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26 results for “interspecific diversity”
Spineless and overlooked: DNA metabarcoding of autonomous reef monitoring structures reveals intra- and interspecific genetic diversity in Mediterranean invertebrates
<p>Sequence data and stepwise pipeline outputs associated with the article "Spineless and overlooked: DNA metabarcoding of autonomous reef monitoring structures reveals intra- and interspecific genetic diversity in Mediterranean invertebrates".</p> <p>Preprint available here: <a href="https://doi.org/10.22541/au.167085544.47638352/v1">10.22541/au.167085544.47638352/v1</a></p> <p>Sequence data is deposited in fastq-format in folders by region (Palinuro.tar.gz, Livorno.tar.gz, and Rovinj.tar.gz) and a separate folder for controls (Controls.tar.gz). Each fastq-file contains sequences for a single PCR replicate named by sample and replicate number. Sample names are described in spineless_sample_names.csv. Positive control sequences are described in SM1_positive_controls.csv. Stepwise pipeline outputs are available in the folder Pipeline_outputs_stepwise.zip</p> <p>Scripts used to generate pipeline outputs as well as other aspects of the final article are available at <a href="https://github.com/thomasdotter/spineless-haplotypes">https://github.com/thomasdotter/spineless-haplotypes</a>.</p> <p> </p>
Elevation differently shapes functional diversity patterns in understory forest communities when considering intraspecific and interspecific trait variability
<p>Datasets used for the analysis done for the paper "Elevation differently shapes functional diversity patterns in understory forest communities when considering intraspecific and interspecific trait variability".</p> <p>Files present are:</p> <p>-Species x Plot (vegetation releveés).</p> <p>-Plot x Environment.</p> <p>-Plot x CWM_inter for Plant height, Leaf area, Specific Leaf Area (SLA), Leaf Dry Matter Content (LDMC) using the traits fixed for species, i.e., holding traits constant as the species mean, thus incorporating only turnover.</p> <p>-Plot x CWM_intra for Plant height, Leaf area, Specific Leaf Area (SLA), Leaf Dry Matter Content (LDMC) based on an individual by trait matrix, therefore incorporating both turnover and intraspecific trait variation.</p> <p>-Plot x SES-FD_inter (Standard Effect Size Functional Diversity) for Plant height, Leaf area, Specific Leaf Area (SLA), Leaf Dry Matter Content (LDMC) using the traits fixed for species, i.e., holding traits constant as the species mean, thus incorporating only turnover.</p> <p>-Plot x SES-FD_intra (Standard Effect Size Functional Diversity) for Plant height, Leaf area, Specific Leaf Area (SLA), Leaf Dry Matter Content (LDMC) based on an individual by trait matrix, therefore incorporating both turnover and intraspecific trait variation.</p> <p>All analysis were carried out using the software R version 4.1.2 (R Foundation for Statistical Computing, Vienna, Austria, <a href="http://www.R-project.org">http://www.R-project.org</a>) and can be consulted on GitHub https://github.com/AriannaFerrara/Elevation-and-Intraspecific-trait-variability.git</p>
Intra and interspecific diversity in a tropical plant clade alter herbivory and ecosystem resilience
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Interspecific soil water partitioning as a driver of increased productivity in a diverse mixed Mediterranean forest
<p><strong>Interspecific soil water partitioning as a driver of increased productivity in a diverse mixed Mediterranean forest</strong></p> <p>Ido Rog<sup>1</sup>, Christina Tague<sup>2</sup>, Gilad Jakoby<sup>1</sup>, Shacham Megidish<sup>1</sup>, Assaf Yaakobi<sup>1</sup>, Yael Wagner<sup>1</sup>, Tamir Klein<sup>1</sup></p> <ol> <li>Plant & Environmental Sciences department, Weizmann Institute of Science, Rehovot, Israel</li> <li>Bren School of Environmental Science & Management, University of California Santa Barbara, California, USA</li> </ol> <p> </p> <p>Empiric data from Yishi forest (31º 43´N 34º 57´E, 320 m elevation) and RHESSys simulation. </p>
Data from: Quantifying interspecific and intraspecific diversity effects on ecosystem functioning
<p>Rapid environmental changes result in massive biodiversity loss with detrimental consequences for the functioning of ecosystems. Recent studies suggest that intraspecific diversity can contribute to ecosystem functioning to an extent comparable to contributions of interspecific diversity. Knowledge of the relative importance of these two sources of biodiversity is essential for predicting ecosystem consequences of biodiversity loss and will aid prioritization of conservation targets and implementation of management measures. However, our quantitative insights into how interspecific and intraspecific biodiversity loss affects ecosystem functioning, and how the effects of these two sources of biodiversity loss on ecosystem functioning can be compared are still very limited. To facilitate this goal, we extend the interspecific Price partitioning method originally introduced by J. Fox in 2006, previously used to quantify species loss and gain effects on ecosystem functioning, to also account for the effects of intraspecific diversity loss and gain on ecosystem function. Using this extended version can provide the quantitative information required for answering research questions addressing correlations between interspecific and intraspecific diversity effects on ecosystem function, identifying interspecific and intraspecific groups with large effects, and assessing whether intraspecific diversity can compensate for losses in interspecific diversity. Applying this method to carefully designed experiments will provide additional insights into how biodiversity loss at different ecological levels contributes to and changes ecosystem functioning.</p>
