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Text-fig. 2. Plot of height versus height to width ratio of leaf scars of the studied species of Protopteris and Oncopteris. in Revision Of Protopteris And Oncopteris Tree Fern Stem Casts From The Late Cretaceous Of Central Europe
Text-fig. 2. Plot of height versus height to width ratio of leaf scars of the studied species of Protopteris and Oncopteris.
Figure 1. Maximum Likelihood tree for 40 in A new species of Fejervarya Bolkay, 1915 from the lateritic plateaus of the Goa parts of the Western Ghats
Figure 1. Maximum Likelihood tree for 40 dicroglossid taxa based on 5430 bp of mitochondrial (16S and 12S) and nuclear genes (BDNF, Rhod, Tyr, RAG-2, NCX1, and CXCR4) (*represents the bootstrap values above 50%).
Figure. Interferon alpha-A based phylogenetic tree (neighbor joining method) constructed by MEGA 6.1 for Punjab urial in comparison with other mammalian species sequences available from GenBank (NCBI). in Characterization of interferon alpha of major histocompatibility complex class I in Punjab urial (Ovis vignei punjabiensis)
Figure. Interferon alpha-A based phylogenetic tree (neighbor joining method) constructed by MEGA 6.1 for Punjab urial in comparison with other mammalian species sequences available from GenBank (NCBI).
Figure 1. A neighbour-joining tree using 604 cytochrome C oxidase sub-unit I in Phylogenetic relationship among slender loris species (Primates, Lorisidae: Loris) in Sri Lanka based on mtDNA CO1 barcoding
Figure 1. A neighbour-joining tree using 604 cytochrome C oxidase sub-unit I (CO1) sequences from 7 different slender loris (Loris) taxas, rooted using slow loris (Nycticebus) sequences deposited in the GenBank.
Fig. 3. Maximum likelihood tree for Culex species showing the 5 clades representing 5 subgroups. Clade I in Mosquito identification and haemosporidian parasites detection in the enclosure of the African penguins (Spheniscus demersus) at the SANBI zoological garden
Fig. 3. Maximum likelihood tree for Culex species showing the 5 clades representing 5 subgroups. Clade I is the Trifilatus Subgroup (Mattingly and Rageau, 1958) for Cx. torrentium; Clade II and III are the Pipiens Complex; Clade IV the Theileri Subgroup (Sirivanakarn, 1976) for Cx. theileri; and Clade V is the Tarsalis (Edwards, 1932) for Cx. declaratory and Apicinus Subgroups (Edwards, 1932) for Cx. mollis. Lutzia sp. used as outgroups. Sequences from this study are indicated by asterisks (*).
Figure 1 in Mosquito (Diptera: Culicidae) species richness and abundance across a tree-height gradient: does adding CO enhance the BG-Lure?
Figure 1. Study Site and Sampling Setting. (A) Monroe County in Indiana, USA. (B) Hickory Ridge Fire Tower and Nearest Weather Station within Monroe County. (C) BG-pro mosquito trap in CDC style. (D) Tower canopy height gradient. / Figura 1. Sitio de estudio y metodologÍa de muestreo. (A) Condado Monroe, Indiana, Estados Unidos. (B) Torre de avistamiento de incendios y estación meteorológica más cercana dentro del Condado Monroe. (C) Trampa de mosquitos BG-pro configurada en estilo CDC. (D) Gradiente de altitud arbórea.
Fig. 1. Maximum likelihood tree generating from a 399 in Isolation and Characterization of Polymorphic Microsatellite Loci for Caridina cantonensis and Transferability Across Eight Confamilial Species (Atyidae, Decapoda)
Fig. 1. Maximum likelihood tree generating from a 399-bp long COI dataset (GenBank accession no. MH176649-MH176993). SH-alrt/ bootstrap support values are indicated at major nodes. Each coloured notation represents one species.
Fig. 5 in Characterization of the entomopathogenic fungal species Conoideocrella luteorostrata on the scale insect pest Fiorinia externa infesting the Christmas tree Abies fraseri in the USA
Fig. 5. Maximum Likelihood phylogenetic reconstruction of Conoideocrella species, using an SSU-LSU-tef1-ITS concatenated dataset with Metarhizium granulomatis (Sigler) Kepler, S.A. Rehner & Humber (Clavicipitaceae) as designated outgroup taxon, and showing host, sexual state and county of isolation. Ex-type species denoted as ExT.
