31–0.95 for height; ρ = 0.14–0.88 for SLA), reflecting differences in species’ trait values from the various estimations. Inconsistencies in species’ trait means across datasets did not translate into large differences in trait-invasion relationships. Although we did not find that methodological choices for building trait datasets greatly affected ecological inference about local invasion processes, we nevertheless recommend: (1) using on-site records to answer local-scale ecological questions whenever possible, and (2) transparency around methodological decisions related to selection of study species and estimation of missing trait values.

Global and regional erosion of mammalian functional diversity across the diel cycle

Biodiversity is declining worldwide. When species are physically active (i.e., their diel niche) may influence their risk of becoming functionally extinct. It may also affect how species losses affect ecosystems. For 5033 terrestrial mammals, we predict future changes to diel global and local functional diversity through a gradient of progressive functional extinction scenarios of threatened species. Across scenarios, diurnal species were at greater risk of becoming functionally extinct than nocturnal, crepuscular, and cathemeral species, resulting in deep functional losses in global diurnal trait space. Redundancy (species with similar roles) will buffer global nocturnal functional diversity; however, across the land surface, losses will mostly occur among functionally dispersed species (species with distinct roles). Functional extinctions will constrict boundaries of cathemeral trait space as megaherbivores, and arboreal foragers are lost. Variation in the erosion of functional diversity across the daily cycle will likely profoundly affect the partitioning of ecosystem functioning between night and day.

Network Analysis for Better Understanding the Complex Psycho-Biological Mechanisms behind Fibromyalgia Syndrome

The aim of this study was to assess potential associations between sensory, cognitive, health-related, and physical variables in women with fibromyalgia syndrome (FMS) using a network analysis for better understanding the complexity of psycho-biological mechanisms. Demographic, clinical, pressure pain threshold (PPT), health-related, physical, and psychological/cognitive variables were collected in 126 women with FMS. A network analysis was conducted to quantify the adjusted correlations between the modeled variables and to assess the centrality indices (i.e., the degree of connection with other symptoms in the network and the importance in the system modeled as a network. This model showed several local associations between the variables. Multiple positive correlations between PPTs were observed, being the strongest weight between PPTs over the knee and tibialis anterior (ρ: 0.28). Catastrophism was associated with higher hypervigilance (ρ: 0.23) and lower health-related EuroQol-5D (ρ: −0.24). The most central variables were PPT over the tibialis anterior (the highest strength centrality), hand grip (the highest harmonic centrality) and Time Up and Go (the highest betweenness centrality). This study, applying network analysis to understand the complex mechanisms of women with FMS, supports a model where sensory-related, psychological/cognitive, health-related, and physical variables are connected. Implications of the current findings, e.g., developing treatments targeting these mechanisms, are discussed.

Biodiversity mediates ecosystem sensitivity to climate variability

A rich body of evidence from local-scale experiments and observational studies has revealed stabilizing effects of biodiversity on ecosystem functioning. However, whether these effects emerge across entire regions and continents remains largely overlooked. Here we combine data on the distribution of more than 57,500 plant species and remote-sensing observations throughout the entire Western Hemisphere to investigate the role of multiple facets of plant diversity (species richness, phylogenetic diversity, and functional diversity) in mediating the sensitivity of ecosystems to climate variability at the regional-scale over the past 20 years. We show that, across multiple biomes, regions of greater plant diversity exhibit lower sensitivity (more stable over time) to temperature variability at the interannual and seasonal-scales. While these areas can display lower sensitivity to interannual variability in precipitation, they emerge as highly sensitive to precipitation seasonality. Conserving landscapes of greater diversity may help stabilize ecosystem functioning under climate change, possibly securing the continuous provisions of productivity-related ecosystem service to people.

With the help of spatial autoregressive models, the relationship between multiple facets of plant biodiversity and ecosystem sensitivity to climate variability is explored on a landscape-scale.

