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1,052 results for “Structural diversity”
FIGURE 1 in Species diversity and community structure of fruit-feeding butterflies (Lepidoptera: Nymphalidae) in an eastern amazonian forest
FIGURE 1: Location of Sítio Aguahy, in the eastern Amazon. (A) Maps of Brazil and the state of Maranhão, demonstrating the distribution of the Brazilian Amazon forest. (B) Dense rainforest (C) Secondary forest.
Tree size, microhabitat diversity and landscape structure determine the value of isolated trees for bats in farmland
<p>Isolated trees are increasingly recognised as playing a vital role in supporting biodiversity in agricultural landscapes, yet their occurrence has declined substantially in recent decades. Most bats in Europe are tree-dependent species that rely on woody elements in order to persist in farmlands. However, isolated trees are rarely considered in conservation programs and landscape planning. Further investigations are therefore urgently required to identify which trees – based on both their intrinsic characteristics and their location in the landscape – are particularly important for bats. We acoustically surveyed 57 isolated trees for bats to determine the relative and interactive effects of size, tree-related microhabitat (TreM) diversity and surrounding landscape context on bat activity. Tall trees with large diameter at breast height and crown area positively influenced the activity of <em>Pipistrellus pipistrellus</em> and small Myotis bats (<em>Myotis</em> spp.) while smaller and thinner trees favoured <em>M. myotis</em> activity. The diversity of TreMs that can be used as roosts had a positive effect on (i) <em>Barbastella barbastellus</em> activity only when trees were relatively close (10% within 100 radius scale). The potential benefits of isolated trees for bats result from ecological mechanisms operating at both tree and landscape scales, underlining the crucial need for implementing a multi-scale approach in conservation programs. Maintaining the largest and most TreM-diversified trees located in the most heterogeneous agricultural landscapes will provide the greatest benefits.</p>
Data from: Chrysolaena obovata, A SPECIES NATIVE OF BRAZILIAN CERRADO: GENETIC DIVERSITY AND STRUCTURE OF NATURAL POPULATIONS AND POTENTIAL FOR INULIN PRODUCTION
<p><em>Chrysolaena obovata</em> (Less.) M. Dematteis, an herbaceous Asteraceae species widely distributed across different Brazilian Cerrado physiognomies, has underground organs, named rhizophores, that accumulate high concentrations of inulin-type fructans. These carbohydrates are recognized as beneficial soluble fibers for human health and are currently used in the food and pharmaceutical industries. Considering that fructans, in addition to their economic potential, provide plants with greater tolerance to drought, heat and cold, it is important to understand whether their metabolism is conserved in natural populations. In this work, we aimed to investigate if the levels of genetic diversity in the populations studied allow the selection of localities with a high genetic base and higher fructan content for future programs of <em>in</em> <em>situ</em> conservation and genetic improvement for inulin production. Therefore, we characterized the diversity, structure, and gene flow of seven natural populations from Brazilian Cerrado, using nine microsatellite loci (SSR). In addition, we compared whether the fructan composition varied between populations of different Cerrado phytophysiognomies. Overall, we found that <em>C. obovata</em> populations exhibited moderate levels of genetic diversity, low genetic differentiation, and high gene flow. This study identified two populations with less genetic diversity and therefore, greater attention should be given to conservation programs including these populations. Fructan metabolism is conserved in all populations, indicating that <em>C. obovata</em> is an important genetic resource with high potential for inulin production.</p> <p><strong>File descriptions</strong></p> <p>Population_code.txt - Contains a matrix that indicates the population_code, Population_name, Brazilian-state, Phytophysiognomy, Collection coordinates and Altitudes (m).</p> <p>Date_ Diaz et al.xlsx – Contains Genotypes crude of the individuals analyzed. Primer used for nine microsatellite loci (Camacho <em>et al</em> 2017). </p> <p>Carbohydrates_Diaz et al - Contains data for carbohydrates in <em>C. obovata</em> plant rhizophores in each population (BRA, UB, SD, SP).</p> <p><strong>Location: Brazilian Cerrado</strong></p>
Local adaptation and archaic introgression shape global diversity at human structural variant loci