Fig. 4 in Characterization of the entomopathogenic fungal species Conoideocrella luteorostrata on the scale insect pest Fiorinia externa infesting the Christmas tree Abies fraseri in the USA
Fig. 4. Features of Conoideocrella luteorostrata: (A) stromatic tissue (white arrow) on Fiorinia externa (black arrow); (B) details of stromatic hyphae on 10% KOH, 40×; (C) 1 mo old culture on PDA (lef) and oatmeal agar (right); (D) conidiophore; and (E) spores, 100×.
Fig. 3 in Characterization of the entomopathogenic fungal species Conoideocrella luteorostrata on the scale insect pest Fiorinia externa infesting the Christmas tree Abies fraseri in the USA
Fig. 3. Field view of Fiorinia externa collected on Abies fraseri from Glade Creek, North Carolina, USA (FDACS-DPI, sample #2019-6449) (A); its slide-mounted view (B); antennae on submargin of the head with short spur (C); anterior spiracle with pores (D); pygidium with five marginal macroducts (E); close-up of wide macroduct (F); antennae on the margin of head, with a long spur, of F. fioriniae collected on Chamaerops humilis from Ocala, Florida, USA (2019-4546) (G); antennae on the margin of head, with a short spur and processing between antennae, of F. phantasma collected on Ligustrum japonicum from Boynton Beach, Florida, USA (2020-1365) (H); pygidium with 4 marginal macroducts (I); close-up of narrow macroduct (J).
Fig. 2 in Characterization of the entomopathogenic fungal species Conoideocrella luteorostrata on the scale insect pest Fiorinia externa infesting the Christmas tree Abies fraseri in the USA
Fig. 2. Original localities of intercepted shipments of Christmas trees in 2019 (shown as circle) and 2020 (triangle). Samples with entomopathogenic fungus Conoideocrella luteorostrata are colored in blue and without fungus in red. Major cities are shown as black diamonds.
Fig. 1 in Characterization of the entomopathogenic fungal species Conoideocrella luteorostrata on the scale insect pest Fiorinia externa infesting the Christmas tree Abies fraseri in the USA
Fig. 1. Features of Fiorinia externa: (A) 30× view of alive first instar (crawler); (B) 30× view of adult female body (inside cover) with exuviae of first and second instar; (C) naked eye view of entomopathogenic fungus Conoideocrella luteorostrata on different stages of F. externa (black arrow heads); (D) close-up of C. luteorostrata covering F. externa (black arrow heads).
Fig. 31. Gene tree for Trigonidium Rambur, 1838 in Small crickets of New Zealand (Orthoptera: Grylloidea: Trigonidiidae and Mogoplistidae), with the description of two new genera and species
Fig. 31. Gene tree for Trigonidium Rambur, 1838 using Maximum Likelihood analysis of ~700 bp of mtDNA (COI) from 23 specimens and 1000 bootstrap replications. The tree with the highest log likelihood (-3571.04) is shown. Numbers next to the branches indicate the percentage of trees in which the associated taxa are clustered together. The tree is drawn to scale, with branch lengths measured in the number of substitutions per site. Specimens in blue were collected as part of this study; the remaining 15 sequences were obtained from the GenBank (Benson et al. 2013) and BOLD (Ratnasingham & Hebert 2007) databases. Detailed information for each specimen included in this analysis can be found in Supp. file 1: Table S11.
Fig. 4 in Taxonomic appraisal of Fagraea ceilanica (Gentianaceae), and description of a new tree species from the Bird's Head Peninsula, western New Guinea
Fig. 4. – Distribution of Fagraea christinae Y.W. Low & V.A. Albert in the Bird's Head Peninsula, New Guinea. Solid coloured area of the map reflects the West Papua Province (before the 2022 split into two separate provinces, Southwest Papua and West Papua), Indonesia.
