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Fig. 5 in Efficiency and selectivity of a trap and truck fish passage system in Brazil

Fig. 5. Relative abundance of migratory species per size class for the lower Mucuri River, in the Santa Clara tailrace (2002/ 2003) and in the Santa Clara Dam fish lift (2003/2004).

Fig. 4 in Efficiency and selectivity of a trap and truck fish passage system in Brazil

Fig. 4. Relative abundance of target species in the lower Mucuri River, in the Santa Clara tailrace (2002/2003) and in the Santa Clara Dam fish lift (2003/2004).

Fig. 6 in Efficiency and selectivity of a trap and truck fish passage system in Brazil

Fig. 6. Number of injured or dead fish after being passed by the fish lift according to species groups.

Fig. 2 in Efficiency and selectivity of a trap and truck fish passage system in Brazil

Fig. 2. Abundance (%) of captured species in the Santa Clara tailrace (2002/2003) and passed by the fish lift (2003/2004).

Fig. 4 in Selectivity of fish ladders: a bottleneck in Neotropical fish movement

Fig. 4. Monthly mean water levels downriver (line) and the number of hours with elevations less than 175.1 m (columns) (a), the number and abundance of fish species in samples downstream from the dam (b and d) and from the fish ladder (c and e) of Lajeado Dam.

Fig. 3 in Selectivity of fish ladders: a bottleneck in Neotropical fish movement

Fig. 3. Monthly occurrence (a) and catch per unit effort (CPUE; individuals per 100 casts) (b) of the four most abundant species in the fish ladder at Lajeado Dam (arrow indicates upward movement).

opencc-by-4.0Apr 2021View details →

FIG. 27. Astrapotherium magnum, selected basicranial features. A in Cranial Morphology And Phylogenetic Relationships Of Trigonostylops Wortmani, An Eocene South American Native Ungulate

FIG. 27. Astrapotherium magnum, selected basicranial features. A, AMNH VP-9278, right basicranium in ventral aspect. Prominent impression labelled "?vasc sulc" may have conducted extracranial venous structures similar to basicranial plexuses seen in extant Equus (fig. 6; see also similarly positioned sulcus in Tapirus, fig. 38: feature 5). Basicapsular fenestra is hidden in this perspective, except for extreme rostral and caudal ends. B, Digitally reconstructed left petrosal of A . magnum MACN A 3208, reversed and rotated to permit com-

opencc-by-4.0Feb 2014View details →

FIGURES 32–36 in Nest Site Selection and Nesting Behavior of the Bee Lithurgopsis apicalis (Megachilidae: Lithurginae)

FIGURES 32–36. Larvae of Lithurgopsis apicalis. 32. Cast head capsules of second and third instars attached to venter of fourth instar. 33. Early defecating fifth instar, showing slender body shape. 34. Intermediate-aged fifth instar demonstrating more tapered body shape. 35. Spinning fifth instar with fibrous cushion of feces and pollen intermeshed with silk. 36. Silken network that has been partly covered by thin film of clear silk (identified by arrow).

Data from: Opposing effects of competition and selection on macroevolutionary dynamics

The diversity of species and traits is the outcome of multiple evolutionary processes operating over millions of years. These processes affect rates of trait evolution, speciation, and extinction. A key problem is identifying the relative importance of distinct processes in driving observed patterns in species traits and phylogenetic trees. Here, we show how two processes, competition and stabilising selection, can act opposingly but still leave identifiable traces in macroevolutionary data. Building on previous simulation studies, we model the joint influence of competition and stabilising selection on rates of trait evolution, speciation completion, and extinction. We find that opposing effects result in nuanced patterns of trait evolution and diversification dynamics that, when considered in isolation, could easily lead to misinterpretation. In particular, while the best fitting likelihood model of trait evolution is typically Brownian motion when competition and stabilising selection act simultaneously, we find stronger phylogenetic signal than expected under BM and trait distributions that are distinctly platykurtic. Taken together, we suggest that by considering multiple simple metrics measuring trait evolution and diversification dynamics it may be possible, though challenging, to identify the relative contribution of these two processes operating together in macroevolutionary data.

opencc-by-4.0Sep 2021View details →

Introduction to Critical Thinking and Source Selection

An introduction to the process of critical thinking and its importance when undertaking academic research.