The roles of isolation and interspecific interaction in generating the functional diversity of an insular mammal radiation
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Data from: Quantifying interspecific and intraspecific diversity effects on ecosystem functioning
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Data from: Preserving wild pears: Using genomic data to assess species boundaries, interspecific hybridization, and genetic diversity to inform conservation
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Interspecific hybridization and island colonization history, not rarity, most strongly affect the genetic diversity in a clade of Mascarene-endemic trees
<p>Many factors shape the genetic diversity of island-endemic trees, with important implications for conservation. Oceanic island-endemic lineages undergo an initial founding bottleneck during the colonization process and subsequently accumulate diversity following colonization. Moreover, many island endemics occur in small populations and are further threatened by anthropogenic factors that cause population declines, making them susceptible to losses in genetic diversity through genetic drift, inbreeding, and bottlenecks. <a name="_Hlk80963234"></a>However, life-history traits commonly found in trees, such as outcrossing mechanisms, long lifespans, and a propensity for interspecific hybridization, may help buffer against losses of genetic variation. To assess the relative importance of colonization history, rarity, and distribution in shaping genetic diversity of island-endemic trees, we conducted a<a name="_Hlk80964566"></a> comparative population genomic analysis of 13 species of <em>Diospyros</em> (Ebenaceae) endemic to the Mascarene Islands that differ in island colonization history, distribution, population size, and IUCN threat status. We genotyped 328 individuals across the islands using 2b-RADseq, compared genetic diversity both among and within species, and assessed patterns of genetic structure. <a name="_Hlk80965008"></a>Genetic diversity did not vary significantly by IUCN status, but we found that species that co-occur with others on the same intermediate-aged island (Mauritius) had much greater genetic diversity than those that occur solitarily on an island (Réunion and Rodrigues), likely because of greater interspecific hybridization among species with overlapping distributions and processes related to time since island colonization. Results presented here were used to <a name="_Hlk80991503"></a>determine priority localities for <em>in situ</em> and <em>ex situ</em> conservation efforts to maximize the genetic diversity of each Mascarene <em>Diospyros</em> species.</p>
Novel sex-specific genes and diverse interspecific expression in the antennal transcriptomes of ithomiine butterflies"
<p>The following repository contains both the genomic and functional annotations for 4 Ithomiini species. Data that was used in GBE paper "Novel sex-specific genes and diverse interspecific expression in the antennal transcriptomes of ithomiine butterflies".</p>
FIGURE 7 in Plastome data provide insights into intra and interspecific diversity and ndh gene loss in Capparis (Capparaceae)
FIGURE 7. MultiPip analysis showing overall sequence similarity of plastid genomes based on complete plastome alignment using Capparis spinosa var. spinosa as a reference sequence. Levels of sequence similarity are indicated by red (75±100%), green (50±75%), and white (<50%). Arrows indicate gene losses.
FIGURE 6 in Plastome data provide insights into intra and interspecific diversity and ndh gene loss in Capparis (Capparaceae)
FIGURE 6. Nucleotide diversity and hotspot regions in genus Capparis. The X-axis represents the nucleotide position and Y-axis represents nucleotide diversity (Pi). 6a. Interspecific variation among four taxa of Capparis. 6b. Intraspecific variation among two varieties of Capparis spinosa viz. var. spinosa and var. herbacea.
FIGURE 2 in Plastome data provide insights into intra and interspecific diversity and ndh gene loss in Capparis (Capparaceae)
FIGURE 2. Plastome maps of Capparis spinosa var. spinosa and Capparis spinosa var. herbacea. Genes shown outside the circles are transcribed clockwise and those inside are transcribed anticlockwise. Genes belonging to different functional groups are in various colours. The dashed area in inner circles indicates the GC content of plastome. ORF – Open reading frame. Asterisks indicate genes containing introns.
FIGURE 5 in Plastome data provide insights into intra and interspecific diversity and ndh gene loss in Capparis (Capparaceae)
FIGURE 5. Comparison of SSRs in four Capparis taxa viz. C. spinosa var. herbacea, var. spinosa, C. versicolor and C. urophylla. 5a. Types of SSRs; 5b. Size of SSRs; 5c. Number of SSR repeats in LSC, SSC and IRs. Numbers above each bar represents the number of repeats.
