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FIGURE 4 in Diversity and fossil record of larvae of three groups of lacewings with unusual ecology and functional morphology: Ithonidae, Coniopterygidae and Sisyridae

FIGURE 4. Fossil larva, "beak larva" type 2, from Myanmar amber, PED 0596, specimen 6803. A. Dorsal view; posterior part not well accessible. B. Colour-marked version of A. Abbreviations: 1t = trunk appendage 1; at = antenna; hc = head capsule; ms = mesothorax; pl = palp; pt = prothorax.

FIGURE 5 in Diversity and fossil record of larvae of three groups of lacewings with unusual ecology and functional morphology: Ithonidae, Coniopterygidae and Sisyridae

FIGURE 5. Fossil larva, "beak larva" type 2, from Myanmar amber, PED 0596, specimen 6803, continued. A. Ventral view; details not well accessible; posterior end not inside the amber. B. Close-up on head in dorsal view. C. Close up on trunk appendage 1 in dorsal view. D. Same as C; estimated outline of appendage, visible through tergite outlined in red. Abbreviations: at = antenna; "b" = beak; pl = palp.

FIGURE 3 in Diversity and fossil record of larvae of three groups of lacewings with unusual ecology and functional morphology: Ithonidae, Coniopterygidae and Sisyridae

FIGURE 3. Fossil larva of Sisyridae from Baltic amber, CCGG 7122, specimen 6502. A. Dorsal view. B. Ventral view. C. Colour-marked version of B. D. Close-up of head in dorsal view. E. Colour-marked version of D. F. Close-up on gills. G. Close-up on trunk end. Abbreviations: at = antenna; hc = head capsule; ms = mesothorax; mt = metathorax; pt = prothorax; sy = stylet.

FIGURE 1 in Diversity and fossil record of larvae of three groups of lacewings with unusual ecology and functional morphology: Ithonidae, Coniopterygidae and Sisyridae

FIGURE 1. Fossil larva of Coniopterygidae from Baltic amber, CCHH 540-1, specimen 6301. A. Ventral view. B. Dorsal view. C. Colour-marked version of B. D. Close-up of head in dorsal view. E. Close-up of head in ventral view. F. Close-up on right hind leg; arrows mark claws. G. Close-up of hind leg; arrows mark claws. Abbreviations: a1–a8 = abdomen segment 1–8; at = antenna; cx = coxa; e1–3 = element 1–3; fe = femur; hc = head capsule; lp = labial palp; ms = mesothorax; mt = metathorax; pt = prothorax; st = stemmata; ta = tarsus; te = trunk end; ti = tibia; tr = trochanter.

FIGURE 2 in Diversity and fossil record of larvae of three groups of lacewings with unusual ecology and functional morphology: Ithonidae, Coniopterygidae and Sisyridae

FIGURE 2. Fossil larva of Sisyridae from Baltic amber, CCGG 1383, specimen 6501. A. Dorsal view. B. Ventral view. C. Colour-marked version of B. D. Close-up of head in dorsal view. E. Colour-marked version of D; arrows mark stemmata. F. Close-up on gills. G. Close-up on processes on trunk segments. Abbreviations: a3–a7 = abdomen segment 3–7; at = antenna; gi = gills; hc = head capsule; ms = mesothorax; mt = metathorax; pt = prothorax; sy = stylet; te = trunk end.

opencc-zeroApr 2024View details →

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Scripts and data for: Integrating different facets of diversity into food web models: how adaptation among and within functional groups shape ecosystem functioning