Data for Integrated Step Selection Analysis of translocated female greater sage-grouse in the 60 days post-release, North Dakota 2018-2020

The data include used and random available steps at 11-hour resolution generated for 26 female greater sage-grouse in the 60 days post-translocation to North Dakota, with associated environmental predictors and individual information. The code fits individual habitat selection models in an Integrated Step Selection Analysis framework. Data used to fit the models described in: Picardi, S., Ranc, N., Smith, B.J., Coates, P.S., Mathews, S.R., Dahlgren, D.K. Individual variation in temporal dynamics of post-release habitat selection. Frontiers in Conservation Science (in review) Code used to implement the analysis is available on GitHub: https://github.com/picardis/picardi-et-al_2021_sage-grouse_frontiers-in-conservation

Data from: Floral scents of a deceptive plant are hyperdiverse and under population-specific phenotypic selection

Floral scent is a key mediator in plant–pollinator interactions; however, little is known to what extent intraspecific scent variation is shaped by phenotypic selection, with no information yet in deceptive plants. We recorded 289 scent compounds in deceptive moth fly-pollinated Arum maculatum from various populations north vs. south of the Alps, the highest number so far reported in a single plant species. Scent and fruit set differed between regions, and some, but not all differences in scent could be explained by differential phenotypic selection in northern vs. southern populations. Our study is the first to provide evidence that phenotypic selection is involved in shaping geographic patterns of floral scent in deceptive plants. The hyperdiverse scent of A. maculatum might result from the plant's imitation of various brood substrates of its pollinators.

How to achieve a higher selection plateau in forest tree breeding? Fostering heterozygote x homozygote relationships in optimal contribution selection in the case study of Populus nigra

In breeding, Optimal Contribution Selection (OCS) is one of the most effective strategies to balance short- and long-term genetic responses, by maximizing genetic gain and minimizing global coancestry. Considering genetic diversity in the selection dynamic – through coancestry – is undoubtedly the reason for the success of OCS, as it avoids intial loss of favorable alleles. Originally formulated with the pedigree relationship matrix, global coancestry can nowadays be assessed with one of the possible formulations of the realized genomic relationship matrix. Most formulations were optimized for genomic evaluation, but few for the management of coancestry. We introduce here an alternative formulation specifically developed for Genomic OCS (GOCS), intended to better control heterozygous loci, and thus better account for Mendelian sampling. We simulated a multi-generation breeding program with mate allocation and under GOCS for twenty generations, solved with quadratic programming. With the case study of Populus nigra, we have shown that, although the dynamic was mainly determined by the trade-off between genetic gain and genetic diversity, better formulations of the genomic relationship matrix, especially those fostering individuals carrying multiple heterozygous loci, can lead to better short-term genetic gain and a higher selection plateau.

opencc-zeroOct 2021View details →

Data from: Selection on growth rate and local adaptation drive genomic adaptation during experimental range expansions in the protist Tetrahymena thermophila

1. Populations that expand their range can undergo rapid evolutionary adaptation of life-history traits, dispersal behaviour, and adaptation to the local environment. Such adaptation may be aided or hindered by sexual reproduction, depending on the context. 2. However, few empirical and experimental studies have investigated the genetic basis of adaptive evolution during range expansions. Even less attention has been given to the question how sexual reproduction may modulate such adaptive evolution during range expansions. 3. We here studied genomic adaptation during experimental range expansions of the protist Tetrahymena thermophilain landscapes with a uniform environment or a pH-gradient. Specifically, we investigated two aspects of genomic adaptation during range expansion. Firstly, we investigated adaptive genetic change in terms of the underlying numbers of allele frequency changes from standing genetic variation and de novo variants. We focused on how sexual reproduction may alter this adaptive genetic change. Secondly, we identified genes subject to selection caused by the expanding range itself, and directional selection due to the presence or absence of the pH-gradient. We focused this analysis on alleles with large frequency changes that occurred in parallel in more than one population to identify the most likely candidate targets of selection. 4. We found that sexual reproduction altered adaptive genetic change both in terms of de novo variants and standing genetic variation. However, sexual reproduction affected allele frequency changes in standing genetic variation only in the absence of long-distance gene flow. Adaptation to the range expansion affected genes involved in cell divisions and DNA repair, whereas adaptation to the pH-gradient additionally affected genes involved in ion balance, and oxidoreductase reactions. These genetic changes may result from selection on growth and adaptation to low pH. 5. In the absence of gene flow, sexual reproduction may have aided genetic adaptation. Gene flow may have swamped expanding populations with maladapted alleles, thus reducing the extent of evolutionary adaptation during range expansion. Sexual reproduction also altered the genetic basis of adaptation in our evolving populations via de novo variants, possibly by purging deleterious mutations or by revealing fitness benefits of rare genetic variants.