Fig. 2. – Fagraea christinae Y.W. Low & V.A. Albert. A in Taxonomic appraisal of Fagraea ceilanica (Gentianaceae), and description of a new tree species from the Bird's Head Peninsula, western New Guinea
Fig. 2. – Fagraea christinae Y.W. Low & V.A. Albert. A. Habit of a flowering and fruiting branch; B. Close-up of calyx lobes outer surface showing warty or verrucose texture; C. Half of a longitudinal section of an open flower; note the stamens are inserted upon a thickened wall (forming a thickened ring in complete flower). [A–C: Wanma et al. MAN-SING45] [Drawings: X.Y. Loh]
Fig. 1. – Fagraea ceilanica Thunb. A in Taxonomic appraisal of Fagraea ceilanica (Gentianaceae), and description of a new tree species from the Bird's Head Peninsula, western New Guinea
Fig. 1. – Fagraea ceilanica Thunb. A. Reproduction of the illustration, tab. IV (THUNBERG, 1782); B. Lectotype (Thunberg s.n. [UPS-THUNB4308]); C. Flowering plant from Rahathangala, Sri Lanka. [Photos: A: Biodiversity Heritage Library (contributed by the Natural History Museum Library, London); B: reproduced with kind permission from the Museum of Evolution, Uppsala University, Sweden; C: Himesh D. Jayasinghe]
Fig. 3 – Fagraea christinae Y.W. Low & V.A. Albert. A in Taxonomic appraisal of Fagraea ceilanica (Gentianaceae), and description of a new tree species from the Bird's Head Peninsula, western New Guinea
Fig. 3 – Fagraea christinae Y.W. Low & V.A. Albert. A. Habit; B. Close-up of flower buds enclosed by calyx lobes and a pair of bracteoles with distinctive crenate margins; C. Side view of an open flower showing curled corolla lobe margins; D. Top view of an open flower with stamens clearly seen inserted upon a fleshy ring; E. Close-up of pink, mature fruits; fruit on the right artificially cut opened to reveal numerous small and black kidney-shaped seeds. [A–E: Wanma et al. MAN-SING45] [Photos: Y.W. Low]
Baseline and Future (2050s and 2090s) Climate Suitability Scores for 116 Useful Tree Species and 220 locations from Côte d'Ivoire, Ghana and Guinea
<p>Climate suitability scores were calculated for 116 Useful Tree Species identified by filtering Top830+ native tree species from Côte d'Ivoire, Ghana and Guinea via the <a href="https://patspo.shinyapps.io/GlobalUsefulTrees/">GlobalUsefulNativeTrees</a> database and checking for the availability of globally observed environmental ranges from the <a href="https://doi.org/10.5281/zenodo.13132613">TreeGOER</a> database.</p> <ul> <li>Score = 3 means that in 'environmental space' the planting site occurs within the 25% - 75% species's range (as documented in the <a href="https://onlinelibrary.wiley.com/doi/full/10.1111/gcb.16914" target="_blank" rel="noopener">TreeGOER</a> ) for all variables</li> <li>Score = 2 corresponds to the 5% - 95% species's range for all variables. For some variables, the planting site occurs outside the 25% - 75% species's range.</li> <li>Score = 1 corresponds to the 0% - 100% species's range for all variables. For some variables, the planting site occurs outside the 5% - 95% species's range.</li> <li>Score = 0 means that the planting site occurs outside the 0% - 100% species's range for some of the variables</li> <li>Score = -1 means that the species is not documented by TreeGOER</li> </ul> <p>Locations corresponded to cities and weather stations from the three target countries sourced from the <a href="https://doi.org/10.5281/zenodo.10004594">CitiesGOER</a> and <a href="https://doi.org/10.5281/zenodo.12679832">ClimateForecasts</a> databases, respectively. Both these databases provide bioclimatic conditions for the historical (baseline) and three future climate change scenarios. Bioclimatic variables for future climates correspond to the median values from 24 Global Climate Models (GCMs) for Shared Socio-Economic Pathway (SSP) 1-2.6 for the 2050s (2041-2060), from 21 GCMs for SSP 3-7.0 for the 2050s and from 13 GCMs for SSP 5-8.5 for the 2090s.</p> <p>Investigations were made for two different sets of bioclimatic variables, allowing for sensitivity analysis:</p> <ul> <li>One set of bioclimatic variables included BIO01 (mean annual temperature), BIO12 (total annual precipitation), climaticMoistureIndex, monthCountByTemp10 (number of months with average temperature above 10 degrees), growingDegDays5, BIO05 (maximum temperature of the warmest month), BIO06 (minimum temperature of teh coldest month), BIO16 (precipitation of the wettest quarter), BIO17 (precipitation of the driest quarter) and MCWD (Maximum Climatological Water Deficit). These are the same bioclimatic variables available internally in the <a href="https://worldagroforestry.org/output/globalusefulnativetrees">GlobalUsefulNativeTrees</a> for climate filtering.