Adaptation of communities to environmental fluctuations can emerge from different facets of biodiversity, which may impact ecosystem functioning differently. Previous work examined how ecosystem functions can be influenced by two sources of adaptive potential: sorting (i.e., changes in community composition due to fitness differences) can occur when multiple species or groups are present (richness), and trait adaptability (i.e., trait adjustments within species or functional groups) can emerge from genetic or phenotypic diversity. However, their effect is typically studied separately, and often in the context of only one trophic level. Therefore, we used a bitrophic trait-based model varying in richness and in the presence of trait adaptability at each trophic level, to investigate how sorting and trait adaptability, at one or two trophic levels, separately or jointly shape ecosystem functions. We found that the adaptive potential emerging from any facet of diversity-induced changes in trophic interactions, in turn, affects biomass distributions within and across trophic levels, dynamical behaviour, and synchrony of biomass dynamics within a trophic level. Particularly, sorting and trait adaptability could contribute to a similar degree and at a similar time to temporal changes in ecosystem functions, but their respective contribution depended on the speed of trait adaptation, the trait range between similar functional groups, and trophic interactions. We thus suggest to consider multiple facets of diversity and their corresponding sources of adaptive potential to deepen our mechanistic understanding of ecosystem functioning, especially in a context of rapid biodiversity change.

opencc-by-4.0Jul 2024View details →

The data for: LCR in fungi display functional groups and are depleted in positively charged amino-acids

Abstract The dataset consists of a TAB formatted table (Main_Dataset.tsv), that integrates information about protein domains (pfam_scan, GO terms), low complexity regions (SEG), signal peptides (SignalP), and transmembrane elements (TMHMM) for each of the analysed proteins within 183 fungal proteomes. The Main Dataset has been designed to ease further searches with Linux bash commands, for e.g. sorting and subsetting by the aforementioned traits. This resource can be used by users interested in detailed annotation of particular protein families, sets of organisms, low complexity regions, types of proteins (for instance transmembrane proteins). Thanks to its simple and clear format, it may also be easily enriched with additional data. Data types: Main_Dataset.tsv is a TSV table with protein annotations Estimate of dataset size:  245MB Readme file: Main_Dataset.tsv is a TSV table with the following columns: <ol> <li> Assembly ID from NCBI </li> <li> Protein ID (NCBI accession) </li> <li> Protein length </li> <li> Presence of protein domains; Boolean </li> <li> symbolic localization of protein domains; 10 bins scaled to sum up to total protein length </li> <li> number of transmembrane elements predicted with TMHMM </li> <li> total length of transmembrane elements </li> <li> Symbolic localization of transmembrane elements; 10 bins scaled to sum up to total protein length </li> <li> Presence of signal peptide; Boolean </li> <li> Total number of LCR </li> <li> Total length of LCR </li> <li> Symbolic localization of LCR; 3 bins: N-termini (0-0.25 of protein length), middle (0.25-0.75 of protein length), and C-term (0.75-1 protein length) </li> <li> Symbolic localization of LCR; 10 bins scaled to sum up to total protein length </li> <li> LCR sequences in the N-terminal part of protein, separated by a comma </li> <li> LCR sequences in the middle part of protein, separated by a comma </li> <li> LCR sequences in the  C-terminal part of the protein, separated by a comma </li> <li> Pfam domains overlapping with LCRs (>80% of LCR length) </li> <li> Pfam domains in protein (ordered by domain start) </li> <li> GO terms based on Pfam domains obtained by mapping on pfam2go, separated with the pipe symbol '|' </li> </ol>   Acknowledgements This work was supported by National Science Centre grants (#2021/41/B/NZ2/02426 to AM, #2019/35/D/NZ2/03411 to K.S).

opencc-by-4.0Nov 2021View details →

The predication of soil nematode and functional groups abundance in the terrestrial on the Tibetan Plateau (Data Set)

This is the dataset which is generated from the manuscript entitled 'The predication of soil nematode and functional groups abundance in the terrestrial on the Tibetan Plateau'. The spatial resolution of this dataset is about 1 km, of which coordinates systems is WGS84. There are 6 layers of nematode abundance in this GeoTiff file: 1. abd - Total Soil Nematode Abundance 2. bact - Abundance of bacterivores 3. fung - Abundance of fungivores 4. herb - Abundance of plant parasite 5. omni - Abundance of omnivores 6. pred - Abundance of predators

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Data from: Plant richness, land use and temperature differently shape invertebrate leaf-chewing herbivory on plant functional groups

