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Dark-coloured ectotherms absorb energy from the environment at higher rates than light-coloured ectotherms. The thermal melanism hypothesis (TMH) states that this physical mechanism links the colour lightness of the body surfaces of ectotherms to their thermal environment and hence to their geographical distribution. Studies on different insect taxa in Europe found support for this prediction of the TMH. However, whether these results hold also for other biogeographical regions remains unclear. Here, we quantify and map the colour lightness of dragonfly species in North America and directly compare our results to previously published findings for Europe. We estimated the colour lightness of 152 North American dragonfly species from published illustrations, compiled their distribution data from the literature and combined all these data with six biologically relevant environmental variables. We evaluated the importance of phylogenetic autocorrelation for the spatial variation of mean colour lightness of dragonfly assemblages (grid cells of approximately 50 × 50 km size) by repeating all analyses also for the phylogenetically predicted component of the colour lightness of species and the species-specific deviation from this prediction. We also accounted for spatial autocorrelation with autoregressive error models. All statistical approaches showed that dragonfly assemblages from both continents consistently tended to be darker coloured in regions with cold climates and lighter coloured in regions with warm climates. Regression slopes, however, were significantly less steep, and the amount of variance explained by environmental variables was lower for North America than for Europe. Our results highlight the importance of colour lightness for the distribution of dragonfly species, but they also indicate that idiosyncrasies of the continents modify the general pattern.

Phenology, the seasonal timing of life events, is an essential component of diversity patterns. However, the mechanisms involved are complex and understudied. Body colour may be an important factor, because dark-bodied species absorb more solar radiation, which is predicted by the Thermal Melanism Hypothesis to enable them to thermoregulate successfully in cooler temperatures. Here we show that colour lightness of dragonfly assemblages varies in response to seasonal changes in solar radiation, with darker early- and late-season assemblages and lighter mid-season assemblages. This finding suggests a link between colour-based thermoregulation and insect phenology. We also show that the phenological pattern of dragonfly colour lightness advanced over the last decades. We suggest that changing seasonal temperature patterns due to global warming together with the static nature of solar radiation may drive dragonfly flight periods to suboptimal seasonal conditions. Our findings open a research avenue for a more mechanistic understanding of phenology and spatio-phenological impacts of climate warming on insects. Body colour may be an important factor in insect phenology. Here, the authors show that colour lightness of dragonfly assemblages from the UK, collected between May and October from 1990-2020, varies in response to seasonal changes in solar radiation, suggesting a link between colour-based thermoregulation and insect phenology.

Small-scale studies have shown that colour lightness variation can have important physiological implications in ectotherms, with darker species having greater heating rates, as well as protection against pathogens and photooxidative damage. Using data for 41% (3059) of all known frog and toad species (Anura) from across the world, we reveal ubiquitous and strong clines of decreasing colour lightness towards colder regions and regions with higher pathogen pressure and UVB radiation. The relative importance of pathogen resistance is higher in the tropics and that of thermoregulation is higher in temperate regions. The results suggest that these functions influence colour lightness evolution in anurans and filtered for more similarly coloured species under climatic extremes, while their concurrent importance resulted in high within-assemblage variation in productive regions. Our findings indicate three important functions of colour lightness in anurans – thermoregulation, pathogen and UVB protection – and broaden support for colour lightness-environment relationships in ectotherms. Anurans—frogs and toads—are a diverse group with a remarkable variety of colours. Here, the authors report a global analysis of colour variation in anurans, finding evidence that colour lightness is important for thermoregulation, protection from UVB radiation and resistance to pathogens.