</li> <li>One set only included BIO01 (mean annual temperature), which is the single bioclimatic variables available for the BGCI <a href="https://cat.bgci.org/">Climate Assessment Tool</a>.</li> </ul> <p>Calculations were made with similar scripting pipelines in the <em>R</em> statistical environment as documented here: <a href="https://rpubs.com/Roeland-KINDT/1168650">https://rpubs.com/Roeland-KINDT/1168650</a>. These scripts use similar calculations methods as those used for the global case studies of the TreeGOER manuscript (Kindt <a href="https://onlinelibrary.wiley.com/doi/10.1111/gcb.16914">2023</a>), and used internally in the <a href="https://worldagroforestry.org/output/globalusefulnativetrees">GlobalUsefulNativeTrees</a> online database. Interested readers should especially refer to the manuscript for further details on methods used and their justification.</p> <p>The maps show the frequency distribution of tree species with climate scores 3, 2, 1 and 0, excluding 18 species not documented by the TreeGOER.</p> <p> </p> <p><strong>References</strong></p> <ul> <li>Kindt, R. (2023). TreeGOER: A database with globally observed environmental ranges for 48,129 tree species. Global Change Biology, 00, 1–16. <a href="https://onlinelibrary.wiley.com/doi/10.1111/gcb.16914">https://onlinelibrary.wiley.com/doi/10.1111/gcb.16914</a>.</li> <li>Kindt, R. (2024). TreeGOER: Tree Globally Observed Environmental Ranges (2024.07) [Data set]. Zenodo. <a href="https://doi.org/10.5281/zenodo.13132613" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.13132613</a></li> <li>Kindt, R., Graudal, L., Lillesø, JP.B. <em>et al.</em> (2023). GlobalUsefulNativeTrees, a database documenting 14,014 tree species, supports synergies between biodiversity recovery and local livelihoods in landscape restoration. <em>Sci Rep</em> <strong>13</strong>, 12640. <a href="https://doi.org/10.1038/s41598-023-39552-1">https://doi.org/10.1038/s41598-023-39552-1</a></li> <li>Kindt, R. (2023). CitiesGOER: Globally Observed Environmental Data for 52,602 Cities with a Population ≥ 5000 (2023.10) [Data set]. Zenodo. <a href="https://doi.org/10.5281/zenodo.10004594" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.10004594</a></li> <li>Kindt, R. (2024). ClimateForecasts: Globally Observed Environmental Data for 15,504 Weather Station Locations (2024.07) [Data set]. Zenodo. <a href="https://doi.org/10.5281/zenodo.12679832" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.12679832</a></li> <li>Fick, S. E., & Hijmans, R. J. (2017). WorldClim 2: New 1‐km spatial resolution climate surfaces for global land areas. <em>International Journal of Climatology</em>, <em>37</em>(12), 4302–4315. <a href="https://doi.org/10.1002/joc.5086">https://doi.org/10.1002/joc.5086</a></li> <li>Title, P. O., & Bemmels, J. B. (2018). ENVIREM: An expanded set of bioclimatic and topographic variables increases flexibility and improves performance of ecological niche modeling. <em>Ecography</em>, <em>41</em>(2), 291–307. <a href="https://doi.org/10.1111/ecog.02880">https://doi.org/10.1111/ecog.02880</a></li> <li>Opendatasoft (2023) Geonames - All Cities with a population > 1000. <a href="https://public.opendatasoft.com/explore/dataset/geonames-all-cities-with-a-population-1000/information/?disjunctive.cou_name_en&sort=name">https://public.opendatasoft.com/explore/dataset/geonames-all-cities-with-a-population-1000/information/?disjunctive.cou_name_en&sort=name</a> (accessed 22-JULY-2023)</li> <li>Meteostat (2024) Weather stations: Lite dump with active weather stations. <a href="https://github.com/meteostat/weather-stations">https://github.com/meteostat/weather-stations</a> (accessed 17-FEB-2024)</li> </ul> <p> </p> <p><strong>Funding</strong></p> <p>The data sets and maps available in this archive were created within the context of an agreement between The International Centre for Research in Agroforestry (ICRAF) and WORLD UNIVERSITY SERVICE OF CANADA (WUSC) for a <em><a href="https://ceci.org/en/projects/nature-based-climate-adaptation-guinean-forest-west-africa-sbn-guinean-forests">Nature-based climate adaptation project in the Guinean forests of West Africa (NbS Guinean Forests)</a></em> funded by <a href="https://www.international.gc.ca/global-affairs-affaires-mondiales/home-accueil.aspx?lang=eng">Global Affairs Canada</a>.</p>