Global relationships in tree functional traits

Due to massive energetic investments in woody support structures, trees are subject to unique physiological, mechanical, and ecological pressures not experienced by herbaceous plants. Despite a wealth of studies exploring trait relationships across the entire plant kingdom, the dominant traits underpinning these unique aspects of tree form and function remain unclear. Here, by considering 18 functional traits, encompassing leaf, seed, bark, wood, crown, and root characteristics, we quantify the multidimensional relationships in tree trait expression. We find that nearly half of trait variation is captured by two axes: one reflecting leaf economics, the other reflecting tree size and competition for light. Yet these orthogonal axes reveal strong environmental convergence, exhibiting correlated responses to temperature, moisture, and elevation. By subsequently exploring multidimensional trait relationships, we show that the full dimensionality of trait space is captured by eight distinct clusters, each reflecting a unique aspect of tree form and function. Collectively, this work identifies a core set of traits needed to quantify global patterns in functional biodiversity, and it contributes to our fundamental understanding of the functioning of forests worldwide.

Understanding patterns in woody plant trait relationships and trade-offs is challenging. Here, by applying machine learning and data imputation methods to a global database of georeferenced trait measurements, the authors unravel key relationships in tree functional traits at the global scale.

Understanding the interaction between clinical, emotional and psychophysical outcomes underlying tension-type headache: a network analysis approach

OBJECTIVE

Evidence supports that tension-type headache (TTH) involves complex underlying mechanisms. The current study aimed to quantify potential multivariate relationships between headache-related, psychophysical, psychological and health-related variables in patients with TTH using network analysis.

METHODS

Demographic (age, height, weight), headache-related (intensity, frequency, duration, and headache-related disability), psychological and emotional (Hospital Anxiety and Depression Scale, Pittsburgh Sleep Quality Index), psycho-physical (pressure pain thresholds [PPTs] and myofascial trigger points) and health-related variables (SF-36 questionnaire) were collected in 169 TTH patients. Network connectivity analysis was unsupervised conducted to quantify the adjusted correlations between the modelled variables and to assess their centrality indices (i.e., the connectivity with other symptoms in the network and the importance in the modelled network).

RESULTS

The connectivity network showed local associations between psychophysical and headache-related variables. Multiple significant local positive correlations between PPTs were observed, being the strongest weight between PPTs over the cervical spine and temporalis area ([Formula: see text]: 0.41). The node with the highest strength, closeness and betweenness centrality was depressive levels. Other nodes with high centrality were vitality and headache intensity.

DISCUSSION

This is the first study applying a network analysis to understand the connections between headache-related, psychophysical, psychological and health-related variables in TTH. Current findings support a model on how the variables are connected, albeit in separate clusters. The role of emotional aspects, such as depression, is supported by the network. Clinical implications of the findings, such as developing TTH treatments strategies targeting these most important variables, are discussed.

A test of Darwin's naturalization conundrum in birds reveals enhanced invasion success in the presence of close relatives

Biological invasions pose one of the most severe environmental challenges of the twenty-first century. A longstanding idea is that invasion risk is predictable based on the phylogenetic distance - and hence ecological resemblance - between non-native and native species. However, current evidence is contradictory. To explain these mixed results, it has been proposed that the effect is scale-dependent, with invasion inhibited by phylogenetic similarity at small spatial scales but enhanced at larger scales. Analyzing invasion outcomes in a global sample of bird communities, we find no evidence to support this hypothesis. Instead, our results suggest that invaders are locally more successful in the presence of closely related and ecologically similar species, at least in human-altered environments where the majority of invasions have occurred. Functional trait analyses further confirm that the ecological niches of invaders are phylogenetically conserved, supporting the notion that successful invasion in the presence of close relatives is driven by shared adaptations to the types of niches available in novel environments.

Global patterns in functional rarity of marine fish

Rare species, which represent a large fraction of the taxa in ecological assemblages, account for much of the biological diversity on Earth. These species make substantial contributions to ecosystem functioning, and are targets of conservation policy. Here we adopt an integrated approach, combining information on the rarity of species trait combinations, and their spatial restrictedness, to quantify the biogeography of rare fish (a taxon with almost 13,000 species) in the world's oceans. We find concentrations of rarity, in excess of what is predicted by a null expectation, near the coasts and at higher latitudes. We also observe mismatches between these rarity hotspots and marine protected areas. This pattern is repeated for both major groupings of fish, the Actinopterygii (bony fish) and Elasmobranchii (sharks, skates and rays). These results uncover global patterns of rarity that were not apparent from earlier work, and highlight the importance of using metrics that incorporate information on functional traits in the conservation and management of global marine fishes.