Insect populations have become increasingly threatened during the last decades due to climate change and landuse intensification. Species characteristics driving these threats remain poorly understood. Trait‐based analyses provide a straight‐forward approach to gain a mechanistic understanding of species' extinction risk, guiding the development of conservation strategies. We combined morphological traits and phylogenetic relationship for 332 European species of butterflies and 115 species of odonates (dragon and damselflies) to model their red list status via phylogenetically controlled ordered logistic regression. We hypothesized that extinction risk increases with increasing body volume and wing area, decreasing range size, and is larger for brighter species. All investigated traits exhibited a strong phylogenetic signal. When controlling for phylogenetic relationship, we found that extinction risk of butterflies increased with decreasing range size. The extinction risk of odonates showed no relationship with the selected traits. Our results show that there is no universal trait defining the extinction risk of our investigated insect taxa. Furthermore, evolutionary history, measured as the phylogenetically predicted part of our analyzed traits, poorly predicted extinction risk. Our study confirms the focus of conservation measures on European butterfly species with small range sizes. A trait‐based analysis for European butterflies and odonates to gain a mechanistic understanding of species’ extinction risk. We found no universal trait defining the extinction risk of our investigated insect taxa. When controlling for phylogenetic relationship the extinction risk of butterflies increased with decreasing range size while extinction risk of odonates showed no relationship with the selected traits.

We investigated the effects of contemporary and historical factors on the spatial variation of European dragonfly diversity. Specifically, we tested to what extent patterns of endemism and phylogenetic diversity of European dragonfly assemblages are structured by 1) phylogenetic conservatism of thermal adaptations and 2) differences in the ability of post-glacial recolonization by species adapted to running waters (lotic) and still waters (lentic). We investigated patterns of dragonfly diversity using digital distribution maps and a phylogeny of 122 European dragonfly species, which we constructed by combining taxonomic and molecular data. We calculated total taxonomic distinctiveness and mean pairwise distances across 4192 50 × 50 km equal-area grid cells as measures of phylogenetic diversity. We compared species richness with corrected weighted endemism and standardized effect sizes of mean pairwise distances or residuals of total taxonomic distinctiveness to identify areas with higher or lower phylogenetic diversity than expected by chance. Broken-line regression was used to detect breakpoints in diversity–latitude relationships. Dragonfly species richness peaked in central Europe, whereas endemism and phylogenetic diversity decreased from warm areas in the south-west to cold areas in the north-east and with an increasing proportion of lentic species. Except for species richness, all measures of diversity were consistently higher in formerly unglaciated areas south of the 0°C isotherm during the Last Glacial Maximum than in formerly glaciated areas. These results indicate that the distributions of dragonfly species in Europe were shaped by both phylogenetic conservatism of thermal adaptations and differences between lentic and lotic species in the ability of post-glacial recolonization/dispersal in concert with the climatic history of the continent. The complex diversity patterns of European dragonflies provide an example of how integrating climatic and evolutionary history with contemporary ecological data can improve our understanding of the processes driving the geographical variation of biological diversity.

Previous macrophysiological studies suggested that temperature‐driven color lightness and body size variations strongly influence biogeographical patterns in ectotherms. However, these trait–environment relationships scale to local assemblages and the extent to which they can be modified by dispersal remains largely unexplored. We test whether the predictions of the thermal melanism hypothesis and the Bergmann's rule hold for local assemblages. We also assess whether these trait–environment relationships are more important for species adapted to less stable (lentic) habitats, due to their greater dispersal propensity compared to those adapted to stable (lotic) habitats. We quantified the color lightness and body volume of 99 European dragon‐ and damselflies (Odonata) and combined these trait information with survey data for 518 local assemblages across Europe. Based on this continent‐wide yet spatially explicit dataset, we tested for effects temperature and precipitation on the color lightness and body volume of local assemblages and assessed differences in their relative importance and strength between lentic and lotic assemblages, while accounting for spatial and phylogenetic autocorrelation. The color lightness of assemblages of odonates increased, and body size decreased with increasing temperature. Trait–environment relationships in the average and phylogenetic predicted component were equally important for assemblages of both habitat types but were stronger in lentic assemblages when accounting for phylogenetic autocorrelation. Our results show that the mechanism underlying color lightness and body size variations scale to local assemblages, indicating their general importance. These mechanisms were of equal evolutionary significance for lentic and lotic species, but higher dispersal ability seems to enable lentic species to cope better with historical climatic changes. The documented differences between lentic and lotic assemblages also highlight the importance of integrating interactions of thermal adaptations with proxies of the dispersal ability of species into trait‐based models, for improving our understanding of climate‐driven biological responses. We quantified the color lightness and body volume of 99 European dragon‐ and damselflies (Odonata) and combined this trait information with survey data for 518 local assemblages across Europe to test whether trait‐environment relationships previously reported at coarse spatial scales also hold for spatially explicit local assemblages. We show that the color lightness of odonates assemblages increased and body size decrease with increasing temperature across Europe, supporting the thermal melanism hypothesis and Bergmann's rule, respectively. Accounting for differences in the dispersal/recolonization ability between lentic and lotic species and the phylogenetic relationships of species indicated that both groups show similar trait‐environment relationships in the phylogenetically predicted part of traits (evolutionary responses), but differ in their responses to (recent) historical climatic changes.