<p>Supporting data associated with the manuscript "Local adaptation and archaic introgression shape global diversity at human structural variant loci". These include:</p> <ul> <li>structural variant genotypes (Paragraph; <a href="https://github.com/Illumina/paragraph">https://github.com/Illumina/paragraph</a>)</li> <li>eQTL mapping results (fastqtl permutation pass; see <a href="http://fastqtl.sourceforge.net/">http://fastqtl.sourceforge.net/</a> for column descriptions)</li> <li>eQTL fine-mapping results (CAVIAR; see <a href="http://genetics.cs.ucla.edu/caviar/index.html">http://genetics.cs.ucla.edu/caviar/index.html</a>)</li> <li>structural variant selection scan results (Ohana; <a href="https://github.com/jade-cheng/ohana">https://github.com/jade-cheng/ohana</a>)</li> </ul> <p>Description of files in this directory:</p> <p><strong>Structural variant genotypes</strong></p> <p><code>SVs_paragraphFormat.vcf.gz</code> - merged long-read structural variant calls</p> <p><code>SVs_1KGP_pgGTs.vcf.gz</code> - genotypes for 1000 Genomes samples in VCF format</p> <p><strong>eQTL mapping results</strong></p> <p><code>fastqtl_out.txt</code> - results from fastQTL permutation pass; see <a href="http://fastqtl.sourceforge.net/">http://fastqtl.sourceforge.net/</a> for column descriptions</p> <p><code>caviar_out.txt</code> - results from fine-mapping SNPs and SVs at significant SV eQTL loci with CAVIAR. Description of columns:</p> <ul> <li>query_sv: SV that was a significant eQTL and underwent fine-mapping</li> <li>gene_id: gene exhibiting an expression association with the query_sv</li> <li>var_id: variant (SNV or SV) that was tested for expression association with the above gene in the fine-mapping analysis</li> <li>var_in_credible_causal_set: Boolean variable denoting whether the above variant is in the 95% credible causal set</li> <li>prob_in_pcausal_set: the amount that this variant contributes to 95% credible causal set</li> <li>causal_post_prob: the posterior probability that the variant is causal in the expression association</li> </ul> <p><strong>Structural variant selection scan results</strong></p> <p><code>chr21_pruned_50_Q.matrix</code> - admixture proportion matrix (generated by Ohana; <a href="https://github.com/jade-cheng/ohana">https://github.com/jade-cheng/ohana</a>)</p> <p><code>chr21_pruned_50_F.matrix</code> - matrix of inferred ancestral allele frequencies (generated by Ohana)</p> <p><code>chr21_pruned_50_C.matrix</code> - matrix of ancestry component covariances (generated by Ohana) Entries of the matrix can be modified to produce "selection hypothesis" matrices where allele frequencies are allowed to vary in one ancestry component (<a href="https://github.com/jade-cheng/ohana/wiki/Population-or-ancestry-specific-selection-scan">https://github.com/jade-cheng/ohana/wiki/Population-or-ancestry-specific-selection-scan</a>).</p> <p><code>selscan_50_k8_p*.txt.gz</code> - raw output of Ohana selscan (see <a href="https://github.com/jade-cheng/ohana">https://github.com/jade-cheng/ohana</a>)</p> <p><code>selscan_res.txt.gz</code> - Ohana selection scan results. These results have been filtered to exclude SVs that have low genotyping rates (<50% of samples), violate Hardy-Weinberg equilibrium expectations (excess of heterozygotes) in more than half of populations, or have extreme global log likelihood estimate (LLE) values. Description of columns:</p> <ul> <li>ID: SV ID</li> <li>#CHROM: SV chromosome</li> <li>POS: SV start position</li> <li>SVLEN: SV length (negative for deletions)</li> <li>step: number of steps needed to interpolate between genome-wide and selection hypothesis models</li> <li>lle_ratio: likelihood ratio statistic (LRS) of the genome-wide vs. selection hypothesis model</li> <li>global-lle: log likelihood of the genome-wide model</li> <li>local-lle: log likelihood of the selection hypothesis model</li> <li>f-pop0: inferred allele frequency in ancestry component 0</li> <li>f-pop1: inferred allele frequency in ancestry component 1</li> <li>f-pop2: inferred allele frequency in ancestry component 2</li> <li>f-pop3: inferred allele frequency in ancestry component 3</li> <li>f-pop4: inferred allele frequency in ancestry component 4</li> <li>f-pop5: inferred allele frequency in ancestry component 5</li> <li>f-pop6: inferred allele frequency in ancestry component 6</li> <li>f-pop7: inferred allele frequency in ancestry component 7</li> <li>ancestry_component: ancestry component tested by the selection hypothesis model. Note that we have added 1 to the ancestry component numbers to match the terminology used in paper (which orders the components from 1-8 rather than 0-7 for interpretability)</li> <li>snp_perc: SV's percentile in the LRS distribution for frequency-matched SNPs</li> <li>p_nominal: nominal p-value calculated from the likelihood ratio</li> <li>p_adj: adjusted p-value calculated from the likelihood ratio</li> </ul> <p> </p>
Fig. 3 in Diversity And Structure Of Nesting Birds In The Coastal Riparian Zones Of Great Kabylia In Algeria
Fig. 3. Principal Components Analysis (PCA) Showing the Avifauna Organization According to the Study Sites and the Environmental Variables.