opencc-by-4.0Oct 2021View details →

Populations of local direction-selective cells encode global motion patterns generated by self-motion. Data, Code and Model.

Directional tuning of the population of local motion detectors T4/T5 in the visual system of the fruit fly Drosophila melanogaster. Direction tuning and receptive field location was measured by recording responses to visual stimuli containing dark or bright edges/stripes moving into 8 directions. All provided MATLAB scripts were used to analyze and illustrate data show in the manuscript 'Populations of local direction-selective cells encode global motion patterns generated by self-motion.' All data were obtained using in vivo two photon microscopy. Image time series were preprocessed using SIMA python software for motion alignment and further processed using custom written matlab or python code. Please find all relevant information to use the code in the README file.

opencc-by-4.0Oct 2021View details →

Supplementary Data for "Convergent evolution as an indicator for selection during acute HIV-1 infection"

Supplementary Data 1. Position of all identified mutations in the env gene. This file contains detailed information about the identity of the observed mutations. It provides the position in the HXB2 genome, the amino acid change they cause in the different genetic backgrounds and the number of HIV-1 subtypes (out of a total of 170) the mutations occurs in. Supplementary Data 2. Position of all identified mutations in the rev exon part of the env gene. Same as Supplementary Data 1, except that only mutations and amino acid substitutions in the rev exon 2 are shown. Supplementary Program. With this program one can redo the analyses and simulations of the manuscript.