Expansion of a poly-glutamine (polyQ) repeat in a group of functionally unrelated proteins is the cause of several inherited neurodegenerative disorders, including Huntington’s disease. The polyQ length-dependent aggregation and toxicity of these disease proteins can be reproduced in Saccharomyces cerevisiae . This system allowed us to screen for genes that when overexpressed reduce the toxic effects of an N-terminal fragment of mutant huntingtin with 103 Q. Surprisingly, among the identified suppressors were three proteins with Q-rich, prion-like domains (PrDs): glycine threonine serine repeat protein (Gts1p), nuclear polyadenylated RNA-binding protein 3, and minichromosome maintenance protein 1. Overexpression of the PrD of Gts1p, containing an imperfect 28 residue glutamine-alanine repeat, was sufficient for suppression of toxicity. Association with this discontinuous polyQ domain did not prevent 103Q aggregation, but altered the physical properties of the aggregates, most likely early in the assembly pathway, as reflected in their increased SDS solubility. Molecular simulations suggested that Gts1p arrests the aggregation of polyQ molecules at the level of nonfibrillar species, acting as a cap that destabilizes intermediates on path to form large fibrils. Quantitative proteomic analysis of polyQ interactors showed that expression of Gts1p reduced the interaction between polyQ and other prion-like proteins, and enhanced the association of molecular chaperones with the aggregates. These findings demonstrate that short, Q-rich peptides are able to shield the interactive surfaces of toxic forms of polyQ proteins and direct them into nontoxic aggregates. Significance Expansion of a poly-glutamine (polyQ) repeat is the causal mutation of several inherited neurological disorders, including Huntington’s disease. In a yeast genetic screen, we identified several proteins with Q-rich, prion-like domains that reduce the toxicity of mutant polyQ proteins when overexpressed. One of these, glycine threonine serine repeat protein (Gts1p), was characterized in more detail. Association with Gts1p did not prevent aggregation but altered the physical properties and the interactome of the aggregates. Specifically, Gts1p expression reduced the sequestration of other prion-like proteins into the polyQ aggregates. These findings link polyQ toxicity in yeast with the coaggregation of prion proteins and show that short Q-rich peptides are able to shield toxic forms of polyQ proteins, directing them into nontoxic aggregates.