Genetic structure in patchy populations of a candidate foundation plant: a case study of Leymus chinensis using genetic and clonal diversity
<p><strong>PREMISE</strong>: The distribution of genetic diversity on the landscape has critical ecological and evolutionary implications. This may be especially the case on a local scale for foundation plant species since they create and define ecological communities, contributing disproportionately to ecosystem function.</p> <p><strong>METHODS</strong>: We examined the distribution of genetic diversity and clones, which we defined first as unique multilocus genotypes (MLG), and then by grouping similar MLGs into multilocus lineages (MLL). We used 186 markers from inter-simple sequence repeats (ISSR) across 358 ramets from 13 patches of the foundation grass <em>Leymus chinensis</em>. We examined the relationship between genetic and clonal diversities, their variation with patch-size, and the effect of the number of markers used to evaluate genetic diversity and structure in this species.</p> <p><strong>RESULTS</strong>: Every ramet had a unique MLG. Almost all patches consisted of individuals belonging to a single MLL. We confirmed this with a clustering algorithm to group related genotypes. The predominance of a single lineage within each patch could be the result of the accumulation of somatic mutations, limited dispersal, some sexual reproduction with partners mainly restricted to the same patch, or a combination of all three.</p> <p><strong>CONCLUSIONS</strong>: We found strong genetic structure among patches of <em>L. chinensis</em>. Consistent with previous work on the species, the clustering of similar genotypes within patches suggests that clonal reproduction combined with somatic mutation, limited dispersal, and some degree of sexual reproduction among neighbors causes individuals within a patch to be more closely related than among patches.</p>
Fig. 2 in Genetic Diversity And Place In The General Phylogeographic Structure Of Capercaillie,Tetrao Urogallus (Galliformes, Phasianidae), From Belarus
Fig. 2. Reconstruction of the phylogeny of the capercaillie according to the polymorphism of the control region of mtDNA. Red dots — sequences from Belarus (this study).
Fig. 3 in Genetic Diversity And Place In The General Phylogeographic Structure Of Capercaillie,Tetrao Urogallus (Galliformes, Phasianidae), From Belarus
Fig. 3. Network of capercaillie haplotypes according to the mtDNA control region. Balkans — the Balkan Peninsula, E_Europe — Eastern Europe, N_Europe — Northern Europe, W_Russia — Western Russia (up to Ural Mountains), W_Europe — Western Europe, NW_Russia — Northwest Russia, C_Europe — Central Europe.
Fig. 1 in Genetic Diversity And Place In The General Phylogeographic Structure Of Capercaillie,Tetrao Urogallus (Galliformes, Phasianidae), From Belarus
Fig. 1. Distribution of samples of the capercaillie. Black circles are samples obtained independently, black squares are mtDNA sequences (control region) downloaded from the GenBank database (see Appendix, table 1).
Fig. 1 in Seasonal Changes In Species Diversity And Dominance Structure In Communities Of Oribatid Mites (Sarcoptiformes, Oribatei) In Megalopolis Green Areas
Fig. 1. Cluster analysis of oribatid species diversity in studied plots at April–September 2011 (plot indexes are given in Material and methods).
Fig. 2 in Seasonal Changes In Species Diversity And Dominance Structure In Communities Of Oribatid Mites (Sarcoptiformes, Oribatei) In Megalopolis Green Areas
Fig. 2. Seasonal fluctuations of numbers of registered species, mean aerial daytime temperature and relative humidity (iv — April, v — May, vi — June, vii — July, viii — August, ix — September).