Inbreeding depression, functional traits and phenotypic plasticity in an endangered tree species from Congo basin with a mixed mating system
<h3><span>Inbreeding depression, functional traits and phenotypic plasticity in an endangered tree species from Congo basin with a mixed mating system</span></h3> <h1><a name="_Hlk166486742"></a><strong><span>Abstract</span></strong></h1> <p><span><span>1. Most tree species can suffer from inbreeding depression (ID), which they escape by reproducing predominantly through outcrossing. A remarkable exception is <em>Pericopsis elata</em>, an African timber species naturally producing 54% of self-fertilized seeds in the eastern Congo Basin. This species is highly logged and suffers from a deficit of natural regeneration, so that silviculture is needed for its sustainable management. While selecting good genetic material can increase the value of plantations, we lack fundamental biological knowledge on the effect of inbreeding and competition on growth potential, variability in leaf traits and phenotypic plasticity. We hypothesize that ID in <em>P. elata</em> could result from the expression of deleterious mutations affecting functional traits, or from a reduction of adaptive phenotypic plasticity in inbred genotypes.</span></span></p> <p><span><span>2. To test our hypotheses, 540 <em>P. elata</em> seedlings were monitored for 4 years in a Nelder-type device located in the DRC, in which trees were planted along concentric circles to generate a density gradient. Nine leaf morphological traits (including specific leaf area, stomata density and size), eight leaf chemical traits, diameter, and total height were measured regularly, while paternity analyses allowed distinguishing inbred and outbred plants. To explain the observed ID on growth, we tested whether inbreeding affected leaf traits and/or their plasticity expressed across years, across the density gradient or across sunlight exposure. </span></span></p> <p><span><span>3. Outbred plants grew faster than inbred ones, demonstrating ID for each level of competition. Despite the significant correlation found between specific leaf area and growth, and the impact of planting density, plant age, and leaf exposure to sunlight on multiple traits, mean leaf trait values did not differ according to inbreeding. However, </span></span><span><span>a few leaf traits (chlorophyl content, </span></span><span><span>maximum stomatal water vapor conductance</span></span><span><span>, and leaf fresh mass) showed significantly higher plasticity in outbred than inbred plants. </span></span></p> <p><span><span>4. Synthesis: the observed ID on growth was not explained by a direct effect of inbreeding on the mean values of functional traits but possibly by a reduction of phenotypic plasticity with inbreeding. Additional studies on the interplay between ID, functional traits and plasticity should be conducted at the intra-specific level to identify general patterns<em>.</em></span></span></p> <p><span><strong><span>Key-words : </span></strong></span><span><span>Inbreeding depression, phenotypic plasticity, silviculture, functionals traits, <em>Pericopsis elata</em>, mating system, Nelder device.</span></span></p>
Linked collectors and determiners for: Identity of the tree-spider crab, Parasesarma leptosoma (Hilgendorf, 1869) (Decapoda: Brachyura: Sesarmidae), with descriptions of seven new species from the Western Pacific.
Natural history specimen data linked to collectors and determiners held within, "Identity of the tree-spider crab, Parasesarma leptosoma (Hilgendorf, 1869) (Decapoda: Brachyura: Sesarmidae), with descriptions of seven new species from the Western Pacific". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/fd24ef18-76ac-46f1-aec2-2faf5b0ff325">https://bionomia.net/dataset/fd24ef18-76ac-46f1-aec2-2faf5b0ff325</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/fd24ef18-76ac-46f1-aec2-2faf5b0ff325">https://gbif.org/dataset/fd24ef18-76ac-46f1-aec2-2faf5b0ff325</a>. Formatted as a Frictionless Data package.
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Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
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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.