It is widely believed that the modular organization of cellular function is reflected in a modular structure of molecular networks. A common view is that a \"module\" in a network is a cohesively linked group of nodes, densely connected internally and sparsely interacting with the rest of the network. Many algorithms try to identify functional modules in protein-interaction networks (PIN) by searching for such cohesive groups of proteins. Here, we present an alternative approach independent of any prior definition of what actually constitutes a \"module\". In a self-consistent manner, proteins are grouped into \"functional roles\" if they interact in similar ways with other proteins according to their functional roles. Such grouping may well result in cohesive modules again, but only if the network structure actually supports this. We applied our method to the PIN from the Human Protein Reference Database (HPRD) and found that a representation of the network in terms of cohesive modules, at least on a global scale, does not optimally represent the network's structure because it focuses on finding independent groups of proteins. In contrast, a decomposition into functional roles is able to depict the structure much better as it also takes into account the interdependencies between roles and even allows groupings based on the absence of interactions between proteins in the same functional role. This, for example, is the case for transmembrane proteins, which could never be recognized as a cohesive group of nodes in a PIN. When mapping experimental methods onto the groups, we identified profound differences in the coverage suggesting that our method is able to capture experimental bias in the data, too. For example yeast-two-hybrid data were highly overrepresented in one particular group. Thus, there is more structure in protein-interaction networks than cohesive modules alone and we believe this finding can significantly improve automated function prediction algorithms.

Expert range maps (ExpRMs) are frequently used to inform species distributions, but often incomplete or missing for many species, particularly among plants and invertebrates. Many species without ExpRMs also have too few occurrence records for reliable application of species distribution models (SDMs). Here we evaluate the performance of commonly used range surrogates and recommend tools that can help fill this significant knowledge gap across a wide range of understudied taxa. Specifically, we explore an alternative range surrogate (ecoregional range maps; EcoRMs), assess its performance versus traditional approaches for 624 North American butterfly species, and outline its use alone and as part of SDMs. As an alternative range estimate, we use terrestrial ecoregions that represent a regionalization of biogeographical zones and we suggest geographical filters and simplifications that improve their performance. We show that consistently across different spatial scales and both in comparison with ExpRMs and SDMs, EcoRMs have an exceptionally high sensitivity and generally a high mean performance. Particularly for species with fewer than 100 occurrence records, EcoRMs outperform other range surrogates. The congruence of species richness patterns was also similar for all approaches. The use of EcoRMs as substitute for data‐poor species without ExpRMs will strongly boost taxonomic coverage of range maps. Additionally, integrating EcoRMs as domains/masks/offsets into SDMs promises significant improvements to model accuracy. For butterflies alone, EcoRMs would thereby provide new range information for 17% and improve basic range information for 43% of all approximately nineteen thousand species. Other technical advantages of generating EcoRMs may also help to overcome issues of the availability, updateability, reproducibility, and circularity of ExpRMs, SDMs and minimum convex hulls (MCVs). In summary, ecoregion‐based range maps offer a versatile tool for ecology and conservation of terrestrial taxa and the application of the EcoRM approach may prove similarly useful for freshwater and marine ecoregions.

Aim: Recent studies increasingly use statistical methods to infer biotic interactions from co-occurrence information at a large spatial scale. However, disentangling biotic interactions from other factors that can affect co-occurrence patterns at the macroscale is a major challenge. Approach: We present a set of questions that analysts and reviewers should ask to avoid erroneously attributing species association patterns to biotic interactions. Our questions relate to the appropriateness of data and models, the causality behind a correlative signal, and the problems associated with static data from dynamic systems. We summarize caveats reported by macroecological studies of biotic interactions and examine whether conclusions on the presence of biotic interactions are supported by the modelling approaches used. Findings: Irrespective of the method used, studies that set out to test for biotic interactions find statistical associations in species' co-occurrences. Yet, when compared with our list of questions, few purported interpretations of such associations as biotic interactions hold up to scrutiny. This does not dismiss the presence or importance of biotic interactions, but it highlights the risk of too lenient interpretation of the data. Combining model results with information from experiments and functional traits that are relevant for the biotic interaction of interest might strengthen conclusions. Main conclusions: Moving from species- to community-level models, including biotic interactions among species, is of great importance for process-based understanding and forecasting ecological responses. We hope that our questions will help to improve these models and facilitate the interpretation of their results. In essence, we conclude that ecologists have to recognize that a species association pattern in joint species distribution models will be driven not only by real biotic interactions, but also by shared habitat preferences, common migration history, phylogenetic history and shared response to missing environmental drivers, which specifically need to be discussed and, if possible, integrated into models.