Frontiers in Ecology and Evolution 01 frontiersin.org Why grazing and soil matter for dry grassland diversity: New insights from multigroup structural equation modeling of micro-patterns
<p>Grazing is recognized as a major process driving the composition of plant<br> communities in grasslands, mostly due to the heterogeneous removal of<br> plant species and soil compaction that results in a mosaic of small patches<br> called micro-patterns. To date, no study has investigated the differences in<br> composition and functioning among these micro-patterns in grasslands in<br> relation to grazing and soil environmental variables at the micro-local scale.<br> In this study, we ask (1) To what extent are micro-patterns different from each<br> other in terms of species composition, species richness, vegetation volume,<br> evenness, and functioning? and (2) based on multigroup structural equation<br> modeling, are those differences directly or indirectly driven by grazing and soil<br> characteristics? We focused on three micro-patterns of the Mediterranean dry<br> grassland of the Crau area, a protected area traditionally grazed in the South-<br> East of France. From 70 plant community relevés carried out in three micro-<br> patterns located in four sites with different soil and grazing characteristics,<br> we performed univariate, multivariate analyses and applied structural equation<br> modeling for the first time to this type of data. Our results show evidence<br> of clear differences among micro-pattern patches in terms of species<br> composition, vegetation volume, species richness, evenness, and functioning<br> at the micro-local scale. These differences are maintained not only by direct<br> and indirect effects of grazing but also by several soil variables such as fine<br> granulometry. Biological crusts appeared mostly driven by these soil variables,<br> whereas reference and edge communities are mostly the result of different<br> levels of grazing pressure revealing three distinct functioning specific to each<br> micro-pattern, all of them coexisting at the micro-local scale in the studied<br> Mediterranean dry grassland. This first overview of the multiple effects of<br> grazing and soil characteristics on communities in micro-patterns is discussed<br> within the scope of the conservation of dry grasslands plant diversity.</p>
Fig 4 in Diversity and taxonomic structure of aquatic macroinvertebrates in a fluvio-lacustrine system in south-west Côte d'Ivoire: The case of the Soubré hydroelectric dam lake
Fig 4: Hierarchical classification of sampling stations based on the similarity of assemblages of aquatic macroinvertebrate families.
Figure 1. A in Structural and diversity changes in coastal dunes from the Mexican Caribbean: the case of the invasive Australian pine (Casuarina equisetifolia)
Figure 1. A) Location of Cozumel Island within the Yucatán Peninsula. B) Study area on the north side of Cozumel Island. C) The distribution of Casuarina equisetifolia, shown as dark gray polygons and the sampling plots (numbered circles). Plots 1, 6–9 are the invaded, while plots 2–5, 10 are non-invaded.
Figure 3 in Structural and diversity changes in coastal dunes from the Mexican Caribbean: the case of the invasive Australian pine (Casuarina equisetifolia)
Figure 3. Grouping of invaded (triangles) and non-invaded (squares) sampling plots according to their species composition similarity (PERMANOVA). The numbers close to the symbols are the assigned sampling plot number. The dotted lines represent the scores' standard deviation of each group. The solid black lines represent the distance (similarity) between sampling plots.
Fig. 2 in Genetic diversity and population structure of endangered Neofinetia falcata (Orchidaceae) in South Korea based on microsatellite analysis
Fig. 2. Structure analyses for putative genetic clusters of N. falcata. A: Graphs of ΔK values to determine the ideal number of groups present in the accessions of N. falcata. B: Estimated genetic structure of the 3 populations of brinjal based on STRUCTURE analysis K = 2 and K = 3.
Figure S1 in Mitochondrial genetic diversity and structuring of northern white-breasted hedgehogs from the Central Balkans
Figure S1. Median-joining network shows the distribution of 13 Erinaceus roumanicus haplotypes from the Central Balkans, with pie chart area proportional to haplotype frequencies in relation to the four detected subpopulations.
Figure 1 in Mitochondrial genetic diversity and structuring of northern white-breasted hedgehogs from the Central Balkans
Figure 1. Geographic position of sampled localities of E. roumanicus from the Central Balkans in this study. Numbers of localities correspond to those shown in Table 1, where the number of individuals sampled for each locality is also given. Localities were organized in four groups as suggested by Geneland analysis (NWC – black circles; NE – red squares; SE – green polygons; SW – blue triangles).
Figure 2 in Mitochondrial genetic diversity and structuring of northern white-breasted hedgehogs from the Central Balkans
Figure 2. Distribution of haplotype frequencies in four detected groups of E. roumanicus from the Central Balkans. The size of pie charts is proportional to sample size. The numbers on the x and y axes correspond to longitude and latitude decimal degrees.
Figure 3b in Species diversity and community structure of zooplankton in three different types of water body within the Sakarya River Basin, Turkey
Figure 3b. CCA biplot diagram with three lakes (all seasons and stations) and 81 species (Rot: Rotifera, Cla: Cladocera, Cop: Copepoda, species abbreviations are listed in Table 2).
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