Nutrient demands of leaf-chewing invertebrate herbivores change with temperature, which causes shifts in herbivores' diets. Temperature may act differently on herbivore species, so that factors shaping herbivore species richness may modulate temperature effects on invertebrate herbivory among plant functional groups with different nutrient composition (C:N ratio low to high: legumes, non-leguminous forbs, grasses). Global warming urges a deeper understanding of temperature effects on herbivory among plant functional groups in different habitats and landscapes. This study obtained measures on proportional leaf area loss to leaf-chewing invertebrate herbivores ('herbivory') on three plant functional groups on 80 plots of open herbaceous vegetation adjacent to different habitat types (forest, grassland, arable field, settlement) along climate and land-use gradients in Bavaria, Germany. Herbivory was analysed with regard to habitat characteristics (habitat type, plant richness at species and family level, local mean temperature), landscape characteristics (proportion of grassland, landscape diversity; 0.2–3.0-km), climate (multi-annual mean temperature, 'MAT') and interactive effects of plant functional group, temperature and habitat or landscape characteristics. Herbivory on plant functional groups changed differently in response to plant richness (family level only) and habitat type, but not to differences in landscape characteristics and temperature – only on grassland plots, multi-annual mean temperature differentially affected herbivory among plant functional groups. Thus, abiotic and biotic factors can differently affect leaf-chewing herbivory on plant functional groups. Under current conditions, plant richness and habitat type more strongly affected herbivory among legumes, forbs and grasses than temperature and landscape-scale land use.

opencc-zeroJun 2022View details →

opencc-by-4.0Jul 2024View details →

Database of Benchmark Molecules with Functional Groups

A dataset was created by calculating 156 molecules, each with around 800 conformers. To store the dataset, a database was designed that supports CRUD (Create, Read, Update, Delete) operations, allowing efficient management and retrieval of the data. Each molecule is associated with a unique identifier (SMILES), and each conformer has an ID as well. The molecules also have their corresponding functional groups, which they can be identified by, as well. A PDF file representing the functional groups is included, ensuring comprehensive documentation and easy access to the molecular data. The python script, can be accessed via the repository link.

FIGURE 3 in A cascade of dams affects fish spatial distributions and functional groups of local assemblages in a subtropical river

FIGURE 3 | Analysis of multivariate homogeneity of group dispersions (PERMIDISP) by betadisper boxplot, using the Bray-Curtis index, considering the abundance (CPUEN) of movement/reproductive/size (A) and trophic categories (B), and biomass (CPUEB) of movement/ reproductive/size categories (C) and trophic categories (D). The data was based on sampling sites, and presented by environment groups: [DU, DD] = Sampling points away from the dams; [R1, R2, R3] = sampling points located in the reservoirs; [DR1, DR2, DR3] = locations downstream from dams. Greater distance to spatial median indicates larger dispersion and therefore a more diverse/heterogeneous environment. Box lower and upper endpoints represent the 25th and 75th quartiles, respectively. The horizontal bar and plus symbol inside each box represent median, excluding outliers, which are presented by open circles. See Tabs. 4 and 5 for P values from environments comparisons.

FIGURE 2 in A cascade of dams affects fish spatial distributions and functional groups of local assemblages in a subtropical river

FIGURE 2 | Ordination plots produced by the non-metric multidimensional scaling analysis (NMDS) using the Bray-Curtis index, considering the abundance (CPUEN) of movement/reproductive/size (A) and trophic categories (B), and biomass (CPUEB) of movement/ reproductive/size categories (C) and trophic categories (D), among survey locations. [DU (red triangle), DD (yellow triangle)] = Sampling points away from the dams; [R1 (red circle), R2 (green circle), R3 (orange circle)] = sampling points located in the reservoirs; [DR1 (green square), DR2 (orange square), DR3 (red square)] = locations downstream from dams. Labels are for Detritivores, Invertivores, Carnivores, Omnivores, and Piscivores; S/SM = sedentary/short migration, NPC = no parental care, PC = parental care, IF = internal fertilization, and LM = long migration; and Small, Medium, and Large body sizes.