opencc-by-4.0Jul 2024View details →

Gene and repeat annotation for snowy owl (Bubo scandiacus) and selected species

Here we provide the gene and repeat annotation for snowy owl (Bubo scandiacus), in addition to gene and repeat annotation done for some species this was compared to. It is unfortunately currently not possible to upload repeat annotation tracks to an international nucleotide sequence database such as ENA. While uploading the gene annotation is possible, some of the cross references to different databases in the functional annotation are removed. Further, the names of the entries in the publicly available genome assemblies on ENA have different names than what is found in the annotation tracks here, so we also provide the FASTA files for the snowy owl assemblies (bBubSca1.1.hap1.fasta.gz and bBubSca1.1.hap2.fasta.gz). Ideally, all this should have been available via ENA. We annotated the snowy owl genome assemblies, in addition to downy woodpecker (Dryobates pubescens; <a href="https://www.ncbi.nlm.nih.gov/assembly/GCA_014839835.1">GCA_014839835.1</a>), Northern Carmine bee-eater (Merops nubicus; <a href="https://www.ncbi.nlm.nih.gov/assembly/GCA_009819595.1">GCA_009819595.1</a>), Northern goshawk (Accipiter gentilis; <a href="https://www.ncbi.nlm.nih.gov/assembly/GCA_929443795.2">GCA_929443795.2</a>) and barn owl (Tyto alba; <a href="https://www.ncbi.nlm.nih.gov/assembly/GCF_018691265.1#/st">GCF_018691265.1</a>), since no genome annotation was publicly available for these species. We used a pre-release version of the EBP-Nor genome annotation pipeline (<a href="https://github.com/ebp-nor/GenomeAnnotation">https://github.com/ebp-nor/GenomeAnnotation</a>). First, AGAT (https://zenodo.org/record/7255559) agat_sp_keep_longest_isoform.pl and agat_sp_extract_sequences.pl were used on the GRCg7b (GCA_016699485.1) chicken genome assembly and annotation to generate one protein (the longest isoform) per gene. Miniprot (Li, 2023) was used to align the proteins to the curated assemblies. UniProtKB/Swiss-Prot (Consortium et al., 2022) release 2022_03 in addition to the vertebrata part of OrthoDB v11 (Kuznetsov et al., 2022) were also aligned separately to the assemblies. Red (Girgis, 2015) was run via redmask (<a href="https://github.com/nextgenusfs/redmask">https://github.com/nextgenusfs/redmask</a>) on the snowy owl assemblies to mask repetitive areas (we used the soft-masked genome assemblies available at NCBI for the other species). GALBA (Brůna et al., 2023; Buchfink et al., 2015; Hoff and Stanke, 2018; Li, 2023; Stanke et al., 2006) was run with the chicken proteins using the miniprot mode on the masked assemblies. The funannotate-runEVM.py script from Funannotate was used to run EvidenceModeler (Haas et al., 2008) on the alignments of chicken proteins, UniProtKB/Swiss-Prot proteins, vertebrata proteins and the predicted genes from GALBA. The resulting predicted proteins were compared to the protein repeats that Funannotate distributes using DIAMOND blastp  and the predicted genes were filtered based on this comparison using AGAT. The filtered proteins were compared to the UniProtKB/Swiss-Prot release 2022_03 using DIAMOND (Buchfink et al., 2015) blastp to find gene names and InterProScan was used to discover functional domains. AGATs agat_sp_manage_functional_annotation.pl was used to attach the gene names and functional annotations to the predicted genes. EMBLmyGFF3 (Norling et al., 2018) was used to combine the fasta files and GFF3 files into a EMBL format for submission to ENA. These files end in gff.gz (the ones ending in fa.out.gff.gz are repeat annotations), proteins.fa.gz and mrna.fa.gz.  All species in this study downy woodpecker (Dryobates pubescens; <a href="https://www.ncbi.nlm.nih.gov/assembly/GCA_014839835.1">GCA_014839835.1</a>), Northern Carmine bee-eater (Merops nubicus; <a href="https://www.ncbi.nlm.nih.gov/assembly/GCA_009819595.1">GCA_009819595.1</a>), Northern goshawk (Accipiter gentilis; <a href="https://www.ncbi.nlm.nih.gov/assembly/GCA_929443795.2">GCA_929443795.2</a>), barn owl (Tyto alba; <a href="https://www.ncbi.nlm.nih.gov/assembly/GCF_018691265.1#/st">GCF_018691265.1</a>), chicken (Gallus gallus; <a href="https://www.ncbi.nlm.nih.gov/assembly/GCF_016699485.2/">GCF_016699485.2</a>), zebra finch (Taeniopygia guttata; <a href="https://www.ncbi.nlm.nih.gov/assembly/GCA_003957565.4">GCA_003957565.4</a>) and California condor (Gymnogyps californianus; <a href="https://www.ncbi.nlm.nih.gov/assembly/GCF_018139145.2">GCF_018139145.2</a>) in addition to hap1 of snowy owl was repeat masked with a bird-specific library from <a href="https://www.pnas.org/doi/abs/10.1073/pnas.1616702114">https://www.pnas.org/doi/abs/10.1073/pnas.1616702114</a>, provided by Alexander Suh. These files are named such as MerNubi.fa.out.gff.gz, MerNubi.fa.masked.gz and MerNubi.fna.cat.gz.  We have also included the species specific repeat library as generated by RepeatModeler running on hap1 of snowy owl. This is called bBubSca1.1.hap1.repeatlibrary.fa.gz, with the files bBubSca1.1.hap1.fasta.masked.gz, bBubSca1.1.hap1.fasta.out.gff.gz, bBubSca1.1.hap1.divsum.gz and bBubSca1.1.hap1.fasta.cat.gz resulting from running RepeatMasker one hap1 using that library. From the Genespace analyses we have included all files including OrthoFinder results. This is found in the file genespace.tgz.

opencc-by-4.0Nov 2018View details →

Selection function for spectroscopic surveys (main set).

Selection function values for large spectroscopic surveys. Supplementary material for A&A paper Minst&Hekker 2018 (https://ui.adsabs.harvard.edu/#abs/2018arXiv181012296M/abstract). Main set (all stars in each survey)

opencc-by-4.0May 2019View details →

Data and code for: Roost selection by male northern long-eared bats (Myotis septentrionalis) in a managed fire-adapted forest

Data and code for: Roost selection by male northern long-eared bats (Myotis septentrionalis) in a managed fire-adapted forest