FIGURE 4 in Plastome data provide insights into intra and interspecific diversity and ndh gene loss in Capparis (Capparaceae)
FIGURE 4. Codon usage of four taxa of Capparis viz. Capparis spinosa var. spinosa, var. herbacea, C. versicolor and C. urophylla. Xaxis: Amino acid, Y- axis: codon usage in percentage. * indicates stop codon.
FIGURE 1 in Plastome data provide insights into intra and interspecific diversity and ndh gene loss in Capparis (Capparaceae)
FIGURE 1. Map depicting distribution and altitudinal ranges of seven varieties of Capparis spinosa. (as per Jacobs 1965, Fici 2014, and POWO 2019).
FIGURE 3 in Plastome data provide insights into intra and interspecific diversity and ndh gene loss in Capparis (Capparaceae)
FIGURE 3. Comparison of LSC, SSC and IR borders of Capparaceae with members of Cleomaceae (Tarenaya hassleriana) and Brassicaceae (Aethionema arabicum). Numbers in boxes indicate total length of the particular region; numbers below the arrows show base pair shift or overlapping regions. Gene and IR lengths are not to scale.
FIG UR E 3 (a) Dated phylogeny of the genus Theodoxus constructed in BEAST based on COI, 16S and ATPα. Node labels denote divergence times in millions of years ago (Ma); node bars indicate the 95% credibility interval around these dates. Small squares at nodes indicate significant support of divergence events found with BEAST and other phylogenetic analyses (see Figures S2.1 and S2.2), as explained through the key. Where MOTUs (A–R) show conspecifics among a number of morphospecies, species names are given in order of their year of description. Morphospecies, incorporated from GenBank, where determination was potentially dubious are highlighted by an asterisk. Clades (C) and subclades (SC) are demarcated by dashed lines between MOTUs. (b) LTT plots indicating the build‐up of lineages in Theodoxus over geological time. Dashed lines surrounding the solid LTT lines indicate the 95% confidence intervals. Where intra‐ and interspecific diversity diverge, interspecific diversity is highlighted in blue and intraspecific diversity in red. Transitions in geological ages are highlighted by narrow grey lines, while the grey bar marks the period of pronounced glacial cycles (last 900 kyr) [Colour figure can be viewed at wileyonlinelibrary.com] in Contributions of biogeographical functions to species accumulation may change over time in refugial regions
FIG UR E 3 (a) Dated phylogeny of the genus Theodoxus constructed in BEAST based on COI, 16S and ATPα. Node labels denote divergence times in millions of years ago (Ma); node bars indicate the 95% credibility interval around these dates. Small squares at nodes indicate significant support of divergence events found with BEAST and other phylogenetic analyses (see Figures S2.1 and S2.2), as explained through the key. Where MOTUs (A–R) show conspecifics among a number of morphospecies, species names are given in order of their year of description. Morphospecies, incorporated from GenBank, where determination was potentially dubious are highlighted by an asterisk. Clades (C) and subclades (SC) are demarcated by dashed lines between MOTUs. (b) LTT plots indicating the build‐up of lineages in Theodoxus over geological time. Dashed lines surrounding the solid LTT lines indicate the 95% confidence intervals. Where intra‐ and interspecific diversity diverge, interspecific diversity is highlighted in blue and intraspecific diversity in red. Transitions in geological ages are highlighted by narrow grey lines, while the grey bar marks the period of pronounced glacial cycles (last 900 kyr) [Colour figure can be viewed at wileyonlinelibrary.com]
Interspecific hybridization and island colonization history, not rarity, most strongly affect the genetic diversity in a clade of Mascarene-endemic trees
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Data from: Exploitation of interspecific diversity for monocot crop improvement
In many cultivated crop species there is limited genetic variation available for the development of new higher yielding varieties adapted to climate change and sustainable farming practises. The distant relatives of crop species provide a vast and largely untapped reservoir of genetic variation for a wide range of agronomically important traits that can be exploited by breeders for crop improvement. In this paper, in what we believe to be the largest introgression programme undertaken in the monocots, we describe the transfer of the entire genome of Festuca pratensis into Lolium perenne in overlapping chromosome segments. The L. perenne/F. pratensis introgressions were identified and characterised via 131 simple sequence repeats and 1612 SNPs anchored to the rice genome. Comparative analyses were undertaken to determine the syntenic relationship between L. perenne/F. pratensis and rice, wheat, barley, sorghum and Brachypodium distachyon. Analyses comparing recombination frequency and gene distribution indicated that a large proportion of the genes within the genome are located in the proximal regions of chromosomes which undergo low/very low frequencies of recombination. Thus, it is proposed that past breeding efforts to produce improved varieties have centred on the subset of genes located in the distal regions of chromosomes where recombination is highest. The use of alien introgression for crop improvement is important for meeting the challenges of global food supply and the monocots such as the forage grasses and cereals, together with recent technological advances in molecular biology, can help meet these challenges.
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Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.