FIGURE 1 in A cascade of dams affects fish spatial distributions and functional groups of local assemblages in a subtropical river

FIGURE 1 | Sampling locations in the Upper Uruguai River, Brazil. The symbols indicate survey sites: circles represent sites within the reservoirs (R1 = site 3 to 5; R2 = site 7 to 9; R3 = site 11 to 14); squares indicate sites located just below dams [Downstream R1 (DR1) = 6, Downstream R2 (DR2) = 10, Downstream R3 (DR3) = 15], and triangles indicate sites that are most distant from dams [Distant Upstream (DU) = 1 and 2; Distant Downstream (DD) = 16 and 17].

FIGURE 3 in Fish functional trophic groups in headwater karst streams from the Upper Paraguay River basin

FIGURE 3 | Representative images of the fish assemblage from Serra da Bodoquena streams. A. Farlowella paraguayensis among twigs and leaf litter in the substrate; B. Hypostomus froehlichi between boulders; C. Creagrutus meridionalis foraging near a sandy substrate; D. Pimelodella taenioptera and Astyanax lacustris foraging among leaf litter in the substrate; E. Hyphessobrycon eques and Jupiaba acanthogaster using marginal vegetation; F. Characidium zebra using the sit-and-wait tactics on the sandy substrate; G. Psalidodon marionae foraging near the rocky substrate; H. Salminus brasiliensis swimming in the water column; I. Prochilodus lineatus foraging near patches of vegetation. Photos: Renato M. Romero and Fabrício B. Teresa.

FIGURE 4 in Fish functional trophic groups in headwater karst streams from the Upper Paraguay River basin

FIGURE 4 | Compilation of number of families on each Functional Trophic Group among different biomes in Brazil. Bar colors represent the shared FTGs among biomes considering Sazima (1986), Sabino, Zuanon (1998), Casatti et al. (2001), Brejão et al. (2013), Freitas et al. (2021), and this work. Blue bar: FTGs registered in Pantanal+Amazon+Atlantic Forest; Red bar: FTGs registered in Pantanal+Amazon; Green bar: FTG registered only in Amazon. Silhouettes represent the families with more records on each FTG.

FIGURE 1 in Fish functional trophic groups in headwater karst streams from the Upper Paraguay River basin

FIGURE 1 | Main drainages of Serra da Bodoquena. The Miranda River watershed (blue) and the Perdido River watershed (red). Highlighted lines represent Salobra River in the North and Perdido River in the South. In green, the Formoso River watershed, a tributary of Miranda drainage. Black dots represent the points of underwater observations of the fish species.

FIGURE 2 in Fish functional trophic groups in headwater karst streams from the Upper Paraguay River basin

FIGURE 2 | Distribution of sizes classes of fish from Serra da Bodoquena stream according to instream horizontal occupation.

FIGURE 5 in Fish functional trophic groups in headwater karst streams from the Upper Paraguay River basin

FIGURE 5 | Number of accumulated Functional Trophic Groups by fish families considering Brazilian inland freshwaters works from Sazima (1986), Sabino, Zuanon (1998), Casatti et al. (2001), Brejão et al. (2013), Freitas et al. (2021), and this work.

FIGURE 1 in Body size responses to land use in stream fish: the importance of different metrics and functional groups

FIGURE 1 | Description of the four body size metrics used to investigate body size patterns in overall stream fish communities and in distinct functional groups. A. Skewness describes the tendency of value distribution being biased towards the right (negative-skewed) or left (positive-skewed). B. Kurtosis describes if the distribution of values is more flatted (platykurtic) or biased towards the center (narrow). Mean values can be the same for distinct kurtosis. Coefficient of variation (CV) describes the variation in values standardized to the mean.

FIGURE 3 in Body size responses to land use in stream fish: the importance of different metrics and functional groups

FIGURE 3 | Clusters of fish species based on ecomorphological and trophic traits, resulting in 11 functional groups (FG). Full species names by FG are available in S2.